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SB1MH126825

Project Grant

Overview

Grant Description
Commercialization Readiness of Visual Biofeedback to Reduce Head Motion During MRI Scans - Project Abstract/Summary

The goal of this CRP application is to successfully commercialize a brain MRI technology that feeds back head motion measurements derived from our Framewise Integrated Real-Time MRI Monitoring (FIRMM) software to MRI scan participants in order to reduce head motion via behavioral training.

Because MRI scanning produces high-resolution images and does not expose patients to radiation, it has become an immensely valuable diagnostic tool, particularly for imaging the brain. Last year, in the United States alone, there were over 8 million brain MRIs, costing an estimated $20-30 billion. Unfortunately, brain MRIs are limited by the fact that head motion during the scan can cause the resulting images to be suboptimal or even unusable. An estimated 20% of all brain MRIs are ruined by motion, wasting $2-4 billion annually.

Currently, there are two predominant strategies to combat head motion: repeat scanning and anesthesia, both of which are inadequate. Repeat scanning, which consists of acquiring extra images (to ensure enough usable ones were acquired), increases scanning time and cost, and can result in too few usable images or unnecessary extra images. Anesthesia, which is given to patients who are likely to move (such as young children), presents a serious safety risk and is sometimes administered unnecessarily (i.e. the patient could hold still without anesthesia). Anesthesia is never an option for functional MRI (fMRI), which requires participants to be awake.

The software-based FIRMM-biofeedback solution we developed uses MR images (as they are being collected) to compute a patient's head motion in real time during an MRI scan. The availability of real-time motion information enables more informed anesthesia use and reduces excess scanning, making these methods safer and more efficient. Armed with real-time motion information, scan operators will know exactly how many usable images have been acquired, preventing the acquisition of too many or too few extra images. Additionally, providing physicians with quantitative information about patient motion will allow them to make an informed decision regarding anesthesia, preventing unnecessary sedation.

FIRMM technology provides a completely new biobehavioral method for combating head motion: patient biofeedback. FIRMM can translate the head motion information into age-appropriate, visual biofeedback for the scan participant. By providing feedback to patients and research subjects, the FIRMM-biofeedback technology helps both pediatric and adult patients remain more still, improving image quality.

