Simplifications inherent in linear numerical models can cause uncertainties in predicting the level of electroporation and efficacy of electroporation-based treatments. To remedy this, we have developed nonlinear electroporation models for modelling electric field distribution, which enable better correspondence of measured and computed currents and electric field-dependent changes of electrical properties of tissue. We have implemented a model of electroporation of macroscopic homogeneous tissues (e.g. liver) and a model composed of an arbitrary number of homogeneous components. We have developed software components for detection of changes of tissue properties depending on electric fields. The software can be used even in cases where electrical properties are unknown or difficult to measure, which represents an important advance. The developments presented in this paper can be used to improve treatment planning and treatment with electroporation-based therapies, such as electrochemotherapy, gene therapy and vaccination, and tissue ablation with irreversible electroporation.
COBISS.SI-ID: 9707348
Electroporation is the phenomenon that occurs when a cell is exposed to a high electric field, which causes transient cell membrane permeabilization. An important electroporation-based application is electrochemotherapy, which is performed by delivering high-voltage electric pulses that enable the chemotherapeutic drug to more effectively destroy the tumor cells. Electrochemotherapy can be used for treating deep-seated metastases (e.g. in the liver, bone, brain, soft tissue) using variable-geometry long-needle electrodes. To treat deep-seated tumors, patient-specific treatment planning of the electroporation-based treatment is required. Treatment planning is based on generating a 3D model of the organ and target tissue subject to electroporation (i.e. tumor nodules). The generation of the 3D model is done by segmentation algorithms. We implemented and evaluated three automatic liver segmentation algorithms: region growing, adaptive threshold, and active contours (snakes). The algorithms were optimized using a seven-case dataset manually segmented by the radiologist as a training set, and finally validated using an additional four-case dataset that was previously not included in the optimization dataset. The presented results demonstrate that patient’s medical images that were not included in the training set can be successfully segmented using our three algorithms. Besides electroporation-based treatments, these algorithms can be used in applications where automatic liver segmentation is required.
COBISS.SI-ID: 10019668
Electroporation-based treatments are currently used for treating of superficial tumors by using standard operating procedures. However, to successfully treat deep-seated tumors, an individualized treatment planning approach is required, due to the diverse shape, size and location of deep-seated tumors. Many institutions that already perform electroporation-based treatments of superficial tumors could benefit from treatment planning software that would enable the preparation of patient-specific treatment plans. To this end, we have developed a web-based treatment planning software, that does not require prior engineering knowledge from the user. The software includes algorithms for automatic tissue segmentation, model generation and electric field optimization.
COBISS.SI-ID: 9937236