Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study

Abdulaziz Hussein; Saida Abdalkreem; Duha Abdu; Abdelmonem Adam; Mohammed Khalifa; Aseif Abdalla; Sayd Ahmed Mohammed; Ahmed Balil

doi:doi:10.11648/j.ijmi.20221002.13

Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study

Abdulaziz Hussein, Saida Abdalkreem, Duha Abdu, Abdelmonem Adam, Mohammed Khalifa, Aseif Abdalla, Sayd Ahmed Mohammed, Ahmed Balil

Published in International Journal of Medical Imaging (Volume 10, Issue 2)

Received: 19 May 2022 Accepted: 1 June 2022 Published: 8 June 2022

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Background: Following the emergence of COVID-19, chest CT exams were utilized as a supplement to RT-PCR for diagnosis and follow-up when RTPCR findings became unavailable. Aims: characterize the patterns and severity of COVID-19 using high resolution computed tomography among Sudanese patients in Jabra Isolation Center, Khartoum State. methods and Materials: A total of 50 patients having COVID-19 who had chest CT and were confirmed positively by RT-PCR were involved in this study. clinical and laboratory data were collected by reviewing the hard medical records. radiology abnormalities were categorized based upon the patterns and distribution within the lungs. The CT-SS was determined by adding individual scores from each of the six lung regions; rated by Likert scale as 0 (0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), or 4 (76–100%). The total severity score was reached by summing the sex lobe scores into mild and severe cases. Results: (33 were men and 17 were women, 26 patients have more than 60 years, they were the majority age group, There were 28 cases of mild and 22 cases of severe disease). Study found that (COVID-19) was distributed as Multi-lesions in 46 cases (92%), bilaterally, and diffused within the lung fields in (39,77%, 41,81% respectively). Peripheral ground glass opacities patterns (GGOs) were the most domain feature. There was a significant difference in distribution of disease between right and left lungs (p < 0.05). Where the right lung was the most infected in both mild and severe cases. The lower lobes of both lungs were the most involved sites by COVID-19 in compare with the upper and middle lobes in both lungs. Conclusions: In COVID-19, thin-section high-resolution chest CT is a critical medical imaging tool for detecting the lung parenchymal diseases. Semi-quantitative CT scoring system can be used to assess the severity of lung involvement rapidly and effectively.

Published in	International Journal of Medical Imaging (Volume 10, Issue 2)
DOI	10.11648/j.ijmi.20221002.13
Page(s)	22-28
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

