Skip to main content
Log in

Improving normal tissue sparing using scripting in endometrial cancer radiation therapy planning

  • Original Article
  • Published:
Radiation and Environmental Biophysics Aims and scope Submit manuscript

Abstract

The aim of this study was to improve the protection of organs at risk (OARs), decrease the total planning time and maintain sufficient target doses using scripting endometrial cancer external beam radiation therapy (EBRT) planning. Computed tomography (CT) data of 14 endometrial cancer patients were included in this study. Manual and automatic planning with scripting were performed for each CT. Scripts were created in the RayStation™ (RaySearch Laboratories AB, Stockholm, Sweden) planning system using a Python code. In scripting, seven additional contours were automatically created to reduce the OAR doses. The scripted and manual plans were compared to each other in terms of planning time, dose-volume histogram (DVH) parameters, and total monitor unit (MU) values. While the mean total planning time for manual planning was 368 ± 8 s, it was only 55 ± 2 s for the automatic planning with scripting (p < 0.001). The mean doses of OARs decreased with automatic planning (p < 0.001). In addition, the maximum doses (D2% and D1%) for bilateral femoral heads and the rectum were significantly reduced. It was observed that the total MU value increased from 1146 ± 126 (manual planning) to 1369 ± 95 (scripted planning). It is concluded that scripted planning has significant time and dosimetric advantages over manual planning for endometrial cancer EBRT planning.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  • ASTEC, T. (2009) Adjuvant external beam radiotherapy in the treatment of endometrial cancer (MRC ASTEC and NCIC CTG EN. 5 randomised trials): pooled trial results, systematic review, and meta-analysis. The Lancet 373(9658):137–146

    Article  Google Scholar 

  • Bai X, Shan G, Chen M, Wang B (2019) Approach and assessment of automated stereotactic radiotherapy planning for early stage non-small-cell lung cancer. Biomed Eng Online 18(1):1–15

    Article  Google Scholar 

  • Bakx N, Bluemink H, Hagelaar E, van der Sangen M, Theuws J, Hurkmans C (2021) Development and evaluation of radiotherapy deep learning dose prediction models for breast cancer. Phys Imaging Radiat Oncol 17:65–70

    Article  Google Scholar 

  • Berry SL, Boczkowski A, Ma R, Mechalakos J, Hunt M (2016) Interobserver variability in radiation therapy plan output: results of a single-institution study. Pract Radiat Oncol 6(6):442–449

    Article  Google Scholar 

  • Bhatla N, Berek JS, Cuello Fredes M, Denny LA, Grenman S, Karunaratne K, Kehoe ST, Konishi I, Olawaiye AB, Prat J (2019) Revised FIGO staging for carcinoma of the cervix uteri. Int J Gynecol Obstet 145(1):129–135

    Article  Google Scholar 

  • Cilla S, Ianiro A, Macchia G, Morganti AG, Valentini V, Deodato F (2019) Automated VMAT treatment planning for complex cancer cases: A Feasibility Study. In: Lhotska L, Sukupova L, Lacković I, Ibbott GS (eds) World congress on medical physics and biomedical engineering 2018. Springer, Springer Singapore, pp 463–467

    Chapter  Google Scholar 

  • Concin N, Matias-Guiu X, Vergote I, Cibula D, Mirza MR, Marnitz S, Ledermann J, Bosse T, Chargari C, Fagotti A (2021) ESGO/ESTRO/ESP guidelines for the management of patients with endometrial carcinoma. Int J Gynecol Cancer 31(1):12–39

    Article  Google Scholar 

  • Guo B, Shah C, Xia P (2019) Automated planning of whole breast irradiation using hybrid IMRT improves efficiency and quality. J Appl Clin Med Phys 20(12):87–96

    Article  Google Scholar 

  • Han EY, Kim G-Y, Rebueno N, Yeboa DN, Briere TM (2019) End-to-end testing of automatic plan optimization using RayStation scripting for hypofractionated multimetastatic brain stereotactic radiosurgery. Med Dosim 44(4):e44–e50

