The Quantitative Imaging Network (QIN) Robert Nordstrom, Ph.D. Larry Clarke, Ph.D.
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Transcript of The Quantitative Imaging Network (QIN) Robert Nordstrom, Ph.D. Larry Clarke, Ph.D.
QIN: A CIP/RRP Initiative
• Quantitative Imaging for Evaluation of Response to Cancer Therapies U01:– Quantitative Imaging Network (QIN)
• Support multi-disciplinary research teams to develop quantitative imaging methods to measure response to therapy.
• Optimization and validation of data collection & analysis methods in ongoing clinical trials.
• Commercial imaging platforms.• Provide image meta-data, clinical outcome data, and
measurement results as a public resource.• Phantoms for quality assurance & control.• http://grants.nih.gov/grants/guide/pa-files/PAR-08-225.html
Purpose of the QIN Program
• Our hypothesis: Optimized and validated quantitative imaging techniques are needed on commercial platforms for large scale multi-center clinical trials focused on therapy response.
• Therefore: Necessary to promote innovative research in this area.
• Goal: Bring quantitative imaging as a validated method or tool to oncologists for clinical decision making.
Deliverables in the QIN Program
• Understand and overcome physical and biological measurement uncertainties.
• Eliminate or minimize qualitative and observer-based estimates of measurements of therapy response.
• Create clinical decision tools that are reliable over multiple sites and commercial devices.
• Database development and informatics.
The QIN Program
• Builds from a successful RIDER (Reference Image Database to Evaluate Response) program.– NCI web-based public resource– Lung and other organ sites images and
metadata– Phantom data, quality assurance
The Quantitative Imaging Network (QIN)
• PAR-08-225; a U01 mechanism issued August 2008– No set-aside funds and no limit to the number of
awards
• Submission dates:– February 5, June 5, and October 5
– Paper submissions
• Reviewed by Special Emphasis Panel (SEP) from NCI
The “Model” Program
A QIN Member
Tool
Annotated databasewith metadata & outcomes
Clinical trial
Data & Results
An AppropriateClinical Trial
Validation
Development
Clinical Trials
• Ongoing or planned trials must be identified: Trials not supported by QIN
• Phase I,II, and/or III
• QIN will support additional images beyond trial protocol (IRB approval)
• QIN will support correlative studies such as genomics
• ACRIN is an obvious source for the trials
Early-Stage QIN & ACRIN Interaction
A Progressing ACRIN Clinical Trial
A QIN Member
Link to trial
Image data are received
QIN & ACRIN Interaction
• The ACRIN trial must be relevant to the cancer problem of the QIN member.
• An ideal way to link QIN and ACRIN
– ACRIN investigators apply to QIN and become network members.
An Example
• University of Washington: QIN– Linking to ACRIN 6687 (prostate) and ACRIN 6688
(breast) for tool development & validation– PET imaging– Focus on early drug trials (Phase I, II)– Tools developed will be applicable to larger Phase III
trials– Enable clinical investigators, cooperative groups and
pharma to include quantitative PET imaging biomarkers in study design and sample size.
QuantitativeMethods
VarianceReduction
ValidatedMethods
ClinicalTools
ACRIN and QIN Association
ImagingDissemination
ImagingImprovements
ImagingTechnologies
ImagingAssessment
ACRIN
ImagingStandards
QIN
Phantoms
Informatics
Steering Committee Organization
• Organization– Two representatives from each team
• PI plus an alternate• Only 1 vote for team
– Two program staff• Only 1 vote
– Lead Program Director• No vote
– Others (non-voting) may be invited to participate, depending on the subject of the meeting.
• Rotating annual chair• Monthly teleconference meetings• Two yearly face-to-face meetings
Working Groups
• Provide “open science” means to address common issues.– e.g. Data sharing, QC issues, Clinical involvement,
Informatics.– Create consensus in these areas.
• Network-wide groups.– Each team contributes members to each working group. A
chair is chosen annually.– Will hold separate monthly meetings (autonomous).– Source for network-wide publications.
Working Groups
• Data Collection
• Image Analysis & Performance Metrics
• Bioinformatics/IT & Data Sharing
• Clinical Trial Design & Development
• Outreach: External/Industrial Relations
Working Groups
• Each working group has– Defined its mission statement– Begun creating first year goals
• In the future, they will– Survey all QIN teams on specific working
group issues– Create consensus dialogues and documents
Current QIN Status
• Currently, 6 charter members– One more team is about to be funded– 1 Face-to-face (kick-off) meeting
• Perhaps over 12 members by 2011• Broad range of imaging modalities
– CT and PET/CT– SPECT– MRI, DCE-MRI, DW-MRI
• Phantom studies, quality assurance• Longitudinal studies• Database development and sharing
Who is Doing What in the QIN
Institute Cancer Problem Imaging Method Imaging Method Other
University of Iowa Head & Neck PET/CT MRI/MRSIPhantoms, database
Brigham & Women's Prostate MRI
Moffitt Cancer Center Lung PET/CT Univ. of
WashingtonBreast & Prostate PET/CT Phantoms
Univ. of Pittsburgh Head & Neck PET/CT MRI
Stanford Univ. Metastatic Colon CT MRI
Vanderbilt Univ. Breast MRI PET 3T
Timeline For Entry Into QIN
Release dateAugust 2008
Termination date
September 2011
U. PittsburghSept 1, 2009
H. Lee Moffitt CC
March 9,2010
U. IowaApril 1, 2010
U. WashingtonApril 15, 2010
Vanderbilt U.May 1, 2010
Stanford U.May 1, 2010
Brigham & Women’s
September 2010
2009 2010 2011
Communication Within QIN
• Steering Committee meetings provide team-to-team communication.
• Regular meetings within each team provides team-to-working group communication.
• Chairs of working groups can participate (non-voting) in steering committee meetings.
• QIN Newsletter and publications
Associate Members to QIN
• Academic– Active research in quantitative imaging for
cancer response– Willingness to participate in face-to-face
meetings• Industrial
– Have products or tools of interest to QIN– Willingness to share and compare
The Program Team for QIN
• Robert Nordstrom, Lead Program Director• Larry Clarke, Science Officer• Gary Kelloff, Science Officer• Pushpa Tandon, CIP Program Director• Huiming Zhang, CIP Program Director• Barbara Croft, CIP Program Director• Barbara Galen, CIP Program Director• James Deye, RRP Program Director