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Purpose: Dosimetry during deep local hyperthermia treatments in the head and neck currently relies on a limited number of invasively placed temperature sensors. The purpose of this study was to assess the feasibility of 3D dosimetry based on patient-specific temperature simulations and sensory feedback., Materials and Methods: The study includes 10 patients with invasive thermometry applied in at least two treatments. Based on their invasive thermometry, we optimised patient-group thermal conductivity and perfusion values for muscle, fat and tumour using a 'leave-one-out' approach. Next, we compared the accuracy of the predicted temperature (ΔT) and the hyperthermia treatment quality (ΔT50) of the optimisations based on the patient-group properties to those based on patient-specific properties, which were optimised using previous treatment measurements. As a robustness check, and to enable comparisons with previous studies, we optimised the parameters not only for an applicator efficiency factor of 40%, but also for 100% efficiency., Results: The accuracy of the predicted temperature (ΔT) improved significantly using patient-specific tissue properties, i.e. 1.0 °C (inter-quartile range (IQR) 0.8 °C) compared to 1.3 °C (IQR 0.7 °C) for patient-group averaged tissue properties for 100% applicator efficiency. A similar accuracy was found for optimisations using an applicator efficiency factor of 40%, indicating the robustness of the optimisation method. Moreover, in eight patients with repeated measurements in the target region, ΔT50 significantly improved, i.e. ΔT50 reduced from 0.9 °C (IQR 0.8 °C) to 0.4 °C (IQR 0.5 °C) using an applicator efficiency factor of 40%., Conclusion: This study shows that patient-specific temperature simulations combined with tissue property reconstruction from sensory data provides accurate minimally invasive 3D dosimetry during hyperthermia treatments: T50 in sessions without invasive measurements can be predicted with a median accuracy of 0.4 °C.

Purpose: Clinical phase III trials have shown the benefit of adding hyperthermia to radiotherapy and chemotherapy for head and neck cancer (H&N). The HYPERcollar, a functional prototype capable of applying hyperthermia to the entire H&N region was developed. Specific absorption rate-based hyperthermia treatment planning (HTP) is used to optimise HYPERcollar treatments. Hence, besides treatment quality, reproduction and reproducibility of the HTP are also pivotal. In the current work we analysed the impact of key parameters on treatment quality and completely redesigned the mechanical layout of the HYPERcollar for improved treatment quality and patient comfort., Material and Methods: The requirements regarding patient position and the water bolus shape were quantified by simulation studies. The complete mechanical redesign was based on these requirements and non-modellable improvements were experimentally validated., Results: From simulation studies we imposed the required positioning accuracy to be within ±5 mm. Simulation studies also showed that the water bolus shape has an important impact on treatment quality. Solutions to meet the requirements were 1) a redesign of the applicator, 2) a redesign of the water bolus, and 3) a renewed positioning strategy. Experiments were used to demonstrate whether the solutions meet the requirements., Conclusions: The HYPERcollar redesign improves water bolus shape, stability and skin contact. The renewed positioning strategy allows for positioning of the patient within the required precision of ±5 mm. By clinically introducing the new design, we aim at improving not only treatment quality and reproducibility, but also patient comfort and operator handling, which are all important for a better hyperthermia treatment quality.

Background and Purpose: Hyperthermia treatment planning (HTP) is used in the head and neck region (H&N) for pretreatment optimization, decision making, and real-time HTP-guided adaptive application of hyperthermia. In current clinical practice, HTP is based on power-absorption predictions, but thermal dose-effect relationships advocate its extension to temperature predictions. Exploitation of temperature simulations requires region- and temperature-specific thermal tissue properties due to the strong thermoregulatory response of H&N tissues. The purpose of our work was to develop a technique for patient group-specific optimization of thermal tissue properties based on invasively measured temperatures, and to evaluate the accuracy achievable., Patients and Methods: Data from 17 treated patients were used to optimize the perfusion and thermal conductivity values for the Pennes bioheat equation-based thermal model. A leave-one-out approach was applied to accurately assess the difference between measured and simulated temperature (∆T). The improvement in ∆T for optimized thermal property values was assessed by comparison with the ∆T for values from the literature, i.e., baseline and under thermal stress., Results: The optimized perfusion and conductivity values of tumor, muscle, and fat led to an improvement in simulation accuracy (∆T: 2.1 ± 1.2 °C) compared with the accuracy for baseline (∆T: 12.7 ± 11.1 °C) or thermal stress (∆T: 4.4 ± 3.5 °C) property values., Conclusion: The presented technique leads to patient group-specific temperature property values that effectively improve simulation accuracy for the challenging H&N region, thereby making simulations an elegant addition to invasive measurements. The rigorous leave-one-out assessment indicates that improvements in accuracy are required to rely only on temperature-based HTP in the clinic.

Background and Purpose: In Rotterdam, patient-specific hyperthermia (HT) treatment planning (HTP) is applied for all deep head and neck (H&N) HT treatments. In this paper we introduce VEDO (the Visualisation Tool for Electromagnetic Dosimetry and Optimisation), the software tool required, and demonstrate its value for HTP-guided online complaint-adaptive (CA) steering based on specific absorption rate (SAR) optimisation during a H&N HT treatment., Materials and Methods: VEDO integrates CA steering, visualisation of the SAR patterns and mean tumour SAR (SAR(target)) optimisation in a single screen. The pre-calculated electromagnetic fields are loaded into VEDO. During treatment, VEDO shows the SAR pattern, overlaid on the patients' CT-scan, corresponding to the actually applied power settings and it can (re-)optimise the SAR pattern to minimise SAR at regions where the patient senses discomfort while maintaining a high SAR(target)., Results: The potential of the quantitative SAR steering approach using VEDO is demonstrated by analysis of the first treatment in which VEDO was used for two patients using the HYPERcollar. These cases show that VEDO allows response to power-related complaints of the patient and to quantify the change in absolute SAR: increasing either SAR(target) from 96 to 178 W/kg (case 1); or show that the first SAR distribution was already optimum (case 2)., Conclusion: This analysis shows that VEDO facilitates a quantitative treatment strategy allowing standardised application of HT by technicians of different HT centres, which will potentially lead to improved treatment quality and the possibility of tracking the effectiveness of different treatment strategies.