SBIR/STTR Research Award

STTR Phase I: Automated object contouring methods and software for head and neck radiotherapy planning

Award identifier 3e3b6453a50fe27e7fe6b42a4f2c598058b1041b8e43fd66b5522c026b921655Awarding agency National Science Foundation

Award amount

$225,000

Program and phase

STTR · Phase I

Award year

2016

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
Quantitative Radiology Solutions LLC
Proposal award date
2016-01-15
Contract end date
2016-12-31
UEI
TLMLBB8Y4SA3
Solicitation number
Not reported
Topic code
BM

Research abstract

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is in the field of radiation therapy (RT) for head & neck cancer patients. RT planning involves designing a radiation treatment regimen so that tumors are irradiated to definitive doses while minimizing irradiation to normal structures. For devising an optimal RT plan, target tumors and critical anatomic structures need to be accurately contoured on medical images. In current clinical practice, organ contour delineation is performed mostly manually due to lack of automated contouring software. This makes RT planning error prone, hampers throughput, and does not allow re-contouring to handle changes taking place during RT. Such changes can cause under dosing to tumor and overdosing to normal surrounding organs. In 2015, 1,658,370 new cancer cases are estimated to occur in the US, where nearly two-thirds will have RT. Given that there are over 2,100 RT centers in the US, there is a strong commercial opportunity for producing an auto-contouring software system. Expected clinical outcomes are significantly improved speed, throughput, and accuracy of contouring compared to current clinical practice, and improved patient outcomes and cost-savings. This Small Business Technology Transfer (STTR) Phase I project addresses a technical hurdle related to auto-contouring in RT planning for cancer patients. Current technical challenges for auto-contouring occur since available contouring methods have been developed mostly for a specific object on images of a particular modality. This project will overcome these hurdles through a novel automatic anatomy recognition methodology which will employ anatomy models derived from patient populations by including all major objects in a body region. The models will codify the rich object anatomic relationship, and will exploit this information to automatically locate and contour objects in any given patient image. The project will have two aims. Aim 1 involves the development of the method and prototype software for contouring major head & neck organs on CT and PET/CT images. Models will be built from already existing image and contour data of 200 cancer patients. Aim 1 outcome will be prototype software technically validated to be accurate within 1 pixel boundary distance compared to ground truth and requiring 3 minutes or less per study. Aim 2 will be a preliminary clinical assessment of the software in RT planning in patients with head & neck malignancies.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

4 SBIR/STTR records share this UEI (2016–2020). Reported award amounts total $2,664,943. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, National Science Foundation

Agency intelligence

National Science Foundation

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