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PathCAM: connecting the digital data pipeline in diagnostic pathology with onboard-camera variable resolution slide imaging

Award Number: R01GM143789
ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/28/2022
PERIOD OF PERFORMANCE END DATE: 06/30/2027

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PathCAM: connecting the digital data pipeline in diagnostic pathology with onboard-camera variable resolution slide imaging - Project Summary: This project aims, for the first time, to bring digital pathology image generation and assis- tance seamlessly into the standard clinical workflow by developing PathCAM, a Computer Assisted Microscope system for pathologists. The field of digital pathology (DP) at first glance seems poised to make significant im- pacts in precision medicine. However, the generation of the digital images at the heart of DP is currently outside of the analog clinical workflow used for the overwhelming majority of clinical slide diagnoses. This is because, until now, digital image generation in pathology has been relegated to acquisition in expensive and slow whole slide imaging (WSI) systems, that are outside of the standard clinical workflow. Thus, the current analog micro- scope workflow will be the prevalent standard for now and the foreseeable future, meaning that any form of digital assistance for pathologists, via artificial intelligence (AI) or external second opinions, is currently signifi- cantly disconnected from practice. Moreover, hospitals and patients that do not have access to WSI systems on a routine basis cannot benefit from these assists. Our low-cost proposed solution is based on a simple insight: using video feeds from “onboard cameras” commonly installed on clinical microscopes, the camera and associ- ated software can build an exact digital record of the clinical review. Through our technical innovations, these images will be created passively, requiring no change in pathologist behavior. Our approach will provide a pathologist with a real-time preview of what they explored on a slide, giving them feedback on the “whole picture” of their review and context of their evaluation. Moreover, it allows the direct integration of AI assistance technol- ogies during clinical review. A transformative aspect to our approach is that images collected during review that are captured regioselectively from the pathology slide across resolution scales, will be combined into a single variable resolution image (VRI), which contains an optimal sampling of the tissue section, containing the exact balance of magnification and resolution needed to render the clinical decision. This optimal image is ideal for immediate data transfer for a remote pathology consultation – with no waiting for a separate digitization system to scan the slide. PathCAM’s applicability to both real-time digital assistance and remote second opinions will be studied in this work. Beyond the direct benefits to clinicians, the data produced by the PathCAM approach can be transformative for DP technologies going forward. PathCAM can cheaply image data from millions of slide reviews that would be otherwise be lost, and would enable more equitable data collection via wide and immediate open-source deployment through our collaboration with Kitware Inc. PathCAM also captures rich information about how pathologists reach clinical decisions (i.e., diagnostic provenance). These records of how pathologists clinically search and view slides across resolution scales and relationships between spatiotemporal attention and diagnosis can support the development of new self-supervised AI algorithms that learn from, but are not limited by, human-machine interaction data, as well as new human-in-the-loop decision support systems.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $0 )
2026	2025	THE ADMINISTRATORS OF TULANE EDUCATIONAL FUND	6823 SAINT CHARLES AVE	NEW ORLEANS	LA	70118	ORLEANS	USA	Biomedical Research and Research Training	000	4	5/20/2026	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2025 ( Subtotal = $416,192 )
2025	2025	THE ADMINISTRATORS OF TULANE EDUCATIONAL FUND	6823 SAINT CHARLES AVE	NEW ORLEANS	LA	70118	ORLEANS	USA	Biomedical Research and Research Training	000	4	7/25/2025	NON-COMPETING CONTINUATION	$416,192
														Subtotal = $416,192

Issue Date FY: 2024 ( Subtotal = $415,460 )
2024	2024	ADMINISTRATORS OF THE TULANE EDUCATIONAL FUND, THE	6823 SAINT CHARLES AVE	NEW ORLEANS	LA	70118	ORLEANS	USA	Biomedical Research and Research Training	000	3	7/10/2024	NON-COMPETING CONTINUATION	$415,460
														Subtotal = $415,460

Issue Date FY: 2023 ( Subtotal = $423,047 )
2023	2023	ADMINISTRATORS OF THE TULANE EDUCATIONAL FUND, THE	6823 SAINT CHARLES AVE	NEW ORLEANS	LA	70118	ORLEANS	USA	Biomedical Research and Research Training	000	2	8/16/2023	NON-COMPETING CONTINUATION	$423,047
														Subtotal = $423,047

Issue Date FY: 2022 ( Subtotal = $442,090 )
2022	2022	ADMINISTRATORS OF THE TULANE EDUCATIONAL FUND, THE	6823 SAINT CHARLES AVE	NEW ORLEANS	LA	70118	ORLEANS	USA	Biomedical Research and Research Training	000	1	9/27/2022	NEW	$442,090
														Subtotal = $442,090

Grand Total All Awards = $1,696,789

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PathCAM: connecting the digital data pipeline in diagnostic pathology with onboard-camera variable resolution slide imaging

Award Number: R01GM143789

ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 09/28/2022

PERIOD OF PERFORMANCE END DATE: 06/30/2027

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