Thermal ablation of biological tissues in disease treatment: A review of computational models and future directions

Percutaneous thermal ablation has proved to be an effective modality for treating both benign and malignant tumors in various tissues. Among these modalities, radiofrequency ablation (RFA) is the most promising and widely adopted approach that has been extensively studied in the past decades. Microwave ablation (MWA) is a newly emerging modality that is gaining rapid momentum due to its capability of inducing rapid heating and attaining larger ablation volumes, and its lesser susceptibility to the heat sink effects as compared to RFA. Although the goal of both these therapies is to attain cell death in the target tissue by virtue of heating above 50 oC, their underlying mechanism of action and principles greatly differs. Computational modelling is a powerful tool for studying the effect of electromagnetic interactions within the biological tissues and predicting the treatment outcomes during thermal ablative therapies. Such a priori estimation can assist the clinical practitioners during treatment planning with the goal of attaining successful tumor destruction and preservation of the surrounding healthy tissue and critical structures. This review provides current state-of- the-art developments and associated challenges in the computational modelling of thermal ablative techniques, viz., RFA and MWA, as well as touch upon several promising avenues in the modelling of laser ablation, nanoparticles assisted magnetic hyperthermia and non- invasive RFA. The application of RFA in pain relief has been extensively reviewed from modelling point of view. Additionally, future directions have also been provided to improve these models for their successful translation and integration into the hospital work flow

Computational Models and Experimentation for Radiofrequency-based Ablative Techniques

Las técnicas ablativas basadas en energía por radiofrecuencia (RF) se emplean con el fin de lograr un calentamiento seguro y localizado en el tejido biológico. En los últimos años ha habido un rápido crecimiento en el número de nuevos procedimientos médicos que hacen uso de dichas técnicas, lo cual ha ido acompañado de la aparición de nuevos diseños de electrodos y protocolos de aplicación de energía. Sin embargo, existen todavía muchas incógnitas sobre el verdadero comportamiento electro-térmico de los aplicadores de energía, así como de la interacción energía-tejido en aplicaciones concretas. El principal propósito de esta Tesis Doctoral es adquirir un mejor conocimiento de los fenómenos eléctricos y térmicos involucrados en los procesos de calentamiento de tejidos biológicos mediante corrientes de RF. Esto permitirá, por un lado, mejorar la eficacia y seguridad de las técnicas actualmente empleadas en la clínica en campos tan diferentes como la cirugía cardiaca, oncológica o dermatológica; y por otro, sugerir mejoras tecnológicas para el diseño de nuevos aplicadores. La Tesis Doctoral combina dos metodologías ampliamente utilizadas en el campo de la Ingeniería Biomédica, como son el modelado computacional (matemático) y la experimentación (ex vivo e in vivo). En cuanto al área cardiaca, la investigación se ha centrado, por una parte, en mejorar la ablación intraoperatoria de la fibrilación auricular por aproximación epicárdica, es decir, susceptible de ser realizada de forma mínimamente invasiva. Para ello, se ha estudiado mediante modelos matemáticos un sistema de medida de la impedancia epicárdica como método de valoración de la cantidad de grasa previo a la ablación. Por otra parte, se ha estudiado cómo mejorar la ablación de la pared ventricular por aproximación endocárdica-endocárdica (septo interventricular) y endocárdica-epicárdica (pared libre del ventrículo). Con este objetivo, se han comparado mediante modelado por computador la eficacia de los modos de ablación bipolar y unipolar en términos de la transmuralidad de la lesión en la pared ventricular. En lo que respecta al área de cirugía oncológica, la investigación se ha centrado en la resección hepática asistida por RF. Las técnicas de calentamiento por RF deberían ser capaces de minimizar el sangrado intraoperatorio y sellar vasos y ductos mediante la creación de una necrosis coagulativa por calentamiento. Si este calentamiento se produce en las cercanías de grandes vasos, existe un problema potencial de daño a la pared de dicho vaso. En este sentido, se ha evaluado con modelos matemáticos y experimentación in vivo si el efecto del flujo de sangre dentro de un gran vaso es capaz de proteger térmicamente su pared cuando se realiza una resección asistida por RF en sus cercanías. Además, se ha realizado un estudio computacional y experimental ex vivo e in vivo del comportamiento electro-térmico de aplicadores de RF bipolares internamente refrigerados, puesto que representan una opción más segura frente a los monopolares en la medida en que las corrientes de RF fluyen casi exclusivamente por el tejido biológico situado entre ambos electrodos. Respecto al área dermatológica, la investigación se ha centrado en mejorar el tratamiento de enfermedades o desórdenes del tejido subcutáneo (tales como lipomatosis, lipedema, enfermedad de Madelung y celulitis) mediante el estudio teórico de la dosimetría correcta en cada caso. Para ello, se han evaluado los efectos eléctricos, térmicos y termo-elásticos de dos estructuras diferentes de tejido subcutáneo durante el calentamiento por RF, y se ha cuantificado el daño térmico producido en ambas estructuras tras dicho calentamientoGonzález Suárez, A. (2014). Computational Models and Experimentation for Radiofrequency-based Ablative Techniques [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/36502TESI

