Adapting Temperature Predictions to MR Imaging in Treatment Position to Improve Simulation-Guided Hyperthermia for Cervical Cancer.

Hyperthermia treatment consists of elevating the temperature of the tumor to increase the effectiveness of radiotherapy and chemotherapy. Hyperthermia treatment planning (HTP) is an important tool to optimize treatment quality using pre-treatment temperature predictions. The accuracy of these predictions depends on modeling uncertainties such as tissue properties and positioning. In this study, we evaluated if HTP accuracy improves when the patient is imaged inside the applicator at the start of treatment. Because perfusion is a major uncertainty source, the importance of accurate treatment position and anatomy was evaluated using different perfusion values. Volunteers were scanned using MR imaging without ("planning setup") and with the MR-compatible hyperthermia device ("treatment setup"). Temperature-based quality indicators were used to assess the differences between the standard, apparent and the optimized hyperthermia dose. We conclude that pre-treatment imaging can improve HTP predictions accuracy but also, that tissue perfusion modelling is crucial if temperature-based optimization is applied.

MATLAB-based innovative 3D finite element method simulator for optimized real-time hyperthermia analysis.

BACKGROUND AND OBJECTIVE: Owing to the significant role of hyperthermia in enhancing the efficacy of chemotherapy or radiotherapy for treating malignant tissues, this study introduces a real-time hyperthermia simulator (RTHS) based on the three-dimensional finite element method (FEM) developed using the MATLAB App Designer. METHODS: The simulator consisted of operator-defined homogeneous and heterogeneous phantom models surrounded by an annular phased array (APA) of eight dipole antennas designed at 915 MHz. Electromagnetic and thermal analyses were conducted using the RTHS. To locally raise the target temperature according to the tumor's location, a convex optimization algorithm (COA) was employed to excite the antennas using optimal values of the phases to maximize the electric field at the tumor and amplitudes to achieve the required temperature at the target position. The performance of the proposed RTHS was validated by comparing it with similar hyperthermia setups in the FEM-based COMSOL software and finite-difference time-domain (FDTD)-based Sim4Life software. RESULTS: The simulation results obtained using the RTHS were consistent, both for the homogeneous and heterogeneous models, with those obtained using commercially available tools, demonstrating the reliability of the proposed hyperthermia simulator. The effectiveness of the simulator was illustrated for target positions in five different regions for both homogeneous and heterogeneous phantom models. In addition, the RTHS was cost-effective and consumed less computational time than the available software. The proposed method achieved 94% and 96% accuracy for element sizes of λ/26 and λ/36, respectively, for the homogeneous model. For the heterogeneous model, the method demonstrated 93% and 95% accuracy for element sizes of λ/26 and λ/36, respectively. The accuracy can be further improved by using a more refined mesh at the cost of a higher computational time. CONCLUSIONS: The proposed hyperthermia simulator demonstrated reliability, cost-effectiveness, and reduced computational time compared to commercial software, making it a potential tool for optimizing hyperthermia treatment.

Differential Evolution Optimization of Microwave Focused Hyperthermia Phased Array Excitation for Targeted Breast Cancer Heating.

Microwave hyperthermia using the phased array applicator is a non-invasive treatment modality for breast cancer. Hyperthermia treatment planning (HTP) is critical to accurately treating breast cancer and avoiding damage to the patient's healthy tissue. A global optimization algorithm, differential evolution (DE) algorithm, has been applied to optimize HTP for breast cancer and its ability to improve the treatment effect was proved by electromagnetic (EM) and thermal simulation results. DE algorithm is compared to time reversal (TR) technology, particle swarm optimization (PSO) algorithm, and genetic algorithm (GA) in HTP for breast cancer in terms of convergence rate and treatment results, such as treatment indicators and temperature parameters. The current approaches in breast cancer microwave hyperthermia still have the problem of hotspots in healthy tissue. DE enhances focused microwave energy absorption into the tumor and reduces the relative energy of healthy tissue during hyperthermia treatment. By comparing the treatment results of each objective function used in DE, the DE algorithm with hotspot to target quotient (HTQ) as the objective function has outstanding performance in HTP for breast cancer, which can increase the focused microwave energy of the tumor and decrease the damage to healthy tissue.

Field and Temperature Shaping for Microwave Hyperthermia: Recent Treatment Planning Tools to Enhance SAR-Based Procedures.

