Study on the Ability of 3D Gamma Analysis and Bio-mathematical Model in Detecting Dose Changes Caused by Dose-calculation-grid-size (DCGS)

Overview

Journal Radiat Oncol

Publisher Biomed Central

Specialties Oncology
Radiology

Date 2020 Jul 8

PMID 32631380

Citations 1

Authors

Han Bai

Sijin Zhu

Xingrao Wu

Xuhong Liu

Feihu Chen

Jiawen Yan

Affiliations

Soon will be listed here.

Abstract

Objective: To explore the efficacy and sensitivity of 3D gamma analysis and bio-mathematical model for cervical cancer in detecting dose changes caused by dose-calculation-grid-size (DCGS).

Methods: 17 patients' plans for cervical cancer were enrolled (Pinnacle TPS, VMAT), and the DCGS was changed from 2.0 mm to 5.0 mm to calculate the planned dose respectively. The dose distribution calculated by DCGS = 2.0 mm as the "reference" data set (RDS), the dose distribution calculated by the rest DCGS as the"measurement"data set (MDS), the 3D gamma passing rates and the (N) TCPs of the all structures under different DCGS were obtained, and then analyze the ability of 3D gamma analysis and (N) TCP model in detecting dose changes and what factors affect this ability.

Results: The effect of DCGS on planned dose was obvious. When the gamma standard was 1.0 mm, 1.0 and 10.0%, the difference of the results of the DCGS on dose-effect could be detected by 3D gamma analysis (all p value < 0.05). With the decline of the standard, 3D gamma analysis' ability to detect this difference shows weaker. When the standard was 1.0 mm, 3.0 and 10.0%, the p value of > 0.05 accounted for the majority. With DCGS = 2.0 mm being RDS, ∆gamma-passing-rate presented the same trend with ∆(N) TCPs of all structures except for the femurs only when the 1.0 mm, 1.0 and 10.0% standards were adopted for the 3D gamma analysis.

Conclusions: The 3D gamma analysis and bio-mathematical model can be used to analyze the effect of DCGS on the planned dose. For comparison, the former's detection ability has a lot to do with the designed standard, and the latter's capability is related to the parameters and calculated accuracy instrinsically.

Citing Articles

Image-based features in machine learning to identify delivery errors and predict error magnitude for patient-specific IMRT quality assurance.

Huang Y, Pi Y, Ma K, Miao X, Fu S, Chen H Strahlenther Onkol. 2023; 199(5):498-510.

PMID: 36988665 PMC: 10133379. DOI: 10.1007/s00066-023-02076-8.

References

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

Ezzell G, Galvin J, Low D, Palta J, Rosen I, Sharpe M . Guidance document on delivery, treatment planning, and clinical implementation of IMRT: report of the IMRT Subcommittee of the AAPM Radiation Therapy Committee. Med Phys. 2003; 30(8):2089-115. DOI: 10.1118/1.1591194. View

Chow J, Jiang R . Dose-volume and radiobiological dependence on the calculation grid size in prostate VMAT planning. Med Dosim. 2018; 43(4):383-389. DOI: 10.1016/j.meddos.2017.12.002. View

Alharthi T, Pogson E, Arumugam S, Holloway L, Thwaites D . Pre-treatment verification of lung SBRT VMAT plans with delivery errors: Toward a better understanding of the gamma index analysis. Phys Med. 2018; 49:119-128. DOI: 10.1016/j.ejmp.2018.04.005. View

Shiba E, Saito A, Furumi M, Murakami Y, Ohguri T, Tsuneda M . Predictive gamma passing rate by dose uncertainty potential accumulation model. Med Phys. 2018; 46(2):999-1005. DOI: 10.1002/mp.13333. View

Sanghangthum T, Suriyapee S, Srisatit S, Pawlicki T . Statistical process control analysis for patient-specific IMRT and VMAT QA. J Radiat Res. 2012; 54(3):546-52. PMC: 3650738. DOI: 10.1093/jrr/rrs112. View

Hussein M, Rowshanfarzad P, Ebert M, Nisbet A, Clark C . A comparison of the gamma index analysis in various commercial IMRT/VMAT QA systems. Radiother Oncol. 2013; 109(3):370-6. DOI: 10.1016/j.radonc.2013.08.048. View

