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Explore the shift towards objective measurement in imaging for clinical trials, addressing challenges like image quality, data reproducibility, and clinical data management for improved treatment efficiency. Discover standard-based solutions, tools for data processing, and future needs in the imaging industry.
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Imaging as a biomarker: standards for change measurements in therapy NIST, Gaithersburg, MD
Workshop « Imaging as Biomarker » • General issue: Imaging use for Clinical trials • Organized by NIST • Supported by: • Sponsoring organization: NIH, NCI (Larry Clarke) • FDA • Pharmaceutical industry: PhRMA, big labs • Normalization structures: NIST, NEMA • Professional societies: RSNA, AAPM, SNM, ISMRM, SPIE • Vendors: Siemens, GE, Philips
The issues (1/2) • Use of imaging to evaluate new treatment efficiency: • Not only a subjective reading of images • But, more and more objective measurements with “quantitative” methods • Examples : Alzheimer desease, lung cancer, arthrosis… • Low efficiency statement of clinical trials • Longs, expensives, and often… no positive result! • …
The issues (2/2) • Main reasons: • Too often, mediocre quality of image data • No quantitative • Reproducibility issues (intra system and inter systems) • Acquisition protocols non respected → lot of cases are non usable • Data processing differs between different site (→ “site” effect) • Too subjective • Not enough automated • Insufficient quality of clinical data associated • “Local” semantic for clinical information • Resulting bias amplify intrinsic variability of the phenomena • → increase of the necessary number of cases • Data management cost • Because support tools needs to be rebuild case by case • Data cannot be re-used • Despite the politic of sponsoring organizations (dissemination plan) • No sharing infrastructure
Solution components, standard based (1/2) • Standard phantoms to calibrate imaging systems • Standard study protocols • To be really identical between machines (patient preparation, image acquisition, pre-processing and applied corrections, reconstruction…) • Standard procedures (guidelines) to manage clinical trials • good comprehension of protocols, physician and technologists education, quality assurance • Meta data and clinical data standardization • Need the use of normalized terminologies, ontologies…
Solution components, standard based (2/2) • Management tools adapted to the data and processing management • Scientific calculation • Step sequencing (including quality assurance) • Providing the required traceability • Compatibility issues with current PACS (regarding image management) • Reference implementation (open source shared tools) • Standard processing tools (that can be shared) • Open source • Plug-in or services remotely executable • Standard data • Anatomical atlases • Reference data (e.g. healthy populations )
Needs for the future • Medical • No more and less than tomorrow treatments for numerous pathologies • Vendors • Pharmaceutical industry, decrease of validation costs for new medication • Imaging systems industry • New generations of systems. Economical model. • Sharing / interoperability of processing tools • Scientific • Validation of processing and image quantification tools • Diffusion and re-use of tools
What happened since the NIST workshop ? • The Gil Jost (RSNA), Larry Clarke (NCI) and Michael Vannier (University of Chicago) propositions were well received in France and Europe • SFR and ESR decided to join RSNA and NCI in an international initiative on biomarkers • At RSNA meeting, Guy Frija (ESR) and Philippe Grenier (SFR) met Gil Jost to discuss on this topic. • SFR will launch a biomarkers working group.