The study and estimation of absorbed and effective dose of corona patients under CT scan in Isfahan based ID Program

Subject Areas : Biomedical Spectroscopy, Microscopy, Imaging, Endoscopy

Ali Ebrahimzadeh Esfahani ¹ , sharifeh shahi ² , farsad zamani ³

1 - Department of Biomedical Engineering, Islamic Azad University of Isfahan (Khorasgan) branch, Isfahan, Iran
2 - Laser and Biophotonics research center in Biotechnologies, Islamic Azad university of Isfahan branch (Khorasgan), Isfahan, Iran
3 - Department of computer engineering, Faculty of engineering, Islamic Azad university of Isfahan branch (Khorasgen), Isfahan, Iran

Received: 2023-07-26 Accepted : 2023-09-10 Published : 2023-09-13

Keywords: Monte Carlo, absorbed dose, COVID-19, Effective dose, Lung CT, Impact dose,

Abstract :

Since the emergence of the coronavirus and the international community's attention to this virus, researchers and medical staff in hospitals have put approaches and methods for dealing with it and early diagnosis on their agenda. In this study, one of the method that called the Impact Dose program has been presented to calculate the absorbed and effective dose of people infected with the Covid-19 virus using CT scans of the respiratory tract. This is an analytical cross-sectional study that was conducted at Isfahan Shariati Hospital. The study is included of the 42 patients with Covid-19, who were selected based on doctor's opinion. The effective and absorbed dose were estimated by using the Impact Dose program, which is based on Monte Carlo. The data were analyzed using SPSS-24 software. The effective dose and DLP were reported as 1.67 mSv and 80.08 mGy.cm, respectively. The absorbed dose and effective dose were found to be higher in women than in men. The multiple CT scans of patients for the diagnosis of Covid-19 resulted in a very high absorbed dose, and lung sonography was recommended as an alternative method due to its high accuracy, similar to CT scans, in diagnosing pneumonia.

References:

• Ciotti, M. Ciccozzi, A. Terrino, W.-C. Jiang, Ch.-B. Wang, and S. Bernardin, “The COVID-19 pandemic,” Critical reviews in clinical laboratory sciences, vol. 57, pp. 365-388, 2020.‏


• I. Khan, J.L. Shah, and M.M. Bhat, “A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images,” Computer Methods and Programs in Biomedicine, Vol. 196, pp. 78-86, 2020.


• Saber, N. Hamzian, and F. Madadizadeh, “COVID-19 Anxiety and Related Factors in Cancer Patients Undergoing External Radiation Therapy,” Asian Pac. J. Cancer Prev.vol. 7, pp. 451-458, 2022.


• K. Verma and S. Prakash “Sadguru. Impact of covid-19 on environment and society,” Journal of Global Biosciences, vol. 9, pp. 7352-7363, 2020‏.‏


• Zhao, X. He, X. Yang, Y. Zhang, S. Zhang, and P. Xie “COVID-CT-dataset: a CT scan dataset about COVID-19,” arXiv preprint arXiv, vol. 42. pp. 849-851, 2020.‏


• Axiaq, A. Almohtadi, S.A. Massias, D. Ngemoh, and A. Harky. “The role of computed tomography scan in the diagnosis of COVID-19 pneumonia,” Curr Opin Pulm Med. vol. 27, pp. 163-168, 2021.‏


• Maltezos and A. Georgakopoulou, “Novel approach for Monte Carlo simulation of the new COVID-19 spread dynamics,” Infect. Genet. Evol.vol. 92, pp. 104896 (1-8), 2021.‏


• Gu, A. Dorgu, and X.G. Xu “Comparison of main software packages for CT dose reporting,” Health Phys, vol. 95, pp. S50, 2008.‏


• Ding, Y. Gao, H. Liu, P.F. Caracappa, D.J. Long, W.E. Bolch, B. Liu, and X.G. Xu “VirtualDose: a software for reporting organ doses from CT for adult and pediatric patients,” Phys. Med. Biol. Vol. 60, pp. 5601, 2015.‏


• Cristofaro, N. Fusco, A. Petrone , F. Albarello, F. Di Stefano , E. Pianura,V. Schininà, S. Ianniello, and P. Campioni, “Increased radiation dose exposure in thoracic computed tomography in patients with Covid-19,” Radiation, vol.1, pp. 153-161, 2021.‏


• Ghetti, O. Ortenzia, M. Maddalo, L. Altabella, and N. Sverzellati, “Dosimetric and radiation cancer risk evaluation of high resolution thorax CT during COVID-19 outbreak,” Phys Med. vol. 1, pp. 119-124, 2020.


• Kang, X. Li, and S Zhou, “Recommendation of low-dose CT in the detection and management of COVID-2019,” Eur. Radiol. Vol. 30, pp. 4356-4357, 2020.‏


• Volpicelli and L. Gargani, “Sonographic signs and patterns of COVID-19 pneumonia,” The Ultrasound Journal, vol. 12, pp. 1-3, 2020.