The proposed research focuses on completing late-stage development for FIRMM-biofeedback, getting ready for commercialization, by building a marketing and reimbursement strategy. The FIRMM-biofeedback technology provides patients and research subjects with real-time head motion information, with the goal of making MR scans safer, faster, more enjoyable, and less expensive.
Funding Goals
THE MISSION OF THE NATIONAL INSTITUTE OF MENTAL HEALTH (NIMH) IS TO TRANSFORM THE UNDERSTANDING AND TREATMENT OF MENTAL ILLNESSES THROUGH BASIC AND CLINICAL RESEARCH, PAVING THE WAY FOR PREVENTION, RECOVERY, AND CURE. IN MAY 2020, NIMH RELEASED ITS NEW STRATEGIC PLAN FOR RESEARCH. THE NEW STRATEGIC PLAN BUILDS ON THE SUCCESSES OF PREVIOUS NIMH STRATEGIC PLANS BY PROVIDING A FRAMEWORK FOR SCIENTIFIC RESEARCH AND EXPLORATION, AND ADDRESSING NEW CHALLENGES IN MENTAL HEALTH. THE NEW STRATEGIC PLAN OUTLINES FOUR HIGH-LEVEL GOALS: GOAL 1: DEFINE THE BRAIN MECHANISMS UNDERLYING COMPLEX BEHAVIORS GOAL 2: EXAMINE MENTAL ILLNESS TRAJECTORIES ACROSS THE LIFESPAN GOAL 3: STRIVE FOR PREVENTION AND CURES GOAL 4: STRENGTHEN THE PUBLIC HEALTH IMPACT OF NIMH-SUPPORTED RESEARCH THESE FOUR GOALS FORM A BROAD ROADMAP FOR THE INSTITUTE'S RESEARCH PRIORITIES OVER THE NEXT FIVE YEARS, BEGINNING WITH THE FUNDAMENTAL SCIENCE OF THE BRAIN AND BEHAVIOR, AND EXTENDING THROUGH EVIDENCE-BASED SERVICES THAT IMPROVE PUBLIC HEALTH OUTCOMES. THE INSTITUTE'S OVERALL FUNDING STRATEGY IS TO SUPPORT A BROAD SPECTRUM OF INVESTIGATOR-INITIATED RESEARCH IN FUNDAMENTAL SCIENCE, WITH INCREASING USE OF INSTITUTE-SOLICITED INITIATIVES FOR APPLIED RESEARCH WHERE PUBLIC HEALTH IMPACT IS A SHORT-TERM MEASURE OF SUCCESS. THE NEW STRATEGIC PLAN ALSO ADDRESSES A NUMBER OF CROSS-CUTTING THEMES THAT ARE RELEVANT TO ALL RESEARCH SUPPORTED BY NIMH, THESE THEMES HIGHLIGHT AREAS WHERE NIMH-FUNDED SCIENCE MAY HAVE THE GREATEST IMPACT, BRIDGE GAPS, AND OFFER NOVEL APPROACHES TO ACCELERATE ADVANCES IN MENTAL HEALTH RESEARCH. FOR EXAMPLE, NIMH VALUES A COMPREHENSIVE RESEARCH AGENDA THAT TAKES AN INCLUSIVE APPROACH THAT ENSURES RESEARCH INTERESTS ARE VARIED, MAINTAIN DIVERSE PARTICIPATION AND PARTNERSHIPS, AND ACHIEVE RESEARCH GOALS ACROSS MULTIPLE TIMEFRAMES. THIS INCLUDES DIVERSE METHODOLOGIES, TOOLS, AND MODELS, RESEARCH ADDRESSING COMPLEX BASIC, TRANSLATIONAL, AND APPLIED QUESTIONS, RESEARCH INCLUDING BOTH SEXES AND, AS APPROPRIATE, GENETIC BACKGROUND, AND, PARTICIPANTS FROM DIVERSE RACIAL AND ETHNIC BACKGROUNDS, AND ACROSS GENDER IDENTITIES, GEOGRAPHICAL CONTEXT, SOCIOECONOMIC STATUS, NEUROTYPE, AND AGE OFFERING THE BEST POSSIBLE REPRESENTATION, FOR THE BROADEST NUMBER OF INDIVIDUALS WHO MAY ULTIMATELY BENEFIT FROM THESE SCIENTIFIC ADVANCES. TO ACCOMPLISH THE GOALS OUTLINED IN THE NEW STRATEGIC PLAN, NIMH WILL SUPPORT RESEARCH