Oleg N Vassiliev1, Christine B Peterson2, Joe Y Chang3, Radhe Mohan1. 1. Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. 2. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. 3. Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Abstract
Aim: Previous studies showed that replacing conventional flattened beams (FF) with flattening filter-free (FFF) beams improves the therapeutic ratio in lung stereotactic body radiation therapy (SBRT), but these findings could have been impacted by dose calculation uncertainties caused by the heterogeneity of the thoracic anatomy and by respiratory motion, which were particularly high for target coverage. In this study, we minimized such uncertainties by calculating doses using high-spatial-resolution Monte Carlo and four-dimensional computed tomography (4DCT) images. We aimed to evaluate more reliably the benefits of using FFF beams for lung SBRT. Materials and methods: For a cohort of 15 patients with early stage lung cancer that we investigated in a previous treatment planning study, we recalculated dose distributions with Monte Carlo using 4DCT images. This included fifteen FF and fifteen FFF treatment plans. Results: Compared to Monte Carlo, the treatment planning system (TPS) over-predicted doses in low-dose regions of the planning target volume. For most patients, replacing FF beams with FFF beams improved target coverage, tumor control, and uncomplicated tumor control probabilities. Conclusions: Monte Carlo tends to reveal deficiencies in target coverage compared to coverage predicted by the TPS. Our data support previously reported benefits of using FFF beams for lung SBRT.
Aim: Previous studies showed that replacing conventional flattened beams (FF) with flattening filter-free (FFF) beams improves the therapeutic ratio in lung stereotactic body radiation therapy (SBRT), but these findings could have been impacted by dose calculation uncertainties caused by the heterogeneity of the thoracic anatomy and by respiratory motion, which were particularly high for target coverage. In this study, we minimized such uncertainties by calculating doses using high-spatial-resolution Monte Carlo and four-dimensional computed tomography (4DCT) images. We aimed to evaluate more reliably the benefits of using FFF beams for lung SBRT. Materials and methods: For a cohort of 15 patients with early stage lung cancer that we investigated in a previous treatment planning study, we recalculated dose distributions with Monte Carlo using 4DCT images. This included fifteen FF and fifteen FFF treatment plans. Results: Compared to Monte Carlo, the treatment planning system (TPS) over-predicted doses in low-dose regions of the planning target volume. For most patients, replacing FF beams with FFF beams improved target coverage, tumor control, and uncomplicated tumor control probabilities. Conclusions: Monte Carlo tends to reveal deficiencies in target coverage compared to coverage predicted by the TPS. Our data support previously reported benefits of using FFF beams for lung SBRT.
Authors: Daniel Gasic; Lars Ohlhues; N Patrik Brodin; Lotte S Fog; Tobias Pommer; Jens P Bangsgaard; Per Munck Af Rosenschöld Journal: Acta Oncol Date: 2014-06-17 Impact factor: 4.089
Authors: Oleg N Vassiliev; Stephen F Kry; He C Wang; Christine B Peterson; Joe Y Chang; Radhe Mohan Journal: Phys Med Biol Date: 2018-09-28 Impact factor: 3.609
Authors: Brendan M Prendergast; John B Fiveash; Richard A Popple; Grant M Clark; Evan M Thomas; Douglas J Minnich; Rojymon Jacob; Sharon A Spencer; James A Bonner; Michael C Dobelbower Journal: J Appl Clin Med Phys Date: 2013-05-06 Impact factor: 2.102