The aim of the article is to provide a summary of the work carried out in the framework of a research project funded by the Italian Ministry of Research. The main goal of the activity was to introduce multiple tools for reliable, affordable, and high-performance microwave hyperthermia for cancer therapy. The proposed methodologies and approaches target microwave diagnostics, accurate in vivo electromagnetic parameters estimation, and improvement in treatment planning using a single device. This article provides an overview of the proposed and tested techniques and shows their complementarity and interconnection. To highlight the approach, we also present a novel combination of specific absorption rate optimization via convex programming with a temperature-based refinement method implemented to mitigate the effect of thermal boundary conditions on the final temperature map. To this purpose, numerical tests were carried out for both simple and anatomically detailed 3D scenarios for the head and neck region. These preliminary results show the potential of the combined technique and improvements in the temperature coverage of the tumor target with respect to the case wherein no refinement is adopted.

Using MRI to measure position and anatomy changes and assess their impact on the accuracy of hyperthermia treatment planning for cervical cancer.

PURPOSE: We studied the differences between planning and treatment position, their impact on the accuracy of hyperthermia treatment planning (HTP) predictions, and the relevance of including true treatment anatomy and position in HTP based on magnetic resonance (MR) images. MATERIALS AND METHODS: All volunteers were scanned with an MR-compatible hyperthermia device, including a filled waterbolus, to replicate the treatment setup. In the planning setup, the volunteers were scanned without the device to reproduce the imaging in the current HTP. First, we used rigid registration to investigate the patient position displacements between the planning and treatment setup. Second, we performed HTP for the planning anatomy at both positions and the treatment mimicking anatomy to study the effects of positioning and anatomy on the quality of the simulated hyperthermia treatment. Treatment quality was evaluated using SAR-based parameters. RESULTS: We found an average displacement of 2 cm between planning and treatment positions. These displacements caused average absolute differences of ∼12% for TC25 and 10.4%-15.9% in THQ. Furthermore, we found that including the accurate treatment position and anatomy in treatment planning led to an improvement of 2% in TC25 and 4.6%-10.6% in THQ. CONCLUSIONS: This study showed that precise patient position and anatomy are relevant since these affect the accuracy of HTP predictions. The major part of improved accuracy is related to implementing the correct position of the patient in the applicator. Hence, our study shows a clear incentive to accurately match the patient position in HTP with the actual treatment.

Rotationally Adjustable Hyperthermia Applicators: A Computational Comparative Study of Circular and Linear Array Applicators.

Microwave breast hyperthermia (MH) aims to increase the temperature at the tumor location with minimal change in the healthy tissue. To this end, the specific absorption rate (SAR) inside the breast is optimized. The choice of the MH applicator design is important for a superior energy focus on the target. Although hyperthermia treatment planning (HTP) changes for every patient, the MH applicator is required to be effective for different breast models and tumor types. The linear applicator (LA) is one of the previously proposed applicator designs with linearly arranged antennas; however, it suffers from low focusing ability in certain breast regions due to its unsymmetrical geometrical features. In this paper, we propose to radially adjust the LA to obtain alternative excitation schemes without actually changing the applicator. Antipodal Vivaldi antennas were utilized, and the antenna excitations were optimized with particle swarm optimization (PSO). The comparison of the rotated and the fixed linear applicator, between 12-antenna circular and linear applicators, and finally, between a 24-antenna circular applicator are provided. Within the 12 rotation angles and two target locations that were analyzed, the 135° axially rotated linear applicator gave a 35% to 84% higher target-to-breast SAR ratio (TBRS) and a 21% to 28% higher target-to-breast temperature ratio (TBRT) than the fixed linear applicator. For the deep-seated target, the 135° rotated linear applicator had an 80% higher TBRS and a 59% higher TBRT than the 12-antenna circular applicator, while the results were comparable to the 24-antenna circular applicator.

Antenna Excitation Optimization with Deep Learning for Microwave Breast Cancer Hyperthermia.

