A Simulation-Based Method for Planning Delivery of TTFields to Brain Tumors

Abstract

Tumor Treating Fields (TTFields) are alternating electric fields that inhibit tumor growth. TTFields are delivered using two pairs of transducer arrays placed on the skin. Each pair of arrays creates a field oriented along the axis between the arrays. Arrays are placed to generate two fields that are roughly orthogonal to one another. Simulation-based studies have shown that TTFields distribution within the body is heterogeneous, and depends on the location of the arrays, the patient anatomy and the location and size of the tumor. A recent study showed a connection between increased TTFields dose at the tumor bed and extended patient survival in newly diagnosed Glioblastoma (ndGBM) patients [1]. This emphasizes the need for simulation-based algorithms for patient-specific TTFields treatment planning. Here we present a novel algorithm that utilizes numerical simulations in order to maximize TTFields dose in brain tumors. The outline for our optimization algorithm is as follows: First a patient-specific computational head model is created in a semi-automatic manner from patient MRI data. Next, machine vision algorithms are used in order to define an axial slice passing above the eyes and eyebrows. To ensure transducer arrays are placed in a practical manner, only transducer array layouts in which all arrays are placed above this slice are tested. Next, a finite set of pairs of virtual transducer arrays are placed on the head model and the electric field created by each pair simulated using a finite elements method. To ensure maximal delivery of TTFields to the tumor, the arrays are placed such that the “imaginary” line connecting their centers passes through the tumor bed. A set of layouts is created by combining pairs of arrays (all possible combinations of pairs are created), and the dose delivered by the layouts calculated. The layout that maximizes TTFields dose at the tumor bed is found, and a set of small shifts and rotations is applied to the arrays in the chosen layout order eliminate overlaps between the transducers of the different arrays. The algorithm was tested on MRI data from ten Glioblastoma patients. In all cases, the algorithm converged to yield an optimal array layout that could be placed in a practical manner. Generally, the arrays of the optimal layout were located on the scalp in close proximity to the tumor. In all cases, the optimal layouts delivered average TTFields intensities above the therapeutic threshold of 1 V/cm to the tumors. The average dose delivered by the optimal layouts to the tumors were well above 1 mW/cm3, which has been associated with prolonged patient survival. We have developed a novel simulation-based method for optimizing TTFields treatment planning for brain tumors. Incorporation of such algorithms into sophisticated treatment planning systems is expected to improve the management of TTFields patients by the treating physician, ultimately improving patient outcomes.