Brain and Human Body Modelling 2021: Selected papers presented at 2021 BHBM Conference at Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital

165 Pages·2022·10.728 MB·English

by  Sergey Makarov, Gregory Noetscher, Aapo Nummenmaa

Sergey Makarov
Gregory Noetscher
Aapo Nummenmaa   Editors
Brain and
Human Body
Modelling 2021
Selected papers presented at 2021
BHBM Conference at Athinoula
A. Martinos Center for Biomedical
Imaging, Massachusetts General
Hospital
Brain and Human Body Modelling 2021
Sergey Makarov • Gregory Noetscher
Aapo Nummenmaa
Editors
Brain and Human Body
Modelling 2021
Selected papers presented at 2021 BHBM
Conference at Athinoula A. Martinos Center
for Biomedical Imaging, Massachusetts
General Hospital
Editors
Sergey Makarov Gregory Noetscher
ECE Department Worcester Polytechnic Institute
Worcester Polytechnic Institute Worcester, MA, USA
Worcester, MA, USA
Aapo Nummenmaa
Harvard Medical School
Massachusetts General Hospital
Charlestown, MA, USA
ISBN 978-3-031-15450-8 ISBN 978-3-031-15451-5 (eBook)
https://doi.org/10.1007/978-3-031-15451-5
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Contents
Part I Low Frequency Electromagnetic Modeling and Experiment:
Tumor Treating Fields
The Impact of Scalp’s Temperature in the Predicted LMiPD
in the Tumor During TTFields Treatment for Glioblastoma
Multiforme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Nichal Gentilal, Ariel Naveh, Tal Marciano, Zeev Bomzon,
Yevgeniy Telepinsky, Yoram Wasserman, and Pedro Cavaleiro Miranda
Standardizing Skullremodeling Surgery and Electrode Array
Layout to Improve Tumor Treating Fields Using Computational
Head Modeling and Finite Element Methods . . . . . . . . . . . . . . . . . . . . . . . . 19
N. Mikic, F. Cao, F. L. Hansen, A. M. Jakobsen, A. Thielscher,
and A. R. Korshøj
Part II Low Frequency Electromagnetic Modeling and Experiment:
Neural Stimulation in Gradient Coils
Peripheral Nerve Stimulation (PNS) Analysis of MRI
Head Gradient Coils with Human Body Models . . . . . . . . . . . . . . . . . . . . . 39
Yihe Hua, Desmond T. B. Yeo, and Thomas K. F. Foo
Part III Low Frequency Electromagnetic Modeling and Experiment:
Transcranial Magnetic Stimulation
Experimental Verification of a Computational Real-Time
Neuronavigation System for Multichannel Transcranial
Magnetic Stimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
Mohammad Daneshzand, Lucia I. Navarro de Lara, Qinglei Meng,
Sergey N. Makarov, Işıl Uluç, Jyrki Ahveninen, Tommi Raij,
and Aapo Nummenmaa
v
vi Contents
Evaluation and Comparison of Simulated Electric Field Differences
Using Three Image Segmentation Methods for TMS . . . . . . . . . . . . . . . . . 75
Tayeb Zaidi and Kyoko Fujimoto
Angle-Tuned Coil: A Focality-Adjustable Transcranial
Magnetic Stimulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
Qinglei Meng, Hedyeh Bagherzadeh, Elliot Hong, Yihong Yang,
Hanbing Lu, and Fow-Sen Choa
Part IV Low Frequency Electromagnetic Modeling and Experiment:
Spinal Cord Stimulation
Interplay Between Electrical Conductivity of Tissues
and Position of Electrodes in Transcutaneous Spinal
Direct Current Stimulation (tsDCS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Sofia R. Fernandes, Mariana Pereira, Sherif M. Elbasiouny,