THAT AIMS: TO CHARACTERIZE THE GENOMIC, MOLECULAR, CELLULAR, AND CIRCUIT COMPONENTS CONTRIBUTING TO BRAIN ORGANIZATION AND FUNCTION, TO IDENTIFY THE DEVELOPMENTAL, FUNCTIONAL, AND REGULATORY MECHANISMS RELEVANT TO COGNITIVE, AFFECTIVE, AND SOCIAL DOMAINS, ACROSS UNITS OF ANALYSIS, AND, TO GENERATE AND VALIDATE NOVEL TOOLS, TECHNIQUES, AND MEASURES TO QUANTIFY CHANGES IN THE ACTIVITY OF MOLECULES, CELLS, CIRCUITS, AND CONNECTOMES. TO DISCOVER GENE VARIANTS AND OTHER GENOMIC ELEMENTS THAT CONTRIBUTE TO THE DEVELOPMENT OF MENTAL ILLNESSES IN DIVERSE POPULATIONS, TO ADVANCE OUR UNDERSTANDING OF THE COMPLEX ETIOLOGY OF MENTAL ILLNESSES USING MOLECULAR EPIDEMIOLOGIC APPROACHES THAT INCORPORATE INDIVIDUAL GENETIC INFORMATION IN LARGE COHORTS, TO ELUCIDATE HOW HUMAN GENETIC VARIATION AFFECTS THE COORDINATION OF MOLECULAR, CELLULAR, AND PHYSIOLOGICAL NETWORKS SUPPORTING HIGHER-ORDER FUNCTIONS AND EMERGENT PROPERTIES OF NEUROBIOLOGICAL SYSTEMS, AND, TO DEVELOP NOVEL TOOLS AND TECHNIQUES FOR THE ANALYSIS OF LARGE-SCALE GENETIC, MULTI-OMIC DATA AS IT APPLIES TO MENTAL HEALTH. TO UTILIZE CONNECTOMIC APPROACHES TO IDENTIFY BRAIN NETWORKS AND CIRCUIT COMPONENTS THAT CONTRIBUTE TO VARIOUS ASPECTS OF MENTAL FUNCTION AND DYSFUNCTION, TO DETERMINE THROUGH BRAIN-WIDE ANALYSIS HOW CHANGES IN THE PHYSIOLOGICAL PROPERTIES OF MOLECULES, CELLS, AND CIRCUITS CONTRIBUTE TO MENTAL ILLNESSES, TO DEVELOP MOLECULAR, CELLULAR, AND CIRCUIT-LEVEL BIOMARKERS OF IMPAIRED NEURAL FUNCTION IN HUMANS, AND, TO DEVELOP INNOVATIVE TECHNOLOGIES, INCLUDING NEW IMAGING, COMPUTATIONAL, PHARMACOLOGICAL, AND GENETIC TOOLS TO INTERROGATE AND MODULATE CIRCUIT ACTIVITY AND STRUCTURE ALTERED IN MENTAL ILLNESSES. TO ELUCIDATE THE MECHANISMS CONTRIBUTING TO THE TRAJECTORIES OF BRAIN DEVELOPMENT AND BEHAVIOR, AND, TO CHARACTERIZE THE EMERGENCE AND PROGRESSION OF MENTAL ILLNESSES, AND IDENTIFYING SENSITIVE PERIODS FOR OPTIMAL INTERVENTION. TO DETERMINE EARLY RISK AND PROTECTIVE FACTORS, AND RELATED MECHANISMS, TO SERVE AS NOVEL INTERVENTION GROUPS, AND, TO DEVELOP RELIABLE AND ROBUST BIOMARKERS AND ASSESSMENT TOOLS TO PREDICT ILLNESS ONSET, COURSE, AND ACROSS DIVERSE POPULATIONS. TO DEVELOP NOVEL INTERVENTIONS USING A MECHANISM-INFORMED, EXPERIMENTAL THERAPEUTICS APPROACH, AND, TO DEVELOP AND IMPLEMENT MEASUREMENT STRATEGIES TO FACILITATE MECHANISM-BASED INTERVENTION DEVELOPMENT AND TESTING. TO INVESTIGATE PERSONALIZED INTERVENTION STRATEGIES ACROSS DISEASE PROGRESSION AND DEVELOPMENT, AND, TO DEVELOP AND REFINE COMPUTATIONAL APPROACHES AND RESEARCH DESIGNS THAT CAN BE USED TO INFORM AND TEST PERSONALIZED INTERVENTIONS. TO DEVELOP AND TEST APPROACHES FOR ADAPTING, COMBINING, AND SEQUENCING INTERVENTIONS TO ACHIEVE THE GREATEST IMPACT ON THE LIVES AND FUNCTIONING OF PERSONS SEEKING CARE, TO CONDUCT EFFICIENT PRAGMATIC