COVID-19, HRCT, Ground Glass Opacities, CT Scoring System

References

[1]	Zhu N, Zhang D, Wang W, et al. A Novel Coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020; 382 (8): 727–733.
[2]	Li Q, Guan X, Wu P, et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. N Engl J Med 2020 Jan 29 [Epub ahead of print].
[3]	Chinese Society of Radiology. Radiological Diagnosis of New Coronavirus Infected Pneumonitis: Expert Recommendation from the Chinese Society of Radiology (First edition). Chin J Radiol 2020; 54: E001.
[4]	Paul NS, Roberts H, Butany J, et al. Radiologic pattern of disease in patients with severe acute respiratory syndrome: the Toronto experience. RadioGraphics 2004; 24 (2): 553–563.
[5]	Mukherjee S, Pahan K. Is COVID-19 gender-sensitive? Journal of Neuroimmune Pharmacology. 2021 Mar; 16 (1): 38-47.
[6]	Assiri A, Al-Tawfi JA, Al-Rabeeah AA, et al. Epidemiological, demographic, and clinical characteristics of 47 cases of Middle East respiratory syndrome coronavirus disease from Saudi Arabia: a descriptive study. Lancet Infect Dis 2013; 13 (9): 752–761.
[7]	Lee N, Hui D, Wu A, et al. A major outbreak of severe acute respiratory syndrome in Hong Kong. N Engl J Med 2003; 348 (20): 1986–1994.
[8]	Baj J, Karakuła-Juchnowicz H, Teresiński G, Buszewicz G, Ciesielka M, Sitarz E, Forma A, Karakuła K, Flieger W, Portincasa P, Maciejewski R. COVID-19: Specific and Non-Specific Clinical Manifestations and Symptoms: The Current State of Knowledge. J Clin Med. 2020 Jun 5; 9 (6): 1753. doi: 10.3390/jcm9061753. PMID: 32516940; PMCID: PMC7356953.
[9]	Li S, Liu S, Wang B, Li Q, Zhang H, Zeng L, Ge H, Ma Q, Shen N. Predictive value of chest CT scoring in COVID-19 patients in Wuhan, China: a retrospective cohort study. Respiratory Medicine. 2021 Jan 1; 176: 106271.
[10]	Ng MY, Lee EYP, Yang J, et al. Imaging profie of the COVID-19 infection: radiologic fidings and literature review. Radiol Cardiothorac Imaging 2020; 2 (1): e200034.
[11]	Lei J, Li J, Li X, Qi X. CT Imaging of the 2019 Novel Coronavirus (2019- nCoV) Pneumonia. Radiology 2020; 295 (1): 18.
[12]	Liu P, Tan XZ. 2019 Novel Coronavirus (2019-nCoV) Pneumonia. Radiology 2020; 295 (1): 19. 22.
[13]	Chung M, Bernheim A, Mei X, et al. CT imaging features of 2019 Novel Coronavirus (2019-nCoV). Radiology 2020; 295 (1): 202–207.
[14]	Jee, Youngmee. “WHO International Health Regulations Emergency Committee for the COVID-19 outbreak.” Epidemiology and health vol. 42 (2020): e2020013. doi: 10.4178/epih.e2020013.
[15]	Saleemi S, Alhajji M, Almaghrabi R. Clinical characteristics of patients with COVID-19 in Saudi Arabia-a single center experience. Res Rev Infect Dis. 2020; 3 (1): 68-74.
[16]	Ng MY, Lee EY, Yang J, Yang F, Li X, Wang H, Lui MM, Lo CS, Leung B, Khong PL, Hui CK. Imaging profile of the COVID-19 infection: radiologic findings and literature review. Radiology: Cardiothoracic Imaging. 2020 Feb 13; 2 (1): e200034.
[17]	Mukherjee, Shreya, and Kalipada Pahan. “Is COVID-19 Gender-sensitive?” Journal of neuroimmune pharmacology: the official journal of the Society on NeuroImmune Pharmacology vol. 16, 1 (2021): 38-47. doi: 10.1007/s11481-020-09974-z.
[18]	Jordan, Rachel E., Peymane Adab, and KK32217618 Cheng. "COVID-19: risk factors for severe disease and death." Bmj 368 (2020).
[19]	Centers for Disease Control and Prevention (CDC); available at: https://www.cdc.gov/aging/covid19/covid19-older-adults.html#increased-risk . Accessed on March 24, 2022. Last reviewed: August 2, 2021.
[20]	Yang R, Li X, Liu H, Zhen Y, Zhang X, Xiong Q, Luo Y, Gao C, Zeng W. Chest CT severity score: an imaging tool for assessing severe COVID-19. Radiology: Cardiothoracic Imaging. 2020 Mar 30; 2 (2): e200047.
[21]	Li K, Fang Y, Li W, Pan C, Qin P, Zhong Y, Liu X, Huang M, Liao Y, Li S. CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19). Eur Radiol. 2020 Aug; 30 (8): 4407- 4416. doi: 10.1007/s00330-020-06817-6. Epub 2020 Mar 25. PMID: 32215691; PMCID: PMC7095246.
[22]	Haseli S, Khalili N, Bakhshayeshkaram M, Sanei Taheri M, Moharramzad Y. Lobar Distribution of COVID-19 Pneumonia Based on Chest Computed Tomography Findings; A Retrospective Study. Arch Acad Emerg Med. 2020 Apr 18; 8 (1): e55. PMID: 32440666; PMCID: PMC7212068.
[23]	Gold JA, Wong KK, Szablewski CM, Patel PR, Rossow J, Da Silva J, Natarajan P, Morris SB, Fanfair RN, Rogers-Brown J, Bruce BB. Characteristics and clinical outcomes of adult patients hospitalized with COVID-19—Georgia, March 2020. Morbidity and Mortality Weekly Report. 2020 May 8; 69 (18): 545.
[24]	Gurumurthy, Balasubramanian et al. “Spectrum of atypical pulmonary manifestations of COVID-19 on computed tomography.” The Egyptian Journal of Radiology and Nuclear Medicine vol. 52, 1 (2021): 72. doi: 10.1186/s43055-021-00448-7.
[25]	Rokaya Rehouma, Michael Buchert, Yi-Ping Phoebe Chen. "Machine learning for medical imaging-based COVID-19 detection and diagnosis", International Journal of Intelligent Systems, 2021.

