MSK-AI software developer ImageBiopsy Lab partners with leading medical device company to support radiologists in faster and more accurate diagnosis of MSK images

The collaboration with GE Healthcare will assist hospitals and research organizations to assess images of patients with musculoskeletal (MSK) disorders more quickly and more precisely. Image Biopsy Lab’s solutions become part of GE Healthcare’s Edison™ Ecosystem, designed to seamlessly integrate artificial intelligence (AI) based clinical applications into the radiology workflow.

ImageBiopsy Lab (IB Lab), the global leader in state-of-the-art AI-based software for image analyses and workflow tasks in MSK radiology, orthopedic surgery, and traumatology, announced today that the company’s solutions are now offered to GE Healthcare’s customers. This partnership between GE Healthcare and IB Lab is to introduce AI-supported MSK image diagnosis to radiologists, orthopedics as well as primary care physicians, making clinically proven AI tools conveniently available directly at the imaging device or via the PACS.

Over 1 billion people worldwide suffering from MSK diseases

Musculoskeletal (MSK) diagnoses are often subjective, inconsistent and time-consuming due to over 1 billion people worldwide suffering from MSK diseases. As an example, Osteoarthritis is a disease that affects almost a fifth of adults 45 years of age or older driving the 140B$ economic burden of OA in the US. It is a paralyzing joint disease that can lead to joint replacement. However, early detection as well as timely therapy can prevent unnecessary surgeries. 100 million knee radiographs are taken every year alone in the US. The low reimbursement of radiographs results in major costs for radiology departments.

This, and the general need to bring MSK-measurements to the digital age, drove IB Lab to change the status quo. The company’s software offers automatization and standardization accelerating and simplifying routine tasks, leaving the physician more time with their patients. Furthermore, it provides quantitative disease parameters to support treatment decisions of the medical experts helping to increase quality within healthcare systems. Assuming IB Labs solutions take one minute to read per radiograph, we can free up to 3 minutes per reading, saving 45 minutes to 1 hour in daily workflow according to a large US based study interviewing 600 radiologists and orthopedic surgeons on their reading behavior.

Michael Gruber, MD specialist in MSK Radiology working in a private practice close to Vienna, Austria used the AI on thousands of cases already: “IB Labs AI-based solutions reduce the amount of work and the findings become more accurate. Objective values are automatically provided on the image and in the report which can be used both for monitoring and forecasting the progress. We offer something that others don’t have.”

IB Lab offers AI-supported software tools for anatomical regions such as the knee (KOALA for detecting knee osteoarthritis), the hand (PANDA for pediatric bone age and developmental assessment), hip (HIPPO for hip angle measurement) and full leg (LAMA for detection of leg length discrepancy, pre and post surgery) while constantly working on additional MSK solutions.

IB Lab’s products have been trained and validated with thousands of cases from various clinical sites across EU and US, thus resulting in AI technology that performs on a level comparable to expert reading in diverse, real-world settings.

“I am delighted that IB Lab’s solutions will be integrated into GE Healthcare’s Edison™ Open AI Orchestrator,” said Richard Ljuhar, CEO of IB Lab. “GE Healthcare’s’ broad customer base means hundreds of thousands of patients with MSK diseases will benefit from the power of our AI solutions.”

All AI solutions are certified to seamlessly integrate  to GE Healthcare Centricity™ PACS and Universal Viewer V7 through their Edison™ Open AI Orchestrator. The medical experts can view the results in GE Healthcare’s DICOM viewer and the visual and structured reports are tailored to seamlessly fit to existing reporting workflows without adding a single click. Ultimately, it is always the expert deciding whether or not to accept the results of the AI-supported software.

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