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

Abstract

AimIn 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 methodsTwenty-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.ResultsThe 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 (V95%: 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).ConclusionsmCycle 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.

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

“…Patients were treated using an Elekta VersaHD linear accelerator equipped with the Agility Multileaf Collimator (MLC, 160 leaves, 5 mm thickness, up to 6.5 cm/sec), with the Monitor Unit (MU) calibration of 1 MU = 1 cGy with the reference eld at the reference depth. The clinical objectives were accounted for in the a-priori MCO of the clinical Monaco™ TPS, as deeply described in Trivellato et al [21]. Final normalization of dose distribution to achieve minimum PTV coverage or to satisfy small bowel constraints has been allowed.…”

“…The mCycle uence optimization (FMO) uses a twopass automated lexicographic MCO in which constraints and prioritized objectives are managed by the planner through the WL. The WL tuning process is a multi-step iterative method described by Hussein et al [2], while the description of the two-passed uence LO was thoroughly discussed by Trivellato et al [21].…”

“…The previous PQI institutional de nition for cervical cancer treatment has been used. The global index is de ned as the quadratic mean of 4 sub-metrics considering the target coverage, the OAR sparing, the accuracy of plan delivery, and the plan complexity, each one of them ranging from 0 to 1 [21]. Each submetric score is increasing as the constraint ful llment improves.…”

“…The LO optimization problem follows the hierarchical order of a treatment site speci c list of requests, a so-called Wish-List (WL). The WLs are generated by imitating the plan discussion process between radiation oncologists and planners, and are characterized by clinical and planning constraints (CC and PC, respectively), which cannot be violated, and a list of prioritized objective functions according to their importance degree [20,21]. At our Institute, a recent validation in cervical cancer treatment has been concluded, demonstrating that automated plans were dosimetric comparable with manual plans, but outperformed manual ones at the blinded clinical scoring [21].…”

“…The following comparison of these plans has been based on dose distributions, complexity, delivery accuracy, and clinical acceptability. The global plan quality score introduced by Trivellato et al [21] was used in the comparison.…”