Pulmonary fibrosis in patients with COVID-19: A retrospective study

Characterization of transient and progressive pulmonary fibrosis by spatially correlated phase contrast microCT, classical histopathology and atomic force microscopy

Pulmonary fibrosis (PF) is a severe and progressive condition in which the lung becomes scarred over time resulting in pulmonary function impairment. Classical histopathology remains an important tool for micro-structural tissue assessment in the diagnosis of PF. A novel workflow based on spatial correlated propagation-based phase-contrast micro computed tomography (PBI-microCT), atomic force microscopy (AFM) and histopathology was developed and applied to two different preclinical mouse models of PF - the commonly used and well characterized Bleomycin-induced PF and a novel mouse model for progressive PF caused by conditional Nedd4-2 KO. The aim was to integrate structural and mechanical features from hallmarks of fibrotic lung tissue remodeling. PBI-microCT was used to assess structural alteration in whole fixed and paraffin embedded lungs, allowing for identification of fibrotic foci within the 3D context of the entire organ and facilitating targeted microtome sectioning of planes of interest for subsequent histopathology. Subsequently, these sections of interest were subjected to AFM to assess changes in the local tissue stiffness of previously identified structures of interest. 3D whole organ analysis showed clear morphological differences in 3D tissue porosity between transient and progressive PF and control lungs. By integrating the results obtained from targeted AFM analysis, it was possible to discriminate between the Bleomycin model and the novel conditional Nedd4-2 KO model using agglomerative cluster analysis. As our workflow for 3D spatial correlation of PBI, targeted histopathology and subsequent AFM is tailored around the standard procedure of formalin-fixed paraffin-embedded (FFPE) tissue specimens, it may be a powerful tool for the comprehensive tissue assessment beyond the scope of PF and preclinical research.

Diagnostic efficacy of chest CT imaging in diagnosis of COVID-19 cases based on duration of symptoms

Background

Chest computed tomography (CT) imaging provides results more rapidly and with higher sensitivity than reverse transcription polymerase chain reaction in diagnosis of COVID-19.

Aim

To evaluate diagnostic efficacy of chest CT imaging in diagnosis of COVID-19 cases based on age and duration of symptoms.

Materials and Methods

A retrospective study conducted during December 2020 to June 2021 in a tertiary care hospital, India. Total 495 patients with typical clinical symptoms of COVID-19, reverse transcription polymerase chain reaction positive for COVID-19 and had undergone chest CT imaging were included. Descriptive statistical analysis was performed for all the variables. Receiver operating characteristic curve analysis was used to determine threshold value of chest CT severity score (CT_SS) based on duration of symptoms and age to diagnose COVID-19.

Results

Mean age of patients was 61.86 ± 10.77 years and 367 (71.4%) patients were male. Ground glass opacities were observed in 456 (92.1%) patients and in 332 (67.1%) patients, multilobes were affected. Total CT_SS showed positive correlation with age (r = 0.257) and duration of symptoms (r = 0.625). Total CT_SS >6 after a duration of 2 days of symptoms identified COVID-19 cases with sensitivity 90.8% (95% confidence interval [CI]: 87.5%-93.5%) and specificity 84.6% (95% CI: 76.2%-90.9%). Total CT_SS >11 in patients aged more than 60 years identified COVID-19 cases with sensitivity 47.4% (95% CI: 41.2%-53.6%) and specificity 87.3% (95% CI: 82.3%-91.4%).

Conclusion

Threshold value of CT_SS determined will help to expedite diagnosis of COVID-19 patients by the clinicians in an early stage especially in India and other developing countries which have a high patient volume and limited health resources.