Template-based automation of treatment planning in advanced radiotherapy: a comprehensive dosimetric and clinical evaluation

Abstract

Despite the recent advanced developments in radiation therapy planning, treatment planning for head-neck and pelvic cancers remains challenging due to large concave target volumes, multiple dose prescriptions and numerous organs at risk close to targets. Inter-institutional studies highlighted that plan quality strongly depends on planner experience and skills. Automated optimization of planning procedure may improve plan quality and best practice. We performed a comprehensive dosimetric and clinical evaluation of the Pinnacle3 AutoPlanning engine, comparing automatically generated plans (AP) with the historically clinically accepted manually-generated ones (MP). Thirty-six patients (12 for each of the following anatomical sites: head-neck, high-risk prostate and endometrial cancer) were re-planned with the AutoPlanning engine. Planning and optimization workflow was developed to automatically generate “dual-arc” VMAT plans with simultaneously integrated boost. Various dose and dose-volume parameters were used to build three metrics able to supply a global Plan Quality Index evaluation in terms of dose conformity indexes, targets coverage and sparing of critical organs. All plans were scored in a blinded clinical evaluation by two senior radiation oncologists. Dose accuracy was validated using the PTW Octavius-4D phantom together with the 1500 2D-array. Autoplanning was able to produce high-quality clinically acceptable plans in all cases. The main benefit of Autoplanning strategy was the improvement of overall treatment quality due to significant increased dose conformity and reduction of integral dose by 6–10%, keeping similar targets coverage. Overall planning time was reduced to 60–80 minutes, about a third of time needed for manual planning. In 94% of clinical evaluations, the AP plans scored equal or better to MP plans. Despite the increased fluence modulation, dose measurements reported an optimal agreement with dose calculations with a γ-pass-rate greater than 95% for 3%(global)-2 mm criteria. Autoplanning engine is an effective device enabling the generation of VMAT high quality treatment plans according to institutional specific planning protocols.

Personalized Treatment Planning Automation in Prostate Cancer Radiation Oncology: A Comprehensive Dosimetric Study

“…Automated VMAT plans exhibited strongly improved organ sparing and higher conformity compared to manual plans, with mean doses of bladder and rectum reduced by 10.7 and 4.5 Gy, respectively. Recently, we evaluated the potential of Pinnacle Autoplanning for head-neck, endometrial, and high-risk prostate cases, reporting a significant increase of dose conformity and a reduction of plans variability and planning times ( 21 ). To the authors’ knowledge only another study has been published in this clinical setting.…”

“…a template of parameters that can be customized for each treatment protocol and tumor site. The Autoplanning engine has been extensively described in a previous study ( 21 ). Briefly, the Technique includes the definition of all beam parameters, dose prescriptions, and planning objectives for PTVs and OARs and was defined on the same beam parameters, dose prescription, and clinical objectives adopted for the MP plans.…”

“…In particular, the Raystation TPS provides a pool of output plans on the Pareto-optimal surface, leaving the user to define the best final plan, while the Erasmus-iCycle engine supplies the most Pareto-optimal plan according to a clinical wish-list of dosimetric objectives. The template-based approach has been implemented in the Pinnacle TPS (Philips Medical Systems, Fitchburg, WI, USA) in the so-called Autoplanning engine ( 21 ). In this strategy, the planning optimization process uses a template to formulate all the planning goals and an iterative approach able to mimic the planning procedure usually adopted by experienced planners to generated high-quality plans.…”

Knowledge-based Planning using Pseudo-structures for Volumetric Modulated arc Therapy (VMAT) of Postoperative Uterine Cervical Cancer: A Multi-Institutional Study

“…The potential bene t of this modeling approach using pseudo-structures is time e ciency. In practice, the correcting of tumor and normal tissue variations through modi cation of the original plan is hampered by the time-consuming re-planning process, which currently represents the major obstacle for large scale implementation of this strategy [33]. Recently, the use of deformable image registration (DIR) for automatic propagation of structures in ART has been widely investigated.…”

Characterization of automatic treatment planning approaches in radiotherapy

“…The behaviour of the iterative optimizer can be unexpected and a large part of protocol development consists of trial-and-error [3,4,6]. Several studies have been published that compare protocol based automatic plans to manual plans for treatment sites H&N [3,[6][7][8][9][10][11], lung [4,12,13], oesophagus [14], hippocampus sparing whole brain [15], and prostate [11,16]. Most studies report that the quality of the automatic plans is at least similar to manual plans.…”