Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
Radiation Oncology
Published in: Radiation Oncology 1/2016

Open Access 01-12-2016 | Research

Radiobiological impact of dose calculation algorithms on biologically optimized IMRT lung stereotactic body radiation therapy plans

Authors: X. Liang, J. Penagaricano, D. Zheng, S. Morrill, X. Zhang, P. Corry, R. J. Griffin, E. Y. Han, M. Hardee, V. Ratanatharathom

Published in: Radiation Oncology | Issue 1/2016

Login to get access

Abstract

Background

The aim of this study is to evaluate the radiobiological impact of Acuros XB (AXB) vs. Anisotropic Analytic Algorithm (AAA) dose calculation algorithms in combined dose-volume and biological optimized IMRT plans of SBRT treatments for non-small-cell lung cancer (NSCLC) patients.

Methods

Twenty eight patients with NSCLC previously treated SBRT were re-planned using Varian Eclipse (V11) with combined dose-volume and biological optimization IMRT sliding window technique. The total dose prescribed to the PTV was 60 Gy with 12 Gy per fraction. The plans were initially optimized using AAA algorithm, and then were recomputed using AXB using the same MUs and MLC files to compare with the dose distribution of the original plans and assess the radiobiological as well as dosimetric impact of the two different dose algorithms. The Poisson Linear-Quadatric (PLQ) and Lyman-Kutcher-Burman (LKB) models were used for estimating the tumor control probability (TCP) and normal tissue complication probability (NTCP), respectively. The influence of the model parameter uncertainties on the TCP differences and the NTCP differences between AAA and AXB plans were studied by applying different sets of published model parameters. Patients were grouped into peripheral and centrally-located tumors to evaluate the impact of tumor location.

Results

PTV dose was lower in the re-calculated AXB plans, as compared to AAA plans. The median differences of PTV(D95%) were 1.7 Gy (range: 0.3, 6.5 Gy) and 1.0 Gy (range: 0.6, 4.4 Gy) for peripheral tumors and centrally-located tumors, respectively. The median differences of PTV(mean) were 0.4 Gy (range: 0.0, 1.9 Gy) and 0.9 Gy (range: 0.0, 4.3 Gy) for peripheral tumors and centrally-located tumors, respectively. TCP was also found lower in AXB-recalculated plans compared with the AAA plans. The median (range) of the TCP differences for 30 month local control were 1.6 % (0.3 %, 5.8 %) for peripheral tumors and 1.3 % (0.5 %, 3.4 %) for centrally located tumors. The lower TCP is associated with the lower PTV coverage in AXB-recalculated plans. No obvious trend was observed between the calculation-resulted TCP differences and tumor size or location. AAA and AXB yield very similar NTCP on lung pneumonitis according to the LKB model estimation in the present study.

