Treatment planning facilitates clinical decision making for hyperthermia treatments

In vivo electrical properties of the healthy liver and the hepatic tumor in a mouse model between 1 Hz and 1 MHz during a thermal treatment

Objective: Understansding the changing patterns of in vivo electrical properties for the target tissue is crucial for the accurate temperature monitoring and the treatment efficacy in thermal therapy. Our research aims to investigate the changing patterns and the reversibility of in vivo electrical properties for both healthy livers and liver tumors in a mouse model over a frequency range of 1 Hz to 1 MHz at temperatures between 30 °C to 90 °C.

Methods and materials: The mice were anesthetized and the target organ was exposed. An 808-nm near-infrared laser was employed as the heating source to heat the organ in vivo. The four-needle electrode, connected to an impedance analyzer, was utilized to obtain the impedance at varying temperatures, which were monitored by a thermocouple.

Results: The findings indicated a gradual decline in impedance with an increase in temperature. Furthermore, the impedance was normalized to that at 30 °C, and the real part of the normalized impedance was defined as the k-values, which range from 0 to 1. The results demonstrated a linear correlation between k-values and temperatures (R2 > 0.9 for livers and R2 > 0.8 for tumors). Significant differences were observed between livers and tumors at 1, 10 and 50 kHz (p < 0.05). Additionally, it was demonstrated that the electrical properties could be reversed when the temperature was below or equal to 45 °C.

Conclusion: We believe that these results will contribute to the advancement of radiofrequency ablation systems and the development of techniques for temperature monitoring during liver thermal treatment.

Validation of the implementation of phased-array heating systems in Plan2Heat

BACKGROUND

Hyperthermia treatment planning can be supportive to ensure treatment quality, provided reliable prediction of the heating characteristics (i.e., focus size and effects of phase-amplitude and frequency steering) of the device concerned is possible. This study validates the predictions made by the treatment planning system Plan2Heat for various clinically used phased-array systems.

METHODS

The evaluated heating systems were AMC-2, AMC-4/ALBA-4D (Med-Logix srl, Rome, Italy), BSD Sigma-30, and Sigma-60 (Pyrexar Medical, Salt Lake City, UT, USA). Plan2Heat was used for specific absorption rate (SAR) simulations in phantoms representing measurement set-ups reported in the literature. SAR profiles from published measurement data based on E‑field or temperature rise were used to compare the device-specific heating characteristics predicted by Plan2Heat.

RESULTS

Plan2Heat is able to predict the correct location and size of the SAR focus, as determined by phase-amplitude settings and operating frequency. Measured effects of phase-amplitude steering on focus shifts (i.e., local SAR minima or maxima) were also correctly reflected in treatment planning predictions. Deviations between measurements and simulations were typically < 10-20%, which is within the range of experimental uncertainty for such phased-array measurements.

CONCLUSION

Plan2Heat is capable of adequately predicting the heating characteristics of the AMC‑2, AMC-4/ALBA-4D, BSD Sigma-30, and Sigma-60 phased-array systems routinely used in clinical hyperthermia.

Robust, planning-based targeted locoregional tumour heating in small animals

Objective.To improve hyperthermia in clinical practice, pre-clinical hyperthermia research is essential to investigate hyperthermia effects and assess novel treatment strategies. Translating pre-clinical hyperthermia findings into clinically viable protocols requires laboratory animal treatment techniques similar to clinical hyperthermia techniques. The ALBA micro8 electromagnetic heating system (Med-logix SRL, Rome, Italy) has recently been developed to provide the targeted locoregional tumour heating currently lacking for pre-clinical research. This study evaluates the heat focusing properties of this device and its ability to induce robust locoregional tumour heating under realistic physiological conditions using simulations.Approach.Simulations were performed using the Plan2Heat treatment planning package (Amsterdam UMC, the Netherlands). First, the specific absorption rate (SAR) focus was characterised using a homogeneous phantom. Hereafter, a digital mouse model was used for the characterisation of heating robustness in a mouse. Device settings were optimised for treatment of a pancreas tumour and tested for varying circumstances. The impact of uncertainties in tissue property and perfusion values was evaluated using polynomial chaos expansion. Treatment quality and robustness were evaluated based on SAR and temperature distributions.Main results.The SAR distributions within the phantom are well-focused and can be adjusted to target any specific location. The focus size (full-width half-maximum) is a spheroid with diameters 9 mm (radially) and 20 mm (axially). The mouse model simulations show strong robustness against respiratory motion and intestine and stomach filling (∆T90≤0.14°C).Mouse positioning errors in the cranial-caudal direction lead to∆T90≤0.23°C. Uncertainties in tissue property and perfusion values were found to impact the treatment plan up to 0.56 °C (SD), with a variation onT90of 0.32 °C (1 SD).Significance.Our work shows that the pre-clinical phased-array system can provide adequate and robust locoregional heating of deep-seated target regions in mice. Using our software, robust treatment plans can be generated for pre-clinical hyperthermia research.

