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.
Bibliographical noteFunding Information:
This research has been made possible by the Dutch Cancer Society and the Netherlands Organization for Scientific Research (NWO) as a part of their joint Partnership Programme: ?Tech-nology for Oncology? grant number: 15195 and the Dutch Cancer Society grant KWF-DDHK 2013-6072. In addition, this project has received funding from the European Union?s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 845645.
- Imaging-based selection
- Locally advanced cervical cancer
- MR thermometry
- RF hyperthermia