Why QIBA: CT Specifics

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PRINCIPAL LOGISTICAL AND

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PROVIDED BY RSNA

WHY QIBA: CT SPECIFICS

Corporation VisitAutumn 2010

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In a poll of 225 top general internists, CT and MRI were judged to be the most important medical advances in the last 50 years, beating out life-saving therapies such as coronary angioplasty and ACE inhibitors.

Fuchs VR, Sox HC Jr. Physicians' views of the relative importance of thirty medical innovations. Health Aff, 2001. 20(5): p. 30-42.

Image courtesy of Toshiba

Autumn 2010 Why QIBA: CT Specifics 2

The Long and Proud History of Innovation of CT• 1972: Prototype CT

– Several hrs per slice acquisition; days for reconstruction• 1974: 1st Generation CT

– 2.5 min/slice• 1976: Whole-body CT

– 5 sec/slice• 1989: Helical/Spiral CT

– 0.3 sec/slice; 40 sec for entire chest (40cm Z-axis)• 1998: 4-row MDCT

– 10 sec for entire chest• 2002: 16-row MDCT

– 8 sec for entire chest• 2004: 64-row MDCT

– 5 sec for entire chest• 20010 and beyond: ?


Image courtesy of Siemens

Since 2004: Spatial Resolution up to 2x higher

HDCTNon HDCT

3mm Stent

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Autumn 2010 4Why QIBA: CT Specifics

Low Temporal ResolutionLow Temporal Resolution High Temporal ResolutionHigh Temporal Resolution

Temporal resolution over 2x faster


Stair-step Artifacts up to 80% Less

Images courtesy of Toshiba

Narrow Volume – 64 detector row CT Wide Volume – 320 detector row CT


Image Noise up to 50% Less

Conventional Reconstruction HD Reconstruction

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60 mAs60 mAs


Radiation Dose Reduction(one example of many promising approaches)


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Multi-energy and Spectral CTTowards resolving multiple energies and materials

34 keV 51 keV Iodine (green) + Gd (red)

• Automatic separation of iodine contrast and bone in a mouse

Schlomka et al. Phys Med Biol (2008).


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Quantitative CT Imaging• The HU has always been “quantitative”, • Technical Advances will help us move from

“qualitative image” to “quantitative image” or measurement


– Longitudinal quantification used to assess patient response to therapy

Picture Slide to Demonstrate Effects of Technology Advancement• (Jim Mulshine’s suggestion of Reeves slides here)• Lung lesion with

– 10 mm thick images– 5 mm thick images– 2.5 mm thick images– 1 mm thick images

• Volumetric representation of each– Showing how blurry and “artifacty”the 10 mm based

image is and how clear the 1mm is.


Movement to Quantitative Imaging• Series of 3 or 4 slides (primarily with pictures)

showing:– Simple phantom lesion (from 1A?) measured twice

(either same reader twice or two readers)– Complex phantom lesion measured twice

• Show diameters• Show volumetric contours

– Simple patient lesion (1B) measured twice– Complex patient lesion (1B) measured twice


Use a better example, but ~ like this


lesion Reader 1 contour(includes sliver)

Reader 2 contour(excludes sliver)

Even with Exquisite images, still uncertainty about what is and isn’t part of a lesion.This leads to uncertainty in measurements, even with experts.

Structural Issues Currently Impede Realization of the Opportunity

Efforts by individual manufacturers to qualify quantitative imaging applications:•Are more costly, and•Run over longer time periods…

…than the business model of device and software manufacturers generally support. Develop

ment

Assay validation

cost

time

Endpoint qualification

Even when individual companies do these steps, community need for standards required to address multi-vendor reproducibility are not accounted for.

These issues are exacerbated by lack of clarity in regulatory and reimbursement policy which increase the risk while decreasing the incentive

June 2010 Buckler Biomedical LLC 14Autumn 2010 14Why QIBA: CT Specifics

What we need to Meet the Opportunity• Need domain experts:

• Problem assessment: which problem could be solved by image analysis algorithms• Usability: are the developed algorithms user friendly and really useful for the experts• Feedback from opinion leaders• Market opportunities

• Have to evaluate their hardware/software:– Standardized image database with annotations– Definitions of standards– Evaluation:

• Phantom data • Clinical trials • Clinical studies• First users (domain expert)

– Cooperation with hardware vendors, because:• DICOM and other standards• Different vendors / Different image data quality• Interfaces with the hardware of different hardware vendors• Different vendors /Different image data acquisition filters• Different Vendors / Different data representation algorithms and hardware (screen)

• Negotiations etc. with Regulatory (compliance FDA and other international regulatory)

Don’t Do ItDon’t Do It

Accept Lower Utilization and

Reimbursement

Do it IndividuallyDo it Individually

Accept Higher Costs and Lower

Reproducibility

Lowest utilization and reimbursement

Localized utilization and reimbursement

Do it TogetherDo it Together

Seek the Win-Win Structure that

Rewards Participants

Highest utilization and reimbursement


We Have Three Choices

The Need

• Need the appropriate Networks (Groups) in order to achieve the previous goals– Because of the

• power of cooperation• Exchange experience • Exchange knowledge• Work with the regulatory (like FDA…)• State of the art knowledge• Etc.

