Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-24T15:42:23.465Z Has data issue: false hasContentIssue false
  • English
  • Français

Study of normal tissue dosimetric benefit using asymmetric margin-based biological fuzzy decision making: volumetric modulated arc therapy of prostate cancer

Published online by Cambridge University Press:  04 November 2020

Santosh Kumar Patnaikuni ,
Sapan Mohan Saini Open the ORCID record for Sapan Mohan Saini [Opens in a new window] ,
Rakesh Mohan Chandola ,
Pradeep Chandrakar ,
Rajeev Jain  and
Vivek Chaudhary
Santosh Kumar Patnaikuni
Affiliation:
Department of Physics, National Institute of Technology, Raipur, Chhattisgarh, India Department of Radiotherapy, Pt. JNM Medical College, Raipur, Chhattisgarh, India
Sapan Mohan Saini*
Affiliation:
Department of Physics, National Institute of Technology, Raipur, Chhattisgarh, India
Rakesh Mohan Chandola
Affiliation:
Department of Radiotherapy, Pt. JNM Medical College, Raipur, Chhattisgarh, India
Pradeep Chandrakar
Affiliation:
Department of Radiotherapy, Pt. JNM Medical College, Raipur, Chhattisgarh, India
Rajeev Jain
Affiliation:
Department of Radiotherapy, Pt. JNM Medical College, Raipur, Chhattisgarh, India
Vivek Chaudhary
Affiliation:
Department of Radiotherapy, Pt. JNM Medical College, Raipur, Chhattisgarh, India
*
Address for correspondence: Dr. Sapan Mohan Saini, Associate Professor, Department of Physics, National Institute of Technology, Raipur492010, Chhattisgarh, India. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Aim:

Radiation therapy has historically used margins for target volume to ensure dosimetric planning criteria. The size of margin for a given treatment site is still uncertain particularly for moving targets along with set-up variations leading to a fuzziness of target volume. In this study, we have estimated the dosimetric benefit of normal structures using biological-based optimal margins. The treatment margins are derived by knowledge-based fuzzy logic technique which is considering the radiotherapy uncertainties in treatment planning.

Materials and methods:

All treatment plans were performed using stepped increments of asymmetric margins to estimate prostate radiobiological indices such as tumour control probability (TCP) and normal tissue complication probability (NTCP). An absolute NTCP of 5% was considered to be the maximum acceptable value while TCP of 85% was considered to be the minimal acceptable limit for each volumetric modulated arc therapy (VMAT) plan of localised prostate cancer radiotherapy. Results were used to formulate rules and membership functions for Mamdani-type fuzzy inference system (FIS). In implementing the rules for the fuzzy system for ΔNTCP values above 10%, the PTV margin was not permitted to exceed 5 mm to avoid rectal complications due to margin selection. The new margins were applied in VMAT planning of prostate cancer for standard displacement errors. The dosimetric results of normal tissue predictors were estimated such as organ mean doses, rectum V60 (volume receiving 60 Gy), bladder V65 (volume receiving 65 Gy) and other clinically significant dose–volume indicators and compared with VMAT plans using current margin formulations.

Results:

Dosimetric results compared well to the results obtained by current techniques. Good agreement was obtained between proposed fuzzy model margins and currently used margins in lower error magnitude, but significant results were observed at higher error magnitude when organ toxicity concerned without compromising the target volumes.

Findings:

The new margins may be helpful to estimate possible outcomes of normal tissue complications and thus may improve complication free survival particularly when organ motion errors are inevitable, case by case.