Quantification of tissue property and perfusion uncertainties in hyperthermia treatment planning: Multianalysis using polynomial chaos expansion

INTRODUCTION

Hyperthermia treatment planning (HTP) tools can guide treatment delivery, particularly with locoregional radiative phased array systems. Uncertainties in tissue and perfusion property values presently lead to quantitative inaccuracy of HTP, leading to sub-optimal treatment. Assessment of these uncertainties would allow for better judgement of the reliability of treatment plans and improve their value for treatment guidance. However, systematically investigating the impact of all uncertainties on treatment plans is a complex, high-dimensional problem and too computationally expensive for traditional Monte Carlo approaches. This study aims to systematically quantify the treatment-plan impact of tissue property uncertainties by investigating their individual contribution to, and combined impact on predicted temperature distributions.

METHODS

A novel Polynomial Chaos Expansion (PCE)-based HTP uncertainty quantification was developed and applied for locoregional hyperthermia of modelled tumours in the pancreatic head, prostate, rectum, and cervix. Patient models were based on the Duke and Ella digital human models. Using Plan2Heat, treatment plans were created to optimise tumour temperature (represented by T90) for treatment using the Alba4D system. For all 25-34 modelled tissues, the impact of tissue property uncertainties was analysed individually i.e., electrical and thermal conductivity, permittivity, density, specific heat capacity and perfusion. Next, combined analyses were performed on the top 30 uncertainties with the largest impact.

RESULTS

Uncertainties in thermal conductivity and heat capacity were found to have negligible impact on the predicted temperature ( < 1 × 10-10 °C), density and permittivity uncertainties had a small impact (< 0.3 °C). Uncertainties in electrical conductivity and perfusion can lead to large variations in predicted temperature. However, variations in muscle properties result in the largest impact at locations that could limit treatment quality, with a standard deviation up to almost 6 °C (pancreas) and 3.5 °C (prostate) for perfusion and electrical conductivity, respectively. The combined influence of all significant uncertainties leads to large variations with a standard deviation up to 9.0, 3.6, 3.7 and 4.1 °C for the pancreatic, prostate, rectal and cervical cases, respectively.

CONCLUSION

Uncertainties in tissue and perfusion property values can have a large impact on predicted temperatures from hyperthermia treatment planning. PCE-based analysis helps to identify all major uncertainties, their impact and judge the reliability of treatment plans.

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.

Advanced Radio Frequency Applicators for Thermal Magnetic Resonance Theranostics of Brain Tumors

Thermal Magnetic Resonance (ThermalMR) is a theranostic concept that combines diagnostic magnetic resonance imaging (MRI) with targeted thermal therapy in the hyperthermia (HT) range using a radiofrequency (RF) applicator in an integrated system. ThermalMR adds a therapeutic dimension to a diagnostic MRI device. Focused, targeted RF heating of deep-seated brain tumors, accurate non-invasive temperature monitoring and high-resolution MRI are specific requirements of ThermalMR that can be addressed with novel concepts in RF applicator design. This work examines hybrid RF applicator arrays combining loop and self-grounded bow-tie (SGBT) dipole antennas for ThermalMR of brain tumors, at magnetic field strengths of 7.0 T, 9.4 T and 10.5 T. These high-density RF arrays improve the feasible transmission channel count, and provide additional degrees of freedom for RF shimming not afforded by using dipole antennas only, for superior thermal therapy and MRI diagnostics. These improvements are especially relevant for ThermalMR theranostics of deep-seated brain tumors because of the small surface area of the head. ThermalMR RF applicators with the hybrid loop+SGBT dipole design outperformed applicators using dipole-only and loop-only designs, with superior MRI performance and targeted RF heating. Array variants with a horse-shoe configuration covering an arc (270°) around the head avoiding the eyes performed better than designs with 360° coverage, with a 1.3 °C higher temperature rise inside the tumor while sparing healthy tissue. Our EMF and temperature simulations performed on a virtual patient with a clinically realistic intracranial tumor provide a technical foundation for implementation of advanced RF applicators tailored for ThermalMR theranostics of brain tumors.

