Statistical breathing curve sampling to quantify interplay effects of moving lung tumors in a 4D Monte Carlo dose calculation framework. (September 2022)

• Record Type: Journal Article
• Authors: von Münchow, Asmus; Straub, Katrin; Losert, Christoph; Shpani, Roel; Hofmaier, Jan; Freislederer, Philipp; Heinz, Christian; Thieke, Christian; Söhn, Matthias; Alber, Markus; Floca, Ralf; Belka, Claus; Parodi, Katia; Reiner, Michael; Kamp, Florian
• Is Part Of: Physica medica. Volume 101(2022)
• Page Start: 104
• Page End: 111
• Publication Date: 2022-09
• Subjects: 4D dose calculation -- Lung tumors -- Monte Carlo dose calculation -- Interplay effects; Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2022.07.006
• Languages: English
• ISSNs: 1120-1797

Abstract

Highlights: 4D Monte Carlo dose calculation and accumulation tool to quantify interplay effects. Statistical sampling of the breathing curve is introduced to broaden applicability. Possibility to comprehensively assess and evaluate dosimetric interplay effects. Linac-log file based recalculations and DICOM-RT plan based prospective simulations. Abstract: Purpose: The interplay between respiratory tumor motion and dose application by intensity modulated radiotherapy (IMRT) techniques can potentially lead to undesirable and non-intuitive deviations from the planned dose distribution. We developed a 4D Monte Carlo (MC) dose recalculation framework featuring statistical breathing curve sampling, to precisely simulate the dose distribution for moving target volumes aiming at a comprehensive assessment of interplay effects. Methods: We implemented a dose accumulation tool that enables dose recalculations of arbitrary breathing curves including the actual breathing curve of the patient. This MC dose recalculation framework is based on linac log-files, facilitating a high temporal resolution up to 0.1 s. By statistical analysis of 128 different breathing curves, interplay susceptibility of different treatment parameters was evaluated for an exemplary patient case. To facilitate prospective clinical application in the treatment planning stage, in which patient breathing curves or linac log-files are not available, we derived a log-file free version with breathing curves generated by a random walk approach. Interplay was quantified by standard deviations σ in D5%, D50% and D95% . Results: Interplay induced dose deviations for single fractions were observed and evaluated for IMRT and volumetric arc therapy ( σ D 95 % up to 1.3 %) showing a decrease with higher fraction doses and an increase with higher MU rates. Interplay effects for conformal treatment techniques were negligible ( σ < 0.1 % ) . The log-file free version and the random walk generated breathing curves yielded similar results (deviations in σ < 0.1 %) and can be used as substitutes for interplay assessment. Conclusion: It is feasible to combine statistically sampled breathing curves with MC dose calculations. The universality of the presented framework allows comprehensive assessment of interplay effects in retrospective and prospective clinically relevant scenarios.