COVID-19 severity stratification using quantitative computed tomography analysis

Akın Çinkooğlu; Habib Ahmad Esmat; Mustafa Bozdağ; Selen Bayraktaroğlu; Naim Ceylan; Mehmet Soylu; Recep Savaş

doi:10.19161/etd.1363417

TR EN

Kantitatif bilgisayarlı tomografi analizi kullanılarak COVID-19 şiddet derecelendirilmesi

Öz

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.

Anahtar Kelimeler

COVID-19 severity stratification using quantitative computed tomography analysis

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

References

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Details

Primary Language

English

Subjects

Radiology and Organ Imaging

Journal Section

Research Article

Authors

Akın Çinkooğlu ^*
0000-0003-3396-3949
Türkiye

Habib Ahmad Esmat
0000-0001-5841-1601
Türkiye

Mustafa Bozdağ
0000-0002-0741-587X
Türkiye

Selen Bayraktaroğlu
0000-0001-9167-9474
Türkiye

Naim Ceylan
0000-0003-1128-0573
Türkiye

Mehmet Soylu
0000-0002-9145-1506
Türkiye

Recep Savaş
0000-0002-7520-760X
Türkiye

Publication Date

September 18, 2023

Submission Date

December 21, 2022

Acceptance Date

February 13, 2023

Published in Issue

Year 2023 Volume: 62 Number: 3

DOI

https://doi.org/10.19161/etd.1363417

IZ

https://izlik.org/JA53AT75SK

Cite

RIS / Bibtex

Vancouver

1.Akın Çinkooğlu, Habib Ahmad Esmat, Mustafa Bozdağ, Selen Bayraktaroğlu, Naim Ceylan, Mehmet Soylu, Recep Savaş. COVID-19 severity stratification using quantitative computed tomography analysis. EJM. 2023 Sep. 1;62(3):440-8. doi:10.19161/etd.1363417