Year 3: High-throughput truthing of microscope slides to validate artificial intelligence algorithms analyzing digital scans of pathology slides: data collection to create the medical device development tool (MDDT)
- Link to pathologist recruiting advertisement
- Research collaboration agreement scope for collaborators providing slides and other materials
- CDRH_RCA_Gallas_Template_7-23-2020.doc (106 KB, uploaded by Brandon D. Gallas 5 months 4 days ago)
- We are crowdsourcing pathologists to collect data (images + pathologist annotations) that can be qualified by the FDA/CDRH medical device development tool program (MDDT). If successful, the MDDT qualified data along with a statistical software package for data analysis would be available to any algorithm developer to be used to validate their algorithm performance in a submission to the FDA/CDRH.
Researchers from the U.S. Food and Drug Administration, alongside academic collaborators, are collecting pathologist annotations as data for AI/ML algorithm validation for tumor infiltrating lymphocyte (TIL) detection and quantitation. We are asking board-certified anatomic pathologists and anatomic pathology residents to score 80 ROIs as part of a research study. We anticipate that this task will take participants a total of 30 minutes. The data are intended to inform the agency’s approach to novel algorithm validation, ensuring high quality commercial products with a faster FDA-pipeline to approval.
HTT_IRBinformedConsent.pdf (47 KB, uploaded by Brandon D. Gallas 1 year 1 month ago)
Please complete this Survey when you finish data collection, and help us improve the HTT project.
- Supply glass slides and their scanned versions
- Help create a Continuing Medical Education course in conjunction with this project
- Host an analog (microscope + eeDAP) data collection event at your clinical site
- Help spread the word, recruit your colleagues to participate in online data collection
Thank you. For more information contact:
Brandon Gallas, PhD, (email@example.com)
FDA/CDRH/OSEL Division of Imaging, Diagnostics, and Software Reliability
on behalf of the High-Throughput Truthing (HTT) Project