Monday, June 23, 2025 6/23/2025

Development of AI-Augmented quality assurance tools for radiation therapy

Award Number: R01CA275772
ORGANIZATION: NATIONAL CANCER INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 02/01/2023
PERIOD OF PERFORMANCE END DATE: 01/31/2028

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Development of AI-Augmented quality assurance tools for radiation therapy - Development of AI-Augmented quality assurance tools for radiation therapy Project summary Quality assurance (QA) is an essential part of radiation therapy (RT) workflow and critically determines the success of patient care. However, current treatment plan QA methods and tools are deficient in multiple aspects and suffer from problems such as limited accountability, labor intensive, and costly. In this project we will leverage the emerging deep learning techniques to create clinically translatable solutions for robust and efficient QA of modern RT. Specifically, we aim to (i) establish a novel framework for using deep learning to verify the machine delivery parameters of an RT treatment plan; (ii) investigate the use of deep learning for RT dose verification; and (iii) evaluate the performance of the QA system and show its potential clinical impact . This research presents the first-of-its-kind treatment plan QA strategy capable of providing both machine delivery parameters (MLC apertures and MUs of the involved IMRT/VMAT fields) and dosimetric distribution on the patient’s treatment geometry. The research will also make it possible to take advantage of the useful features of both deep learning models from Aims 1 and 2 and check the cycle-consistency of a treatment plan (i.e., from the beam parameters of the plan to the corresponding 3D dose distribution, and then from the 3D dose to the beam parameters) for enhanced plan QA. Successful completion of the project will provide urgently needed plan QA tools for safe, efficient and high-quality RT practice, and enable patients to truly benefit from modern RT modalities. Finally, the proposed strategy is quite broad and can be readily generalized for QA of other treatment modalities, such as proton therapy and high-dose rate (HDR) brachytherapy.


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 = $514,576 )
2025	2025	THE LELAND STANFORD JUNIOR UNIVERSITY	450 JANE STANFORD WAY	STANFORD	CA	94305	SANTA CLARA	USA	Cancer Treatment Research	001	3	5/22/2025	NON-COMPETING CONTINUATION	$51,458
2025	2025	THE LELAND STANFORD JUNIOR UNIVERSITY	450 JANE STANFORD WAY	STANFORD	CA	94305	SANTA CLARA	USA	Cancer Treatment Research	000	3	2/19/2025	NON-COMPETING CONTINUATION	$463,118
														Subtotal = $514,576

Issue Date FY: 2024 ( Subtotal = $500,676 )
2024	2024	THE LELAND STANFORD JUNIOR UNIVERSITY	450 JANE STANFORD WAY	STANFORD	CA	94305	SANTA CLARA	USA	Cancer Treatment Research	001	2	4/16/2024	NON-COMPETING CONTINUATION	$26,353
2024	2024	THE LELAND STANFORD JUNIOR UNIVERSITY	450 JANE STANFORD WAY	STANFORD	CA	94305	SANTA CLARA	USA	Cancer Treatment Research	000	2	1/23/2024	NON-COMPETING CONTINUATION	$474,323
														Subtotal = $500,676

Issue Date FY: 2023 ( Subtotal = $550,091 )
2023	2023	LELAND STANFORD JUNIOR UNIVERSITY, THE	450 JANE STANFORD WAY	STANFORD	CA	94305	SANTA CLARA	USA	Cancer Treatment Research	000	1	12/16/2022	NEW	$550,091
														Subtotal = $550,091

Grand Total All Awards = $1,565,343

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Development of AI-Augmented quality assurance tools for radiation therapy

Award Number: R01CA275772

ORGANIZATION: NATIONAL CANCER INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 02/01/2023

PERIOD OF PERFORMANCE END DATE: 01/31/2028

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