Brandon D. Gallas provides mathematical, statistical, and modeling expertise to the evaluation of medical imaging devices at the FDA (https://www.fda.gov/medical-devices/medical-device-regulatory-science-research-programs-conducted-osel/digital-pathology-program-research-digital-pathology-medical-devices). His main areas of research are image quality, computer-aided diagnosis, imaging physics, and the design, execution, and statistical analysis of reader studies (https://github.com/DIDSR/iMRMC/releases, https://cran.r-project.org/web/packages/iMRMC/index.html, https://www.fda.gov/medical-devices/science-and-research-medical-devices/imrmc-software-do-multi-reader-multi-case-statistical-analysis-reader-studies). Recently, he has been investigating pathologist performance and agreement using whole slide imaging devices and the microscope (https://didsr.github.io/HTT.home/). These studies are enabled by an evaluation environment that registers the digital images to the glass slides (https://github.com/DIDSR/eeDAP/releases). Dr. Gallas also participates in the Pathology Innovation Collaborative Community (https://www.pathologyinnovationcc.org/), a regulatory science initiative to harmonize and standardize digital pathology processes to speed up innovation to patients.
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Methods: We create a registration accuracy task by identifying a visually distinct target. This target will be the center of a WSI ROI and is expected to appear in the center of the microscope FOV. We examined the registration accuracy of 60 ROIs from six slides, alternating registration methods and slide order within each study. We measure the distance between the target and the FOV center (registration error) using an eye piece reticle ruler as the stage moves from target to target. We summarize each error as a success (≤ 5.0 µm) or failure (> 5.0 µm). We completed a multi-reader multicase (MRMC) analysis of the registration successes and failures to estimate the variance components due to the readers and the cases.
Results: When using eeDAP in-focus, accuracy was within 5 µm in more than 97% of the FOVs.
Conclusions: The eeDAP registration methods were robust to new hardware, and the MRMC analysis has provided variance components for sizing future registration accuracy studies to account for the variability from readers and cases.
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