150 likes | 334 Views
Status and potential for further collaboration with RSNA QIBA QIN Meeting, March 28, 2014. D. Sullivan, MD Duke University; RSNA. Premise. Variation in clinical practice results in poorer outcomes and higher costs. RSNA’s Perspective:.
E N D
Status and potential for further collaboration with RSNA QIBA QIN Meeting, March 28, 2014 D. Sullivan, MD Duke University; RSNA
Premise Variation in clinical practice results in poorer outcomes and higher costs.
RSNA’s Perspective: • Extracting objective, quantitative results from imaging studies will improve the value of imaging in clinical practice.
Quantitative Imaging Biomarkers Alliance (QIBA): Background Started in 2007 Mission: Improve value and practicality of quantitative imaging biomarkers by reducing variability across devices, patients, and time. “Industrialize imaging biomarkers”
QIBA Criteria for Biomarker Selection • Transformational • addresses a significant medical need • Translational • will likely result in significant improvement in the development, approval, or delivery of care to patients. • Feasible • end goals can likely be achieved in a specific timeframe • Practical • leverages preexisting resources (e.g., intellectual capital, personnel, facilities, specimens, reagents, data) wherever possible; warrants access to RSNA resources and support. • Collaborative • the biomarker has the support of the stakeholder community and the organizational impetus to sustain continued efforts.
QIBA Committees Quantitative Magnetic Resonance Imaging [Q-MR] • Perfusion, Diffusion, and Flow-MRI (PDF-MRI) • Functional MRI (fMRI) Quantitative Computed Tomography [Q-CT] • CT Volumetry in Solid Tumors and Lung Nodules • CT Densitometry in COPD • Airway Morphology in Asthma Quantitative Nuclear Medicine [Q-NM] • FDG-PET SUV • Amyloid-PET Quantitative Ultrasound [Q-US] • Shear Wave Speed for liver fibrosis
Imaging Assays Assays are characterized by their: Technical Performance Clinical Performance Clinical validation Clinical utility QIN
Variability in imaging measurements is related to: • Image acquisition variability • Radiologist/Reader variability • Measurement method variability
QIBA Profiles A QIBAProfile describes a specific performance Claim and how it can be achieved.
QIBA Claim Template • List Biomarkers/Measurand(s) • Specify: Cross-sectional vs. Longitudinal measurement • List Indices: • Bias Profile (Disaggregate indices) • Precision Profile • Test-retest Repeatability (Repeatability coefficient) • Reproducibility (Reproducibility coefficient; Intra-class Correlation Coefficient [ICC]; Concordant Correlation Coefficient [CCC]). • Specify conditions, e.g., • Measuring System variability (hardware & software) • Site variability • Operator variability (Intra- or Inter-reader) • Clinical Context
True Biologic Change … … is approximately twice the variability Clinical Significance of that change needs to be determined by clinical studies.
Reducing variability in imaging measurements is important to both QIN and QIBA: • Image acquisition variability • Test objects – physical and virtual • Radiologist/Reader variability • Measurement method variability • Algorithm comparisons
Measurement method variability How do we deal with the fact that different algorithms that purport to measure the same thing give different answers? • Methodology for comparing algorithms • Metrics of performance on same task • Criteria for acceptability (compliance).