RemedyLogic AI MRI Lumbar Spine Reader
Remedy Logic Inc.The RemedyLogic AI MRI Lumbar Spine Reader is a software tool that automatically analyzes MRI images of the lumbar spine to identify and measure anatomical features. It helps radiologists and spine surgeons by providing quantitative measurements and image segmentations, which can improve the efficiency and accuracy of their analyses and reporting. Users review and adjust the software's outputs before finalizing diagnostic or treatment decisions.
Intended Use
RemedyLogic AI MRI Lumbar Spine Reader is an image post-processing and measurement software tool that provides quantitative spine measurements from previously-acquired DICOM lumbar spine MR images for user review, analysis, and interpretation. It performs feature segmentation, measurement, and exports results in DICOM Structured Report and .docx files to assist in radiology report preparation. Intended for radiologists and spine/neuro-surgeons using MRI on patients 18 or older, excluding those with certain conditions such as pregnancy, contrast scans, post-operative complications, scoliosis, tumors, infections, or fractures.
Technology
The device uses a cloud-based convolutional neural network algorithm running on a GPU cloud service, integrated via an API with the client's PACS system. It processes previously acquired lumbar spine MRI images in DICOM format uploaded by the user, automatically segments anatomical structures, performs quantitative measurements, and exports results back to PACS via DICOM Structured Report and .docx files.
Performance
Performance testing included a standalone software performance study with 200 lumbar spine MRI studies from diverse U.S. sites, comparing software outputs with ground truth established by five radiologists. Results showed measurement accuracy within predefined allowable error limits and segmentation accuracy with mean Dice coefficients above threshold levels. Testing confirmed safety, effectiveness, and compliance with FDA guidance and cybersecurity requirements.
Predicate Devices
No predicate devices specified
Device Timeline
- 1
Submission
4/22/2024
6 months - 2
FDA Approval
10/30/2024
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