Optimization of multi‐electrode implant configurations and programming for the delivery of non‐ablative electric fields in intratumoral modulation therapy

Abstract

Purpose Application of low intensity electric fields to interfere with tumor growth is being increasingly recognized as a promising new cancer treatment modality. Intratumoral modulation therapy (IMT) is a developing technology that uses multiple electrodes implanted within or adjacent tumor regions to deliver electric fields to treat cancer. In this study, the determination of optimal IMT parameters was cast as a mathematical optimization problem, and electrode configurations, programming, optimization, and maximum treatable tumor size were evaluated in the simplest and easiest to understand spherical tumor model. The establishment of electrode placement and programming rules to maximize electric field tumor coverage designed specifically for IMT is the first step in developing an effective IMT treatment planning system. Methods Finite element method electric field computer simulations for tumor models with 2 to 7 implanted electrodes were performed to quantify the electric field over time with various parameters, including number of electrodes (2 to 7), number of contacts per electrode (1 to 3), location within tumor volume, and input waveform with relative phase shift between 0 and 2π radians. Homogeneous tissue specific conductivity and dielectric values were assigned to the spherical tumor and surrounding tissue volume. In order to achieve the goal of covering the tumor volume with a uniform threshold of 1 V/cm electric field, a custom least square objective function was used to maximize the tumor volume covered by 1 V/cm time averaged field, while maximizing the electric field in voxels receiving less than this threshold. An additional term in the objective function was investigated with a weighted tissue sparing term, to minimize the field to surrounding tissues. The positions of the electrodes were also optimized to maximize target coverage with the fewest number of electrodes. The complexity of this optimization problem including its non‐convexity, the presence of many local minima, and the computational load associated with these stochastic based optimizations led to the use of a custom pattern search algorithm. Optimization parameters were bounded between 0 and 2π radians for phase shift, and anywhere within the tumor volume for location. The robustness of the pattern search method was then evaluated with 50 random initial parameter values. Results The optimization algorithm was successfully implemented, and for 2 to 4 electrodes, equally spaced relative phase shifts and electrodes placed equidistant from each other was optimal. For 5 electrodes, up to 2.5 cm diameter tumors with 2.0 V, and 4.1 cm with 4.0 V could be treated with the optimal configuration of a centrally placed electrode and 4 surrounding electrodes. The use of 7 electrodes allow for 3.4 cm diameter coverage at 2.0 V and 5.5 cm at 4.0 V. The evaluation of the optimization method using 50 random initial parameter values found the method to be robust in finding the optimal solution. Conclusions This study has established a robust optimiza...

Planning system for the optimization of electric field delivery using implanted electrodes for brain tumor control

“…The optimization module (Figure S1d) requires connection to preexisting MATLAB (v2021a) code 7 that communicates with COMSOL Multiphysics (v5.4) for model creation and electric field computation at each iteration using the COMSOL‐MATLAB Livelink. A MATLAB function was created to connect to the Livelink automatically and run the optimization code.…”

“…[1][2][3][4][5][6][7][8][9][10] Intratumoral modulation therapy (IMT) is an emerging technique intended to restrict tumor growth by applying low-intensity electric fields using bioelectrodes implanted within or adjacent to tumor volumes. [7][8][9][10] Preclinical in vitro and in vivo investigations into the application of 200 kHz, low-intensity (± 2.00 V stimulation) electric fields to glioblastoma (GBM) and diffuse intrinsic pontine glioma (DIPG) cells have shown the efficacy of this modality as a monotherapy, 9 and in conjunction with chemotherapy and radiation. 8 A single stimulating electrode paradigm was implemented in these early studies but computer simulations and optimization studies have since prompted the use of multiple stimulating electrodes with optimized relative phase shifts of input waveforms to increase the coverage capacity of the IMT fields.…”

“…8 A single stimulating electrode paradigm was implemented in these early studies but computer simulations and optimization studies have since prompted the use of multiple stimulating electrodes with optimized relative phase shifts of input waveforms to increase the coverage capacity of the IMT fields. 7 The previous IMT optimization study 7 established a method for temporally maximizing tumor coverage from IMT electric fields. This algorithm allowed for electrode location and stimulation phase shift parameters to be optimized for multiple electrodes, each with multiple separately programmable contacts.…”

“…30 While the goal of electroporation is to ablate a tumor volume using multiple electrodes, 33 the permanent implantation and low-intensity nature of IMT fields requires additional optimization considerations, where we maximize the electric field tumor coverage with minimal input voltage, achieved by optimizing relative phase shifts of the delivered waveforms between electrode contacts. 7 Lastly, radiotherapy treatments consider the delivered ionizing radiation dose to the tumor volume and nearby organs at risk, whereas IMT considers nonionizing electric fields that interfere with one another. The differences between IMT and other modalities necessitate the creation of a custom treatment planning system for IMT.…”

“…In this study, the treatment stimulation parameters and electrode placement is determined by designing a treatment planning system that utilizes and expands upon the IMT optimization algorithm previously established. 7 The goal of this study is to amalgamate the numerous steps in the optimization pipeline into a cohesive, user-friendly system using the 3D Slicer 47,48 platform and to validate the trajectories and plan in a brain phantom. All planning steps are accessed in a single application with ordered steps, with options for preoperative or postoperative planning, human or preclinical in vivo animal planning, and different electrode models (multi-contact cylindrical electrodes, custom electrode arrays, or preclinical multi-electrode wire constructs).…”