Widely Available, High Performance, Quantitative Imaging

Result:

Imaging Science, Metrology, and Biostatistics


How We Will Succeed

Ground work

Profile Claims

Clinical Context

Profile Details

With an IHE-likecertificationreputation


QIBA Overcomes Obstacles to Enable the Opportunity

Profiles are actionable for both Marketing and R&D

QIBA PROFILE

I. CLINICAL CONTEXT II. CLAIMS III. PROFILE DETAILS IV. COMPLIANCE SECTION V. ACKNOWLEDGEMENTS

PRODUCT CREATION PROCESS (PCP)

Customer Requirements

Specification (CRS)

Customer Requirements

Specification (CRS)

System Requirements

Specification (SRS)

System Requirements

Specification (SRS)

Verification Plan and Protocol

Verification Plan and Protocol

Participation and visibility


Example: Lung CancerMake drug development more efective:• Faster (Window trials—quantitative

endpoint);Cheaper (Adaptive Bayesian Design, two to three weeks of drug exposure);Better (Phantom calibration, standardize method, open source reference tools, defined molecular targets, tailored delivery systems)

• Tighter (variance), lighter (dose), standardized (protocol/profile)

Make care more personalized to patient:• Clinically proven detection and

longitudinal quantification• Quantitiative CT measures incorporated

into adaptive therapy / monitoring


Example: Emphysema and COPD• Chronic obstructive pulmonary disease

(COPD) is a progressive lung disease which include emphysema, chronic bronchitis, refractory (irreversible) asthma, and severe bronchiectasis.

• 12 million adults have COPD, and another 12 million are undiagnosed or developing COPD. It is the fourth leading cause of death in the U.S., accounting for 126,129 deaths in 2003.

• COPD does not have a cure, but treatments are currently available to help individuals manage their symptoms of COPD


Utility of CT evaluation of COPD• A. Dirksen et al., "A randomized clinical trial of alpha(1)-antitrypsin

augmentation therapy," Am J Respir Crit Care Med 160, 1468-1472 (1999).

– “We conclude that lung density measurements by CT may facilitate future randomized clinical trials of investigational drugs for a disease in which little progress in therapy has been made in the past 30 yr.”

• In 2009: ”…CT is a more sensitive outcome measure of emphysema-modifying therapy than physiology and health status, and demonstrates a trend of treatment benefit from alpha(1)-AT augmentation.”

• Present limitations of CT evaluation of emphysema:

– Density measurements vary because level of inspiration varies.

– There are inconsistencies between lung density measurements made using different vendor scanners, particularly using contemporary scanners.

– May be associated with differences in CT number scale.

Profile “Target”

Protocol

Profile “Ideal”


QIBA: Active in Several Aspects

QIBA PROFILE


Analyzing/Creating Data to Inform Profiles

QIBA Experiments and GroundworkQIBA Experiments and Groundwork


Analyzing:Effects of Measurement Methods

• 1D, 2D, 3D•Effects of Slice thickness

• Phantoms•Apply to Patient Images

• e.g. Coffee Break Experiment• Standardization across scanners

Analyzing:Effects of Measurement Methods

• 1D, 2D, 3D•Effects of Slice thickness

• Phantoms•Apply to Patient Images

• e.g. Coffee Break Experiment• Standardization across scanners

QIBA: Active in Several Aspects

QIBA PROFILE


UPICT Profiles (Target Concept)


Acceptable

Target

Ideal

Determining Which Parameters (Slice Thickness, Recon Algorithm, etc.) Affect Measurement Variability

<to be fed into profiles>Requests from John Boone:1. It was agreed that each vendor would work together with others to come up with a reconstruction kernel which would deliver

consistent spatial resolution (in three dimensions) between scanners. After discussion it was also concluded that the slice thickness should not be at the limit of resolution, but perhaps in the 1.0 to 1.5 mm slice thickness range. Mike and I felt that to some extent this is less of an exercise in developing a new kernel and more just finding which existing kernels match the best, but perhaps some kernel tweaking would be in order. Ultimately this is an exercise in matching MTF(x,y,z) between scanners.

