WHY QIBA: PET-CT SPECIFICSqibawiki.rsna.org/images/0/08/Why_QIBA_PET-CT_specifics.pdf ·...

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PRINCIPAL LOGISTICAL AND

FINANCIAL SUPPORT

PROVIDED BY RSNA

WHY QIBA: PET-CT SPECIFICS

Corporation Visit

Autumn 2010

Andrew J. Buckler, MS

Program Director, QIBA

Our Team

Autumn 2010 Why QIBA: PET-CT Specifics 2

AmgenAstraZenecaBeth Israel Deaconess Medical CenterBioClinicaBoston Medical CenterBrown UniversityBuckler Biomedical LLCCancer Imaging Program, NCICCS Associates, Inc.Duke UniversityFDAFraunhofer MEVIS, Inst for Medical Image ComputingGE HealthcareGlaxoSmithKlineHarvard Medical SchoolICON Medical ImagingImagepaceIndiana UniversityJohns Hopkins UniversityKing's College LondonMedical Imaging & Technology AllianceMerge HealthcareMIMvista Corp.NIST

NovartisPerceptive Informatics, Inc.PfizerPharmtracePhilips HealthcareRadPharmSegami CorporationSiemensSNMState University of New YorkTeraRecon, Inc.University of California, BerkeleyUniversity of California, DavisUniversity of California, San FranciscoUniversity of Colorado, DenverUniversity of IowaUniversity of MichiganUniversity of UtahUniversity of WashingtonVital Images, Inc.VU Medical Center, Amsterdam, NLWashington University in St. LouisWeill Cornell Medical CollegeWm. Beaumont Hospital

See speaker notes for full list of individual

names

Presenter

Presentation Notes

Ramsey D. Badawi, PhD University of California, Davis Prashant Bansal, MS Beth Israel Deaconess Medical Center Nikhil Bhushan, MBA, MS Vital Images, Inc. Ronald Boellaard, PhD VU Medical Center, Amsterdam, NL John Buatti, MD University of Iowa Andrew J. Buckler, MS Buckler Biomedical LLC Janice Campbell, PhD Wm. Beaumont Hospital Sabin Carme, PhD GlaxoSmithKline Michael E. Casey, PhD Siemens Sung Chang, PhD Amgen Sandra Chica, MD Novartis Paul E. Christian University of Utah David A. Clunie, MBBS RadPharm Patricia E. Cole, PhD, MD Imagepace James J. Conklin, MD, MS ICON Medical Imaging Shiva K. Das, PhD Duke University Simon DeBruin, MSEE Segami Corporation Todd Deckard, MSEE Vital Images, Inc. Jon DeVries, MBA Merge Healthcare Gary S. Dorfman, MD Weill Cornell Medical College Richard Eaton, JD Medical Imaging & Technology Alliance Richard A. Frank, MD, PhD, FFPM GE Healthcare Constantine Gatsonis, PhD Brown University Igor D. Grachev, MD, PhD GE Healthcare Leo J. Grady, PhD Siemens Michael Graham, MD, PhD University of Iowa Donald P. Harrington, MD, MA State University of New York Markus T. Harz, PhD Fraunhofer MEVIS, Inst for Medical Image Computing Howard Higley, PhD CCS Associates, Inc. Otto Hoekstra, MD, PhD VU Medical Center, Amsterdam, NL John M. Hoffman, MD University of Utah Yuying C. Hwang, PhD Amgen William Jagust, MD University of California, Berkeley Lisa R. Karam, PhD Ionizing Radiation Division, NIST Gary J. Kelloff, MD Cancer Imaging Program, NCI Paul E. Kinahan, PhD University of Washington Robert Koeppe, PhD University of Michigan Steve Kohlmyer GE Healthcare Feng-Ming (Spring) Kong, MD, PhD University of Michigan Marianne Maffoni TeraRecon, Inc. Piotr Maniawski Philips Healthcare Paul Marsden, MD King's College London Timothy J. McCarthy, PhD Pfizer Alexander (Sandy) McEwan, MB SNM Matthew P. Miller, PhD GE Healthcare Michael A. Miller, PhD Indiana University David Miller, PhD University of Colorado, Denver Colin G. Miller, PhD BioClinica Sarah J. Nelson, PhD University of California, San Francisco Dennis Nelson, PhD MIMvista Corp. Chuck Nortmann Philips Healthcare Eric S. Perlman, MD RadPharm Andrea Perrone, MD BioClinica Wolf S. Richter Pharmtrace Yuanxin Rong MD, MPH Perceptive Informatics, Inc. Ling X. Shao, PhD Philips Healthcare Barry A. Siegel, MD Washington University in St. Louis Rathan Subramaniam, MD, PhD Boston Medical Center Daniel C. Sullivan, MD Duke University Valerie Treyer, PhD ICON Medical Imaging Timothy G. Turkington, PhD Duke University Richard L. Wahl, MD, FACR Johns Hopkins University Scott D Wollenweber, PhD GE Healthcare John G. Wolodzko, PhD RadPharm Jeffrey T. Yap, PhD Harvard Brenda Ye, MD FDA Helen Young, PhD (Co-Chair) AstraZeneca T. C. Zhao, PhD TeraRecon, Inc. Brian E. Zimmerman, PhD Physics Lab, NIST