Cite This Article

Plain Text BibTeX RIS

APA Style

Abdulaziz Hussein, Saida Abdalkreem, Duha Abdu, Abdelmonem Adam, Mohammed Khalifa, et al. (2022). Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study. International Journal of Medical Imaging, 10(2), 22-28. https://doi.org/10.11648/j.ijmi.20221002.13

Copy | Download

ACS Style

Abdulaziz Hussein; Saida Abdalkreem; Duha Abdu; Abdelmonem Adam; Mohammed Khalifa, et al. Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study. Int. J. Med. Imaging 2022, 10(2), 22-28. doi: 10.11648/j.ijmi.20221002.13

Copy | Download

AMA Style

Abdulaziz Hussein, Saida Abdalkreem, Duha Abdu, Abdelmonem Adam, Mohammed Khalifa, et al. Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study. Int J Med Imaging. 2022;10(2):22-28. doi: 10.11648/j.ijmi.20221002.13

Copy | Download

@article{10.11648/j.ijmi.20221002.13,
  author = {Abdulaziz Hussein and Saida Abdalkreem and Duha Abdu and Abdelmonem Adam and Mohammed Khalifa and Aseif Abdalla and Sayd Ahmed Mohammed and Ahmed Balil},
  title = {Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study},
  journal = {International Journal of Medical Imaging},
  volume = {10},
  number = {2},
  pages = {22-28},
  doi = {10.11648/j.ijmi.20221002.13},
  url = {https://doi.org/10.11648/j.ijmi.20221002.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmi.20221002.13},
  abstract = {Background: Following the emergence of COVID-19, chest CT exams were utilized as a supplement to RT-PCR for diagnosis and follow-up when RTPCR findings became unavailable. Aims: characterize the patterns and severity of COVID-19 using high resolution computed tomography among Sudanese patients in Jabra Isolation Center, Khartoum State. methods and Materials: A total of 50 patients having COVID-19 who had chest CT and were confirmed positively by RT-PCR were involved in this study. clinical and laboratory data were collected by reviewing the hard medical records. radiology abnormalities were categorized based upon the patterns and distribution within the lungs. The CT-SS was determined by adding individual scores from each of the six lung regions; rated by Likert scale as 0 (0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), or 4 (76–100%). The total severity score was reached by summing the sex lobe scores into mild and severe cases. Results: (33 were men and 17 were women, 26 patients have more than 60 years, they were the majority age group, There were 28 cases of mild and 22 cases of severe disease). Study found that (COVID-19) was distributed as Multi-lesions in 46 cases (92%), bilaterally, and diffused within the lung fields in (39,77%, 41,81% respectively). Peripheral ground glass opacities patterns (GGOs) were the most domain feature. There was a significant difference in distribution of disease between right and left lungs (p Conclusions: In COVID-19, thin-section high-resolution chest CT is a critical medical imaging tool for detecting the lung parenchymal diseases. Semi-quantitative CT scoring system can be used to assess the severity of lung involvement rapidly and effectively.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study
AU  - Abdulaziz Hussein
AU  - Saida Abdalkreem
AU  - Duha Abdu
AU  - Abdelmonem Adam
AU  - Mohammed Khalifa
AU  - Aseif Abdalla
AU  - Sayd Ahmed Mohammed
AU  - Ahmed Balil
Y1  - 2022/06/08
PY  - 2022
N1  - https://doi.org/10.11648/j.ijmi.20221002.13
DO  - 10.11648/j.ijmi.20221002.13
T2  - International Journal of Medical Imaging
JF  - International Journal of Medical Imaging
JO  - International Journal of Medical Imaging
SP  - 22
EP  - 28
PB  - Science Publishing Group
SN  - 2330-832X
UR  - https://doi.org/10.11648/j.ijmi.20221002.13
AB  - Background: Following the emergence of COVID-19, chest CT exams were utilized as a supplement to RT-PCR for diagnosis and follow-up when RTPCR findings became unavailable. Aims: characterize the patterns and severity of COVID-19 using high resolution computed tomography among Sudanese patients in Jabra Isolation Center, Khartoum State. methods and Materials: A total of 50 patients having COVID-19 who had chest CT and were confirmed positively by RT-PCR were involved in this study. clinical and laboratory data were collected by reviewing the hard medical records. radiology abnormalities were categorized based upon the patterns and distribution within the lungs. The CT-SS was determined by adding individual scores from each of the six lung regions; rated by Likert scale as 0 (0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), or 4 (76–100%). The total severity score was reached by summing the sex lobe scores into mild and severe cases. Results: (33 were men and 17 were women, 26 patients have more than 60 years, they were the majority age group, There were 28 cases of mild and 22 cases of severe disease). Study found that (COVID-19) was distributed as Multi-lesions in 46 cases (92%), bilaterally, and diffused within the lung fields in (39,77%, 41,81% respectively). Peripheral ground glass opacities patterns (GGOs) were the most domain feature. There was a significant difference in distribution of disease between right and left lungs (p Conclusions: In COVID-19, thin-section high-resolution chest CT is a critical medical imaging tool for detecting the lung parenchymal diseases. Semi-quantitative CT scoring system can be used to assess the severity of lung involvement rapidly and effectively.
VL  - 10
IS  - 2
ER  -