The Relevance of High Temperatures and Short Time Intervals Between Radiation Therapy and Hyperthermia: Insights in Terms of Predicted Equivalent Enhanced Radiation Dose

PURPOSE

The radiosensitization effect of hyperthermia can be considered and quantified as an enhanced equivalent radiation dose (EQD_RT), that is, the dose needed to achieve the same effect without hyperthermia. EQD_RT can be predicted using an extended linear quadratic model, with temperature-dependent parameters. Clinical data show that both the achieved temperature and time interval between radiation therapy and hyperthermia correlate with clinical outcome, but their effect on expected EQD_RT is unknown and was therefore evaluated in this study.

METHODS AND MATERIALS

Biological modeling was performed using our in-house developed software (X-Term), considering a 23- × 2-Gy external beam radiation scheme, as applied for patients with locally advanced cervical cancer. First, the EQD_RT was calculated for homogeneous temperature levels, evaluating time intervals between 0 and 4 hours. Next, realistic heterogeneous hyperthermia treatment plans were combined with radiation therapy plans and the EQD_RT was calculated for 10 patients. Furthermore, the effect of achieving 0.5°C to 1°C lower or higher temperatures was evaluated.

RESULTS

EQD_RT increases substantially with both increasing temperature and decreasing time interval. The effect of the time interval is most pronounced at higher temperatures (>41°C). At a typical hyperthermic temperature level of 41.5°C, an enhancement of ∼10 Gy can be realized with a 0-hour time interval, which is decreased to only ∼4 Gy enhancement with a 4-hour time interval. Most enhancement is already lost after 1 hour. Evaluation in patients predicted an average additional EQD_RT (D95%) of 2.2 and 6.3 Gy for 4- and 0-hour time intervals, respectively. The effect of 0.5°C to 1°C lower or higher temperatures is most pronounced at high temperature levels and short time intervals. The additional EQD_RT (D95%) ranged between 1.5 and 3.3 Gy and between 4.5 and 8.5 Gy for 4- and 0-hour time intervals, respectively.

CONCLUSIONS

Biological modeling provides relevant insight into the relationship between treatment parameters and expected EQD_RT. Both high temperatures and short time intervals are essential to maximize EQD_RT.

Application of photogrammetry reconstruction for hyperthermia quality control measurements

PURPOSE

Hyperthermia is a cancer treatment in which the target region is heated to temperatures of 40-44 °C usually applying external electromagnetic field sources. The behavior of the hyperthermia applicators (antennas) in clinical practice should be periodically checked with phantom experiments to verify the applicator's performance over time. The purpose of this study was to investigate the application of photogrammetry reconstructions of 3D applicator position in these quality control procedure measurements.

METHODS

Photogrammetry reconstruction was applied at superficial hyperthermia scenario using the Lucite cone applicator (LCA) and phased-array heating in the head and neck region using the HYPERcollar3D. Wire-frame models of the entire measurement setups were created from multiple-view images and used for recreation of the setup inside 3D electromagnetic field simulation software. We evaluated applicator relation (R_a) between measured and simulated absolute specific absorption rate (SAR) for manually created and photogrammetry reconstructed simulation setups.

RESULTS

We found a displacement of 7.9 mm for the LCA and 8.2 mm for the HYPERcollar3D setups when comparing manually created and photogrammetry reconstructed applicator models placements. R_a improved from 1.24 to 1.18 for the LCA and from 1.17 to 1.07 for the HYPERcollar3D when using photogrammetry reconstructed simulation setups.

CONCLUSION

Photogrammetry reconstruction technique holds promise to improve measurement setup reconstruction and agreement between measured and simulated absolute SAR.

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.

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

Simple Summary

When treatment limiting hot spots occur during locoregional hyperthermia (i.e., heating tumors to 40–44 °C for ~1 h), system settings are adjusted based on experience. In this study, we developed and evaluated treatment planning with temperature-based re-optimization and compared the predicted effectiveness to clinically applied protocol/experience-based steering. Re-optimization times were typically ~10 s; sufficiently fast for on-line use. Effective hot spot suppression was predicted, while maintaining adequate tumor heating. Inducing new hot spots was avoided. Temperature-based re-optimization to suppress treatment limiting hot spots seemed feasible to match the effectiveness of long-term clinical experience and will be further evaluated in a clinical setting. When numerical algorithms are proven to match long-term experience, the overall treatment quality within hyperthermia centers can significantly improve. Implementing these strategies would then imply that treatments become less dependent on the experience of the center/operator.

Abstract

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.