Muscle is tissue of choice for successful electroporation based gene transfection in vivo, which is usually performed trancutaneously. This is the first study that provides numerically and in vivo determined electroporation threshold for transcutaneous muscle electroporation based on 3D realistic numerical modeling. The results are compared to the direct muscle electroporation (i.e. with skin removed). We found that the same electroporation threshold is needed for both transcutaneous and direct electroporation. The presence of skin decreases the amount of transported molecules into muscle tissue. Our findings carry important information for successful electroporation based gene therapy and vaccination, as well as for successful outcome of other electroporation based therapies and treatments such as electrochemotherapy and transdermal drug delivery.
COBISS.SI-ID: 9484884
Electroporation based therapies and treatments (e.g. electrochemotherapy, gene electrotransfer for gene therapy and DNA vaccination, tissue ablation with irreversible electroporation and transdermal drug delivery) require a precise prediction of the therapy or treatment outcome by a personalized treatment planning procedure. Recent studies have reported that the uncertainties in electrical properties predefined in linear numerical models (i.e. tissue conductivity is constant) have large effect on electroporation based therapy and treatment effectiveness. In our study we showed that the changes in electrical conductivity due to electroporation need to be taken into account when an electroporation based treatment is planned or investigated. We concluded that the model of electric field distribution that takes into account the increase in electric conductivity due to electroporation (i.e. nonlinear electroporation model) yields more precise prediction of successfully electroporated target tissue volume. The findings of our study can significantly contribute to the current development of individualized patient-specific electroporation based treatment planning.
COBISS.SI-ID: 9707348