AccScience Publishing / ARNM / Online First / DOI: 10.36922/arnm.2784
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ORIGINAL RESEARCH ARTICLE

Assessing the adequacy of a 5-mm planning target volume margin for 4D-CT scan-based image-guided radiotherapy for locally advanced carcinoma of the lung

Animesh Saha1* Aditi Mishra1 Shreya Manna1 Ajay Banik1 Suchanda Goswami1 Jibak Bhattacharya1 Tanmoy Mukhopadhay1 Prosenjit Soren2 Sayantan Mondal2 Saptaswa Chattopadhyay2 Biplab Sarkar2 Suvra Biswal2 Kiruba George2 Mousin Gazi2 Sandipan Roy Chowdhury2
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1 Department of Radiation Oncology, Apollo Multispeciality Hospitals, Kolkata, West Bengal, India
2 Department of Medical Physics, Apollo Multispeciality Hospitals, Kolkata, West Bengal, India
Submitted: 19 January 2024 | Accepted: 12 March 2024 | Published: 27 March 2024
© 2024 by the Author (s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

In developed nations, 4D-computed tomography (4D-CT)-based image-guided radiotherapy (IGRT) has become the standard for treating lung carcinoma patients, with the primary goal of achieving disease cure. However, its usage in India remains limited. Here, we compared target volume delineation for radical radiation planning in patients with locally advanced lung carcinoma using helical free-breathing CT (FBCT) and 4D-CT. In addition, we assessed the adequacy of a 5-mm planning target volume (PTV) margin with 4D-CT planning. Fifty patients with locally advanced lung cancer were enrolled in the study. Each patient underwent contouring based on 4D-CT to generate an internal target volume, and a 5-mm PTV margin (PTV_4D) was added for radical radiation. Subsequently, each patient underwent two intensity-modulated radiation therapy (IMRT) plans with comparable planning and optimization parameters. One plan was based on the FBCT-based volume (PTV_3D), while the other was based on the 4D-CT-based volume (PTV_4D). PTV, organ at risk (OAR) dose, and PTV coverage by 95% of the prescribed dose (PTVD 95_3D vs. PTVD 95_4D) were compared between the two schemes. Results revealed that 4D-CT-based planning reduced PTV (mean PTV volume: 539 cc vs. 782 cc) and lowered OAR doses (mean lung dose: 13 Gy vs. 15 Gy; mean esophagus dose: 18.5 Gy vs. 21.15 Gy; mean spinal cord max dose: 35.59 Gy vs. 37.39 Gy). At 3 months after treatment imaging, 40% of the patients showed a complete response, 48% showed a partial response, 4% showed stable disease, and 8% showed progressive disease. In conclusion, 4D-CT-based radiation planning for locally advanced lung carcinoma with a reduced PTV margin of 5 mm can dramatically decrease the PTV and OAR doses without sacrificing PTV coverage compared to FBCT-based planning. However, daily online image guidance or at least a well-defined offline image guidance protocol is recommended when employing such a small PTV margin.

Keywords
Lung cancer
4D-CT
Image-guided radiotherapy
Planning target volume
Funding
None.
References
  1. Bradley JD, Paulus R, Komaki R, et al. Standard-dose versus high-dose conformal radiotherapy with concurrent and consolidation carboplatin plus paclitaxel with or without cetuximab for patients with stage IIIA or IIIB non-small-cell lung cancer (RTOG 0617): A randomised, two-by-two factorial phase 3 study. Lancet Oncol. 2015;16(2):187-199. doi: 10.1016/S1470-2045(14)71207-0

 

  1. Curran WJ Jr., Paulus R, Langer CJ, et al. Sequential vs. Concurrent chemoradiation for stage III non-small cell lung cancer: Randomized phase III trial RTOG 9410. J Natl Cancer Inst. 2011;103(19):1452-1460. doi: 10.1093/jnci/djr325

 

  1. Fournel P, Robinet G, Thomas P, et al. Randomized phase III trial of sequential chemoradiotherapy compared with concurrent chemoradiotherapy in locally advanced non-small-cell lung cancer: Groupe Lyon-Saint- Etienne d’Oncologie Thoracique-Groupe Français de Pneumo-Cancérologie NPC 95-01 study. J Clin Oncol. 2005;23(25):5910-5917. doi: 10.1200/JCO.2005.03.070

 

  1. Ashworth A, Rodrigues G, Boldt G, Palma D. Is there an oligometastatic state in non-small cell lung cancer? A systematic review of the literature. Lung Cancer. 2013;82(2):197-203. doi: 10.1016/j.lungcan.2013.07.026

 

