Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.
Department of Physics and Astronomy, Western University, London, Ontario, Canada.
Med Phys. 2022 Sep;49(9):6055-6067. doi: 10.1002/mp.15825. Epub 2022 Jul 10.
The use of non-ionizing electric fields from low-intensity voltage sources (< 10 V) to control malignant tumor growth is showing increasing potential as a cancer treatment modality. A method of applying these low-intensity electric fields using multiple implanted electrodes within or adjacent to tumor volumes has been termed as intratumoral modulation therapy (IMT).
This study explores advancements in the previously established IMT optimization algorithm, and the development of a custom treatment planning system for patient-specific IMT. The practicality of the treatment planning system is demonstrated by implementing the full optimization pipeline on a brain phantom with robotic electrode implantation, postoperative imaging, and treatment stimulation.
The integrated planning pipeline in 3D Slicer begins with importing and segmenting patient magnetic resonance images (MRI) or computed tomography (CT) images. The segmentation process is manual, followed by a semi-automatic smoothing step that allows the segmented brain and tumor mesh volumes to be smoothed and simplified by applying selected filters. Electrode trajectories are planned manually on the patient MRI or CT by selecting insertion and tip coordinates for a chosen number of electrodes. The electrode tip positions and stimulation parameters (phase shift and voltage) can then be optimized with the custom semi-automatic IMT optimization algorithm where users can select the prescription electric field, voltage amplitude limit, tissue electrical properties, nearby organs at risk, optimization parameters (electrode tip location, individual contact phase shift and voltage), desired field coverage percent, and field conformity optimization. Tables of optimization results are displayed, and the resulting electric field is visualized as a field-map superimposed on the MR or CT image, with 3D renderings of the brain, tumor, and electrodes. Optimized electrode coordinates are transferred to robotic electrode implantation software to enable planning and subsequent implantation of the electrodes at the desired trajectories.
An IMT treatment planning system was developed that incorporates patient-specific MRI or CT, segmentation, volume smoothing, electrode trajectory planning, electrode tip location and stimulation parameter optimization, and results visualization. All previous manual pipeline steps operating on diverse software platforms were coalesced into a single semi-automated 3D Slicer-based user interface. Brain phantom validation of the full system implementation was successful in preoperative planning, robotic electrode implantation, and postoperative treatment planning to adjust stimulation parameters based on actual implant locations. Voltage measurements were obtained in the brain phantom to determine the electrical parameters of the phantom and validate the simulated electric field distribution.
A custom treatment planning and implantation system for IMT has been developed in this study and validated on a phantom brain model, providing an essential step in advancing IMT technology toward future clinical safety and efficacy investigations.
利用低强度电压源（<10V）产生的非电离电场来控制恶性肿瘤生长，作为一种癌症治疗方法，其潜力正在不断增加。一种在肿瘤内或附近使用多个植入电极施加这些低强度电场的方法被称为肿瘤内调制治疗（IMT）。
本研究探讨了先前建立的 IMT 优化算法的进展，并开发了一种用于患者特定 IMT 的定制治疗计划系统。通过在具有机器人电极植入、术后成像和治疗刺激的脑模型上实施完整的优化流程，证明了治疗计划系统的实用性。
3D Slicer 中的集成规划流程从导入和分割患者磁共振成像（MRI）或计算机断层扫描（CT）图像开始。分割过程是手动进行的，然后是半自动平滑步骤，通过应用选定的滤波器，可以对分割后的大脑和肿瘤网格体积进行平滑和简化。通过选择选定数量的电极的插入和尖端坐标，在患者的 MRI 或 CT 上手动规划电极轨迹。然后可以使用定制的半自动 IMT 优化算法优化电极尖端位置和刺激参数（相移和电压），用户可以在其中选择处方电场、电压幅度限制、组织电特性、附近的危险器官、优化参数（电极尖端位置、单个接触相移和电压）、所需的场覆盖百分比和场一致性优化。显示优化结果表，并将得到的电场作为场图叠加在 MRI 或 CT 图像上进行可视化，同时还可以对大脑、肿瘤和电极进行 3D 渲染。优化后的电极坐标被传输到机器人电极植入软件中，以实现电极在所需轨迹上的规划和随后植入。
开发了一种 IMT 治疗计划系统，该系统结合了患者特定的 MRI 或 CT、分割、体积平滑、电极轨迹规划、电极尖端位置和刺激参数优化以及结果可视化。所有以前在不同软件平台上运行的手动管道步骤都合并到了一个基于 3D Slicer 的单一半自动用户界面中。在术前规划、机器人电极植入和术后治疗计划中，对全系统实施的脑模型进行了成功的验证，以根据实际植入位置调整刺激参数。在脑模型中进行了电压测量，以确定模型的电参数并验证模拟的电场分布。
本研究开发了一种用于 IMT 的定制治疗计划和植入系统，并在脑模型上进行了验证，为推进 IMT 技术向未来的临床安全性和有效性研究迈出了重要一步。
