The Interventional Centre Rikshospitalet University Hospital

Faculty of Medicine, University of Oslo, Norway

MRI-Guided Interventions Technological solutions

Eigil Samset

Submitted as partial fulfillment of the Requirements of the degree

Doctor of Philosophy

At the Faculty of Medicine, University of Oslo,

Norway

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Contents

CONTENTS........................................................................................................................... II

ACKNOWLEDGEMENTS.................................................................................................III

LIST OF ORIGINAL PAPERS..........................................................................................IV

INTRODUCTION.................................................................................................................. 1 GENERAL INTRODUCTION...................................................................................................... 1 MAGNETIC RESONANCE IMAGING ......................................................................................... 2 INTRA-OPERATIVE MR IMAGING........................................................................................... 4 STEREOTACTIC NEUROSURGERY........................................................................................... 5

Framebased stereotaxy .................................................................................................... 5 Frameless stereotaxy........................................................................................................ 5

CRYOSURGERY...................................................................................................................... 6

CLINICAL PROBLEMS ...................................................................................................... 8 PRE-OPERATIVE IMAGES ARE OUTDATED DURING SURGERY.................................................. 8 FUNCTIONAL STEREOTACTIC PROCEDURES ARE SUBOPTIMAL ............................................... 9 MR DOES NOT GIVE INFORMATION ON SUB-ZERO TEMPERATURES ........................................ 9 CRYO ABLATION OF TUMORS NEEDS EVIDENCE BASED HEURISTIC RULES.............................. 9 CURRENT INTRA-OPERATIVE IMAGE GUIDANCE DOES NOT FACILITATE GOOD EYE-HAND COORDINATION.................................................................................................................... 10

AIMS OF THE PRESENT WORK.................................................................................... 11

CONTEXT OF THE STUDY.............................................................................................. 12

THE INTERVENTIONAL CENTRE........................................................................................... 12

CORE EQUIPMENT........................................................................................................... 13

MR SCANNER...................................................................................................................... 13 NEURONAVIGATION SYSTEM ............................................................................................... 13 CRYO EQUIPMENT ............................................................................................................... 13

SUMMARY OF RESULTS................................................................................................. 15 NAVIGATION AND VISUALIZATION ...................................................................................... 15 3D TEMPERATURE ESTIMATION AND VALIDATION IN CRYO SURGERY ................................. 16

DISCUSSION ....................................................................................................................... 17 CONCOMITANT DEVELOPMENT OF CLINICAL PROCEDURES AND TECHNOLOGY.................... 17 EYE-HAND COORDINATION ................................................................................................ 19 ACCURACY OF SPATIAL AND THERMAL VALUES .................................................................. 19

CONCLUSIONS................................................................................................................... 21

REFERENCE LIST ............................................................................................................. 22

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Acknowledgements The present work was carried out during the years 1998-2002 at the Interventional Centre, Rikshospitalet University Hospital. During the period I worked as a senior engineer and received a doctoral stipend from the Norwegian Research Council. I wish to express my sincere gratitude to my advisor professor dr.med. Erik Fosse, who hired me in 1997, encouraged me to do the doctorate study and has kept encouraging and giving me self-confidence throughout the work. I would like to thank dr.med. Henry Hirschberg with whom I have worked closely on this study. He has introduced me to the field of neurosurgery, and has been a great collaborator and mentor for me. I would like to thank Tom Mala, who I have collaborated closely with in parts of the presented work. Many thanks to the members of the technology group at the Interventional centre; to Ole Jakob Elle who has endured sharing office with me, to Lars Aurdal who always has a perfect analogy for anything, to Jan Sigurd Røtnes for his everlasting enthusiasm, and to Margunn Johansen, Marius Kintel, Arne Enger Hansen, Eivind Eriksen and Kristoffer Gleditsh. Thanks to MR technicians Terje Tillung and Ingrid Erikstad for helping me out and making a joyful atmosphere in the MR controlroom. Special thanks to Frode Lærum, whose idea led the establishment of then Intervetional Centre and for being to great inspiration. Also thanks to the radiologists: Finn Lilleås, Per Kristian Hol and Örjan Smedby for educating me in the field of MR image reading. Thanks to Åge Kristiansen who has made all the mechanical devices needed. I would also like to thank the whole staff at the Interventional Centre for great support and a lot of fun. Finally, thanks to my loving wife Ingunn who makes my days bright and to my son Sindre who came along in spring 2001 and is a fountain of joy.

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List of original papers

Paper I. Samset E., Hirschberg H., “Neuronavigation in intra-operative MRI”, Journal for Computer Aided Surgery 1999;4(4):200-207

Paper II. Samset E., Hirscberg H., “Stereotactic target localization accuracy in

the interventional MRI”, Stereotactic and functional neurosurgery

Paper III. Samset E., Hirschberg H., “Image guided stereotaxy in the interventional MRI”, Minimal Invasive Neurosurgery 2003;46(1):1-6

Paper IV. Samset E., Mala T., Edwin, B., Gladhaug I., Søreide O., Fosse E.,

"Validation of estimated 3D temperature maps during hepatic cryo surgery", Magnetic Resonance Imaging 2001;19(5):715-721

Paper V. Samset E., Mala T., Ellingsen R., Gladhaug I., Søreide O., Fosse E.,

"Temperature measurement in soft tissue using a distributed fiber bragg grating sensor system", Min Invas Ther & Allied Technol 2001;10(2):89-93

Paper VI. Mala T. Samset E., Aurdal L., Gladhaug I., Edwin B., Søride O.,

”Magnetic Resonance Imaging-Estimated Three-Dimensional Temperature Distribution in Liver Cryolesions: A study of Cryolesions Characteristics Assumed Necessary for Tumor Ablation”, Cryobiology 2001; 43(3): 268-275

Paper VII. Samset E., Talsma A., Kintel M., Elle O.J., Aurdal L., Hirschberg H.,

Fosse E., “A virtual environment for navigating and controlling intraoperative magnetic resonance images”, Journal for Computer Aided Surgery, 2002;7(4):187-96

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Introduction

General introduction Since the introduction of Magnetic Resonance Imaging (MRI) in the beginning of the nineteen eighties the number of medical applications for the technique has steadily increased. MRI is currently used to diagnose diseases and abnormalities in all parts of the body. Open MRI systems became available in the previous decade (1-3). These systems target the following applications: diagnostic examinations of patients that cannot go through a conventional examination (due to claustrophobia or to inhibiting patient habitus), non-conventional patient positioning in static or dynamic studies and finally surgical or interventional procedures. The most unique property of open MRI systems is the access to the patient during scanning. Conventional examination in an open MRI system is not particularly challenging, as the examination is conducted in a similar manner as for a closed system. Unconventional patient examination or dynamic studies demand special positioning- or fixation- devices as well as means to measure angels and positions. Surgical- and interventional procedures are much more demanding, both technologically and practically. The key feature for successful MRI-guided interventions is a well-designed interactive image guidance system. For each procedure special care has to be taken in the design of instruments, the choice of image acquisition technique, patient positioning, positioning devices, image guidance systems and human-computer interface. The main motives for the use of intra-operative MRI is to make the procedure less invasive and to increase precision and radicality during surgery. MRI can give the image guidance that enables this. However, images alone are not enough, the images need to be related to the surgical space in an intuitive and robust way. This means that the images on the screen have to provide the information necessary to give the operator good eye-hand coordination. This motivates the need for instrument- as well as patient- and operator tracking in certain applications. Today intraoperative MRI is an established tool in neurosurgical procedures (4). The brain is a relatively easy organ to scan and relate to in an intra-operative MRI context. This is due to the relative absence of movement, and the ability to immobilize the head. Intraoperative MRI is also a useful tool in thermo theraputic procedures due to the possibility of using properties of the Magnetic Resonance (MR) signal to detect changes in temperature and thus visualize the effect of the thermal application. This applies to thermal hyper- and hypo-therapy and ablation using heat or cold. As thermal ablation to an increasing degree is performed minimally invasive, temperature control by MRI makes this treatment safer and simpler.

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Magnetic Resonance Imaging Magnetic Resonance as a nuclear phenomenon was discovered independently by Felix Bloch and Edward Mills Purcell in 1946 (5;6). They were awarded the Nobel Prize in physics in 1952. The first experiments using nuclear magnetic resonance (NMR) in the period between 1950 and 1970, were conducted for chemical and physical molecular analysis. In 1975 Paul Lauterbur showed the first magnetic resonance images (7), using a back-projection technique similar to that of Computer Tomography, which was introduced the same year. Two years later Richard Ernst proposed magnetic resonance images using phase and frequency encoding, and the Fourier transform (8). Richard Ernst was awarded the Nobel Prize in chemistry for this achievement in 1991. In 1980 a single MR image could be acquired in five minutes, in 1986 the imaging time, with similar quality, was reduced to five seconds. Magnetic resonance imaging of the human body is possible due to the high content of water. The process that lays behind the acquisition of an MR image can very simplified be explained as follows: Water molecules are dipoles and behave like a small magnets. When placed in a magnetic field these small magnets align with the field. If a radio frequency (RF) pulse is transmitted at the appropriate frequency, the dipoles will start to spin around the magnetic field as a result. When the RF pulse is turned off, the dipoles will return to their equilibrium, were they are aligned with the magnetic field. In this process the dipoles loose energy to their surroundings. Some of this energy can be picked up by a receiver coil and used to generate and MR image. The rate at which the energy is lost to the surroundings is dependant on the chemical composition. Combined with the density of water, this gives rise to the contrast in the image.

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The process described above will by itself not generate an image, but merely a spectrum. To generate an image different spatial variations of the magnetic field, called field gradients, must also be employed. The RF pulses and gradients are put together in a sequence with very precise timing, such a sequence is called a pulse-sequence, and an example of a “spin-echo” pulse-sequence is given below:RF transm it

Sli ce s elect

Ph ase code ing

Fre qu enc y cod ing

RF recei ve

The figure illustrates a spin-echo sequence for MR imaging. The first row indicates how an RF pulse is transmitted, followed by another RF pulse that causes a spin-echo to occur. During RF exitation a field gradient (Slice select) is applied to limit the response to one slice. After this another field gradient ( phase encoding) is applied to change the phase of the spins along one spatial direction. During the receive of the resulting signal the last field gradient is applied (frequency encoding) to complete the spatial coding of this 2D imaging sequence. The decoding is done by a computer using the inverse Fourier transform.

An MR system has three major components: Magnet and coils, electronics and a computer system. In most MR systems the magnet is superconducting using liquid hydrogen as cryogen. The magnet sets up a stable homogenous magnetic field. Common fieldstrenghts in use today are 0.5, 1.5 and 3.0 Tesla. Integrated in the magnet bore are three gradient coils. These coils change the homogenous field, by setting up spatial linear field gradients. These gradient fields are used for slice-selection and spatial encoding. They are controlled by the electronics of the MR system. An RF coil is used to transmit the appropriate RF pulses. Usually a separate RF coil is used to receive the signal transmitted by the nuclear spins. The electronic system consists mainly of amplifiers and receivers. There are amplifiers for each gradient and a RF amplifier. Modern MR systems have multiple receivers, to support multi-coil receiving. This electronic subsystem is high-performance equipment with accurate timing and low noise-levels. The electronics are controlled by the computer system. The computer system consists of a workstation, where a technician prescribes the images with all appropriate parameters. A different computer, running a real-time operation system loads the pulse-sequence with parameters and controls the electronics during scanning. After signal acquisition the image is reconstructed on the workstation for display, often using special visualization software for improved presentation.

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Intra-operative MR imaging

The first open MR scanner was introduced by Fonar Inc. in 1980. It was a permanent magnet with a vertical field direction. Since then open MR scanners based on permanent magnets with higher fieldstrenghts have been developed by Fonar and others. The first superconductive open MR scanner was developed by General Electric Medical Systems (GEMS), and was first installed at Brigham and Women’s Hospital in Boston, Massachusetts in 1992. The scanner was developed at the initiative of professor Ferenc Jolesz at Harvard Medical School (1;2;9;10). During the next four years 14 university hospitals in North America and Europe joined the “Clinical Investigation Program” to collaborate with GEMS in the development of MRI-guided clinical procedures. Rikshospitalet University Hospital was one of the first to have the magnet installed, in 1996. Later other MR vendors have adapted their open or closed MR systems to intra-operative imaging (3;11-14). Since the introduction of MR imaging in clinical practice, surgeons have used the images to plan and guide procedures. Neurosurgeons and orthopedic surgeons have for more than a decade used interactive image-guidance systems, based on pre-operatively acquired MR data sets, as intra-operative navigation tools. Pre-operative MR images can be very useful in the planning phase of a procedure, to optimize approach, and in parts of the anatomy where changes during the course of surgery are negligible. In most cases, however, the anatomical deformations during the surgical procedure results in a discrepancy between pre-acquired images and the reality. This discrepancy between “map and terrain” renders the pre-operatively acquired images with little value and motivates for intra-operative image acquisition. Intra-operative MR imaging gives the operator cross-sectional images or 3D volume images of the structure of interest while it is being manipulated or treated. These features greatly extend the use of this imaging technique from being purely diagnostic, to also find applications in surgery and interventions. In many cases using intra-operative MR imaging is an eye-opener to the surgeon.