Yasin Y. Dhaher, Mamede de Carvalho, and Pedro C. Miranda
Part V High Frequency Electromagnetic Modeling and Experiment:
MRI Safety with Active and Passive Implants
RF-induced Heating Near Active Implanted Medical Devices
in MRI: Impact of Tissue Simulating Medium . . . . . . . . . . . . . . . . . . . . . . 125
James E. Brown, Paul J. Stadnik, Jeffrey A. Von Arx,
and Dirk Muessig
Computational Tool Comprising Visible Human Project®
Based Anatomical Female CAD Model and Ansys
HFSS/Mechanical® FEM Software for Temperature Rise
Prediction Near an Orthopedic Femoral Nail Implant During a
1.5 T MRI Scan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Gregory Noetscher, Peter Serano, Ara Nazarian,
and Sergey N. Makarov
Part VI High Frequency Electromagnetic Modeling:
Microwave Imaging
Modeling and Experimental Results for Microwave Imaging
of a Hip with Emphasis on the Femoral Neck . . . . . . . . . . . . . . . . . . . . . . . 155
Johnathan Adams, Peter Serano, and Ara Nazarian
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
Part I
Low Frequency Electromagnetic Modeling
and Experiment: Tumor Treating Fields
The Impact of Scalp’s Temperature
in the Predicted LMiPD in the Tumor
During TTFields Treatment
for Glioblastoma Multiforme
Nichal Gentilal, Ariel Naveh, Tal Marciano, Zeev Bomzon,
Yevgeniy Telepinsky, Yoram Wasserman, and Pedro Cavaleiro Miranda
1 Introduction
1.1 Tumor Treating Fields (TTFields)
Tumor Treating Fields (TTFields) is an anti-mitotic cancer treatment technique
used for solid tumors. It consists in applying an electric field (EF) with a frequency
between 100 and 500 kHz in two perpendicular directions alternately to affect the
mitosis of tumoral cells [1]. TTFields are FDA-approved for the treatment of recur-
rent glioblastoma (GBM) since 2011, of newly diagnosed GBM cases since 2014,
and of malignant pleural mesothelioma since 2019, after the promising results from
the EF-11 [2], EF-14 [3] and STELLAR [4] clinical trials, respectively. The mecha-
nisms by which TTFields act are not completely understood, but in-vitro studies
showed that these EFs can slow down the rate at which tumoral cells divide or even
completely arrest cell proliferation for EF intensities at the tumor of at least 1 V/
cm [1, 5].
In patients, TTFields are applied using a specific device named Optune
(Novocure, Haifa, Israel) which consists in an electric field generator connected to
four arrays with 9 transducers each. These arrays work in pairs to induce an EF in
the tumor in two perpendicular directions alternately. The rationale behind the
application of the fields in more than one direction is based on the results of the in-
vitro study by Kirson et al. [5] that showed an increase of 20% in the number of
N. Gentilal (*) · P. C. Miranda
Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências da Universidade de
Lisboa, Campo Grande, Lisbon, Portugal
e-mail: [email protected]
A. Naveh · T. Marciano · Z. Bomzon · Y. Telepinsky · Y. Wasserman
Novocure LTD, Haifa, Israel
© The Author(s) 2023 3
S. Makarov et al. (eds.), Brain and Human Body Modelling 2021,
https://doi.org/10.1007/978-3-031-15451-5_1
4 N. Gentilal et al.
tumoral cells arrested during mitosis when two directions were used alternately
compared to a single direction.