Microwave hyperthermia (MH) requires the effective calibration of antenna excitations for the selective focusing of the microwave energy on the target region, with a nominal effect on the surrounding tissue. To this end, many different antenna calibration methods, such as optimization techniques and look-up tables, have been proposed in the literature. These optimization procedures, however, do not consider the whole nature of the electric field, which is a complex vector field; instead, it is simplified to a real and scalar field component. Furthermore, most of the approaches in the literature are system-specific, limiting the applicability of the proposed methods to specific configurations. In this paper, we propose an antenna excitation optimization scheme applicable to a variety of configurations and present the results of a convolutional neural network (CNN)-based approach for two different configurations. The data set for CNN training is collected by superposing the information obtained from individual antenna elements. The results of the CNN models outperform the look-up table results. The proposed approach is promising, as the phase-only optimization and phase-power-combined optimization show a 27% and 4% lower hotspot-to-target energy ratio, respectively, than the look-up table results for the linear MH applicator. The proposed deep-learning-based optimization technique can be utilized as a protocol to be applied on any MH applicator for the optimization of the antenna excitations, as well as for a comparison of MH applicators.

Validation and practical use of Plan2Heat hyperthermia treatment planning for capacitive heating.

BACKGROUND: Capacitive devices are used for hyperthermia delivery, initially mainly in Asia, but nowadays also increasingly in Europe. Treatment planning can be very useful to determine the most effective patient-specific treatment set-up. This paper provides a validation of GPU-based simulations using Plan2Heat for capacitive hyperthermia devices. METHODS: Validation was first performed by comparing simulations with an analytical solution for a spherical object placed inside a uniform electric field. Resolution was 5, 2.5 or 1 mm. Next, simulations for homogeneous and inhomogeneous phantom setups were performed for Thermotron RF8 and Celsius TCS capacitive heating devices at 2.5 mm resolution. Also different combinations of electrode sizes were evaluated. Normalized SAR profiles were compared to phantom measurements from the literature. Possible clinical use of treatment planning was demonstrated for an anal cancer patient, evaluating different treatment set-ups in prone and supine position. RESULTS: Numerical and analytical solutions showed excellent agreement. At the center of the sphere, the error was 5.1%, 2.9% and 0.2% for a resolution of 5, 2.5 and 1 mm, respectively. Comparison of measurements and simulations for both Thermotron RF8 and Celsius TCS showed very good agreement within 5% for all phantom set-ups. Simulations were capable of accurately predicting the penetration depth; a very relevant parameter for clinical application. The patient case illustrated that planning can provide insight by comparing effectiveness of different treatment strategies. CONCLUSION: Plan2Heat can rapidly and accurately predict heating patterns generated by capacitive devices. Thus, Plan2Heat is suitable for patient-specific treatment planning for capacitive hyperthermia.

Adapt2Heat: treatment planning-assisted locoregional hyperthermia by on-line visualization, optimization and re-optimization of SAR and temperature distributions.

BACKGROUND: Hyperthermia treatment planning is increasingly used in clinical applications and recommended in quality assurance guidelines. Assistance in phase-amplitude steering during treatment requires dedicated software for on-line visualization of SAR/temperature distributions and fast re-optimization in response to hot spots. As such software tools are not yet commercially available, we developed Adapt2Heat for on-line adaptive hyperthermia treatment planning and illustrate possible application by different relevant real patient examples. METHODS: Adapt2Heat was developed as a separate module of the treatment planning software Plan2Heat. Adapt2Heat runs on a Linux operating system and was developed in C++, using the open source Qt, Qwt and VTK libraries. A graphical user interface allows interactive and flexible on-line use of hyperthermia treatment planning. Predicted SAR/temperature distributions and statistics for selected phase-amplitude settings can be visualized instantly and settings can be re-optimized manually or automatically in response to hot spots. RESULTS: Pretreatment planning E-Field, SAR and temperature calculations are performed with Plan2Heat and imported in Adapt2Heat. Examples show that Adapt2Heat can be helpful in assisting with phase-amplitude steering, e.g., by suppressing indicated hot spots. The effects of phase-amplitude adjustments on the tumor and potential hot spot locations are comprehensively visualized, allowing intuitive and flexible assistance by treatment planning during locoregional hyperthermia treatments. CONCLUSION: Adapt2Heat provides an intuitive and flexible treatment planning tool for on-line treatment planning-assisted hyperthermia. Extensive features for visualization and (re-)optimization during treatment allow practical use in many locoregional hyperthermia applications. This type of tools are indispensable for enhancing the quality of hyperthermia treatment delivery.

