Functional Impairment in Small Airways Associated With the Breathlessness Symptoms in Long–Coronavirus Disease

Author:

Kim Minsuok1,Hwang Jeongeun23,Grist James T.456,Abueid Gabriele5,Yoon Soon Ho7,Grau Vicente8,Fraser Emily9,Gleeson Fergus V.105

Affiliation:

1. School of Mechanical, Electrical, and Manufacturing Engineering, Loughborough University, Loughborough

2. Department of Engineering Science, Institute of Biomedical Engineering, Oxford e-Research Centre

3. Department of Medical IT Engineering, Soonchunhyang University, Chungcheonnam-do

4. Department of Physiology, Anatomy, and Genetics

5. Department of Radiology

6. Oxford Centre for Clinical MR Research, John Radcliffe Hospital, Oxford University Hospitals NHS Trust, Oxford, UK

7. Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea

8. Division of Medical Oncology, Department of Internal Medicine, Korea University College of Medicine

9. Oxford Interstitial Lung Disease Service, The Churchill Hospital

10. Department of Oncology, University of Oxford

Abstract

Purpose: This study aimed to determine the association between functional impairment in small airways and symptoms of dyspnea in patients with Long-coronavirus disease (COVID), using imaging and computational modeling analysis. Patients and Methods: Thirty-four patients with Long-COVID underwent thoracic computed tomography and hyperpolarized Xenon-129 magnetic resonance imaging (HP Xe MRI) scans. Twenty-two answered dyspnea-12 questionnaires. We used a computed tomography–based full-scale airway network (FAN) flow model to simulate pulmonary ventilation. The ventilation distribution projected on a coronal plane and the percentage lobar ventilation modeled in the FAN model were compared with the HP Xe MRI data. To assess the ventilation heterogeneity in small airways, we calculated the fractal dimensions of the impaired ventilation regions in the HP Xe MRI and FAN models. Results: The ventilation distribution projected on a coronal plane showed an excellent resemblance between HP Xe MRI scans and FAN models (structure similarity index: 0.87 ± 0.04). In both the image and the model, the existence of large clustered ventilation defects was not identifiable regardless of dyspnea severity. The percentage lobar ventilation of the HP Xe MRI and FAN model showed a strong correlation (ρ = 0.63, P < 0.001). The difference in the fractal dimension of impaired ventilation zones between the low and high dyspnea-12 score groups was significant (HP Xe MRI: 1.97 [1.89 to 2.04] and 2.08 [2.06 to 2.14], P = 0.005; FAN: 2.60 [2.59 to 2.64] and 2.64 [2.63 to 2.65], P = 0.056). Conclusions: This study has identified a potential association of small airway functional impairment with breathlessness in Long-COVID, using fractal analysis of HP Xe MRI scans and FAN models.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Pulmonary and Respiratory Medicine,Radiology, Nuclear Medicine and imaging

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