Abstract
BackgroundType-C dose algorithms provide more accurate dosimetry for lung SBRT treatment planning. However, because current dosimetric protocols were developed based on conventional algorithms, its applicability for the new generation algorithms needs to be determined. Previous studies on this issue used small sample sizes and reached discordant conclusions. Our study assessed dose calculation of a Type-C algorithm with current dosimetric protocols in a large patient cohort, in order to demonstrate the dosimetric impacts and necessary treatment planning steps of switching from a Type-B to a Type-C dose algorithm for lung SBRT planning.MethodsFifty-two lung SBRT patients were included, each planned using coplanar VMAT arcs, normalized to D95% = prescription dose using a Type-B algorithm. These were compared against three Type-C plans: re-calculated plans (identical plan parameters), re-normalized plans (D95% = prescription dose), and re-optimized plans. Dosimetric endpoints were extracted and compared among the four plans, including RTOG dosimetric criteria: (R100%, R50%, D2cm, V105%, and lung V20), PTV Dmin, Dmax, Dmean, V% and D90%, PTV coverage (V100%), homogeneity index (HI), and Paddick conformity index (PCI).ResultsRe-calculated Type-C plans resulted in decreased PTV Dmin with a mean difference of 5.2% and increased Dmax with a mean difference of 3.1%, similar or improved RTOG dose compliance, but compromised PTV coverage (mean D95% and V100% reduction of 2.5 and 8.1%, respectively). Seven plans had >5% D95% reduction (maximum reduction = 16.7%), and 18 plans had >5% V100% reduction (maximum reduction = 60.0%). Re-normalized Type-C plans restored target coverage, but yielded degraded plan conformity (average PCI reduction 4.0%), and RTOG dosimetric criteria deviation worsened in 11 plans, in R50%, D2cm, and R100%. Except for one case, re-optimized Type-C plans restored RTOG compliance achieved by the original Type-B plans, resulting in similar dosimetric values but slightly higher target dose heterogeneity (mean HI increase = 13.2%).ConclusionsType-B SBRT lung plans considerably overestimate target coverage for some patients, necessitating Type-C re-normalization or re-optimization. Current RTOG dosimetric criteria appear to remain appropriate.
Highlights
Type-C dose algorithms provide more accurate dosimetry for lung Stereotactic body radiotherapy (SBRT) treatment planning
Several studies showed a substantial reduction in the treatment time for SBRT lung cases using volumetric-modulated arc therapy (VMAT) when compared to intensity-modulated radiation therapy (IMRT) and conformal beam treatment, from dozens of to just a few minutes, especially when combined with the high dose rates provided by flattening-filter-free modes of modern linear accelerators (LINACs) [7, 9, 11]
While offering comparable steep dose gradients and critical tissue sparing to IMRT, VMAT was found to be less susceptible to the interplay effect that prevented the wide application of IMRT in thoracic radiotherapy, especially when conventional dose rates are used [8, 10, 12]
Summary
Type-C dose algorithms provide more accurate dosimetry for lung SBRT treatment planning. Because current dosimetric protocols were developed based on conventional algorithms, its applicability for the new generation algorithms needs to be determined Previous studies on this issue used small sample sizes and reached discordant conclusions. Several studies showed a substantial reduction in the treatment time for SBRT lung cases using VMAT when compared to intensity-modulated radiation therapy (IMRT) and conformal beam treatment, from dozens of to just a few minutes, especially when combined with the high dose rates provided by flattening-filter-free modes of modern linear accelerators (LINACs) [7, 9, 11]. Conventional homogeneous dose calculations and Type-A or pencil beam algorithms with equivalent path length corrections can often lead to target peripheral dose over-estimation as high as 50% [22,23,24,25]. Studies have shown that while these algorithms resulted in
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