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Deep learning to quantify glaucomatous damage on fundus photographs for teleophthalmology

Award Number: K23EY030897
ORGANIZATION: NATIONAL EYE INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: TRAINING/TRAINEESHIP
PERIOD OF PERFORMANCE START DATE: 06/02/2021
PERIOD OF PERFORMANCE END DATE: 02/28/2027

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Deep learning to quantify glaucomatous damage on fundus photographs for teleophthalmology - PROJECT SUMMARY/ABSTRACT Candidate: Atalie Carina Thompson, MD, MPH is a current glaucoma fellow and Heed fellow with a long-term career goal of becoming an independent clinician-scientist and leader in the field of glaucoma and public health. She has a long-standing interest in addressing healthcare disparities in medicine, and in improving the diagnosis of glaucoma and other ophthalmic diseases through imaging technology. While obtaining a medical degree at Stanford, she received a fellowship to complete a master’s degree in public health with additional higher-level coursework in biostatistics and epidemiology. Her immediate goal in this proposal is to refine and validate a deep learning (DL) algorithm capable of quantifying neuroretinal damage on optic disc photographs and then to apply it in a pilot teleophthalmology program. With a K23 Mentored Patient-Oriented Research Career Development Award, she will acquire additional didactic training and mentored research experience in glaucoma imaging, machine learning, biostatistics, clinical research, and the responsible conduct of research. Environment: The mentorship and expertise of the advisory committee, the extensive resources at the Duke Eye Center and Departments of Biostatistics and Biomedical Engineering, and the significant institutional commitment will provide her with the support needed to transition successfully into an independent clinician-scientist. Research: This proposal will test the hypothesis that a DL algorithm trained with SDOCT detects glaucoma on optic disc photographs with greater accuracy than human graders. In Specific Aim 1, a DL algorithm that quantifies neuroretinal damage on optic disc photographs will be refined. The main hypothesis is that the quantitative output provided by the DL algorithm will allow accurate discrimination of eyes at different stages of the disease according to standard automated perimetry, and will generate cut-offs suitable for use in a screening setting. In Specific Aim 2, the short-term repeatability and reproducibility of the DL algorithm in optic disc photographs acquired over a time period of several weeks will be determined. The hypothesis is that the test-retest variability of the predictions from the DL algorithm will be similar to the original measurements acquired by SDOCT. In Specific Aim 3, the DL algorithm will be applied to optic disc photographs obtained during a pilot screening teleophthalmology program in primary care clinics and assisted living facilities. The hypothesis is that the DL algorithm will be more accurate than human graders when a full ophthalmic examination is used as the gold standard. This work will constitute the basis of an R01 grant and will advance our understanding of the application of deep learning algorithms in glaucoma and teleophthalmology.


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	2024	WAKE FOREST UNIVERSITY HEALTH SCIENCES	MEDICAL CENTER BLVD	WINSTON SALEM	NC	27157	FORSYTH	USA	Vision Research	000	6	12/19/2025	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2025 ( Subtotal = $0 )
2025	2024	WAKE FOREST UNIVERSITY HEALTH SCIENCES	MEDICAL CENTER BLVD	WINSTON SALEM	NC	27157	FORSYTH	USA	Vision Research	000	6	12/2/2024	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2024 ( Subtotal = $189,104 )
2024	2024	WAKE FOREST UNIVERSITY HEALTH SCIENCES	MEDICAL CENTER BLVD	WINSTON SALEM	NC	27157	FORSYTH	USA	Vision Research	000	6	2/21/2024	NON-COMPETING CONTINUATION	$189,104
														Subtotal = $189,104

Issue Date FY: 2023 ( Subtotal = $194,790 )
2023	2023	WAKE FOREST UNIVERSITY HEALTH SCIENCES	MEDICAL CENTER BLVD	WINSTON SALEM	NC	27157	FORSYTH	USA	Vision Research	000	5	2/21/2023	NON-COMPETING CONTINUATION	$194,790
														Subtotal = $194,790

Issue Date FY: 2022 ( Subtotal = $194,790 )
2022	2022	WAKE FOREST UNIVERSITY HEALTH SCIENCES	MEDICAL CENTER BLVD	WINSTON SALEM	NC	27157	FORSYTH	USA	Vision Research	003	4	4/4/2022	NON-COMPETING CONTINUATION	$194,790
2022	2021	WAKE FOREST UNIVERSITY HEALTH SCIENCES	MEDICAL CENTER BLVD	WINSTON SALEM	NC	27157	FORSYTH	USA	Vision Research	002	3	1/7/2022	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$61,928
2022	2021	DUKE UNIVERSITY	2200 W MAIN ST	DURHAM	NC	27705	DURHAM	USA	Vision Research	001	2	1/7/2022	NON-COMPETING CONTINUATION	-$22,123
2022	2020	DUKE UNIVERSITY	2200 W MAIN ST	DURHAM	NC	27705	DURHAM	USA	Vision Research	000	1	1/7/2022	NEW	-$39,805
														Subtotal = $194,790

Issue Date FY: 2021 ( Subtotal = $193,774 )
2021	2021	WAKE FOREST UNIVERSITY HEALTH SCIENCES	MEDICAL CENTER BLVD	WINSTON SALEM	NC	27157	FORSYTH	USA	Vision Research	002	3	8/9/2021	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$171,651
2021	2021	DUKE UNIVERSITY	2200 W MAIN ST STE 710	DURHAM	NC	27708	DURHAM	USA	Vision Research	000	2	2/10/2021	NON-COMPETING CONTINUATION	$193,774
2021	2021	DUKE UNIVERSITY	2200 W MAIN ST STE 710	DURHAM	NC	27708	DURHAM	USA	Vision Research	001	2	8/9/2021	NON-COMPETING CONTINUATION	-$171,651
														Subtotal = $193,774

Issue Date FY: 2020 ( Subtotal = $195,131 )
2020	2020	DUKE UNIVERSITY	2200 W MAIN ST STE 710	DURHAM	NC	27708	DURHAM	USA	Vision Research	000	1	2/12/2020	NEW	$195,131
														Subtotal = $195,131

Grand Total All Awards = $967,589

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Deep learning to quantify glaucomatous damage on fundus photographs for teleophthalmology

Award Number: K23EY030897

ORGANIZATION: NATIONAL EYE INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: TRAINING/TRAINEESHIP

PERIOD OF PERFORMANCE START DATE: 06/02/2021

PERIOD OF PERFORMANCE END DATE: 02/28/2027

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