The potential of constrained SAR focusing for hyperthermia treatment planning: analysis for the head & neck region

Clinical trials have shown that hyperthermia is a potent adjuvant to conventional cancer treatments, but the temperatures currently achieved in the clinic are still suboptimal. Hyperthermia treatment planning simulations have potential to improve the heating profile of phased-array applicators. An i...

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Bibliographic Details
Published in:Physics in medicine & biology 2018-12, Vol.64 (1), p.15013-015013
Main Authors: Bellizzi, G G, Drizdal, T, van Rhoon, G C, Crocco, L, Isernia, T, Paulides, M M
Format: Article
Language:English
Subjects:
constrained optimization
convex programming
SAR
treatment planning
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Summary:Clinical trials have shown that hyperthermia is a potent adjuvant to conventional cancer treatments, but the temperatures currently achieved in the clinic are still suboptimal. Hyperthermia treatment planning simulations have potential to improve the heating profile of phased-array applicators. An important open challenge is the development of an effective optimization procedure that enables uniform heating of the target region while keeping temperature below a threshold in healthy tissues. In this work, we analyzed the effectiveness and efficiency of a recently proposed optimization approach, i.e. focusing via constrained power optimization (FOCO), using 3D simulations of twelve clinical patient specific models. FOCO performance was compared against a clinically used particle swarm based optimization approach. Evaluation metrics were target coverage at the 25% iso-SAR level, target hotspot quotient, median target temperature (T50) and computational requirements. Our results show that, on average, constrained power focusing performs slightly better than the clinical benchmark (T50 °C), but outperforms this clinical benchmark for large target volumes (40 cm, T50 °C). In addition, the results are achieved in a shorter time (%) and are repeatable because the approach is formulated as a convex optimization problem.
ISSN:0031-9155
1361-6560
1361-6560
DOI:10.1088/1361-6560/aaf0c4