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Increasing Interoperability of Brain Morphometrics Using FHIR

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R43EB030910-01A1
Agency Tracking Number: R43EB030910
Amount: $149,500.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: NIBIB
Solicitation Number: PA20-260
Timeline
Solicitation Year: 2020
Award Year: 2021
Award Start Date (Proposal Award Date): 2021-09-30
Award End Date (Contract End Date): 2022-03-31
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
 LEE TIRRELL
 (617) 959-1896
 ltirrell@corticometrics.com
Business Contact
 NICHOLAS SCHMANSKY
Phone: (617) 959-1896
Email: nicks@corticometrics.com
Research Institution
N/A
Abstract

PROJECT SUMMARY
With the rise of artificial intelligence (AI) algorithms in medicine, radiologists have new tools at their disposal to
quantitatively assess imaging data. However, in order to unlock this potential, data needs to be shared easily
and effectively between all parts of the health information technology (IT) system. The goal of this project is to
reduce data access barriers by developing software to cleanly integrate medical imaging data stored in a
radiology department’s picture archiving and communication systems (PACS) with the rest of patients’
electronic health record (EHR) using the Fast Healthcare Interoperability Resources (FHIR®) standard.
CorticoMetrics will use our THINQ™ software as a medical device (SaMD) product to provide brain
morphometrics derived from MR imaging data, and extend its functionality to output results in both Digital
Imaging and Communications in Medicine structured reporting (DICOM-SR) and Health Level 7 Fast
Healthcare Interoperability Resources (HL7 FHIR) compliant formats. Based off of the scientifically validated
FreeSurfer suite of automated neuroimaging analysis software, THINQ provides measurements of brain
structures that can aid in the care of neurological conditions such as Alzheimerandapos;s disease and dementia,
traumatic brain injury, epilepsy, hydrocephalus, Parkinsonandapos;s disease and multiple sclerosis. Output in FHIR and
DICOM-SR formats will be validated and included in CorticoMetrics’ next FDA 510(k) submission of THINQ.
Incorporating this information with the rest of the rest of a patient’s EHR will enable a seamless workflow for
clinicians to make decisions more efficiently and accurately while also improving the performance of those with
less experience.
This project will develop and disseminate an open source software tool to interconvert neuroimaging data
between formats used in academic settings (such as FreeSurfer’s MGH or Neuroimaging Informatics
Technology Initiative (NIfTI)) with the standard formats used in health care settings (DICOM and FHIR).
Common Data Elements (CDE) will be used to facilitate data sharing across studies where appropriate. The
product will lead to an increase in interoperability of brain morphometrics, giving medical professionals access
to key data directly in the EHR. While THINQ will serve as an initial use case of this technology, the conversion
tool will be easily extensible to other use cases, and freely available to developers of the next generation of
quantitative imaging software.PROJECT NARRATIVE
The proposed project will develop software using the Fast Healthcare Interoperability Resources (FHIR®)
standard to integrate quantitative assessment of brain MRI data from CorticoMetrics’ THINQ™ software as a
medical device (SaMD) product into existing clinical workflows. FHIR application programming interfaces
(APIs) enable seamless connection of medical imaging data and metadata stored in a picture archiving and
communication system (PACS) with the rest of patients’ electronic health record (EHR), giving radiologists
more information for earlier and more accurate assessment of changes in brain structure that occur in many
neurological conditions such as Alzheimerandapos;s disease and dementia, traumatic brain injury, epilepsy,
hydrocephalus, Parkinsonandapos;s disease and multiple sclerosis. The resulting efforts will lead to the standalone
release of open source tools, enhancing the ability to share data within and between health information
systems and leading to improved quality of care and reduction in radiology report turnaround time.

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

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