Copy | Download

Author Information

Abdulaziz Hussein

College of Medical Radiological Science, Sudan University of Science and Technology, Khartoum, Sudan
Saida Abdalkreem

College of Medical Radiological Science, Sudan University of Science and Technology, Khartoum, Sudan
Duha Abdu

College of Medical Radiological Science, Sudan University of Science and Technology, Khartoum, Sudan
Abdelmonem Adam

College of Medical Radiological Science, Sudan University of Science and Technology, Khartoum, Sudan
Mohammed Khalifa

College of Medical Radiological Science, Sudan University of Science and Technology, Khartoum, Sudan
Aseif Abdalla

College of Medical Radiological Science, Sudan University of Science and Technology, Khartoum, Sudan
Sayd Ahmed Mohammed

College of Medical Radiological Science, Sudan University of Science and Technology, Khartoum, Sudan
Ahmed Balil

College of Medical Radiological Science, Sudan University of Science and Technology, Khartoum, Sudan

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Abdulaziz Hussein, Saida Abdalkreem, Duha Abdu, Abdelmonem Adam, Mohammed Khalifa, et al. (2022). Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study. International Journal of Medical Imaging, 10(2), 22-28. https://doi.org/10.11648/j.ijmi.20221002.13

Copy | Download

ACS Style

Abdulaziz Hussein; Saida Abdalkreem; Duha Abdu; Abdelmonem Adam; Mohammed Khalifa, et al. Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study. Int. J. Med. Imaging 2022, 10(2), 22-28. doi: 10.11648/j.ijmi.20221002.13

Copy | Download

AMA Style

Abdulaziz Hussein, Saida Abdalkreem, Duha Abdu, Abdelmonem Adam, Mohammed Khalifa, et al. Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study. Int J Med Imaging. 2022;10(2):22-28. doi: 10.11648/j.ijmi.20221002.13

