B Aklan1, B Zilles1, P Paprottka2, K Manz3, M Pfirrmann3, M Santl1, S Abdel-Rahman1, L H Lindner1. 1. a Department of Internal Medicine III , Ludwig Maximilians University Hospital , Munich , Germany. 2. b Institute for Clinical Radiology, Ludwig Maximilians University Hospital , Munich, Germany. 3. c Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Ludwig-Maximilians-University Munich , Munich , Germany.
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.
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.
Authors: Sergio Curto; Bassim Aklan; Tim Mulder; Oliver Mils; Manfred Schmidt; Ulf Lamprecht; Michael Peller; Ruediger Wessalowski; Lars H Lindner; Rainer Fietkau; Daniel Zips; Gennaro G Bellizzi; Netteke van Holthe; Martine Franckena; Margarethus M Paulides; Gerard C van Rhoon Journal: Cancers (Basel) Date: 2019-11-02 Impact factor: 6.639