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Stereotactic Neurosurgery

Framebased stereotaxy ‘Stereotaxy’ is defined as “being a technique or apparatus used in neurological research or surgery for directing the tip of a delicate instrument (as a needle or an electrode) in the three planes in attempting to reach a specific locus in the brain”(15). A conventional stereotactic procedure includes the following steps:

1. Mounting of a stereotactic ring/frame to the patient’s head. 2. Mounting of a stereotactic localizer frame consisting of typically

9-12 rods (visible on CT or MR) to the ring/frame 3. 3D imaging of the patient in a CT or MR scanner with the

localizer frame 4. Transfer of the 3D image dataset to a specialized stereotactic

workstation 5. Manual or automatic detection of the frame rod position in every

image slice 6. Selection of target based on the images 7. Calculation of stereotactic target coordinates relative to the

stereotactic frame 8. Mounting of a stereotactic positioning frame to the ring/frame 9. Adjustment of the positioning frame according to the calculated

target coordinates 10. Insertion of instrument

The use of guided probes in the neurophysiology laboratory was first recorded in 1873 (16). Since then the technique and stereotactic devices have steadily been improved. The current procedure was developed shortly after the introduction of CT imaging of the brain and has undergone few changes except from higher degree of automation of the calculation steps by utilization of computers. Ideally a stereotactic procedure is very precise, but several factors can potentially decrease the accuracy, such as: inaccuracy in imaging of target and rods, deviation from the rigid body assumptions due to weigh-bearing and torque in the frame and changes in the location of the target due to brainshift (17). Normally intra-operative imaging is not conducted during clinical applications. If negative results are reported from biopsy or electro-physiology- recording, it is not possible to know how the reached location deviates from the predetermined target. Stereotactic procedures in an awake patient can be very stressful to the patient.

Frameless stereotaxy The use of three-dimensional tracking equipment instead of a stereo-tactic frame in combination with image-guidance to assess structures of interest is sometimes called frameless stereotaxy, neuronavigation or more precisely; interactive image-guided surgery (18-23). The objective of directing a tip in the three-dimensional space to reach a specific locus in the brain remains the same as for frame-based stereotactic neurosurgery, but the added interactivity brings a new dimension to the stereotactic concept. The image-guidance system can be used not only to guide towards a pre-specified location, but also to identify any location in the pre-acquired images of the patient.

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A conventional interactive image-guided neurosurgical procedure contains the following steps:

1. Attachment of skin markers or other fiducial markers, visible in CT or MR images

2. 3D imaging of the patient with CT or MRI with markers 3. Transfer of the 3D image dataset to a neuronavigation

workstation 4. Registration of image space to physical space, by physically

identifying corresponding markers in the images and on the patient.

5. Interactive navigation The first interactive image-guided surgery systems were tested in the beginning of the 1980s by utilizing a mechanical arm. Current neuronavigation systems rely on optical tracking using passive or active infrared markers on the surgical instruments for optimal accuracy. Neuronavigation is most commonly used as a image-guidance tool during tumor resection and brain biopsy procedures, while functional stereotaxy is most often performed using framebased stereotaxy. When applied to tumor resection a major limitation of this method is brainshift during surgery. When pressure is relieved and mass is removed, the structures in the brain can shift significantly and the pre-operative images used for the navigation becomes outdated.

Cryosurgery The use of thermo therapeutic tools has been known for centuries. This treatment modality is compelling due to its minimally invasive nature, and it can also be an option when surgical resection is not possible. Several systems exist to conduct thermo therapy, with different means of delivering or removing energy. Current heating modalities include: Radio-frequency ablation, microwave ablation, focused ultrasound and laser ablation. Heating beyond 60°C produces a permanent tissue damage due to denaturation of protein (24). Tissue destruction may also be obtained by systems that reduce tissue temperature, enabling the creation of a cryolesion using Joule-Thomson engines or circulating cryogens. In cryosurgery the tissue temperature is lowered to produce a specific response which may lead to inflammation or necrosis (25). The modern era of cryosurgery began with the invention of an automated cryosurgical apparatus by Cooper, Lee and colleagues in 1961 (25). The system was vacuum insulated and cooled by liquid nitrogen. The probe was designed to produce a lesion in the brain for the treatment of Parkinsons disease. During the mid-60s this technique was also applied to treatment of prostate cancer using transurethral freezing (25). During the 70s and 80s some uses of cryosurgery fell into disfavor, this was partly due to the advancement of other techniques and the lack of good documented results. In the nineteen nineties cryosurgery gained renewed interest partly due to the development of intraoperative ultrasound and its use to monitor the freezing process. Advanced cryosurgical equipment was also developed using small probes driven by supercooled liquid nitrogen or high-pressure argon gas. One of the major applications has been the

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treatment of prostatic cancer, where 5 or more thin probes (<=3mm) are placed under ultrasound guidance and the freezing process is monitored using intraoperative ultrasound.

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Clinical problems

Pre-operative images are outdated during surgery When frame based and frameless stereotaxy techniques are used, it is assumed that the target areas of interest are fixed with relation to the skull between imaging and surgery. This assumption is largely true during surgery near the skull base. In other parts of the brain, significant movements can often be recorded during opening of the dura, cyst-drainage and tumor resection (21;26-28). When such movements or displacements occur, navigation based on pre-operative images has little value. It can be valuable during the planning phase, but will loose its power as an intra-operative tool. Two solutions present themselves to this problem: intra-operative imaging or morphological image processing of pre-operative images based on intra-operative observations. The latter implies complex algorithms and robust solutions are yet to be implemented. Several options exist for the first solution, these include x-ray, ultrasound, CT and MRI (29-31). In this work, intra-operative MRI has been the focus of attention. MR imaging is currently the state-of-the-art image modality for most cerebral diagnosis. Although intra-operative MRI is available the problem of out-dated pre-operative images during surgery is not completely solved. An intra-operative MR scanner provides updated images that compensate for the target shift that may have occurred (32-34). Such images can be acquired multiple times during a surgical procedure depending on the surgical need. However, new problems present themselves using this modality; the strong magnetic field restricts the type of surgical instruments that can be used, the confined space puts restrictions on ergonomics, the real-time scanning system has long interactive delay which makes navigation unpractical, the intra-operative MR scanner system does not include navigation in 3D datasets and other features found in conventional neuronavigation systems. Solving the two last problems was the main focus of this work, although other related problems were also addressed. Interactive real-time scanning, supplied by the intra-operative MR system, can be very useful when immediate visual feedback is wanted during placement of probes and needles close to critical structures. Due to the nature of MR and the properties of the MR system used, the acquisition of a 2D image takes time in the order of seconds (1 s. to 15 s. for the most used pulse-sequences). The location and orientation of such a real-time image slice is prescribed interactively by a hand-held locator device. When the user wants an image in a new position the scanner needs to complete the current acquisition before an image in the new position can be acquired. The interactive delay will thus be the time to complete the previous scan plus the time to acquired a new scan. This time can typically be around 11 seconds, which is too long for image-based navigation.

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Functional stereotactic procedures are suboptimal In functional stereotactic procedures successful treatment is most likely to be achieved when high precision targeting is preserved (20). During some of these procedures the patient needs to be awake and not given sedation. The extensive patient transport and long procedure times can be particularly stressful for the patient A solution to this problem that may meet the accuracy requirements, reduce procedure time and eliminate the need for patient transport during the procedure is to conduct the entire procedure inside an intra-operative MR scanner. This solution requires the following: An open MR scanner for stereotactic target determination with accuracy within acceptable limits, a high-precision MR-compatible stereotactic device and specialized navigation software.

MR does not give information on sub-zero temperatures Cryosurgery is a treatment modality that can be used for local destruction of tumors by utilizing low temperatures. This treatment method has had a renaissance after the introduction of intra-operative ultrasound due to the ability to monitor the cryo-lesion (35). The visualization of the cryo-lesion provided by ultrasound is however distorted by artefacts. The most dominant artefact is the shadow distal to the frozen region. The ultrasound waves will be almost totally reflected at the surface of the outer boarder of the frozen region. This gives a black shadow behind the frozen region (35). MR imaging gives an excellent visualisation of the frozen region (36). Due to the ultra-short T2* relaxation time of frozen tissue a sharp border can be seen between the non-frozen tissue and the signal-void of the frozen tissue (37-41). Both ultrasound and MR do not give information on sub-zero temperatures. The critical temperature assumed necessary for hepatic tumor ablation is –40°C (25;41;42;43). Above this limit cell destruction can not be guaranteed. The isotherm surface of interest for such procedures is therefore not the 0°C isotherm surface which MR can give directly but the –40°C isotherm surface. Estimation of 3D temperature maps based on thermal models can solve this problem (38;39). When such maps are available a number of possibilities for visualization of temperature maps opens.

Cryo ablation of tumors needs evidence based heuristic rules To ensure radical removal of all malignant cells it is necessary to make a free resection margin around the tumor. The same principle is applied in cryo-ablation of malignant tumors. The critical temperature assumed necessary for hepatic tumor ablation is –40°C. A heuristic rule often mentioned in the literature is that this is achieved when the outer rim of the frozen region is one centimeter outside the tumor margin. This rule needs to be compared to the position of the isotherm-surface of the assumed critical temperature to be validated. New evidence based heuristic rules need to take the totality of these factors into account: adequate resection margin, distance calculations based on quantitative calculation on 3D temperature maps and biological studies of the effect of cold on tumor tissue (44).

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Current intra-operative image guidance does not facilitate good eye-hand coordination Conventional image guidance using intra-operative MRI is not designed with human-computer interface requirements in mind. The images are often presented to be compliant with standard radiological views. These views are standardized for diagnostic purposes and are not optimal for image-guidance. Thus the images have a non-intuitive relation to the view the operator has of the patient. The human mind is trained to see the world as a 3D scene using stereo-vision with perspective projection. A intuitive human-computer interface should seek to maintain this way of viewing a 3D scene where appropriate. The open MR provides a computerized visual interface to the patient, this interface can be augmented with other virtual reality tools that can aid the user in optimal utilization of the system. Others (45-47) have done important work on this issue, but the potential for further improvement remains.

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Aims of the present work The main aim of the present work was to develop technological solutions that would improve and facilitate clinical procedures guided by intra-operative MRI. A separate aim was to integrate the technological developments into the clinical procedure, by concomitant development of both the clinical procedure and the technology to optimize the result. Another aim was to test and validate the technological developments to ensure their quality and accuracy. These aims were applied to two major clinical applications: Neurosurgery in interventional MRI Improve visualization and navigation Assess stereotactic target determination Facilitate imageguided stereotaxy Cryoablation of liver metastases in interventional MRI Improve visualization and navigation Calculate and validate 3D temperature maps within the frozen region

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Context of the study

The Interventional Centre The present work was carried out at the Interventional Centre in the period from 1998-2002. The Interventional Centre is a crossdiciplinary research and development department at Rikshospitalet University Hospital. The main focus of the centre is minimally invasive patient treatment and image guided intervention. The Interventional Centre is uniquely configured with respect to equipment and personnel. Intra-operative imaging equipment is a central part of most projects at the Interventional centre. Currently the following modalities are present for intra-operative use: open MR, X-ray angio, ultrasound and multiple video-scopic systems (providing both mono- and stereo-vision). The introduction of advanced imaging in the operation room requires the presence of specialists that are normally not found in the operation room. Therefore the Interventional Centre has a cross-disciplinary staff of surgeons, radiologist, engineers, radiographers and nurses. Teamwork across professional boundaries is not only encouraged, but is the foundation of the Interventional Centre, and is a necessity for reaching the centre’s objectives. The original idea behind establishing the Interventional Centre was that the introduction of new technology in the hospitals increases the demand for new inter-disciplinary collaboration between the different medical professions, in particular surgical and radiological professionals. The need for technological expertise was also foreseen. After 6 years 1/3 of the staff of the Interventional Centre are engineers. The technology group is also cross-disciplinarily assembled; currently it consists of people with backgrounds in image processing, robotics, cybernetics, physics and visualization. Today the Interventional Centre functions as a development department for all the clinical departments in the hospital. The present work is an example of such cross-disciplinary work, both between engineers and clinicians and between engineering disciplines.

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Core equipment

MR scanner A 0.5T Signa SP (Special Procedures) scanner designed by General Electric Medical Systems (Milwaukee, USA) was used in this study. The scanner utilizes a Helmholtz pair of superconductive magnets instead of one single solenoid. The two magnets are separated by a 60 cm. gap where the magnetic field is homogenous, thus providing access to the patient during scanning. To save space and weight the magnet does not have a cryogen (such as liquid helium), in stead cyclic cryocoolers are used to cool the coils to 9K. Special superconductive tape was made of an Nb3Sn alloy, to achieve zero resistance at this temperature.