  1. Din OS, Harden SV, Hudson E, et al. Accelerated hypo-fractionated radiotherapy for non small cell lung cancer: Results from 4 UK centres. Radiother Oncol. 2013;109(1):8-12. doi: 10.1016/j.radonc.2013.07.014

 

  1. Faivre-Finn C, Snee M, Ashcroft L, et al. Concurrent once-daily versus twice-daily chemoradiotherapy in patients with limited-stage small-cell lung cancer (CONVERT): An open-label, phase 3, randomised, superiority trial. Lancet Oncol. 2017;18(8):1116-1125. doi: 10.1016/S1470-2045(17)30318-2

 

  1. Le Chevalier T, Arriagada R, Tarayre M, et al. Significant effect of adjuvant chemotherapy on survival in locally advanced non-small-cell lung carcinoma. J Natl Cancer Inst. 1992;84(1):58. doi: 10.1093/jnci/84.1.58

 

  1. ICRU. ICRU Report 62: Prescribing, Recording and Reporting Photon Beam Therapy (Supplement to ICRU 50). Available from: https://www.icru.org/report/prescribing-recording-and-reporting-photon-beam-therapy-report-62

 

  1. Chen QS, Weinhous MS, Deibel FC, Ciezki JP, Macklis RM. Fluoroscopic study of tumor motion due to breathing: Facilitating precise radiation therapy for lung cancer patients. Med Phys. 2001;28(9):1850-1856. doi: 10.1118/1.1398037

 

  1. Keall PJ, Mageras GS, Balter JM, et al. The management of respiratory motion in radiation oncology report of AAPM task group 76. Med Phys. 2006;33(10):3874-3900. doi: 10.1118/1.2349696

 

  1. Plathow C, Ley S, Fink C, et al. Analysis of intrathoracic tumor mobility during whole breathing cycle by dynamic MRI. Int J Radiat Oncol Biol Phys. 2004;59(4):952-959. doi: 10.1016/j.ijrobp.2003.12.035

 

  1. Ahmed N, Venkataraman S, Johnson K, Sutherland K, Loewen SK. Does motion assessment with 4-dimensional computed tomographic imaging for non-small cell lung cancer radiotherapy improve target volume coverage? Clin Med Insights Oncol. 2017;11:1-7. doi: 10.1177/1179554917698461

 

  1. De Ruysscher D, Faivre-Finn C, Nestle U, et al. European organisation for research and treatment of cancer recommendations for planning and delivery of high-dose, high-precision radiotherapy for lung cancer. J Clin Oncol. 2010;28(36):5301-5310. doi: 10.1200/JCO.2010.30.3271

 

  1. Rietzel E, Chen GT, Choi NC, Willet CG. Four-dimensional image-based treatment planning: Target volume segmentation and dose calculation in the presence of respiratory motion. Int J Radiat Oncol Biol Phys. 2005;61(5):1535-1550. doi: 10.1016/j.ijrobp.2004.11.037

 

  1. Steiner E, Shieh CC, Caillet V, et al. Both four-dimensional computed tomography and four-dimensional cone beam computed tomography under-predict lung target motion during radiotherapy. Radiother Oncol. 2019;135:65-73. doi: 10.1016/j.radonc.2019.02.019

 

  1. Glide-Hurst CK, Schwenker Smith M, Ajlouni M, Indrin J, Chetty IJ. Evaluation of two synchronized external surrogates for 4D CT sorting. J Appl Clin Med Phys. 2013;14(6):4301. doi: 10.1120/jacmp.v14i6.4301

 

  1. Kong FM, Ritter T, Quint DJ, et al. Consideration of dose limits for organs at risk of thoracic radiotherapy: Atlas for lung, proximal bronchial tree, esophagus, spinal cord, ribs, and brachial plexus. Int J Radiat Oncol Biol Phys. 2011;81(5):1442-1457. doi: 10.1016/j.ijrobp.2010.07.1977

 

  1. Grills IS, Fitch DL, Goldstein NS, et al. Clinicopathologic analysis of microscopic extension in lung adenocarcinoma: Defining clinical target volume for radiotherapy. Int J Radiat Oncol Biol Phys. 2007;69(2):334-341. doi: 10.1016/j.ijrobp.2007.03.023

 

  1. Yuan S, Meng X, Yu J, et al. Determining optimal clinical target volume margins on the basis of microscopic extracapsular extension of metastatic nodes in patients with non-small-cell lung cancer. Int J Radiat Oncol Biol Phys. 2007;67(3):727-734. doi: 10.1016/j.ijrobp.2006.08.057

 

  1. Mori S, Kanematsu N, Mizuno H, Sunaoka M, Endo M. Physical evaluation of CT scan methods for radiation therapy planning: Comparison of fast, slow and gating scan using the 256-detector row CT scanner. Phys Med Biol. 2006;51(3):587-600. doi: 10.1088/0031-9155/51/3/008

 

  1. Pierce G. Assessing and Improving 4D-CT Imaging for Radiotherapy Applications Western Thesis and Dissertation Repository; 2011.

