Abnormal dynamic ventilation function of COVID-19 survivors detected by pulmonary free-breathing proton MRI

Abstract

Objectives To visualize and quantitatively assess regional lung function of survivors of COVID-19 who were hospitalized using pulmonary free-breathing 1 H MRI. Methods A total of 12 healthy volunteers and 27 COVID-19 survivors (62.4 ± 8.1 days between infection and image acquisition) were recruited in this prospective study and performed chest 1 H MRI acquisitions with free tidal breathing. Then, conventional Fourier decomposition ventilation (FD-V) and global fractional ventilation (FV Global ) were analyzed. Besides, a modified PREFUL (mPREFUL) method was developed to adapt to COVID-19 survivors and generate dynamic ventilation maps and parameters. All the ventilation maps and parameters were analyzed using Student’s t -test. Pearson’s correlation and a Bland-Altman plot between FV Global and mPREFUL were analyzed. Results There was no significant difference between COVID-19 and healthy groups regarding a static FD-V map (0.47 ± 0.12 vs 0.42 ± 0.08; p = .233). However, mPREFUL demonstrated lots of regional high ventilation areas (high ventilation percentage (HVP): 23.7% ± 10.6%) existed in survivors. This regional heterogeneity (i.e., HVP) in survivors was significantly higher than in healthy volunteers ( p = .003). The survivors breathed deeper (flow-volume loop: 5375 ± 3978 vs 1688 ± 789; p = .005), and breathed more air in respiratory cycle (total amount: 62.6 ± 19.3 vs 37.3 ± 9.9; p < .001). Besides, mPREFUL showed both good Pearson’s correlation ( r = 0.74; p < .001) and Bland-Altman consistency (mean bias = −0.01) with FV Global . Conclusions Dynamic ventilation imaging using pulmonary free-breathing 1 H MRI found regional abnormity of dynamic ventilation function in COVID-19 survivors. Key Points • Pulmonary free-breathing 1 H MRI was used to visualize and quantitatively assess regional lung ventilation function of COVID-19 survivors. • Dynamic ventilation maps generated from 1 H MRI were more sensitive to distinguish the COVID-19 and healthy groups (total air amount: 62.6 ± 19.3 vs 37.3 ± 9.9; p < .001), compared with static ventilation maps (FD-V value: 0.47 ± 0.12 vs 0.42 ± 0.08; p = .233). • COVID-19 survivors had larger regional heterogeneity (high ventilation percentage: 23.7% ± 10.6% vs 13.1% ± 7.9%; p = .003), and breathed deeper (flow-volume loop: 5375 ± 3978 vs 1688 ± 789; p = .005) than healthy volunteers. Supplementary Information The online version c...

Inter‐ and intravisit repeatability of free‐breathing MRI in pediatric cystic fibrosis lung disease

“…Postprocessing techniques such as Fourier decomposition, matrix pencil, self-gated non-contrast-enhanced functional lung, and phase-resolved functional lung (PREFUL) can generate ventilation-and perfusion-weighted maps of the lung based on free-breathing MRI data and have been used to assess lung function in a variety of pulmonary diseases. [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] Whereas other postprocessing methods can require extensive pulse sequence modifications, PREFUL MRI can be performed using a conventional spoiled gradient echo sequence, showing promise at both 1.5 and 3 T. PREFUL MRI also sorts images acquired during free breathing into complete respiratory cycles in the time domain, so both static and dynamic ventilation parameters, including regional ventilation (RVent) and flow-volume loops (FVL), can be obtained. Ventilation parameters derived from PREFUL MRI have been shown to correlate to PFTs and Xe-MRI in chronic obstructive pulmonary disease (COPD), CF, and health, 21 and can characterize the severity of coronavirus 2019 infection.…”

“…Ventilation parameters derived from PREFUL MRI have been shown to correlate to PFTs and Xe-MRI in chronic obstructive pulmonary disease (COPD), CF, and health, 21 and can characterize the severity of coronavirus 2019 infection. 22,23 Specifically, FVL cross-correlation has been shown to be sensitive to chronic lung allograft syndrome 24 and to indacaterol-glycopyrronium treatment response in COPD. 25 PREFUL MRI has also been demonstrated to be feasible in term neonates and older infants 26 and has been shown to be repeatable in health and COPD.…”

Evaluation of image registration algorithms for 3D phase‐resolved functional lung ventilation magnetic resonance imaging in healthy volunteers and chronic obstructive pulmonary disease patients

“…PREFUL MRI 4 has been demonstrated to be sensitive for the early detection of abnormal ventilation dynamics in patients after lung transplantation 5 and in COVID-19 survivors. 6,7 In a recent study, dynamic ventilation parameters derived by PREFUL MRI were shown to depict the treatment response to indacaterol-glycopyrronium therapy in chronic obstructive pulmonary disease (COPD) patients. 8 These recent results emphasize the applicability of functional lung MR imaging for diagnosis and patient monitoring.…”

“…Proton magnetic resonance 3D phase‐resolved functional lung (PREFUL) 1 and other 3D lung MRI techniques 2,3 provide contrast‐free ventilation‐weighted whole lung imaging using dynamic data acquisition during free breathing. PREFUL MRI 4 has been demonstrated to be sensitive for the early detection of abnormal ventilation dynamics in patients after lung transplantation 5 and in COVID‐19 survivors 6,7 . In a recent study, dynamic ventilation parameters derived by PREFUL MRI were shown to depict the treatment response to indacaterol‐glycopyrronium therapy in chronic obstructive pulmonary disease (COPD) patients 8 .…”

Free-Breathing Low-Field MRI of the Lungs Detects Functional Alterations Associated With Persistent Symptoms After COVID-19 Infection

“…As the signal intensity is related to the tissue proton density, which itself varies depending on the blood water content of the tissue and the lung volume, perfusion and ventilation parameters can then be extracted. The recent application of a modified version of PREFUL at 3 T in COVID-19 patients around 60 days after infection measured a larger ventilation volume with more heterogeneous and aggregated regions of high ventilation compared with healthy volunteers and increasing with the severity of infection 17 …”