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Cloud quantitative imaging for whole-body tumor burden in neurofibromatoses

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R41CA192600-01A1
Agency Tracking Number: R41CA192600
Amount: $225,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: 102
Solicitation Number: PA14-072
Timeline
Solicitation Year: 2015
Award Year: 2015
Award Start Date (Proposal Award Date): 2015-05-01
Award End Date (Contract End Date): 2016-12-31
Small Business Information
116 DOUGLAS RD
Belmont, MA 02478-3915
United States
DUNS: 079142619
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 YIN WU
 (617) 489-9871
 yinwu@iqmedicalimaging.com
Business Contact
 YIN WU
Phone: (617) 489-9871
Email: yinwu@iqmedicalimaging.com
Research Institution
 MASSACHUSETTS GENERAL HOSPITAL
 
55 FRUIT STREET
BOSTON, MA 02114-2696
United States

 Domestic Nonprofit Research Organization
Abstract

DESCRIPTION provided by applicant The neurofibromatoses NFs including NF NF and schwannomatosis are a group of autosomal dominant neurogenetic disorders characterized by a predisposition in virtually of patients to develop multiple nerve sheath tumors The determination of tumor burden on magnetic resonance imaging MRI images is crucial for the management of NF patients which is a life long follow up for the monitoring of tumor progression and the assessment of treatment responses However volumetric tumor quantification is not a clinical routine for the longitudinal management of NF patients because of the technical challenges in the accurate and efficient segmentation of highly irregular and infiltrating NF tumors in particular plexiform neurofibromas and the less attention and financial restriction to the development of this specialized software In this project we propose an innovative technical solution cloud quantitative imaging CQI for NF quantification denoted as CQI NF which will provide the volumetric quantification of NF tumors on whole body and regional MRI images via andquot virtualizationandquot cloud computing technology for NF clinics nationwide and worldwide without the high cost to develop and maintain on site advanced quantitative imaging software and hardware This project will be built upon existing technologies for quantitative imaging analysis developed at the D Imaging Lab at Massachusetts General Hospital MGH It will make use of the core technology dynamic thresholding level set DT level set developed by the MGH research team for accurate segmentation of plexiform neurofibromas on MRI images Project collaborators include neuro oncologists specialized in NF management at the MGH NF Clinic musculoskeletal radiologists specialized in NF diagnosis on MRI images and imaging scientists specializing in quantitative imaging analysis from the MGH D Imaging Lab The specific aims of the project are Development of CQI NF system We will develop the prototype CQI NF system on a cloud computing platform including a parallel DT level set method for segmentation of NF tumors on MRI images a cloud based scheme for quantification of NF tumors including segmentation interactive contouring tumor burden analysis visualization and point of care data access for the longitudinal management of NF patients Evaluation of CQI NF system We will retrospectively collect three groups of MRI NF cases including whole body MRI cases at the MGH NF Clinic multiple site cases from our four collaborative NF clinics outside MGH and multiple time cases over the last years at MGH We will conduct a clinical study to evaluate the software accuracy interobserver repeatability cloud interaction performance regional and whole body MRI agreement and software reliability of the proposed CQI NF system Plan of project Phase II Following on this Phase I project we will prepare the Phase II application and plan the software development clinical re evaluation and commercialization in Phase II

PUBLIC HEALTH RELEVANCE The determination of whole body tumor burden is crucial for the management of neurofibromatosis NF patients which is a life long follow up for the monitoring of tumor progression and assessment of treatment responses However the volumetric quantification of NF is not a clinical routine because of the technical challenges in segmentation of NF tumors in particular plexiform neurofibromas and the less attention and financial restriction to the development of this specialized software By using the core technology developed at the MGH D Imaging Lab we propose an innovative technical solution cloud quantitative imaging CQI for NF quantification which will provide the volumetric
quantification of NF tumors on both whole body and regional MRI images via andquot virtualizationandquot cloud computing technology for NF clinics nationwide and worldwide without the high cost to develop and maintain on site advanced quantitative imaging software and hardware

* Information listed above is at the time of submission. *

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