Standardization and Validation of Brachytherapy Seeds'' Modelling Using GATE and GGEMS Monte Carlo Toolkits

Simple Summary:& nbsp;This study used GATE and GGEMS simulation toolkits, to estimate dose distribution on Brachytherapy procedures. Specific guidelines were followed as defined by the American Association of Physicists in Medicine (AAPM) as well as by the European SocieTy for Radiotherapy and Oncology (ESTRO). Several types of brachytherapy seeds were modelled and simulated, namely Low-Dose-Rate (LDR), High-Dose-Rate (HDR), and Pulsed-Dose-Rate (PDR). The basic difference between GATE and GGEMS is that GGEMS incorporates GPU capabilities, which makes the use of Monte Carlo (MC) simulations more accessible in clinical routine, by minimizing the computational time to obtain a dose map. During the validation procedure of both codes with protocol data, differences as well as uncertainties were measured within the margins defined by the guidelines. The study concluded that MC simulations may be utilized in clinical practice, to optimize dose distribution in real time, as well as to evaluate therapeutic plans.This study aims to validate GATE and GGEMS simulation toolkits for brachytherapy applications and to provide accurate models for six commercial brachytherapy seeds, which will be freely available for research purposes. The AAPM TG-43 guidelines were used for the validation of two Low Dose Rate (LDR), three High Dose Rate (HDR), and one Pulsed Dose Rate (PDR) brachytherapy seeds. Each seed was represented as a 3D model and then simulated in GATE to produce one single Phase-Space (PHSP) per seed. To test the validity of the simulations'' outcome, referenced data (provided by the TG-43) was compared with GATE results. Next, validation of the GGEMS toolkit was achieved by comparing its outcome with the GATE MC simulations, incorporating clinical data. The simulation outcomes on the radial dose function (RDF), anisotropy function (AF), and dose rate constant (DRC) for the six commercial seeds were compared with TG-43 values. The statistical uncertainty was limited to 1% for RDF, to 6% (maximum) for AF, and to 2.7% (maximum) for the DRC. GGEMS provided a good agreement with GATE when compared in different situations: (a) Homogeneous water sphere, (b) heterogeneous CT phantom, and (c) a realistic clinical case. In addition, GGEMS has the advantage of very fast simulations. For the clinical case, where TG-186 guidelines were considered, GATE required 1 h for the simulation while GGEMS needed 162 s to reach the same statistical uncertainty. This study produced accurate models and simulations of their emitted spectrum of commonly used commercial brachytherapy seeds which are freely available to the scientific community. Furthermore, GGEMS was validated as an MC GPU based tool for brachytherapy. More research is deemed necessary for the expansion of brachytherapy seed modeling

Brain and Human Body Modeling

This open access book describes modern applications of computational human modeling with specific emphasis in the areas of neurology and neuroelectromagnetics, depression and cancer treatments, radio-frequency studies and wireless communications. Special consideration is also given to the use of human modeling to the computational assessment of relevant regulatory and safety requirements. Readers working on applications that may expose human subjects to electromagnetic radiation will benefit from this book’s coverage of the latest developments in computational modelling and human phantom development to assess a given technology’s safety and efficacy in a timely manner. Describes construction and application of computational human models including anatomically detailed and subject specific models; Explains new practices in computational human modeling for neuroelectromagnetics, electromagnetic safety, and exposure evaluations; Includes a survey of modern applications for which computational human models are critical; Describes cellular-level interactions between the human body and electromagnetic fields

Functionalized Anatomical Models for Computational Life Sciences

The advent of detailed computational anatomical models has opened new avenues for computational life sciences (CLS). To date, static models representing the anatomical environment have been used in many applications but are insufficient when the dynamics of the body prevents separation of anatomical geometrical variability from physics and physiology. Obvious examples include the assessment of thermal risks in magnetic resonance imaging and planning for radiofrequency and acoustic cancer treatment, where posture and physiology-related changes in shape (e.g., breathing) or tissue behavior (e.g., thermoregulation) affect the impact. Advanced functionalized anatomical models can overcome these limitations and dramatically broaden the applicability of CLS in basic research, the development of novel devices/therapies, and the assessment of their safety and efficacy. Various forms of functionalization are discussed in this paper: (i) shape parametrization (e.g., heartbeat, population variability), (ii) physical property distributions (e.g., image-based inhomogeneity), (iii) physiological dynamics (e.g., tissue and organ behavior), and (iv) integration of simulation/measurement data (e.g., exposure conditions, “validation evidence” supporting model tuning and validation). Although current model functionalization may only represent a small part of the physiology, it already facilitates the next level of realism by (i) driving consistency among anatomy and different functionalization layers and highlighting dependencies, (ii) enabling third-party use of validated functionalization layers as established simulation tools, and (iii) therefore facilitating their application as building blocks in network or multi-scale computational models. Integration in functionalized anatomical models thus leverages and potentiates the value of sub-models and simulation/measurement data toward ever-increasing simulation realism. In our o2S2PARC platform, we propose to expand the concept of functionalized anatomical models to establish an integration and sharing service for heterogeneous computational models, ranging from the molecular to the organ level. The objective of o2S2PARC is to integrate all models developed within the National Institutes of Health SPARC initiative in a unified anatomical and computational environment, to study the role of the peripheral nervous system in controlling organ physiology. The functionalization concept, as outlined for the o2S2PARC platform, could form the basis for many other application areas of CLS. The relationship to other ongoing initiatives, such as the Physiome Project, is also presented

Numerical modeling of percutaneous auricular vagus nerve stimulation : a realistic 3D model to evaluate sensitivity of neural activation to electrode position

Percutaneous stimulation of the auricular branch of the vagus nerve (pVNS) by miniaturized needle electrodes in the auricle gained importance as a treatment for acute and chronic pain. The objective is to establish a realistic numerical model of pVNS and investigate the effects of stimulation waveform, electrodes' depth, and electrodes' position on nerve excitation threshold and the percentage of stimulated nerves. Simulations were performed with Sim4Life. An electrostatic solver and neural tissue models were combined for electromagnetic and neural simulation. The numerical model consisted of a realistic high-resolution model of a human ear, blood vessels, nerves, and three needle electrodes. A novel 3D ear model was established, including blood vessels and nerves. The electric field distribution was extracted and evaluated. Maximum sensitivity to needles' depth and displacement was evaluated to be 9.8 and 15.5% per 0.1 mm, respectively. Stimulation was most effective using biphasic compared to mono-phasic pulses. The established model allows easy and quantitative evaluation of various stimulation setups, enabling optimization of pVNS in experimental settings. Results suggest a high sensitivity of pVNS to the electrodes' position and depth, implying the need for precise electrode positioning. Validation of the model needs to be performed