Investigating the Connection Between Tumor-Treating Fields Distribution in the Brain and Glioblastoma Patient Outcomes. A Simulation-Based Study Utilizing a Novel Model Creation Technique

Here we describe preliminary results of a simulation-based study investigating the connection between tumor-treating fields (TTFields) distribution in the brain and glioblastoma patient outcomes. In order to perform this study, we developed a semiautomatic method for creating realistic head models from glioblastoma patient MRI using a deformable template and atlas-based registration. This method, which is described in detail in this chapter, is robust and fast, making it suitable for rapid creation of multiple realistic head models. Using this method, we created 119 head models of newly diagnosed glioblastoma patients that were treated with tumor-treating fields. Finite element simulations were used to simulate delivery of TTFields to these patients, and the connection between field intensity distribution at the tumor bed and patient outcome was analyzed. The result of this analysis support the hypothesis that increasing field intensity at the tumor bed improves patient outcome.

[1]  Z. Ram,et al.  Post Hoc analyses of intention-to-treat population in phase III comparison of NovoTTF-100A™ system versus best physician's choice chemotherapy. , 2014, Seminars in oncology.

[2]  Eilon D. Kirson,et al.  Effect of Tumor-Treating Fields Plus Maintenance Temozolomide vs Maintenance Temozolomide Alone on Survival in Patients With Glioblastoma , 2017 .

[3]  Daniel Hernandez,et al.  Electrical conductivity and permittivity maps of brain tissues derived from water content based on T1‐weighted acquisition , 2017, Magnetic resonance in medicine.

[4]  Longzhi Mei,et al.  High‐Frequency Stimulation of Dorsal Column Axons: Potential Underlying Mechanism of Paresthesia‐Free Neuropathic Pain Relief , 2016, Neuromodulation : journal of the International Neuromodulation Society.

[5]  F. Lieberman,et al.  Effect of Tumor-Treating Fields Plus Maintenance Temozolomide vs Maintenance Temozolomide Alone on Survival in Patients With Glioblastoma: A Randomized Clinical Trial , 2017, JAMA.

[6]  Bin He,et al.  Magnetic-Resonance-Based Electrical Properties Tomography: A Review , 2014, IEEE Reviews in Biomedical Engineering.

[7]  E. Kirson,et al.  Mitotic Spindle Disruption by Alternating Electric Fields Leads to Improper Chromosome Segregation and Mitotic Catastrophe in Cancer Cells , 2015, Scientific Reports.

[8]  S. Toms,et al.  Correlation of Tumor Treating Fields Dosimetry to Survival Outcomes in Newly Diagnosed Glioblastoma: A Large-Scale Numerical Simulation-Based Analysis of Data from the Phase 3 EF-14 Randomized Trial. , 2019, International journal of radiation oncology, biology, physics.

[9]  Kevin Bui,et al.  End-to-end workflow for finite element analysis of tumor treating fields in glioblastomas. , 2017, Physics in medicine and biology.

[10]  P. Basser,et al.  Improving Tumor Treating Fields Treatment Efficacy in Patients With Glioblastoma Using Personalized Array Layouts. , 2016, International journal of radiation oncology, biology, physics.

[11]  A. Thielscher,et al.  Enhancing Predicted Efficacy of Tumor Treating Fields Therapy of Glioblastoma Using Targeted Surgical Craniectomy: A Computer Modeling Study , 2016, PloS one.

[12]  Alan C. Evans,et al.  Enhancement of MR Images Using Registration for Signal Averaging , 1998, Journal of Computer Assisted Tomography.

[13]  Jerry L. Prince,et al.  Reconstruction of High-Resolution Tongue Volumes From MRI , 2012, IEEE Transactions on Biomedical Engineering.

[14]  Yoram Palti,et al.  NovoTTF™-100A System (Tumor Treating Fields) transducer array layout planning for glioblastoma: a NovoTAL™ system user study , 2015, World Journal of Surgical Oncology.

[15]  John Ashburner,et al.  SPM: A history , 2012, NeuroImage.

[16]  Yu Huang,et al.  Fully Automated Whole-Head Segmentation with Improved Smoothness and Continuity, with Theory Reviewed , 2015, PloS one.

[17]  E. Dekel,et al.  Alternating electric fields arrest cell proliferation in animal tumor models and human brain tumors , 2007, Proceedings of the National Academy of Sciences.

[18]  E. Dekel,et al.  Disruption of cancer cell replication by alternating electric fields. , 2004, Cancer research.

[19]  Guido Gerig,et al.  User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.

[20]  Axel Thielscher,et al.  Field modeling for transcranial magnetic stimulation: A useful tool to understand the physiological effects of TMS? , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[21]  Axel Thielscher,et al.  Importance of electrode position for the distribution of tumor treating fields (TTFields) in a human brain. Identification of effective layouts through systematic analysis of array positions for multiple tumor locations , 2018, PloS one.

[22]  Ricardo Salvador,et al.  The electric field distribution in the brain during TTFields therapy and its dependence on tissue dielectric properties and anatomy: a computational study , 2015, Physics in medicine and biology.

[23]  A. Thielscher,et al.  Impact of tumor position, conductivity distribution and tissue homogeneity on the distribution of tumor treating fields in a human brain: A computer modeling study , 2017, PloS one.