Copy | Download

@article{10.11648/j.ijmi.20221002.13,
  author = {Abdulaziz Hussein and Saida Abdalkreem and Duha Abdu and Abdelmonem Adam and Mohammed Khalifa and Aseif Abdalla and Sayd Ahmed Mohammed and Ahmed Balil},
  title = {Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study},
  journal = {International Journal of Medical Imaging},
  volume = {10},
  number = {2},
  pages = {22-28},
  doi = {10.11648/j.ijmi.20221002.13},
  url = {https://doi.org/10.11648/j.ijmi.20221002.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmi.20221002.13},
  abstract = {Background: Following the emergence of COVID-19, chest CT exams were utilized as a supplement to RT-PCR for diagnosis and follow-up when RTPCR findings became unavailable. Aims: characterize the patterns and severity of COVID-19 using high resolution computed tomography among Sudanese patients in Jabra Isolation Center, Khartoum State. methods and Materials: A total of 50 patients having COVID-19 who had chest CT and were confirmed positively by RT-PCR were involved in this study. clinical and laboratory data were collected by reviewing the hard medical records. radiology abnormalities were categorized based upon the patterns and distribution within the lungs. The CT-SS was determined by adding individual scores from each of the six lung regions; rated by Likert scale as 0 (0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), or 4 (76–100%). The total severity score was reached by summing the sex lobe scores into mild and severe cases. Results: (33 were men and 17 were women, 26 patients have more than 60 years, they were the majority age group, There were 28 cases of mild and 22 cases of severe disease). Study found that (COVID-19) was distributed as Multi-lesions in 46 cases (92%), bilaterally, and diffused within the lung fields in (39,77%, 41,81% respectively). Peripheral ground glass opacities patterns (GGOs) were the most domain feature. There was a significant difference in distribution of disease between right and left lungs (p Conclusions: In COVID-19, thin-section high-resolution chest CT is a critical medical imaging tool for detecting the lung parenchymal diseases. Semi-quantitative CT scoring system can be used to assess the severity of lung involvement rapidly and effectively.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Severity and Patterns of COVID-19 Among Sudanese Patients Using High Resolution Computed Tomography: Jabra Isolation Centre Based Study
AU  - Abdulaziz Hussein
AU  - Saida Abdalkreem
AU  - Duha Abdu
AU  - Abdelmonem Adam
AU  - Mohammed Khalifa
AU  - Aseif Abdalla
AU  - Sayd Ahmed Mohammed
AU  - Ahmed Balil
Y1  - 2022/06/08
PY  - 2022
N1  - https://doi.org/10.11648/j.ijmi.20221002.13
DO  - 10.11648/j.ijmi.20221002.13
T2  - International Journal of Medical Imaging
JF  - International Journal of Medical Imaging
JO  - International Journal of Medical Imaging
SP  - 22
EP  - 28
PB  - Science Publishing Group
SN  - 2330-832X
UR  - https://doi.org/10.11648/j.ijmi.20221002.13
AB  - Background: Following the emergence of COVID-19, chest CT exams were utilized as a supplement to RT-PCR for diagnosis and follow-up when RTPCR findings became unavailable. Aims: characterize the patterns and severity of COVID-19 using high resolution computed tomography among Sudanese patients in Jabra Isolation Center, Khartoum State. methods and Materials: A total of 50 patients having COVID-19 who had chest CT and were confirmed positively by RT-PCR were involved in this study. clinical and laboratory data were collected by reviewing the hard medical records. radiology abnormalities were categorized based upon the patterns and distribution within the lungs. The CT-SS was determined by adding individual scores from each of the six lung regions; rated by Likert scale as 0 (0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), or 4 (76–100%). The total severity score was reached by summing the sex lobe scores into mild and severe cases. Results: (33 were men and 17 were women, 26 patients have more than 60 years, they were the majority age group, There were 28 cases of mild and 22 cases of severe disease). Study found that (COVID-19) was distributed as Multi-lesions in 46 cases (92%), bilaterally, and diffused within the lung fields in (39,77%, 41,81% respectively). Peripheral ground glass opacities patterns (GGOs) were the most domain feature. There was a significant difference in distribution of disease between right and left lungs (p Conclusions: In COVID-19, thin-section high-resolution chest CT is a critical medical imaging tool for detecting the lung parenchymal diseases. Semi-quantitative CT scoring system can be used to assess the severity of lung involvement rapidly and effectively.
VL  - 10
IS  - 2
ER  -

Copy | Download