Standard spirometry to assess emphysema in patients with chronic obstructive pulmonary disease: the Emphysema Severity Index (ESI)

Roberto W. Dal Negro; Matteo Poletti; Massimo Pistolesi

doi:10.4081/mrm.2021.805

Standard spirometry to assess emphysema in patients with chronic obstructive pulmonary disease: the Emphysema Severity Index (ESI)

Authors

Roberto W. Dal Negro National Centre for Respiratory Pharmacoeconomics and Pharmacoepidemiology - CESFAR, Verona https://orcid.org/0000-0001-6305-0732
Matteo Poletti Department of Experimental and Clinical Medicine, University of Florence
Massimo Pistolesi Department of Experimental and Clinical Medicine, University of Florence

DOI: https://doi.org/10.4081/mrm.2021.805

Keywords:

COPD, airflow limitation, emphysema severity index, ESI, phenotypes

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is a generic term identifying a condition characterized by variable changes in peripheral airways and lung parenchyma. Standard spirometry cannot discriminate the relative role of conductive airways inflammatory changes from destructive parenchymal emphysema changes. The aim of this study was to quantify the emphysema component in COPD by a simple parameter (the Emphysema Severity Index - ESI), previously proved to reflect CT-assessed emphysema.
Methods: ESI was obtained by fitting the descending limb of MEFV curves by a fully automated procedure providing a 0 to 10 score of emphysema severity. ESI was computed in COPD patients enrolled in the CLIMA Study.
Results: the vast majority of ESI values ranged from 0 to 4, compatible with no-to-mild/moderate emphysema component. A limited proportion of patients showed ESI values >4, compatible with severe-to-very severe emphysema. ESI values were greatly dispersed within each GOLD class indicating that GOLD classification cannot discriminate emphysema and conductive airways changes in patients with similar airflow limitation. ESI and diffusing capacity (DL_CO) were significantly correlated (p<0.001). However, the great dispersion in their correlation suggests that ESI and DLCO reflect partially different anatomo-functional determinants in COPD.
Conclusions: airflow limitation has heterogenous determinants in COPD. Inflammatory and destructive changes may combine in CT densitometric alterations that cannot be detected by standard spirometry. ESI computation from spirometric data helps to define the prevailing pathogenetic mechanism underlying the measured airflow limitation. ESI could be a reliable advancement to select large samples of patients in clinical or epidemiological trials, and to compare different pharmacological treatments.

References

Burrows B, Fletcher CM, Heard BE, Jones NL, Wootliff JS he emphysematous and bronchial types of chronic airways obstruction. A cliniopathological study of patients in London and Chicago. Lancet 1966;87:830-35.

Pistolesi M, Camiciottoli G, Paoletti M, Marmai C, Lavorini F, Meoni E, et al. Identification of a predominant COPD phenotype of COPD in clinical practice. Respir Med 2008;102:367-76.

Camiciottoli G, Bigazzi F, Paoletti M, Cestelli L, Lavorini F, Pistolesi M. Pulmonary function and sputum characteristics predict computed tomography phenotype and severity of COPD. Eur Respir J 2013;42:626-35.

Ogawa E, Nakano Y, Ohara T, Muro S, Hirai T, Sato S, et al. Body mass index in male patients with COPD: correlation with low attenuation areas on CT. Thorax 2009;64:20-5.

Dal Negro RW, Carone M, Cuttitta G, Gallelli L, Pistolesi M, Privitera S, et al. Prevalence and clinical features of most frequent phenotypes in the Italian COPD population: the CLIMA Study. Multidiscip Respir Medi 2021;16:790.

Nishimura M, Makita H, Nagai K, Konno S, Nasuhara Y, Hasegawa M, et al. Annual change in pulmonary function and clinical phenotype in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2012;185:44-52.

Kurashima K, Takaku Y, Hoshi T, Kanauchi T, Nakamoto K, Takayanagi N, et al. Lobe-based computed tomography assessment of airway diameter, airway or vessel number, and emphysema extent in relation to the clinical outcomes of COPD. Int J Chron Obstruct Pulmon Dis 2015;10:1027-33.

Haruna A, Muro S, Nakano Y, Ohara T, Hoshino Y, Ogawa E, et al. CT scan findings of emphysema predict mortality in COPD. Chest 2010;138:635-40.

Johannessen A, Skorge TD, Bottai M, Grydeland TB, Nilsen RM, Coxson H, et al. Mortality by level of emphysema and airway wall thickness. Am J Respir Crit Care Med 2013;187:602-8.

Han MK, Agusti A, Calverly PM, Celli BR, Criner G, Curtis JL, et al. Chronic obstructive pulmonary disease phenotypes: the future of COPD. Am J Respir Crit Care Med 2010;182:598-604.

Macklem PT, Mead J. Resistance of central and peripheral airways measured by a retrograde catheter. J Appl Physiol 1967;22:395-401.

Lange P, Halpin DM, O’Connell DE, MacNee W. Diagnosis, assessment, and phenotyping of COPD beyond FEV1. Int J COPD 2016;11:3-12.

