Current state of the art of regional hyperthermia treatment planning: A review

Locoregional hyperthermia, i.e. increasing the tumor temperature to 40-45 °C using an external heating device, is a very effective radio and chemosensitizer, which significantly improves clinical outcome. There is a clear thermal dose-effect relation, but the pursued optimal thermal dose of 43 °C for 1 h can often not be realized due to treatment limiting hot spots in normal tissue. Modern heating devices have a large number of independent antennas, which provides flexible power steering to optimize tumor heating and minimize hot spots, but manual selection of optimal settings is difficult. Treatment planning is a very valuable tool to improve locoregional heating. This paper reviews the developments in treatment planning software for tissue segmentation, electromagnetic field calculations, thermal modeling and optimization techniques. Over the last decade, simulation tools have become more advanced. On-line use has become possible by implementing algorithms on the graphical processing unit, which allows real-time computations. The number of applications using treatment planning is increasing rapidly and moving on from retrospective analyses towards assisting prospective clinical treatment strategies. Some clinically relevant applications will be discussed

Real-time modelling and visualization of soft tissue thermomechanical behaviour for radiofrequency thermal ablation

A review of current literature indicates a limited knowledge and documentation of thermomechanical response of soft tissue during Minimally Invasive Surgical (MIS) hyperthermia procedures such as Radiofrequency Thermal Ablation (RFA). Furthermore, current models and simulations have not accounted for the temperature-dependence of the stress-strain behaviour of soft tissue. The only quantified data for temperature-dependent stress-strain relationships in literature is yielded from Xu and Lu (2009) and Xu, Seffen and Lu (2008a). As well as this, hardware-accelerated (by use of Graphics Processing Units (GPUs)) heat transfer simulations of RFA had not been documented prior to commencement of this project, and the first conference paper announcing this achievement was published in April of 2014 following research and implementation by NE Scientific LLC. A computational three-dimensional (3D) simulated virtual model of liver tissue is developed to establish temperature distributions resulting from single point temperature sources in emulation of the RFA heat treatment procedure. The temperature distribution in the virtual tissue domain is produced by Finite Element (FEM) spatial discretization and Finite Difference (FDM) temporal discretization of the Pennes bioheat transfer equation. The modelled temperature distribution is utilized to determine the degree of transient thermal damage to the virtual tissue based on the Arrhenius Burn Integration. Furthermore, the temperature distribution is used in conjunction with linear thermal expansion to model thermal strains and thermal stresses within the virtual tissue, resulting from the heat source. Novel work is undertaken in producing a thermal stress profile of virtual liver tissue under operational temperatures based on temperature-dependent material stress-strain. The simulation of tissue bioheat transfer and thermal damage is developed in C++ and the High-Level Shader Language (HLSL) with Microsoft’s Direct3D11 Application Programming Interface (API), where the numerical solution process is parallelized and accelerated in performance upon an NVIDIA GTX 770M GPU far beyond its performance upon a single thread/core of an Intel® Core™ i7-4700MQ Central Processing Unit (CPU). A maximum mesh resolution is determined for producing visual real-time post-processing output data based on the GPU accelerated simulation performance. A commercial FEM software package (LISA) is used for determining thermal strain and thermal stress distributions from the temperature distribution data. Examination of simulation results when comparing tissue thermomechanical response for temperature-independent and temperature-dependent stress-strain relationships indicates a dramatic difference in magnitude and distribution of the thermally-induced stresses within the soft tissue. The implications are that RFA simulations must account for this stress-strain temperature-dependence in order to produce remotely accurate stress and strain distributions (both thermomechanical and mechanical) due to the behavioural response of the collagenous biological soft tissue. Furthermore, GPU acceleration is highly recommended for RFA simulation, as the visual real-time maximum mesh resolution far surpasses that of real-time performed on a single modern CPU core

Doctor of Philosophy

dissertationMagnetic resonance-guided focused ultrasound surgery (MRgFUS) is a noninvasive means of causing selective tissue necrosis using high-power ultrasound and MR temperature imaging. Inhomogeneities in the medium of propagation can cause significant distortion of the ultrasound beam, resulting in changes in focal-zone amplitude, location and shape. Current ultrasound beam simulation techniques are either only applicable to homogeneous media or are relatively slow in calculating power deposition patterns in inhomogeneous media. Further, these techniques use table-value estimates of the acoustic parameters for predicting ultrasound beam propagation in inhomogeneous media, resulting in at best an approximate power deposition pattern. This work improves numerical analysis of ultrasound beam propagation by developing techniques for: 1) fast, accurate predictions of ultrasound beam propagation in inhomogeneous media, 2) noninvasive estimation of acoustic parameters (speed of sound and attenuation coefficient) of tissue types present in inhomogeneous media, 3) noninvasive determination of changes in tissue acoustic properties due to treatment. These beam simulation techniques utilizing subject-specific tissue parameters will rapidly predict power deposition patterns in real patient geometries and estimate changes in tissue acoustic parameters during treatment, leading to treatment-responsive patientspecific treatment plans that will improve the safety, efficacy and effectiveness of MRgFUS

A modeling-based assessment of acousto-optic sensing for monitoring high-intensity focused ultrasound lesion formation

