Impact of number of segmented tissues on SAR prediction accuracy in deep pelvic hyperthermia treatment planning

Iva Vilasboas-Ribeiro*, Gerard C. van Rhoon, Tomas Drizdal, Martine Franckena, Margarethus M. Paulides

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

11 Citations (Scopus)
37 Downloads (Pure)


In hyperthermia, the general opinion is that pre-treatment optimization of treatment settings requires a patient-specific model. For deep pelvic hyperthermia treatment planning (HTP), tissue models comprising four tissue categories are currently discriminated. For head and neck HTP, we found that more tissues are required for increasing accuracy. In this work, we evaluated the impact of the number of segmented tissues on the predicted specific absorption rate (SAR) for the pelvic region. Highly detailed anatomical models of five healthy volunteers were selected from a virtual database. For each model, seven lists with varying levels of segmentation detail were defined and used as an input for a modeling study. SAR changes were quantified using the change in target-to-hotspot-quotient and maximum SAR relative differences, with respect to the most detailed patient model. The main finding of this study was that the inclusion of high water content tissues in the segmentation may result in a clinically relevant impact on the SAR distribution and on the predicted hyperthermia treatment quality when considering our pre-established thresholds. In general, our results underline the current clinical segmentation protocol and help to prioritize any improvements.

Original languageEnglish
Article number2646
Pages (from-to)1-16
Issue number9
Publication statusPublished - 2020


  • 3D patient modeling
  • Deep hyperthermia treatment planning
  • RF hyperthermia
  • Tissue delineation and segmentation


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