Desenvolvimento de um software de análise estatística do sinal respiratório para realização tomografia 4D

Authors

DOI:

https://doi.org/10.29384/rbfm.2021.v15.19849001641

Keywords:

radioterapia, tomografia 4D, 4DTC, respiração

Abstract

The quality improvement in radiotherapy treatments, from the point of view of increased tumor control and decrease in normal tissue damages led to the creation, among other technologies, of retrospective 4DCT. This technology allows the obtaining of tomographic images related to the respiratory phase, thus creating a 4D tomography. However, the reliability of this imaging modality is directly related to the patient's breath reproductivity. Because of this, the department uses a visual analysis of respiratory signal quality that covers 4 parameters: peak amplitude, valley amplitude, cycle period and point variations. Currently, the analysis process is carried out qualitatively, which generates great divergence between observers and the risk that some problem is not detected. The objective of this work was to create a tool that allows the analysis of quantitative parameters of the measured respiratory signal, to assist in the qualitative analysis of the observers. The data obtained as software output are the mean and standard deviation of the amplitudes of the peaks, the amplitudes of the valleys and the peak and valley periods. The program also generates graphs for visual analysis of parameters. The software allowed the achievement of quantitative characteristics of the patient's breathing during the clinical routine. Adding information that was previously not available to the observer.

Downloads

Download data is not yet available.

References

1. WHO. Delivering quality health services [Internet]. World Health Organization, World Bank Group, OECD. 2018. 1–100 p. Available from: http://apps.who.int/bookorders.
2. Cochrane. Cochranelibrary - MeSH - Radiotherapy [Internet]. [cited 2021 Feb 24]. Available from: https://www.cochranelibrary.com/advanced-search/mesh#0
3. Aznar MC, Warren S, Hoogeman M, Josipovic M. The impact of technology on the changing practice of lung SBRT. Phys Medica [Internet]. 2018;47(December 2017):129–38. Available from: https://doi.org/10.1016/j.ejmp.2017.12.020
4. AAPM. The Management of Respiratory Motion in Radiation Oncology Report of AAPM Task Group 76. 2006. Available from https://www.aapm.org/pubs/reports/rpt_91.pdf
5. Davies SC, Hill AL, Holmes RB, Halliwell M, Jackson PC. Ultrasound quantitation of respiratory organ motion in the upper abdomen. Br J Radiol. 1994; Available from https://doi.org/10.1259/0007-1285-67-803-1096
6. Korin HW, Ehman RL, Riederer SJ, Felmlee JP, Grimm RC. Respiratory kinematics of the upper abdominal organs: A quantitative study. Magn Reson Med. 1992; Available from https://doi.org/10.1002/mrm.1910230118
7. Kubo HD, Hill BC. Respiration gated radiotherapy treatment: A technical study. Phys Med Biol. 1996; Available from https://doi.org/10.1088/0031-9155/41/1/007
8. Chen QS, Weinhous MS, Deibel FC, Ciezki JP, Macklis RM. Fluoroscopic study of tumor motion due to breathing: Facilitating precise radiation therapy for lung cancer patients. Med Phys. 2001; Available from https://doi.org/10.1118/1.1398037
9. Giraud P, De Rycke Y, Dubray B, Helfre S, Voican D, Guo L, et al. Conformal radiotherapy (CRT) planning for lung cancer: Analysis of intrathoracic organ motion during extreme phases of breathing. Int J Radiat Oncol Biol Phys. 2001; Available from https://doi.org/10.1016/S0360-3016(01)01766-7
10. Pan H, Simpson DR, Mell LK, Mundt AJ, Lawson JD. A survey of stereotactic body radiotherapy use in the United States. Cancer. 2011. Available from https://doi.org/10.1002/cncr.26067
11. Baumann P, Nyman J, Lax I, Friesland S, Hoyer M, Ericsson SR, et al. Factors important for efficacy of stereotactic body radiotherapy of medically inoperable stage I lung cancer. A retrospective analysis of patients treated in the Nordic countries. Acta Oncol (Madr). 2006;45(7):787–95. Available from https://doi.org/10.1080/02841860600904862
12. Kini VR, Vedam SS, Keall PJ, Patil S, Chen C, Mohan R. Patient training in respiratory-gated radiotherapy. Med Dosim. 2003;28(1):7–11.Available from https://doi.org/10.1016/S0958-3947(02)00136-X
13. Underberg RWM, Lagerwaard FJ, Cuijpers JP, Slotman BJ, Van Sörnsen De Koste JR, Senan S. Four-dimensional CT scans for treatment planning in stereotactic radiotherapy for stage I lung cancer. Int J Radiat Oncol Biol Phys. 2004; Available from https://doi.org/10.1016/j.ijrobp.2004.07.665
14. Rietzel E, Pan T, Chen GTY. Four-dimensional computed tomography: Image formation and clinical protocol. Med Phys. 2005; Available from https://doi.org/10.1118/1.1869852
15. Vedam SS, Keall PJ, Kini VR, Mostafavi H, Shukla HP, Mohan R. Acquiring a four-dimensional computed tomography dataset using an external respiratory signal. Phys Med Biol. 2003;48(1):45–62. Available from https://doi.org/10.1088/0031-9155/48/1/304
16. Rietzel E, Chen GTY. Improving retrospective sorting of 4D computed tomography data. Med Phys. Available from https://doi.org/10.1118/1.2150780
17. Mutaf YD, Antolak JA, Brinkmann DH. The impact of temporal inaccuracies on 4DCT image quality. Med Phys. 2007;34(5):1615–22. Available from https://doi.org/10.1118/1.2717404.

Published

2021-09-30

How to Cite

Valani Marques de Sousa, J. ., Francisco Carmello Guimarães, L. ., & Milena. (2021). Desenvolvimento de um software de análise estatística do sinal respiratório para realização tomografia 4D. Brazilian Journal of Medical Physics, 15, 641. https://doi.org/10.29384/rbfm.2021.v15.19849001641

Issue

Section

Artigo Original

Most read articles by the same author(s)