Madani A, De Maertelaer V, Zanen J, Gevenois PA. Pulmonary emphysema: radiation dose and section thickness at multidetector CT quantification--comparison with macroscopic and microscopic morphometry. Radiology 2007;243:250-7.

Hackx M, Bankier AA, Gevenois PA. Chronic obstructive pulmonary disease: CT quantification of airways disease. Radiology 2012;265:34-48.

Lynch DA, Austin JH, Hogg JC, Grenier PA, Kauczor HU, Bankier AA, et al. CT-definable subtypes of chronic obstructive pulmonary disease: A statement of the Fleischner Society. Radiology 2015; 277:192-205.

Galbán CJ, Han MK, Boes JL, Chughtai KA, Meyer CR, Johnson TD, et al. Computed tomography-based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression. Nat Med 2012;18:1711-5.

Bartholmai BJ, Raghunath S, Karwoski RA, Moua T, Rajagopalan S, Maldonado F, et al. Quantitative computed tomography imaging of interstitial lung diseases. J Thorac Imaging 2013; 28:298-307.

Raghunath S, Rajagopalan S, Karwoski RA, Maldonado F, Peikert T, Moua T, et al. Quantitative stratification of diffuse parenchymal lung diseases. PLoS One 2014;9:e93229.

Pompe E, van Rikxoort EM, Schmidt M, Rühaak J, Estrella LG, Vliegenthart R, et al. Parametric response mapping adds value to current computed tomography biomarkers in diagnosing chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2015;191:1084-6.

Aerts HJ. The potential of radiomic-based phenotyping in precision medicine: A review. JAMA Oncol 2016;2:1636-42.

Frix AN, Cousin F, Refaee T, Bottari F, Vaidyanathan A, Desir C, et al. Radiomics in lung diseases imaging: State-of-the-art for clinicians. J Pers Med 2021;11:602.

Occhipinti M, Paoletti M, Bartholmai BJ, Rajagopalan S, Karwoski RA, Nardi C, et al. Spirometric assessment of emphysema presence and severity as measured by quantitative CT and CT-based radiomics in COPD. Respir Res 2019;20:101.

Occhipinti M, Paoletti M, Crapo JD, Make BJ, Lynch DA, Brusasco V, et al. Validation of a method to assess emphysema severity by spirometry in the COPDGene study. Respir Res. 2020;21:103.

Singh D, Agusti A, Anzueto A, Barnes PJ, Bourbeau J, Celli BR, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease: the GOLD science committee report 2019. Eur Respir J 2019;18;53:1900164.

Hogg JC, Chu F, Utokaparch S, Woods R, Elliott WM, Buzatu L, et al. The nature of small-airway obstruction in chronic obstructive pulmonary disease. N Engl J Med 2004;350:2645-53.

Gelb AF, Schein M, Kuei J, Tashkin DP, Müller NL, Hogg JC, et al. Limited contribution of emphysema in advanced chronic obstructive pulmonary disease. Am Rev Respir Dis 1993;147:1157-61.

Vazquez JH, Garcia IA, Meca AA, de Andres AL, Ruix CM, Garcia MJB, de Miguel Diez J. COPD phenotypes: differences in survival. Int J COPD 2018;13:2245-51.

Karimi R, Tornling G, Forsslund H, Mikko M, Wheelock Å, Nyrén S, et al. Lung density on high resolution computer tomography (HRCT) reflects degree of inflammation in smokers.Respir Res 2014;15:23.

Paoletti M, Cestelli L, Bigazzi F, Camiciottoli G, Pistolesi M. Chronic obstructive pulmonary disease: Pulmonary function and CT lung attenuation do not show linear correlation. Radiology 2015;276:571-8.

Makita H, Nasuhara Y, Nagai K, Ito Y, Hasegawa M, Betsuyaku T, et al. Characterisation of phenotypes based on severity of emphysema in chronic obstructive pulmonary disease. Thorax 2007;62:932-7.

Dal Negro RW, Bonadiman L, Turco P, Tognella S, Iannazzo S. Costs of illness analysis in Italian patients with chronic obstructive pulmonary disease (COPD): an update. Clinicoecon Outcomes Res 2015;7:153-9.

Calverley PM, Anderson JA, Celli B, Ferguson GT, Jenkins C, Jones PW, et al; TORCH investigators. Salmeterol and fluticasone propionate and survival in chronic obstructive pulmonary disease. N Engl J Med 2007;356:775-89.

Chalmers JD, Keir HR. 10 years since TORCH: shining a new light on the risks of inhaled corticosteroids in COPD. Eur Respir J 2017;50:1701582.

Suissa S. Inhaled corticosteroids and pneumonia mortality in COPD patients. Eur Respir J 2019;54:1901276.

Occhipinti M, Paoletti M, Bigazzi F, Camiciottoli G, Inchingolo R, Larici AR, et al. Emphysematous and nonemphysematous gas trapping in chronic obstructive pulmonary disease: Quantitative CT findings and pulmonary function. Radiology 2018;287:683-92.