Mr thermometry accuracy and prospective imaging-based patient selection in mr-guided hyperthermia treatment for locally advanced cervical cancer

Journal Article (2021)
Author(s)

Iva Vilasboas-Ribeiro (Erasmus MC)

Sergio Curto (Erasmus MC)

Gerard Van Rhoon (TU Delft - RST/Applied Radiation & Isotopes, Erasmus MC)

Martine Franckena (Erasmus MC)

Margarethus M. Paulides (Erasmus MC, Eindhoven University of Technology)

Research Group
RST/Applied Radiation & Isotopes
Copyright
© 2021 Iva Vilasboas-Ribeiro, Sergio Curto, G.C. van Rhoon, Martine Franckena, Margarethus M. Paulides
DOI related publication
https://doi.org/10.3390/cancers13143503
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Iva Vilasboas-Ribeiro, Sergio Curto, G.C. van Rhoon, Martine Franckena, Margarethus M. Paulides
Research Group
RST/Applied Radiation & Isotopes
Issue number
14
Volume number
13
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Abstract

The efficacy of a hyperthermia treatment depends on the delivery of well-controlled heating; hence, accurate temperature monitoring is essential for ensuring effective treatment. For deep pelvic hyperthermia, there are no comprehensive and systematic reports on MR thermometry. Moreover, data inclusion generally lacks objective selection criteria leading to a high probability of bias when comparing results. Herein, we studied whether imaging-based data inclusion predicts accuracy and could serve as a tool for prospective patient selection. The accuracy of the MR thermometry in patients with locally advanced cervical cancer was benchmarked against intraluminal temperature. We found that gastrointestinal air motion at the start of the treatment, quantified by the Jaccard similarity coefficient, was a good predictor for MR thermometry accuracy. The results for the group that was selected for low gastrointestinal air motion improved compared to the results for all patients by 50% (accuracy), 26% (precision), and 80% (bias). We found an average MR thermometry accuracy of 2.0 °C when all patients were considered and 1.0 °C for the selected group. These results serve as the basis for comprehensive benchmarking of novel technologies. The Jaccard similarity coefficient also has good potential to prospectively determine in which patients the MR thermometry will be valuable.