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AutoRegister: A system for enhancing the accuracy of tumor change detection

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 2R42CA183150-02
Agency Tracking Number: R42CA183150
Amount: $1,500,000.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: 102
Solicitation Number: PA15-270
Timeline
Solicitation Year: 2015
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-04-01
Award End Date (Contract End Date): 2020-03-31
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.wighton@gmail.com
Business Contact
 NICHOLAS 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
This project proposes to continue the development of AutoRegisterTMan integrated software based system for
enhancing the accuracy of tumor change detectionThe intent of the system is to automate the alignment of a
patient s brain scan with that of a prior scan such that subsequent offline tumor measurements do not have
error introduced solely by differing slice orientationsWhile similar to current technologiessuch as Siemens
AutoAlignthe proposed technology is not sensitive to the inherent noise of such genericlandmark based
techniquesAutoRegisterTM exemplifies personalized medicineit uses the patient s previous data as its own
referenceAdditionallythe proposed technology is based upon a novel registration algorithm that is robust to
atypical anatomysuch as a tumorwhich often adversely affects techniques such as AutoAlignIn the United Statesthere are an estimateddeaths per year due to tumors in the primary central
nervous systemStandard and experimental therapies rely on accurate measurement of tumor size change to
assess treatment response and guide clinical decision making during treatment and clinical trialsThe project will continue to translate existing technology developed by CorticoMetrics and the Martinos Center
for Biomedical Imaging at the Massachusetts General HospitalMGHOur objectives are tocreate a
commercial readyand regulatory compliantsoftware medical device based on work conducted in Phase Ifurther develop our reference integration with Siemens MRI scanners for validationdemonstration and
research purposesandcontinue to gather validation data with the ongoing assistance of Phase I
collaborators conducting imaging of glioblastoma patientsand by establishing new collaborationsAutoRegisterTM employs a novelD MR image registration algorithm designed by advisors DrsReuter and
Fischlwhich achieves highly accurate alignment both within subject and within modalityand ignores brainimaging voxels for which no feasible matches exists due to inherent changessuch as tumor tissue and
surrounding localized mass or edema effectsThe co PI on the projectDrvan der Kouweis a renowned MRI
head motion correction expert and is the original creator of SiemensAutoAlignthe closest competitor to the
CorticoMetricsAutoRegisterTM system

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

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