CT-based Subject-Specific Whole-lung Computational Fluid Dynamics and Particle Deposition in Post-COVID-19 Subjects

This work investigates the health-related effects of COVID-19 subjects using whole-lung computational fluid and particle dynamics (CFPD). The subjects underwent examination at approximately 4 months (V0) and 36 months (V1) after their initial COVID-19 diagnosis. Data gathered included demographic information, pulmonary function tests (PFT), St. George’s respiratory Questionnaire (SGRQ) and CT scans. This study identified two groups of post-COVID subjects at V1 based on the total SGRQ score (SGRQ ≥ 25 and SGRQ < 25). The mean SGRQ for subjects (n=14) with SGRQ ≥ 25 was approximately 42.6 ± 12.2, and the mean score was approximately 13.1 ± 6 for SGRQ < 25 (n=19). Subjects with higher SGRQ scores reported persistent coughing and difficulty in daily physical activities. The 1D CFPD predicted total resistances for all subjects decreased from V0 to V1 (7.03 cmH₂O×s/L ± 2.5 vs. 5.9 cmH₂O×s/L ± 1.6). We found that SGRQ ≥ 25 is negatively correlated (r =-0.41, p < 0.05) with predicted forced expiratory volume at 1s (FEV₁) and SGRQ < 25 was weakly correlated with total airways resistance (r =0.11, p < 0.05). The study highlights distinct biomarkers associated with CFPD-predicted airway resistance, SGRQ score and PFTs among post-COVID subjects. The results indicate that health-related negative effects on their quality of life among post-COVID subjects with a higher prevalence among those with SGRQ ≥ 25.

NIH R01HL168116 and ED P116S210005