The MR system is equipped with two RF shielded in bore monitors, optical tracking system, software for interactive scan guidance and software for real time image processing. In the upper enclosure of the magnet, (between the magnet pair above the patient bed) three linear infrared cameras are mounted (Image guided Technologies, Boulder, Colorado). These cameras track the position and direction of a handpiece, which is equipped with two or three light emitting infrared diodes (LEDs). The cameras are connected to a computer (Flashpoint 5000, IGT) that calculates the coordinates based on the camera input and information about the LED configuration. The coordinate system of the tracking system is calibrated to be equal to the coordinate system of the MR scanner. A handpiece can be used to direct the scanned slice interactively. The scanner is depicted in Paper I, figure 1.

Neuronavigation system The neuronavigation system used in this study was OTS designed by Radionics (Bourlington, Massachusetts, USA). This system consists of an optical tracking system including a PC, cameras and handpieces, called Flashpoint 5000 made by Image Guided Technologies (Boulder, Colorado). A visualization computer (HP, California, USA) connected to the flashpoint-system was used to run the neuronavigation software. This software can receive DICOM images over the hospital-network. The images are loaded into the navigation software and registered. This registration is done by identifying physical markers on the patient and in the image set. The neuronavigation system displays tri-planar images in realtime at a position corresponding to the position of a localization probe that can be attached to a surgical instrument. The localization probe is displayed in the images as graphics overlay.

Cryo equipment The cryo equipment used was CryoHit designed by Galil Medical (Yokneam, Israel). This system utilizes high pressure Argon gas (300 bar) to cool down the tip of a probe. The gas

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is run through a central control station to a 3mm cryoprobe. In the tip of the cryoprobe a Joule-Thomson heat motor brings the temperature down to –180°C at a minimum. Five cryoprobes can be used simultaneously, each with a small thermocouple in the tip that is used to measure and control the temperature.

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Summary of results

Navigation and visualization Navigation by utilization of probe tracking and 3D digital images is well established in the fields of neurosurgery and orthopedic surgery. The first step was therefore to integrate a conventional neuronavigation system (OTS, Radionics) into the interventional MRI (Paper I). Such integration had not previously been performed. The integration was achieved by developing interface software on the MR workstation. The interface software communicates with both the neuronavigation system and the MR system, transforming the information from the MR to an appropriate format. A concept called “virtual registration” was also developed (Paper I). This concept eliminated the need for physical registration of the patient, as is required in a conventional setup using neuronavigation. “Virtual registration” was made possible by exploiting the property of the MR system that the image space and the tracking space is identical, and the fact that the patient is not moved between image acquisition and navigation. Clinical use of this setup showed that neuronavigation in combination with intraoperative MRI is feasible, and that the significant brain shift that can occur during surgery was accounted for by intra-operative updating of the image set. In order to allow more customized navigation features than what was possible with a conventional navigation system, a visualization system was developed (Paper VII). This system used a ‘virtual-reality’ approach to the visualization, where the localization probe and real-time images were rendered in a 3D scene. This gave a transparent human-computer interface, since the scene can be viewed in a perspective, similar to how the eye views the real world. A navigation feature implemented as part of the software facilitated the insertion of a probe to reach a predefined target. This was tested in an animal cryo-procedure in the liver and found useful. This navigation feature was also used to test the difference in using mono-vision and stereo-vision. Test persons used the visualization system to hit a set of predefined targets on a head phantom, using head mounted displays. On average, the persons tested reached the predefined targets in 24.9 seconds using mono-vision and 15.1 seconds using stereo-vision. High precision navigation is essential in applications like functional neurosurgery. Initially the target coordinate has to be accurate. To establish the stereotactic target localization accuracy in the interventional MRI a phantom study was conducted, and the open MR scanner was compared to a conventional 1.5T closed MR scanner and a CT. The target determination accuracy of the open MR was found to be similar to that of a conventional 1.5T closed MR scanner and not significantly inferior to that of CT (Paper II). The mean difference between targets determined from interventional MR images and CT images was 0.90±0.28 mm with a maximum difference of 1.57 mm. Secondly a precise apparatus to aim at the target and guide a canula or probe insertion is crucial. A skull-mountable positioning device was developed and validated (Paper III). This positioning device was made to be adjusted under image guidance. A special software navigation tool to facilitate image-guided adjustment of the mechanical positioning device was also developed (Paper VII). This was tested by hitting predefined targets in a skull phantom with a glass wand.

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The mean distance between the targets hit and the planned target coordinates was 0.7±0.3 mm with a maximum distance of 1.3 mm. The total accuracy of the system consisting of the open MR scanner, the mechanical positioning tool and the navigation software was calculated to be 1.6±0.6 mm.

3D temperature estimation and validation in cryo surgery MRI is an excellent tool to visualize the frozen region during cryo-surgery. However, standard pulse-sequences do not give any information within the frozen region. In cryo-ablation of liver metastases, information about sub-zero temperatures is of interest, since temperatures as low as –40°C are assumed necessary to ensure tumor cell necrosis. To overcome the information void in MRI when it comes to subzero temperatures, thermal models can be used to estimate the temperatures. The solution of the simplified bio-heat differential equation, as proposed by Hong et al. (38), was implemented (Paper IV) and used to calculate estimated 3D temperature maps during cryo-ablation of in-vivo porcine liver. To validate the results, a fiber-optic temperature sensor was made (Paper V) in collaboration with OptoMed (Trondheim, Norway). This temperature sensor consists of a fiber with inscribed 10 BRAGG gratings, to allow spatial resolution, coated with polyamid. The temperature was logged on a PC through an opto-electric unit. The sensor system was highly MR compatible and can be utilized for many other clinical applications. Comparison of estimated temperatures within the frozen region with measured temperatures showed a median difference of 3.03°C. Since the temperature gradient differs greatly throughout the volume another measure was also identified. This measure compared the distance from a sensor element to the closest iso-surface with the corresponding estimated temperature. The median distance of this measure was 0.7 mm (Paper IV). A study of geometric characteristics of cryo lesions was undertaken (Paper VI). The mean distance from the –40°C isosurface to the phase-transition front was measured as a function a total lesion volume. This relationship was found to be linear, a finding which was supported by theoretical consideration (Paper VI - appendix). Another finding was that the criteria commonly used in cryosurgery: -40°C is necessary for tumor destruction and a 1-cm rim zone is sufficient for radical ablation, are in most cases contradictory. An example of merging of the 3D temperature information with a visualization and navigation system was shown in Paper VII.

16

Discussion The clinical use of interventional MRI has spread more slowly than anticipated. A reason might be the lack of customized visualization and monitoring software. One of the participants of the Clinical Investigation Program (established by GE Medical Systems to investigate the clinical use of MRI-guided procedures), Wladyslaw Gedroyc from St. Marys hospital in London, expressed it this way: “It is like getting a Mercedes without steering wheel and tires”. The technical solutions presented in this study were not defined at random, but developed in order to solve clinical problems faced by the surgeons and radiologists at the Interventional center. In this work, steps have been taken towards making the open MR more usable with a special focus on neurosurgery and cryo-surgery. In accordance with the main aim of this work, technological solutions for the clinical problems described earlier were developed. The solutions to each of these problems are discussed separately in papers I-VII. ‘Technological solutions’ in this context is a general term and encompasses the full range of possible engineering activities related to the improvement of a clinical procedure. The ‘technological solutions’ presented in this work includes activities in the following engineering areas: interface programming, visualization, MR physics, opto-electronics, thermal modeling, image processing and mechanical engineering. Interestingly multi-disciplinary effort, from a technological point of view, is commonly necessary in cross-disciplinary work between medical- and technological professions, which this work exemplifies. In the following text, the results will be discussed not with respect to their engineering complexity or with respect to a particular clinical procedure, but with respect to three central themes, each of which represent a cross-section of the work. The first theme is the concomitant development of clinical procedures and the technology. Here the idea- and design phase of the work will be discussed along with the cross-disciplinary nature of the work. The second theme is eye-hand coordination of the surgeon. Here the visual and haptic interface between the surgeon and the technology is discussed. Finally, the theme of accuracy of spatial and thermal values is discussed.

Concomitant development of clinical procedures and technology All stages of the research and development presented in this work have been done in close collaboration with surgeons, radiologists and radiographers. This cross-disciplinary approach has proven essential to the success of the project. When advanced technology is introduced into a clinical procedure, one or more of the following criteria should be fulfilled: increased safety of the procedure, increased speed of the procedure and improved clinical result. In addition an important design criteria is always that the technology is transparent so that it is intuitive to use and that it does not demand substantial extra mental capacity from the operator. Finally, the safety of the patient shall not be compromised and the outcome for the patient shall not be affected negatively by the introduction of new technology.

17

In the first steps of new technology introduction, only a few of the above-mentioned criteria are normally fulfilled. When the technology and clinical procedure are customized and streamlined for mutual adaptation a majority of these criteria can often be fulfilled. In cerebral tumor resection the most dominant change to the procedural algorithm by introducing intra-operative MR scanning was the introduction of post-resection image control and the possibility to continue resection if this control is not satisfactory. It is important that the image information obtained in this control is easy to relate to the surgical space. This can be done by real-time 2D imaging controlled by a localization probe, or by acquiring a 3D image volume followed by navigation in this volume utilizing a localization probe. The latter solution was chosen, in spite of the non-realtime nature of these images. This was done to work around the inherited interactive delay in the 2D real-time images and to benefit from the higher signal-to-noise ratio in 3D images. In this procedure the safety was improved by allowing navigation with intra-operative images corresponding the surgical space (which pre-operative images not always do). Improved clinical outcome was not proven in this work, but the image control of radical resection makes this likely (if an effect on outcome is assumed from radical resection). In functional cerebral stereotaxy a new procedural algorithm was proposed (Paper III). The main infrastructural difference between the conventional procedure and the procedure proposed in this work is that intra-operative MRI allows all phases of the procedure to be executed without moving the patient. The positioning of the patient inside the MR scanner, with known relationship to the scanner coordinate-system greatly simplifies the coordinate transformations normally involved in stereotactic procedures. The developments done for functional stereotaxy, including development of a mechanical positioning tool and navigation software, has the potential of improving the speed of the procedure. Time can be saved since patient transport is not necessary and by eliminating some of the steps involved in transforming coordinate systems. The setup proposed also has the potential of increasing the safety of the procedure since intra-operative image control gives fail-safe capabilities not present in the conventional setup. The work on this subject focus on optimizing target accuracy. Final validation in a clinical setting will in most cases be microelectrode recording. However, when the result of microelectrode recording is negative, there is no information on how to move the probe to correct the problem. This information is only assessable by intra-operative imaging. MRI-guided cryo ablation of liver metastases for local tumor destruction was established at the Interventional Centre. The procedure consists of two parts: image-guided placement of cryoprobes and cryo-ablation with temperature monitoring. The percutaneous placement of cryo probes in human livers was in many cases time consuming. This is most likely due to a combination of the following factors: no mechanical device to facilitate aiming, poor fit of localization probe to cryo probe, mediocre MR images and poor image-guidance software. During the course of the work some of these factors were improved. The visualization system developed as part of this project (paper VII) has the potential of greatly reducing the time spent on the procedure. The 3D temperature estimation (paper IV, V, VI) was validated and used post-operatively to increase the knowledge and understanding about hepatic cryo-ablation. The techniques developed to conduct 3D temperature estimation, in

18

combination with the visualization system developed (paper VII) has the potential of increasing the safety of cryo procedures and hopefully improved patient outcome.

Eye-Hand Coordination Eye-hand coordination is a mental skill that is learnt at a very early infant stage. Trials have been carried out to study the development of visual guided behavior in kitten. Removing the natural connection between leg-movement and change of view in kittens during the first weeks after birth made the test kittens functionally blind (48). Test kittens exposed to the same experimental setting, but with the motoric-visual connection preserved developed normal sensorimotor coordination. Contra-intuitive relationships between eye (image) and hand-movement can be learned, but requires substantial training and does not always give the right response in critical situations. Medical images are often presented using standardized views as defined by the radiological community. This is seldom appropriate for image-guided surgery, which requires a different approach. It is important when surgery is done based on images that there is an intuitive relationship between the images and the surgical space. When such an intuitive relationship is not present, the procedure may at best take more time, and at worst result in erroneous actions and wrong reactions to critical situations. In the present work, good eye-hand coordination was achieved by using 3D rendering techniques (Paper VII). Viewing images and localization probe in perspective from a viewpoint close to the surgeons eyes, made navigation eye-hand coordination straight-forward. Stereo-vision was tested as a means of utilizing the properties of the human visual system further. There has been a debate in the video-scopic community about the benefit of using stereo-vision in video-scopic surgery (49;50). The setup described in paper VII showed a significant difference in the speed of completing a specified task with mono-vision compared to stereo-vision. The difference between different individuals was greater than the overall difference between the stereo and mono. This reflects the different level of training and talent in the test group. The overall effect was nevertheless clear and was present for test persons with an overall good performance as well as test persons with an overall poor performance. In addition incidences of being ‘lost’ were much more frequent when using mono-vision compared to using stereo-vision. Although 3D rendering of images corresponds most closely with normal vision, 3D vision is not always feasible. When a navigation task is of two-dimensional nature, a two-dimensional view is most appropriate. The mechanical positioning device presented in paper III has two degrees of freedom and is adjusted guided by images. The 2D graphics presented to aid adjustment of the positioning device had straightforward relation to the adjustment capabilities of the device.