TRIALS THAT EMPLOY NEW TOOLS TO RAPIDLY IDENTIFY, ENGAGE, ASSESS, AND FOLLOW PARTICIPANTS IN THE CONTEXT OF ROUTINE CARE, AND, TO ENHANCE THE PRACTICAL RELEVANCE OF EFFECTIVENESS RESEARCH VIA DEPLOYMENT-FOCUSED, HYBRID, EFFECTIVENESS-IMPLEMENTATION STUDIES. TO EMPLOY ASSESSMENT PLATFORMS WITHIN HEALTHCARE SYSTEMS TO ACCURATELY ASSESS THE DISTRIBUTION AND DETERMINANTS OF MENTAL ILLNESSES AND TO INFORM STRATEGIES FOR IMPROVED SERVICES, TO OPTIMIZE REAL-WORLD DATA COLLECTION SYSTEMS TO IDENTIFY STRATEGIES FOR IMPROVING ACCESS, QUALITY, EFFECTIVENESS, AND CONTINUITY OF MENTAL HEALTH SERVICES, AND, TO COMPARE ALTERNATIVE FINANCING MODELS TO PROMOTE EFFECTIVE AND EFFICIENT CARE FOR INDIVIDUALS WITH SERIOUS EMOTIONAL DISTURBANCES AND SERIOUS MENTAL ILLNESSES. TO STRENGTHEN PARTNERSHIPS WITH KEY STAKEHOLDERS TO DEVELOP AND VALIDATE STRATEGIES FOR IMPLEMENTING, SUSTAINING, AND CONTINUOUSLY IMPROVE EVIDENCE-BASED PRACTICES, TO BUILD MODELS TO SCALE-UP EVIDENCE-BASED PRACTICES FOR USE IN PUBLIC AND PRIVATE PRIMARY CARE, SPECIALTY CARE AND OTHER SETTINGS, AND, TO DEVELOP DECISION-SUPPORT TOOLS AND TECHNOLOGIES THAT INCREASE THE EFFECTIVENESS AND CONTINUOUS IMPROVEMENT OF MENTAL HEALTH INTERVENTIONS IN PUBLIC AND PRIVATE PRIMARY CARE, SPECIALTY CARE, AND OTHER SETTINGS. TO ADAPT, VALIDATE, AND SCALE-UP PROGRAMS CURRENTLY IN USE THAT IMPROVE MENTAL HEALTH SERVICES FOR UNDERSERVED POPULATIONS, TO DEVELOP AND VALIDATE SERVICE DELIVERY MODELS THAT PROVIDE EVIDENCE-BASED CARE FOR INDIVIDUALS THROUGHOUT THE COURSE OF MENTAL ILLNESS, TO DEVELOP AND VALIDATE SYSTEMS-LEVEL STRATEGIES USING TECHNOLOGY AND OTHER APPROACHES, TO IDENTIFY, SUPPORT, AND MONITOR THE EFFECTIVENESS OF EVIDENCE-BASED CARE THROUGHOUT THE COURSE OF ILLNESS, AND, TO DEVELOP AND VALIDATE DECISION-MAKING MODELS THAT BRIDGE MENTAL HEALTH, MEDICAL, AND OTHER CARE SETTINGS TO INTEGRATE THE APPROPRIATE CARE FOR PEOPLE WITH SERIOUS MENTAL ILLNESSES AND COMORBID MEDICAL CONDITIONS.
Place of Performance
Missouri United States
Geographic Scope
State-Wide
Analysis Notes
Amendment Since initial award the End Date has been extended from 11/30/24 to 11/30/25 and the total obligations have increased 201% from $1,136,868 to $3,421,062.
Turing Medical Technologies was awarded Commercializing Visual Biofeedback Head Motion Reduction in MRI Scans Project Grant SB1MH126825 worth $3,421,062 from the National Institute of Mental Health in December 2021 with work to be completed primarily in Missouri United States. The grant has a duration of 4 years and was awarded through assistance program 93.242 Mental Health Research Grants. The Project Grant was awarded through grant opportunity SBIR/STTR Commercialization Readiness Pilot (CRP) Program Technical Assistance and Late Stage Development (SB1, Clinical Trial Not Allowed).

