Fully Automated Volumetric Modulated Arc Therapy Plan Generation for Prostate Cancer Patients

Validation of Fully Automated VMAT Plan Generation for Library-Based Plan-of-the-Day Cervical Cancer Radiotherapy

“…Secondly, the automated building of patient-specific templates for automated plan generation by Monaco was tuned such that Erasmus-iCycle plans were properly re-constructed in Monaco. The generated patient-specific templates have a layering (Monaco terminology) determined by the Erasmus-iCycle priorities, in addition to parallel and serial cost functions with volume effect parameters for OARs (details in [9]).…”

“…The highest priority objective was given to the PTV, using the Logarithmic Tumor Control Probability (LTCP) function to obtain adequate PTV coverage for all plans (see [9,13] for details on the LTCP). The applied cell sensitivity parameter α was set to 0.8.…”

“…This limits the widespread clinical implementation of library-based plan-of-the-day strategies or puts constraints on the number of plans in a library. In previous studies, we have demonstrated for head and neck and prostate cancer that automated treatment plan generation could substantially reduce the workload compared to conventional planning with equal or superior plan quality [8,9]. The purpose of this work was to develop and validate automatic dual-arc VMAT treatment planning for cervical cancer patients, based on our in-house platform for automated plan generation.…”

Shortening Delivery Times of Intensity Modulated Proton Therapy by Reducing Proton Energy Layers During Treatment Plan Optimization

“…Generally, a single wish list can be used per patient group, which enables fully automatic treatment planning. Automatic plan generation allows for an objective comparison between different planning strategies and was shown to result in superior plan quality compared with manual planning (10,11).…”

Improved robotic stereotactic body radiation therapy plan quality and planning efficacy for organ-confined prostate cancer utilizing overlap-volume histogram-driven planning methodology

“…Several studies indicated that the plan quality of inverse planning in terms of organ sparing and target coverage relies heavily on planner experience and available planning time [6,7]. Thus, an efficient and planner-experience independent planning approach to robotic SBRT is in great need.Multi-criteria optimization, MdaccAutoPlan and several knowledge-based models have been developed for improving plan quality and planning efficiency in IMRT [8][9][10][11][12][13][14][15][16][17]. Here, we introduce a knowledge-based planning approach that utilizes overlap-volume histogram (OVH) and a prior patient library [11][12][13] to enhance plan quality and efficiency in robotic SBRT for organ-confined prostate cancer.…”