    Article  Google Scholar 

  • Heron D, Gerszten K, Selvaraj R, King G, Sonnik D, Gallion H, Comerci J, Edwards R, Wu A, Andrade R (2003) Conventional 3D conformal versus intensity-modulated radiotherapy for the adjuvant treatment of gynecologic malignancies: a comparative dosimetric study of dose–volume histograms☆. Gynecol Oncol 91(1):39–45

    Article  Google Scholar 

  • Hussein M, Heijmen BJM, Verellen D, Nisbet A (2018) Automation in intensity modulated radiotherapy treatment planning—a review of recent innovations. Br J Radiol 91(1092):20180270

    Article  Google Scholar 

  • Kim H, Kwak J, Jung J, Jeong C, Yoon K, Lee S-W, Ahn SD, Choi EK, Kim SS, Cho B (2018) Automated field-in-field (FIF) plan framework combining scripting application programming Interface and user-executed program for breast forward IMRT. Technol Cancer Res Treat 17:1533033818810391

    Article  Google Scholar 

  • Klopp AH, Yeung AR, Deshmukh S, Gil KM, Wenzel L, Westin SN, Gifford K, Gaffney DK, Small W Jr, Thompson S (2018) Patient-reported toxicity during pelvic intensity-modulated radiation therapy: NRG Oncology–RTOG 1203. J Clin Oncol 36(24):2538

    Article  Google Scholar 

  • Knapp P, Eva B, Reseigh G, Gibbs A, Sim L, Daly T, Cox J, Bernard A (2019) The role of volumetric modulated arc therapy (VMAT) in gynaecological radiation therapy: A dosimetric comparison of intensity modulated radiation therapy versus VMAT. J Med Radiat Sci 66(1):44–53

    Article  Google Scholar 

  • Krayenbuehl J, Zamburlini M, Ghandour S, Pachoud M, Tanadini-Lang S, Tol J, Guckenberger M, Verbakel W (2018) Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer. Radiat Oncol 13(1):1–8

    Google Scholar 

  • Lindsay K, Wheldon E, Deehan C, Wheldon T (2001) Radiation carcinogenesis modelling for risk of treatment-related second tumours following radiotherapy. Br J Radiol 74(882):529–536

    Article  Google Scholar 

  • Martin S, Johnson C, Brophy M, Palma DA, Barron JL, Beauchemin SS, Louie AV, Yu E, Yaremko B, Ahmad B (2015) Impact of target volume segmentation accuracy and variability on treatment planning for 4D-CT-based non-small cell lung cancer radiotherapy. Acta Oncol 54(3):322–332

    Article  Google Scholar 

  • McIntosh C, Conroy L, Tjong MC, Craig T, Bayley A, Catton C, Gospodarowicz M, Helou J, Isfahanian N, Kong V (2021) Clinical integration of machine learning for curative-intent radiation treatment of patients with prostate cancer. Nat Med 27(6):999–1005

    Article  Google Scholar 

  • Mitchell RA, Wai P, Colgan R, Kirby AM, Donovan EM (2017) Improving the efficiency of breast radiotherapy treatment planning using a semi-automated approach. J Appl Clin Med Phys 18(1):18–24

    Google Scholar 

  • Nguyen D, Long T, Jia X, Lu W, Gu X, Iqbal Z, Jiang S (2019) A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning. Sci Rep 9(1):1–10

    Google Scholar 

  • Nguyen, D., X. Jia, D. Sher, M.-H. Lin, Z. Iqbal, H. Liu and S. Jiang (2018). "Three-dimensional radiotherapy dose prediction on head and neck cancer patients with a hierarchically densely connected u-net deep learning architecture." arXiv preprint arXiv:1805.10397.

