Brain Hub Explorer for Surgical Planning
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Solution Overview
Problem
Current medical imaging systems lack precision in parcellating individual brains, leading to potential collateral damage during surgeries due to inadequate visualization of functional areas, especially in structurally abnormal brains, and existing graph theories struggle to effectively analyze connectivity data, making it challenging for medical professionals to make informed decisions during procedures.
Innovation Solution
The development of an interactive brain navigation system that overlays nodes representing brain parcels on a graphical user interface, allowing medical professionals to visualize and analyze connectivity data, simulate surgical procedures, and make informed decisions by interacting with a 3D representation of the brain, using diffusion weighted imaging and blood oxygen consumption data to determine connectivity and impact of excising brain areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a standard brain atlas is used for parcellation, then the parcellation process is simplified and can be applied universally, but precision is lost when applied to structurally abnormal brains
Solution Approach 1:
The system dynamically adapts the parcellation scheme to match the individual patient's brain structure by warping the standard atlas to align with patient-specific anatomical features, allowing the parcellation to be both universally applicable and precisely accurate for each patient
Solution Approach 2:
The system changes the parameters of the standard brain atlas by applying spatial transformations and warping to align it with the patient's actual brain structure, thereby maintaining universal applicability while achieving patient-specific precision
2Loss of information
If brain graphs are used to display connectivity data, then comprehensive connectivity information is provided, but the visualization becomes cluttered and difficult to analyze
Solution Approach 1:
The system extracts and highlights only the most relevant connectivity information (such as hubs and their connections) from the complete brain graph, removing unnecessary visual clutter while preserving the essential connectivity data needed for surgical planning
Solution Approach 2:
The system applies different visualization qualities to different parts of the connectivity data, emphasizing critical hubs and their connections with enhanced visual properties while displaying less critical connections with reduced visual prominence, making the data both complete and analyzable
3Reliability
If detailed connectivity data is visualized for all brain regions, then comprehensive surgical risk assessment is possible, but the complexity of the system increases
Solution Approach 1:
The system segments the brain into functionally relevant parcels and identifies critical hubs, then focuses detailed connectivity visualization only on these segmented regions rather than all brain areas, maintaining comprehensive risk assessment while reducing system complexity
Data Source
AI summary
Disclosed herein are systems and methods for providing interactive graphical user interfaces (GUIs) for users, such as medical professionals, to glean insight about connectivity data associated with a particular brain. A method can include overlaying nodes representing locations of parcels of a patient's brain on a representation of a brain and displaying the representation of the brain with the overlaid nodes in a GUI. Nodes having connectivity above a first threshold can be represented in a first indicia and nodes having connectivity below a second threshold can be represented in a second indicia. The method can include receiving user input and taking an action based on the user input. The user input can include selecting an area of the representation of the brain for excision. Taking an action based on the input can include calculating an impact of excising the area of the brain on the particular patient.