Accuracy of spatial and thermal values Magnetic resonance imaging is not a linear imaging method, in contrast to Computer Tomography. The spatial accuracy of the MR images is therefore important to establish before this imaging method is used for applications where high accuracy is demanded (51).

19

The factors involved in modeling the spatial accuracy of a MR system are many and complex. In this study the focus of accuracy assessment has been to investigate spatial and thermal values that are clinically relevant and that can be easily validated. The accuracy of estimation of 3D temperatures based on MR images is affected by a number of factors: spatial accuracy of the MR images, selection of segmentation algorithm and parameters for determination of the phase-transition front, definition of cryo-probe position, thermal-conductivity of the involved materials and the presence / absence of temperature transients. The variance in each of these factors was sought minimized by standardization of the experimental setup and data processing. Validation by sampling temperature in 10 points using a fiber-optic Bragg grating temperature sensor (52;53) gave good results, with respect to two measures: 1) the difference in measured and estimated temperature in a fixed point and 2) the distance between a point with a certain measured temperature and the closes point with the same estimated temperature. The 3D temperature maps were also used to characterize cryolesions assumed necessary for tumor ablation (Paper VI). In paper VI the linear relation found between lesion volume and the mean distance from the –40°C isotherm-surface to the lesion surface was extrapolated beyond the lesion-volumes used in the study. Based on this extrapolation it was concluded that a 1 cm rim zone around the tumor is not enough to ensure that the highest temperature within the tumor is lower than –40°C. This extrapolation can be justified since theoretical modeling of the thermal process matched the measured linear relation. Spatial accuracy of both target determination and application of positioning device is essential in functional stereotactic surgery. Acceptable accuracy limits may vary, but errors above 2 mm are seldom feasible. Utilization of CT in combination with stereotactic frames is well established to produce results of high accuracy. However, CT does not provide the high anatomical definition that MR imaging gives. In order to combine the anatomical quality of MR images and spatial accuracy of CT images these image modalities may be fused by means of image processing algorithms (54). The total accuracy of the procedure, combining accuracy of each step from imaging, target determination, image fusion and application of positioning system, is called application accuracy and is discussed in detail in paper II, III and by Maciunas et al.(55). Others have reported on the accuracy of the individual steps (56-81). In tumor resection procedures the demand for accuracy is not as high, but it is important for safe and radical surgery that brain-shift, as reported in Paper I, is accounted for.

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Conclusions

1. Advanced technological development for clinical treatment requires close cross-disciplinary co-operation.

2. The problem that pre-operative images are outdated during surgery was solved by combining neuronavigation and intra-operative MR imaging. Intra-operative MRI provides high resolution 3D data representation in the surgical field. Neuronavigation provides images reformatted in three orthogonal planes and fast interaction with the data set.

3. The stereotactic target determination accuracy of a 0.5T vertical gap interventional MR scanner, assessed in a skull phantom, is not inferior to that of a conventional 1.5T MR scanner and comparable to CT.

4. The stereotactic accuracy of a system consisting of a skull mounted stereotactic positioning device and the interventional MR scanner is comparable to frame based systems. The stereotactic system has the potential of overcoming the following shortcomings often present when using framebased systems: long procedure time, patient discomfort and transport, poor fail-safe capabilities and targeting inaccuracies due to brain shift.

5. MR is an excellent tool for monitoring cryo ablation procedures. MR combined with thermal models can provide 3D temperature maps of high accuracy.

6. Intuitive visual interfaces utilizing 3D rendering and stereo-display was developed. This approach is promising in improving the performance of the operator during minimally invasive surgery.

7. The clinical value of these solutions will be determined in clinical studies

21

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Appendix A

Samset E., Hirschberg H.: “Neuronavigation in intra-operative MRI” Published in: Journal for Computer Aided Surgery 1999:4(4):200-207

Appendix B

Samset E., Hirscberg H.: “Stereotactic target localization accuracy in the interventional MRI” In press: Stereotact Funct Neurosurg 2002;79:191-201

Samset, E. Page 1

STEREOTACTIC TARGET LOCALIZATION ACCURACY

IN THE INTERVENTIONAL MRI

Samset, E., M.Sc., Hirschberg H., M.D., Ph.D.

The Interventional Centre (ES),

The Department of Nerosurgery (HH)

The National Hospital of Norway, University of Oslo

Summary

Objective: To compare stereotactic target determination, based on images obtained from

interventional MRI (iMRI), conventional closed MR and CT. Methods: Stereotactic

coordinates for 55 targets in an artificial scull were derived from iMRI scans and compared

using CT as the standard. Stereotactic coordinates were also derived from iMRI scans in a

series of patients and compared using iMRI fused with CT as the standard. Results: The

mean difference between targets in the skull phantom determined from iMRI images and CT

images was 0.90mm±0.28mm with a maximum difference of 1.57mm. The mean difference

between targets in the patients derived from iMRI alone and interventional MR fused with

CT was 1.39mm±0.54 with a maximum difference of 2.47mm. Interpretation: The results

indicate that interventional MR images can be used for stereotactic target localization.

Key words: stereotactic surgery; MRI; accuracy

Introduction

Stereotactic target determination for functional stereotactic surgery, based on CT imaging,

has recently become an accepted modality [l,n,o,v,x,y,ac] . CT provides high in-plane

spatial precision, and is considered to be geometrical accurate [j,k] . This is due to the linear

nature of the imaging method, where distortion can easily be compensated for, while out-of-

plane precision is limited by the selected slice thickness. Additionally CT scanners are

readily available in most hospitals. On the other hand, several limitations like; images are

available in only one scan-plane, artefacts from stereotactic frame can obscure the image,

and the low soft tissue contrast in CT makes delineation of specific nuclei impossible,

imposes important disadvantages on this modality.

Samset, E. Page 2

In contrast MRI provides images in all orthogonal and oblique scan planes, there are no

artefacts from the stereotactic frame that degrade the images and the high soft tissue contrast

shows most brain structures allowing direct target determination in both the globus pallidum

(GPi ) and subthalamic neucleous (STN) [z]. Despite these clear advantages, uncertainties in

the geometric accuracy of MRI have limited its use in clinical functional stereotactic

neurosurgery [h,z] .

The geometrical accuracy of MRI is limited by non-linear gradient fields, inhomogeneities

in the static magnetic field and magnetic susceptibility effects causing pixel shifts. Image

distortion in MRI has been investigated by others [c,e,g,aa,ab,ad,af,ag], and matching of CT

and MRI targeting has been carried out [a,g] .

Many of the non-linear distortions can be compensated for by applying correction schemes

tailored to specific MRI scanners making MRI the method of choice for stereotactic

targeting [s,aa,ab] .

Recently open MRI systems have become available that allow direct access to the patient

during scanning [b,t,ah] . This enables the execution of surgery within the imaging volume

of the MRI. An interventional MRI can acquire pre-surgical images for planning, intra-

operative images for direct image guidance compensating for brain shift after dural opening

[u,w] and post-operative images for verification of treatment. All stages of the procedure

can be conducted with minimum patient transport greatly increasing preservation of the

sterile surgical field. Although performing stereotactic surgery in the open MRI scanner has

clear advantages, the non-linear distortion problems involved with conventional closed MRI

are also present in open MRI systems and often to a greater degree [m]. The aim of this

study was to compare target determination on CT, conventional closed MRI and

interventional MRI images in a phantom model and in patients.

Materials and Methods

CT and MRI scanners

The CT scanner used was a HiSpeed CT/i (General Electric Medical Systems, Milwaukee,

WI, USA). The open MRI scanner, Signa SP/i (General Electric Medical Systems,

Milwaukee, WI, USA) was used. This MRI scanner is a 0.5 T, super-conducting magnet. It

has a 60-cm wide vertical gap where both imaging and surgery are conducted. The system

has in-bore monitors for evaluation of images and flexible surface coils, specially designed

for interventions. A picture of the scanner can be found in figure A. The static field

Samset, E. Page 3

homogeneity is <=15ppm in a spherical volume with 30cm diameter, the temporal stability

is <=0.1ppm/h. The interventional MR scanner has an actively shielded gradient system

with maximum gradient strength of 12mT/ms. The conventional MR scanner used was a

1.5T Magnetom Vision (Siemens, Erlangen, Germany) with an actively shielded gradient

system (maximum gradient strength 25 mT/m), a magnetic field homogeneity of <2 ppm/50

cm, and a temporal field stability of <0.1 ppm/h.

Head phantom

The head phantom consisted of a plastic artificial skull filled with gelatine. The skull was

constructed of polyamid 12 (PA2200) employing the EOS Laser Sintering method, which gives a

replica of a real scull derived from CT images [d,q] . The skull was filled with gelatine doped

with Magnevist (Berlex Imaging, Montville, NJ, USA) 1:500. Gelatine was added in layers of

approximately 20mm. After each layer had solidified, 1mm glass spheres were added, giving a

distribution of point targets in all dimensions. A total of 55 glass spheres were added.

Accuracy testing

The head phantom described above was positioned in a stereotactic headring (UCHR,

Radionics, Burlington, MA, USA) with a MR localizer (UCLF, Radionics). The localizer

rods were filled with 1:200 dilution of the contrast agent Magnevist (Berlex Imaging). The

phantom with the localizer in place was scanned in the interventional MR system (3D

spoiled gradient recalled echo, TR=34ms, TE=15ms, 256x224 matrix, 25cm FOV, 1mm

slice thickness, 2 acquisitions, phase-direction: p-a) as well as a conventional 1.5T MR

system (3D FLASH, TR=15ms, TE=7ms, 256x256 matrix, 25cm FOV, 1mm slice

thickness, 1 acquisition, phase-direction p-a). A CT scan of the same phantom with a CT

localizer (BRW-LF, Radionics) was also conducted, with 1mm slice thickness. All image

sets were transferred to a stereotactic workstation (BrainLAB, Heimstetten, Germany). The

relation between image space and stereotactic space where established for each dataset by

utilizing the ‘Localize’ function in the @Target software (BrainLAB, Heimstetten,

Germany) for semi-automatic fiducial rod detection. The stereotactic frame coordinates for

the centre of each target were recorded, using the @Target software for each image

modality and compared.

Samset, E. Page 4

Accuracy testing with anatomical markers

A series of patients undergoing placement of DBS electrode for treatment of Parkisons

disease was scanned in interventional MR with the stereotactic localizer in place; in addition

to the CT and MTI scans used for the procedure. The MR datasets were localized using the

UCLF MR localizer frame. Stereotactic targets were derived from various anatomical points

in each patient using the @Target software from the interventional MR dataset. The MR

dataset was also fused with the CT dataset and localized using the BRW-LF localizer frame.

Stereotactic coordinates were derived for the same anatomical points independent of the MR

localizer frame. The image fusion was done using the @Target software. After recording the

stereotactic coordinates with the two methods, one based on MR localizer and one base on

CT localiser, the coordinates were compared.

Results

The headphantom where mounted in the stereotactic headring and scanned in a CT scanner,

a conventional closed MR scanner and an open interventional MR scanner with a

stereotactic localizer in place. The images were transferred digitally to a surgical planning

computer. Stereotactic coordinates for each point-target were collected for all three image

modalities and compared. Table A summarizes the absolute differences between the various

modalities (difference in error). As can be seen from the table, the maximum difference

between target determination from CT and iMRI was 1.6mm. The results shown in Table B

are the relative differences along the orthogonal axies. To further illustrate the difference

along the three axies, figure B plots the target displacement from the iMRI data sets against

CT, while figure C plots the target displacement from the conventional MRI data set against

CT. The figures show that the distributions of errors are biased. For both MR data sets the

bias is mainly towards negative lateral and negative vertical displacement, as can also be

seen from the numbers found in table B. Figure C shows the distribution of errors obtained

from iMRI and conventional MRI datasets. Table C shows the absolute differences after

compensation for linear displacement, by subtracting the mean displacement vector, given

by the directional comparison of coordinates in table B, from each target MR coordinate.

In addition th the CT and MRI scans normally used for DBS electrode placement, some

patients were scanned in the iMRI with the stereotactic localizer frame in place. Stereotactic

coordinates for 10 anatomical targets were first derived based on iMR images alone, and

Samset, E. Page 5

were compared to coordinates of the same targets based on iMR images fused with CT

images. Table D summarized the absolute differences (difference in error) obtained from

these measurements.

Discussion

The present study was undertaken to evaluate the feasibility of conducting functional

stereotactic surgery in an interventional MR scanner. It was designed to assess the

stereotactic target localization accuracy of an iMRI system in comparison with CT as the

gold standard.

The total accuracy error for conventional stereotactic procedures is the sum of the errors in

all of the involved steps [r]. These steps can be summarized as follows: Target identification

on MR (CT) images, transformation of target from image- to frame-coordinates through rod

identification, and inaccuracies inherent in the stereotactic frame itself.

