Volume : 09, Issue : 12, December – 2022
Title:
24.ROLE OF CHEST COMPUTED TOMOGRAPHY SCANS IN THE EVALUATION OF CHEST MORPHOLOGY IN COVID-19 PATIENTS
Authors :
Ali Mohd Ali Alyami, Munassar Dakkam Lasloom, Hashan Dakkam Alsallum, Essa Alhashlan,Mohammed Ali Alammari
Abstract :
Objectives: This study aims to demonstrate the role of chest computed tomography scans in the evaluation of chest morphology in patients with a history of COVID-19.
Methodology: This study was conducted at King Khalid Hospital, Najran, Saudi Arabia, from January 2022 to May 2022.
The study sample included 100 patients with positive polymerase chain test, 64 slice units GE Medical Systems were used to examine patients with COVID-19.
Results: 100 patients with a positive polymerase chain for COVID-19 were included. Regarding the signs and symptoms, 48 (48%) of the 100 patients had a fever, and 22 (22%) of the 100 patients had a cough. The most frequent CT abnormalities observed were ground-glass opacity 32 (32%), consolidation (20, 20%), and interlobular septal thickening (17, 17%).
Moreover, The distribution of these findings was most common in the Subpleural zone (55, 55%) and the diffuse zone (31, 31%).
Conclusion: COVID-19 primarily impacts the Subpleural Zone, according to the studies. According to this study, the imaging hallmark of COVID-19 infection is ground-glass opacities and consolidation in the lung periphery. This finding could help physicians with limited healthcare resources predict cases with potentially higher mortality when treating patients.
Keywords: COVID-19, HRCT, Chest
Cite This Article:
Please cite this article in press Ali Mohd Ali Alyami et al, Role Of Chest Computed Tomography Scans In The Evaluation Of Chest Morphology In Covid-19 Patients.., Indo Am. J. P. Sci, 2022; 09(12).
Number of Downloads : 10
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2. Alsleem, H. A. A. H. M. (2020). The Feasibility of Contrast-to-Noise Ratio on Measurements to Evaluate CT Image Quality in Terms of Low-Contrast Detailed Detectability. Medical Sciences Medical Sciences, 8(3), 26.
3. Armitage, P. (1985). Multistage models of carcinogenesis. Environ Health Perspect, 63, 195-201. doi:10.1289/ehp.8563195
4. Aung, H. H., Sivakumar, A., Gholami, S. K., Venkateswaran, S. P., Gorain, B., & Shadab. (2019). Chapter 1 – An Overview of the Anatomy and Physiology of the Lung. In P. Kesharwani (Ed.), Nanotechnology-Based Targeted Drug Delivery Systems for Lung Cancer (pp. 1-20): Academic Press.
5. Bernheim, A., Mei, X., Huang, M., Yang, Y., Fayad, Z. A., Zhang, N., . . . Chung, M. (2020). Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection. Radiology, 295(3), 200463. doi:10.1148/radiol.2020200463
6. Bontranger, K. L., & Lampignano, K. L. B. J. P. (2005). Textbook of radiographic positioning and related anatomy. St. Louis, MO.: Elsevier Mosby.
7. Bos, L. D. J., Paulus, F., Vlaar, A. P. J., Beenen, L. F. M., & Schultz, M. J. (2020). Subphenotyping Acute Respiratory Distress Syndrome in Patients with COVID-19: Consequences for Ventilator Management. Annals of the American Thoracic Society, 17(9), 1161-1163. doi:10.1513/AnnalsATS.202004-376RL
8. Bösmüller, H., Matter, M., Fend, F., & Tzankov, A. (2021). The pulmonary pathology of COVID-19. Virchows Arch, 478(1), 137-150. doi:10.1007/s00428-021-03053-1
9. Brantigan, O. C. (1963). Clinical anatomy. New York: Blakiston Division, McGraw-Hill.
10. Bwire, G. M., Majigo, M. V., Njiro, B. J., & Mawazo, A. (2021). Detection profile of SARS-CoV-2 using RT-PCR in different types of clinical specimens: A systematic review and meta-analysis. J Med Virol, 93(2), 719-725. doi:10.1002/jmv.26349
11. Chaudhry, R., & Bordoni, B. (2022). Anatomy, Thorax, Lungs StatPearls. Treasure Island (FL): StatPearls Publishing
12. Copyright © 2022, StatPearls Publishing LLC.
13. Cheesman, K., & Burdett, E. (2011). Anatomy of the nose and pharynx. Anaesthesia & Intensive Care Medicine, 12(7), 283-286. doi:https://doi.org/10.1016/j.mpaic.2011.04.013
14. Drake, R. L. (2019). Gray’s anatomy for students and Paulsen : Sobotta, Atlas of anatomy.
15. Garvey, C. J., & Hanlon, R. (2002). Computed tomography in clinical practice. BMJ (Clinical research ed.), 324(7345), 1077-1080. doi:10.1136/bmj.324.7345.1077
16. Gattinoni, L., Caironi, P., Cressoni, M., Chiumello, D., Ranieri, V. M., Quintel, M., . . . Bugedo, G. (2006). Lung recruitment in patients with the acute respiratory distress syndrome. N Engl J Med, 354(17), 1775-1786. doi:10.1056/NEJMoa052052
17. Gruden, J. F., Naidich, D. P., Machnicki, S. C., Cohen, S. L., Girvin, F., & Raoof, S. (2020). An Algorithmic Approach to the Interpretation of Diffuse Lung Disease on Chest CT Imaging: A Theory of Almost Everything. Chest, 157(3), 612-635. doi:https://doi.org/10.1016/j.chest.2019.10.017
