Objective: In this study, it was aimed to evaluate the healthy and infected area volumes and elementary lesion characteristics in thorax computed tomography examinations of mild-moderate and severe patient groups according to the clinical severity scoring determined by the World Health Organization, and to compare the obtained findings with laboratory and clinical data.
📌 3 Key Takeaways
🎯
Objective & Hypothesis:Objective: In this study, it was aimed to evaluate the healthy and infected area volumes and elementary lesion characteristics in thorax computed tomography examinations of mild-moderate and severe patient groups according to the clinical severity scoring determined by the World Health Organization, and to compare the obtained findings with laboratory and clinical data.
📊
Key Findings & Data:Objective: In this study, it was aimed to evaluate the healthy and infected area volumes and elementary lesion characteristics in thorax computed tomography examinations of mild-moderate and severe patient groups according to the clinical severity scoring determined by the World Health Organization, and to compare the obtained findings with laboratory and clinical data.
💡
Conclusion & Impact:Objective: In this study, it was aimed to evaluate the healthy and infected area volumes and elementary lesion characteristics in thorax computed tomography examinations of mild-moderate and severe patient groups according to the clinical severity scoring determined by the World Health Organization, and to compare the obtained findings with laboratory and clinical data.
Objective: In this study, it was aimed to evaluate the healthy and infected area volumes and elementary lesion characteristics in thorax computed tomography examinations of mild-moderate and severe patient groups according to the clinical severity scoring determined by the World Health Organization, and to compare the obtained findings with laboratory and clinical data.
Özet
Amaç: Bu çalışmada, Dünya Sağlık Örgütü’nün belirlediği klinik şiddet skorlamasına göre hafif-orta grup ile ağır hasta gruplarının toraks bilgisayarlı tomografi tetkiklerinde sağlıklı ve enfekte alan volümleri ile elementer lezyon özelliklerinin değerlendirilmesi, elde edilen bulguların laboratuvar ve klinik verilerle karşılaştırılması amaçlanmıştır.
Köksal, M., Özkan, E., Gülbay, M., Bilir, Y. A., Akınci, E., Aypak, A., Güner, H. R. (2022). COMPARISON OF INFECTED LUNG VOLUME OF COVID-19 PATIENTS AND THEIR CLINIC AND LABORATORY DATA. Kırıkkale Üniversitesi Tıp Fakültesi Dergisi, Cilt: 24 Sayı: 1, 63–72. https://doi.org/10.24938/kutfd.1008677
Song F, Shi N, Shan F, Zhang Z, Shen J, Lu H et al. Emerging 2019 Novel Coronavirus (2019-nCoV) Pneumonia. Radiology. 2020;295(1):210-7.
Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W et al. Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology. 2020;296(2):E32-E40.
Tay MZ, Poh CM, Rénia L, MacAry PA, Ng LFP. The trinity of COVID-19: immunity, inflammation and intervention. Nat Rev Immunol. 2020;20(6):363-74.
Lin L, Lu L, Cao W, Li T. Hypothesis for potential pathogenesis of SARS-CoV-2 infection-a review of immune changes in patients with viral pneumonia. Emerg Microbes Infect. 2020;9(1):727-32.
Tian S, Xiong Y, Liu H, Niu L, Guo J, Liao M et al. Pathological study of the 2019 novel coronavirus disease (COVID-19) through postmortem core biopsies. Mod Pathol. 2020;33(6):1007-14.
Belen-Apak FB, Sarialioglu F. Pulmonary intravascular coagulation in COVID-19: possible pathogenesis and recommendations on anticoagulant/thrombolytic therapy. J Thromb Thrombolysis. 2020;50(2):278-80.
Felsenstein S, Herbert JA, McNamara PS, Hedrich CM. COVID-19: Immunology and treatment options. Clin Immunol. 2020;215:108448.
Zhang M, Lin B. Diagnostic Imaging of Novel Coronavirus Pneumonia. 1st ed. Springer, Singapore. Henan Science and Technology Press, 2020.
Li Y, Xia L. Coronavirus Disease 2019 (COVID-19): Role of Chest CT in Diagnosis and Management. AJR Am J Roentgenol. 2020;214(6):1280-6.
Zhao W, Zhong Z, Xie X, Yu Q, Liu J. Relation between chest CT findings and clinical conditions of Coronavirus Disease (COVID-19) pneumonia: A multicenter study. AJR Am J Roentgenol. 2020;214(5):1072-7.
Belfiore MP, Urraro F, Grassi R, Giacobbe G, Patelli G, Cappabianca S et al. Artificial intelligence to codify lung CT in Covid-19 patients. Radiol Med. 2020;125(5):500-4.
Grassi R, Belfiore MP, Montanelli A, Patelli G, Urraro F, Giacobbe G et al. COVID-19 pneumonia: computer-aided quantification of healthy lung parenchyma, emphysema, ground glass and consolidation on chest computed tomography (CT). Radiol Med. 2021;126(4):553-60.
Hosseiny M, Kooraki S, Gholamrezanezhad A, Reddy S, Myers L. Radiology perspective of Coronavirus Disease 2019 (COVID-19): Lessons from Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome. AJR Am J Roentgenol. 2020;214(5):1078-82.
Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507-13.
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.
Cheng Z, Qin L, Cao Q, Dai J, Pan A, Yang W et al. Quantitative computed tomography of the coronavirus disease 2019 (COVID-19) pneumonia. Radiol Infect Dis. 2020;7(2):55-61.
Colombi D, Bodini FC, Petrini M, Maffi G, Morelli N, Milanese G et al. Well-aerated lung on admitting chest CT to predict adverse outcome in Covid-19 pneumonia. Radiology. 2020;296(2):E86-E96.
Lanza E, Muglia R, Bolengo I, Santonocito OG, Lisi C, Angelotti G et al. Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation. Eur Radiol. 2020;30(12):6770-8.