The trends are clear regarding 3D medical imaging — the demand for high-quality 3D imaging and its processing is increasing while the number of medical professionals is declining. The Association of American Medical Colleges acknowledges that the U.S. shortage of radiologists and other specialist physicians could climb to nearly 42,000 by 2033. Furthermore, research from the journal Orthopedic Surgery shows that the number of knee arthroplasties (TKAs) in the U.S. is projected to grow to 3.48 million by 2030, while total hip arthroplasties (THAs) will grow to 572,000 in the same period.
As 3D imaging plays an increasingly integral role in orthopedic procedures, with more and more personalized surgical plans, guides, and devices coming to the market, there is a greater imbalance between the amount of data being created and the scalability of its processing for surgical planning, device/guide design, and even in silico clinical trials.
This imbalance has created an increased demand for automated workflows to reduce the amount of time devoted to 3D image processing. Clinicians, technicians, designers, and engineers need and want to focus more on their final applications, not tedious image processing and anatomical model generation.
The Simpleware™ Product Group at Synopsys is addressing this need by providing a robust and powerful software platform for 3D image processing and model generation, as well as leveraging machine learning-based artificial intelligence (AI) technology to help automate certain workflows.
Johann Henckel, M.D., an orthopedic surgeon from the Royal National Orthopaedic Hospital, said the following about the Simpleware™ platform as it applies to the hospital’s patient-specific workflows:
"Image segementation of MRI and CT scans presents a signifcant challenge for our surgical and egineering multidiscplinary teams. What is currently a laborious process that occupies significant egineering resources and time can now be completed quickly, accurately and with less variability, promising a scalable solution for generating high-fidelity, patient-specific models, surgical tolls and bespoke implants."