The accuracy of the determination of the target coordinates is crucial. For target coordinates

directly obtained from the open MR images, the possible source of error is the absence of a

one-to-one relationship between image coordinates and physical coordinates. An attempt to

measure this inaccuracy was not performed in this study, but it has been shown by others

[ae] that the error is greater at the periphery of the imaging volume, and relatively small

close the iso-centre.

The results found in this study give a measure of the sum of the inaccuracy involved in

target identification and transformation of target coordinates from image- to frame

coordinates. Since the fiducial rods are at the periphery of the imaging volume, it is

expected that error in rod locations in the MR images is a major contribution to the overall

errors in accuracy.

Others have studied the mechanical accuracy of stereotactic frames [f,i,r] . These results

combined with the results in this study will give the total application accuracy of stereotaxy

based on MR images acquired in an interventional scanner. Using the numbers from

Maciunas et. al [r] for the CRW frame (Radionics, Burlington, MA, USA) and the numbers

found from the present phantom study the accuracy of the total system, would therefore be

1.2mm±0.45mm.

Correction for the empirically found mean displacement gave an improvement of the results

by approximately a factor of two. It is however yet to be proven that this result is generally

applicable. The mean displacement may result from the above-mentioned error in imaging

Samset, E. Page 6

of the rods. Others have suggested that a displacement in the anterior-posterior direction is

due to the spin vector of the Hydrogen elections [p]. More studies, targeted to answer this

question, must be conduction before a conclusion can be drawn.

The difference between target coordinates derived from either conventional 1.5T images or

images from the interventional 0.5T scanner and coordinates derived from CT images were

less than 1mm on average. The maximum error was less than 2mm. Taking into

consideration that the voxel size in all image sets was about 1x1x1mm the error can be said

to be within 2 voxels distance.

The results from the phantom study show that target identification on a conventional 1.5T

MR as well as an open interventional 0.5T MR is feasible for stereotactic procedures. The

numbers from the patient study supports that this conclusion also holds clinically. The

results can however not be generalized to other MR imagining systems, or even other

instances of the same systems as used in this study. The necessary individual calibration of

the MR systems employed at each site should therefore be performed and repeated on a

routine basis. The promising performance of the interventional MR scanner with respect to

accuracy opens the possibility for a new approach to stereotactic surgery, where entire

stereotactic procedure can be done within the interventional MR scanner. The feasibility of

this approach is presently being evaluated. Although definitive placement of DNS

electrodes is usually done by microelectrode recording or stimulation, minimalization of

target coordinate errors is a clear help in minimizing the number of trajectories required.

In conclusion the accuracy of stereotactic target determination employing the intraoperative

MRI is equal to that of conventional closed MRI systems, and is comparable to that of CT.

Acknowledgements

This study was partly founded by a grant from Norsk Parkinsonforening and from the

Norwegian Research Council. We acknowledge the support of GTPrototyper, for providing

the laser-sintered skull.

Samset, E. Page 7

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Table A – Comparison of target coordinates, measures from head phantom

Compared modalities Mean absolute error Standard Dev. Maximum

absolute error

Conv. 1.5T - CT 0.88mm 0.27mm 1.67mm

Open 0.5T - CT 0.90mm 0.28mm 1.57mm

Open 0.5T – Conv. 1.5T 0.61mm 0.27mm 1.20mm

Table B – Directional comparison of target coordinates

Compared modalities A-P (mm) Lateral (mm) Vertical (mm)

Conv. 1.5T - CT 0.35 ± 0.2 -0.56 ± 0.2 -0.45 ± 0.3

Open 0.5T - CT -0.07 ± 0.3 -0.61 ± 0.3 -0.47 ± 0.3

Open 0.5T – Conv. 1.5T -0.42 ± 0.3 -0.05 ± 0.2 -0.02 ± 0.3

Table C – Comparison of target coordinates after subtraction of mean directional

displacement

Compared modalities Mean absolute error Standard Dev. Maximum

absolute error

Conv. 1.5T - CT 0.42mm 0.19mm 0.97mm

Open 0.5T - CT 0.50mm 0.19mm 1.12mm

Open 0.5T – Conv. 1.5T 0.47mm 0.20mm 1.08mm

Table D – Comparison of target coordinates, measures from patients

Compared modalities Mean absolute error Standard Dev. Maximum

absolute error

Open 0.5T - CT 1.39mm 0.54mm 2.47mm

Samset, E. Page 13

Figure A: The open interventional MRI scanner; Signa SP/i.

-80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40-1.5

-1

-0.5

0

0.5

1

A-P coordinates from CT (mm)A-P displacement (mm)

-50 -40 -30 -20 -10 0 10 20 30 40 50-1.5

-1

-0.5

0

0.5

1

Lateral coordinates from CT (mm)Lateral displacement (mm)

0 10 20 30 40 50-1.5

-1

-0.5

0

0.5

1

Vertical coordinates from CT (mm)Vertical displacement (mm)

Figure B: Displacement of targets in interventional 0.5T images vs. CT images. X axis

indicate CT coordinate of target, y axis indicate the difference between MR coordinate and

CT coordinate.

Samset, E. Page 14

-80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40-1.5

-1

-0.5

0

0.5

1

A-P coordinates from CT (mm)A-P displacement (mm)

-50 -40 -30 -20 -10 0 10 20 30 40 50-1.5

-1

-0.5

0

0.5

1

Lateral coordinates from CT (mm)Lateral displacement (mm)

0 10 20 30 40 50-1.5

-1

-0.5

0

0.5

1

Vertical coordinates from CT (mm)Vertical displacement (mm)

Figure C: Displacement of targets in conventional 1.5T images vs. CT images. X axis

indicate CT coordinate of target, y axis indicate the difference between MR coordinate and

CT coordinate.

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.80

5

10

15

error (mm)

# targets, 0.5T open

0.2 0.4 0.6 0.8 1 1.2 1.4 1.60

2

4

6

8

10

12

error (mm)

# targets, 1.5T closed

Figure D: Error histogram for target differences in 1.5T MRI and 0.5T open MRI with

respect to CT target coordinates.

Appendix C Samset E., Hirschberg H.,: “Image-guided stereotaxy in the interventional MRI” Published in Minimal Invasive Neurosurgery 2003:46(1), 5-10

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Appendix D Samset E., Mala T., Edwin, B., Gladhaug I., Søreide O., Fosse E.: "Validation of estimated 3D temperature maps during hepatic cryo surgery" Published in: Magnetic Resonance Imaging 2001:19(5):715-721

Validation of estimated 3D temperature maps during hepatic cryo surgery

E. Samseta,*, T. Malaa, B. Edwina, I. Gladhaugb, O. Søreideb, E. Fossea

aThe Interventional Center, Rikshospitalet, 0027 Oslo, NorwaybDepartment of Surgery, Rikshospitalet, Norway

Received 23 October 2000; accepted 31 March 2001

Abstract

A simple model for estimating temperature distribution within the frozen region during cryo ablation was tested for accuracy. Freezingexperiments were conducted in both ex vivo and in vivo porcine livers. Temperature was measured during freezing using a fiber-optictemperature sensor. Three-dimensional MR images were obtained at the end of each freezing cycle. From the MR image volumes,three-dimensional temperature maps were calculated numerically using a simplified bio-heat model. Estimated temperatures were comparedto measured temperatures. The median difference between measured and estimated temperature was 3.03°C. The median distance from asensor element to the closest point on a isotherm surface with the corresponding estimated temperature was 0.70 mm. The accuracy of thismodel is acceptable. Temperature maps as outlined here may be used for monitoring of cryotherapy in order to increase clinicaleffectiveness. © 2001 Elsevier Science Inc. All rights reserved.

Keywords:Cryosurgery; Thermal distribution; Computer simulation; Magnetic resonance imaging

1. Introduction

Local destruction of hepatic tumors by freezing has ex-perienced increased interest in recent years due to the abilityto monitor the freezing process [1]. The commonly usedimaging modality for monitoring the freezing process isultrasound sonography (US). US has some limitation be-cause of acoustic shadowing and complete three-dimen-sional delineation of the frozen region can not be obtained[2]. With the introduction of open magnetic resonance im-aging (MRI) systems and an increased interest in magneticresonance imaging as a near real-time intra-operative imag-ing modality [3], local ablative modalities such as cryosurgery are increasingly popular.

MR imaging gives excellent visualization of frozen tis-sue during freezing. With conventional echo times the fro-zen region can be observed as a region of signal void, dueto the very short T2* of frozen tissue [4–6]. This facilitatesdelineation of the frozen region [7]. Information about thetemperature distribution within the frozen region is notavailable. In cryosurgery of the liver, such temperature

information is important as subzero temperatures not nec-essarily ensure cell destruction [8,9].

The relationship between thermodynamic parameterssuch as temperature and freezing rate, and cell destruction isnot completely established [10]. If thermodynamic param-eters can be used as indicators of cell destruction, assess-ment and visualization of these parameters will improve theaccuracy and effectiveness of the ablative process. Quanti-tative estimation of temperatures and freezing rates are alsoimportant tools for investigating this relationship [11].

Hong et al. proposed a method for temperature estima-tion in frozen tissue using the bio-heat equation [4]. Bound-ary conditions for the numerical solution of this equationwas found using MR imaging, thus reducing the complexityof the problem of estimating such temperature maps. In thisreport, this model has been studied in the context of vali-dating the results of the estimated temperatures.

2. Materials and methods

2.1. Specimen and animal preparation

Ex vivo and in vivo experiments were performed. In thefirst group six non perfused ex vivo porcine livers wereused, all with ischemic time less than 3 h at thestart of the

* Corresponding author. Tel.:147-23070111; fax:147-23070110.E-mail address:eigil.samset@klinmed.uio.no (E. Samset).

Magnetic Resonance Imaging 19 (2001) 715–721

0730-725X/01/$ – see front matter © 2001 Elsevier Science Inc. All rights reserved.PII: S0730-725X(01)00389-7

experiment. In the second group four living pigs (weight24–26 kg) were studied. The animals were kept starvedovernight, but could drink water freely. Intramuscular (i.m.)ketalar (10 mg/kg) was given as premedication, and pento-barbital and morphine were then given i.v. Tracheostomywas performed and a central venous catheter and an arterialaccess line was established. After intubation the animalswere anesthetized with isofluran gas. Blood pressure, uri-nary output and rectal temperature were monitored. Theanimals were sacrificed 1 h after the last MRI scan by i.v.infusion of 3 molar potassium chloride. The research pro-tocol was approved by the Local Veterinary Control Group.

2.2. Freezing and temperature measurement

Freezing was achieved using a 3.2 mm cryo probe andthe cryo system CryoHit (Galil Medical, Yokneam, Israel)which can produce temperatures as low as2180°C at theprobe tip. The cryo system was driven by pressurized Argongas (300 bar) utilizing the Joule Thomson effect. The systemlogged temperatures at the cryo probe tip continuously. Thecryo probe was fixed to the experimental set-up and an opticaltraceable locator (Flashpoint, Image Guide Technologies) wasused to measure position and direction of the cryo probe.

A fiber-optic thermo sensor (Optomed, Trondheim, Nor-way), capable of measuring distributed temperatures as atemperature profile along the fiber, was inserted at an arbi-trary angle to the cryoprobe. The center element of thethermo sensor was positioned closer than 1 cm to the cryoprobe. The thermo sensor measures temperature optically by10 Bragg gratings inscribed in an optical fiber [12]. Eachsensor element is separated by 6.5 mm and the external diam-eter of the probe is 1.25 mm. An opto-electronic unit connectedto the fiber generated and detected signals that were sent to acommunicating PC for continuous logging (5 sec. sample in-terval) and presentation of temperature data. Each freezingcycle lasted 20 min, upon which thermal equilibrium wasachieved, intervened by 15 min of passive thawing.

2.3. Experimental procedure

2.3.1. Ex vivo experimentsA flexible surface coil was wrapped around the liver and

arranged in a box which was placed in the image volume ofan open GE Signa SP/i MR scanner (GE, Milwaukee, WI) with0.5 Tesla field strength. The scanner has a 60 cm vertical gapwhere both surgery and imaging can be conducted. MR imageswere obtained prior to freezing, and at the end of each freezingperiod. The imaging sequence used was a 3D Spoiled GRASSwith 3 mm-slice thickness. An echo time of 9 ms and arepetition time of 25 ms was used for the scan. The imageswere taken in the plane of the cryo probe. Scan duration wasfrom 1.2 to 3.5 min depending on the phase matrix size. Twocryo lesions were made in each specimen, and in each lesiontwo freeze-thaw cycles were conducted.

2.3.2. In vivo experimentsA midline laparotomy was performed enabling access to

the liver. A flexible surface coil was wrapped around theanimal to cover the right lower chest and the right subcostalregion. Two cryo lesions were made without interference inthe upper frontal lobe of the liver. The same freeze protocolas for the ex vivo experiments was used, two cycles offreezing (20 min) interrupted by passive thawing (15 min).Images were taken in an axial plane using the same imagingsequence as for the ex vivo experiments. The setup of cryoprobe, locator and thermo sensor was also identical to the exvivo experiments.

