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 (&amp;#x201C;planning setup&amp;#x201D;) and with the MR-compatible hyperthermia device (&amp;#x201C;treatment setup&amp;#x201D;). 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.</p

Assessment of the thermal tissue models for the head and neck hyperthermia treatment planning

Purpose: To compare different thermal tissue models for head and neck hyperthermia treatment planning, and to assess the results using predicted and measured applied power data from clinical treatments. Methods: Three commonly used temperature models from literature were analysed: “constant baseline”, “constant thermal stress” and “temperature dependent”. Power and phase data of 93 treatments of 20 head and neck patients treated with the HYPERcollar3D applicator were used. The impact on predicted median temperature T50 inside the target region was analysed with maximum allowed temperature of 44 °C in healthy tissue. The robustness of predicted T50 for the three models against the influence of blood perfusion, thermal conductivity and the assumed hotspot temperature level was analysed. Results: We found an average predicted T50 of 41.0 ± 1.3 °C (constant baseline model), 39.9 ± 1.1 °C (constant thermal stress model) and 41.7 ± 1.1 °C (temperature dependent model). The constant thermal stress model resulted in the best agreement between the predicted power (P = 132.7 ± 45.9 W) and the average power measured during the hyperthermia treatments (P = 129.1 ± 83.0 W). Conclusion: The temperature dependent model predicts an unrealistically high T50. The power values for the constant thermal stress model, after scaling simulated maximum temperatures to 44 °C, matched best to the average measured powers. We consider this model to be the most appropriate for temperature predictions using the HYPERcollar3D applicator, however further studies are necessary for developing of robust temperature model for tissues during heat stress.</p

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

Quantitative, Multi-institutional Evaluation of MR Thermometry Accuracy for Deep-Pelvic MR-Hyperthermia Systems Operating in Multi-vendor MR-systems Using a New Anthropomorphic Phantom

Clinical outcome of hyperthermia depends on the achieved target temperature, therefore target conformal heating is essential. Currently, invasive temperature probe measurements are the gold standard for temperature monitoring, however, they only provide limited sparse data. In contrast, magnetic resonance thermometry (MRT) provides unique capabilities to non-invasively measure the 3D-temperature. This study investigates MRT accuracy for MR-hyperthermia hybrid systems located at five European institutions while heating a centric or eccentric target in anthropomorphic phantoms with pelvic and spine structures. Scatter plots, root mean square error (RMSE) and Bland–Altman analysis were used to quantify accuracy of MRT compared to high resistance thermistor probe measurements. For all institutions, a linear relation between MRT and thermistor probes measurements was found with R2 (mean ± standard deviation) of 0.97 ± 0.03 and 0.97 ± 0.02, respectively for centric and eccentric heating targets. The RMSE was found to be 0.52 ± 0.31 °C and 0.30 ± 0.20 °C, respectively. The Bland-Altman evaluation showed a mean difference of 0.46 ± 0.20 °C and 0.13 ± 0.08 °C, respectively. This first multi-institutional evaluation of MR-hyperthermia hybrid systems indicates comparable device performance and good agreement between MRT and thermistor probes measurements. This forms the basis to standardize treatments in multi-institution studies of MR-guided hyperthermia and to elucidate thermal dose-effect relations

Introduction to computational modeling in hyperthermia

Over the past two decades, computational modeling has gained a prominent role in hyperthermia research and its role for guiding treatments is expanding. Computational modeling serves e.g., to design new applicators, in silico testing of novel treatment approaches and providing insight in treatment safety. Hyperthermia treatment modeling and optimization (HTM&O), also known as hyperthermia treatment planning (HTP), is the process in which the multidisciplinary hyperthermia team defines the optimal treatment plan for a specific cancer patient using the available hyperthermia treatment resources. HTM&O includes computational modeling approaches for pretreatment HTP and online treatment guidance

The Required Patient Modeling Realism in Radiofrequency Heating Simulation Studies

Clinical effectiveness of hyperthermia would benefit from a more controlled and target conformal heating of the tumor. Over the years, dosimetry using electromagnetic simulators has become a potent tool to study improvements in the application of hyperthermia. Literature suggests that simulation accuracy is dependent on the realism of the patient models. In this work, we compare the results for a detailed head and neck patient model to those for models with an approximated shape, a reduced tissue number and/or a spherical target volume. Our comparison shows a relative difference above 25% in the administered power absorption pattern. This large difference calls upon 1) follow-up research to establish the true impact using a larger set of patient models and 2) the development of a reference set of patient models to facilitate benchmarking of novel devices, methods and treatment approaches

