Project Details
Description
Project Abstract/Summary
The goal of this STTR application is to deliver a brain MRI technology that feeds back head motion
measurements derived from our Framewise Integrated Real-Time MRI Monitoring (FIRMM) 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 proposed in this grant 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 will enable 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.
The proposed solution focuses on a completely new biobehavioral method for combating head motion: subject
biofeedback. The technology 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 delivering proof-of-concept for FIRMM-biofeedback (Phase I) and building and
validating a product version of FIRMM-biofeedback (Phase II). 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.
Status | Finished |
---|---|
Effective start/end date | 9/11/19 → 5/31/23 |
Funding
- National Institute of Mental Health: $1,549,171.00
- National Institute of Mental Health: $966,084.00
- National Institute of Mental Health: $1,825,319.00
- National Institute of Mental Health: $1,519,212.00
- National Institute of Mental Health: $291,100.00
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