A two‐step treatment planning strategy incorporating knowledge‐based planning for head‐and‐neck radiotherapy

Abstract

AbstractPurposeThere has been much research interest in automated head‐and‐neck (HN) planning with the goal of reducing planning time and inter‐planner variability while improving plan quality. However, clinical uses are still limited and institution‐dependent due to the plan complexity. This work aims to investigate whether the use of a novel semi‐automated two‐step optimization method (TSP) can improve the quality and efficiency of planning while providing a simple framework that other institutions can follow.Methods and materialsForty patients (two and three prescription isodose levels) were retrospectively studied. Plans were generated by TSP which incorporates a knowledge‐based planning solution. Comparisons were performed for plan conformity and selected dose‐volume indices between clinical plan (CP) and TSP. Blind reviews were carried out by 15 clinicians to determine preference between the CP and TSP, as well as clinical suitability.ResultsFor majority of patients studied, TSP had similar or slightly better conformity for the high‐dose PTV, and better conformity for the low‐dose PTV and 45 Gy isodose lines compared to CP. The only statistically significant difference observed for the serial organs was a reduction of the spinal cord maximum dose with TSP. Except for left parotid gland (Dmean and V30 for both 2R× and 3R× groups) and oral cavity (Dmean for 3R× group), TSP had significant dose reductions for all parallel organs compared to CP. Blind reviewers either showed preference/no preference for 57.2%/21.7% (2R×) and 57.5%/27.8% (3R×) of TSP compared with CP. Excluding no preference votes, 60% of TSP were preferred. TSP was selected majority of the time when looking at the vote distribution for each patient individually.ConclusionOur TSP allows plans to be created within 90‐min time frame while offering improvements in plan quality and less inter‐planner variability as compared to traditional planning techniques.