18. Hansen, J. T. M. C. A. G. D. M. G. (2022). Netter’s anatomy colouring book.
19. Kakinuma, R., Moriyama, N., Muramatsu, Y., Gomi, S., Suzuki, M., Nagasawa, H., . . . Asamura, H. (2015). Ultra-High-Resolution Computed Tomography of the Lung: Image Quality of a Prototype Scanner. PloS one, 10(9), e0137165-e0137165. doi:10.1371/journal.pone.0137165
20. Kalantari, H., Tabrizi, A. H. H., & Foroohi, F. (2020). Determination of COVID-19 prevalence with regards to the age range of patients referring to the hospitals located in western Tehran, Iran. Gene Rep, 21, 100910. doi:10.1016/j.genrep.2020.100910
21. Kanne, J. P. (2020). Chest CT Findings in 2019 Novel Coronavirus (2019-nCoV) Infections from Wuhan, China: Key Points for the Radiologist. Radiology, 295(1), 16-17. doi:10.1148/radiol.2020200241
22. Krueger, G. R. F. B. L. M. (2013). Atlas of Anatomic Pathology with Imaging: a Correlative Diagnostic Companion.
23. Kubo, T., Ohno, Y., Takenaka, D., Nishino, M., Gautam, S., Sugimura, K., . . . i, L. s. g. (2016). Standard-dose vs low-dose CT protocols in the evaluation of localized lung lesions: Capability for lesion characterization-iLEAD study. European journal of radiology open, 3, 67-73. doi:10.1016/j.ejro.2016.03.002
24. Lai-Fook, S. J. (2006). STRESS DISTRIBUTION IN THE LUNG. In G. J. Laurent & S. D. Shapiro (Eds.), Encyclopedia of Respiratory Medicine (pp. 124-131). Oxford: Academic Press.
25. Lott, D. G. (2015). Chapter 47 – Tissue Engineering of Larynx. In A. Vishwakarma, P. Sharpe, S. Shi, & M. Ramalingam (Eds.), Stem Cell Biology and Tissue Engineering in Dental Sciences (pp. 625-640). Boston: Academic Press.
26. Mahadevan, V. (2015). Anatomy of the heart. Surgery (Oxford), 33(2), 47-51. doi:https://doi.org/10.1016/j.mpsur.2014.12.001
27. Minnich, D. J., & Mathisen, D. J. (2007). Anatomy of the Trachea, Carina, and Bronchi. Thoracic Surgery Clinics, 17(4), 571-585. doi:https://doi.org/10.1016/j.thorsurg.2006.12.006
28. Organization, W. H. (2020). Novel Coronavirus (2019-nCoV) SITUATION REPORT – 1. Retrieved from https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200121-sitrep-1-2019-ncov.pdf?sfvrsn=20a99c10_4.
29. Patton, K. T. T. G. A. (2013). Anatomy & physiology.
30. Prevention, C. f. D. C. a. (2021). Post-COVID Conditions. Retrieved from https://www.cdc.gov/coronavirus/2019-ncov/long-term-effects/index.html
31. Prionas, N. D., Ray, S., & Boone, J. M. (2010). Volume assessment accuracy in computed tomography: a phantom study. Journal of applied clinical medical physics, 11(2), 3037-3037. doi:10.1120/jacmp.v11i2.3037
32. Riario Sforza, G. G., & Marinou, A. (2017). Hypersensitivity pneumonitis: a complex lung disease. Clinical and molecular allergy : CMA, 15, 6-6. doi:10.1186/s12948-017-0062-7
33. Song, F., Shi, N., Shan, F., Zhang, Z., Shen, J., Lu, H., . . . Shi, Y. (2020). Emerging 2019 Novel Coronavirus (2019-nCoV) Pneumonia. Radiology, 295(1), 210-217. doi:10.1148/radiol.2020200274
34. Sostre, S., Ashare, A. B., Quinones, J. D., Schieve, J. B., & Zimmerman, J. M. (1978). Thyroid scintigraphy: pinhole images versus rectilinear scans. Radiology, 129(3), 759-762. doi:10.1148/129.3.759
35. Vijayan, V. K. (2013). Chronic obstructive pulmonary disease. The Indian journal of medical research, 137(2), 251-269.
36. Waugh, A. G. A. (2022). ROSS & WILSON ANATOMY AND PHYSIOLOGY IN HEALTH AND ILLNESS. [S.l.]: ELSEVIER – HEALTH SCIENCE.
37. Webb, S. (1990). From the watching of shadows : the origins of radiological tomography. Bristol; New York: A. Hilger.
38. Wu, J., Wu, X., Zeng, W., Guo, D., Fang, Z., Chen, L., . . . Li, C. (2020). Chest CT Findings in Patients With Coronavirus Disease 2019 and Its Relationship With Clinical Features. Invest Radiol, 55(5).
39. Xiang, C. L. J. Z. J. G. L. Y. C. C. C. (2020). CT Findings in a Novel Coronavirus Disease (COVID-19) Pneumonia at Initial Presentation. Biomed Res Int BioMed research international, 2020, 5436025.
40. Xu, Z., Shi, L., Wang, Y., Zhang, J., Huang, L., Zhang, C., . . . Wang, F. S. (2020). Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med, 8(4), 420-422. doi:10.1016/S2213-2600(20)30076-X
41. Yang, R. L. X. L. H. Z. Y. Z. X. X. Q. L. Y. G. C. Z. W. (2020). Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19. Radiol Cardiothorac Imaging Radiology. Cardiothoracic Imaging, 2(2), e200047.