Pre-clinical validation of a novel system for fully-automated treatment planning

Rik Bijman; Abdul Wahab Sharfo; Linda Rossi; Sebastiaan Breedveld; Ben Heijmen

doi:10.1016/j.radonc.2021.03.003

Pre-clinical validation of a novel system for fully-automated treatment planning

Rik Bijman^*, Abdul Wahab Sharfo, Linda Rossi, Sebastiaan Breedveld, Ben Heijmen

^*Corresponding author for this work

Radiotherapy

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

Introduction: Many approaches for automated treatment planning (autoplanning) have been proposed and investigated. Autoplanning can enhance plan quality compared to ‘manual’ trial-and-error planning, and decrease routine planning workload. A few approaches have been implemented in commercial treatment planning systems (TPSs). We performed a pre-clinical validation of a new system (‘NovelATP’) that is based on fully-automated multi-criterial optimization (MCO). The aim of NovelATP is to automatically generate for each patient a single high-quality, Pareto-optimal plan without manual Pareto navigation. Material and methods: Validation was performed by generating VMAT/IMRT plans for conventional treatment of prostate cancer (101 pts), prostate SBRT (20 pts), bilateral head-and-neck cancer (50 pts) and rectal cancer treated at an MR-Linac (23 pts). NovelATP autoplans were compared to plans that were generated with our in-house autoplanning system. In many previous validation studies, the latter system consistently showed enhanced plan quality when compared to manual planning. Results: Dosimetrical differences between NovelATP and benchmark plans were on average small and presumably not clinically relevant, pointing at high NovelATP dosimetric plan quality. MUs were 11–19% higher with NovelATP. NovelATP delivery times were up to 12% longer. Overall, there was a slight disadvantage for NovelATP regarding gamma analyses. Calculation times for NovelATP plans were between 29 and 151 min with no overall differences with the benchmark plans. Conclusion: The new autoplanning system was able to produce high-quality plans for four highly different planning protocols/treatment sites with a total of 194 patients investigated.

Original language	English
Pages (from-to)	253-261
Number of pages	9
Journal	Radiotherapy and Oncology
Volume	158
DOIs	https://doi.org/10.1016/j.radonc.2021.03.003
Publication status	Published - 1 May 2021

Bibliographical note

Acknowledgements:
The authors want to thank Elekta AB for NovelATP training and assistance. Erik Loef (Erasmus MC) for his assistance on performing the QA measurements. The NKI in Amsterdam is acknowledged for providing MRL data.

Publisher Copyright: © 2021 The Authors

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10.1016/j.radonc.2021.03.003

PIIS0167814021061181Final published version, 2.74 MBLicence: CC BY

Cite this

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title = "Pre-clinical validation of a novel system for fully-automated treatment planning",

abstract = "Introduction: Many approaches for automated treatment planning (autoplanning) have been proposed and investigated. Autoplanning can enhance plan quality compared to {\textquoteleft}manual{\textquoteright} trial-and-error planning, and decrease routine planning workload. A few approaches have been implemented in commercial treatment planning systems (TPSs). We performed a pre-clinical validation of a new system ({\textquoteleft}NovelATP{\textquoteright}) that is based on fully-automated multi-criterial optimization (MCO). The aim of NovelATP is to automatically generate for each patient a single high-quality, Pareto-optimal plan without manual Pareto navigation. Material and methods: Validation was performed by generating VMAT/IMRT plans for conventional treatment of prostate cancer (101 pts), prostate SBRT (20 pts), bilateral head-and-neck cancer (50 pts) and rectal cancer treated at an MR-Linac (23 pts). NovelATP autoplans were compared to plans that were generated with our in-house autoplanning system. In many previous validation studies, the latter system consistently showed enhanced plan quality when compared to manual planning. Results: Dosimetrical differences between NovelATP and benchmark plans were on average small and presumably not clinically relevant, pointing at high NovelATP dosimetric plan quality. MUs were 11–19% higher with NovelATP. NovelATP delivery times were up to 12% longer. Overall, there was a slight disadvantage for NovelATP regarding gamma analyses. Calculation times for NovelATP plans were between 29 and 151 min with no overall differences with the benchmark plans. Conclusion: The new autoplanning system was able to produce high-quality plans for four highly different planning protocols/treatment sites with a total of 194 patients investigated.",

author = "Rik Bijman and Sharfo, {Abdul Wahab} and Linda Rossi and Sebastiaan Breedveld and Ben Heijmen",

note = "Acknowledgements: The authors want to thank Elekta AB for NovelATP training and assistance. Erik Loef (Erasmus MC) for his assistance on performing the QA measurements. The NKI in Amsterdam is acknowledged for providing MRL data. Publisher Copyright: {\textcopyright} 2021 The Authors",

