Temperature monitoring plays a central role in improving clinical effectiveness of adjuvant hyperthermia. The potential of magnetic resonance thermometry for treatment monitoring purposes led to several MR-guided hyperthermia approaches. However, the proposed solutions were sub-optimal due to technological and intrinsic limitations. These hamper achieving target conformal heating possibilities (applicator limitations) and accurate thermometry (inadequate signal-to-noise-ratio (SNR)). In this work, we studied proof of principle of a dual-function hyperthermia approach based on a coil array (64 MHz, 1.5 T) that is integrated in-between a phased array for heating (434 MHz) for maximum signal receive in order to improve thermometry accuracy. Hereto, we designed and fabricated a superficial hyperthermia mimicking planar array setup to study the most challenging interactions of generic phased-array setups in order to validate the integrated approach. Experiments demonstrated that the setup complies with the superficial hyperthermia guidelines for heating and is able to improve SNR at 2-4 cm depth by 17%, as compared to imaging using the body coil. Hence, the results showed the feasibility of our dual-function MR-guided hyperthermia approach as basis for the development of application specific setups.@en

Objective: The addition of hyperthermia in the treatment of intact breast cancer with the aim to improve local response is currently in a research phase. First, optimal hyperthermia devices need to be developed, for which a diverse, anatomically and pathologically accurate set of patient models is necessary. Methods: To investigate the effects of inter-subject variations on hyperthermia treatment plans, we generated a repository of 22 anatomically and pathologically diverse patient models based on MR images of breast cancer patients. Hyperthermia treatment plans were generated for the 22 models using a generic theoretical phased array hyperthermia applicator. Results: Good temperature coverage was achieved in the vast majority of the models, with median values for T 10 = 43.5°C (41.9–43.8°C), T 50 = 42.5°C (41.3–43.3°C), and T 90 = 41.3°C (39.8–42.6°C) under the condition that the maximum temperature increase in the patient is limited to 44°C. Conclusions: For future development of hyperthermia devices and treatment methods, a repository with a sufficiently large number of representative patient models, such as the one provided in this study, should be used to ensure applicability to a wide variety of patients. This repository is therefore made publicly available.@en

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.@en