Rho is a machine learning software that analyzes standard frontal x-rays of various body parts in patients aged 50 and older to identify possible low bone mineral density. It helps radiologists by generating reports suggesting patients who may benefit from further clinical bone health assessment, thereby assisting in early detection and management of bone health issues.
Rho is a software application intended for use opportunistically with standard frontal radiographs of the lumbar spine, thoracic spine, chest, pelvis, knee, or hand/wrist performed in patients aged 50 years and older to aid in identifying possible low bone mineral density (BMD) at L1-L4 or the femoral neck to prompt a clinical assessment of bone health.
Rho is a machine learning-based software integrated with PACS that uses patient age, sex, and frontal X-ray DICOM images to estimate BMD at femoral neck or lumbar vertebrae with a locked algorithm trained on patient data. It outputs a binary classification and generates a report for clinical use.
Clinical performance was evaluated retrospectively using multiple datasets with paired DXA (gold standard) comparison showing high specificity (~0.90+) but moderate to low sensitivity. The device met performance goals for specificity and AUC but had lower sensitivity in some subgroups and datasets. Postmarket monitoring is planned to assess real-world generalizability.
Submission
4/3/2023
FDA Approval
4/9/2024
Join hundreds of your peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.
We respect your privacy. Unsubscribe at any time.