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ScanDiags Ortho L-Spine MR-Q software is an image-processing and measurement software tool that provides quantitative spine measurements from previously-acquired DICOM lumbar spine Magnetic Resonance (MR) images for users' review, analysis, and interpretation. It provides the following functionality to assist users in visualizing, and documenting area and distance measurements of relevant anatomical structures (vertebral body, intervertebral disc, neuroforamina, thecal sac) of the lumbar spine: Feature Segmentation; Feature measurement; and Export of measurement results to a PDF report containing measurement results and overlay images for user's review, revise and approval. ScanDiags Ortho L-Spine MR-Q software does not produce or recommend any type of medical diagnosis or treatment. Instead, it simply helps users to more easily identify and classify features in lumbar MR images and compile a report. The user is responsible for reviewing and verifying the software-generated measurements and approving draft report content using their medical judgment and discretion. The device is intended to be used only by hospitals and other medical institutions. Only DICOM images of MRI acquired from lumbar spine exams of patients aged 22 and above are considered to be valid input. ScanDiags Ortho L-Spine MR-Q software does not support DICOM images of patients that are pregnant, undergo MRI scan with contrast media, have post-operational complications or infections.

ScanDiags Ortho L-Spine MR-Q software is a software as a medical device (SaMD) intended for visualization, and quantification of lumbar spine anatomical structures including vertebral bodies, intervertebral discs, neuroforamina, thecal sacs from a set of standard lumbar spine MRI images in DICOM (Digital Imaging and Communications in Medicine) format. The semi-automatic segmentation of these structures forms the bases for the distance and area measurement outputs. The software has features for log-in, viewing, revising, and saving measurement results in addition to generating PDF reports. The PDF report includes images, measurements. ScanDiags Ortho L-Spine MR-Q software includes a viewing application (ScanDiags DICOM Viewer) to visualize, review, and apply corrections to the measurement results shown as overlay on the original lumbar spine MRI images. Pre-existing MR images of the lumber spine are uploaded into the software for analysis. The semi-automatic segmentations are based on deep convolutional neural networks (DCNN) which are developed by applying well-established supervised deep learning methods on unstructured MRI scans (DICOM image format). ScanDiags Ortho L-Spine MR-Q combines deep learning, image analysis, as well as regression-based machine methods. The segmentations and distance measurements are user modifiable. Results are reviewed and approved by the radiologist's user before a PDF report is generated. Once approved, the result PDF report is sent to the clinician's PACS system. The PACS system stores the PDF report within the corresponding patient MRI study. ScanDiags Ortho L-Spine MR-Q does not interface directly with any MR or data collection equipment; instead, the software uploads data files previously generated by such equipment. Its functionality is independent of the vendor type of the acquisition equipment. The analysis results are available on the ScanDiags DICOM Viewer screen and can be edited, saved, and approved. The approved measurement results are sent back to the PACS system as a Measurement Result PDF Report. The software does not perform any functions that could not be accomplished by a trained user with manual tracing methods; the purpose of the software is to save time and automate the tedious manual task of segmentation and distance measurement. ScanDiags Ortho L-Spine MR-Q software is an adjunct tool and is not intended to replace a radiologist's review of the MRI study, nor is it intended to replace his or her clinical judgment, and it does not detect, diagnose or identify any abnormalities. Radiologists must not use the generated output as a primary interpretation.