Phase I Amount
$1,136,868
The goal of this CRP application is to successfully commercialize a brain MRI technology that feedsback 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 MRIscanning produces high-resolution images and does not expose patients to radiation, it has become animmensely 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 limitedby the fact that head motion during the scan can cause the resulting images to be suboptimal or evenunusable. 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 whichare inadequate. Repeat scanning, which consists of acquiring extra images (to ensure enough usable oneswere acquired), increases scanning time and cost, and can result in too few usable images or unnecessaryextra images. Anesthesia, which is given to patients who are likely to move (such as young children), presentsa serious safety risk and is sometimes administered unnecessarily (i.e. the patient could hold still withoutanesthesia). 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 beingcollected) to compute a patient's head motion in real time during an MRI scan. The availability of real timemotion information enables more informed anesthesia use and reduce excess scanning, making thesemethods safer and more efficient. Armed with real time motion information, scan operators will know exactlyhow 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 aninformed 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, visualbiofeedback 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. Theproposed research focuses on completing late-stage development for FIRMM-biofeedback getting ready forcommercialization, by building a marketing and reimbursement strategy. The FIRMM-biofeedback technologyprovides patients and research subjects with real time head motion information, with the goal of making MRscans safer, faster, more enjoyable and less expensive.
Public Health Relevance Statement: Project Narrative Magnetic resonance imaging (MRI) has unrivaled clinical and research utility, is non-invasive, and provides extremely high spatial resolution, however, MRIs have an Achilles heel: subject motion during scanning greatly diminishes the quality of the resulting images. We have developed software (FIRMM) that allows for non- invasive monitoring and reduction of subject motion during brain MRIs. In this proposal we complete late-stage development and commercialization readiness preparations to bring 510(k) FDA-cleared FIRMM into clinical practice.
Project Terms: <21+ years old><0-11 years old>
