Patient-Specific Local Field Potential Model for Brain Stimulation
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Solution Overview
Problem
Current brain stimulation technologies, such as Deep Brain Stimulation (DBS), face challenges in understanding the biophysical basis of local field potentials (LFPs) and how patient-specific brain anatomy and electrode placement impact recordings, limiting the accuracy of targeting and stimulation effectiveness.
Innovation Solution
A patient-specific computational framework is developed to model LFPs by creating anatomically and electrically accurate models of brain regions, incorporating radiological imaging and neuron models to determine optimal electrode placement and stimulation parameters for personalized DBS treatments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional DBS electrode placement is used without patient-specific modeling, then the procedure is simpler and faster, but the accuracy of target identification and stimulation effectiveness is reduced
Solution Approach 1:
The patent applies preliminary action by performing radiological imaging and creating patient-specific anatomical models before the actual DBS procedure. The computational framework pre-calculates optimal electrode placement and stimulation parameters based on individual brain anatomy, allowing clinicians to execute the procedure with greater precision without real-time complexity
Solution Approach 2:
The patent creates a virtual copy of the patient's brain anatomy through radiological imaging and computational modeling. This digital twin allows for simulation and optimization of electrode placement and stimulation parameters without affecting the actual patient, enabling high-precision planning before the invasive procedure
2Adaptability or versatility
If generic brain models are used for DBS planning, then the process is more straightforward, but the individual anatomical variations and their impact on LFP recordings cannot be accounted for
Solution Approach 1:
The patent applies local quality by creating patient-specific models that capture individual anatomical variations in brain structure and electrode placement. The computational framework calculates LFP recordings specific to each patient's unique anatomy, allowing personalized optimization of stimulation parameters rather than using generic models for all patients
Solution Approach 2:
The patent introduces a computational modeling framework as an intermediary between raw radiological images and clinical DBS decision-making. This intermediary layer translates anatomical images into quantitative LFP predictions, making the complex biophysical relationships understandable and actionable for clinicians
3Reliability
If detailed patient-specific anatomical modeling is performed, then the therapeutic efficacy is enhanced, but the computational resources and time required increase
Solution Approach 1:
The patent performs detailed anatomical modeling and LFP calculations in advance, before the actual DBS procedure. By completing the computationally intensive work during the planning phase using pre-operative radiological images, the system enables high-precision therapy without delaying the clinical procedure
Solution Approach 2:
The computational framework automatically processes radiological images and calculates optimal stimulation parameters without requiring manual intervention for each calculation step. The system self-services by iteratively optimizing electrode placement and stimulation settings based on the patient's anatomy, reducing both time and expert labor requirements
Data Source
AI summary
Embodiments discussed herein facilitate identification of a target area within a region of a brain for stimulation via one or more BS (Brain Stimulation) electrodes. One example embodiment comprises generating, based on radiological imaging of a region of a brain of a patient and BS electrode lead(s), a patient-specific anatomical model of the region and lead(s); populating the patient-specific anatomical model with neuron models based on associated neuronal densities of at least one of the region or one or more sub-regions of the region; constructing a patient-specific local field potential (LFP) model of the region based on the patient-specific anatomical model and location(s)/orientation(s) of the one or more BS electrode leads; and identifying, via the patient-specific LFP model of the region, a target area within the region for at least one of monitoring or treatment of a medical condition via the one or more BS electrode leads.