Multi-Channel RF Supervision Module for Thermal Magnetic Resonance Based Cancer Therapy.

Glioblastoma multiforme (GBM) is the most lethal and common brain tumor. Combining hyperthermia with chemotherapy and/or radiotherapy improves the survival of GBM patients. Thermal magnetic resonance (ThermalMR) is a hyperthermia variant that exploits radio frequency (RF)-induced heating to examine the role of temperature in biological systems and disease. The RF signals' power and phase need to be supervised to manage the formation of the energy focal point, accurate thermal dose control, and safety. Patient position during treatment also needs to be monitored to ensure the efficacy of the treatment and avoid damages to healthy tissue. This work reports on a multi-channel RF signal supervision module that is capable of monitoring and regulating RF signals and detecting patient motion. System characterization was performed for a broad range of frequencies. Monte-Carlo simulations were performed to examine the impact of power and phase errors on hyperthermia performance. The supervision module's utility was demonstrated in characterizing RF power amplifiers and being a key part of a feedback control loop regulating RF signals in heating experiments. Electromagnetic field simulations were conducted to calculate the impact of patient displacement during treatment. The supervision module was experimentally tested for detecting patient motion to a submillimeter level. To conclude, this work presents a cost-effective RF supervision module that is a key component for a hyperthermia hardware system and forms a technological basis for future ThermalMR applications.

Fast Adaptive Temperature-Based Re-Optimization Strategies for On-Line Hot Spot Suppression during Locoregional Hyperthermia.

BACKGROUND: Experience-based adjustments in phase-amplitude settings are applied to suppress treatment limiting hot spots that occur during locoregional hyperthermia for pelvic tumors. Treatment planning could help to further optimize treatments. The aim of this research was to develop temperature-based re-optimization strategies and compare the predicted effectiveness with clinically applied protocol/experience-based steering. METHODS: This study evaluated 22 hot spot suppressions in 16 cervical cancer patients (mean age 67 ± 13 year). As a first step, all potential hot spot locations were represented by a spherical region, with a user-specified diameter. For fast and robust calculations, the hot spot temperature was represented by a user-specified percentage of the voxels with the largest heating potential (HPP). Re-optimization maximized tumor T90, with constraints to suppress the hot spot and avoid any significant increase in other regions. Potential hot spot region diameter and HPP were varied and objective functions with and without penalty terms to prevent and minimize temperature increase at other potential hot spot locations were evaluated. Predicted effectiveness was compared with clinically applied steering results. RESULTS: All strategies showed effective hot spot suppression, without affecting tumor temperatures, similar to clinical steering. To avoid the risk of inducing new hot spots, HPP should not exceed 10%. Adding a penalty term to the objective function to minimize the temperature increase at other potential hot spot locations was most effective. Re-optimization times were typically ~10 s. CONCLUSION: Fast on-line re-optimization to suppress treatment limiting hot spots seems feasible to match effectiveness of ~30 years clinical experience and will be further evaluated in a clinical setting.

Impact of Number of Segmented Tissues on SAR Prediction Accuracy in Deep Pelvic Hyperthermia Treatment Planning.

In hyperthermia, the general opinion is that pre-treatment optimization of treatment settings requires a patient-specific model. For deep pelvic hyperthermia treatment planning (HTP), tissue models comprising four tissue categories are currently discriminated. For head and neck HTP, we found that more tissues are required for increasing accuracy. In this work, we evaluated the impact of the number of segmented tissues on the predicted specific absorption rate (SAR) for the pelvic region. Highly detailed anatomical models of five healthy volunteers were selected from a virtual database. For each model, seven lists with varying levels of segmentation detail were defined and used as an input for a modeling study. SAR changes were quantified using the change in target-to-hotspot-quotient and maximum SAR relative differences, with respect to the most detailed patient model. The main finding of this study was that the inclusion of high water content tissues in the segmentation may result in a clinically relevant impact on the SAR distribution and on the predicted hyperthermia treatment quality when considering our pre-established thresholds. In general, our results underline the current clinical segmentation protocol and help to prioritize any improvements.

Advanced patient-specific hyperthermia treatment planning.