PET-CT: A Proud History of Innovation


1953

First coincidence positron imaging system

1975

PETT III

1989

whole-body imaging

1991

3D PET

1998

PET/CT

2005

respiratory gating

2006

time-of-flight

2008

PET/MR?

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

1998 2000 2002 2004 2006 2008

Pro

cedu

res/

yr

0%

20%

40%

60%

80%

100%

% s

cann

ers

Procedures/yr

PET/CT % ofSales

What’s next? Quantitative PET to Characterize Disease Hallmarks


• Clinical research, Clinical trials, and Drug discovery

• New molecular diagnostic agents

• Assessing individual response to therapy

• SUVs are now routinely reported, and are asked for, by referring physicians

Castell and Cook, British J Cancer 2008

Pre-therapy

1 wk imatinib therapy

CT PET/CT

PET SUV:5 to 1.8

Response to therapy of liver met GISTDrivers

volume

Biomarkers To Quantify Hallmarks of Cancer

glucose metabolism

Biologic

Target

bone formation

proliferation

hypoxia

amino acid metabolism

angiogenesis

receptor status apotosis

18F-FDG18F-NaF

18F-FLT18F-

FACBC

18F-FMISO

18F-XXX

18F-YYY

18F-FES

• New molecular diagnostic agents

• New uses for existing agents

Autumn 2010 5Why QIBA: PET-CT Specifics

Treatment Population 2007 2008 2009 2010 2011 2012 2013 2014 2015

Cancer patients treated with Anti-angiogenesis treatment

2.8% 3.4% 4.4% 5.3% 6.7% 8.1% 9.5% 10.3% 11.6%

Assist with increasing number of oncology targeted pharmaceuticals

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

IPILIMUMAB(MDX 010)

DENOSUMAB(AMG 162)

AVASTIN(bevacizumab) RECENTIN

(cediranib)

SUTENT(sunitinib)

NEXAVAR(sorafenib) RAMUCIRUMAB

(IMC 1121b)

TORISEL(temsirolimus)

CILENGITIDE

AFILBERCEPT

BRIVANIB

AXITINIB

ZACTIMA

XL-184

MOTESANIB

AFINITOR(everolimus,RAD001)

VOTRIENT(Pazopanib)

Courtesy Richard Frank, GE Healthcare


num

ber

of m

easu

rem

ents

nee

ded

increasing measurement error means:• slower accrual of data for approval• less reliable for patients

10%20%

30%40% Doot et al JNM 2009

∆SUV < 0

∆SUV ≥ 0

Nahmias JNM 2007

Improve individual patient care

• Clinically proven detection and longitudinal quantitation for follow-up

• Moves imaging from diagnostics and staging to therapy assessment

Accelerate adoption of new molecular diagnostics

Make clinical trials of new therapies more effective

All tied to quantitative accuracy

Quantitation Improves Characterization of Disease Hallmarks


Technical as well as Business Obstacles Impede Realization of the Opportunity


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

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.

