Covid 19 Pozitif Hastaların Akciğer ve Göğüs Hacminin Incelenmesi

Abstract

Amaç: Covid-19 pozitif olan hastaların BT görüntülerinde, cinsiyete ve buzlu cam opasitesi varlığına göre akciğer hacmini, lezyon hacmini ve toraks çaplarını incelemeyi amaçladık. Materyal ve Metod: Çalışmamıza Covid-19 pozitif tanılı 113 kişinin (Erkek;58, Kadın;55) BT görüntülerini dahil ettik. Her hastanın BT görüntüleri DICOM veri setlerine aktarıldı ve MicroDicom kullanılarak toraks çap ölçümleri yapıldı. Ayrıca BT görüntülerinden üç boyutlu görüntüleme yöntemi (Vitrea) kullanılarak akciğer hacmi ve lezyon hacmi parametreleri hesaplandı. Tüm ölçüm parametreleri cinsiyete ve buzlu cam opaklık görünümüne göre karşılaştırıldı. Bulgular: Çalışmamıza yaş ortalaması 44,57±14,59 olan ve Covid-19 tanısı alan 113 hasta (Erkek;58, Kadın;55) dahil edildi. Akciğer hacmi (erkek; 3530,90±1454,99 ml ve kadın; 3149,92±1335,16 ml) ve lezyon hacmi (erkek; 434,59±664,19 ml ve kadın; 557,10±671,99 ml) parametrelerinin ortalama değerlerinde cinsiyete göre anlamlı fark elde edildi. Ayrıca buzlu cam opasitesi olan ve olmayan gruplar arasında, akciğer hacmi (p<0.001) ve lezyon hacmi (p<0.001) parametrelerinde anlamlı fark elde edildi. Ayrıca buzlu cam opasitesi olan ve olmayan gruplar arasında toraks ön-arka çap uzunluğu parametresinde anlamlı fark (p=0.001) elde edildi. Ancak göğüs çapları ölçümleri açısından cinsiyetler arasında anlamlı bir fark bulunamadı (p=0,542). Sonuç: Çalışmamızda kadınlarda, Covid-19 kaynaklı akciğer hasarının daha fazla olabileceğini bulduk. Çalışmamızın eldeki veriler ışığında, çalışmamızın bulgularının aşılamanın henüz yapılmadığı pandeminin erken evrelerine ve uzun vadeli etkilerine katkı sağlayacağına inanıyoruz.

Keywords

• covid-19
• göğüs çapları
• akciğer hacmi

Examination of Lung and Thorax Volume of Patients with Covid 19 Positive

Abstract

Background: We aimed to reveal lung volume, lesion volume and thorax diameters in patients with Covid-19 positive in CT images according to gender and presence of ground glass opacity. Materials and Methods: We included CT images of 113 people (male;58, female;55) diagnosed with Covid-19 positive in our study. CT images of each patient were imported the DICOM datasets and thorax diameter measurements were performed by using MicroDicom. Moreover, lung volume and lesion volume parameters were calculated from the CT images using the three-dimensional imaging method (Vitrea). All measurement parameters were compared according to gender and ground glass opacity appearance. Results: The 113 patients (male;58, female;55) with a mean age of 44.57±14.59 diagnosed with Covid-19 were included in our study. There was a significant difference between the gender in the mean values of lung volume (males; 3530.90±1454.99 ml and females; 3149.92±1335.16 ml) and lesion volume (males; 434.59±664.19 ml and females; 557.10±671.99 ml) parameters. In addition, a significant difference in lung volume (p<0.001) and lesion volume (p<0.001) was obtained between the groups with ground glass opacity and without ground glass opacity. Moreover, A significant difference (p=0.001) in thorax anteroposterior diameter length was obtained between the groups the with/without ground glass opacity. However, there was no significant difference (p=0.542) between genders in thorax diameters. Conclussion: In our study, we found that in the females may have more lung damage from Covid-19. We believe that our work in the light of the available data, we believe that the findings of our study will contribute to early stages of the pandemic, in which vaccination has not yet , and the long-term effects of post-covid.

