SimBioSys, an Illinois-based startup, is revolutionizing breast cancer surgery with its AI-powered imaging technology that produces precise 3D models of tumors, veins, and soft tissues. This innovation aims to assist surgeons in performing more effective operations and improving treatment outcomes, according to NVIDIA.
Advanced Imaging Technology
The technology transforms standard MRI scans into volumetric images that clearly distinguish different structures within the breast. Tumors, veins, and surrounding tissues are color-coded, allowing surgeons to manipulate these 3D visualizations for better surgical planning. Known as TumorSight, the system provides crucial data such as tumor volume and proximity to the chest wall, aiding decisions on whether to preserve the breast or proceed with a mastectomy.
Having received FDA clearance last year, TumorSight is a significant advancement in pre-surgical imaging, offering more comprehensive insights than traditional methods. Jyoti Palaniappan, Chief Commercial Officer at SimBioSys, highlighted that this technology represents a substantial improvement over standard radiology reports, which typically offer limited data before surgery.
AI in Surgical Planning
Dr. Barry Rosen, Chief Medical Officer at SimBioSys, emphasized the potential of AI to standardize surgical imaging, thereby enhancing surgical outcomes. The startup uses NVIDIA’s A100 Tensor Core GPUs for model training and validation, alongside other NVIDIA technologies like MONAI and CUDA-X libraries. This collaboration is part of NVIDIA’s Inception program for startups.
Further Developments in AI Applications
SimBioSys is also exploring additional AI applications to further improve breast cancer survival rates. A novel technique has been developed to adjust MRI images taken with the patient face down into 3D visualizations that reflect how the breast and tumor will appear during surgery, when the patient is face up. This accounts for the effects of gravity and skin elasticity, providing surgeons with crucial pre-surgical insights.
Moreover, the company is developing an AI-driven method to expedite the analysis of tumors post-surgery. This new approach offers a rapid risk analysis of cancer recurrence, using 3D tumor features and initial pathology reports, significantly reducing the time and cost compared to traditional methods.
According to Palaniappan, SimBioSys’s risk analysis method matches or surpasses traditional scoring methods for recurrence risk, offering results in a fraction of the time and at a lower cost. This advancement holds promise for more timely and informed treatment planning, potentially improving patient outcomes.
Image source: Shutterstock
Credit: Source link