The goal of this SBIR/STTR application is to deliver a technology that accurately and non-invasively measures a patient?s head motion during a structural magnetic resonance imaging (MRI) scan (Framewise Integrated Real-Time MRI Monitoring -structural [FIRMM-s]). Because structural 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). The software-based FIRMM-s 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 also contains an entirely new method for combating head motion: patient biofeedback. The technology can translate the head motion information into age-appropriate, visual biofeedback for the patient. By providing feedback to patients, the technology helps both pediatric and adult patients remain more still, improving image quality. The proposed research focuses on delivering proof-of-concept for FIRMM-s (Phase I) and building and validating a clinical-ready version of FIRMM-s (Phase II). The FIRMM-s device provides scan operators, physicians, and patients with real time motion information, with the goal of making MR scans safer, faster, and less expensive.
Magnetic resonance imaging (MRI) has unrivaled clinical utility, is non-invasive, and provides extremely high spatial resolution; however, MRIs have one severe limitation: patient motion during an MRI scan diminishes the quality of the resulting images. Despite this fact, motion is not currently monitored during clinical MRI scans. The goal of this application is to develop an accurate and non-invasive software-based solution for monitoring patient motion during structural brain MRIs.