Preoperative trajectory planning for percutaneous procedures in deformable environments

International audienceIn image-guided percutaneous interventions, a precise planning of the needle path is a key factor to a successful intervention. In this paper we propose a novel method for computing a patient-specific optimal path for such interventions, accounting for both the deformation of the needle and soft tissues due to the insertion of the needle in the body. To achieve this objective, we propose an optimization method for estimating preoperatively a curved trajectory allowing to reach a target even in the case of tissue motion and needle bending. Needle insertions are simulated and regarded as evaluations of the objective function by the iterative planning process. In order to test the planning algorithm, it is coupled with a fast needle insertion simulation involving a flexible needle model and soft tissue finite element modeling, and experimented on the use-case of thermal ablation of liver tumors. Our algorithm has been successfully tested on twelve datasets of patient-specific geometries. Fast convergence to the actual optimal solution has been shown. This method is designed to be adapted to a wide range of percutaneous interventions

A 3-Dimensional In Silico Test Bed for Radiofrequency Ablation Catheter Design Evaluation and Optimization

Atrial fibrillation (AF) is the disordered activation of the atrial myocardium, which is a major cause of stroke. Currently, the most effective, minimally traumatic treatment for AF is percutaneous catheter ablation to isolate arrhythmogenic areas from the rest of the atrium. The standard in vitro evaluation of ablation catheters through lesion studies is a resource intensive effort due to tissue variability and visual measurement methods, necessitating large sample sizes and multiple prototype builds. A computational test bed for ablation catheter evaluation was built in SolidWorks® using the morphology and dimensions of the left atrium adjacent structures. From this geometry, the physical model was built in COMSOL Multiphysics®, where a combination of the laminar fluid flow, electrical currents, and bioheat transfer was used to simulate radiofrequency (RF) tissue ablation. Simulations in simplified 3D geometries led to lesions sizes within the reported ranges from an in-vivo ablation study. However, though the ellipsoid lesion morphologies in the full atrial model were consistent with past lesion studies, perpendicularly oriented catheter tips were associated with decreases of -91.3% and -70.0% in lesion depth and maximum diameter. On the other hand, tangentially oriented catheter tips produced lesions that were only off by -28.4% and +7.9% for max depth and max diameter. Preliminary investigation into the causes of the discrepancy were performed for fluid velocities, contact area, and other factors. Finally, suggestions for further investigation are provided to aid in determining the root cause of the discrepancy, such that the test bed may be used for other ablation catheter evaluations

Investigation of Heat Therapies using Multi-Scale Models and Statistical Methods

Ph.DDOCTOR OF PHILOSOPH

Parameter Estimation for Personalization of Liver Tumor Radiofrequency Ablation

International audienceMathematical modeling has the potential to assist radiofrequency ablation (RFA) of tumors as it enables prediction of the extent of ablation. However, the accuracy of the simulation is challenged by the material properties since they are patient-specific, temperature and space dependent. In this paper, we present a framework for patient specific radiofrequency ablation modeling of multiple lesions in the case of metastatic diseases. The proposed forward model is based upon a computational model of heat diffusion, cellular necrosis and blood flow through vessels and liver which relies on patient images. We estimate the most sensitive material parameters, those need to be personalized from the available clinical imaging and data. The selected parameters are then estimated using inverse modeling such that the point to-mesh distance between the computed necrotic area and observed lesions is minimized. Based on the personalized parameters, the ablation of the remaining lesions are predicted. The framework is applied to a dataset of seven lesions from three patients including pre- and post-operative CT images. In each case, the parameters were estimated on one tumor and RFA is simulated on the other tumor(s) using these personalized parameters, assuming the parameters to be spatially invariant within the same patient. Results showed significantly good correlation between predicted and actual ablation extent (average point-to-mesh errors of 4.03 mm)