ImageBiopsy Lab announced it has received clearance from the United States Food and Drug Administration (FDA) for IB Lab LAMA, the first fully-automated radiological image processing software for geometric length and angle measurements of the lower limb on full leg X-rays. The company previously FDA-cleared its IB Lab KOALA Knee-Osteoarthritis Labeling Assistant and intends to expand to the US with further MSK-focused software solutions.
Nearly two million joints are replaced every year worldwide and that number is set to double by the end of the decade. Accurate and standardized measurements to assess the lower leg geometry are critical before and after surgery. However, surgeons are often time constrained due to large caseloads and busy practices. Relieving healthcare professionals of time-consuming and repetitive tasks frees up valuable time for proactive patient consultations and postoperative follow ups.
IB Lab expedites image-based workflows of surgeons and radiologists alike by combining deep learning technology and state of the art software engineering to provide fast, accurate and standardized radiological MSK parameters on X-rays. The measurements are compared to fixed predetermined norm-ranges, based on standard state of the art clinical practices. Outputs are summarized in detailed reports that can be viewed on any cleared medical DICOM viewer.
“FDA clearance serves as a significant validation of the accuracy and quality of our LAMA module. It is a huge milestone to bring AI-supported software tools to surgeons, not only to increase efficiency, but also to improve the outcomes and follow-ups for their patients” said Richard Ljuhar, CEO & co-founder of IB Lab.
Avneesh Chhabra, MD, MBA, FACR, Professor & Chief of the Musculoskeletal Radiology Division at the University of Texas Southwestern (UTSW) in Dallas and Principal Investigator of the Standalone Performance Study: “Artificial intelligence’s potential role in orthopedic surgery is significant. Using deep learning, we aim to support pre- & post-operative decision management, representing a potential key for a more personalized treatment pathway for each patient”.