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Unbiased longitudinal neuromorphometry for clinical decision support

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R42AG062026-01A1
Agency Tracking Number: R42AG062026
Amount: $224,843.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: NIA
Solicitation Number: PAS18-188
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-07-01
Award End Date (Contract End Date): 2020-06-30
Small Business Information
100 CAPTAINS ROW, APT. 108
Chelsea, MA 02150-4021
United States
DUNS: 078509164
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 PAUL WIGHTON
 (617) 230-4172
 paul@corticometrics.com
Business Contact
 NICK SCHMANSKY
Phone: (617) 959-1896
Email: nicks@corticometrics.com
Research Institution
 MASSACHUSETTS GENERAL HOSPITAL
 
55 FRUIT STREET
BOSTON, MA 02114-2696
United States

 Domestic Nonprofit Research Organization
Abstract

Project Summary Normal human neuroanatomy is incredibly variableand increases with ageThis impedes the ability of neuroimaging to detect effects in neurological conditions such as Alzheimerandapos s diseaseADHuntingtonandapos s diseaseHDmultiple sclerosisMSand schizophreniaMost of the recently available state of the art quantitative imaging tools still use cross sectional methods to analyze repeated scansThese tools lack the sensitivity to monitor subtle progressive changes because such approaches do not account for the large intrinsic variability of normal neuroanatomyThe goal of this project is to commercialize a longitudinalneuro morphometric image processing pipeline for use in radiologyneurology and related clinical fieldsThe successful completion of this project will result in a clinically useful neuro morphometric longitudinal analysis stream with more statistical power than is currently available commerciallyThis increase in power will directly translate into an enhanced ability to detect and assess progression at both the individual and group levelsIt will also alleviate a major pain point in current longitudinal neuroradiology reading workflowsreducing radiology report turnaround timesRTATProject Narrative The proposed project will develop software to help clinicians quantitatively assess and interpret changes in brain MRI data in a way that integrates seamlessly into an existing clinical workflowIt will help radiologists detect changes to brain structures earlier and more accuratelyin neurological conditions such as Alzheimerandapos s diseaseADHuntingtonandapos s diseaseHDmultiple sclerosisMSand schizophreniaThe resulting efforts will translate into an enhanced ability to detect and assess disease progressionand reduce radiology report turnaround time

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

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