2. we talked about 1024 x 1024 reconstruction, but that was determined to not be feasible, and so that request was dropped. 3. we also talked about HU accuracy - and I believe that all vendors seek to have quantitatively meaningful and accurate HU values,

but with the ever widening collimators this becomes harder to deliver due to scatter. Given that this is already a desire of all manufacturers, we dropped this as a specific request.

“Wish list” items from PET that also apply to CT• Software Version Tracking Use enhanced DICOM attributes to follow version number of software for 1 Acqusition, 2

Reconstruction, 3 post-processing, 4 Display/VOI analysis, 5 Dynamic Analysis Build list (on console) of dates of all s/w versions • QA/QC Tracking CT: Daily water equivalent phantom values tracked in DICOM header PET: Daily/weekly/monthly scanner QA

values included in DICOM header PET: Daily (or frequent) uniform cylinder analysis, with link to results in patient DICOM header Dose calibrator is calibrated for F-18 using NIST-traceable source with information included in patient DICOM header

• Covariates Wieght - allow disabling of auto wieght import from HIS/RIS Hieght - required field All needed information for Injected activity (e.g. residual activity, injection time) is required Scanner performs all decay corrections (not the operator) Blood glucose (from CLIA compliant device) at time of injection is recorded with DICOM patient information All scanner times should be synchronized to NTP Patient meta-data recorded, e.g. using enhanced DICOM attributes Diplays should have ability to show information that effects SUVs (uptake time, etc.)

• Quantitative Reporting Include reference tissue value (e.g. 3 cm diameter VOI in liver) Populate reports from DICOM header information Mechanism for flagging artifacts (motion, extravasation, etc.)


<groundwork projects where we need vendor help>• Maybe use the process map from qualification

with pointers to areas of vendor involvement (but showing the whole thing for context)


Image Archives


June 2010 Buckler Biomedical LLC 29

Where We Are NowComplete Consultative Phase leading to Qualification of VIA

with chest CT for Lung Cancer Clinical TrialsScope of

Work Confidence of Achiving

Other group alredy doing it

Overlap of worh other

group

Ower/Driver

Target date/Status Action/Comments

Compose letter and review Low High 0% Paul Q2-10

Send letter

Follow-up through BQRT meeting Medium High 40% Paul

A

Assemble Declaratory information High Low UPICT, CTN 30% Andy Q4-10

Write Clinical Context section in Briefing Document

Write literature review sections in Briefing Document

Write QIBA process section in Briefing Document

B<phantom task 1> Low High 0% Paul Q2-10

…

<phantom task n, e.g., write section in Briefing Document> Medium High 40% Paul

C

<Profile task 1, e.g., UPICT consensus protocol> Low

… (e.g., create non-protocol portions of Profile) Low

… (e.g., add QIBA subcommittee findings)

<Profile task n, e.g., write section in Briefing Document> High High 100%

D<process map task 1, e.g., determine what steps are needed> Medium Low 60%

…

<process map task n, e.g., write section in Briefing Document> Low Med 40%

E<clinical performance task 1, e.g., summary of what's ongoing> Medium Low 60%

… (e.g., compile performance evaluation figures of merit)

<clinical performance task n> Low Med 40%

Write Results section of Briefing Document Medium Low 60% Write Completing the Full Data Package section Review Briefing Document Send to agency Participate in BQRT

Iterate with BQRT Low Med 40%


What we can do together• With QIBA in order to achieve their goals concerning VIA:

– Workout the advantages of VIA concerning: • Diagnosis• Prognosis• Therapy decision• Therapy success, effect and efficacy, change

In General Context and especially in the Context of

Theranostics = Diagnostics + Therapywhich is a “Strategy requires teamwork, partnering, and tricky regulatorymaneuvering”, The Scientist 2004, 18(16):38, Published 30 August 2004

– Definition and acceptance of Volumetric Changes based on VIA as a standard BIOMARKER for Volumetric CT

June 2010 Buckler Biomedical LLC 31

Conclusions


• Utilization of imaging grows as it is used in therapy for predicting and monitoring response.

• Despite enormous progress and technological possibilities, deployment of quantitative imaging applications has not kept pace.

• Increased use requires established interpretation and proof of performance.

• Working together according to the QIBA process overcomes structural hurdles and offers a way forward.

• The process draws from the IHE precedent but is built on imaging science. Flows and activities are defined to account for individual stakeholder value propositions.

• New products based on this approach would fuel a virtuous cycle of innovation with reward to participants.

Acknowledgements

• CT team (all of us)• Daniel Rubin• Matthew Cham• Images provided by:

– General Electric– Philips– Siemens– Toshiba


Documents

Why QIBA: CT Specifics