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Assessment of Treatment Response in Patients With Severe Asthma Using Visual and Quantitative Analysis of Chest CT

  • Han Na Lee (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Jin An (Department of Pulmonary, Allergy and Critical Care Medicine, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University) ;
  • Miji Lee (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Hye Jeon Hwang (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Jooae Choe (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Jihye Yoon (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Ji-Hyang Lee (Department of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine) ;
  • Min-Hye Kim (Department of Internal Medicine, Ewha Womans University Seoul Hospital, Ewha Womans University College of Medicine) ;
  • Young-Joo Cho (Department of Allergy and Clinical Immunology, Ewha Womans University Mokdong Hospital, Ewha Womans University College of Medicine) ;
  • Sang Min Lee (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Tae-Bum Kim (Department of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine) ;
  • Joon Beom Seo (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center)
  • Received : 2024.01.29
  • Accepted : 2024.04.26
  • Published : 2024.07.01

Abstract

Objective: To evaluate the role of visual and quantitative chest CT parameters in assessing treatment response in patients with severe asthma. Materials and Methods: Korean participants enrolled in a prospective multicenter study, named the Precision Medicine Intervention in Severe Asthma study, from May 2020 to August 2021, underwent baseline and follow-up chest CT scans (inspiration/expiration) 10-12 months apart, before and after biologic treatment. Two radiologists scored bronchiectasis severity and mucus plugging extent. Quantitative parameters were obtained from each CT scan as follows: normal lung area (normal), air trapping without emphysema (AT without emph), air trapping with emphysema (AT with emph), and airway (total branch count, Pi10). Clinical parameters, including pulmonary function tests (forced expiratory volume in 1 s [FEV1] and FEV1/forced vital capacity [FVC]), sputum and blood eosinophil count, were assessed at initial and follow-up stages. Changes in CT parameters were correlated with changes in clinical parameters using Pearson or Spearman correlation. Results: Thirty-four participants (female:male, 20:14; median age, 50.5 years) diagnosed with severe asthma from three centers were included. Changes in the bronchiectasis and mucus plugging extent scores were negatively correlated with changes in FEV1 and FEV1/FVC (ρ = from -0.544 to -0.368, all P < 0.05). Changes in quantitative CT parameters were correlated with changes in FEV1 (normal, r = 0.373 [P = 0.030], AT without emph, r = -0.351 [P = 0.042]), FEV1/FVC (normal, r = 0.390 [P = 0.022], AT without emph, r = -0.370 [P = 0.031]). Changes in total branch count were positively correlated with changes in FEV1 (r = 0.349 [P = 0.043]). There was no correlation between changes in Pi10 and the clinical parameters (P > 0.05). Conclusion: Visual and quantitative CT parameters of normal, AT without emph, and total branch count may be effective for evaluating treatment response in patients with severe asthma.

Keywords

Acknowledgement

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (Grant No. HI22C1723). This research was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT) (No. 2019M3E5D3073365). This work was supported by the NRF grant funded by the MSIT (No. RS-2023-00211367).

