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Imaging as a biomarker: standards for change measurements in therapy NIST, Gaithersburg, MD
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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 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
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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! … 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! …
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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 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
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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… 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…
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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 ) 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 )
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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 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
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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. 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.
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