SBIR Details

Research Type
SBIR Phase II
Title
Commercialization readiness of visual biofeedback to reduce head motion during MRI scans
Abstract
Project Abstract/SummaryThe goal of this CRP application is to successfully commercialize a brain MRI technology that feeds back head motion measurements derived from our Framewise Integrated Real-Time MRI Monitoring (FIRMM) software to MRI scan participants in order to reduce head motion via behavioral training. Because MRI scanning produces high-resolution images and does not expose patients to radiation, it has become an immensely valuable diagnostic tool, particularly for imaging the brain. Last year, in the United States alone, there were over 8 million brain MRIs, costing an estimated $20-30 billion. Unfortunately, brain MRIs are limited by the fact that head motion during the scan can cause the resulting images to be suboptimal or even unusable. An estimated 20% of all brain MRIs are ruined by motion, wasting $2-4 billion annually. Currently, there are two predominant strategies to combat head motion: repeat scanning and anesthesia, both of which are inadequate. Repeat scanning, which consists of acquiring extra images (to ensure enough usable ones were acquired), increases scanning time and cost, and can result in too few usable images or unnecessary extra images. Anesthesia, which is given to patients who are likely to move (such as young children), presents a serious safety risk and is sometimes administered unnecessarily (i.e. the patient could hold still without anesthesia). Anesthesia is never an option for functional MRI (fMRI), which requires participants to be awake.The software-based FIRMM-biofeedback solution we developed uses MR images (as they are being collected) to compute a patient’s head motion in real time during an MRI scan. The availability of real time motion information enables more informed anesthesia use and reduce excess scanning, making these methods safer and more efficient. Armed with real time motion information, scan operators will know exactly how many usable images have been acquired, preventing the acquisition of too many or too few extra images. Additionally, providing physicians with quantitative information about patient motion will allow them to make an informed decision regarding anesthesia, preventing unnecessary sedation.FIRMM technology provides a completely new biobehavioral method for combating head motion: patient biofeedback. FIRMM can translate the head motion information into age-appropriate, visual biofeedback for the scan participant. By providing feedback to patients and research subjects, the FIRMM- biofeedback technology helps both pediatric and adult patients remain more still, improving image quality. The proposed research focuses on completing late-stage development for FIRMM-biofeedback getting ready for commercialization, by building a marketing and reimbursement strategy. The FIRMM-biofeedback technology provides patients and research subjects with real time head motion information, with the goal of making MR scans safer, faster, more enjoyable and less expensive.
Topic Code
NIMH
Solicitation Number
PAR20-129

Status
(Ongoing)

Last Modified 3/20/25

Period of Performance
12/1/21
Start Date
11/30/25
End Date
99.0% Complete

Funding Split
$3.4M
Federal Obligation
$0.0
Non-Federal Obligation
$3.4M
Total Obligated
100.0% Federal Funding
0.0% Non-Federal Funding

Activity Timeline

Interactive chart of timeline of amendments to SB1MH126825

Transaction History

Modifications to SB1MH126825

Additional Detail

Award ID FAIN
SB1MH126825
SAI Number
SB1MH126825-2498138654
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Small Business
Awarding Office
75N700 NIH National Institute of Mental Health
Funding Office
75N700 NIH National Institute of Mental Health
Awardee UEI
DXK7YWNEZEL4
Awardee CAGE
87D22
Performance District
MO-90
Senators
Joshua Hawley
Eric Schmitt

Budget Funding

Federal Account Budget Subfunction Object Class Total Percentage
National Institute of Mental Health, National Institutes of Health, Health and Human Services (075-0892) Health research and training Grants, subsidies, and contributions (41.0) $2,273,736 100%
Modified: 3/20/25