Thermal dosimetry for bladder hyperthermia treatment. An overview.

The urinary bladder is a fluid-filled organ. This makes, on the one hand, the internal surface of the bladder wall relatively easy to heat and ensures in most cases a relatively homogeneous temperature distribution; on the other hand the variable volume, organ motion, and moving fluid cause artefacts for most non-invasive thermometry methods, and require additional efforts in planning accurate thermal treatment of bladder cancer. We give an overview of the thermometry methods currently used and investigated for hyperthermia treatments of bladder cancer, and discuss their advantages and disadvantages within the context of the specific disease (muscle-invasive or non-muscle-invasive bladder cancer) and the heating technique used. The role of treatment simulation to determine the thermal dose delivered is also discussed. Generally speaking, invasive measurement methods are more accurate than non-invasive methods, but provide more limited spatial information; therefore, a combination of both is desirable, preferably supplemented by simulations. Current efforts at research and clinical centres continue to improve non-invasive thermometry methods and the reliability of treatment planning and control software. Due to the challenges in measuring temperature across the non-stationary bladder wall and surrounding tissues, more research is needed to increase our knowledge about the penetration depth and typical heating pattern of the various hyperthermia devices, in order to further improve treatments. The ability to better determine the delivered thermal dose will enable clinicians to investigate the optimal treatment parameters, and consequentially, to give better controlled, thus even more reliable and effective, thermal treatments

Identification of Material Parameters from Temperature Measurements in Radio Frequency Ablation

The mathematical simulation of the method of radio frequency ablation (RFA) offers an opportunity to improve the success of the RFA. The results of the RFA depend highly on the experience of the radiologist. A simulation will offer a prediction of the results which can be used to adapt the setting and enable a complete destruction of the tumor, e.g. by adapting the probe's position. A good simulation needs as much information of the reality as possible. Especially the material properties pose a challenge since they vary from patient to patient, they can not be measured in vivo and they additionally change during the ablation. The aim of this thesis is to develop a mathematical model for the identification of the material parameters from temperature measurements and apply it to appropriate data sets. At first a minimization problem is formulated, where the difference between the measured temperature and the calculated temperature is minimized with respect to the material parameters. The temperature distribution is calculated with a coupled system of partial differential equations. Different approaches are considered which depend on the diverse modeling of the material parameters. The parameters are modeled as constant values as well as temperature dependent, tissue dependent and also spatially distributed. The advantages and disadvantages of the diverse models are illustrated by the numerical results for the identification with artificial temperature distributions as well as real temperature measurements

Identification of Material Parameters from Temperature Measurements in Radio Frequency Ablation

The mathematical simulation of the method of radio frequency ablation (RFA) offers an opportunity to improve the success of the RFA. The results of the RFA depend highly on the experience of the radiologist. A simulation will offer a prediction of the results which can be used to adapt the setting and enable a complete destruction of the tumor, e.g. by adapting the probe's position. A good simulation needs as much information of the reality as possible. Especially the material properties pose a challenge since they vary from patient to patient, they can not be measured in vivo and they additionally change during the ablation. The aim of this thesis is to develop a mathematical model for the identification of the material parameters from temperature measurements and apply it to appropriate data sets. At first a minimization problem is formulated, where the difference between the measured temperature and the calculated temperature is minimized with respect to the material parameters. The temperature distribution is calculated with a coupled system of partial differential equations. Different approaches are considered which depend on the diverse modeling of the material parameters. The parameters are modeled as constant values as well as temperature dependent, tissue dependent and also spatially distributed. The advantages and disadvantages of the diverse models are illustrated by the numerical results for the identification with artificial temperature distributions as well as real temperature measurements