References

  1. Reddel HK, Bacharier LB, Bateman ED, Brightling CE, Brusselle GG, Buhl R, et al. Global initiative for asthma strategy 2021: executive summary and rationale for key changes. Am J Respir Crit Care Med 2022;205:17-35 
  2. Kavanagh JE, Hearn AP, Jackson DJ. A pragmatic guide to choosing biologic therapies in severe asthma. Breathe (Sheff) 2021;17:210144 
  3. Hansen S, von Bulow A, Sandin P, Ernstsson O, Janson C, Lehtimaki L, et al. Prevalence and management of severe asthma in the Nordic countries: findings from the NORDSTAR cohort. ERJ Open Res 2023;9:00687-2022 
  4. Maspero J, Adir Y, Al-Ahmad M, Celis-Preciado CA, Colodenco FD, Giavina-Bianchi P, et al. Type 2 inflammation in asthma and other airway diseases. ERJ Open Res 2022;8:00576-2021 
  5. Dragonieri S, Carpagnano GE. Biological therapy for severe asthma. Asthma Res Pract 2021;7:12 
  6. Schoettler N, Strek ME. Recent advances in severe asthma: from phenotypes to personalized medicine. Chest 2020;157:516-528 
  7. Busse WW, Kraft M, Rabe KF, Deniz Y, Rowe PJ, Ruddy M, et al. Understanding the key issues in the treatment of uncontrolled persistent asthma with type 2 inflammation. Eur Respir J 2021;58:2003393 
  8. Dunican EM, Elicker BM, Gierada DS, Nagle SK, Schiebler ML, Newell JD, et al. Mucus plugs in patients with asthma linked to eosinophilia and airflow obstruction. J Clin Invest 2018;128:997-1009 
  9. Chan R, Duraikannu C, Lipworth B. Clinical associations of mucus plugging in moderate to severe asthma. J Allergy Clin Immunol Pract 2023;11:195-199.e2 
  10. Verbanck S. Quantitative computed tomography in asthma: for good measure. Am J Respir Crit Care Med 2020;201:885-886 
  11. Svenningsen S, Haider E, Boylan C, Mukherjee M, Eddy RL, Capaldi DPI, et al. CT and functional MRI to evaluate airway mucus in severe asthma. Chest 2019;155:1178-1189 
  12. Eddy RL, Svenningsen S, Kirby M, Knipping D, McCormack DG, Licskai C, et al. Is computed tomography airway count related to asthma severity and airway structure and function? Am J Respir Crit Care Med 2020;201:923-933 
  13. McIntosh MJ, Kooner HK, Eddy RL, Jeimy S, Licskai C, Mackenzie CA, et al. Asthma control, airway mucus, and 129Xe MRI ventilation after a single benralizumab dose. Chest 2022;162:520-533 
  14. Chung KF, Wenzel SE, Brozek JL, Bush A, Castro M, Sterk PJ, et al. International ERS/ATS guidelines on definition, evaluation and treatment of severe asthma. Eur Respir J 2014;43:343-373 
  15. Cloutier MM, Schatz M, Castro M, Clark N, Kelly HW, Mangione-Smith R, et al. Asthma outcomes: composite scores of asthma control. J Allergy Clin Immunol 2012;129(3 Suppl):S24-S33 
  16. Lee JH, Dixey P, Bhavsar P, Raby K, Kermani N, Chadeau-Hyam M, et al. Precision medicine intervention in severe asthma (PRISM) study: molecular phenotyping of patients with severe asthma and response to biologics. ERJ Open Res 2023;9:00485-2022 
  17. Bhalla M, Turcios N, Aponte V, Jenkins M, Leitman BS, McCauley DI, et al. Cystic fibrosis: scoring system with thin-section CT. Radiology 1991;179:783-788 
  18. Tulek B, Kivrak AS, Ozbek S, Kanat F, Suerdem M. Phenotyping of chronic obstructive pulmonary disease using the modified Bhalla scoring system for high-resolution computed tomography. Can Respir J 2013;20:91-96 
  19. Kim EY, Seo JB, Lee HJ, Kim N, Lee E, Lee SM, et al. Detailed analysis of the density change on chest CT of COPD using non-rigid registration of inspiration/expiration CT scans. Eur Radiol 2015;25:541-549 
  20. Lee SM, Seo JB, Lee SM, Kim N, Oh SY, Oh YM. Optimal threshold of subtraction method for quantification of air-trapping on coregistered CT in COPD patients. Eur Radiol 2016;26:2184-2192 
  21. Hwang HJ, Seo JB, Lee SM, Kim N, Yi J, Lee JS, et al. New method for combined quantitative assessment of air-trapping and emphysema on chest computed tomography in chronic obstructive pulmonary disease: comparison with parametric response mapping. Korean J Radiol 2021;22:1719-1729 
  22. Cho YH, Seo JB, Kim N, Lee HJ, Hwang HJ, Kim EY, et al. Comparison of a new integral-based half-band method for CT measurement of peripheral airways in COPD with a conventional full-width half-maximum method using both phantom and clinical CT images. J Comput Assist Tomogr 2015;39:428-436 
  23. Lee SW, Lee SM, Shin SY, Park TS, Oh SY, Kim N, et al. Improvement in ventilation-perfusion mismatch after bronchoscopic lung volume reduction: quantitative image analysis. Radiology 2017;285:250-260 
  24. Tang M, Elicker BM, Henry T, Gierada DS, Schiebler ML, Huang BK, et al. Mucus plugs persist in asthma, and changes in mucus plugs associate with changes in airflow over time. Am J Respir Crit Care Med 2022;205:1036-1045 
  25. Kirby M, Tanabe N, Tan WC, Zhou G, Obeidat M, Hague CJ, et al. Total airway count on computed tomography and the risk of chronic obstructive pulmonary disease progression. Findings from a population-based study. Am J Respir Crit Care Med 2018;197:56-65 
  26. Wu F, Jiang C, Zhou Y, Zheng Y, Tian H, Li H, et al. Association of total airway count on computed tomography with pulmonary function decline in early-stage COPD: a population-based prospective cohort study. Int J Chron Obstruct Pulmon Dis 2021;16:3437-3448 
  27. Tsubokawa F, Koya T, Murai Y, Tanaka K, Tsutsui Y, Naramoto S, et al. Effects of benralizumab on three-dimensional computed tomography analysis in severe eosinophilic asthma. Int Arch Allergy Immunol 2023;184:243-251 
  28. Dunican EM, Elicker BM, Henry T, Gierada DS, Schiebler ML, Anderson W, et al. Mucus plugs and emphysema in the pathophysiology of airflow obstruction and hypoxemia in smokers. Am J Respir Crit Care Med 2021;203:957-968