AI for Bone Disease Diagnostics Assessed by Top Clinic

One of the most advanced AI-based image analysis platforms for bone disease diagnostics will get rolled out at the radiology and orthopedic departments of the University Hospital of the Ludwig-Maximilian University Munich (LMU Hospital), Germany. The innovative analysis tool is already in clinical use at several other medical and academic institutions throughout the EU and US. The AI based platform allows for standardized, effective and precise
assessment of chronic musculoskeletal (MSK) diseases for pediatric and adult patients, offering a range of modules that are optimized for
specific bone systems of the body such as knee, hip, hand, spine and others. Several units at the LMU Hospital will now access the AI to optimize diagnosis with a focus on different patient populations as well as jointly optimize specific diagnosis aspects.

Worldwide, more people suffer from musculoskeletal diseases than of the circulatory or respiratory system. Despite the hundreds of millions of patients, common diagnosis methods seem to be stuck in the 20th century. Physical interpretation of x-rays or MRT-images by trained experts is still the norm. Subjective and time consuming, these methods are not standardized and accuracies depend on individual competences. The AI-based MSK-focused platform developed by ImageBiopsy Lab (IB Lab) offers a novel way to translate imaging data efficiently into objective, structured health information. Now, the section of Musculoskeletal Imaging and the Clinic for Orthopedics, Physical Medicine and Rehabilitation at the LMU Hospital joins a growing number of medical and academic institutions in Europe and the US that deploys the AI and validate its use in clinical settings.

IB Lab’s platform, named IB Lab ZOO, has been trained since 2016 and millions of images of bone and joint anatomies have been used to train and validate the MSK-AI software. “We have established collaborations with leading experts with excellent domain knowledge on specific bone and joint diseases and their diagnosis, connecting the world of radiology and orthopedics”, explains Dr. Richard Ljuhar, CEO and Co-founder of IB Lab. Indeed, LMU Hospital and IB Lab now signed a multi-year collaboration agreement giving LMU Hospital access to several of IB ZOO modules for clinical and research use and IB Lab in turn access to leading domain expertise, especially for pediatric and orthopedic innovations. Also, both partners will engage in joint research projects that will help to further advance the software.

Dr. med. Paul Reidler, Head of Musculoskeletal Imaging at LMU Hospital on the cooperation: “The solutions of IB Lab deliver highly accurate and clinically relevant results that make real impact in pediatric and MSK radiology. We are enthusiastic to use their AI tools to explore research opportunities with orthopedic and pediatric colleagues as well as to further optimize our established osteoporosis care pathways.» Dr. med. Felix Endres, orthopedic surgeon at LMU Hospital adds: “Leveraging standardized image and patient datasets can be now enriched with IB Lab’s radiomics data to discover impactful new clinical insights. The combination of excellent MSK radiology, data driven orthopedics and the AI tools are an ideal fit to create impactful discovery and care.”

For this specific deployment, IB Lab will expand its partnership with the Munich-based AI integrator deepc GmbH, an universal connector and strong technical partner for future hospital network integrations. Through advanced AI-technology provided by deepc, all modules of the IB Lab ZOO integrate seamlessly in existing imaging workflows.  After image acquisition, an automated screening process checks for correct image parameters and positioning. “And it is thereafter that the real power of our AI fully kicks in”, Dr. Ljuhar explains. “Based on millions of datasets and machine learning algorithms, IB Lab modules such as PANDA for bone age assessments or FLAMINGO for detection & quantification of silent vertebral fractures in the spine now extract complex information from those images. This includes bone length, angles, joint head coverage and other clinical scores that are instantaneously assessed.” However, depending on the required information, other end-users such as insurances, pharma and research companies or digital health services may benefit from such structured (anonymized) information, too.

IB Lab establishes world-wide collaborations with clinicians and scientists to advance the development of new modules such as FLAMINGO and SQUIRREL for the assessment of spinal disorders. At the same time the application range of modules already in clinical use is continuously extended. And it is to both, further development and clinical use, that the now established collaboration with the renowned LMU Hospital will contribute over the next four years.

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