The bootstrap method to improve statistical analysis of dosimetric data for radiotherapy outcomes

Abdulhamid Chaikh, Jean-Pierre Bresciani, Jacques Balosso

Abstract


Purpose: The purpose of this study is to validate a new technique in radiotherapy, the medical physicist needs to evaluate the dosimetric benefit and the risk of toxicity before integrating it in the clinical use.

Methods: We validate a sound decision tool based on bootstrap method to help the radio oncologist and the medical physicist to usefully analyze the dosimetric data obtained from small-sized samples, with few patients. Statistical investigation principles are presented in the framework of a clinical example based on 36 patients with 6 different cancer sites treated with radiotherapy. For each patient, two treatment plans were generated. In plan 1, the dose was calculated using Modified Batho's (MB) density correction method integrated with pencil beam convolution (PBC) as type (a) algorithm. In plan 2, the dose was calculated using Anisotropic Analytical Algorithm (AAA) as type (b) algorithm. The delivered doses in monitor units (MUs) were compared using the two plans. Then, the bootstrap method was applied to the original data set to assess the dose differences and evaluate the impact of sample size on the 95% confidence interval (95%.CI). Shapiro-Wilks and Wilcoxon signed-rank tests were used to assess the normality of the data and determine the p-value. In addition, Spearman’s rank test was used to calculate the correlation coefficient between the doses calculated with both algorithms.

Results: A significant difference was observed between AAA and MB for all tested radiation sites. Spearman’s test indicated a good correlation between the doses calculated with both methods. The bootstrap simulation with 1000 random samplings can be used for small populations with n = 10 and provides a true estimation.

Conclusion: one must be cautious when implementing this method for radiotherapy: the data should be representative of the real variations of the cases and the cases should be as homogeneous as possible to avoid bias of over/under estimation of the results.


Keywords


Bootstrap method, Delivered dose, Radiotherapy

Full Text:

PDF

References


Efron B, Tibshirani RJ. An introduction to the bootstrap. Chapman & Hall, New York. 1993.

Efron B. Bootstrap methods: Another look at the jackknife. Ann Statist. 1979;7:1-26.

Task Group Number 65. Radiation Therapy Committee of the American Association of Physicists in Medicine. Tissue inhomogeneity corrections for MV photon beams. Med Phys. 2004.

Ahnesjö A, Aspradakis MM. Dose calculations for external photon beams in radiotherapy. Phys Med Biol. 1999;44 :99–155.

Batho HF. Lung corrections in cobalt 60 beam therapy. J Can Assoc Radiol. 1964;15:79-83.

El-Khatib E, Battista JJ. Improved lung dose calculation using tissue-maximum ratios in the Batho correction. Med Phys. 1984;11(3):279–86.

Rana S. Clinical dosimetric impact of Acuros XB and analytical anisotropic algorithm (AAA) on real lung cancer treatment plans: review. Int J Cancer Ther Oncol. 2014;2:02019.

Ojala J. The accuracy of the Acuros XB algorithm in external beam radiotherapy – a comprehensive review. Int J Cancer Ther Oncol. 2014;2:020417.

Chaikh A, Giraud JY, Perrin E, et al. The choice of statistical methods for comparisons of dosimetric data in radiotherapy. Radiat Oncol. 2014;9:205.

The R project for statistical computing.

Minna W. Assessing the uncertainty in QUANTEC’s dose response relation of lung and spinal cord with a bootstrap analysis. Int J Radiat Oncol Biol Phys. 2013;87(4):795-801.

Marcella P, Stefano M, Paola F, et al. Analysis of inter-fraction setup errors and organ motion by daily kilovoltage cone beam computed tomography in intensity modulated radiotherapy of prostate cancer. Radiat Oncol. 2012;7:56.

Hout W, Kramer G, Noordijk E, et al. Cost- utility analysis of short-versus long-course palliative radiotherapy in patients with Non – Small-Cell Lung Cancer. J Natl Cancer Inst. 2006; 98(24):1786-94.

Chaikh A, Balosso J. Correlation between pneumonitis risk in radiation oncology and lung density measured with X-ray computed tomography. Quant Imaging Med Surg. 2016;6(4):413-7.

Chaikh A, Balosso J. NTCP variability in radiotherapy of lung cancer when changing the radiobiologic models and the photon dose calculation algorithms. J Cancer Clin Oncol. 2016;2(1):100108.




DOI: http://dx.doi.org/10.14319/ijcto.51.2

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

------------------------------------------------------------

International Journal of Cancer Therapy and Oncology (ISSN 2330-4049)

© International Journal of Cancer Therapy and Oncology (IJCTO)

To make sure that you can receive messages from us, please add the 'ijcto.org' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.

------------------------------------------------------------

Number of visits since October, 2013
AmazingCounters.com