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A clinical tool for automated detection and delineation of intracranial metastases from MRI

Award Number: R01CA262182
ORGANIZATION: NATIONAL CANCER INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/01/2021
PERIOD OF PERFORMANCE END DATE: 07/31/2027

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A clinical tool for automated detection and delineation of intracranial metastases from MRI - As the management of multiple intracranial metastases is rapidly evolving, the demands for detection and delineation of a large number of potentially very small metastatic lesions in the brain on 3D magnetic resonance images (MRI) are increasing dramatically. Artificial intelligence (AI) systems can assist both the radiologist as well as radiation oncologist in their roles in management of patients with multiple tumors metastatic to the brain. In response to PAR-20- 155, we have assembled an academic-industrial partnership including investigators from three academic institutes and an industrial AI team to develop, translate and validate AI systems to address this unmet clinical question. In this proposal, a neural network system based upon multiple scale 3D fully convolutional one-stage objective detectors containing segmentation heads will be optimized and investigated. Training and testing data will be provided from clinical images of patients treated with radiosurgery to multiple small metastases acquired from three academic centers, curated by experts, and augmented by addition of realistic synthetic lesions injected into images. The clinical utility of the network will be investigated for its ability to assist a) radiologists in detecting multiple metastases accurately and efficiently, and b) radiation oncologists in delineating multiple metastatic lesions to support selection of therapeutic strategies and planning of treatments.


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	REGENTS OF THE UNIVERSITY OF MICHIGAN	1109 GEDDES AVE STE 3300	ANN ARBOR	MI	48109	WASHTENAW	USA	Cancer Detection and Diagnosis Research	000	5	6/2/2026	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2025 ( Subtotal = $332,510 )
2025	2025	REGENTS OF THE UNIVERSITY OF MICHIGAN	1109 GEDDES AVE STE 3300	ANN ARBOR	MI	48109	WASHTENAW	USA	Cancer Detection and Diagnosis Research	000	5	7/8/2025	NON-COMPETING CONTINUATION	$332,510
														Subtotal = $332,510

Issue Date FY: 2024 ( Subtotal = $315,716 )
2024	2024	REGENTS OF THE UNIVERSITY OF MICHIGAN	1109 GEDDES AVE, SUITE 3300	ANN ARBOR	MI	48109	WASHTENAW	USA	Cancer Detection and Diagnosis Research	000	4	6/26/2024	NON-COMPETING CONTINUATION	$315,716
														Subtotal = $315,716

Issue Date FY: 2023 ( Subtotal = $351,135 )
2023	2023	REGENTS OF THE UNIVERSITY OF MICHIGAN	1109 GEDDES AVE, SUITE 3300	ANN ARBOR	MI	48109	WASHTENAW	USA	Cancer Detection and Diagnosis Research	000	3	7/7/2023	NON-COMPETING CONTINUATION	$351,135
														Subtotal = $351,135

Issue Date FY: 2022 ( Subtotal = $410,695 )
2022	2022	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON ST	ANN ARBOR	MI	48109	WASHTENAW	USA	Cancer Detection and Diagnosis Research	000	2	8/15/2022	NON-COMPETING CONTINUATION	$410,695
														Subtotal = $410,695

Issue Date FY: 2021 ( Subtotal = $456,195 )
2021	2021	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON ST	ANN ARBOR	MI	48109	WASHTENAW	USA	Cancer Detection and Diagnosis Research	000	1	7/20/2021	NEW	$456,195
														Subtotal = $456,195

Grand Total All Awards = $1,866,251

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A clinical tool for automated detection and delineation of intracranial metastases from MRI

Award Number: R01CA262182

ORGANIZATION: NATIONAL CANCER INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 08/01/2021

PERIOD OF PERFORMANCE END DATE: 07/31/2027

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