Conclusion

AAA apparently overestimates the PTV dose; the magnitude of resulting difference in calculated TCP was up to 5.8 % in our study. AAA and AXB yield very similar NTCP on lung pneumonitis based on the LKB model parameter sets we used in the present study.
Literature
1.
Lyman JT. Complication probability as assessed from dose-volume histograms. Radiat Res. 1985;104 Suppl. 8:S13–9.
2.
Lyman JT, Wolbarst AB. Optimization of radiation therapy, III: A method of assessing complication probabilities from dose-volume histograms. Int J Radiat OncolBiol Phys. 1987;13:103–9.CrossRef
3.
Kutcher GJ, Burman C. Calculation of complication probability factors for non-uniform normal tissue irradiation: the effective volume method. Int J Radiat OncolBiol Phys. 1989;16:1623–30.CrossRef
4.
Burman C, Kutcher GJ, Emami B, Goitein M. Fitting of normal tissue tolerance data to an analytic fuction. Int J Radiat Oncol Biol Phys. 1991;21(1):123–35.CrossRefPubMed
5.
Kutcher GJ, Burman C, Brewster L, Gotein M, Mohan R. Histogram reduction method for Calculation complication probabilities for three dimensional treatment evaluation. Int J Radiat Oncol Biol Phys. 1991;21(1):137–46.CrossRefPubMed
6.
Källman P, Agren A, Brahme A. Tumour and normal tissue responses to fractionated non-uniform dose delivery. Int J Radiat Biol. 1992;62(2):249–62.CrossRefPubMed
7.
Schultheiss TE, Orten CG. Models in radiotherapy: definition of decision criteria. Med Phys. 1985;12(2):183–7.CrossRefPubMed
8.
Morrill SM, Lane RG, Jacobson G, Rosen II. Treatment planning optimization using constrained simulated annealing. Phys Med Biol. 1991;36(10):1341–61.CrossRefPubMed
9.
Qi XS, Semenenko VA, Li XA. Improved critical structure sparing with biologically based IMRT optimization. Med Phys. 2009;36(5):1790–9.CrossRefPubMed
10.
Das S. A role for biological optimization within the current treatment planning paradigm. Med Phys. 2009;36(10):4672–82.CrossRefPubMed
11.
Doit Q, Kavanagh B, Timmerman R, Miften M. Biological-based optimization and volumetric modulated arc therapy delivery for stereotactic body radiation therapy. Med Phys. 2012;39(1):237–45.CrossRef
12.
Allen Li X, Alber M, Deasy JO, Jackson A, Ken Jee KW, Marks LB, et al. The use and QA of biologically related models for treatment planning: short report of the TG-166 of the therapy physics committee of the AAPM. Med Phys. 2012;39(3):1386–409.CrossRefPubMed
13.
Ulmer W, Pyyry J, Kaissl W. A 3D photon superposition/convolution algorithm and its foundation on results of Monte Carlo calculations. Phys Med Biol. 2005;50(8):1767–90.CrossRefPubMed
14.
Lewis EE, Miller WF. Computational Methods of Neutron Transport. New York: Wiley; 1984.
15.
Ahnesjö A, Aspradakis MM. Dose calculations for external photon beams in radiotherapy. Phys Med Biol. 1999;44(11):R99–155.CrossRefPubMed
16.
Vassiliev ON, Wareing TA, McGhee J, Failla G, Salehpour MR, Mourtada F. Validation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beams. Phys Med Biol. 2010;55(3):581–98.CrossRefPubMed
17.
Bush K, Gagne IM, Zavgorodni S, Ansbacher W, Beckham W. Dosimetric validation of Acuros XB with Monte Carlo methods for photon dose calculations. Med Phys. 2011;38(4):2208–21.CrossRefPubMed
18.
Fogliata A, Nicolini G, Clivio A, Vanetti E, Mancosu P, Cozzi L. Dosimetric validation of the Acuros XB Advanced Dose Calculation algorithm: fundamental characterization in water. Phys Med Biol. 2011;56(6):1879–904.CrossRefPubMed
19.
Kan MW, Leung LH, Yu PK. Verification and dosimetric impact of Acuros XB algorithm on intensity modulated stereotactic radiotherapy for locally persistent nasopharyngeal carcinoma. Med Phys. 2012;39(8):4705–14.CrossRefPubMed
20.
Han T, Mikell JK, Salehpour M, Mourtada F. Dosimetric comparison of Acuros XB deterministic radiation transport method with Monte Carlo and model-based convolution methods in heterogeneous media. Med Phys. 2011;38(5):2651–64.PubMedCentralCrossRefPubMed
21.
Moiseenko V, Liu M, Bergman AM, Gill B, Kristensen S, Teke T, et al. Monte Carlo calculation of dose distribution in early stage NSCLC patients planned for accelerated hypofractionated radiation therapy in the NCIC-BR25 protocol. Phys Med Biol. 2010;55(3):723–33.CrossRefPubMed
