COVID-19 pnömonisinin akciğer hacmi üzerindeki etkilerinin kantitatif bilgisayarlı tomografi ile değerlendirilmesi

Year 2022, , 415 - 425, 31.03.2022

Ayşe Özlem Balık , Buket Yağcı

https://doi.org/10.17826/cumj.1030243

Abstract

Amaç: Bu çalışmanın amacı COVID-19 pnömonisi olan hastalarda erken dönemde akciğer hacim azalması ile bilgisayarlı tomografi (BT) bulguları arasındaki ilişkiyi değerlendirmektir.
Gereç ve Yöntem: Çalışmaya inceleme kriterlerini karşılayan elli dört hasta dahil edildi. Hastaların her bir akciğeri için yazılım tabanlı kantitatif BT ile ölçüm yapılarak akciğer hacimleri hesaplandı. Hastalara ait demografik veriler, komorbidite ve sigara içme durumu, BT'deki inflamasyon bulguları, akciğer parankimindeki tutulum miktarını gösteren BT şiddet skorlaması ile ilk ve takip BT'lerindeki akciğer hacmindeki değişiklikler (azalma) arasındaki ilişki değerlendirildi.
Bulgular: Hacim azalma oranı, yaş, cinsiyet, sigara içme veya hastanede yatış durumu ile istatistiksel olarak ilişkili değildi. Takip BT lerinde akciğer hacmi ve ciddiyet skorlaması arasındaki korelasyon incelendiğinde, sağ akciğerde (r = -0.583; p = 0.001) ve sol akciğerde (r = -0.478; p = 0.001) iyi derecede ters korelasyon vardı. Sağ akciğer hacmindeki azalma oranı komorbiditesi olan hastalarda diğer hastalara göre anlamlı derecede yüksekti. Sağ akciğerde hacim kaybı ile ciddiyet skoru arasında istatistiksel olarak orta derecede ters korelasyon varken (r = -0.294; p = 0.031) ve sol akciğerde anlamlı bir korelasyon bulunmadı (r = -0.096; p = 0.489).
Sonuç: COVID-19 pnömonisi olan hastalarda parankimal tutulum miktarı ile birlikte akciğer hasarı oranı ve buna bağlı hacim azalması artar. Bu değişiklik komorbiditesi olanlarda daha sık görülmektedir. BT bulgularının nicel verilerle doğru yorumlanması, hekimlerin hastalığı yönetmesine yardımcı olabilir.

Keywords

• COVID-19 virüs, Akciğer volüm ölçümleri, Çok kesitli bilgisayarlı tomografi, Kantitatif, Pulmoner fibrozis

Supporting Institution

-

Project Number

2020/KK/201-2927

Thanks

Dr. Güven Mengü ve Dr. Sırma Tilev'e makalenin yazım diline verdikleri destekten dolayı teşekkür ederiz.

Quantitative computerized tomography evaluation of the effects of COVID-19 pneumonia on lung volume

Abstract

Purpose: The aim of this study was o assess the relationship between lung volume decrease and computed tomography (CT) findings in patients with COVID-19 pneumonia in early period.
Materials and Methods: Fifty-four patients were included in the study. The lung volume (LV) was calculated separately for each lung by software-based quantitative CT (QCT). Patient demographics, comorbidity and smoking status, CT findings, visual semi-quantitative CT severity scoring (CT-SS), and decrease of LV were analyzed.
Results: The rate of volume decrease was not statistically related to, age, gender, smoking, or hospitalization status. When the correlation between follow-up CT (FUCT) LV and CT-SS was examined there were good inverse correlation on the right lung (r = -0.583; p = 0.001) and left lung (r = -0.478; p = 0.001). The rate of decrease in the right LV was significantly higher in patients with comorbidities compared to other patients. There was a statistically moderate inverse correlation between decrease of LV and CT-SS in the right lung (r = -0.294; p = 0.031), and no significant correlation was found between the decrease of LV and CT-SS in the left lung (r = -0.096; p = 0.489).
Conclusion: The rate of lung damage and associated volume decrease both increase with the amount of parenchymal involvement in patients with COVID-19 pneumonia. This change is more frequent in patients with multiple comorbidities. Accurate interpretation of CT findings with quantitative data can help physicians to manage the disease.

Keywords

COVID-19, lung volume measurements, multidetector computed tomography, quantitative, pulmonary fibrosis.

