SBIR/STTR Research Award

Internet-Based Distributed Quantitative 4D Analysis of Aortic MR/MDCT Images

Award identifier 86ac3af915caba0f1409415ac33313f161ff1d345b588c6ff740b77c9d4cb1cdAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$684,889

Program and phase

STTR · Phase II

Award year

2013

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
MEDICAL IMAGING APPLICATIONS, LLC
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
PA11-097
Topic code
NHLBI

Research abstract

Aortic aneurysms and dissections are a cause of frequently preventable death for over 13,000 people annually in the US alone. Many more patients live under a constant threat of a catastrophic aortic event from atheroscle- rotic or congenital causes. Therefore, early and comprehensive diagnosis of morphological or dynamic changes in the aorta is of great importance. This STTR proposal extends and transfers the technology for quantitative assessment of 3D and 4D aortic image data from MR and MDCT, the resultsof recent NIH-funded research at the University of Iowa, to clinical applicability. No such analyses are currently commercially available for either assessment of connective tissue disorders using MR nor for MDCT-based assessment of atherosclerosis. The proposed project will allow Internet-enabled highly-automated quantitative 4D analysis of the entire aorta from MR/MDCT images for the entire aortic length between the aortic valve and the diaphragm. The following specific aims will be completed in Phase I:Aim 1: Demonstrate the technology transfer feasibility of University of Iowa's basic-research methods for aortic MR and MDCT segmentation and quantitative analysis in 3D and 4D. Build functional comp- onents and specify their interfaces, thus establishing the prerequisites for modularization in Phase II. Aim 2: Develop a 4D segmentation method for lumen and wall of the atherosclerotic thoracic aorta from MDCT by significantly extending our enabling technology, and demonstrate its feasibility. Aim 3: Develop novel indices for MR- and MDCT-based aorta assessment, and new metrics to quantify congenital-disease progression and the effectiveness of surgery or therapy. and in Phase II: Aim 4: Translate the Phase I methods for segmentation of the thoracic aorta from MR and MDCT and quantitative analysis in 3D and 4D to a modular distributed multi-platform processing environment. Aim 5: Develop a distributed prototype of a modular aortic image analysis system, adding communication, payment mechanisms, and security modules as the basis for commercialization. Aim 6: Validate and show the clinical utility of the prototype by (a) full 4D validation using 130 MR/MDCT datasets, (b) extensive testing of performance and ergonomics of the overall system in various deployment scenarios, and (c) design of a patient report and evaluation of its suitability for clinical decision making. As a result, a fully-functional prototype of a distributed Internet-based aortic quantitative image analysis system will be developed and ready for commercialization in the subsequent Phase III. PUBLIC HEALTH RELEVANCE Aortic aneurysms and dissections are a cause of frequently preventable death for over 13,000 people annually in the US alone. Many more patients live under a constant threat of a catastrophic aortic event. Early diagnosis of connective tissue disorders and atherosclerosis, objective monitoring of disease status, and contributing to accurate prediction of disease progression are thus of great importance. Theproposed project will allow distributed Internet- enabled highly-automated quantitative 4D (3D+time) analysis of the entire aorta between the aortic valve and the diaphragm and will thus contribute to objective diagnosis and disease monitoring in patientswith congenital or atheriosclerotic conditions affecting their aortas.

Technology keywords

Not reported

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Agency intelligence

Department of Health and Human Services

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