Spine Case report



Magnetic Resonance Imaging (MRI) is a non-invasive radiologic examination which does not produce ionizing radiation like X-ray imaging and Computed Tomography (CT). Due to superior soft tissue contrast and image resolution, MR is an important part of clinical practice in making accurate diagnosis, monitoring therapeutic response, and follow-ups. Despite these advantages, however, MR exams typically require long scan times – limiting its use compared to other modalities. To this effect, numerous research and technical developments are now focused on reducing the scan time to increase scanner efficiency and improving the patient experience.

SwiftMR™ is FDA 510(k)-cleared* deep learning (DL)-based software medical device developed by AIRS Medical. SwiftMR™ reduces image noise and increases sharpness of MR images based on its vast training dataset of high-quality MR images.

The following clinical cases were collected from research conducted at Seoul National University Hospital (Seoul, Korea). This study was approved by the institutional review board (IRB) and informed consents were received from all enrolled patients. The purpose of this study was to clinically evaluate the quality of spine (C-Spine, L-Spine) images processed with SwiftMR™, where input images were acquired at were acquired under reduced scan time compared to the institutional conventional. To do this, images were acquired from enrolled patients using both conventional and faster scan protocol, then images were compared after applying SwiftMR™ to the latter.


* FDA 510(k)-cleared for Standard of Care (SOC) and reduced scan time MR images for all body parts. Supported field strength may vary by country.