Korean J Radiol.  2019 Jul;20(7):1236-1245. 10.3348/kjr.2019.0083.

Structural and Functional Features on Quantitative Chest Computed Tomography in the Korean Asian versus the White American Healthy Non-Smokers

• Cho HB
• Chae KJ
• Jin GY
• Choi J
• Lin CL
• Hoffman EA
• Wenzel SE
• Castro M
• Fain SB
• Jarjour NN
• Schiebler
• Barr RG
• Hansel N
• Cooper CB
• Kleerup EC
• Han MK
• Woodruff P
• Kanner RE
• Bleecker E
• Peters SP
• Moore WC
• Lee CH
• Choi S
• the National Heart, Lung and Blood Institute's SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Severe Asthma Research Program (SARP)

• KMID: 2467034
• DOI: http://doi.org/10.3348/kjr.2019.0083

Abstract

OBJECTIVE
Considering the different prevalence rates of diseases such as asthma and chronic obstructive pulmonary disease in Asians relative to other races, Koreans may have unique airway structure and lung function. This study aimed to investigate unique features of airway structure and lung function based on quantitative computed tomography (QCT)-imaging metrics in the Korean Asian population (Koreans) as compared with the White American population (Whites).
MATERIALS AND METHODS
QCT data of healthy non-smokers (223 Koreans vs. 70 Whites) were collected, including QCT structural variables of wall thickness (WT) and hydraulic diameter (Dh) and functional variables of air volume, total air volume change in the lung (ΔVair), percent emphysema-like lung (Emph%), and percent functional small airway disease-like lung (fSAD%). Mann-Whitney U tests were performed to compare the two groups.
RESULTS
As compared with Whites, Koreans had smaller volume at inspiration, ΔVair between inspiration and expiration (p < 0.001), and Emph% at inspiration (p < 0.001). Especially, Korean females had a decrease of ΔVair in the lower lobes (p < 0.001), associated with fSAD% at the lower lobes (p < 0.05). In addition, Koreans had smaller Dh and WT of the trachea (both, p < 0.05), correlated with the forced expiratory volume in 1 second (R = 0.49, 0.39; all p < 0.001) and forced vital capacity (R = 0.55, 0.45; all p < 0.001).
CONCLUSION
Koreans had unique features of airway structure and lung function as compared with Whites, and the difference was clearer in female individuals. Discriminating structural and functional features between Koreans and Whites enables exploration of inter-racial differences of pulmonary disease in terms of severity, distribution, and phenotype.

Keyword

Hydraulic luminal diameter; Airway wall thickness; Image registration; Percent emphysema-like lung; Percent functional small airway disease-like lung

MeSH Terms

Asian Continental Ancestry Group*
Asthma
Continental Population Groups
Female
Forced Expiratory Volume
Humans
Lung
Lung Diseases
Phenotype
Prevalence
Pulmonary Disease, Chronic Obstructive
Thorax*
Trachea
Vital Capacity

Figure

• 

  Fig. 1 Flow chart of subject selection of male and female subgroups.Values are presented as mean (standard deviation). COPD = chronic obstructive pulmonary disease, SARP = Severe Asthma Research Program, SPIROMICS = SubPopulations and InteRmediate Outcome Measures In COPD Study

• 

  Fig. 2 A. Five central airways and five subgroups of segmental airway. B. Frontal view of color-coded five lobes.Hydraulic diameter and wall thickness included regions in A. Percent emphysema-like lung and percent fSAD involved regions in B. BronInt = bronchus intermedius, fSAD = functional small airway disease-like lung, LLL = left lower lobe, LMB = left main bronchus, LUL = left upper lobe, RLL = right lower lobe, RMB = right main bronchus, RML = right middle lobe, RUL = right upper lobe, sLLL = subgrouped LLL including branches of LB6 and LB8 to LB10, sLUL = subgrouped LUL including branches of LB1 to LB5, sRLL = subgrouped RLL including branches of RB6 to RB10, sRML = subgrouped RML including branches of RB4 and RB5, sRUL = subgrouped RUL including branches of RB1 to RB3, TriLLB = trifurcation of left lower bronchus,TriLUL = trifurcation of LUB, TriRLL = trifurcation of RLL, TriRUL = trifurcation of RUB

• 

  Fig. 3 Distribution of ΔVair* (A, B), and fSAD in Korean (left column) and White female (right column) samples (C, D).Left lateral view is shown, and each cube represents average of about 1000 voxels; voxels in C and D are labeled as 0 (non-fSAD) to 1 (fSAD). ΔVair* = air volume change normalized by median value

Reference

1. Song WJ, Kang MG, Chang YS, Cho SH. Epidemiology of adult asthma in Asia: toward a better understanding. Asia Pac Allergy. 2014; 4:75–85. PMID: 24809012.

2. Iqbal S, Oraka E, Chew GL, Flanders WD. Association between birthplace and current asthma: the role of environment and acculturation. Am J Public Health. 2014; 104(Suppl 1):S175–S182. PMID: 24354818.

3. Adeloye D, Chua S, Lee C, Basquill C, Papana A, Theodoratou E, et al. Global Health Epidemiology Reference Group (GHERG). Global and regional estimates of COPD prevalence: systematic review and meta-analysis. J Glob Health. 2015; 5:020415. PMID: 26755942.

