Abstract
Aim: This study aimed to examine the utility of computer-assisted quantitative assessment of chest
computed tomography (CT) images in the stratification of Coronavirus Disease 2019 (COVID-19)
severity.
Materials and Methods: This study was designed as a retrospective, single-center study and
included a total of 142 RT-PCR-confirmed COVID-19 patients. CT findings were visually evaluated
and noted for their morphology and distribution characteristics. Visual semi-quantitative score (VSS)
and computer-aided quantitative score (CQS) were calculated. The utility of the approach was
assessed based on its ability to predict the patients who would require intensive care.
Results: The presence of underlying fibrosis, air bubble sign, and co-occurrence of central and
peripheral lung area involvement were the CT findings that were significantly more commonly
encountered in patients with intensive care requirements during the follow-up period. We found a
significant positive correlation between total VSS and CQS (p<0.001). Total CQSs were significantly
higher in ICU patients (n=19) than non-ICU patients (n=123) (p<0.001).
Conclusion: Computer-aided quantitative assessment appears to be a valuable tool for radiologists to
assess the severity of COVID-19 pneumonia.
Keywords
Ethical Statement
.
Supporting Institution
.
Thanks
.
References
- Diao K, Han P, Pang T, Li Y, Yang Z. HRCT imaging features in representative imported cases of 2019 novel coronavirus pneumonia. Precis Clin Med. 2020;3(1):9-13.
- Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients. AJR Am J Roentgenol. 2020;215(1):87-93.
- Ding X, Xu J, Zhou J, Long Q. Chest CT findings of COVID-19 pneumonia by duration of symptoms. Eur J Radiol.2020;127:109009.
- Pan F, Ye T, Sun P, et al. Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19). Radiology. 2020;295(3):715-21.
- Wasilewski PG, Mruk B, Mazur S, Półtorak-Szymczak G, Sklinda K, Walecki J. COVID-19 severity scoring systems in radiological imaging - a review. Pol J Radiol. 2020;85:e361-e368.
- Grassi R, Cappabianca S, Urraro F, et al. Chest CT Computerized Aided Quantification of PNEUMONIA Lesions in COVID-19 Infection: A Comparison among Three Commercial Software. Int J Environ Res Public Health. 2020;17(18):6914.
- Chung M, Bernheim A, Mei X, et al. CT Imaging Features of 2019 Novel Coronavirus (2019- nCoV). Radiology. 2020;295(1):202-7.
- Fang Y, Zhang H, Xie J, et al. Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR. Radiology. 2020;296(2):E115-E117.
- Yoon SH, Lee KH, Kim JY, et al. Chest Radiographic and CT Findings of the 2019 Novel Coronavirus Disease (COVID-19): Analysis of Nine Patients Treated in Korea. Korean J Radiol. 2020;21(4):494–500.
- Wu J, Wu X, Zeng W, et al. Chest CT Findings in Patients With Coronavirus Disease 2019 and Its Relationship With Clinical Features. Invest Radiol. 2020; 55(5):257–61.
- Çinkooğlu A, Hepdurgun C, Bayraktaroğlu S, Ceylan N, Savaş R. CT imaging features of COVID-19 pneumonia: initial experience from Turkey. Diagn Interv Radiol. 2020;26(4):308-14.
- Song F, Shi N, Shan F, et al. Emerging 2019 Novel Coronavirus (2019-nCoV) Pneumonia. Radiology. 2020;297(3):E346.
- Li M, Lei P, Zeng B, et al. Coronavirus Disease (COVID-19): Spectrum of CT Findings and Temporal Progression of the Disease. Acad Radiol. 2020;27(5):603-8.
- Ye Z, Zhang Y, Wang Y, Huang Z, Song B. Chest CT manifestations of new coronavirus disease 2019 (COVID-19): a pictorial review. Eur Radiol. 2020;30(8):4381-9.
- Li K, Fang Y, Li W, et al. CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19). Eur Radiol. 2020;30(8):4407-16.
