Craniotomy Simulation Path Derivation via Cerebral Sulci
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Solution Overview
Problem
Current craniotomy simulation methods are inefficient in determining a path to an abnormal area in the brain, as they often result in the simulation passing through critical structures like cranial nerves and blood vessels, and may not meet the surgeon's preferences, requiring repeated simulations to adjust the incision position.
Innovation Solution
A craniotomy simulation device that derives paths from an abnormal area to the brain's surface through cerebral sulci, sets a craniotomy pattern based on selected templates, and corrects them according to the subject's head shape, while avoiding designated organs, and displays the simulation image to visualize the path effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a simulation path is determined using conventional methods, then the simulation can be performed, but the path may pass through critical structures like cranial nerves and blood vessels
Solution Approach 1:
The system performs preliminary identification of cerebral sulci and pre-evaluation of potential simulation paths before actual surgery. By deriving multiple candidate paths in advance and evaluating them against critical structures, the system prepares safe surgical routes beforehand, avoiding the need to discover safe paths during the actual surgical procedure
Solution Approach 2:
The system uses cerebral sulci as intermediary structures to guide the surgical path. Instead of directly planning a path through brain tissue, the system routes the simulation path through the cerebral sulci (which are natural anatomical spaces), thereby avoiding critical structures like cranial nerves and blood vessels that may be present in direct tissue paths
2Reliability
If the incision position is adjusted to avoid critical structures, then surgical safety improves, but repeated simulations are required
Solution Approach 1:
The system performs preliminary derivation of multiple candidate simulation paths simultaneously, evaluating each path against critical structures in advance. This allows the surgeon to review multiple pre-evaluated options and select the safest path without performing repeated time-consuming simulations during the surgical planning process
Solution Approach 2:
The system dynamically evaluates multiple candidate paths by deriving them in parallel and assessing their safety relative to critical structures. Rather than sequentially adjusting one path at a time, the system generates and evaluates multiple paths simultaneously, enabling efficient comparison and selection of the optimal safe path
3Reliability
If the simulation path follows cerebral sulci, then critical structures are avoided, but the path planning becomes more complex
Solution Approach 1:
The system uses cerebral sulci as intermediary guide structures that naturally lead away from critical structures. By constraining the simulation path to follow the geometry of cerebral sulci (which are visible in preoperative imaging), the system automatically routes around critical structures without requiring complex manual avoidance calculations
Solution Approach 2:
The system replaces complex manual path-planning mechanics with automated computer-based image processing and path derivation algorithms. The computer automatically identifies cerebral sulci in three-dimensional images and derives simulation paths that follow these anatomical features, substituting manual complex planning with automated computational geometry
Data Source
AI summary
In a craniotomy simulation device, method, and program, a path to an abnormal area can be efficiently determined for a simulation of a craniotomy. A path derivation unit derives, in a three-dimensional image of a brain of a subject including an abnormal area, at least one path from the abnormal area to a surface of the brain through a cerebral sulcus in the brain. A craniotomy pattern setting unit sets a craniotomy pattern for tracing the path, on a surface of a head of the subject included in the three-dimensional image.