SBIR/STTR Research Award

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

Award identifier 26a3586e9d18b308bb0eda2b14c878ee50742df964b43dc876e3ad586e286ca1Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,500,000

Program and phase

STTR · Phase II

Award year

2017

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
CORTICOMETRICS LLC
Proposal award date
2017-04-01
Contract end date
2020-03-31
UEI
WQ9CMMLAWGB5
Solicitation number
PA15-270
Topic code
102

Research 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

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.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

10 SBIR/STTR records share this UEI (2013–2021). Reported award amounts total $7,380,343. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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