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)
In Year 3 of the High Throughput Truthing project, the team will collect data at various collaborating sites and conferences.
Check out our completed work from Year 1 and Year 2 in the HTT project
- Pitch:
- 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.
Complete the HTT Data Collection Training
NOTE: EVERYTHING BELOW THIS WILL BE MOVED
Training documents:
The Study: dataCollectionTutorialHTT.pdf (4 MB, uploaded by Brandon D. Gallas 4 years 1 month ago) – This DRAFT tutorial outlines the project, and provides a demonstration of your tasks for all three data collection platforms.
The Clinical Task: TILs evaluation manuscript, TILs training slides – Participating pathologists can review the clinical training slides (required to participate), and read the related manuscript if possible. These materials were created by the TILs in breast cancer working group.
The Hardware Used in the Study: eeDAP – Annotations will be collected in digital and microscope modes. For the microscope mode, we will use eeDAP, an Evaluation Environment for Digital and Analog Pathology (eeDAP), a registration system between the microscope and digital whole slide images.
Consent Form:
HTT_IRBinformedConsent.pdf (47 KB, uploaded by Brandon D. Gallas 4 years 2 months ago)
Exit Survey:
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, (brandon.gallas@fda.hhs.gov)
FDA/CDRH/OSEL Division of Imaging, Diagnostics, and Software Reliability
on behalf of the High-Throughput Truthing (HTT) Project