Brain Mapping Data Processing for Cognitive Outcome Prediction
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Solution Overview
Problem
Current neurosurgical procedures lack an integrated hardware-software solution for flexible cognitive testing that seamlessly interfaces with existing technologies in operating rooms, failing to record, score, and integrate behavioral consequences of electrical stimulation mapping with other data streams, such as MRI and electrocorticography, which hampers the balance between tumor removal and preservation of critical brain functions.
Innovation Solution
A data processing system that integrates patient behavioral performance with structural and functional imaging data to predict treatment effects on the brain, using machine learning models to generate visualizations of brain regions at risk for adverse outcomes, allowing real-time simulation of surgeries and flexible cognitive testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If electrical stimulation mapping is performed with manual behavioral testing, then cognitive function mapping can be achieved, but the behavioral consequences are not recorded, scored, and integrated with other data streams
Solution Approach 1:
The patent combines multiple data streams (electrical stimulation mapping, structural MRI, functional MRI, electrocorticography, and behavioral performance data) into a unified integrated system. This merging allows comprehensive recording, scoring, and integration of behavioral consequences with other neurological data streams, resolving the information loss problem while managing system complexity through unified architecture.
Solution Approach 2:
The patent introduces a computing device as an intermediary that receives data from multiple sources including sensors, imaging systems, and stimulation devices. This intermediary processes, integrates, and analyzes the combined data streams, enabling the system to capture and utilize behavioral consequences without requiring direct complex integration between all individual components.
2Reliability
If surgeons rely on traditional electrical stimulation mapping, then critical brain regions can be identified, but the balance between tumor removal and functional preservation is hampered without integrated data analysis
Solution Approach 1:
The patent performs preliminary integration and analysis of multiple data streams (structural imaging, functional imaging, electrocorticography, and stimulation mapping) before surgical intervention. This preliminary action creates a comprehensive pre-operative model that identifies critical brain regions and predicts functional outcomes, allowing surgeons to plan more accurate resection boundaries while preserving eloquent areas.
Solution Approach 2:
The patent implements feedback mechanisms where intraoperative electrical stimulation mapping results are immediately integrated with pre-operative imaging data and analyzed by the computing device. This real-time feedback allows dynamic adjustment of surgical plans based on actual functional responses, improving the reliability of tumor removal while maintaining functional preservation.
3Measurement precision
If comprehensive data integration is implemented, then prediction accuracy improves, but the system requires integrated hardware-software solution that seamlessly interfaces with existing technologies
Solution Approach 1:
The patent designs the computing device and software platform to universally interface with multiple existing technologies including MRI systems, electrocorticography equipment, electrical stimulation devices, and various sensor systems. This multi-functional capability allows comprehensive data integration from diverse sources while maintaining ease of operation through standardized interfaces and unified processing protocols.
Solution Approach 2:
The computing device serves as an intermediary layer that standardizes interfaces between various existing technologies and the integrated analysis system. It receives data from multiple sources through standardized protocols, processes the information uniformly, and outputs results in formats compatible with existing surgical and diagnostic systems, thereby improving measurement precision without compromising ease of operation.
Data Source
AI summary
A system for outputting a visual representation of a brain of a patient is configured to receive sensor data representing a behavior of a region of the brain of the patient. The system retrieves mapping data that maps a prediction value to the region. The prediction value is indicative of an effect on a behavior of the patient responsive to a treatment of the region, the mapping data being indexed to a patient identifier. The system receives, responsive to an application of a stimulation to the region, sensor data representing behavior of the region. The system executes a model that updates, based on the sensor data, the prediction value for the region. The system updates, responsive to executing the model, the mapping data by including the updated prediction value in the mapping data. The system outputs a visual representation of the updated mapping data comprising the updated prediction value.