Project Number

2020/KK/201-2927

References

• Gavriatopoulou M, Korompoki E, Fotiou D, Ntanasis-Stathopoulos I, Psaltopoulou T, Kastritis E et al. Organ-specific manifestations of COVID-19 infection. Clin Exp Med. 2020;20:493-506.
• Zhang T, Sun LX, Feng RE. Comparison of clinical and pathological features between severe acute respiratory syndrome and coronavirus disease 2019. Zhonghua Jie He He Hu Xi Za Zhi. 2020;43:496-502.
• Otoupalova E, Smith S, Cheng G, Thannickal VJ. Oxidative stress in pulmonary fibrosis. Compr Physiol. 2020;10:509-47.
• Zhou S, Wang Y, Zhu T, Xia L. CT features of coronavirus disease 2019 (COVID-19) pneumonia in 62 patients in Wuhan, China. Ajr Am J Roentgenol, 2020;214:1287-94.
• Shen C, Yu N, Cai S, Zhou J, Sheng J, Liu K et al. Quantitative computed tomography analysis for stratifying the severity of Coronavirus Disease 2019. J Pharm Anal. 2020;10:123-9.
• Ardali Duzgun S, Durhan G, Basaran Demirkazik F, Irmak I, Karakaya J, Akpinar E et al. AI-Based quantitative CT analysis of temporal changes according to disease severity in COVID-19 pneumonia. J Comput Assist Tomogr. 2021;45:970-8.
• Savaş R, Öz Özcan A. Evaluation of lung volume loss with 3D CT volumetry in COVID-19 patients. Diagn Interv Radiol. 2021;27:155-6.
• Iwasawa T, Sato M, Yamaya T, Sato Y, Uchida Y, Kitamura H et al. Ultra-high-resolution computed tomography can demonstrate alveolar collapse in novel coronavirus (COVID-19) pneumonia. Jpn J Radiol. 2020;38:394-8.
• Robbie H, Wells AU, Jacob J, Walsh SLF, Nair A, Srikanthan A et al. Visual and automated CT measurements of lung volume loss in idiopathic pulmonary fibrosis. AJR Am J Roentgenol. 2019;213:318-24.
• Rubin GD, Ryerson CJ, Haramati LB, Sverzellati N, Kanne JP, Raoof S et al. The role of chest imaging in patient management during the COVID-19 pandemic: a multinational consensus statement from the Fleischner Society. Chest. 2020;158:106-16.
• Hansell DM, Bankier AA, MacMahon H, McLoud TC, Müller NL, Remy J. Fleischner Society: Glossary of terms for thoracic imaging, Radiology. 2008;246:697-722.
• Yang R, Li X, Liu H, Zhen Y, Zhang X, Xiong Q et al. Chest CT severity score: an imaging tool for assessing severe COVID-19. Radiol Cardiothorac Imaging. 2: e200047.
• Liu D, Zhang W, Pan F, Li L, Yang L, Zheng D et al. The pulmonary sequalae in discharged patients with COVID-19: a short-term observational study. Respir Res. 2020;21:125.
• Zhou Z, Chen P, Peng H. Are healthy smokers really healthy? Tob Induc Dis. 2016;14:35.
• Park JE, Jung S, Kim A, Park JE. MERS transmission and risk factors: a systematic review. BMC public health. 2018;18:574.
• Chung M, Bernheim A, Mei X, Zhang N, Huang M, Zeng X et al. CT imaging features of 2019 novel coronavirus (2019-nCoV). Radiology. 2020;295:202-7.
• Pan F, Ye T, Sun P, Gui S, Liang B, Li L et al. Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19). Radiology. 2020;295:715-21.
• Wang K, Kang S, Tian R, Zhang X, Wang Y. Imaging manifestations and diagnostic value of chest CT of coronavirus disease 2019 (COVID-19) in the Xiaogan area. Clin Radiol. 2020;75:341-7.
• Martinez FJ, Collard HR, Pardo A, Raghu G, Richeldi L, Selman M et al. Idiopathic pulmonary fibrosis. Nat Rev Dis Primers. 2017;3:17074.
• Bozdağ M, Savas R. Chest CT imaging features of COVID-19-related pulmonary fibrosis: A case report. Iran J Radiol. 2021;18-1.
• Bornstein SR, Dalan R, Hopkins D, Mingrone G, Boehm BO. Endocrine and metabolic link to coronavirus infection. Nat Rev Endocrinol. 2020;16:297‐8.
• Ceriello A. Hyperglycemia and the worse prognosis of COVID‐19. Why a fast blood glucose control should be mandatory. Diabetes Res Clin Pract. 2020;163:108186.
• Rajpal A, Rahimi L, Ismail‐Beigi F. Factors leading to high morbidity and mortality of COVID‐19 in patients with type 2 diabetes. J Diabetes. 2020;12:895-908.
• Pitocco D, Fuso L, Conte EG, Zaccardi F, Condoluci C, Scavone G et al. The diabetic lung--a new target organ?. Rev Diabet Stud. 2012;9:23‐35.
• Kolahian S, Leiss V, Nürnberg B. Diabetic lung disease: fact or fiction? Rev Endocr Metab Disord. 2019;20:303‐19.
• Kumar A, Arora A, Sharma P, Anikhindi SA, Bansal N, Singla V et al. Is diabetes mellitus associated with mortality and severity of COVID-19? A meta-analysis. Diabetes Metab Syndr. 2020;14:535-45.
• Antonio GE, Wong KT, Hui DS, Wu A, Lee N, Yuen EH et al. Thin-section CT in patients with severe acute respiratory syndrome following hospital discharge: preliminary experience. Radiology. 2003;228:810-5.
• Lippi G, Henry BM. Active smoking is not associated with severity of coronavirus disease 2019 (COVID-19). Eur J Intern Med. 2020;75:107-8.
• Chen A, Karwoski RA, Gierada DS, Bartholmai BJ, Koo CW. Quantitative CT analysis of diffuse lung disease. Radiographics. 2020;40:28-43.