- Yang R, Li X, Liu H, et al. Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19. Radiol Cardiothorac Imaging. 2020;2(2):e200047.
- Yuan M, Yin W, Tao Z, Tan W, Hu Y. Association of radiologic findings with mortality of patients infected with 2019 novel coronavirus in Wuhan, China. PLoS One. 2020;15(3):e0230548.
- Zhang K, Liu X, Shen J, et al. Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography. Cell. 2020;181(6):1423-33.
- Caruso D, Polici M, Zerunian M, et al. Quantitative Chest CT analysis in discriminating COVID-19 from nonCOVID-19 patients. Radiol Med. 2021;126(2):243-9.
- Cheng Z, Qin L, Cao Q, et al. Quantitative computed tomography of the coronavirus disease 2019 (COVID19) pneumonia. Radiol Infect Dis. 2020;7(2):55-61.
- Yin X, Min X, Nan Y, et al. Assessment of the Severity of Coronavirus Disease: Quantitative Computed Tomography Parameters versus Semiquantitative Visual Score. Korean J Radiol. 2020;21(8):998-1006.
- Ufuk F, Demirci M, Uğurlu E, Çetin N, Yiğit N, Sarı T. Evaluation of disease severity with quantitative chest CT in COVID-19 patients. Diagn Interv Radiol. 2021;27(2):164-171.
- Gürün E. , Akdulum İ. , Akyüz M. Revealing the dilemma in COVID-19 pneumonia: use of the prone thorax CT imaging in differentiation of opacificities due to dependant zone and pneumonic consolidation. Anatolian Curr Med J. 2021; 3(1): 78-80.
Abstract
Amaç: Bu çalışma, Koronavirüs Hastalığı 2019 (COVID-19) şiddetinin sınıflandırılmasında göğüs
bilgisayarlı tomografi (BT) görüntülerinin bilgisayar destekli kantitatif değerlendirmesinin faydasını
incelemeyi amaçlamıştır.
Araçlar ve Yöntem: 142 RT-PCR COVID-19 hastasını içeren retrospektif, tek-merkezli bir çalışma
tasarladık. Morfoloji ve dağılım özelliklerine göre BT bulgularının görsel değerlendirmesi not edildi.
Görsel yarı kantitatif skor (GKS) ve bilgisayar destekli kantitatif skor (BKS) hesaplandı. Yaklaşımın
faydası, yoğun bakıma ihtiyaç duyacak hastaları tahmin etme yeteneğine göre değerlendirildi.
Bulgular: Altta yatan fibrozis varlığı, hava kabarcığı bulgusu, santral ve periferik akciğer alanı
tutulumu birlikteliği takip döneminde yoğun bakıma ihtiyacı olan hastaların BT görüntülerinde anlamlı
olarak daha yüksek oranda görülen bulgulardı. Total GKS'lar ve BKS'lar arasında anlamlı pozitif
korelasyon saptadık (p<0.001). YBÜ hastalarının (s=19) toplam BKS'ları, YBÜ’de olmayan
hastalardan (s=123) anlamlı derecede yüksek saptandı. (p<0.001).
Sonuç: Bilgisayar destekli kantitatif değerlendirme, radyologların COVID-19 pnömonisinin şiddetini
değerlendirmeleri için değerli bir araç gibi görünmektedir.
References
- Diao K, Han P, Pang T, Li Y, Yang Z. HRCT imaging features in representative imported cases of 2019 novel coronavirus pneumonia. Precis Clin Med. 2020;3(1):9-13.
- Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients. AJR Am J Roentgenol. 2020;215(1):87-93.
- Ding X, Xu J, Zhou J, Long Q. Chest CT findings of COVID-19 pneumonia by duration of symptoms. Eur J Radiol.2020;127:109009.
- Pan F, Ye T, Sun P, et al. Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19). Radiology. 2020;295(3):715-21.
- Wasilewski PG, Mruk B, Mazur S, Półtorak-Szymczak G, Sklinda K, Walecki J. COVID-19 severity scoring systems in radiological imaging - a review. Pol J Radiol. 2020;85:e361-e368.
