Semi-quantitative software evaluation of COVID-19 CT examinations-correlation with clinical parameters.

ABSTRACT:

Background

Software-guided semi-quantitative analysis of coronavirus disease 2019 (COVID-19) pneumonia in lung computed tomography (CT) datasets for severity assessment. Further to correlate imaging findings with the need of intensive care medicine and clinical parameters.

Methods

This single-center retrospective study analyzed 66 consecutive patients (31 females, mean age 64.6±16.2 years) with lung CT datasets from 12/2020 to 05/2021 and confirmed COVID-19 pneumonia. Lung CT datasets were evaluated using a semi-quantitative software for segmentation and quantification. Correlation with underlying diseases, laboratory parameters and further course were assessed, including intubation and need for intensive care.

Results

Total lung volume was 3,903.65±1,185.67 mL, mean

SUBMITTER: Trif N 

PROVIDER: S-EPMC12603536 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature