Imaging measurements including quantitative imaging biomarkers are analogous to clinical laboratory assays that help track health conditions; therefore, quality assurance and quality control (QA/QC) standards developed for lab assays should be adapted to quantitative imaging, say leaders of the Quantitative Medical Imaging Coalition (QMIC).
The independent nonprofit coalition launched in November 2025 to develop imaging guidelines that ensure measurement reproducibility throughout the entire imaging chain -- especially important with wider use of quantitative imaging (QI) in clinical practice and clinical trials.
Among QMIC goals are to designate centers of excellence in quantitative imaging, said Gudrun Zahlmann, PhD, who leads QMIC as co-president with Caroline Chung, MD, chief data and analytics officer at the University of Texas MD Anderson Cancer Center.
Such QI designations will increase understanding of the importance of high-precision, quantitative results obtained at imaging centers around the world, according to Chung and Zahlmann, who discussed QMIC’s strategy for AuntMinnie.
Why it matters now
Caroline Chung, MD
The reason QMIC’s work is timely and urgent, Chung explained, is that the imaging community stands at an inflection point shaped by three converging forces:
- AI and computational tools are creating unprecedented capability to extract quantitative information from medical images, yet these tools are only as reliable as the underlying data.
- Imaging-derived measurements now directly guide treatment eligibility and monitor response, so measurement accuracy directly affects patients.
- The global imaging ecosystem lacks the standardization infrastructure that the clinical laboratory world established decades ago.
“Our colleagues across the medical imaging community recognize that something needs to change, but connecting the scientific discoveries in quantitative imaging to real-world clinical impact requires coordinated effort across institutions, vendors, regulators, payers and clinical specialties,” Chung said. “That’s exactly what QMIC is designed to enable.”
QI specifications
“We’re becoming more reliant on imaging data to tell us whether a treatment has worked or not worked, but what are we measuring over time?” said Zahlmann, whose vision is that imaging teams should follow “QI specifications."
To that end, QMIC is actively engaging clinical organizations, radiology and imaging organizations, health research organizations, regulatory organizations, emerging data science and AI organizations, and industry partners from imaging, pharma, biotech, and software and AI companies.
QMIC expands the RSNA Quantitative Imaging Biomarkers Alliance (QIBA). That was primarily focused on establishing technically detailed imaging biomarker profiles, according to Zahlmann. QMIC aims to build and connect the broad communities needed to enable "systemic changes" for adoption of quantitative imaging into practice, she told AuntMinnie.
QMIC draws on more than 300 volunteer experts organized across 15 active biomarker committees spanning MRI, CT, nuclear/molecular imaging, and ultrasound, Zahlmann said.
“Quantitative imaging challenges exist across CT, MRI, nuclear medicine, and ultrasound already,” Zahlmann explained. “The physics are different, the clinical applications are different, but the fundamental metrology challenge to ensure that a measurement means the same thing wherever and whenever it is obtained is universal.”
Ultimately, QMIC expands the scope of the former QIBA biomarker profiles into technical guidelines encompassing the entire imaging chain -- from institutional readiness and image acquisition to image processing and analysis. QMIC also aims to expand its scope beyond purely radiological imaging to support the various growing areas of medical imaging.
“We are not trying to reduce imaging to a single reference method,” Chung said. “We are trying to build consensus-based guidelines that define the conditions under which a quantitative imaging measurement can deliver results with known bias and precision and then help the community implement those guidelines in practice to inform and benefit clinical decisions.”
Vendor collaboration
QMIC is working toward conformance models with streamlined testing procedures, phantom-based QA protocols integrated into routine clinical workflow, and close collaboration with vendors to embed profile-conformant acquisition settings into scanner preset libraries.
“Scanner vendors must be willing to expose and standardize the parameters that affect quantitative accuracy -- some of which are embedded in proprietary reconstruction algorithms that vendors consider competitive differentiators,” Zahlmann noted.
Clinical sites must also adopt standardized protocols even when they conflict with local preferences, and radiologists and technologists need training to understand why a particular slice thickness or reconstruction kernel matters for a volumetric measurement, she continued.
“These are cultural and economic challenges as much as technical ones,” Zahlmann said. "But the clinical payoff is substantial."
