Automated Planning for Prostate Stereotactic Body Radiation Therapy on the 1.5 T MR-Linac

Naccarato, S.; Rigo, Michele; Pellegrini, Roberto; Voet, P.; Akhiat, Hafid; Gurrera, Davide; Simone, Antonio De; Sicignano, G.; Mazzola, Rosario; Figlia, Vanessa; Ricchetti, F.; Nicosia, Luca; Giaj-Levra, Niccolò; Cuccia, Francesco; Stavreva, N; Pressyanov, D.; Stavrev, Pavel; Alongi, Filippo; Ruggieri, R.

doi:10.1016/j.adro.2021.100865

Cited by 20 publications

(17 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar differences, i.e. slightly higher target coverages and lower OAR doses, were also observed in mCycle validation studies [8] , [21] , [23] .…”

Section: Discussionsupporting

confidence: 81%

See 1 more Smart Citation

Benchmarking daily adaptation using fully automated radiotherapy treatment plan optimization for rectal cancer

Jagt

Janssen

Betgen

et al. 2022

Physics and Imaging in Radiation Oncology

View full text Add to dashboard Cite

“…Similar differences, i.e. slightly higher target coverages and lower OAR doses, were also observed in mCycle validation studies [8] , [21] , [23] .…”

Section: Discussionsupporting

confidence: 81%

“…While no fully automated treatment planning is yet available for clinical use on the MR-Linac, the vendor Elekta AB has developed a feature to allow autoplanning in a research setting [8] , [21] , [23] , called mCycle.…”

Section: Methods/materialsmentioning

confidence: 99%

Benchmarking daily adaptation using fully automated radiotherapy treatment plan optimization for rectal cancer

Jagt

Janssen

Betgen

et al. 2022

Physics and Imaging in Radiation Oncology

View full text Add to dashboard Cite

“…Over the past decade several such systems have been proposed, e.g. knowledge-based planning (KBP), multi-criteria optimization (MCO), template-based approaches and particle swarm optimization [1] , [2] , [3] , [4] , [5] , [6] , [7] . All of these tend to reduce the inter-planner variability, decrease the time spent on the optimization procedure and improve the plan quality.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of an automated template-based treatment planning system for radiotherapy of anal, rectal and prostate cancer

Calmels

Sibolt

Åström

et al. 2022

Technical Innovations & Patient Support in Radiation Oncolo

View full text Add to dashboard Cite

“…A completely new code has been written to embed this approach in the Monaco environment with a different mathematical solver, a different patient model, the typical Monaco cost functions, and a Monte Carlo Algorithm (XVMC) ( 8 ). The published experiences are mainly focused on iCycle application in several anatomic sites, while applications of the novel mCycle are reported only for head and neck, prostate and rectal cancer volumetric-modulated arc therapy (VMAT) treatment planning ( 8 , 9 ), and prostate treatment on an MR-Linac ( 10 ). This is the first feasibility study of mCycle implementation for cervical cancer treatment.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Automated Planning for Prostate Stereotactic Body Radiation Therapy on the 1.5 T MR-Linac

Cited by 20 publications

References 24 publications

Benchmarking daily adaptation using fully automated radiotherapy treatment plan optimization for rectal cancer

Benchmarking daily adaptation using fully automated radiotherapy treatment plan optimization for rectal cancer

Evaluation of an automated template-based treatment planning system for radiotherapy of anal, rectal and prostate cancer

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

Contact Info

Product

Resources

About