Updating approach for lexicographic optimization-based planning to improve cervical cancer plan quality

Abstract

Background To investigate the capability of mCycle (Elekta AB, Stockholm, Sweden), a fully automated lexicographic-optimization planning algorithm, to enhance plan quality of an already-validated Wish-List (WL) pushing on the organs-at-risk (OAR) sparing. Material and Methods Twenty-four mono-institutional cervical cancer VMAT plans were retrospectively selected. Two WLs have been defined to reproduce manual plans (WL01), and to improve the OAR sparing without affecting minimum target coverage and plan delivery accuracy (WL02). These WLs were used to automatically re-plan the selected cases. Manual plans (MP) and mCycle plans (mCP01 and mCP02) were compared in terms of dose distributions, complexity, delivery accuracy, and clinical acceptability. Two senior physicians independently performed a blind clinical evaluation, and a global quality index was used for overall assessment. Results WL tweaking requests 5 and 3 working days for the WL01 and the WL02, respectively. The re-planning took 3 working days in both cases. mCP01 best performed in terms of target coverage (PTV V95% (%): MP 98.0 [95.6–99.3], mCP01 99.2 [89.7–99.9], mCP02 96.9 [89.4–99.5]), while mCP02 showed an OAR sparing improvement (e.g., Rectum D50% (Gy): MP 41.7 [30.2–47.0], mCP01 40.3 [31.4–45.8], mCP02 32.6 [26.9–42.6]). The complexity of mCPs increased without affecting plan delivery accuracy. In blinded comparisons, all mCPs were considered clinically acceptable, and were preferred over MP in 90% of cases. Globally, mCPs registered plan quality scores at least comparable to MP. Conclusions This study showed the flexibility of the lexicographic approach in creating more demanding WL that can potentially minimize toxicities in RT plans.