Determination of Thermal Dose Model Parameters Using Magnetic Resonance Imaging

Magnetic Resonance Temperature Imaging (MRTI) is a powerful technique for noninvasively monitoring temperature during minimally invasive thermal therapy procedures. When coupled with thermal dose models, MRTI feedback provides the clinician with a real-time estimate of tissue damage by functioning as a surrogate for post-treatment verification imaging. This aids in maximizing the safety and efficacy of treatment by facilitating adaptive control of the damaged volume during therapy. The underlying thermal dose parameters are derived from laboratory experiments that do not necessarily reflect the surrogate imaging endpoints used for treatment verification. Thus, there is interest and opportunity in deriving model parameters from clinical procedures that are tailored to radiologic endpoints. The objective of this work is to develop and investigate the feasibility of a methodology for extracting thermal dose model parameters from MR data acquired during ablation procedures. To this end, two approaches are investigated. One is to optimize model parameters using post-treatment imaging outcomes. Another is to use a multi-parametric pulse sequence designed for simultaneous monitoring of temperature and damage dependent MR parameters. These methodologies were developed and investigated in phantom and feasibility established using retrospective analysis of in vivo thermal therapy treatments. This technique represents an opportunity to exploit experimental data to obtain thermal dose parameters that are highly specific for clinically relevant endpoints

Multi-objective particle swarm optimization for the structural design of concentric tube continuum robots for medical applications

Concentric tube robots belong to the class of continuum robotic systems whose morphology is described by continuous tangent curvature vectors. They are composed of multiple, interacting tubes nested inside one another and are characterized by their inherent flexibility. Concentric tube continuum robots equipped with tools at their distal end have high potential in minimally invasive surgery. Their morphology enables them to reach sites within the body that are inaccessible with commercial tools or that require large incisions. Further, they can be deployed through a tight lumen or follow a nonlinear path. Fundamental research has been the focus during the last years bringing them closer to the operating room. However, there remain challenges that require attention. The structural synthesis of concentric tube continuum robots is one of these challenges, as these types of robots are characterized by their large parameter space. On the one hand, this is advantageous, as they can be deployed in different patients, anatomies, or medical applications. On the other hand, the composition of the tubes and their design is not a straightforward task but one that requires intensive knowledge of anatomy and structural behavior. Prior to the utilization of such robots, the composition of tubes (i.e. the selection of design parameters and application-specific constraints) must be solved to determine a robotic design that is specifically targeted towards an application or patient. Kinematic models that describe the change in morphology and complex motion increase the complexity of this synthesis, as their mathematical description is highly nonlinear. Thus, the state of the art is concerned with the structural design of these types of robots and proposes optimization algorithms to solve for a composition of tubes for a specific patient case or application. However, existing approaches do not consider the overall parameter space, cannot handle the nonlinearity of the model, or multiple objectives that describe most medical applications and tasks. This work aims to solve these fundamental challenges by solving the parameter optimization problem by utilizing a multi-objective optimization algorithm. The main concern of this thesis is the general methodology to solve for patient- and application-specific design of concentric tube continuum robots and presents key parameters, objectives, and constraints. The proposed optimization method is based on evolutionary concepts that can handle multiple objectives, where the set of parameters is represented by a decision vector that can be of variable dimension in multidimensional space. Global optimization algorithms specifically target the constrained search space of concentric tube continuum robots and nonlinear optimization enables to handle the highly nonlinear elasticity modeling. The proposed methodology is then evaluated based on three examples that include cooperative task deployment of two robotic arms, structural stiffness optimization under the consideration of workspace constraints and external forces, and laser-induced thermal therapy in the brain using a concentric tube continuum robot. In summary, the main contributions are 1) the development of an optimization methodology that describes the key parameters, objectives, and constraints of the parameter optimization problem of concentric tube continuum robots, 2) the selection of an appropriate optimization algorithm that can handle the multidimensional search space and diversity of the optimization problem with multiple objectives, and 3) the evaluation of the proposed optimization methodology and structural synthesis based on three real applications