Keywords

asymmetric marginsfuzzy inference systemorgan motionprostate cancertreatment planningvolumetric modulated arc therapy
Type
Technical Note
Information
Journal of Radiotherapy in Practice , Volume 21 , Issue 1 , March 2022 , pp. 129 - 137
Check for updates
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

Byrne, TE. A review of prostate motion with considerations for the treatment of prostate cancer. Med Dosim 2005; 30 (3): 155–161.10.1016/j.meddos.2005.03.005CrossRefGoogle ScholarPubMed
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): 1121–1135.10.1016/S0360-3016(00)00518-6CrossRefGoogle ScholarPubMed
Alasti, H, Petric, MP, Catton, CN, Warde, PR. Portal imaging for evaluation of daily on-line setup errors and off-line organ motion during conformal irradiation of carcinoma of the prostate. Int J Radiat Oncol 2001; 49 (3): 869–884.10.1016/S0360-3016(00)01446-2CrossRefGoogle ScholarPubMed
Deasy, JO, Charles, SM, Colin, GO. Treatment optimization and evaluation should be biologically and not physical dose/volume based. Med Phys 2015; 42 (6): 2753–2756.10.1118/1.4916670CrossRefGoogle ScholarPubMed
Yartsev, S, Bauman, G. Target margins in radiotherapy of prostate cancer. Br J Radiol 2016; 89: 20160312.10.1259/bjr.20160312CrossRefGoogle ScholarPubMed
Chen, Z, Yang, Z, Wang, J, Weigang, H. Dosimetric impact of different bladder and rectum filling during prostate cancer radiotherapy. Radiat Oncol 2016; 11: 103–110.10.1186/s13014-016-0681-zCrossRefGoogle ScholarPubMed
Patnaikuni, SK, Saini, SM, Chandola, RM, Chandrakar, P, Chaudhary, V. Study of asymmetric margins in prostate cancer radiation therapy using fuzzy logic. J Med Phys 2020; 45: 88–97.Google ScholarPubMed
Nuyttens, JJ, Milito, S, Rust, PF, Turrisi, AT. Dose volume relationship for acute side effects during high dose conformal radiotherapy for prostate cancer. Radiother Oncol 2002; 64: 209–214.10.1016/S0167-8140(02)00185-8CrossRefGoogle ScholarPubMed
Ling, CC, Liu, M, Berthelet, E, Patterson, K, Dick, K, Kwan, W. Various techniques of contouring the rectum and their impact on rectal dose volume histograms. Med Dosim 2003; 28: 189–192.Google Scholar
NCCN. Prostate cancer. NCCN Practice. https://www.nccn.org/. 2016. Accessed on 05th August 2018.Google Scholar
Niemierko, A. Reporting and analyzing dose distributions: a concept of equivalent uniform dose. Med Phys 1997; 24 (1): 103–110.10.1118/1.598063CrossRefGoogle ScholarPubMed
Mzenda, B, Hosseini-Ashrafi, ME, Palmer, A, Hodgson, DF, Liu, H, Brown, DJ. Determination of target volumes in radiotherapy and the implications of technological advances: a literature review. J Radiother Pract 2009; 8 (1): 41–51.10.1017/S1460396908006614CrossRefGoogle Scholar
Benk, VA, Adams, JA, Shipley, WU et al. Late rectal bleeding following combined X-ray and proton high dose irradiation for patients with stages T3–T4 prostate carcinoma. Int J Radiat Oncol Biol Phys 1993; 26 (3): 551–557.10.1016/0360-3016(93)90978-5CrossRefGoogle ScholarPubMed
Combs, WE, Andrews, JE. Combinatorial rule explosion eliminated by a fuzzy rule configuration. IEEE Trans fuzzy Syst 1998; 6 (1): 1–11.10.1109/91.660804CrossRefGoogle Scholar
Mzenda, B, Hosseini-Ashrafi, M, Gegov, A, Brown, DJ. Implementation of a fuzzy model for computation of margins in cancer treatment. International Conference on Fuzzy Systems IEEE 2010, ISBN 978-1-4244-6919-2. 2010: 1931–1938.Google Scholar
Lee, TF, Fang, FM, Chao, PJ, Su, TJ, Leung, SW. Dosimetric comparisons of helical tomotherapy and step and shoot intensity modulated radiotherapy in nasopharyngeal carcinoma. Radiother Oncol 2008; 89 (1): 89–96.10.1016/j.radonc.2008.05.010CrossRefGoogle ScholarPubMed