2.4. Temperature estimation

The bio-heat equation describes the energy balance of invivo biologic tissue. It can be expressed as:

¹~K ¹T! 5 ~rC!­T

­t1 wb~T 2 Ta! 1 qm (1)

whereT is the temperature,K is the thermal conductivity,ris the density,C is the heat capacity,wb is the volumetricmass flow rate of blood,Ta is the arterial blood temperature,qm is the metabolic heat andt is time. Inside the frozenregion in a cryo surgical setting the latter two terms will bezero and the equation thus becomes:

¹~K ¹T! 5 ~rC!­T

­t(2)

In temperature steady-state this will be further simplified to:

¹~K ¹T! 5 0 (3)

K was assumed to only take on two different values. One forthe liver tissue and one for the cryo probe. The equation wastransformed to a difference equation and solved iteratively,as described by Hong et al. [4]:

Ti, j,k 5 SKi21,j,k 1 Ki11,j,k

Dx2 1Ki, j21,k 1 Ki, j11,k

Dy2

1Ki, j,k21 1 Ki11,j,k11

Dz2 D21

3 SKi21,j,kTi21,j,k 1 Ki11,j,kTi11,j,k

Dx2

1Ki, j21,kTi, j21,k 1 Ki, j11,kTi, j11,k

Dy2

1Ki, j,k21Ti, j,k21 1 Ki, j,k11Ti, j,k11

Dz2 D (4)

The boundary conditions:

Tio, jo,ko5 0

(5)

Tic, jc,kc5 Tc

716 E. Samset et al. / Magnetic Resonance Imaging 19 (2001) 715–721

were given by the phase transition front (i0,j0,k0), which canbe found from the MR images, and the temperature, Tc, atthe tip of the cryo probe (ic,jc,kc).

The MR images were segmented to delineate the frozentissue, the unfrozen tissue, and the cryo probe. The frozentissue was found by thresholding, followed by median fil-tering and manual clipping of parts not belonging to theregion. The cryo probe holder was tracked optically and thecryo probe position could thus be accurately found. Thecryo probe was modeled as a solid metal with a heatsink inits interior. The heatsink was defined to be 5 mm from thetip of the cryo probe in the center of the probe. The distancewas established by the experiment described below forassessment of the thermal conductivity of the cryo probe.The position of the heatsink was found by aligning the pointof minimum measured temperature with the cryo probe.

The estimated temperature map was calculated numeri-cally by iterating until convergence. The calculation wasdone on an O2 workstation (SGI) with a 200 MHz processor(MIPS R5000). To test for convergence the sum of esti-mated temperatures for all pixels in the frozen region wascompared with the same sum in the previous step. If the sumof difference for all voxels was less than 60 degrees centi-grade for more than 100 consecutive iterations, the conver-gence test was considered positive.

2.5. Assessment of model parameters

The thermal conductivity of the cryo probe was found byconducting an experiment where water was frozen in acylindrical tank. The fiber optic temperature sensor wasplaced adjacent and parallel to the cryo probe. The thermalconductivity of the cryo probe was assessed by finding theK, which gave the best fit between the estimated and themeasured temperatures. The thermal conductivity constantused for frozen water (220°C) was 2.42 W/mK [13].

The thermal conductivity of frozen pig liver was foundby conducting a freezing experiment in an ex vivo liver inthe same way as described above. The fiber optic tempera-ture sensor was positioned perpendicular to the cryo probeand distal to the cryo probe tip. The thermal conductivity ofthe liver was assessed by finding the K that gave the best fitbetween estimated and measured data.

2.6. Validation of estimated temperatures

Estimated temperatures calculated from the above-de-scribed model and temperatures measured by the fiber op-tical thermo sensor, were compared in two different per-spectives. First the temperatures at a sensor element and thecorresponding position in the 3D-temperature map werecompared. This comparison waslabeled iso-position vali-dation,as temperatures at a given position were compared.Secondly, the distance from a sensor element (measuredtemperature), to the closest isotherm-surface of identicalestimated temperature were compared. This comparison

was labeledisotherm validation,as positions for a giventemperature were compared.

In both cases the temperature at a given position in the3D-temperature map was calculated as a weighted sum ofthe closest voxels to the desired point. Each voxel was sized0.9 3 0.9 3 3.0 mm. The thermo-sensor was modeled as astraight line. The position of this line was found from theMR images. In the MR images, the thermo-sensor could beseen as a line of signal void. Two points of this line, oneclose to the tip and the other close to the point of insertion,were recorded. From these points an analytic line was cal-culated, the sensor elements was defined to be along thisline. A sensor element would thus, not necessarily lie in thecenter of a voxel. To find the corresponding estimatedtemperature to a temperature measured by a sensor element,a cube of 33 3 3 3 voxels, centered around the givenposition, was evaluated to calculate a weighted average. Theweight for each of these voxels was calculated as:

w~v,p! 5 cos~~vx 2 px!p/2! 3

cos~~vy 2 py!p/ 2! 3 cos~~vz 2 pz!p/ 2! (6)

Where v is the voxel under consideration (discrete), p is thegiven position (non discrete), at which a temperature issought. The weighting function w is visualized in Fig. 1.The estimated temperature in position p will be given as:

Tw~ p!

5

Ol521

1 Om521

1 On521

1

w~vi1l, j1m,k1n,p! z T~vi1l, j1m,k1n!

Ol521

1 Om521

1 On521

1

w~vi1l, j1m,k1n,p!

(7)

where T() is the estimated temperature at voxel vi,j,k.

Fig. 1. Weighting function used to calculate the temperature value in ananalytic point as a weighted sum of neighbor voxels depending on distance.The figure illustrates Eq. (6) in two dimensions.

717E. Samset et al. / Magnetic Resonance Imaging 19 (2001) 715–721

The distance from a sensor element to the closest iso-therm-surface was calculated using the local temperaturegradient. At the starting point, the local temperature gradi-ent was calculated. The gradient vector points in the direc-tion of increasing temperature. If the measured temperaturein the starting point is lower than the estimated temperature,an incremental step in the direction of the local temperaturegradient was made, otherwise an incremental step in theopposite direction was made (toward decreasing tempera-ture). This procedure was iterated until a point of equaltemperature to the measured value was found. The distancebetween the point found by this procedure and the point ofthe thermo sensor was used as a measure for isothermvalidation.

When evaluating the error in temperature and positionfor the calculated data, statistical median (with 95% confi-dence interval) was used due to the asymmetry in the datadistribution.

3. Results

3.1. Animal toleration

Despite long anesthetic time (mean 355 min) and 4cycles of cryotherapy, the animals tolerated the procedurewell. No major bleeding from surface cracks or after re-moving the cryoprobes occurred, nor any bleeding afterextraction of the temperature probe. The cryolesions wereobserved at the liver surface as a sharply demarcated dark/black circular area. A slice from a 3D MRI volume of oneof the ex vivo cases can be seen in Fig. 2.

3.2. Temperature estimation

Temperature estimation by numerical solution of thesimplified bioheat equation was done for a total of 10

lesions in the 6 ex vivo livers and 6 lesions in the 4 in vivolivers. The numerical calculation took 30–90 s computerprocessing time, with iterations to convergence rangingfrom 600–1800. A plot of the difference in sum of allestimated voxels from one iteration to the next is shown inFig. 3. From the figure it can be seen that the number ofiterations to convergence were approximately 1700.

3.3. Assessment of model parameters

The thermal conductivity of the cryo probe was found tobe 19.2 W/mK. The thermal conductivity of frozen pig liverwas found to be 0.78 W/mK.

3.4. Validation of estimated temperatures

Iso-position validationof the estimated temperaturesgave a difference between estimated and measured temper-ature of median 3.03°C (95% CI 2.30–5.87) for the ex vivolivers. In the in vivo experiments the median of the differ-ence was 3.78 (95% CI 1.12–11.67). The error was found tobe larger close to the cryo probe than in the peripheralregions. A comparison between the measured and the esti-mated temperature profile can be seen in Fig. 4.

Fig. 2. MRI slice of an iceball from an ex vivo experiment. The dark lineextending from the iceball (lower left) is the thermal sensor probe.

Fig. 3. Convergence of numeric solution. The graph shows the differencebetween the sum of all voxel values from one iteration to the next. Thehorizontal lines show the convergence criteria; 100 consecutive iterationswith overall voxel temperature sum within660 degrees.

Fig. 4. Comparison of measured and estimated temperatures from an invivo experiment. The solid line shows the estimated temperature while thesquares shows measured temperatures. The x-axis denotes distance fromthe tip of the thermo sensor probe.

718 E. Samset et al. / Magnetic Resonance Imaging 19 (2001) 715–721

Iso-temperaturevalidation of the estimated temperaturesgave a distance from a sensor element to a point in thetemperature map with corresponding temperature of median0.75 mm (95% CI 0.48–1.25) for the ex vivo livers. In thein vivo experiments the median of the difference was 0.61mm, (95% CI 0.22–2.68). A visual comparison betweenmeasured temperatures and the corresponding isotherms canbe seen in Fig. 5. The figure shows the sensor elements ascolored squares. The calculated isotherm for the measuredtemperature is shown with corresponding color.

A summary of the statistics is given in Table 1.

4. Discussion

The objective of thermal energy treatment in hepaticsurgery is ablation of tumor tissue. Ideally, in vivo moni-toring of cell destruction should be performed in order toensure that irreversible tissue destruction has taken place.This is currently not possible and assessment of parameters

that correlates with cell destruction is the second bestmethod. Thermodynamic parameters such as absolute tem-perature and rate of temperature changes can be used assuch indirect parameters [8,9]. Although the relationshipbetween temperature and cell destruction is not conclusivelyestablished in all tissue types, this relationship will probablybe defined as a consequence of ongoing research currentlyperformed by our group and others.

Temperature estimation by numerical solution of a sim-plified bio-heat equation has been known for some time[4,5]. It is not easily implemented, however, and can some-times seem inaccurate in non-idealized settings. The fewstudies reported, show an acceptable correlation betweenestimated and measured temperatures. In most of thesestudies, however, only one single point of measurement fortemperature comparison has been used. In this report, amethod of distributed temperature measurement and com-parison of these measured temperatures with the estimatedtemperatures is presented.

The correlation between measured and estimated tem-peratures at a given point was not always of optimal accu-racy. This is most likely due to the sources of error dis-cussed later. Nevertheless, the distance from a point ofdirect temperature measurement to the closest estimatedpoint with the same temperature was small (median 0.7mm). Clinically this difference is hardly of any significance,indicating that the temperature modeling is adequate forisotherm estimation. The difference between estimated andmeasured temperatures were larger close to the cryo probethan in peripheral regions. This is due to the steep temper-ature gradient in this area. As mentioned later this source ofinaccuracy was partially compensated. In clinical settings,however the main objective is destruction of tissue and thecentral area is therefor of less importance, as the tempera-ture in this region is adequate for cellular destruction. Theperipheral region of the cryolesion is more important tomonitor, as temperatures in this region may not be loweredto a level which ensure destruction [14]. The ability todemonstrate that the temperature distribution in a cryolesionis sufficiently low to achieve cellular destruction in theregion of interest will improve treatment efficacy signifi-cantly. Information given by the isotherms are also benefi-

Fig. 5. Comparison of measured and estimated temperatures with respect todistance. The figure shows estimated isotherms corresponding to the mea-sured temperatures. The squares give sensor element positions (measuredtemperatures), only eight of the ten sensor element were within the frozenregion. The color of a sensor element and the isotherm for correspondingestimated temperature corresponds.

Table 1Summary of statistical distribution of the error in the temperature estimation. Temperature error denotes the difference in temperature between measuredand calculated temperature at a fixed point in space. Position error denotes the distance in mm between a sensor element and the calculated isothermsurface with the same temperature.

Specimengroup Median

95% ConfidenceInterval (CI) Range Mean

Temperature error (°C) Ex vivo 3.03 2.30–5.87 0.19–69.36 7.37In vivo 3.78 1.12–11.67 0.17–27.92 7.77Total 3.03 2.51–5.87 0.17–69.36 7.48

Position error (mm) Ex vivo 0.75 0.48–1.25 0.00–7.09 1.42In vivo 0.61 0.22–2.68 0.01–4.52 1.36Total 0.70 0.48–1.21 0.00–7.09 1.40

719E. Samset et al. / Magnetic Resonance Imaging 19 (2001) 715–721

cial to research on temperature distribution within frozentissue as noninvasive spatial information is provided.

In the thermal model described here assumptions aremade that are reasonable in idealized situations where ther-mal equilibrium is reached. When thermal equilibrium isnot present, however, the time dependent part of the bio-heat equation should not be omitted. With scanning times asused in this study, the problem of thermal equilibrium maynot play an important role. With faster scanning techniquesin higher field- and gradient strength MRI systems, nearreal-time 3D acquisition may be possible and temperaturetransients should thus be incorporated in the model.

