Comparison of Gamma Index Based on Dosimetric Error and Clinically Relevant Dose-volume Index Based on Three-dimensional Dose Prediction in Breast Intensity-modulated Radiation Therapy

Overview

Journal Radiat Oncol

Publisher Biomed Central

Specialties Oncology
Radiology

Date 2019 Feb 28

PMID 30808377

Citations 1

Authors

Akari Kaneko

Iori Sumida

Hirokazu Mizuno

Fumiaki Isohashi

Osamu Suzuki

Yuji Seo

Keisuke Otani

Keisuke Tamari

Kazuhiko Ogawa

Affiliations

Soon will be listed here.

Abstract

Background: Measurement-guided dose reconstruction has lately attracted significant attention because it can predict the delivered patient dose distribution. Although the treatment planning system (TPS) uses sophisticated algorithm to calculate the dose distribution, the calculation accuracy depends on the particular TPS used. This study aimed to investigate the relationship between the gamma passing rate (GPR) and the clinically relevant dose-volume index based on the predicted 3D patient dose distribution derived from two TPSs (XiO, RayStation).

Methods: Twenty-one breast intensity-modulated radiation therapy plans were inversely optimized using XiO. With the same plans, both TPSs calculated the planned dose distribution. We conducted per-beam measurements on the coronal plane using a 2D array detector and analyzed the difference in 2D GPRs between the measured and planned doses by commercial software. Using in-house software, we calculated the predicted 3D patient dose distribution and derived the predicted 3D GPR, the predicted per-organ 3D GPR, and the predicted clinically relevant dose-volume indices [dose-volume histogram metrics and the value of the tumor-control probability/normal tissue complication probability of the planning target volume and organs at risk]. The results derived from XiO were compared with those from RayStation.

Results: While the mean 2D GPRs derived from both TPSs were 98.1% (XiO) and 100% (RayStation), the mean predicted 3D GPRs of ipsilateral lung (73.3% [XiO] and 85.9% [RayStation]; p < 0.001) had no correlation with 2D GPRs under the 3% global/3 mm criterion. Besides, this significant difference in terms of referenced TPS between XiO and RayStation could be explained by the fact that the error of predicted V of ipsilateral lung derived from XiO (29.6%) was significantly larger than that derived from RayStation (- 0.2%; p < 0.001).

Conclusions: GPR is useful as a patient quality assurance to detect dosimetric errors; however, it does not necessarily contain detailed information on errors. Using the predicted clinically relevant dose-volume indices, the clinical interpretation of dosimetric errors can be obtained. We conclude that a clinically relevant dose-volume index based on the predicted 3D patient dose distribution could add to the clinical and biological considerations in the GPR, if we can guarantee the dose calculation accuracy of referenced TPS.

Citing Articles

Impact of Dose Calculation Algorithms and Radiobiological Parameters on Prediction of Cardiopulmonary Complications in Left Breast Radiation Therapy.

Kargar N, Zeinali A, Molazadeh M J Biomed Phys Eng. 2024; 14(2):129-140.

PMID: 38628897 PMC: 11016826. DOI: 10.31661/jbpe.v0i0.2305-1616.

References

Gagliardi G, Bjohle J, Lax I, Ottolenghi A, Eriksson F, LIEDBERG A . Radiation pneumonitis after breast cancer irradiation: analysis of the complication probability using the relative seriality model. Int J Radiat Oncol Biol Phys. 2000; 46(2):373-81. DOI: 10.1016/s0360-3016(99)00420-4. View

Deng J, Jiang S, Kapur A, Li J, Pawlicki T, Ma C . Photon beam characterization and modelling for Monte Carlo treatment planning. Phys Med Biol. 2000; 45(2):411-27. DOI: 10.1088/0031-9155/45/2/311. View

Miften M, Wiesmeyer M, Monthofer S, Krippner K . Implementation of FFT convolution and multigrid superposition models in the FOCUS RTP system. Phys Med Biol. 2000; 45(4):817-33. DOI: 10.1088/0031-9155/45/4/301. View