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doi = "10.1016/j.radonc.2021.03.003",

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T1 - Pre-clinical validation of a novel system for fully-automated treatment planning

AU - Bijman, Rik

AU - Sharfo, Abdul Wahab

AU - Rossi, Linda

AU - Breedveld, Sebastiaan

AU - Heijmen, Ben

N1 - Acknowledgements: The authors want to thank Elekta AB for NovelATP training and assistance. Erik Loef (Erasmus MC) for his assistance on performing the QA measurements. The NKI in Amsterdam is acknowledged for providing MRL data. Publisher Copyright: © 2021 The Authors

PY - 2021/5/1

Y1 - 2021/5/1

N2 - Introduction: Many approaches for automated treatment planning (autoplanning) have been proposed and investigated. Autoplanning can enhance plan quality compared to ‘manual’ trial-and-error planning, and decrease routine planning workload. A few approaches have been implemented in commercial treatment planning systems (TPSs). We performed a pre-clinical validation of a new system (‘NovelATP’) that is based on fully-automated multi-criterial optimization (MCO). The aim of NovelATP is to automatically generate for each patient a single high-quality, Pareto-optimal plan without manual Pareto navigation. Material and methods: Validation was performed by generating VMAT/IMRT plans for conventional treatment of prostate cancer (101 pts), prostate SBRT (20 pts), bilateral head-and-neck cancer (50 pts) and rectal cancer treated at an MR-Linac (23 pts). NovelATP autoplans were compared to plans that were generated with our in-house autoplanning system. In many previous validation studies, the latter system consistently showed enhanced plan quality when compared to manual planning. Results: Dosimetrical differences between NovelATP and benchmark plans were on average small and presumably not clinically relevant, pointing at high NovelATP dosimetric plan quality. MUs were 11–19% higher with NovelATP. NovelATP delivery times were up to 12% longer. Overall, there was a slight disadvantage for NovelATP regarding gamma analyses. Calculation times for NovelATP plans were between 29 and 151 min with no overall differences with the benchmark plans. Conclusion: The new autoplanning system was able to produce high-quality plans for four highly different planning protocols/treatment sites with a total of 194 patients investigated.

AB - Introduction: Many approaches for automated treatment planning (autoplanning) have been proposed and investigated. Autoplanning can enhance plan quality compared to ‘manual’ trial-and-error planning, and decrease routine planning workload. A few approaches have been implemented in commercial treatment planning systems (TPSs). We performed a pre-clinical validation of a new system (‘NovelATP’) that is based on fully-automated multi-criterial optimization (MCO). The aim of NovelATP is to automatically generate for each patient a single high-quality, Pareto-optimal plan without manual Pareto navigation. Material and methods: Validation was performed by generating VMAT/IMRT plans for conventional treatment of prostate cancer (101 pts), prostate SBRT (20 pts), bilateral head-and-neck cancer (50 pts) and rectal cancer treated at an MR-Linac (23 pts). NovelATP autoplans were compared to plans that were generated with our in-house autoplanning system. In many previous validation studies, the latter system consistently showed enhanced plan quality when compared to manual planning. Results: Dosimetrical differences between NovelATP and benchmark plans were on average small and presumably not clinically relevant, pointing at high NovelATP dosimetric plan quality. MUs were 11–19% higher with NovelATP. NovelATP delivery times were up to 12% longer. Overall, there was a slight disadvantage for NovelATP regarding gamma analyses. Calculation times for NovelATP plans were between 29 and 151 min with no overall differences with the benchmark plans. Conclusion: The new autoplanning system was able to produce high-quality plans for four highly different planning protocols/treatment sites with a total of 194 patients investigated.

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DO - 10.1016/j.radonc.2021.03.003

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AN - SCOPUS:85103033174

SN - 0167-8140

VL - 158

SP - 253

EP - 261

JO - Radiotherapy and Oncology

JF - Radiotherapy and Oncology

ER -

Pre-clinical validation of a novel system for fully-automated treatment planning

Abstract

Bibliographical note

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