4. Krishnaswamy S, Kanteti R, Duke-Cohan JS, Loganathan S, Liu W, Ma PC, et al. Ethnic differences and functional analysis of MET mutations in lung cancer. Clin Cancer Res. 2009; 15:5714–5723. PMID: 19723643.

5. Yang TS, Peat J, Keena V, Donnelly P, Unger W, Woolcock A. A review of the racial differences in the lung function of normal Caucasian, Chinese and Indian subjects. Eur Respir J. 1991; 4:872–880. PMID: 1955009.

6. Whittaker AL, Sutton AJ, Beardsmore CS. Are ethnic differences in lung function explained by chest size? Arch Dis Child Fetal Neonatal Ed. 2005; 90:F423–F428. PMID: 15871993.

7. Hoffman EA, Ahmed FS, Baumhauer H, Budoff M, Carr JJ, Kronmal R, et al. Variation in the percent of emphysema-like lung in a healthy, nonsmoking multiethnic sample. The MESA lung study. Ann Am Thorac Soc. 2014; 11:898–907. PMID: 24983825.

8. Kim SS, Jin GY, Li YZ, Lee JE, Shin HS. CT quantification of lungs and airways in normal Korean subjects. Korean J Radiol. 2017; 18:739–748. PMID: 28670169.

9. Choi S, Hoffman EA, Wenzel SE, Castro M, Fain SB, Jarjour NN, et al. Quantitative assessment of multiscale structural and functional alterations in asthmatic populations. J Appl Physiol (1985). 2015; 118:1286–1298. PMID: 25814641.

10. Choi S, Haghighi B, Choi J, Hoffman EA, Comellas AP, Newell JD, et al. Differentiation of quantitative CT imaging phenotypes in asthma versus COPD. BMJ Open Respir Res. 2017; 4:e000252.

11. Choi S, Hoffman EA, Wenzel SE, Tawhai MH, Yin Y, Castro M, et al. Registration-based assessment of regional lung function via volumetric CT images of normal subjects vs. severe asthmatics. J Appl Physiol (1985). 2013; 115:730–742. PMID: 23743399.

12. Choi S, Hoffman EA, Wenzel SE, Castro M, Lin CL. Improved CT-based estimate of pulmonary gas trapping accounting for scanner and lung-volume variations in a multicenter asthmatic study. J Appl Physiol (1985). 2014; 117:593–603. PMID: 25103972.

13. Choi S, Hoffman EA, Wenzel SE, Castro M, Fain S, Jarjour N, et al. National Heart, Lung and Blood Institute's Severe Asthma Research Program. Quantitative computed tomographic imaging-based clustering differentiates asthmatic subgroups with distinctive clinical phenotypes. J Allergy Clin Immunol. 2017; 140:690–700.e8. PMID: 28143694.

14. Moore WC, Bleecker ER, Curran-Everett D, Erzurum SC, Ameredes BT, Bacharier L, et al. National Heart, Lung, Blood Institute's Severe Asthma Research Program. Characterization of the severe asthma phenotype by the National Heart, Lung, and Blood Institute's Severe Asthma Research Program. J Allergy Clin Immunol. 2007; 119:405–413. PMID: 17291857.

15. Couper D, LaVange LM, Han M, Barr RG, Bleecker E, Hoffman EA, et al. SPIROMICS Research Group. Design of the Subpopulations and Intermediate Outcomes in COPD Study (SPIROMICS). Thorax. 2014; 69:491–494.

16. Crapo RO, Hankinson JL, Irvin C, Maclntyre NR, Voter KZ, Wise RA, et al. Standardization of Spirometry, 1994 update. American Thoracic Society. Am J Respir Crit Care Med. 1995; 152:1107–1136. PMID: 7663792.

17. Jahani N, Choi S, Choi J, Iyer K, Hoffman EA, Lin CL. Assessment of regional ventilation and deformation using 4D-CT imaging for healthy human lungs during tidal breathing. J Appl Physiol (1985). 2015; 119:1064–1074. PMID: 26316512.

18. Hoff BA, Pompe E, Galbán S, Postma DS, Lammers JJ, Ten Hacken NHT, et al. CT-based local distribution metric improves characterization of COPD. Sci Rep. 2017; 7:2999. PMID: 28592874.

19. Mann HB, Whitney DR. On a test of whether one of two random variables is stochastically larger than the other. Ann Math Statist. 1947; 18:50–60.

20. Lawrence MA. Easy analysis and visualization of factorial experiments. R package version 4.1-1. 2012. Available at: https://cran.r-project.org/web/packages/ez/ez.pdf.

21. Korotzer B, Ong S, Hansen JE. Ethnic differences in pulmonary function in healthy nonsmoking Asian-Americans and European-Americans. Am J Respir Crit Care Med. 2000; 161(4 Pt 1):1101–1108. PMID: 10764297.

22. Becklake MR, Kauffmann F. Gender differences in airway behaviour over the human life span. Thorax. 1999; 54:1119–1138. PMID: 10567633.

23. Peat JK, Salome CM, Woolcock AJ. Factors associated with bronchial hyperresponsiveness in Australian adults and children. Eur Respir J. 1992; 5:921–929. PMID: 1426199.