The technique of temperature estimation described herehas several sources of error that are not related to thethermal model itself. Such sources of error include:

4.1. Inaccuracy in defining cryo probe position due toimage artifacts from the cryo probe

The position of the cryo probe is crucial to the estimatedtemperature map [15]. The cryo probe has a different ther-mal conductivity than the surrounding tissue. The positionof the cryo probe will therefore strongly influence the re-sulting temperature map, since it defines both the heatsinkand a thermal body different from the tissue in which it isinserted. Ideally, the cryo probe position should be foundfrom the MR images prior to freezing. Due to the imageartifacts of the cryoprobe, such determination of the cryoprobe position would be inaccurate. To adjust for this anoptical traceable locator was used. This enabled accuratedetermination of the cryo probe position in the ex vivosituation, but in the in vivo experiments, respiratory motionmade the determination of the cryo probe position lessaccurate.

4.2. Inaccuracy in defining the fiber optic temperaturesensor position, due to partial volume effects

The position of the fiber optic temperature sensor wascrucial to the validation procedure. Accurate mapping ofsensor elements to voxels in the estimated 3D-temperaturemap was the foundation of this validation. The thermosensor position was found from the MR images. A voxelsize of 0.93 0.9 3 3.0 mm combined with a bendablethermo sensor, however, made accurate determination of thesensor position in the submillimeter range not possible.

4.3. Problems related to image resolution and theresolution used in the model of temperature calculation

The resolution used in MR imaging defines an upperboundary to the accuracy of all defined positions (cryoprobe, thermo sensors and boundaries). This quantificationerror will influence the result of the calculation. In thispaper, the calculation was done with the same resolution as

the image data. This resolution could be increased, but thiswould also have consequences for computation time.

4.4. Inaccuracy in delineating the border of the frozenregion

The interface between frozen and unfrozen tissue wasfound by thresholding. An error in delineation of this borderin the order of one to two pixels would not be unexpected.When the frozen region extended to the liver surface, theborder between frozen tissue and air also needed to beoutlined. This was done by comparing images prior tofreezing with images during freezing. Close to the cryoprobe the temperature difference between two neighboringvoxels could sometime be more than 20°C. This was due tothe large temperature gradient in the center of the frozenregion. Small inaccuracies in position could therefore resultin large inaccuracies in temperature. This was partly com-pensated for by using a weighting function for the determi-nation of a temperature at a specific point, by taking neigh-boring voxels into account.

Theoretically, higher resolution images and faster imag-ing would compensate for most of the above mentionedproblems.

5. Conclusions

Temperature estimation by thermal modeling is an alter-native method of temperature monitoring giving resultscomparable to direct temperature measurements. The esti-mated temperature at a given point may not always be exact,but is within acceptable limits and the distance from theestimated to the exact temperature is small. 3D temperaturemaps may play an important role in the research of biologiceffects of cryo ablation and may also have potential clinicalapplications.

References

[1] Gage AA. History of cryosurgery. Semin Surg Oncol 1998;14(2):99–109.

[2] Gilbert JC, Onik GM, Hoddick WK, Rubinsky B, Ferrell LD. Ultra-sound monitored hepatic cryosurgery: longevity study on an animalmodel. Cryobiology 1986;23(3):277–85.

[3] Gould SW, Darzi A. The interventional magnetic resonance unit—theminimal access operating theatre of the future? Br J Radiol 1997;70(Spec No):S89–S97.

[4] Hong JS, Wong S, Pease G, Rubinsky B. MR imaging assistedtemperature calculations during cryosurgery. Magnetic ResonanceImaging 1994;12(7):1021–31.

[5] Gilbert JC, Rubinsky B, Wong ST, Brennan KM, Pease GR, LeungPP. Temperature determination in the frozen region during cryosur-gery of rabbit liver using MR image analysis. Magn Reson Imaging1997;15(6):657–67.

[6] Tacke J, Speetzen R, Heschel I, Hunter DW, Rau G, Gunther RW.Imaging of interstitial cryotherapy—an in vitro comparison of ultra-

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sound, computed tomography, and magnetic resonance imaging.Cryobiology 1999;38(3):250–9.

[7] Pease GR, Wong ST, Roos MS, Rubinsky B. MR image-guidedcontrol of cryosurgery. J Magn Reson Imaging 1995;5(6):753–60.

[8] Gage AA, Guest K, Montes M, Caruana JA, Whalen DA. Effect ofvarying freezing and thawing rates in experimental cryosurgery.Cryobiology 1985;22(2):175–82.

[9] Gage AA, Baust J. Mechanisms of tissue injury in cryosurgery.Cryobiology 1998;37(3):171–86.

[10] Rubinsky B, Lee CY, Bastacky J, Onik G. The process of freezingand the mechanism of damage during hepatic cryosurgery. Cryobi-ology 1990;27(1):85–97.

[11] Rewcastle JC, Sandison GA, Hahn LJ, Saliken JC, McKinnon JG,Donnelly BJ. A model for the time-dependent thermal distribution

within an iceball surrounding a cryoprobe. Phys Med Biol 1998;43(12):3519–34.

[12] Samset E, Mala T, Ellingsen R, Gladhaug I, Søreide O, Fosse E.Temperature measurement in soft tissue using a distributed fibreBragg-grating sensor system. Min Invas Ther & Allied Technol2001;10(2).

[13] Geankoplis CJ. Transport processes, and unit operation. Pretence-Hall International Editions, 1993.

[14] Baust J, Gage AA, Ma H, Zhang CM. Minimally invasive cryo-surgery—technological advances. Cryobiology 1997;34(4):373–84.

[15] Daniel BL, Butts K. The use of view angle tilting to reduce distortionsin magnetic resonance imaging of cryosurgery. Magn Reson Imaging2000;18(3):281–6.

721E. Samset et al. / Magnetic Resonance Imaging 19 (2001) 715–721

Appendix E

Samset E., Mala T., Ellingsen R., Gladhaug I., Søreide O., Fosse E.: "Temperature measurement in soft tissue using a distributed fiber bragg grating sensor system" Published in: Min Invas Ther & Allied Technol 2001:10(2):89-93

Appendix F Mala T. Samset E., Aurdal L., Gladhaug I., Edwin B., Søride O.: ”Magnetic Resonance Imaging-Estimated Three-Dimensional Temperature Distribution in Liver Cryolesions: A study of Cryolesions Characteristics Assumed Necessary for Tumor Ablation” Published in: Cryobiology 2001;43(3): 268-275

Magnetic Resonance Imaging-Estimated Three-Dimensional TemperatureDistribution in Liver Cryolesions: A Study of Cryolesion Characteristics

Assumed Necessary for Tumor Ablation

Tom Mala,*,†,1 Eigil Samset,* Lars Aurdal,* Ivar Gladhaug,† Bjørn Edwin,*,† and Odd Søreide†

*Interventional Center and †Surgical Department, The National Hospital, 0027 Oslo, Norway

lesionsnding un-are fre-dered numeri-ion bor-is-d thetures ofedian

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Cryobiology 43,268–275 (2001)doi:10.1006/cryo.2001.2351, available online at http://www.academicpress.com on

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The goal of this study was to estimate the three-dimensional (3D) temperature distribution in liver cryoand assess the margin of the transition zone between the tumoricidal core of the lesion and the surroufrozen tissue, using criteria proposed in the literature. Local recurrences after liver tumor cryoablation quent. Temperatures below 240°C and a 1-cm zone of normal tissue included in the cryolesion are consinecessary for adequate ablation. The 3D temperature distribution in 10 pig cryolesions was estimated bycal solution of a simplified bioheat equation using magnetic resonance imaging data to establish cryolesder conditions. Volumes encompassed by the 220,240, and 260°C isotherms were estimated. The shortest dtance from every voxel on the 240°C isotherm to the cryolesion edge was calculated and the mean anmaximal of these distances were defined for each cryolesion. Median cryolesion volumes with tempera220,240, and 260°C or colder were 53, 26, and 14% of the total cryolesion volume, respectively. The mcryolesion volume was 12.3 cm3. The median of the mean distances calculated between the 240°C isotherm andthe cryolesion edge was 4.1 mm and increased with increasing cryolesion volume. The median of the lthese distances calculated for each cryolesion was 8.1 mm. Temperatures claimed to be adequate for struction were obtained only in parts of the cryolesion. The adequacy of a 1-cm zone of normal liver tiscluded in the cryolesion to ensure tumor ablation is questioned.© 2001 Elsevier Science (USA)

Key Words:cryosurgery; cryoablation; temperature; thermal profile; isotherms; magnetic resonance imaliver tumors; liver.

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Cryotherapy is one of several ablative teniques used for local destruction of liver tumo(3, 5). Completein situ destruction of malignantumors has proved difficult to accomplish arecurrences at the cryosite have been reportemore than 5–44% of patients treated (25). Seral factors influence tumor cell destruction,cluding temperature, number of freeze cycand rate of temperature changes (2, 4, 7,Temperatures below240 to250°C are assumeby many as necessary to ensure lethal freeinjury to neoplastic tissue (1, 6, 8, 17, 28).critical temperature, equal to or lower th240°C, is achievable only in parts of the cryosion. Due to this a 1-cm zone of normal hepa

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ceived August 16, 2001; accepted November 14, 20is work was funded by the Research Council of No

o whom correspondence and reprint requests shoddressed. Fax:1 47 23070110. E-mail: tom.mala@ospitalet.no.

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tissue is often included in the cryolesion to esure total tumor destruction (16, 20, 25, 29).

Previously, cryolesion temperatures habeen measured using single or multiple pomeasurements. Cryolesion expansion and shave generally been monitored by ultrasou(US). Magnetic resonance imaging (MRI) of thcryolesion enables improved visualization of tspatial configuration and can be used for thrdimensional (3D) temperature calculation (114, 27, 29). MRI monitoring thus provides moinformation about the volume–temperature dtribution during freezing than alternative montoring modalities.

In this report, the temperature distribution the cryolesion was estimated based on MRI dand mathematical models of temperature disbution in frozen tissue. Cryolesion volumes different temperatures (defined by isothermand the distances from the assumed tumoriccore of the cryolesion to the interface betwefrozen and unfrozen tissue were studied.

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METHODS

Animal Preparation

In vivoexperiments were performed using pigs with median weight 25 kg (range 24–kg). The animals were starved overnight could drink water. Intramuscular ketalar (mg/kg) was given as premedication followedpentobarbital and morphine which were givintravenously. Tracheostomy was performand the animals were anesthetized with isoran gas. Venous and arterial access lines westablished. A midline laparotomy enabled cess to the liver. The animals were sacrificedafter the last MRI scan using 3 M potassichloride intravenously. The research protowas approved by the Hospital Veterinary Ctrol Group.

Experimental Procedure

The pigs were placed in the image volumea 0.5 Tesla open GE Signa SP/i MR scan(GE, Milwaukee, WI). This scanner has a 60-vertical gap where both surgery and imagcan be conducted simultaneously. Two sepacryolesions were made in the upper frontal pof the liver using a 3.2-mm (diameter) MRcompatible cryoprobe. The probe reaches tperatures of 2180°C at the heat sink utilizinpressurized argon gas (300 Bar) and Joule–Thomson effect (CryoHit; Galil MedicaYokneam, Israel). At each location two freecycles of 20 min each were performed intvened by passive thawing (15 min). MR imaing was conducted prior to freezing and at end of each freeze cycle when steady state ditions had been reached (no further changelesion geometry). 3D Spoiled GRASS imagsequences were used with 2 or 3 mm slice thness. Scan duration was from 1.2 to 3.5 minpending on the phase matrix size, and the sparameters were TE 5 9 ms and TR 5 25. Im-ages were taken in the longitudinal plane of cryoprobe.

CRYOLESION TEMPE

MR Temperature Estimation

Temperatures were estimated by numerisolution of the simplified bioheat equation

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s inngick-de-can

the

described by Hong et al.(11) and applied by ourgroup before,

[1]

where K is thermal conductivity and T is tem-perature (see Appendix for theoretical discusion of this equation).

The initial conditions for solving this equatioare given by the phase transition front betwefrozen and unfrozen tissue and the temperatat the cryoprobe tip. The thermal conductivity the cryoprobe and the liver tissue are paramein the equation. The phase transition front is trieved from the MRI images at the end of thsecond freeze and the cryoprobe tip temperais given by the cryoprobe itself. Further detaof this model are given by Hong et al. andGilbert et al.(9, 11, 21).

In six cryolesions a fiber optic sensor thmonitors temperatures along the fiber wasserted at an arbitrary angle to the cryoprobe amean of validating the temperatures estimatedthe bioheat steady-state model (19). The accurof absolute temperature estimations was63°Cand is described elsewhere (23). The distancetween measured and the closest correspondestimated temperature was median 0.7 mm.

Volumes encompassed by a given isothewere found by summation of all voxel volumein the calculated 3D temperature map with esmated temperature equal to or below the teperature defined by the isotherm surface.

The shortest distance from any voxel withthe cryolesion volume to the phase transitifront was also calculated. The sizes of the dmatrices considered were sufficiently small allow for calculation of these distances by all-to-all calculation enabling identification othe true minimal distance from any lesion voxto the lesion edge. Combining the data in ttemperature and distance maps made it easstudy how voxels at or below a certain tempeture were positioned relative to the cryolesiedge. A binary erosion (12) in 6-connectivity

∇ ∇ =( ( , , ) ( , , )) ,K x y z T x y z 0

ATURE DISTRIBUTION 269

calas

the object defined by voxels at or below 240°Cprovided a closed surface (in 26-connectivity)and allowed us to study how voxels at the

ET

h

hiuuhig Dl iss

e

oish

edna-

eon un-

frozen tissue. The gray area represents cryolesion volume

270 MALA

240°C isotherm were positioned relative to tphase transition.