Design of a High Selectivity Filter for MRI Guided RF Hyperthermia Therapy

Hyperthermia devices have been integrated with MR scanners to exploit MR thermometry. Integrating two RF systems require the filtering of high-power RF heating signal from MR system for simultaneous heating and imaging. Currently, a filter that suppresses 100MHz and its harmonics is in use. Development of a MR-compatible hyperthermia applicator for head and neck requires a filter that can suppress also the 433.92MHz signal. A unique new filter which has high power handling, extremely high suppression, and selectivity has been designed that attenuates 100MHz and 433.92MHz signals with low insertion loss (<0.25dB) at 63.89MHz. 0.14dB insertion loss at 63.89MHz, 112dB, 88dB and 93dB signal attenuation were achieved at 100MHz, 200MHz and 433.92MHz, respectively, with the new filter design using model of LM-500 cable. A proof of concept filter was constructed to validate the design. Our investigation shows that filter requirements can be satisfied, but high-power low-loss coaxial cables are necessary

An Approximate Electromagnetic Model for Optimizing Wireless Charging of Biomedical Implants

Computational modeling is increasingly used to design charging systems for implanted medical devices. The design of these systems must often satisfy conflicting criteria, and fast electromagnetic solvers are pivotal for enabling multi-criteria optimization. In this paper, we look at wireless power transfer for implantable devices and the specific absorption rate and induced currents related to the implanted side of the design. We present an analytical model based on the quasi-static approximation as a fast, yet sufficiently accurate, alternative for full wave electromagnetic modeling. The analytic model was benchmarked against full-wave simulations to validate accuracy and improvement in computation time. Our analysis shows that the analytic model allows for feasible complete optimization of coil shapes, as the analytic model takes only 11 seconds to compute a single iteration, while the full-wave model takes 5 hours to compute the same case. The maximum difference with full-wave simulations was less than 25\% and the mean difference less than 2.3%. Adding a novel figure of merit into the multi-criterion optimization resulted in a 16% higher charging speed. The specific absorption rate and coupling factor were both experimentally verified to show that the measured results are within a 5~mm coil offset margin, which validates the simulation results

The potential of adjusting water bolus liquid properties for economic and precise MR thermometry guided radiofrequency hyperthermia

The potential of MR thermometry (MRT) fostered the development of MRI compatible radiofrequency (RF) hyperthermia devices. Such device integration creates major technological challenges and a crucial point for image quality is the water bolus (WB). The WB is located between the patient body and external sources to both couple electromagnetic energy and to cool the patient skin. However, the WB causes MRT errors and unnecessarily large field of view. In this work, we studied making the WB MRI transparent by an optimal concentration of compounds capable of modifying T2 * relaxation without an impact on the efficiency of RF heating. Three different T2 * reducing compounds were investigated, namely CuSO4, MnCl2, and Fe3 O4. First, electromagnetic properties and T2 * relaxation rates at 1.5 T were measured. Next, through multi-physics simulations, the predicted effect on the RF-power deposition pattern was evaluated and MRT precision was experimentally assessed. Our results identified 5 mM Fe3 O4 solution as optimal since it does not alter the RF-power level needed and improved MRT precision from 0.39◦ C to 0.09◦ C. MnCl2 showed a similar MRT improvement, but caused unacceptable RF-power losses. We conclude that adding Fe3 O4 has significant potential to improve RF hyperthermia treatment monitoring under MR guidance

Impact of segmentation detail in hyperthermia treatment planning: comparison between detailed and clinical tissue segmentation

Treatment planning for deep pelvic hyperthermia is currently based on tissue models comprising four tissue categories. For head and neck hyperthermia, we earlier found that more tissues are required for an accurate representation. Hence, we studied the accuracy of the clinical tissue segmentation (4 tissues) using a full detailed tissue list segmentation (80 tissues) as benchmark. The SAR and temperature distributions were evaluated and relevant differences were found. Also, the large and unknown variation in blood perfusion results in a large uncertainty in the predicted temperature distributions. In summary, this study showed that the number of tissues segmented is relevant for both SAR and the temperature prediction accuracy