Robotic System Development for Precision MRI-Guided Needle-Based Interventions

This dissertation describes the development of a methodology for implementing robotic systems for interventional procedures under intraoperative Magnetic Resonance Imaging (MRI) guidance. MRI is an ideal imaging modality for surgical guidance of diagnostic and therapeutic procedures, thanks to its ability to perform high resolution, real-time, and high soft tissue contrast imaging without ionizing radiation. However, the strong magnetic field and sensitivity to radio frequency signals, as well as tightly confined scanner bore render great challenges to developing robotic systems within MRI environment. Discussed are potential solutions to address engineering topics related to development of MRI-compatible electro-mechanical systems and modeling of steerable needle interventions. A robotic framework is developed based on a modular design approach, supporting varying MRI-guided interventional procedures, with stereotactic neurosurgery and prostate cancer therapy as two driving exemplary applications. A piezoelectrically actuated electro-mechanical system is designed to provide precise needle placement in the bore of the scanner under interactive MRI-guidance, while overcoming the challenges inherent to MRI-guided procedures. This work presents the development of the robotic system in the aspects of requirements definition, clinical work flow development, mechanism optimization, control system design and experimental evaluation. A steerable needle is beneficial for interventional procedures with its capability to produce curved path, avoiding anatomical obstacles or compensating for needle placement errors. Two kinds of steerable needles are discussed, i.e. asymmetric-tip needle and concentric-tube cannula. A novel Gaussian-based ContinUous Rotation and Variable-curvature (CURV) model is proposed to steer asymmetric-tip needle, which enables variable curvature of the needle trajectory with independent control of needle rotation and insertion. While concentric-tube cannula is suitable for clinical applications where a curved trajectory is needed without relying on tissue interaction force. This dissertation addresses fundamental challenges in developing and deploying MRI-compatible robotic systems, and enables the technologies for MRI-guided needle-based interventions. This study applied and evaluated these techniques to a system for prostate biopsy that is currently in clinical trials, developed a neurosurgery robot prototype for interstitial thermal therapy of brain cancer under MRI guidance, and demonstrated needle steering using both asymmetric tip and pre-bent concentric-tube cannula approaches on a testbed

Radiofrequency ablation combined with conductive fluid-based dopants (saline normal and colloidal gold): computer modeling and ex vivo experiments

[EN] Background: The volume of the coagulation zones created during radiofrequency ablation (RFA) is limited by the appearance of roll-off. Doping the tissue with conductive fluids, e.g., gold nanoparticles (AuNPs) could enlarge these zones by delaying roll-off. Our goal was to characterize the electrical conductivity of a substrate doped with AuNPs in a computer modeling study and ex vivo experiments to investigate their effect on coagulation zone volumes. Methods: The electrical conductivity of substrates doped with normal saline or AuNPs was assessed experimentally on agar phantoms. The computer models, built and solved on COMSOL Multiphysics, consisted of a cylindrical domain mimicking liver tissue and a spherical domain mimicking a doped zone with 2, 3 and 4 cm diameters. Ex vivo experiments were conducted on bovine liver fragments under three different conditions: non-doped tissue (ND Group), 2 mL of 0.9% NaCl (NaCl Group), and 2 mL of AuNPs 0.1 wt% (AuNPs Group). Results: The theoretical analysis showed that adding normal saline or colloidal gold in concentrations lower than 10% only modifies the electrical conductivity of the doped substrate with practically no change in the thermal characteristics. The computer results showed a relationship between doped zone size and electrode length regarding the created coagulation zone. There was good agreement between the ex vivo and computational results in terms of transverse diameter of the coagulation zone. Conclusions: Both the computer and ex vivo experiments showed that doping with AuNPs can enlarge the coagulation zone, especially the transverse diameter and hence enhance sphericity.This work was supported by the National Council of Science and Technology (CONACYT, Mexico) through a scholarship grant to Dora Luz Castro-Lopez, CVU Registration No. 446604; and by the Spanish Ministerio de Ciencia, Innovacion y Universidades under the "Plan Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad", Grant No "RTI2018-094357-B-C21"Castro-López, DL.; Berjano, E.; Romero-Méndez, R. (2021). Radiofrequency ablation combined with conductive fluid-based dopants (saline normal and colloidal gold): computer modeling and ex vivo experiments. BioMedical Engineering OnLine. 20:1-20. https://doi.org/10.1186/s12938-020-00842-8S12020Zhu F, Rhim H. Thermal ablation for hepatocellular carcinoma: what’s new in 2019. 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