Optimo Medical AG Accelerates Patient-specific Surgery Planning By 100 Times, thanks to Neural Concept

Providing care for 15 million low-cylinder astigmatism patients each year has traditionally forced ophthalmologists to plan eye surgeries with largely run-of-the-mill statistical models. This has often caused suboptimal incision placement and imperfections in patient vision correction, requiring multiple operations to solve issues.

With Optimo Medical AG's Optimeyes™ digital twin technology, ophthalmologists can create identical digital copies of patients' corneas to test surgical strategies for individual patients, which substantially improves results. This process, which traditionally relies on Ansys Mechanical for the evaluation of the structural behavior of the eye, has just become incredibly faster and practical, thanks to Neural Concept. Neural Concept Shape's integration with Ansys Mechanical APDL allows to natively read .cdb files and the AI model was trained using an historical database of structural simulations and corresponding eye scans. Once trained, the AI model is able to handle a wide range of eye topographies, corresponding to the patients’ specifications.

This unique ability of NC Shape to handle non-parametrized, raw 3D eye scans as input, while predicting the corresponding structural behavior in a few seconds, allowed a seamless integration within Optimeyes. This collaboration, leveraging Ansys, Neural Concept and Optimo Medical's joint expertise, enables Optimeyes to provide ophthalmologists with patient specific surgery plans within a few minutes where hours were needed with previous versions. Patients can now receive a custom surgery without coming back to the clinic several times.  

Figure 1: Comparison of FEA Simulation with AI prediction from a given scanned eye topography within Optimeyes

Delivering a solution that powers surgical precision to maximize patient outcomes in just a few minutes, the collaboration also drives in silico clinical trials of new eye products —significantly reducing development time and cost.  

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