TY - JOUR
T1 - EXTH-04. GUIDING PRINCIPLES FOR PREDICTING THE DISTRIBUTION OF TUMOR TREATING FIELDS IN A HUMAN BRAIN: A COMPUTER MODELING STUDY INVESTIGATING THE IMPACT OF TUMOR POSITION, CONDUCTIVITY DISTRIBUTION AND TISSUE HOMOGENEITY
AU - Korshøj, Anders Rosendal
AU - Lundgaard Hansen, Frederik
AU - Thielscher, Axel
AU - Oettingen, Gorm von
AU - Sørensen, Jens Christian Hedemann
PY - 2017/11/6
Y1 - 2017/11/6
N2 - Tumor treating fields (TTFields) are increasingly used as a fourth modality in glioblastoma therapy. TTFields are alternating electrical fields, which inhibit cancer growth by disrupting mitotic processes. Optimization of TTFields efficacy requires thorough understanding of distribution of TTFields “dose” in the brain. Here we provide simple guiding principles, which facilitate intuitive understanding of such distributions and the impact of the technology. Our results are based on extensive electrical field modeling. We estimated TTFields distribution in a realistic human head model using finite element methods. We introduced twenty-four virtual tumors, which were systematically placed at different positions relative to the active transducer-arrays. We found that the TTFields distribution is largely determined by local differences in tissue conductivity. The cerebrospinal fluid creates high-conductivity pathways, which causes currents to flow through the sulci, ventricles and resection cavities towards deeper regions. Correspondingly, local field “hot spots” occurred in deeply seated tumors embedded in white matter, in tumors close to the sulcal fundi and at regions around the resection border. Field strengths were not higher for tumors close to the active arrays. The left/right array configuration was superior to the anterior/posterior configuration, regardless of the tumor position. High conducting glioma-tissue creates a preferred pathway for current flow, which causes focal enhancement of the field near boundaries between the tumor and surrounding tissue that are perpendicular to the applied field. This effect was even more pronounced for tumors with high conductive central necrosis. Necrosis further caused a significant non-uniformity of the induced field within the tumor. The presented results provide guiding principles to understand the distribution of TTFields. This may potentially be used for a variety of applications, including prediction local risk and site of recurrence. However, studies examining the connection between field distribution and site of recurrence need to be conducted.
AB - Tumor treating fields (TTFields) are increasingly used as a fourth modality in glioblastoma therapy. TTFields are alternating electrical fields, which inhibit cancer growth by disrupting mitotic processes. Optimization of TTFields efficacy requires thorough understanding of distribution of TTFields “dose” in the brain. Here we provide simple guiding principles, which facilitate intuitive understanding of such distributions and the impact of the technology. Our results are based on extensive electrical field modeling. We estimated TTFields distribution in a realistic human head model using finite element methods. We introduced twenty-four virtual tumors, which were systematically placed at different positions relative to the active transducer-arrays. We found that the TTFields distribution is largely determined by local differences in tissue conductivity. The cerebrospinal fluid creates high-conductivity pathways, which causes currents to flow through the sulci, ventricles and resection cavities towards deeper regions. Correspondingly, local field “hot spots” occurred in deeply seated tumors embedded in white matter, in tumors close to the sulcal fundi and at regions around the resection border. Field strengths were not higher for tumors close to the active arrays. The left/right array configuration was superior to the anterior/posterior configuration, regardless of the tumor position. High conducting glioma-tissue creates a preferred pathway for current flow, which causes focal enhancement of the field near boundaries between the tumor and surrounding tissue that are perpendicular to the applied field. This effect was even more pronounced for tumors with high conductive central necrosis. Necrosis further caused a significant non-uniformity of the induced field within the tumor. The presented results provide guiding principles to understand the distribution of TTFields. This may potentially be used for a variety of applications, including prediction local risk and site of recurrence. However, studies examining the connection between field distribution and site of recurrence need to be conducted.
M3 - Tidsskriftartikel
SN - 1522-8517
VL - 19
JO - Neuro-Oncology
JF - Neuro-Oncology
M1 - Vol 19
ER -