Hyperthermia treatment planning (HTP) is valuable to optimize tumor heating during thermal therapy delivery. Yet, clinical hyperthermia treatment plans lack quantitative accuracy due to uncertainties in tissue properties and modeling, and report tumor absorbed power and temperature distributions which cannot be linked directly to treatment outcome. Over the last decade, considerable progress has been made to address these inaccuracies and therefore improve the reliability of hyperthermia treatment planning. Patient-specific electrical tissue conductivity derived from MR measurements has been introduced to accurately model the power deposition in the patient. Thermodynamic fluid modeling has been developed to account for the convective heat transport in fluids such as urine in the bladder. Moreover, discrete vasculature trees have been included in thermal models to account for the impact of thermally significant large blood vessels. Computationally efficient optimization strategies based on SAR and temperature distributions have been established to calculate the phase-amplitude settings that provide the best tumor thermal dose while avoiding hot spots in normal tissue. Finally, biological modeling has been developed to quantify the hyperthermic radiosensitization effect in terms of equivalent radiation dose of the combined radiotherapy and hyperthermia treatment. In this paper, we review the present status of these developments and illustrate the most relevant advanced elements within a single treatment planning example of a cervical cancer patient. The resulting advanced HTP workflow paves the way for a clinically feasible and more reliable patient-specific hyperthermia treatment planning.

Radiofrequency applicator concepts for thermal magnetic resonance of brain tumors at 297 MHz (7.0 Tesla).

Purpose: Thermal intervention is a potent sensitizer of cells to chemo- and radiotherapy in cancer treatment. Glioblastoma multiforme (GBM) is a potential clinical target, given the cancer's aggressive nature and resistance to current treatment options. The annular phased array (APA) technique employing electromagnetic waves in the radiofrequency (RF) range allows for localized temperature increase in deep seated target volumes (TVs). Reports on clinical applications of the APA technique in the brain are still missing. Ultrahigh field magnetic resonance (MR) employs higher frequencies than conventional MR and has potential to provide focal temperature manipulation, high resolution imaging and noninvasive temperature monitoring using an integrated RF applicator (ThermalMR). This work examines the applicability of RF applicator concepts for ThermalMR of brain tumors at 297 MHz (7.0 Tesla).Methods: Electromagnetic field (EMF) simulations are performed for clinically realistic data based on GBM patients. Two algorithms are used for specific RF energy absorption rate based thermal intervention planning for small and large TVs in the brain, aiming at maximum RF power deposition or RF power uniformity in the TV for 10 RF applicator designs.Results: For both TVs , the power optimization outperformed the uniformity optimization. The best results for the small TV are obtained for the 16 element interleaved RF applicator using an elliptical antenna arrangement with water bolus. The two row elliptical RF applicator yielded the best result for the large TV.Discussion: This work investigates the capacity of ThermalMR to achieve targeted thermal interventions in model systems resembling human brain tissue and brain tumors.

Integrating Loco-Regional Hyperthermia Into the Current Oncology Practice: SWOT and TOWS Analyses.

Moderate hyperthermia at temperatures between 40 and 44°C is a multifaceted therapeutic modality. It is a potent radiosensitizer, interacts favorably with a host of chemotherapeutic agents, and, in combination with radiotherapy, enforces immunomodulation akin to "in situ tumor vaccination." By sensitizing hypoxic tumor cells and inhibiting repair of radiotherapy-induced DNA damage, the properties of hyperthermia delivered together with photons might provide a tumor-selective therapeutic advantage analogous to high linear energy transfer (LET) neutrons, but with less normal tissue toxicity. Furthermore, the high LET attributes of hyperthermia thermoradiobiologically are likely to enhance low LET protons; thus, proton thermoradiotherapy would mimic 12C ion therapy. Hyperthermia with radiotherapy and/or chemotherapy substantially improves therapeutic outcomes without enhancing normal tissue morbidities, yielding level I evidence reported in several randomized clinical trials, systematic reviews, and meta-analyses for various tumor sites. Technological advancements in hyperthermia delivery, advancements in hyperthermia treatment planning, online invasive and non-invasive MR-guided thermometry, and adherence to quality assurance guidelines have ensured safe and effective delivery of hyperthermia to the target region. Novel biological modeling permits integration of hyperthermia and radiotherapy treatment plans. Further, hyperthermia along with immune checkpoint inhibitors and DNA damage repair inhibitors could further augment the therapeutic efficacy resulting in synthetic lethality. Additionally, hyperthermia induced by magnetic nanoparticles coupled to selective payloads, namely, tumor-specific radiotheranostics (for both tumor imaging and radionuclide therapy), chemotherapeutic drugs, immunotherapeutic agents, and gene silencing, could provide a comprehensive tumor-specific theranostic modality akin to "magic (nano)bullets." To get a realistic overview of the strength (S), weakness (W), opportunities (O), and threats (T) of hyperthermia, a SWOT analysis has been undertaken. Additionally, a TOWS analysis categorizes future strategies to facilitate further integration of hyperthermia with the current treatment modalities. These could gainfully accomplish a safe, versatile, and cost-effective enhancement of the existing therapeutic armamentarium to improve outcomes in clinical oncology.

