Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-27T11:40:32.207Z Has data issue: false hasContentIssue false
  • English
  • Français

Dosimetric comparison of RapidPlan and manually optimised volumetric modulated arc therapy plans in prostate cancer

Published online by Cambridge University Press:  20 May 2020

Loyce M. H. Chua Open the ORCID record for Loyce M. H. Chua [Opens in a new window] ,
Eric P. P. Pang Open the ORCID record for Eric P. P. Pang [Opens in a new window] ,
Zubin Master Open the ORCID record for Zubin Master [Opens in a new window] ,
Rehena Sultana Open the ORCID record for Rehena Sultana [Opens in a new window] ,
Jeffrey K. L. Tuan Open the ORCID record for Jeffrey K. L. Tuan [Opens in a new window]  and
Christopher M. Bragg
Loyce M. H. Chua*
Affiliation:
Division of Radiation Oncology, National Cancer Centre Singapore, Singapore Faculty of Health and Wellbeing, Sheffield Hallam University, Sheffield, UK
Eric P. P. Pang
Affiliation:
Division of Radiation Oncology, National Cancer Centre Singapore, Singapore
Zubin Master
Affiliation:
Division of Radiation Oncology, National Cancer Centre Singapore, Singapore
Rehena Sultana
Affiliation:
Duke-NUS Medical School, Singapore
Jeffrey K. L. Tuan
Affiliation:
Division of Radiation Oncology, National Cancer Centre Singapore, Singapore Duke-NUS Medical School, Singapore
Christopher M. Bragg
Affiliation:
Faculty of Health and Wellbeing, Sheffield Hallam University, Sheffield, UK
*
Author for correspondence: Loyce M. H. Chua, Division of Radiation Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, Singapore169610, Singapore. Tel: +65 81686568. Fax: +65 62228675. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Purpose:

The aim of this study was to evaluate whether RapidPlan (RP) could generate clinically acceptable prostate volumetric modulated arc therapy (VMAT) plans.

Methods:

The in-house RP model was used to generate VMAT plans for 50 previously treated prostate cancer patients, with no additional optimisation being performed. The VMAT plans that were generated using the RP model were compared with the patients’ previous, manually optimised clinical plans (MP), none of which had been used for the development of the in-house RP prostate model. Differences between RP and MP in planning target volume (PTV) doses, organs at risk (OAR) sparing, monitor units (MU) and planning time required to produce treatment plans were analysed. Assessment of PTV doses was based on the conformation number (CN), homogeneity index (HI), D2%, D99% and the mean dose of the PTV. The OAR doses evaluated were the rectal V50 Gy, V65 Gy, V70 Gy and the mean dose, the bladder V65 Gy, V70 Gy and the mean dose, and the mean dose to both femurs.

Results:

D99% and mean dose of the PTV were lower for RP than for MP (p = 0·006 and p = 0·040, respectively).V50 Gy, V65 Gy and the mean dose to rectum were lower in RP than in MP (p < 0·001). V65 Gy, V70 Gy and the mean dose to bladder were lower in RP than in MP (p < 0·001). RP had enhanced the sparing of both femurs (p < 0·001) and significantly reduced the planning time to less than 5% of the time taken with MP. MU in RP was significantly higher than MP by an average of 52·5 MU (p < 0·001) and 46 out of the 50 RP plans were approved by the radiation oncologist.

Conclusion:

This study has demonstrated that VMAT plans generated using an in-house RP prostate model in a single optimisation for prostate patients were clinically acceptable with comparable or better plan quality compared to MP. RP can add value and improve treatment planning efficiency in a high-throughput radiotherapy department through reduced plan optimisation time while maintaining consistency in the plan quality.

Keywords

dosimetryprostate VMATradiotherapy treatment planningRapidPlan
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 20 , Issue 3 , September 2021 , pp. 257 - 264
Copyright
© The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

