Insight Surgical Technologies Inc.

Intraoperative Stereovision for Surgical Guidance - Project Summary/abstract: Insight Surgical Technologies, LLC, Is a Start-up Founded by Senior Members of a Long-standing Nih-funded Research Effort to Develop Intraoperative Image Updating That Maintains Accurate Image Correspondence With the Surgical Field Throughout a Procedure. the Effort Has Led to Research Innovations That Have Generated an Intellectual Property (IP) Portfolio of 13 Issued and 8 Pending Patents. Phase I Demonstrated Feasibility of New Algorithms for Assembling Multiple Intraoperative Stereovision (ISV) Acquisitions Into a Composite Field-of-view and Accomplishing Isv-to-mri Registration/re-registration, and Conversion of Existing Isv Algorithms for 3D Surface Reconstruction and Calibration in Graphics Processing Unit (GPU) Accelerated Forms. Additionally, Phase I Results Obtained During Resection of a Large Animal (SWINE) Brain Tumor Indicate This Model Is a Superb System for Testing and Validating Insight’s Complete Image Updating System, I2UPDATETM, in Vivo in Phase Ii. Specifically, We Will Leverage Phase I Results to Automate I2UPDATETM Fully, and Demonstrate Its Technical Performance and Clinical Functionality Under Quality Systems Sufficient to Meet Regulatory Requirements. Specific Aims Will (i) Develop a Fully-automated, Gpu-enabled Processing System for Intraoperative Image-updating (I2UPDATETM), (II) Complete Verification Testing and Pre-clinical in Vivo Validation of I2UPDATETM, Under Quality System Controls Sufficient for Supporting Regulatory Filings at the End of Phase Ii, and (III) Conduct a Multi-site Clinical-use Study With I2UPDATETM Under Non-significant Risk in Patients Undergoing Brain Tumor Resection. Successful Completion of Phase Ii Will Produce the I2UPDATETM Product Platform as a Finalized Commercial Gpu-enabled Software System With Concomitant Design Control, Software Validation, Procedural Use and Quality Systems, Accompanied by in Vivo Animal Validation and Multi-site, Multi-surgeon Use Demonstrating Clinically- Relevant and Acceptable Image-updating Performance in Terms of Automation, Computational Efficiency and Registration Accuracy.