Solving the Time- and Frequency-Multiplexed Problem of Constrained Radiofrequency Induced Hyperthermia.

Targeted radiofrequency (RF) heating induced hyperthermia has a wide range of applications, ranging from adjunct anti-cancer treatment to localized release of drugs. Focal RF heating is usually approached using time-consuming nonconvex optimization procedures or approximations, which significantly hampers its application. To address this limitation, this work presents an algorithm that recasts the problem as a semidefinite program and quickly solves it to global optimality, even for very large (human voxel) models. The target region and a desired RF power deposition pattern as well as constraints can be freely defined on a voxel level, and the optimum application RF frequencies and time-multiplexed RF excitations are automatically determined. 2D and 3D example applications conducted for test objects containing pure water (rtarget = 19 mm, frequency range: 500-2000 MHz) and for human brain models including brain tumors of various size (r1 = 20 mm, r2 = 30 mm, frequency range 100-1000 MHz) and locations (center, off-center, disjoint) demonstrate the applicability and capabilities of the proposed approach. Due to its high performance, the algorithm can solve typical clinical problems in a few seconds, making the presented approach ideally suited for interactive hyperthermia treatment planning, thermal dose and safety management, and the design, rapid evaluation, and comparison of RF applicator configurations.

Locoregional peritoneal hyperthermia to enhance the effectiveness of chemotherapy in patients with peritoneal carcinomatosis: a simulation study comparing different locoregional heating systems.

Introduction: Intravenous chemotherapy plus abdominal locoregional hyperthermia is explored as a noninvasive alternative to hyperthermic intraperitoneal chemotherapy (HIPEC) in treatment of peritoneal carcinomatosis (PC). First clinical results demonstrate feasibility, but survival data show mixed results and for pancreatic and gastric origin results are not better than expected for chemotherapy alone. In this study, computer simulations are performed to compare the effectiveness of peritoneal heating for five different locoregional heating systems.Methods: Simulations of peritoneal heating were performed for a phantom and two pancreatic cancer patients, using the Thermotron RF8, the AMC-4/ALBA-4D system, the BSD Sigma-60 and Sigma-Eye system, and the AMC-8 system. Specific absorption rate (SAR) distributions were optimized and evaluated. Next, to provide an indication of possible enhancement factors, the corresponding temperature distributions and thermal enhancement ratio (TER) of oxaliplatin were estimated.Results: Both phantom and patient simulations showed a relatively poor SAR coverage for the Thermotron RF8, a fairly good coverage for the AMC-4/ALBA-4D, Sigma-60, and Sigma-Eye systems, and the best and most homogeneous coverage for the AMC-8 system. In at least 50% of the peritoneum, 35-45 W/kg was predicted. Thermal simulations confirmed these favorable peritoneal heating properties of the AMC-8 system and TER values of ∼1.4-1.5 were predicted in at least 50% of the peritoneum.Conclusion: Locoregional peritoneal heating with the AMC-8 system yields more favorable heating patterns compared to other clinically used locoregional heating devices. Therefore, results of this study may promote the use of the AMC-8 system for locoregional hyperthermia in future multidisciplinary studies for treatment of PC.

Feasibility and relevance of discrete vasculature modeling in routine hyperthermia treatment planning.

