Computed tomography (CT) plays a critical role in assessing lung damage in SARS-CoV-2-infected patients. This study introduces an innovative approach by correlating pulmonary abnormalities detected in CT scans with laboratory findings, providing insights into disease progression and treatment outcomes. Utilizing the capabilities of 3D Slicer software and its Lung CT Analyzer extension, we conducted a detailed temporal analysis of pulmonary impairments, comparing pre- and post-treatment scans. The analysis focused on key parameters such as volume of inflammatory processes and fibrosis, presence and extent of ground-glass opacities, emphysema, and overall affected lung volume versus healthy lung volume. The image database comprised CT scans from 62 patients hospitalized between February and August 2021. Quantification results of lung impairments before and after treatment revealed statistically significant differences in Wilcoxon signed-rank tests for inflammatory process/fibrosis (p = 0.0344), ground-glass opacity (p = 0.0127), total affected volume (p = 0.0453), and inflated lung volume (p = 0.0428). Spearman correlation analyses indicated a significant relationship between pre-treatment lymphocyte levels and post-treatment total affected volume (R =  − 0.353, p = 0.0056) and inflated lung volume (R = 0.348, p = 0.0064). Similar trends were observed between pre-treatment leukocyte levels and post-treatment total affected volume (R = 0.255, p = 0.0494) and inflated lung volume (R =  − 0.258, p = 0.0469). These findings underscore the clinical significance of integrating imaging and laboratory data to predict COVID-19 respiratory sequelae, affirming the value of advanced imaging tools in patient care. By integrating quantitative imaging with lab parameters, our research advocates for a more personalized and precise approach to COVID-19 management, aiming to enhance patient prognosis and treatment strategies.