(NRDO) NRDO. Singapore Cancer Registry, Annual Registry Report: Trends in Cancer Incidence in Singapore 2011–2015. Retrieved from https://www.nrdo.gov.sg2017. Accessed on 31 December 2017.Google Scholar
Otto, K. Volumetric modulated arc therapy: IMRT in a single gantry arc. Med Phys 2007; 35:310–317.CrossRefGoogle Scholar
Popescu, C, Olivotto, I, Beckham, W et al. Volumetric modulated arc therapy improves dosimetry and reduces treatment time compared to conventional intensity-modulated radiotherapy for locoregional radiotherapy of left-sided breast cancer and internal mammary nodes. Int J Radiat Oncol Biol Phys 2010; 76:287–295.CrossRefGoogle ScholarPubMed
Chung, H, Lee, B, Park, E, Lu, J, Xia, P. Can all centers plan intensity-modulated radiotherapy (IMRT) effectively? An external audit of dosimetric comparisons between three-dimensional conformal radiotherapy and IMRT for adjuvant chemoradiation for gastric cancer. Int J Radiat Oncol Biol Phys 2008; 71:1167–1174.CrossRefGoogle ScholarPubMed
Williams, M, Bailey, M, Forstner, D, Metcalfe, P. Multicentre quality assurance of intensity-modulated radiation therapy plans: a precursor to clinical trials. Australas Radiol 2007; 51:472–479.CrossRefGoogle ScholarPubMed
Das, I, Cheng, C, Chopra, K, Mitra, R, Srivastava, S, Glatstein, E. Intensity-modulated radiation therapy dose prescription, recording, and delivery: patterns of variability among institutions and treatment planning systems. J Natl Cancer Inst 2008; 100:300–307.CrossRefGoogle ScholarPubMed
Nelms, B, Robinson, G, Markham, J et al. Variation in external beam treatment plan quality: an inter-institutional study of planners and planning systems. Pract Radiat Oncol 2012; 2:296–305.CrossRefGoogle ScholarPubMed
Tol, J, Delaney, A, Dahele, M, Slotman, B, Verbakel, W. Evaluation of a knowledge-based planning solution for head and neck cancer. Int J Radiat Oncol Biol Phys 2015; 91:612–620.CrossRefGoogle ScholarPubMed
Ma, C, Luo, J, Zhang, Z, Ma, C. Knowledge-based intensity-modulated radiotherapy plans for cervical cancer with overlap volume of target and organs at risk. Precis Radiat Oncol 2018; 2:21–27.CrossRefGoogle Scholar
Schreibman, E, Fox, T. Prior-knowledge treatment planning for volumetric arc therapy using feature-based database mining. J Appl Clin Med Phys 2014; 15:19–27.CrossRefGoogle Scholar
Voet, P, Dirkx, M, Breedveld, S, Al-Mamgani, A, Incrocci, L, Heijmen, B. Fully automated volumetric modulated arc therapy plan generation for prostate cancer patients. Int J Radiat Oncol Biol Phys 2014; 88:1175–1179.CrossRefGoogle ScholarPubMed
Craft, D L, Hong, T S, Shih, H A, Bortfeld, T R. Improved planning time and plan quality through multicriteria optimisation for intensity-modulated radiotherapy. Int J Radiat Oncol Biol Phys 2012; 82: e90.CrossRefGoogle Scholar
Voet, P, Dirkx, M, Breedveld, S, Fransen, D, Levendag, P, Heijmen, B. Toward fully automated multicriterial plan generation: a prospective clinical study. Int J Radiat Oncol Biol Phys 2013; 85:866–872.CrossRefGoogle ScholarPubMed
Lu, R, Radke, R, Happersett, L et al. Reduced-order parameter optimisation for simplifying prostate IMRT planning. Phys Med Biol 2007; 52:849–870.CrossRefGoogle Scholar
Quan, E, Chang, J, Liao, Z et al. Automated volumetric modulated arc therapy treatment planning for stage III lung cancer: how does it compare with intensity-modulated radio therapy? Int J Radiat Oncol Biol Phys 2012; 84(1): e69–e76.CrossRefGoogle ScholarPubMed
Zhang, X, Li, X, Quan, E, Pan, X, Li, Y. A methodology for automatic intensity-modulated radiation treatment planning for lung cancer. Phys Med Biol 2011; 56:3873–3893.CrossRefGoogle ScholarPubMed
Chanyavanich, V, Das, S K, Lee, W R, Lo, J Y. Knowledge-based IMRT treatment planning for prostate cancer. Med Phys 2011; 38:2515–2522.CrossRefGoogle ScholarPubMed
Wu, B, McNutt, T, Zahurak, M et al. Fully automated simultaneous integrated boosted–intensity modulated radiation therapy treatment planning is feasible for head-and-neck cancer: a prospective clinical study. Int J Radiat Oncol Biol Phys 2012; 84: e653.CrossRefGoogle ScholarPubMed
Appenzoller, L M, Michalski, J M, Thorstad, W L, Mutic, S, Moore, K L. Predicting dose-volume histograms for organs-at-risk in IMRT planning. Med Phys 2012; 39:7446–7441.CrossRefGoogle ScholarPubMed