Developm’t

Assay validation

cost

time

Endpoint qualification

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

Measured values for 10 different PET centers

Incorrect calibration Correct calibration

Kinahan JNM 2007

Lockhart JNM 2009

QIBA Addresses the Obstacles, Enabling Profitable New Products

Widely Available, High Performance, Quantitative Imaging

Result:

Imaging Science, Metrology, and Biostatistics

Mak

e it

actio

nabl

e fo

r en

gine

erin

g an

d R&

D,

addr

essi

ng b

oth

desi

gn a

nd u

se

Mak

e it

fam

iliar

to m

arke

ting

and

give

them

a p

rodu

ct, n

ot

just

a c

ost

Prov

ide

a re

gula

tory

pat

hway

th

at w

orks

in th

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sine

ss

mod

elJune 2010 Buckler Biomedical LLC 9Autumn 2010 9Why QIBA: PET-CT Specifics

QIBA Profile Content


Claims:“Detect tumor response with twice the sensitivity of RECIST in the Lung”

nodules > 1cm …

Actors TableCT Acquisition SystemMeasurement SoftwareRadiologist…

Activity DefinitionsCalibration / QA Patient PreparationImage AcquisitionReconstructionPost-Processing Analysis / Measurement Reading / Interpretation…

User Perspective

Will it do what I need?

What/who do I need

to get started?

What do I have to do

(procedures, training,

performance targets)

to achieve the Claims?

Vendor View

Why do you want me to do this?

Which of my products

are affected?

What do I have to implement;

(features, capabilities,

performance targets)

How will I be tested?

Details:

QIBA “Industrializes” QI


Select a Biomarker

AcademicResearch

ClinicalTrial Use

ClinicalPractice

DraftQIBA Profile

Coordinate Groundwork

Draft Protocol

ValidateEquipment

& Sites

• Identify significant sources of variance• Estimate achievable repeatability and accuracy • Validate underlying assumptions and mechanisms• Determine details critical to specify in the Profile

• Document the agreed parameters and procedures• Converge practice; reduce gratuitous variation• Initiate regulatory engagement

• Specify details necessary to be robust in general use• Drive out any impeding variance and complexity• Make details stable, clear, implementable, testable

• Test compliance with QIBA Profile specifications• Publish validated products/sites

• Apply selection criteria:−Transformational, Translational, Feasible, Practical

QIBA is an Active Sponsor in Regulatory Pathways that Leverage Collaboration


Quantitative Imaging Test Approval[National regulatory agencies, e.g., FDA CDRH]

Evidentiary Studies for Coverage Decisions

[Payer organizations, e.g., CMS]

Quantitative Imaging Biomarker Qualification

[National regulatory agencies, e.g., FDA CDER]

Feedback path to provide evidence to extend initial intended use for new, stronger, clinical claim

Initial intended use now extended to stronger association with mechanism-of-action or surrogacy

Intended use (usually initially having no claim of surrogacy but which could be extended if further

clinical data could be collected)

Reimbursable based on accumulated evidence of necessary and reasonable use

Quantitative Imaging Test Discovery, Development, and Validation[Private & Academic Sectors]

Use in Routine Clinical Care

Use in Clinical Research

Path when use is established in clinical trials first (though feedback path would allow its use in clinic later)

Path when clinical use is pursued first (though can proceed to qualification later)

Quantitative Imaging Test Approval[National regulatory agencies, e.g.,

FDA CDRH]




Quantitative Imaging Biomarker Qualification



Use in Drug Development

1

2

36

5

4

FDG-PET Example

Example Drill Down: How Pathways may be Applied to Quantitative FDG-PET


1. Vendors have developed and continue to refine FDG-related products (hardware, software, agent.

2. Products have been approved by CDRH using the approval pathway, and— based partly on data from the National Oncologic PET Registry (NOPR) --they are reimbursed for clinical care, but only for disease stratification and diagnosis, not in quantitative applications for therapy monitoring.

3. A sponsoring collaborative would qualify the class of devices for clinical research applications by following the qualification pathway.

4. Data collected during the qualification activity, substantiating performance as a response measure, could be referenced by vendors to add therapy monitoring (and thereby expand their market) as a new indicated use (claim). This would be done by establishing compliance with the class by referencing data collected as part of the qualification pathway in the validation pathway.

