Precision heating in cancer therapy with MRI-guided hyperthermia control
Sven Nouwens defended his PhD thesis at the Department of Mechanical Engineering on October 30th.
With his PhD research Sven Nouwens proposes new solutions to increase the precision of hyperthermia therapy for the treatment of cancer. By using MRI-guided feedback controls and advanced algorithms he enhances accuracy and patient safety.
Cancer is a leading cause of early mortality worldwide, with surgical resection, chemotherapy, and radiotherapy being the primary treatments to combat it. Yet, these treatments often carry severe side effects and sometimes fail to work effectively. Mild hyperthermia—carefully heating tumors to between 39 and 45°C for an hour or more—has emerged as a promising way to enhance traditional therapies, boosting chemotherapy uptake and compromising cancer cells’ ability to repair after radiotherapy. However, a major challenge lies in accurately delivering heat to tumor tissue without impacting nearby healthy cells. Hospitals currently use radio-frequency antennas and computer-based models to simulate the treatment, but these approaches often fall short, unintentionally overheating surrounding tissues.
Feedback control system
A key focus of this research is achieving precise heating of the tumor while protecting healthy tissues, which demands real-time adjustments during treatment. Typically, radio-frequency antennas are used to administer heat non-invasively, while virtual treatment simulations help guide device settings. However, limitations in current mathematical models can result in undesired heating of healthy tissues, as simulated heat distributions often differ from real-life conditions. By implementing a feedback control system, the researcher proposes using temperature measurements from within the patient’s body to continuously adjust the heating device settings. For instance, by detecting regions that get too hot, the device can be controlled to avoid them. Such real-time feedback allows for dynamic responses to temperature changes, minimizing the risk of overheating surrounding tissues and maximizing treatment effectiveness.
Efficient algorithms
To overcome the current challenges in hyperthermia treatment, explores solutions to improve temperature measurement and control accuracy. One approach involves leveraging MRI scanners to correct for measurement artifacts, providing reliable internal temperature readings essential for safe treatment. Furthermore, new algorithms have been developed to create predictive models that can handle complex heating scenarios, allowing for precise, targeted adjustments of the heating device settings. Together, these innovations enable hyperthermia therapy to become a more effective and safer option in cancer treatment, with the potential to significantly improve patient outcomes by accurately achieving therapeutic tumor temperatures.
Related on this research is the PhD defense of Daniel Deenen. Read the article.
Title of PhD thesis: . Supervisors: Prof. Maurice Heemels and Prof. Maarten paulides.