Purpose: To investigate the effect of patient specific vessel cooling on head and neck hyperthermia treatment planning (HTP). Methods and materials: Twelve patients undergoing radiotherapy were scanned using computed tomography (CT), magnetic resonance imaging (MRI) and contrast enhanced MR angiography (CEMRA). 3D patient models were constructed using the CT and MRI data. The arterial vessel tree was constructed from the MRA images using the 'graph-cut' method, combining information from Frangi vesselness filtering and region growing, and the results were validated against manually placed markers in/outside the vessels. Patient specific HTP was performed and the change in thermal distribution prediction caused by arterial cooling was evaluated by adding discrete vasculature (DIVA) modeling to the Pennes bioheat equation (PBHE). Results: Inclusion of arterial cooling showed a relevant impact, i.e., DIVA modeling predicts a decreased treatment quality by on average 0.19 °C (T90), 0.32 °C (T50) and 0.35 °C (T20) that is robust against variations in the inflow blood rate (|ΔT| < 0.01 °C). In three cases, where the major vessels transverse target volume, notable drops (|ΔT| > 0.5 °C) were observed. Conclusion: Addition of patient-specific DIVA into the thermal modeling can significantly change predicted treatment quality. In cases where clinically detectable vessels pass the heated region, we advise to perform DIVA modeling.

Predictive value of SAR based quality indicators for head and neck hyperthermia treatment quality.

PURPOSE: Hyperthermia treatment quality determines treatment effectiveness as shown by the clinically derived thermal-dose effect relations. SAR based optimization factors are used as possible surrogate for temperature, since they are not affected by thermal tissue properties uncertainty and variations. Previously, target coverage (TC) at the 25% and 50% iso-SAR level was shown predictive for treatment outcome in superficial hyperthermia and the target-to-hot-spot-quotient (THQ) was shown to highly correlate with predictive temperature in deep pelvic hyperthermia. Here, we investigate the correlation with temperature for THQ and TC using an 'intermediate' scenario: semi-deep hyperthermia in the head & neck region using the HYPERcollar3D. METHODS: Fifteen patient-specific models and two different planning approaches were used, including random perturbations to circumvent optimization bias. The predicted SAR indicators were compared to predicted target temperature distribution indicators T50 and T90, i.e., the median and 90th percentile temperature respectively. RESULTS: The intra-patient analysis identified THQ, TC25 and TC50 as good temperature surrogates: with a mean correlation coefficient R2T50 = 0.72 and R2T90=0.66. The inter-patient analysis identified the highest correlation with TC25 (R2T50 = 0.76, R2T90=0.54) and TC50 (R2T50 = 0.74, R2T90 = 0.56). CONCLUSION: Our investigation confirmed the validity of our current strategy for deep hyperthermia in the head & neck based on a combination of THQ and TC25. TC50 was identified as the best surrogate since it enables optimization and patient inclusion decision making using one single parameter.

Clinical validation of a novel thermophysical bladder model designed to improve the accuracy of hyperthermia treatment planning in the pelvic region.

PURPOSE: Hyperthermia treatment planning for deep locoregional hyperthermia treatment may assist in phase and amplitude steering to optimize the temperature distribution. This study aims to incorporate a physically correct description of bladder properties in treatment planning, notably the presence of convection and absence of perfusion within the bladder lumen, and to assess accuracy and clinical implications for non muscle invasive bladder cancer patients treated with locoregional hyperthermia. METHODS: We implemented a convective thermophysical fluid model based on the Boussinesq approximation to the Navier-Stokes equations using the (finite element) OpenFOAM toolkit. A clinician delineated the bladder on CT scans obtained from 14 bladder cancer patients. We performed (1) conventional treatment planning with a perfused muscle-like solid bladder, (2) with bladder content properties without and (3) with flow dynamics. Finally, we compared temperature distributions predicted by the three models with temperature measurements obtained during treatment. RESULTS: Much higher and more uniform bladder temperatures are predicted with physically accurate fluid modeling compared to previously employed muscle-like models. The differences reflect the homogenizing effect of convection, and the absence of perfusion. Median steady state temperatures simulated with the novel convective model (3) deviated on average -0.6 °C (-12%) from values measured during treatment, compared to -3.7 °C (-71%) and +1.5 °C (+29%) deviation for the muscle-like (1) and static (2) models, respectively. The Grashof number was 3.2 ± 1.5 × 105 (mean ± SD). CONCLUSIONS: Incorporating fluid modeling in hyperthermia treatment planning yields significantly improved predictions of the temperature distribution in the bladder lumen during hyperthermia treatment.