AI-powered 3D visualization improves breast cancer surgery

SimBioSys, an Illinois-based startup, is revolutionizing breast cancer surgery with AI-based imaging technology that creates precise 3D models of tumors, veins, and soft tissue. According to NVIDIA, this innovation aims to help surgeons perform more effective surgeries and improve treatment outcomes.

advanced imaging technology

This technology converts standard MRI scans into volumetric images that clearly distinguish the various structures within the breast. Tumors, veins, and surrounding tissue are color-coded, allowing surgeons to manipulate these 3D visualizations to better plan surgery. Known as TumorSight, the system provides vital data, including tumor volume and proximity to the chest wall, to help determine whether to preserve the breast or proceed with a mastectomy.

TumorSight, which received FDA clearance last year, represents a significant advance in preoperative imaging and provides more comprehensive insights than existing methods. Jyoti Palaniappan, Chief Commercial Officer at SimBioSys, emphasized that this technology represents a significant improvement over standard radiology reports, which typically provide limited data before surgery.

AI in surgical planning

Dr. Barry Rosen, Chief Medical Officer of SimBioSys, highlighted the potential of AI to improve surgical outcomes by standardizing surgical imaging. The startup uses NVIDIA’s A100 Tensor Core GPUs for model training and validation, along with other NVIDIA technologies such as MONAI and CUDA-X libraries. This collaboration is part of the NVIDIA Inception program for startups.

Further development of AI applications

SimBioSys is also exploring additional AI applications to further improve breast cancer survival rates. A new technique has been developed to adjust MRI images taken with the patient’s face down into a 3D visualization to reflect how the breast and tumor would appear during surgery with the patient’s face up. This provides surgeons with important preoperative insight by accounting for the effects of gravity and skin elasticity.

We are also developing AI-based methods to accelerate tumor analysis after surgery. This new approach uses 3D tumor features and initial pathology reports to provide rapid risk analysis for cancer recurrence, resulting in significant time and cost savings compared to traditional methods.

According to Palaniappan, SimBioSys’ risk analysis method matches or exceeds existing scoring methods for recurrence risk, providing results in less time and at lower cost. These advances promise more timely and informed treatment planning and potentially improve patient outcomes.

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