Quantitative Characterization of Respiratory Patterns on Dynamic Higher Temporal Resolution MRI to Stratify Postacute Covid‐19 Patients by Cardiopulmonary Symptom Burden
Authors: Azour Lea , Rusinek Henry , Mikheev Artem , Landini Nicholas , Keerthivasan Mahesh Bharath , Maier Christoph , Bagga Barun , Bruno Mary , Condos Rany , Moore William H. , Chandarana Hersh 
Published: March 2024

BackgroundPostacute Covid‐19 patients commonly present with respiratory symptoms; however, a noninvasive imaging method for quantitative characterization of respiratory patterns is lacking.PurposeTo evaluate if quantitative characterization of respiratory pattern on free‐breathing higher temporal resolution MRI stratifies patients by cardiopulmonary symptom burden.Study TypeProspective analysis of retrospectively acquired data.SubjectsA total of 37 postacute Covid‐19 patients (25 male; median [interquartile range (IQR)] age: 58 [42–64] years; median [IQR] days from acute infection: 335 [186–449]).Field Strength/Sequence0.55 T/two‐dimensional coronal true fast imaging with steady‐state free precession (trueFISP) at higher temporal resolution.AssessmentPatients were stratified into three groups based on presence of no (N = 11), 1 (N = 14), or ≥2 (N = 14) cardiopulmonary symptoms, assessed using a standardized symptom inventory within 1 month of MRI. An automated lung postprocessing workflow segmented each lung in each trueFISP image (temporal resolution 0.2 seconds) and respiratory curves were generated. Quantitative parameters were derived including tidal lung area, rates of inspiration and expiration, lung area coefficient of variability (CV), and respiratory incoherence (departure from sinusoidal pattern) were. Pulmonary function tests were recorded if within 1 month of MRI. Qualitative assessment of respiratory pattern and lung opacity was performed by three independent readers with 6, 9, and 23 years of experience.Statistical TestsAnalysis of variance to assess differences in demographic, clinical, and quantitative MRI parameters among groups; univariable analysis and multinomial logistic regression modeling to determine features predictive of patient symptom status; Akaike information criterion to compare the quality of regression models; Cohen and Fleiss kappa (κ) to quantify inter‐reader reliability. Two‐sided 5% significance level was used.ResultsTidal area and lung area CV were significantly higher in patients with two or more symptoms than in those with one or no symptoms (area: 15.4 cm2 vs. 12.9 cm2 vs. 12.8 cm2; CV: 0.072, 0.067, and 0.058). Respiratory incoherence was significantly higher in patients with two or more symptoms than in those with one or no symptoms (0.05 vs. 0.043 vs. 0.033). There were no significant differences in patient age (P = 0.19), sex (P = 0.88), lung opacity severity (P = 0.48), or pulmonary function tests (P = 0.35–0.97) among groups. Qualitative reader assessment did not distinguish between groups and showed slight inter‐reader agreement (κ = 0.05–0.11).Data ConclusionQuantitative respiratory pattern measures derived from dynamic higher‐temporal resolution MRI have potential to stratify patients by symptom burden in a postacute Covid‐19 cohort.Level of Evidence3Technical EfficacyStage 3