The geometry of the cryolesions was not tof a perfect sphere. To define cryolesion radto compare cryolesion size with that of previoreports, a straight line from the heatsink of tcryoprobe was made in one direction. The dtance from the heatsink to the cryolesion edwas recorded. This procedure was repeatedall possible line directions limited by the 3temperature map data matrix which was equathe MRI matrix size. The mean of these dtances was defined as mean cryolesion radiu

Statistics

Numbers are given as median and rangecept the distances from the 240°C isotherm sur-face to the cryolesion edge and the mean crysion radius, which were close to normal dtribution and are therefore given as mean. Tcorrelation coefficients in Fig. 2 were calculatusing Pearson’s correlation test. Data were a

la

inxt ae,e

le-to

e-nd

la-sis-on

oncal-gein-al

the

lyzed using SPSS 9.0 (Windows) and Mat6.0 (R12) by Mathworks.

RESULTS

Ten of the 12 cryolesions were eligible for clusion in this study. Two cryolesions were ecluded due to suboptimal imaging. The tocryolesion volumes produced by each probegiven in Table 1. Median cryolesion volumcolder than 220,240, and 260°C were 53, 26and 14% of the total cryolesion volume, resptively (Table 1).

To characterize the proportion of the cryosion colder than 240°C, the spatial configuration of the 240°C isotherm surface relative

the total cryolesion was analyzed further (s

aTotal cryolesion is defined as total cryolesion volume a

b

--

alre

s

c-

-

There was a statistically significant linear rlationship between the cryolesion volumes athe mean distance from the240°C isothermsurface to the cryolesion edge (Fig. 2; corretion r 5 0.88;P 5 0.001). Table 2 summarizecryolesion volume and the mean of the dtances calculated from each of the voxelsthe 240°C isotherm surface to the cryolesiedge. The median of these mean distancesculated for each cryolesion was 4.1 mm (ran2.5–5.2 mm) (Table 2) and increased bycreasing lesion volume (Fig. 2). The maximvalues of the distances calculated from

with temperatures below 240°C.

e

AL.

e

atsses-e

for

to-.

x-

le--e

FIG. 1. Illustration of a cryolesion: the “d” denotes thdistance from the 240°C isotherm surface to the cryolesiedge, i.e., phase transition front between frozen and

e240°C isotherm to the shortest cryolesionn

e

Fig. 1 for model). edge for each of the 10 cryolesions are show

TABLE 1Total Cryolesion Volumes and Cryolesion Volumes Colder Than 220,240, and 260°C.

Median cryolesion Range Percentage of RangVolume (cm3) volume (cm3) (cm3) total cryolesion (%)

Total cryolesiona (n 5 10) 12.3 6.4–24.4 100Temperature , 220°C (n 5 10) 6.5 4.0–12.4 53 46–84Temperature , 240°C (n 5 10) 3.2 2.0–5.2 26 21–50Temperature , 260°C (n 5 10) 1.7 1.0–2.8 14 9–27

fter the second freeze.

71

n gele-

chthe dis-

c

in Table 2. This maximal distance also icreased by increasing lesion volume (Fig.

tances calculated between the 240°C isotherm to thesion volume.

4.5s a

o

c

h

column.

-2;of these maximal distances was 8.1 mm (ran4.8–10.0 mm) (Table 2). In the largest cryosion the maximal distance was 10 mm.

The mean cryolesion radius was median 1mm (range 11.5–18.6 mm). Figure 3 show

ryolesion edge for each cryolesion relative to the cryole-

CRYOLESION TEMPERATURE DISTRIBUTION 2

FIG. 2. The largest of the calculated distances between the 240°C isotherm and the cryolesion edge for eacryolesion related to the volume of the cryolesion (upper curve). The lower curve shows the mean of all

temperature map superimposed on one of the

/4le

tionces

wasces.1

cese.ori-

correlationr 5 0.83,P 5 0.003). The median

TABLE 2Shortest Distance from Any Voxel on the 240°C Isothermto the Cryolesion Edge as Calculated for Each Cryolesi

Cryolesion volume Mean distance Maximal distan(cm3) (mm) (mm)

6.4 2.5 5.66.8 2.5 4.89.2 3.8 8.29.5 3.7 7.5

11.8 4.4 8.212.7 4.1 8.012.9 4.1 8.813.9 4.6 8.014.5 4.0 8.424.4 5.2 10.0

Note.The mean value of these distances is shown for eof the cryolesions in the second column. The largest ofdistances defined for each cryolesion is shown in the t

cryolesions.

DISCUSSION

This report demonstrates that only roughly 1of the cryolesion volume produced by a sing3.2-mm probe is colder than 240°C, the temper-ature assumed necessary for liver tumor abla(1, 6, 8, 16, 17). The mean value of the distancalculated between the 240°C isotherm and thecryolesion edge for each separate cryolesion median 4.1 mm and the largest of these distandefined for each cryo-lesion was median 8mm. Both the mean and the maximal distanincreased with increasing cryolesion volumThe largest distance defined between the tum

n

e

achtheird

cidal part of the cryolesion and the cryolesion

2

e

ely

ri

3a

re

oebsmin

in-saryererim

rgerres(1,ortnot

rs.imione

thenalc-d,m-

p ese0

edge demonstrates that in some regions of thsion this distance may be close to 1 cm. For mof the cryolesions examined, all with volumless than 25 cm3, a 1-cm rim zone would barebe sufficient to ensure temperatures of 240°C inthe entire target volume enclosed by the zone. A cryolesion volume of 25 cm3 corre-sponds to a spherical cryo-lesion diameter ofcm and a tumor diameter of 1.6 cm if 1 cm of parently normal liver tissue is to be includedthe lesion. For lesions larger than 25 cm3 the 1-cm rim zone is not likely to ensure temperatuadequate for ablation in the entire volume closed by the rim zone.

Although small in size, the radius of the crylesions in this report corresponds to that of prous and similar reports (13, 15, 29). The variaity of cryolesion volume may have been cauby differences in thickness of the liver lobes, nuber and size of nearby blood vessels, and m

FIG. 3. The isotherm temperature map superimrepresents isotherm surfaces of the cryolesion edg24

variations in penetration depth of the cryoprobeSimilar variations of cryolesion size have been rported in corresponding experiments (15).

le-osts

m

.6p-in

esn-

-vi-il-ed

-or

A 1-cm rim zone of normal hepatic tissue cluded in the cryolesion is assumed necesfor adequate tumor ablation (17, 19, 25). Thare several arguments for such a margin (i.e.,zone). One is that the cryolesion should be lathan the tumor itself to achieve temperatucold enough for lethal damage in the tumor 16, 17). However, as demonstrated in this repand by others (19) the 1-cm rim zone does seem to ensure temperatures of 240°C in thewhole tumor volume except for small tumoAnother argument for the use of the 1-cm rzone is the finding of occult intrahepatic invasidentified within 1 cm of the tumor edge. Thrim zone may be expected to correspond to1-cm free resection margin used in conventioresection of malignant liver tumors (i.e., “resetion margin”) (26). However, as demonstratethe cryolesion periphery does not contain teperatures assumed cold enough (240°C) for ab-

osed on a cryolesion. Starting from the periphery the lin,,280, and 2120°C, respectively.

72 MALA ET AL.

s.e-lation of malignant tissue in the 1-cm rim zone.To compare to the conventional resection marginthe 240°C isotherm should thus include the

v

l

y l

i

ithstns5

ia

oeeaa

fghz

la

ao

s

nnd,ig) beis-m-r-onr-

edetnhegerbei-n

c-

heal

f or---tedas

a-

ededtswla-r-o

CRYOLESION TEMPER

outer edge of the 1 cm of apparently normal litissue. A parallel to the resection margin usedconventional surgery is therefore not achievedthe 1-cm rim zone regularly used for cryoabtion of liver tumors.

These experimental data are supported btheoretical analysis of temperature distributiona spherical cryolesion (see Appendix for detaiThe empirical findings and the theoretical conserations mentioned in regard to the increasdistance between the assumed critical isotherm240°C and the cryolesion edge as a functioncryolesion size indicate that the 1-cm rim zoneinadequate for ensuring total tumor ablation.

The presented data are also reflected in clcal observations. Local recurrences atcryosite following cryotherapy of liver tumorhave been reported in 5–44% of patients trea(24, 25). In a study of 85 patients undergoihepatic cryotherapy for colorectal metastaselocal recurrence rate of 33% was reported (2Metastases larger than 3 cm were associawith shorter disease-free survival at the cryosthan smaller tumors. In the study freezing wcontinued until the iceball exceeded the tumby 1-cm. The present study indicates that maggressive freezing is necessary to ensure tperatures of240°C or colder throughout thwhole tumor volume. To achieve an additionsafety margin comparable to the resection mgin used in conventional surgery of liver tumors, i.e., placement of the240°C isotherm 1cm beyond the tumor borders, cryo-lesions cosiderably larger than those currently usedtumor ablation should be made. Although larcryolesions may be produced in the liver, tconsiderations mentioned limit the tumor sithat is suitable for ablation.

There are several limitations when extrapoing the experimental data to clinical situationFirst, during cryoablation multiple probes mbe used simultaneously and in such situatithe temperature profiles may be different (2The interaction between probes, however, is pendent on the cryoprobe setup and increa

the distances between the probes reduce thisteraction. Cryolesion temperatures may also influenced by the type of delivery system, th

ATURE DISTRIBUTION 273

er inbya-

ains).id-ng of

of is

ni-e

edga

).tedtes

orrem-

lr-

-

n-oreee

t-s.y

cryogen used (argon, liquid nitrogen, nitrogeoxide), and the cryoprobe size (8, 10). Secothe experiments were performed in normal (pliver. Tumor tissue has been demonstrated tomore resistant to freezing than normal liver tsue (2). Physical differences may influence teperature distribution within cryolesions of nomal and malignant tissue. This calls for cautiin extrapolating data from cryoablation of nomal liver tissue to malignant tissue.

The theoretical analysis of this report is bason a perfect location match between the targlesion and the cryolesion volume colder tha240°C. In clinical settings such a perfect matcis difficult or impossible to accomplish. To ensuradequate tumor ablation, therefore, lesions larthan estimated in ideal situations have tomade. The effect of relative reduction in tumoricdal volume as a function of increasing cryolesiosize is thus even more important in clinical pratice than in ideal situations.

MRI provides excellent monitoring of thecryosurgical process as illustrated in Fig. 3. Tcryolesion edge is clearly defined due to signvoid (T2) (9, 11, 18). 3D MRI estimation ocryolesion temperature and display of the tumwithin the area of signal void may further improve MRI monitoring of the cryoablative procedure. In our validation of 3D MRI temperature estimation the distance between estimaand measured temperature in a single point wfound to be median 0.7 mm in in vivopig livers(23). This provides relatively accurate estimtions of the distances between the 240°Cisotherm and the cryolesion edge.

In conclusion, this report demonstratesin vivo3D temperature profiles of cryolesions producby a 3.2-mm cryoprobe. Temperatures assumadequate for tumor ablation occur only in parof the cryolesion volume. If temperatures belo240°C are required to ensure total tumor ab

ns

1).de-ing

tion, the adequacy of the 1-cm rim zone of nomal liver tissue included in the cryolesion tprovide such temperatures is questioned.

in-bee

APPENDIX

If Eq. [1] is solved for a uniform sphericalgeometry with a central heat sink, the theoreti-

E

th

r

-r

e y

ury

K.ter-of

Ad

MRing

tice

e-.

e-

o-

274 MALA

cal solution as a function of a radius r from sphere center is (with spatially invariant thermconductivity)

[2]

Tc is the temperature of the heatsink and R thecryolesion radius. For a given isotherm the dius of this isotherm can be calculated as a fution of R:

[3]

Equation [3] is linear in R. The distance between the 240°C isotherm surface and the colesion edge is given by

[4]

Equation [4] demonstrates that the (theorcal) distance between the cryolesion volumesumed adequate for tumor destruction andcryolesion edge increases with increasing cr

R r T R R T T RT T R

iso iso c

iso c

− = − − =( ) ( / )( / )

1

r T R T T Riso iso c( ) ( / ), = −1

T r T r Rc( ) ( – / )= 1

nd

o

.

-

.

th

of

ct

n

F.,r-ot

ntal

r

sky,

P.,allithan

s

L.

M.3-

ide,t tis-ys-

lesion radius. The relative tumoricidal volumof a cryolesion, therefore, decreases with creasing cryolesion size.

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CRYOLESION TEMPERATURE DISTRIBUTION 275

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Appendix G Samset E., Talsma A., Kintel M., Elle O.J., Aurdal L., Hirschberg H., Fosse E.: “A virtual environment for navigating and controlling intraoperative magnetic resonance images” Published in: Journal for Computer Aided Surgery; 2002: 7(4):187-96