Towards a computational method for imaging the extracellular potassium concentration during regional ischemia

Area of Science:

• Biomedical Engineering
• Computational Biology
• Medical Imaging

Background:

• Regional ischemia poses significant diagnostic challenges.
• Accurate imaging of extracellular potassium concentration is crucial for understanding ischemic events.
• Current methods for monitoring ischemia may lack sufficient spatial resolution or real-time capability.

Purpose of the Study:

• To investigate the feasibility of using body surface potential maps for imaging extracellular potassium concentration during regional ischemia.
• To develop and validate a computational model for this imaging task.

Main Methods:

• Formulated the problem as an inverse problem using a linear approximation of the bidomain model.
• Employed a one-shot technique to solve the partial differential equations (PDEs) system, adjoint problem, and minimization relation simultaneously.
• Utilized synthetic data for performance evaluation of the developed model.

Main Results:

• The model successfully identified the approximate location and size of ischemic regions in many test cases.
• Certain scenarios presented greater challenges for accurate localization.
• Qualitative assessment showed that post-processed results closely resembled the true solutions.

Conclusions:

• Body surface potential mapping shows promise for imaging extracellular potassium during regional ischemia.
• The developed inverse problem formulation and one-shot solution technique are effective.
• Further refinement may improve localization accuracy in more complex cases.