  • Purdie TG, Dinniwell RE, Letourneau D, Hill C, Sharpe MB (2011) Automated planning of tangential breast intensity-modulated radiotherapy using heuristic optimization. Int J Radiat Oncol Biol Phys 81(2):575–583

    Article  Google Scholar 

  • Shih KK, Milgrom SA, Abu-Rustum NR, Kollmeier MA, Gardner GJ, Tew WP, Barakat RR, Alektiar KM (2013) Postoperative pelvic intensity-modulated radiotherapy in high risk endometrial cancer. Gynecol Oncol 128(3):535–539

    Article  Google Scholar 

  • Small W Jr, Bosch WR, Harkenrider MM, Strauss JB, Abu-Rustum N, Albuquerque KV, Beriwal S, Creutzberg CL, Eifel PJ, Erickson BA (2021) NRG oncology/RTOG consensus guidelines for delineation of clinical target volume for intensity modulated pelvic radiation therapy in postoperative treatment of endometrial and cervical cancer: an update. Int J Radiat Oncol Biol Phys 109(2):413–424

    Article  Google Scholar 

  • Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Ca Cancer J Clin 71(3):209–249

    Article  Google Scholar 

  • Teruel JR, Malin M, Liu EK, McCarthy A, Hu K, Cooper BT, Sulman EP, Silverman JS, Barbee D (2020) Full automation of spinal stereotactic radiosurgery and stereotactic body radiation therapy treatment planning using Varian Eclipse scripting. J Appl Clin Med Phys 21(10):122–131

    Article  Google Scholar 

  • Teruel JR, Taneja S, Galavis PE, Osterman KS, McCarthy A, Malin M, Gerber NK, Hitchen C, Barbee DL (2021) Automatic treatment planning for VMAT-based total body irradiation using Eclipse scripting. J Appl Clin Med Phys 22(3):119–130

    Article  Google Scholar 

  • van Duren-Koopman MJ, Tol JP, Dahele M, Bucko E, Meijnen P, Slotman BJ, Verbakel WF (2018) Personalized automated treatment planning for breast plus locoregional lymph nodes using Hybrid RapidArc. Pract Radiat Oncol 8(5):332–341

    Article  Google Scholar 

  • Wang C, Zhu X, Hong JC, Zheng D (2019) Artificial intelligence in radiotherapy treatment planning: present and future. Technol Cancer Res Treat 18:1533033819873922

    Article  Google Scholar 

  • Xhaferllari I, Wong E, Bzdusek K, Lock M, Chen JZ (2013) Automated IMRT planning with regional optimization using planning scripts. J Appl Clin Med Phys 14(1):176–191

    Article  Google Scholar 

  • Xia W, Han F, Chen J, Miao J, Dai J (2020) Personalized setting of plan parameters using feasibility dose volume histogram for auto-planning in Pinnacle system. J Appl Clin Med Phys 21(7):119–127

    Article  Google Scholar 

  • Yang R, Xu S, Jiang W, Wang J, Xie C (2010) Dosimetric comparison of postoperative whole pelvic radiotherapy for endometrial cancer using three-dimensional conformal radiotherapy, intensity-modulated radiotherapy, and helical tomotherapy. Acta Oncol 49(2):230–236

    Article  Google Scholar 

  • Yang Y, Shao K, Zhang J, Chen M, Chen Y, Shan G (2020) Automatic planning for nasopharyngeal carcinoma based on progressive optimization in raystation treatment planning system. Technol Cancer Res Treat 19:1533033820915710

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

YY designed and performed the experiments, derived the models, and analyzed the data. MG assisted with plan evaluation. YY and SYS wrote the manuscript in consultation with MG and FY.

Corresponding author

Correspondence to Yagiz Yedekci.

Ethics declarations

Competing interests

The authors declare no competing interests.

Conflict of interest

There is no conflict of interest to declare.

Ethical approval

All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The research protocol was approved by the institutional ethics committee of Hacettepe University with the protocol number GO 21/1357.

Informed consent

Informed consent was obtained from all individual patients included in the study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yedekci, Y., Gültekin, M., Sari, S.Y. et al. Improving normal tissue sparing using scripting in endometrial cancer radiation therapy planning. Radiat Environ Biophys 62, 253–260 (2023). https://doi.org/10.1007/s00411-023-01019-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00411-023-01019-2

Keywords

Navigation