Simulating QMR surface electrodes performance in post-surgical environments
In our ongoing collaboration with Telea, this project focused on optimizing their non-thermal QMR therapy for post-surgical glioblastoma applications.. The primary challenge was understanding how post-surgical resection cavities, which naturally fill with cerebrospinal fluid (CSF) after resection, impact the performance of electric currents by the surface electrodes. We developed a 3D bio-electromagnetic and thermal model to systematically analyze the effects of the cavity's position and size. The simulation demonstrated that these anatomical variables significantly influence power dissipation, current, and temperature, providing Telea with a predictive roadmap to guide electrode placement and treatment parameters based on patient-specific, post-surgical anatomy.
Adapting therapy to the post-surgical brain
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The simulation provided clear, actionable conclusions, transforming a complex problem into a design and application guide for Telea.
Critical influence of cavity locationThe simulation provided conclusive evidence that the cavity's position is a critical factor, significantly impacting the dissipated power, total current, and maximum temperature. This insight is fundamental, as it highlights the opportunity to optimize the therapy by adapting the electrode configuration to the specific surgical location. It gives Telea the technical basis to demonstrate that the configuration must be adapted to the specific location of a patient's surgical resection.
Quantitative impact of cavity sizeFurthermore, the study quantified how the cavity's size alters energy absorption, with larger cavities concentrating the electric current differently than smaller ones. This data is directly applicable, as it allows for the adjustment of key treatment parameters, such as input power, based on a patient's post-operative imaging (e.g., an MRI). This represents a key step towards an adaptive therapeutic strategy.
A predictive roadmap for R&DUltimately, the study generated a comprehensive predictive roadmap linking patient anatomy, device configuration, and physical outcomes. Instead of guesswork, Telea now possesses a powerful model that can be used to plan treatments, train clinicians, and accelerate the future development of their technology, ensuring it is applied as safely and effectively as possible.
Towards an optimized post-surgical therapy
We developed a high-fidelity 3D model of a human head that incorporated these post-surgical variables.
Geometric model: A 3D geometry of an adult head was constructed with its key layers (scalp, skull, CSF, grey, and white matter), into which a virtual resection cavity was integrated.
Coupled physics: The model was implemented to simultaneously solve for:
Electromagnetics (RF): To simulate how radiofrequency energy from the surface electrodes propagates through the different tissue layers and is affected by the conductive CSF in the cavity.
Bioheat transfer: To calculate the resulting thermal effects and ensure the treatment remained within the non-thermal principles of the QMR technology.
3. Comprehensive Parametric Study: The core of the project was a systematic analysis where key variables were swept to understand their impact:
Cavity position: Six anatomically relevant locations were analyzed (infero-lateral, supero-lateral, central, deep, posterior, and frontal).
Cavity size: Multiple cavity diameters were simulated.
Incident power: The analysis was repeated for different input power levels.
A predictive model for post-surgical scenarios
Surgery fundamentally alters the brain's anatomy, leaving a resection cavity that naturally fills with cerebrospinal fluid (CSF)—a fluid with very different electrical properties than brain tissue. This creates a unique anatomical environment for each patient, introducing a critical question: How does this new landscape affect the delivery and distribution of the electric currents from the QMR therapy?
To maximize the therapy's potential, the placement of the surface electrodes must be precisely adapted to this new post-surgical anatomy. This requires a predictive tool to understand the complex interactions between the electric field and the specific size and location of the cavity, ensuring the energy is delivered effectively to the target area.