Sergey Makarov

Sergey Makarov · Marc Horner Gregory Noetscher Editors Brain and Human Body Modeling Computational Human Modeling at EMBC 2018 Brain and Human Body Modeling Sergey Makarov • Marc Horner Gregory Noetscher Editors Brain and Human Body Modeling Computational Human Modeling at EMBC 2018 Editors Sergey Makarov Marc Horner Massachusetts General Hospital ANSYS, Inc. Boston, MA, USA Evanston, IL, USA Worcester Polytechnic Institute Worcester, MA, USA Gregory Noetscher Worcester Polytechnic Institute Worcester, MA, USA This book is an open access publication. ISBN 978-3-030-21292-6 ISBN 978-3-030-21293-3 (eBook) https://doi.org/10.1007/978-3-030-21293-3 © The Editor(s) (if applicable) and The Author(s) 2019 Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this book are included in the book’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the book’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. 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This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface to Computation Human Models and Brain Modeling: EMBC 2018 Numerical modeling has become an essential enabling technology in a variety of engineering fields, including mechanics, chemistry, fluid dynamics, electromagnet- ics, and acoustics. Modeling accelerates the product development cycle, giving sci- entists and engineers the opportunity to explore design iterations and scenarios in virtual space, and allowing optimization over a host of external conditions that would be time and cost prohibitive to experimentally characterize and quantify. Furthermore, simulations permit the examination of resulting field values, such as internal current distributions or energy absorption in tissues that would typically not be available to an experimentalist due to safety or ethics concerns. However, regardless of the physics under consideration or the method utilized, every practitioner in the field of numerical modeling knows one fundamental rule: the simulation is only as good as the underlying model being employed. This is a more articulate or eloquent way of saying “garbage in equals garbage out,” but regardless of how it is phrased, the message is the same. If there are fundamental flaws or inaccuracies in the model that mask or modify the physics under examination, even if the simulation itself runs flawlessly, results might be erroneous and predictions based on that simulation will not accurately embody the intended aspects of the physical world. It is with this motivation in mind that developers of phantoms characterizing the human body and its corresponding physiological pro- cesses have continuously advanced the state of the art and pursued ever more accurate representations of human anatomy at a variety of geometric scales. Advancements in human phantoms are a product of many converging disciplines, ranging from the basic sciences of chemistry, biology, and physics to more applied areas such as electrical and computer engineering, material science, medical data acquisition and segmentation, surface and volumetric mesh manipulation, and large-scale data processing. The memory and computational processing limitations encountered in previous model generations, where human bodies were represented with basic, homogeneous geometric primitives or highly de-featured faceted models, no longer apply to modern simulation platforms. The rapid advance in comput- ing hardware permits a new generation of ever more detailed models with substantially enhanced levels of anatomical accuracy. Similarly, the incorporation v vi Preface to Computation Human Models and Brain Modeling: EMBC 2018 of sophisticated material properties to support coupled multi-physics simulations is also now possible. Furthermore, advances in our understanding of the anatomy and physiology of the human body continue to provide ever-growing insights into the tissue properties and their detailed organization at the macro- and microscopic levels, thus enabling models that increasingly capture the most relevant properties. As human models have improved, the scope of applications examined via simulation has also grown, providing researchers and engineers with powerful tools to explore new and exciting hypotheses regarding human physiology, pathophysiol- ogy, and biomedical engineering. The application of electromagnetic fields in biomedical engineering has produced promising diagnostic and therapeutic methodologies and protocols that may now be competently and thoroughly studied to generate detailed analyses on estimated efficacy and patient safety. Topics of recent interest to the research and medical communities are broadly distributed across the electromagnetic frequency spectrum and include: cancer ablation via radio frequency (RF) heating; safety and efficacy assessments of patients with and without implanted medical devices during procedures such as magnetic resonance imaging (MRI); new and varied coil designs for optimal MRI protocols; treatment of brain disorders, such as depression, via noninvasive brain stimulation techniques like transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS); optimal design, configuration, and placement of single or multiple coils or electrodes for focused and deep internal electromagnetic field generation; pain management therapies that rely on noninvasive nerve stimulation rather than potentially addictive pharmaceuticals; and many others. While seemingly disparate, these applications are united in their need for high-quality computational human phantoms and optimized simulation methods that enable fast and accurate approxi- mations of the underlying physics that govern responses of the body to externally applied electromagnetic stimuli. This is the motivation that drives the research contained in this work and has provided inspiration to the researchers and engineers laboring in this field. This work is a collection of selected papers presented during the third Annual Invited Session on Computational Human Models. The session was conducted from July 17 to 21, 2018, in Honolulu, HI, as part of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), which provided a collaborative platform showcasing academic and commercial research representing the current state of the art in computational human models and applications for which they are employed. The various session tracks brought together subject matter experts in diverse fields representing academia, government institutions, and industry partners. A clear outcome of this effort was a comprehen- sive, multidisciplinary review of each area, and the promotion of a rich dialogue on promising future paths in human phantom development, numerical methods, and simulation applications. The chapters presented here provide an overview of the invited session and highlight a myriad of potential avenues of development and exploration during future EMBS conferences. The first section presents chapters devoted to models specifically tailored for noninvasive stimulation. A collection of techniques that employ the physics of elec- Preface to Computation Human Models and Brain Modeling: EMBC 2018 vii tromagnetism to stimulate specific regions of human anatomy are reviewed. The research is aimed at treating various pathologies, including neurological disorders treated with noninvasive brain stimulation and chronic pain treated via peripheral nerve stimulation. Several brain stimulation modalities are presented along with custom models that have been generated to best represent the anatomic features most affected by these treatments. The second section is devoted to tumor-treating fields (TTFields), which is a new and promising treatment for glioblastoma that was recently approved by the US Food and Drug Administration. The simulations employed in these chapters include human models that inform practitioners on the impact of electrode placements on the surface of the body, leading to optimization of electrode configurations and knowledge-based estimates of the resulting field strengths

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