Comprehensive dosimetric and clinical evaluation of lexicographic optimization-based planning for cervical cancer

Sara Trivellato; Paolo Caricato; Roberto Pellegrini; Gianluca Montanari; Martina Camilla Daniotti; Bianca Bordigoni; Valeria Faccenda; Denis Panizza; Sofia Meregalli; Elisa Bonetto; Stefano Arcangeli; Elena De Ponti

doi:10.3389/fonc.2022.1041839

Comprehensive dosimetric and clinical evaluation of lexicographic optimization-based planning for cervical cancer

Front Oncol. 2022 Nov 16:12:1041839. doi: 10.3389/fonc.2022.1041839. eCollection 2022.

Authors

Sara Trivellato¹, Paolo Caricato^{1

2}, Roberto Pellegrini³, Gianluca Montanari¹, Martina Camilla Daniotti^{1

2}, Bianca Bordigoni^{1

4}, Valeria Faccenda^{1

2}, Denis Panizza^{1

5}, Sofia Meregalli^{5

6}, Elisa Bonetto⁶, Stefano Arcangeli^{5

6}, Elena De Ponti^{1

5}

Affiliations

¹ Medical Physics Department, Azienda Socio Sanitaria Territoriale (ASST) Monza, Monza, Italy.
² Department of Physics, University of Milan, Milan, Italy.
³ Global Clinical Science, Elekta AB, Stockholm, Sweden.
⁴ Department of Physics, University of Milan Bicocca, Milan, Italy.
⁵ School of Medicine and Surgery, University of Milan Bicocca, Milan, Italy.
⁶ Department of Radiation Oncology, Azienda Socio Sanitaria Territoriale (ASST) Monza, Monza, Italy.

Abstract

Aim: In this study, a not yet commercially available fully-automated lexicographic optimization (LO) planning algorithm, called mCycle (Elekta AB, Stockholm, Sweden), was validated for cervical cancer.

Material and methods: Twenty-four mono-institutional consecutive treatment plans (50 Gy/25 fx) delivered between November 2019 and April 2022 were retrospectively selected. The automatic re-planning was performed by mCycle, implemented in the Monaco TPS research version (v5.59.13), in which the LO and Multicriterial Optimization (MCO) are coupled with Monte Carlo calculation. mCycle optimization follows an a priori assigned priority list, the so-called Wish List (WL), representing a dialogue between the radiation oncologist and the planner, setting hard constraints and following objectives. The WL was tuned on a patient subset according to the institution's clinical protocol to obtain an optimal plan in a single optimization. This robust WL was then used to automatically re-plan the remaining patients. Manual plans (MP) and mCycle plans (mCP) were compared in terms of dose distributions, complexity (modulation complexity score, MCS), and delivery accuracy (perpendicular diode matrices, gamma analysis-passing ratio, PR). Their clinical acceptability was assessed through the blind choice of two radiation oncologists. Finally, a global quality score index (SI) was defined to gather into a single number the plan evaluation process.

Results: The WL tuning requested four patients. The 20 automated re-planning tasks took three working days. The median optimization and calculation time can be estimated at 4 h and just over 1 h per MP and mCP, respectively. The dose comparison showed a comparable organ-at-risk spare. The planning target volume coverage increased (V_95%: MP 98.0% [95.6-99.3]; mCP 99.2%[89.7-99.9], p >0.05). A significant increase has been registered in MCS (MP 0.29 [0.24-0.34]; mCP 0.26 [0.23-0.30], p <0.05) without affecting delivery accuracy (PR (3%/3mm): MP 97.0% [92.7-99.2]; mCP 97.1% [95.0-98.6], p >0.05). In the blind choice, all mCP results were clinically acceptable and chosen over MP in more than 75% of cases. The median SI score was 0.69 [0.41-0.84] and 0.73 [0.51-0.82] for MP and mCP, respectively (p >0.05).

Conclusions: mCycle plans were comparable to clinical manual plans, more complex but accurately deliverable and registering a similar SI. Automated plans outperformed manual plans in blinded clinical choice.

Keywords: VMAT (volumetric modulated arc therapy); automated planning; cervical cancer; lexicographic optimization; plan comparison; plan quality.