COMPUTER AIDED DIAGNOSIS IN CHESTRADIOGRAPHY

Grant Number: 5R01CA062625-08PI Name: Doi, Kunio

Abstract: Description (Adapted from Applicant’s Abstract):The applicants proposed to develop computer-aided diagnos-tic (CAD) schemes for detection and characterization of pul-monary nodules in digital chest images. For development ofreliable and predictable CAD schemes, they proposed to es-tablish a large database with 2,000 cases of chest radio-graphs, which include 1,000 nodule cases and 1,000 non-nodule cases, in collaboration with Richard M. Slone, M.D.,Mallinckrodt Institute of Radiology, Washington University,under a consortium arrangement. An advanced CAD schemefor detection of lung nodules will be developed by incorpo-rating three subtraction techniques–temporal subtraction, con-tralateral subtraction and energy subtraction–in order toachieve, on average, a high sensitivity of 80-90% with a lowfalse positive rate of approximately 0.5 per chest image.They would investigate the usefulness of the temporal sub-traction technique in increasing the detection of subtle nod-ules overlapped with ribs and also decreasing the number offalse positives due to rib-crossings, when a previous chestimage of the same patient is available. Contralateral subtrac-tion, which is a novel technique for removal of peripheralribs in a single PA chest image, will be examined for en-hancement in the detection of overlapped nodules and reduc-tion in the number of false positives. They would also inves-tigate the usefulness of energy subtraction soft-tissue imagefor improved computerized detection of lung nodules incombination with conventional chest images. In addition tothe detection task, they would to develop CAD schemes forcharacterization of nodules in order to distinguish betweenbenign and malignant nodules. This characterization task isto provide the likelihood of malignance of lung nodulesbased on quantitative analysis of image features of nodulesdetected by computer and/or by radiologists. With the highlevel of detection performance that they expect to achieve,they propose to develop a prototype CAD workstation andcarry out a pilot study to examine the clinical usefulness ofCAD schemes on detection and characterization of pulmo-nary nodules.

Thesaurus Terms: artificial intelligence, computer-assisteddiagnosis, computer system design/evaluation, diagnosis de-sign/evaluation, lung neoplasm, neoplasm/cancer radiodiag-nosis, noninvasive diagnosis, pneumoradiography computerhuman interaction, digital imaging, disease/disorder classifi-cation, image processing, information system bioimaging/biomedical imaging, human data

Institution: University Of Chicago5801 S Ellis AveChicago, IL 60637

Fiscal Year: 2002Department: RadiologyProject Start: 10-May-1995Project End: 28-Feb-2005ICD: National Cancer InstituteIRG: ZRG1

IMRI/SPECT GUIDED PROSTATE CANCERBIOPSY AND THERAPY

Grant Number: 5R33CA088144-03PI Name: Duerk, Jeffrey L.

Abstract: Description: (Applicant’s Description) While ade-nocarcinoma of the prostate is the most commonly diagnosedcancer in American men and the second leading cause ofcancer mortality, technologic and engineering advances havenot pushed diagnosis or treatment methods forward whencompared to, for example, brain cancers. The objective ofthis research and development project is to create a method-ology suitable for spatially accurate image-guided diagnosisand treatment of prostate cancer. Our method is basedaround the newly emerging techniques in interventional MRI(IMRI) and nuclear imaging, including image registration,image guided biopsy, and direct monitoring of thermal ther-apy. To test our methodology, we will perform careful vali-dation testing in an experimental animal model to justifyfuture clinical trials and clinical evaluation in patients. Spe-cifically, we will acquire MRI volume scans of the pelvisand register these images with nuclear scans that providemetabolic/monoclonal indicators of disease. This first regis-tration will semi-automatically combine image data sets withmarkedly different spatial, contrast and SNR characteristics.During guidance to the prostate lesion, we will compare newrapid MRI techniques with improved immunity to motion toexisting methods, and we will complete development andvalidation of two methods for IMRI navigation where thetarget tissue and the interventional device are ensured to re-main in the scan plane. Two methods shown to be feasiblefor IMRl guided procedures will be integrated with regis-tered data sets to provide both scan planes which alwaysinclude the interventional tool and the target tissue and abest estimate of the registered data at the same orientation toimprove accuracy of placement of the tools into the mostappropriate tissue location. Guidance accuracy will be vali-dated. Image registration methods during guidance will pro-vide accurate automated multi-modality resolution betweenthe new rapidly acquired data and previously registered nu-clear and MRI data as a method to improve targeted biopsyand treatment. We will develop new methods to visualizeinformation, like the interventional tool trajectory and tissuetemperature and validate their accuracy. We will use phan-toms when possible, but more importantly, we will create acanine model to provide comparable tissue deformation, per-

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fusion, morphology and organ and physiologic motion ex-pected in human trials. Finally, we will validate accuracy ofboth our image-guided biopsy and image-guided minimallyinvasive treatment under realistic conditions.

Thesaurus Terms: biopsy, magnetic resonance imaging,neoplasm/cancer thermotherapy, nonhuman therapy evalua-tion, prostate neoplasm, single photon emission computedtomography phantom model bioimaging/biomedical imaging,dog

Institution: Case Western Reserve University10900 Euclid AveCleveland, OH 44106

Fiscal Year: 2002Department: RadiologyProject Start: 14-Sep-2000Project End: 31-Aug-2003ICD: National Cancer InstituteIRG: ZCA1

Academic Radiology, Vol 10, No 8, August 2003 ABSTRACTS OF NIH GRANTS

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