22.
Elmpt WV, Ollers M, Velders M, Poels K, Mijnheer B, Ruysscher DD, et al. Transition from a simple to a more advanced dose calculation algorithm for radiotherapy of non-small cell lung cancer (NSCLC): implications for clinical implementation in an individualized dose-escalation protocol. Radio Ther Oncol. 2008;88(3):326–34.CrossRef
23.
Vanderstraeten B, Reynaert N, Paelinck L, Madani I, De Wagter C, De Gersem W, et al. Accuracy of patient dose calculation for lung IMRT: A comparison of Monte Carlo, convolution/superposition, and pencil beam computations. Med Phys. 2006;33(9):3149–58.CrossRefPubMed
24.
Fogliata A, Nicolini G, Clivio A, Vanetti E, Cozzi L. Critical appraisal of Acuros XB and Anisotropic Analytic Algorithm dose calculation in advanced non-small-cell lung cancer treatments. Int J Radiat Oncol Biol Phys. 2012;83(5):1587–95.CrossRefPubMed
25.
Rana S, Rogers K, Pokharel S, Cheng C. Evaluation of Acuros XB algorithm based on RTOG 0813 dosimetric criteria for SBRT lung treatment with RapidArc. J Appl Clin Med Phys. 2014;15(1):4474.PubMed
26.
Kroon PS, Hol S, Essers M. Dosimetric accuracy and clinical quality of Acuros XB and AAA dose calculation algorithm for stereotactic and conventional lung volumetric modulated arc therapy plans. Radiat Oncol. 2013;8:149.PubMedCentralCrossRefPubMed
27.
Timmerman R, McGarry R, Yiannoutsos C, Papiez L, Tudor K, DeLuca J, et al. Excessive toxicity when treating central tumors in a phase II study of stereotactic body radiation therapy for medically inoperable early-stage lung cancer. J Clin Oncol. 2006;24(30):4833–9.CrossRefPubMed
28.
29.
Mutter RW, Liu F, Abreu A, Yorke E, Jackson A, Rosenzweig KE. Dose-volume parameters predict for the development of chest wall pain after stereotactic body radiation for lung cancer. Int J Radiat Oncol Biol Phys. 2012;82(5):1783–90.PubMedCentralCrossRefPubMed
30.
Joiner MC, Bentzen SM. Time-dose relationships: the linear-quadratic approach. In: Steel GG, editor. Basic clinical radiobiology. London: Edward Arnold; 2002.
31.
Petillion S, Swinnen A, Defraene G, Verhoeven K, Weltens C, Van den Heuvel F. The photon dose calculation algorithm used in breast radiotherapy has significant impact on the parameters of radiobiological models. J Appl Clin Med Phys. 2014;15(4):4853.PubMed
32.
Willner J, Baier K, Caragiani E, Tschammler A, Flentje M. Dose, volume, and tumor control prediction in primary radiotherapy of non-small-cell lung cancer. Int J Radiat Oncol Biol Phys. 2002;52(2):382–9.CrossRefPubMed
33.
Martel MK, Ten Haken RK, Hazuka MB, Kessler ML, Strawderman M, Turrisi AT, et al. Estimation of tumor control probability model parameters from 3-D dose distributions of non-small cell lung cancer patients. Lung Cancer. 1999;24(1):31–7.CrossRefPubMed
34.
Guckenberger M, Wulf J, Mueller G, Krieger T, Baier K, Gabor M, et al. Dose-response relationship for image-guided stereotactic body radiotherapy of pulmonary tumors: relevance of 4D dose calculation. Int J Radiat Oncol Biol Phys. 2009;74(1):47–54.CrossRefPubMed
35.
Niemierko A. A generalized concept of equivalent uniform dose (EUD). Med Phys. 1999;26:1100.
36.
Seppenwoolde Y, Lebesque JV, de Jaeger K, Belderbos JS, Boersma LJ, Schilstra C, et al. Comparing different NTCP models that predict the incidence of radiation pneumonitis. Normal tissue complication probability. Int J Radiat Oncol Biol Phys. 2003;55(3):724–35.CrossRefPubMed
37.
Kwa SL, Lebesque JV, Theuws JC, Marks LB, Munley MT, Bentel G, et al. Radiation pneumonitis as a function of mean lung dose: an analysis of pooled data of 540 patients. Int J Radiat Oncol Biol Phys. 1998;42(1):1–9.CrossRefPubMed
38.
Scheenstra AE, Rossi MM, Belderbos JS, Damen EM, Lebesque JV, Sonke JJ. Alpha/beta ratio for normal lung tissue as estimated from lung cancer patients treated with stereotactic body and conventionally fractionated radiation therapy. Int J Radiat Oncol Biol Phys. 2014;88(1):224–8.CrossRefPubMed
39.
KruskalHK WWA. Use of ranks in one-criterion variance analysis. J Am Stat Assoc. 1952;47(260):583–621.CrossRef
