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RSI-AI: Predicting clinically significant prostate cancer to guide biopsy decisions by combining advanced tissue microstructure imaging with deep learning

Award Number: R44CA254738
ORGANIZATION: NATIONAL CANCER INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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RSI-AI: Predicting clinically significant prostate cancer to guide biopsy decisions by combining advanced tissue microstructure imaging with deep learning - Prostate biopsies are critical for the diagnosis of prostate cancer, but it is often unclear who should be biopsied and where in the gland the biopsy should be targeted. This results in missed diagnoses, unnecessary biopsies, and overdiagnosis and overtreatment of cancer that is not life threatening. The goal of this proposal is to develop a set of quantitative and non-invasive tools, RSI-AI and RSI-AI+, to help clinicians determine who should be biopsied for prostate cancer and the locations of clinically significant lesions. RSI-AI uses deep learning to predict the location and pathological grade of prostate cancer lesions from restriction spectrum imaging (RSI) data. RSI is an advanced diffusion magnetic resonance imaging (MRI) technique that models the restricted diffusion of water molecules to improve microtissue classification and tumor detection. By utilizing RSI data in the deep learning model, RSI-AI will produce pathological grade predictions that are more accurate than models trained with conventional MRI data. RSI-AI+ integrates the pathological grade predictions from RSI-AI with clinical data including age, family history, genetics, and prostate volume to accurately and comprehensively quantify current and future risk for prostate cancer. Phase I of this proposal will develop and validate the RSI-AI and RSI-AI+ models and compare their performance to models trained with conventional MRI data. Phase II of this proposal will deploy RSI-AI and RSI-AI+ to the Cortechs cloud platform, demonstrate their clinical usability and utility, and generate the materials required for a 510K FDA submission. The clinical software generated through this proposal will ultimately improve diagnostic yields, reduce unnecessary biopsies and overtreatment of indolent prostate cancer, while facilitating early detection and appropriate treatment of clinically significant prostate cancer


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: 2025 ( Subtotal = $0 )
2025	2021	CORTECHS LABS, INC.	5060 SHOREHAM PL STE 240	SAN DIEGO	CA	92122	SAN DIEGO	USA	Cancer Detection and Diagnosis Research	000	1	2/13/2025	NEW	$0
														Subtotal = $0

Issue Date FY: 2024 ( Subtotal = $860,506 )
2024	2024	CORTECHS LABS, INC.	5060 SHOREHAM PL STE 240	SAN DIEGO	CA	92122	SAN DIEGO	USA	Cancer Detection and Diagnosis Research	001	3	7/4/2024	NON-COMPETING CONTINUATION	$860,506
2024	2023	CORTECHS LABS, INC.	5060 SHOREHAM PL STE 240	SAN DIEGO	CA	92122	SAN DIEGO	USA	Cancer Detection and Diagnosis Research	000	2	10/24/2023	EXTENSION WITH OR WITHOUT FUNDS	$0
														Subtotal = $860,506

Issue Date FY: 2023 ( Subtotal = $735,773 )
2023	2023	CORTECHS LABS, INC.	5060 SHOREHAM PL STE 240	SAN DIEGO	CA	92122	SAN DIEGO	USA	Cancer Detection and Diagnosis Research	000	2	9/21/2023	EXTENSION WITH OR WITHOUT FUNDS	$735,773
														Subtotal = $735,773

Issue Date FY: 2021 ( Subtotal = $251,720 )
2021	2021	CORTECHS LABS, INC.	5060 SHOREHAM PL STE 240	SAN DIEGO	CA	92122	SAN DIEGO	USA	Cancer Detection and Diagnosis Research	000	1	8/11/2021	NEW	$251,720
														Subtotal = $251,720

Grand Total All Awards = $1,847,999

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RSI-AI: Predicting clinically significant prostate cancer to guide biopsy decisions by combining advanced tissue microstructure imaging with deep learning

Award Number: R44CA254738

ORGANIZATION: NATIONAL CANCER INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

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