Venselaar J, Welleweerd H, Mijnheer B . Tolerances for the accuracy of photon beam dose calculations of treatment planning systems. Radiother Oncol. 2001; 60(2):191-201. DOI: 10.1016/s0167-8140(01)00377-2. View

Kallman 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. DOI: 10.1080/09553009214552071. View

Horton J, Halle J, Chang S, Sartor C . Comparison of three concomitant boost techniques for early-stage breast cancer. Int J Radiat Oncol Biol Phys. 2005; 64(1):168-75. DOI: 10.1016/j.ijrobp.2005.07.004. View

Kim Y, Tome W . Risk-adaptive optimization: selective boosting of high-risk tumor subvolumes. Int J Radiat Oncol Biol Phys. 2006; 66(5):1528-42. PMC: 2423330. DOI: 10.1016/j.ijrobp.2006.08.032. View

Ezzell G, Burmeister J, Dogan N, LoSasso T, Mechalakos J, Mihailidis D . IMRT commissioning: multiple institution planning and dosimetry comparisons, a report from AAPM Task Group 119. Med Phys. 2009; 36(11):5359-73. DOI: 10.1118/1.3238104. View

Gagliardi G, Constine L, Moiseenko V, Correa C, Pierce L, Allen A . Radiation dose-volume effects in the heart. Int J Radiat Oncol Biol Phys. 2010; 76(3 Suppl):S77-85. DOI: 10.1016/j.ijrobp.2009.04.093. View

10.

Li J, Lin T, Chen L, Price Jr R, Ma C . Uncertainties in IMRT dosimetry. Med Phys. 2010; 37(6):2491-500. DOI: 10.1118/1.3413997. View

11.

Boggula R, Lorenz F, Mueller L, Birkner M, Wertz H, Stieler F . Experimental validation of a commercial 3D dose verification system for intensity-modulated arc therapies. Phys Med Biol. 2010; 55(19):5619-33. DOI: 10.1088/0031-9155/55/19/001. View

12.

Nelms B, Zhen H, Tome W . Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors. Med Phys. 2011; 38(2):1037-44. PMC: 3188652. DOI: 10.1118/1.3544657. View

13.

Nielsen T, 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. DOI: 10.1118/1.3575418. View

14.

Olch A . Evaluation of the accuracy of 3DVH software estimates of dose to virtual ion chamber and film in composite IMRT QA. Med Phys. 2012; 39(1):81-6. DOI: 10.1118/1.3666771. View

15.

Nelms B, Opp D, Robinson J, Wolf T, Zhang G, Moros E . VMAT QA: measurement-guided 4D dose reconstruction on a patient. Med Phys. 2012; 39(7):4228-38. DOI: 10.1118/1.4729709. View

16.

Stasi M, Bresciani S, Miranti A, Maggio A, Sapino V, Gabriele P . Pretreatment patient-specific IMRT quality assurance: a correlation study between gamma index and patient clinical dose volume histogram. Med Phys. 2012; 39(12):7626-34. DOI: 10.1118/1.4767763. View

17.

Zhen H, Nelms B, Tome W . On the use of biomathematical models in patient-specific IMRT dose QA. Med Phys. 2013; 40(7):071702. DOI: 10.1118/1.4805105. View

18.

Hedin E, Back A . Influence of different dose calculation algorithms on the estimate of NTCP for lung complications. J Appl Clin Med Phys. 2013; 14(5):127-39. PMC: 5714575. DOI: 10.1120/jacmp.v14i5.4316. View

19.

Coleman L, Skourou C . Sensitivity of volumetric modulated arc therapy patient specific QA results to multileaf collimator errors and correlation to dose volume histogram based metrics. Med Phys. 2013; 40(11):111715. DOI: 10.1118/1.4824433. View

20.

Abo-Madyan Y, Aziz M, Aly M, Schneider F, Sperk E, Clausen S . Second cancer risk after 3D-CRT, IMRT and VMAT for breast cancer. Radiother Oncol. 2014; 110(3):471-6. DOI: 10.1016/j.radonc.2013.12.002. View