40.
Sikora M, Muzik J, Söhn M, Weinmann M, Alber M, Monte Carlo V. pencil beam based optimization of stereotactic lung IMRT. Radiat Oncol. 2009;12(4):64.CrossRef
41.
Guckenberger M, Wilbert J, Krieger T, Richter A, Baier K, Meyer J, et al. Four-dimensional treatment planning for stereotactic body radiotherapy. Int J Radiat Oncol Biol Phys. 2007;69(1):276–85.CrossRefPubMed
42.
Marks LB, Bentzen SM, Deasy JO, Kong FM, Bradley JD, Vogelius IS, et al. Radiation dose-volume effects in the lung. Int J Radiat Oncol Biol Phys. 2010;76(3 Suppl):s70–6.PubMedCentralCrossRefPubMed
43.
Nielsen TB, Wieslander E, Fogliata A, Nielsen M, Hansen O, Brink C. Influence of dose calculation algorithms on the predicted dose distribution and NTCP values for NSCLC patients. Med Phys. 2011;38(5):2412–8.CrossRefPubMed
44.
Bufacchi A, Nardiello B, Capparella R, Begnozzi L. Clinical implications in the use of the PBC algorithm versus the AAA by comparison of different NTCP models/parameters. Radiat Oncol. 2013;8(1):164.PubMedCentralCrossRefPubMed
45.
Rana S, Rogers K. Radiobiological impact of Acuros XB dose calculation algorithm on low-risk prostate cancer treatment plans created by RapidArc technique. Austral-Asian J Cancer. 2012;11(4):261–9.
46.
Padmanaban S, Warren S, Walsh A, Partridge M, Hawkins MA. Comparison of Acuros (AXB) and Anisotropic Analytical Algorithm (AAA) for dose calculation in treatment of oesophageal cancer: effects on modelling tumour control probability. Radiat Oncol. 2014;9:286.PubMedCentralCrossRefPubMed
47.
Park C, Papiez L, Zhang S, Story M, Timmerman RD. Universal survival curve and single fraction equivalent dose: useful tools in understanding potency of ablative radiotherapy. Int J Rad Onc Biol Phys. 2008;70(3):847–52.CrossRef
48.
Park HJ, Griffin RJ, Hui S, Levitt SH, Song CW. Radiation-induced vascular damage in tumors: implications of vascular damage in ablative hypofractionated radiotherapy (SBRT and SRS). Radiat Res. 2012;177(3):311–27.CrossRefPubMed
49.
Song CW, Cho LC, Yuan J, Dusenbery KE, Griffin RJ, Levitt SH. Radiobiology of stereotactic body radiation therapy/stereotactic radiosurgery and the linear-quadratic model. Int J Radiat OncolBiol Phys. 2013;87(1):18–9.CrossRef
50.
Chapet O, Kong FM, Lee JS, Hayman JA, Ten Haken RK. Normal tissue complication probability modeling for acute esophagitis in patients treated with conformal radiation therapy for non-small cell lung cancer. Radiother Oncol. 2005;77(2):176–81.CrossRefPubMed
51.
Martel MK, Sahijdak WM, Ten Haken RK, Kessler ML, Turrisi AT. Fraction size and dose parameters related to the incidence of pericardial effusions. Int J Radiat Oncol Biol Phys. 1998;40(1):155–61.CrossRefPubMed
52.
AgrenCronqvist AK, Källman P, Turesson I, Brahme A. Volume and heterogeneity dependence of the dose-response relationship for head and neck tumours. Acta Oncol. 1995;34(6):851–60.CrossRef
Metadata
Title
Radiobiological impact of dose calculation algorithms on biologically optimized IMRT lung stereotactic body radiation therapy plans
Authors
X. Liang
J. Penagaricano
D. Zheng
S. Morrill
X. Zhang
P. Corry
R. J. Griffin
E. Y. Han
M. Hardee
V. Ratanatharathom
Publication date
01-12-2016
Publisher
BioMed Central
Published in
Radiation Oncology / Issue 1/2016
Electronic ISSN: 1748-717X
DOI
https://doi.org/10.1186/s13014-015-0578-2

Other articles of this Issue 1/2016

Radiation Oncology 1/2016 Go to the issue

Research

Local radiotherapy alone following neoadjuvant chemotherapy and surgery in combined clinical stage II and III breast cancer

Research

Target dose conversion modeling from pencil beam (PB) to Monte Carlo (MC) for lung SBRT

Methodology

Initial characterization, dosimetric benchmark and performance validation of Dynamic Wave Arc

Research

Beyond D’Amico risk classes for predicting recurrence after external beam radiotherapy for prostate cancer: the Candiolo classifier

Research

Dosimetric impact of different bladder and rectum filling during prostate cancer radiotherapy

Research

SBRT for centrally localized NSCLC – What is too central?