Zhen H, Hrycushko B, Lee H, Timmerman R, Pompos A, Stojadinovic S . Dosimetric comparison of Acuros XB with collapsed cone convolution/superposition and anisotropic analytic algorithm for stereotactic ablative radiotherapy of thoracic spinal metastases. J Appl Clin Med Phys. 2015; 16(4):181–192. PMC: 5690024. DOI: 10.1120/jacmp.v16i4.5493. View

Lam D, Zhang X, Li H, Deshan Y, Schott B, Zhao T . Predicting gamma passing rates for portal dosimetry-based IMRT QA using machine learning. Med Phys. 2019; 46(10):4666-4675. DOI: 10.1002/mp.13752. View

10.

Fogliata A, Thompson S, Stravato A, Tomatis S, Scorsetti M, Cozzi L . On the gEUD biological optimization objective for organs at risk in Photon Optimizer of Eclipse treatment planning system. J Appl Clin Med Phys. 2017; 19(1):106-114. PMC: 5768006. DOI: 10.1002/acm2.12224. View

11.

McNair H, Adams E, Clark C, Miles E, Nutting C . Implementation of IMRT in the radiotherapy department. Br J Radiol. 2004; 76(912):850-6. DOI: 10.1259/bjr/19737738. View

12.

Leibel S, Zelefsky M, Kutcher G, Burman C, Mohan R, Mageras G . The biological basis and clinical application of three-dimensional conformal external beam radiation therapy in carcinoma of the prostate. Semin Oncol. 1994; 21(5):580-97. View

13.

Jursinic P, Sharma R, Reuter J . MapCHECK used for rotational IMRT measurements: step-and-shoot, TomoTherapy, RapidArc. Med Phys. 2010; 37(6):2837-46. DOI: 10.1118/1.3431994. View

14.

Park J, Park S, Kim J, Carlson J, Kim J . The influence of the dose calculation resolution of VMAT plans on the calculated dose for eye lens and optic pathway. Australas Phys Eng Sci Med. 2017; 40(1):209-217. DOI: 10.1007/s13246-016-0517-z. View

15.

Cho K, Kim J, Lee S, Yoo H, Shin S, Moon S . Simultaneous integrated boost intensity-modulated radiotherapy in patients with high-grade gliomas. Int J Radiat Oncol Biol Phys. 2010; 78(2):390-7. DOI: 10.1016/j.ijrobp.2009.08.029. View

16.

Sharfo A, Voet P, Breedveld S, Mens J, Hoogeman M, Heijmen B . Comparison of VMAT and IMRT strategies for cervical cancer patients using automated planning. Radiother Oncol. 2015; 114(3):395-401. DOI: 10.1016/j.radonc.2015.02.006. View

17.

Wali L, Helal A, Darwesh R, Attar M . A dosimetric comparison of Volumetric Modulated Arc Therapy (VMAT) and High Dose Rate (HDR) brachytherapy in localized cervical cancer radiotherapy. J Xray Sci Technol. 2019; 27(3):473-483. DOI: 10.3233/XST-180468. View

18.

Wang Y, Chen L, Zhu F, Guo W, Zhang D, Sun W . A study of minimum segment width parameter on VMAT plan quality, delivery accuracy, and efficiency for cervical cancer using Monaco TPS. J Appl Clin Med Phys. 2018; 19(5):609-615. PMC: 6123131. DOI: 10.1002/acm2.12422. View

19.

Kim J, Park S, Kim H, Kim J, Ye S, Park J . The sensitivity of gamma-index method to the positioning errors of high-definition MLC in patient-specific VMAT QA for SBRT. Radiat Oncol. 2014; 9:167. PMC: 4118611. DOI: 10.1186/1748-717X-9-167. View

20.

Templeton A, Chu J, Turian J . The sensitivity of ArcCHECK-based gamma analysis to manufactured errors in helical tomotherapy radiation delivery. J Appl Clin Med Phys. 2015; 16(1):4814. PMC: 5689971. DOI: 10.1120/jacmp.v16i1.4814. View