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Aklan, B.; Zilles, B.; Paprottka, P.; Manz, Kirsi ORCID: 0000-0002-7740-4076; Pfirrmann, M.; Santl, M.; Abdel-Rahman, S.; Lindner, L.H. (2019): Regional deep hyperthermia: quantitative evaluation of predicted and direct measured temperature distributions in patients with high-risk extremity soft-tissue sarcoma. In: International Journal of Hyperthermia, Vol. 36, No. 1: pp. 170-185
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Abstract

Background: Temperature distributions resulting from hyperthermia treatment of patients with high-risk soft-tissue sarcoma (STS) were quantitatively evaluated and globally compared with thermal simulations performed by a treatment planning system. The aim was to test whether the treatment planning system was able to predict correct temperature distributions. Methods: Five patients underwent computed tomography (CT) fluoroscopy-guided placement of tumor catheters used for the interstitial temperature measurements. For the simulations, five 3 D patient models were reconstructed by segmenting the patient CT datasets into different tissues. The measured and simulated data were evaluated by calculating the temperature change (ΔT), T90, T50, T20, Tmean, Tmin and Tmax, as well as the 90th percentile thermal dose (CEM43T90). In order to measure the agreement between both methods quantitatively, the Bland–Altman analysis was applied. Results: The absolute difference between measured and simulated temperatures were found to be 2°, 6°, 1°, 4°, 5° and 4 °C on average for Tmin, Tmax, T90, T50, T20 and Tmean, respectively. Furthermore, the thermal simulations exhibited relatively higher thermal dose compared to those that were measured. Finally, the results of the Bland–Altman analysis showed that the mean difference between both methods was above 2 °C which is considered to be clinically unacceptable. Conclusion: Given the current practical limitations on resolution of calculation grid, tissue properties, and perfusion information, the software SigmaHyperPlan™ is incapable to produce thermal simulations with sufficient correlation to typically heterogeneous tissue temperatures to be useful for clinical treatment planning.