5. These “qualification data” would be available to be contributory as evidence for individual device sponsors as they re-register their products (if they are already a compliant implementation) or re-engineer them (to become compliant).

6. Payers could extend coverage decisions to include therapy monitoring as an additional code for reimbursement.

7. Subsequently, the intended use claims may be extended to additional settings (e.g., tumor types or subtypes) and/or for different therapeutic approaches (e.g., cytotoxic vs. targeted, etc.).

Quantitative Imaging Test Approval[National regulatory agencies, e.g.,

FDA CDRH]




Quantitative Imaging Test Qualification



Use in Drug Development

1

2

3

5

4

FMISO-PET Example

Example Drill Down: How Pathways may be Applied to Advance Newer Tracers


1. Vendors develop and refine FMISO imaging methods for hypoxia.

2. The first application might be in clinical trials and not clinical care, so qualification would precede approval to market.

3. The qualification data may be used by vendors if they also intend to sell a product for clinical care to efficiently seek approval from CDRH.

4. Ultimately, payers might make decisions based on already-collected qualification data, or with additional collection using a model similar to that used by the National Oncologic PET Registry.

QIBA PROFILE

I. CLINICAL CONTEXT

II. CLAIMS

III. DETAILS

IV. COMPLIANCE

V. ACKNOWLEDGEMENTS

QIBA GROUNDWORK for ANALYZING/CREATING DATA

to INFORM PROFILES

Reports and Data Sets Analyzing:

• Technical characteristics and sources of errors

• Stand-alone performance on phantoms and synthetic data

• Clinical performance in terms of intra- and inter-reader variability

• Clinical efficacy• Standardization across

scanners


PRODUCT CREATION PROCESS of DEVICE and SOFTWARE

MANUFACTURERS

Customer Requirements Specification

System Requirements Specification

Verification Plan and Protocol

Participation and visibility for all stakeholders

QIBA Leverages Resources and Bridges Perspectives Across Communities

QIBA PROFILE

I. CLINICAL CONTEXT

II. CLAIMS

III. DETAILS

IV. COMPLIANCE

V. ACKNOWLEDGEMENTS

QIBA GROUNDWORK for ANALYZING/CREATING DATA

to INFORM PROFILES

Reports and Data Sets Analyzing:

• Technical characteristics and sources of errors

• Stand-alone performance on phantoms and synthetic data

• Clinical performance in terms of intra- and inter-reader variability

• Clinical efficacy• Standardization across

scanners


PRODUCT CREATION PROCESS of DEVICE and SOFTWARE

MANUFACTURERS

Customer Requirements Specification

System Requirements Specification

Verification Plan and Protocol

Participation and visibility for all stakeholders

Our Offer – and our Request – is to Increase your Engagement with Us

•Collate existing knowledge on aggregate technical performance:

• Identify common gaps•Evaluate methods for

quantitative standards and tools (e.g., PERCIST)

Use Profiles to create QIBA-

compliant product

Assign company resources to join committees for

writing/reviewing Profiles

To be specific, for FDG-PET now and newer tracers soon, we are requesting:• Assist with collaborative groundwork activities:

– Participate in experimental studies for characterizing performance.

– Review requests and provide feedback on standardizing acquisition system characteristics.

• Apply engineering resources to help refine QIBA profiles:– Assist with the engineering analysis being performed to arrive at

requirement levels and functional specifications.

– Assist with the writing of QIBA profile claims.

• Prepare for future product development and marketing:– Review QIBA profiles and current product performance claims.

– Perform QIBA studies and internally validate QIBA compliance.

– Obtain approval to claim QIBA compliance.


June 2010 Buckler Biomedical LLC 18

We can’t do it alone, you can’t do it alone. We need to do it together.


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

• Technical as well as business obstacles impede commercialization.

• QIBA addresses these obstacles, accounting for individual stakeholder value propositions.

• The commercialization model is similar to IHE, including relationship to product creation process.

• Collaborative resources in precompetitive model address the science and provide critical mass as well as cost sharing for regulatory data collection.

• We invite you to join us in making the critical step of defining Profiles.

• New products compliant with the outputs of this process will fuel a virtuous cycle of innovation in this next generation of imaging, rewarding all participants.

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