Post-hoc analyses of clinical trials data showed that the time that a patient is on
active treatment, i.e., the treatment compliance, significantly affects the expected
overall survival (OS) [6]. Patients with recurrent GBM tumors that participated in
the EF-11 trial and whose daily compliance was at least 18 hours had an OS of
7.7 months, whereas those who were under treatment less than these 18 daily hours
had an OS of 4.5 months. More recently, Ballo et al. [7] used data from newly diag-
nosed GBM patients who took part on the EF-14 clinical trial to find a relation
between TTFields dose and treatment outcome. The results showed that the OS
survival is significantly different in patients whose average electric field in the
tumor was at least 1.06 V/cm (24.3 months vs. 21.6 months), thus corroborating
what was seen in in-vitro studies [1]. In the same study, the authors suggested a new
metric, the power density (PD), that could be used to evaluate treatment efficacy
instead of the electric field. By defining the dose in the tumor in the terms of PD,
TTFields planning will be more like other cancer treatment techniques planning,
such as radiotherapy, as this metric quantifies the energy that is deposited in tissues.
The same study showed that the threshold that best divides patients into the two
groups with the most significant difference in terms of OS is 1.15 mW/cm3.
1.2 Optimization of the Array Placement:
The NovoTAL System
To optimize the PD in both directions, the array layouts are strategically placed on
the scalp in regions that maximize the dose delivered to the tumor. The NovoTAL
system (Novocure, Haifa, Israel) is an FDA-approved tool used to help certified
physicians find the best array layouts for each patient. The importance of personal-
ized array layouts is clearly shown in the literature by different authors. The study
by Wenger et al. [8] was the first work to quantify the importance of creating per-
sonalized treatment maps for each patient based on tumor location. In general, the
average field intensity in the tumor increased between 32 and 45% when array posi-
tioning was adjusted to the tumor location. Smaller improvements were seen in the
work by Korshoej et al. [9], in which adapted layouts led to an enhancement of the
average field strength in the tumor between 9% and 23%.
In the NovoTAL system personalized head models are created and several
array layouts are tested to find the one that yields the best option for each patient.
One of the approaches that is most commonly considered comprehends an exten-
sive search in which a finite number of layouts, available in the NovoTAL data-
base, are tested and the one that induces the highest EF in the tumor is chosen.
After the best layout is known small adjustments can be made to optimize the
induced electric field. A detailed description of how this software works can be
found in [10].
The Impact of Scalp’s Temperature in the Predicted LMiPD in the Tumor… 5
1.3 Heat Transfer During Treatment
In the studies mentioned above, the choice of which layout to use was based solely
on the electric field delivered to the tumor. However, there are other factors that can
affect the current that is injected in each array pair during the therapy and conse-
quently the predicted treatment efficacy. As TTFields are applied for long periods of
time, the temperature of the head increases inevitably because of the Joule effect. To
avoid any thermal harm to tissues, the Optune device monitors the temperature of
the scalp and keeps it around 39.5 °C by controlling the amount of current that is
injected into each array pair. As the EF produced at the tumor by a given pair of
arrays is proportional to the injected current, a decrease in the injected current
implies a reduction in the EF at the tumor.
Recent computational studies [11–13] modelled how TTFields were applied
considering these thermal restrictions, quantified the temperature increases in tis-
sues and predicted what physiological changes could occur when TTFields were
applied. These works showed that heating was very localised, and it occurred mainly
underneath the regions where the transducers were placed. The scalp was the tissue
that heated up the most and the brain the one whose temperature varied the least. In
each tissue, the temperature increased the most at the surface and quickly decreased
with depth [13].
1.4 Aim of the Work
Given that the scalp’s temperature limits the dose that is administrated to the tumor,
and consequently the predicted treatment effectiveness, in this work we investigated
the impact of including this parameter on the choice of the best layout for TTFields
treatment.
2 Methods
2.1 The Simplified Head Model (SHM)
As a first step we used a simplified head model (SHM) to investigate the impact that
the temperature might have in the metric used to choose the best layout. This model
is composed by several spheroid shells each one representing a different tissue of
interest (scalp, skull, CSF, brain and ventricles) as shown in Fig. 1. The dimensions
assigned to each shell were based on the typical dimensions of the head of patients
that participated in the EF-14 clinical trial. A spherical lesion with a radius of
7.1 mm was also added to the model to mimic a GBM tumor.