Real-time acousto-optic (AO) sensing - a dual-wave modality that combines ultrasound with diffuse light to probe the optical properties of turbid media - has been demonstrated to non-invasively detect changes in ex vivo tissue optical properties during high-intensity focused ultrasound (HIFU) exposure. The AO signal indicates the onset of lesion formation and predicts resulting lesion volumes. Although proof-of-concept experiments have been successful, many of the underlying parameters and mechanisms affecting thermally induced optical property changes and the AO detectability of HIFU lesion formation are not well understood. In thesis, a numerical simulation was developed to model the AO sensing process and capture the relevant acoustic, thermal, and optical transport processes. The simulation required data that described how optical properties changed with heating. Experiments were carried out where excised chicken breast was exposed to thermal bath heating and changes in the optical absorption and scattering spectra (500 nm - 1100 nm) were measured using a scanning spectrophotometer and an integrating sphere assembly. Results showed that the standard thermal dose model currently used for guiding HIFU treatments needs to be adjusted to describe thermally induced optical property changes. To model the entire AO process, coupled models were used for ultrasound propagation, tissue heating, and diffusive light transport. The angular spectrum method was used to model the acoustic field from the HIFU source. Spatial-temporal temperature elevations induced by the absorption of ultrasound were modeled using a finite-difference time-domain solution to the Pennes bioheat equation. The thermal dose model was then used to determine optical properties based on the temperature history. The diffuse optical field in the tissue was then calculated using a GPU-accelerated Monte Carlo algorithm, which accounted for light-sound interactions and AO signal detection. The simulation was used to determine the optimal design for an AO guided HIFU system by evaluating the robustness of the systems signal to changes in tissue thickness, lesion optical contrast, and lesion location. It was determined that AO sensing is a clinically viable technique for guiding the ablation of large volumes and that real-time sensing may be feasible in the breast and prostate

Thermal analysis in a triple-layered skin structure with embedded vasculature, tumor, and gold nanoshells

In hyperthermia skin cancer treatment, the objective is to control laser heating of the tumor (target temperatures of 42-46 °C) so that the temperatures of the normal tissue surrounding the tumor remains low enough not to damage the normal tissue. However, obtaining accurate temperature distributions in living tissue related to hyperthermia skin cancer treatment without using an intruding sensor is a challenge. The objective of this dissertation research is to develop a mathematical model that can accurately predict the temperature distribution in the tumor region and surrounding normal tissue induced by laser irradiation. The model is based on a modified Pennes\u27 equation for the bioheat transfer in a 3-D triple-layered skin structure embedded with a vascular countercurrent network and a tumor appearing in the subcutaneous region. The vascular network is designed based on the constructal theory of multi-scale tree-shaped heat exchangers. The tumor is injected with gold nanoshells in order to be heated quickly. The proposed model is implemented numerically using a stable finite-difference scheme. To determine the laser intensity so that an optimal temperature distribution can be obtained, we pre-specify the temperature elevations to be obtained at the center of the tumor and on some locations on the perimeter of the skin\u27s surface. Using the least squares method, we obtain the optimal laser power and develop a computational procedure to obtain the temperature distribution. The method was tested in a 3-D triple-layered skin structure embedded with a vascular countercurrent network and a tumor appearing in the subcutaneous region. Gold nanoshells are assumed to have been injected into the central region of the tumor. The tumor region that has the gold nanoshells has ? x 109 particles/cm3 for each voxel of 0.01 cm x 0.01 cm x 0.001 cm. The tempeature is elevated by means of laser irradiation. The results show that the nanoshells have an effect on the tumor by heating the entire tumor to above 42 °C while not overheating the surrounding tissue. In comparison, results show that without nanoshells in the tumor region the tumor does heat up along its central axis; however, the perimeter of the tumor fails to reach 42 °C while the top of the skin reaches undesirable temperature levels due to the laser intensity required to heat the tumor. Such research may provide a useful tool for optimizing laser irradiation to kill the tumor while keeping the damage to the surrounding healthy tissue to a minimum (≤ 42 °C) during the hyperthermia cancer treatment

Evidence-based Development of Trustworthy Mobile Medical Apps

abstract: Widespread adoption of smartphone based Mobile Medical Apps (MMAs) is opening new avenues for innovation, bringing MMAs to the forefront of low cost healthcare delivery. These apps often control human physiology and work on sensitive data. Thus it is necessary to have evidences of their trustworthiness i.e. maintaining privacy of health data, long term operation of wearable sensors and ensuring no harm to the user before actual marketing. Traditionally, clinical studies are used to validate the trustworthiness of medical systems. However, they can take long time and could potentially harm the user. Such evidences can be generated using simulations and mathematical analysis. These methods involve estimating the MMA interactions with human physiology. However, the nonlinear nature of human physiology makes the estimation challenging. This research analyzes and develops MMA software while considering its interactions with human physiology to assure trustworthiness. A novel app development methodology is used to objectively evaluate trustworthiness of a MMA by generating evidences using automatic techniques. It involves developing the Health-Dev β tool to generate a) evidences of trustworthiness of MMAs and b) requirements assured code generation for vulnerable components of the MMA without hindering the app development process. In this method, all requests from MMAs pass through a trustworthy entity, Trustworthy Data Manager which checks if the app request satisfies the MMA requirements. This method is intended to expedite the design to marketing process of MMAs. The objectives of this research is to develop models, tools and theory for evidence generation and can be divided into the following themes: • Sustainable design configuration estimation of MMAs: Developing an optimization framework which can generate sustainable and safe sensor configuration while considering interactions of the MMA with the environment. • Evidence generation using simulation and formal methods: Developing models and tools to verify safety properties of the MMA design to ensure no harm to the human physiology. • Automatic code generation for MMAs: Investigating methods for automatically • Performance analysis of trustworthy data manager: Evaluating response time generating trustworthy software for vulnerable components of a MMA and evidences.performance of trustworthy data manager under interactions from non-MMA smartphone apps.Dissertation/ThesisDoctoral Dissertation Computer Science 201