The correlation between HRCT phenotypes and spirometric indices in patients with COPD

mustafa ahmed karim

doi:10.70863/karbalajm.v14i1.839

المؤلفون

mustafa ahmed karim ministry of health

DOI:

https://doi.org/10.70863/karbalajm.v14i1.839

الكلمات المفتاحية:

COPD, CT phenotypes, GOLD scoring, CT scoring

الملخص

Abstract

Background: chronic obstructive pulmonary disease (COPD) is a preventable and treatable inflammatory respiratory disease that is a leading cause of morbidity and mortality worldwide.

Aims: to investigate COPD phenotypes by HRCT, and to compare these phenotypes and other CT findings with the severity of lung function test variables.

Patients and Methods: a cross-sectional, observational study was performed on 56 patients with COPD of any duration and smoking history referred to the radiology department of Al-Imamain Al-Kadhimein Medical city, during the period from 1^st of May, 2019 to 31^st of December, 2019. PFT (pulmonary function test) was performed at the same visit during which chest HRCT was imaged and these images were interpreted by two independent radiologists and findings were evaluated according to the modified Bhalla scoring system.

Results: from 56 patient included in the study, 47 patients exhibited morphological CT changes while 9 had no pathological findings. Patient with HRCT changes were classified into three phenotypes: Emphysema dominant (n=19), airway dominant (n=18) and mixed phenotype (n=10). With the exception of forced expiratory volume in 1 second to forced vital capacity ratio (FEV1/FVC), other spirometric variables including severity stages termed as global initiative for chronic obstructive lung disease (GOLD) showed no significant correlation with the correspondent phenotypes. While HRCT findings including those scored according to modified Bhalla system were correlated to the CT phenotypes (p- value< 0.001). On the other hand, GOLD severity showed to have no correlation with presence or severity of morphological lung changes detected on HRCT (P- value= 0.4).

Conclusion: the study revealed that GOLD stages of COPD severity based on spirometry have no correlation with radiological phenotypes recognized on CT or the severity of those morphological changes and on the other hand found the close relationship between COPD phenotypes characterized on CT and the severity of morphological abnormalities.

المراجع

1- Gupta PP, Yadav R, Verma M, Agarwal D, Kumar M. Correlation between high-resolution computed tomography features and patients' characteristics in chronic obstructive pulmonary disease. Ann Thorac Med. 2008;3(3):87–93. doi:10.4103/1817-1737.39676
2- Pauwels RA, Buist AS, Calverley PM, Jenkins CR, Hurd SS. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: NHLBI/WHO Global Initiative for Chronic Obstructive Lung Disease (GOLD) Workshop summary. American journal of respiratory and critical care medicine. 2001 Apr 1;163(5):1256-76
3- Snell N, Strachan D, Hubbard R, Gibson J, Gruffydd-Jones K, Jarrold I. S32 Epidemiology of chronic obstructive pulmonary disease (COPD) in the uk: findings from the british lung foundation’s ‘respiratory health of the nation’ project. Thorax. 2016;71(Suppl 3):A20-A.
4- Vogelmeier CF, Criner GJ, Martinez FJ, Anzueto A, Barnes PJ, Bourbeau J, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 report. GOLD executive summary. Am J Respir Crit Care Med. 2017;195(5):557–82.
5- Global Initiative for Chronic Obstructive Lung Disease (GOLD) Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease. Updated. 2015 [PubMed] [Google Scholar]
6- Ali MN, Jasim AH, Nassr AN, Kaddish MA. Forced vital capacity (FVC), peaked expiratory flow rate (PEFR), are additional parameters in the assessment of the reversibility test. Journal of the Faculty of Medicine Baghdad. 2018 Apr 1;60(1):24-7.
7- Qaseem A, Wilt TJ, Weinberger SE, Hanania NA, Criner G, van der Molen T, et al. Diagnosis and Management of Stable Chronic Obstructive Pulmonary Disease: A Clinical Practice Guideline Update from the American College of Physicians, American College of Chest Physicians, American Thoracic Society, and European Respiratory Society. Ann Intern Med. 2011 Aug 2;155(3):179–191. [PubMed] [Google Scholar]
8- Barker A., Babar J. CT phenotypes in COPD – implications for treatment. Rad magazine [Internet]. 2019Oct;44(521):12–4. Available from: https://www.radmagazine.co.uk/wp-content/uploads/2018/10/October-2018-CT-phenotypes-in-COPD-Judith-Babar.pdf.
9- Singh A, Kumar S, Mishra AK, Kumar M, Kant S, Verma SK, et al. Correlation between clinical characteristics, spirometric indices and high resolution computed tomography findings in patients of chronic obstructive pulmonary disease. Lung India : Official Organ of Indian Chest Society 2016; 33(1):42-48.
10- Regan EA, Lynch DA, Curran-Everett D, et al. Clinical and Radiologic Disease in Smokers With Normal Spirometry. JAMA Intern Med 2015;175:1539-49.
11- Chen C, Jian W, Gao Y, Xie Y, Song Y, Zheng J.Int J Chron Obstruct Pulmon Dis. 2016; 11:2519-2526. Epub 2016 Oct 7.
12- Lange P, Halpin DM, O’Donnell DE, MacNee W. Diagnosis, assessment, and phenotyping of COPD: beyond FEV1. International journal of chronic obstructive pulmonary disease. 2016;11(Spec Iss):3.
13- Chronic Dyspnea-Noncardiovascular Origin [Internet]. Acsearch.acr.org. revised 2018 [cited 31 October 2019]. Available from: https://acsearch.acr.org/docs/69448/Narrative/
14- West JB. GOLD Executive Summary. Am J Respir Crit Care Med. 2013;188(11):1366–1367.
15- The Spanish COPD Guidelines (GESEPOC). Arch Ronconenmol 2011; 7: 379–381
16- Dogra V, Menon B, Bansal V, Gaur SN. Correlation between CT phenotypic patterns with clinical, nutritional and pulmonary function parameters among COPD patients. International Journal of Research in Medical Sciences. 2018 May;6(5):1770
17- da Silva SM, Paschoal IA, De Capitani EM, Moreira MM, Palhares LC, Pereira MC. COPD phenotypes on computed tomography and its correlation with selected lung function variables in severe patients. International journal of chronic obstructive pulmonary disease. 2016;11:503.
18- He SZ, He Q, Su YS, Wang P, Xiang ST, Su W, Mao CW. Analysis of high-resolution computed tomography phenotypes and pulmonary function in chronic obstructive pulmonary disease. Journal of International Medical Research. 2020 Jan;48(1):0300060519889459.
19- Tulek B, Kivrak AS, Ozbek S, Kanat F, Suerdem M, Can Respir J. Phenotyping of chronic obstructive pulmonary disease using the modified Bhalla scoring system for high-resolution computed tomography.2013 Mar-Apr; 20(2):91-6