Photon Optimizer (PO) prevails over Progressive Resolution Optimizer (PRO) for VMAT planning with or without knowledge‐based solution

Abstract

The enhanced dosimetric performance of knowledge‐based volumetric modulated arc therapy (VMAT) planning might be jointly contributed by the patient‐specific optimization objectives, as estimated by the RapidPlan model, and by the potentially improved Photon Optimizer (PO) algorithm than the previous Progressive Resolution Optimizer (PRO) engine. As PO is mandatory for RapidPlan estimation but optional for conventional manual planning, appreciating the two optimizers may provide practical guidelines for the algorithm selection because knowledge‐based planning may not replace the current method completely in a short run. Using a previously validated dose–volume histogram (DVH) estimation model which can produce clinically acceptable plans automatically for rectal cancer patients without interactive manual adjustment, this study reoptimized 30 historically approved plans (referred as clinical plans that were created manually with PRO) with RapidPlan solution (PO plans). Then the PRO algorithm was utilized to optimize the plans again using the same dose–volume constraints as PO plans, where the line objectives were converted as a series of point objectives automatically (PRO plans). On the basis of comparable target dose coverage, the combined applications of new objectives and PO algorithm have significantly reduced the organs‐at‐risk (OAR) exposure by 23.49–32.72% than the clinical plans. These discrepancies have been largely preserved after substituting PRO for PO, indicating the dosimetric improvements were mostly attributable to the refined objectives. Therefore, Eclipse users of earlier versions may instantly benefit from adopting the model‐generated objectives from other RapidPlan‐equipped centers, even with PRO algorithm. However, the additional contribution made by the PO relative to PRO accounted for 1.54–3.74%, suggesting PO should be selected with priority whenever available, with or without RapidPlan solution as a purchasable package. Significantly increased monitor units were associated with the model‐generated objectives but independent from the optimizers, indicating higher modulation in these plans. As a summary, PO prevails over PRO algorithm for VMAT planning with or without knowledge‐based technique.

RapidPlan knowledge based planning: iterative learning process and model ability to steer planning strategies

“…In the present work, the clinical plans (for CL-1 models) were generated with the PRO optimization engine and the AAA algorithm, while in the whole RP validation and subsequent model, the PO optimization and Acuros dose calculation algorithms were used. It is known that PO was found to prevail over PRO for VMAT planning [30, 31], and Acuros is more accurate than AAA [32, 33]. Concerning the optimizer, outperforming PO with respect to PRO, could have a double effect.…”

Improving treatment efficiency via photon optimizer (PO) MLC algorithm for synchronous single‐isocenter/multiple‐lesions VMAT lung SBRT

“…A few investigators have reported the dosimetric differences in PO algorithm for IMRT/VMAT planning in a digital phantom, conventional prostate, head and neck, and brain treatments, knowledge‐based planning to rectal cancer patients and a single‐lesion lung SBRT and stereotactic brain treatments . For instance, Jiang et al evaluated the performance of PO over PRO for VMAT planning of 30 rectal cancer patients with or without knowledge‐based planning. A knowledge‐based model was generated using manually optimized PRO plans.…”

“…Fixed voxel resolutions of 1.25, 2.5 or 5 mm can be used during multiresolution optimization. For a single‐lesion treatment, a few investigators have reported dosimetric differences between PO and PRO optimization for IMRT/VMAT plans . For instance, the advantages and limitations of PO algorithm compared to its predecessor PRO for IMRT plans were evaluated by Binny et al Eleven plans including prostate, brain, and head and neck treatments were optimized using both PO and PRO algorithms.…”

Impact of nominal photon energies on normal tissue sparing in knowledge-based radiotherapy treatment planning for rectal cancer patients

“…A published RapidPlan model for pre-surgical rectal cancer patients was used in this study[11,12,13]. As a brief review, the model was trained with 81 historical plans that were contoured and planned following Li's study [14].…”

“…Considering the large target volumes were relatively deep-seated, all historical plans were optimized with 10 MV flattened photon beams (10X) by experts. The robustness of the model has been validated on over 100 cases [11–13].…”