Keywords

• covid-19
• thorax diameters
• lung volume

References

1. 1. Hu B, Guo H, Zhou P, Shi ZL. Characteristics of SARS-CoV-2 and COVID-19. Nat Rev Microbiol. 202;19(3):141-154. doi: 10.1038/s41579-020-00459-7.
2. 2. Dayan S. Covid-19 ve aşı. Dicle Tıp Dergisi. 2021;48 (Özel Sayı):98-113.
3. 3. Lytras T, Tsiodras S. Lockdowns and the COVID-19 pandem-ic: What is the endgame? Scand J Public Health. 2021;49(1):37-40. doi: 10.1177/1403494820961293.
4. 4. Ye Z, Zhang Y, Wang Y, Huang Z, Song B. Chest CT manifesta-tions of new coronavirus disease 2019 (COVID-19): a pictori-al review. Eur Radiol. 2020;30(8):4381-4389. doi:10.1007/s00330-020-06801-0.
5. 5. Fang Y, Zhang H, Xie J, Lin M, Ying L, Pang P, et al. Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR. Radiolo-gy. 2020;296:115–7.
6. 6. 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):500–504. https://doi.org/10.1007/s11547-020-01195-x.
7. 7. Rich-Edwards JW, Kaiser UB, Chen GL, Manson JE, Goldstein JM. Sex and gender differences research design for basic, clinical, and population studies: essentials for investigators. Endocr Rev. 2018;39(4):424-439. doi:10.1210/er.2017-00246.
8. 8. Connor J, Madhavan S, Mokashi M, Amanuel H, Johnson NR, Pace LE, et al. Health risks and outcomes that dispro-portionately affect women during the Covid-19 pandemic: A review. Soc Sci Med. 2020;266:113364. doi:10.1016/j.socscimed.2020.113364.

9. 9. Xu X, Yu C, Qu J, Zhang L, Jiang S, Huang D, et al. Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2. Eur J Nucl Med Mol Imaging. 2020;47(5):1275-1280. doi:10.1007/s00259-020-04735-9.
10. 10. Silveyra P, Fuentes N, Rodriguez Bauza DE. Sex and gender differences in lung disease. Adv Exp Med Biol. 2021;1304:227-258. doi: 10.1007/978-3-030-68748-9_14.
11. 11. Li X, Zeng W, Li X, Chen H, Shi L, Li X, Xiang H, et al. CT imag-ing changes of corona virus disease 2019(COVID-19): a mul-ti-center study in Southwest China. J Transl Med. 2020;18(1):154. doi: 10.1186/s12967-020-02324-w.
12. 12. Bekir SA, Ataç GK, Akpinar EE, Büyük E, Güngör S, Tunçay E, et al. The role of quantitative computed tomography in de-termining the phenotype of chronic obstructive pulmonary disease. Maltepe Medical Journal. 2021;13(3):97-103. doi: https://doi.org/10.35514/mtd.2021.56.
13. 13. Heussel CP, HerthF JF, Kappes J, Hantusch R, Hartlieb S, Weinheimer O, et al. Fully automatic quantitative as sess-mentof emphysema in computed tomography: comparison with pulmonary function test ingand normal values. EurRa-diol. 2009;19: 2391–2402.
14. 14. Ippolito D, Ragusi M, Gandola D, Maino C, Pecorelli A, Terrani S, et al. Computed tomography semi-automated lung volume quantification in SARS-CoV-2-related pneumo-nia. Eur Radiol. 2021;31(5):2726-2736. doi: 10.1007/s00330-020-07271-0.
15. 15. Obikili EN, Okoye IJ. Transverse thoracic diameter in frontal chest radiographs of an adult Nigerian population. West Afr J Med. 2006;25(3):186-189. doi:10.4314/wajm.v25i3.28275.
16. 16. Ümit TB, Sogut O, Az A, Cakmak S, Demirel I. Relationship between measures of thoracic diameter and cardiopulmo-nary resuscitation-induced thoracoabdominal injury. Rev Assoc Med Bras (1992). 2022;68(10):1470-1475. doi:10.1590/1806-9282.20220822.
17. 17. Oya S, Shinjo T, Fujii Y, Kamo J, Teruya H, Kinoshita H. CPR related thoracic injury: a comparison of CPR guidelines be-tween 2005 and 2010. Acute Med Surg. 2016;3(4):351–355. doi: 10.1002/ams2.215.
18. 18. Pickard A, Darby M, Soar J. Radiological assessment of the adult chest: implications for chest compressions. Resuscita-tion. 2006; 71: 387–90.