 

  1. Alasti H, Cho YB, Vandermeer AD, et al. A novel four-dimensional radiotherapy method for lung cancer: Imaging, treatment planning and delivery. Phys Med Biol. 2006;51(12):3251-3267. doi: 10.1088/0031-9155/51/12/017

 

  1. Ju X, Li M, Zhou Z, et al. 4D-CT-based plan target volume (PTV) definition compared with conventional PTV definition using general margin in radiotherapy for lung cancer. Zhonghua Zhong Liu Za Zhi. 2014;36(1):34-38.

 

  1. Cole AJ, O’Hare JM, McMahon SJ, et al. Investigating the potential impact of four-dimensional computed tomography (4DCT) on toxicity, outcomes and dose escalation for radical lung cancer radiotherapy. Clin Oncol (R Coll Radiol). 2014;26(3):142-150. doi: 10.1016/j.clon.2013.11.024

 

  1. Kong F, Hu C, Machtay M, et al. OA02.04 randomized phase II trial (RTOG1106) on midtreatment PET/CT guided adaptive radiotherapy in locally advanced non-small cell lung cancer. J Thorac Oncol. 2021;16(3):S104-S105. doi: 10.1016/j.jtho.2021.01.277

 

  1. Van Diessen J, De Ruysscher D, Sonke JJ, et al. The acute and late toxicity results of a randomized phase II dose-escalation trial in non-small cell lung cancer (PET-boost trial). Radiother Oncol. 2019;131:166-173. doi: 10.1016/j.radonc.2018.09.019

 

  1. Van Herk M, Remeijer P, Rasch C, Lebesque JV. The probability of correct target dosage: Dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys. 2000;47(4):1121-1135. doi: 10.1016/s0360-3016(00)00518-6

 

  1. Stroom JC, Heijmen BJ. Geometrical uncertainties, radiotherapy planning margins, and the ICRU-62 report. Radiother Oncol. 2002;64(1):75-83. doi: 10.1016/s0167-8140(02)00140-8

 

  1. Ecclestone G, Heath E, Bissonnette JP. Poster-thur Eve-62: Assessing the clinical application of the van Herk margin formula for lung radiotherapy. Med Phys. 2012;39(7Part3):4636. doi: 10.1118/1.4740170

 

  1. Jasper K, Liu B, Olson R, Matthews Q. Evidence-based planning target volume margin reduction for modern lung stereotactic ablative radiation therapy using deformable registration. Adv Radiat Oncol. 2021;6(6):100750. doi: 10.1016/j.adro.2021.100750

 

  1. Liang Z, Yang J, Liu H, et al. Real-time tumor motion monitoring and PTV margin determination in lung SBRT treatment. Acta Oncol. 2019;58(12):1786-1789. doi: 10.1080/0284186X.2019.1648862

 

  1. Murray L, Ramasamy S, Lilley J, et al. Stereotactic ablative radiotherapy (SABR) in patients with medically inoperable peripheral early stage lung cancer: Outcomes for the first UK SABR cohort. Clin Oncol (R Coll Radiol). 2016;28(1):4-12. doi: 10.1016/j.clon.2015.09.007

 

  1. SABR UK Consortium. Stereotactic Ablative Body Radiation Therapy (SABR): A Resource. United Kingdom: SABR UK Consortium; 2014.

 

  1. Yamamoto T, Langner U, Loo BW Jr., Shen J, Keall PJ. Retrospective analysis of artifacts in four-dimensional CT images of 50 abdominal and thoracic radiotherapy patients. Int J Radiat Oncol Biol Phys. 2008;72(4):1250-1258. doi: 10.1016/j.ijrobp.2008.06.1937

 

  1. Sentker T, Schmidt V, Ozga AK, et al. 4D CT image artifacts affect local control in SBRT of lung and liver metastases. Radiother Oncol. 2020;148:229-234. doi: 10.1016/j.radonc.2020.04.006

 

  1. Jiang SB, Wolfgang J, Mageras GS. Quality assurance challenges for motion-adaptive radiation therapy: Gating, breath holding, and four-dimensional computed tomography. Int J Radiat Oncol Biol Phys. 2008;71(1 Suppl):S103-S107. doi: 10.1016/j.ijrobp.2007.07.2386
Conflict of interest
The authors declare that they have no competing interests.
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Advances in Radiotherapy & Nuclear Medicine, Electronic ISSN: 2972-4392 Published by AccScience Publishing