Shiraishi, S, Tan, J, Olsen, L A, Moore, K L. Knowledge-based prediction of plan quality metrics in intracranial stereotactic radiosurgery. Med Phys 2015; 42:908–917.CrossRefGoogle ScholarPubMed
Good, D, Lo, J, Lee, W R, Wu, Q J, Yin, F, Das, S K. A knowledge-based approach to improving and homogenising intensity modulated radiation therapy planning quality among treatment centers: an example application to prostate cancer planning. Int J Radiat Oncol Biol Phys 2013; 87:176–181.CrossRefGoogle Scholar
Moore, K, Brame, R, Low, D, Mutic, S. Experience-based quality control of clinical intensity-modulated radiotherapy planning. Int J Radiat Oncol Biol Phys 2011; 81:545–551.CrossRefGoogle ScholarPubMed
Varian Medical Systems, Inc. Eclipse Photon And Electron Instructions For Use. Palo Alto, CA: Author, 2014.Google Scholar
Fogliata, A, Belosi, F, Clivio, A et al. On the pre-clinical validation of a commercial model-based optimisation engine: application to volumetric modulated arc therapy for patients with lung or prostate cancer. Radiother Oncol 2014; 113:385–391.CrossRefGoogle ScholarPubMed
Fogliata, A, Wang, P, Belosi, F et al. Assessment of a model based optimisation engine for volumetric modulated arc therapy for patients with advanced hepatocellular cancer. Radiat Oncol 2014; 9:236.CrossRefGoogle Scholar
Fogliata, A, Nicolini, G, Clivio, A et al. A broad scope knowledge based model for optimisation of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers. Radiat Oncol 2015; 10:220.CrossRefGoogle ScholarPubMed
Schubert, C, Waletzko, O, Weiss, C et al. Intercenter validation of a knowledge based model for automated planning of volumetric modulated arc therapy for prostate cancer. The experience of the German RapidPlan Consortium. PLoS One 2017; 12: e0178034.CrossRefGoogle ScholarPubMed
RTOG 0924 Protocol - Androgen Deprivation Therapy and Radiation Therapy in treating patients with prostate cancer. Clinicaltrials.gov Identifier: NCT01368588. Retrieved from https://clinicaltrials.gov/ct2/show/NCT01368588. Accessed on 25th November 2019.Google Scholar
Lawton, C. Michalski, J, El-Naqa, I et al. RTOG GU radiation oncology specialists reach consensus on pelvic lymph node volumes for high-risk prostate cancer. Int J Radiat Oncol Biol Phys 2009; 74:383–387.CrossRefGoogle ScholarPubMed
Wu, H, Jiang, F, Yue, H, Li, S, Zhang, Y. A dosimetric evaluation of knowledge-based VMAT planning with simultaneous integrated boosting for rectal cancer patients. J Appl Clin Med Phys 2016; 17:78–85.CrossRefGoogle ScholarPubMed
Kataria, T, Sharma, K, Subramani, V, Karrthick, K, Bisht, S. Homogeneity Index: an objective tool for assessment of conformal radiation treatments. J Med Phys 2012; 37:207–213.CrossRefGoogle ScholarPubMed
van’t Riet, A, Mak, A, Moerland, M, Elders, L, van der Zee, W. A conformation number to quantify the degree of conformality in brachytherapy and external beam irradiation: application to the prostate. Int J Radiat Oncol Biol Phys 1997; 37:731–736.CrossRefGoogle ScholarPubMed
Hussein, M, South, C, Barry, M et al. Clinical validation and benchmarking of knowledge-based IMRT and VMAT treatment planning in pelvic anatomy. Radiother Oncol 2016; 120:473–479.CrossRefGoogle ScholarPubMed
Kubo, K, Monzen, H, Ishii, K et al. Dosimetric comparison of RapidPlan and manually optimised plans in volumetric modulated arc therapy for prostate cancer. Phys Med 2017; 44:199–204.CrossRefGoogle Scholar
Cagni, E, Botti, A, Micera, R et al. Knowledge-based treatment planning: an inter-technique and inter-system feasibility study for prostate cancer. Phys Med 2017; 36:38–45.CrossRefGoogle ScholarPubMed
Oliver, M, Ansbacher, W, Beckham, W. Comparing planning time, delivery time and plan quality for IMRT, RapidArc and tomotherapy. J Appl Clin Med Phys 2009; 10:117–131.CrossRefGoogle ScholarPubMed
Ma, C, Huang, F. Assessment of a knowledge-based RapidPlan model for patients with postoperative cervical cancer. Precis Radiat Oncol 2017; 1:102–107.CrossRefGoogle Scholar
Wang, J, Hu, W, Yang, Z et al. Is it possible for knowledge-based planning to improve intensity modulated radiation therapy plan quality for planners with different planning experiences in left-sided breast cancer patients? Radiat Oncol 2017; 12:85.CrossRefGoogle ScholarPubMed