- Grassi R, Cappabianca S, Urraro F, et al. Chest CT Computerized Aided Quantification of PNEUMONIA Lesions in COVID-19 Infection: A Comparison among Three Commercial Software. Int J Environ Res Public Health. 2020;17(18):6914.
- Chung M, Bernheim A, Mei X, et al. CT Imaging Features of 2019 Novel Coronavirus (2019- nCoV). Radiology. 2020;295(1):202-7.
- Fang Y, Zhang H, Xie J, et al. Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR. Radiology. 2020;296(2):E115-E117.
- Yoon SH, Lee KH, Kim JY, et al. Chest Radiographic and CT Findings of the 2019 Novel Coronavirus Disease (COVID-19): Analysis of Nine Patients Treated in Korea. Korean J Radiol. 2020;21(4):494–500.
- Wu J, Wu X, Zeng W, et al. Chest CT Findings in Patients With Coronavirus Disease 2019 and Its Relationship With Clinical Features. Invest Radiol. 2020; 55(5):257–61.
- Çinkooğlu A, Hepdurgun C, Bayraktaroğlu S, Ceylan N, Savaş R. CT imaging features of COVID-19 pneumonia: initial experience from Turkey. Diagn Interv Radiol. 2020;26(4):308-14.
- Song F, Shi N, Shan F, et al. Emerging 2019 Novel Coronavirus (2019-nCoV) Pneumonia. Radiology. 2020;297(3):E346.
- Li M, Lei P, Zeng B, et al. Coronavirus Disease (COVID-19): Spectrum of CT Findings and Temporal Progression of the Disease. Acad Radiol. 2020;27(5):603-8.
- Ye Z, Zhang Y, Wang Y, Huang Z, Song B. Chest CT manifestations of new coronavirus disease 2019 (COVID-19): a pictorial review. Eur Radiol. 2020;30(8):4381-9.
- Li K, Fang Y, Li W, et al. CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19). Eur Radiol. 2020;30(8):4407-16.
- Yang R, Li X, Liu H, et al. Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19. Radiol Cardiothorac Imaging. 2020;2(2):e200047.
- Yuan M, Yin W, Tao Z, Tan W, Hu Y. Association of radiologic findings with mortality of patients infected with 2019 novel coronavirus in Wuhan, China. PLoS One. 2020;15(3):e0230548.
- Zhang K, Liu X, Shen J, et al. Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography. Cell. 2020;181(6):1423-33.
- Caruso D, Polici M, Zerunian M, et al. Quantitative Chest CT analysis in discriminating COVID-19 from nonCOVID-19 patients. Radiol Med. 2021;126(2):243-9.
- Cheng Z, Qin L, Cao Q, et al. Quantitative computed tomography of the coronavirus disease 2019 (COVID19) pneumonia. Radiol Infect Dis. 2020;7(2):55-61.
- Yin X, Min X, Nan Y, et al. Assessment of the Severity of Coronavirus Disease: Quantitative Computed Tomography Parameters versus Semiquantitative Visual Score. Korean J Radiol. 2020;21(8):998-1006.
- Ufuk F, Demirci M, Uğurlu E, Çetin N, Yiğit N, Sarı T. Evaluation of disease severity with quantitative chest CT in COVID-19 patients. Diagn Interv Radiol. 2021;27(2):164-171.
- Gürün E. , Akdulum İ. , Akyüz M. Revealing the dilemma in COVID-19 pneumonia: use of the prone thorax CT imaging in differentiation of opacificities due to dependant zone and pneumonic consolidation. Anatolian Curr Med J. 2021; 3(1): 78-80.
Details
| Primary Language | English |
|---|---|
| Subjects | Radiology and Organ Imaging |
| Journal Section | Research Articles |
| Authors | |
| Publication Date | September 18, 2023 |
| Submission Date | December 21, 2022 |
| Published in Issue | Year 2023Volume: 62 Issue: 3 |
