Endoscopic Navigation System for Renal Anatomy Mapping
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Solution Overview
Problem
During endoscopic kidney surgery, surgeons face challenges in navigating the complex three-dimensional anatomy of the renal collecting system, identifying kidney stones and tumors, and tracking stone fragments due to limited preoperative imaging, obscured views, and dispersion of stones, leading to incomplete treatments and repeat surgeries.
Innovation Solution
A navigational system that generates a three-dimensional map of the renal anatomy using preoperative CT scans and real-time endoscopic video, tracks the endoscope tip, and identifies anatomical features using computational models to overlay kidney stones and tumors on the visual display, enhancing navigation and identification accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If preoperative two-dimensional CT images are used as navigation guide, then the surgical procedure can be performed with available imaging, but the surgeon cannot effectively navigate the three-dimensional anatomy of the renal collecting system
Solution Approach 1:
The system transforms two-dimensional preoperative CT images into a three-dimensional virtual model of the renal collecting system. This dimensional transformation allows surgeons to navigate and visualize the complex 3D anatomy accurately, resolving the contradiction between using available 2D imaging and needing 3D navigation capability.
2Productivity
If endoscopic surgery is performed with standard visualization, then the surgical procedure can proceed, but the field of view is frequently obscured by blood, bubbles, debris, and blood clots
Solution Approach 1:
The system introduces a computational model as an intermediary that processes endoscopic video feeds to identify and highlight anatomical features, kidney stones, and tumors. This computational intermediary enhances visibility and detection despite obscuration by blood, bubbles, and debris, allowing surgeons to maintain surgical efficiency while overcoming visualization difficulties.
3Ease of manufacture
If kidney stones are fragmented during surgery, then stone treatment can be performed, but the stone fragments disperse throughout the anatomy making tracking difficult
Solution Approach 1:
The system implements real-time feedback by continuously tracking and visualizing the location of stone fragments as they disperse during fragmentation procedures. The computational model monitors the anatomical space and provides ongoing location information about fragments, allowing surgeons to maintain awareness of fragment positions and achieve complete stone-free status.
4Reliability
If the entire renal collecting system needs to be visualized to locate all stones and tumors, then complete treatment can be achieved, but the complex branched anatomy makes comprehensive navigation difficult
Solution Approach 1:
The system performs preliminary action by pre-segmenting the renal collecting system from preoperative CT scans to create a detailed virtual model before surgery begins. This pre-processing organizes the complex branched anatomy into a structured navigational framework, enabling comprehensive visualization and reliable detection of all stones and tumors throughout the entire collecting system.
Data Source
AI summary
Systems and methods for navigation and identification for endoscopic kidney surgery may include generating a map of an internal space of a patient's collecting system, including segmentation preoperative CT scans, using localization and three-dimensional reconstruction techniques on endoscopic video to create a point cloud, and registering the point cloud to the segmented CT scans. The systems and methods may include tracking a tip of the endoscope during the endoscopic kidney surgery using localization and three-dimensional reconstruction techniques. The systems and methods may include identifying and tracking kidney stones during the endoscopic kidney surgery using computational models.