Automated detection of ribs in chest CT scans and assessment of changes in their morphology between Total Lung Capacity (TLC) and Residual Volume (RV)

Syed Ahmed Nadeem; Alejandro P. Comellas; Eric A. Hoffman; Punam K. Saha

doi:10.1117/12.2653941

10 April 2023 Automated detection of ribs in chest CT scans and assessment of changes in their morphology between Total Lung Capacity (TLC) and Residual Volume (RV)

Syed Ahmed Nadeem, Alejandro P. Comellas, Eric A. Hoffman, Punam K. Saha

Author Affiliations +

Proceedings Volume 12468, Medical Imaging 2023: Biomedical Applications in Molecular, Structural, and Functional Imaging; 124680H (2023) https://doi.org/10.1117/12.2653941
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Abstract

Aging of the thoracic musculoskeletal system can result in adverse impacts on lung function. Measurement of rib morphology in chest CT scans and assessment of their changes between full inspiratory, or total lung capacity (TLC), and full expiratory, or residual volume (RV), help examine the impacts of rib cage-related changes on lung function. We present new and automated methods using deep learning, multi-parametric thresholding, and topological analysis to segment and label individual ribs in chest CT scans, compute static morphological features at individual rib locations, and assess their lung volume related changes (Δ_LV) between TLC and RV scans. The method was applied on TLC and RV scans from the COPDGene Iowa cohort at baseline visits, and accuracy of rib segmentation and computed metrics were examined by comparing with manually outlined results on TLC and RV scans (n=2×20). An average Dice score of 0.93 was observed in all TLC and RV rib segmentations, and root-mean-square errors for different static and Δ_LV metrics were found between 0.7 and 4.9%. Application on a larger population (n=200) revealed a five-year loss of 6.2% (p<.001) in the trendline for Δ_LV in the anterior-posterior diameter of the 5^th rib with losses of 8.4 and 4.0% for males and females, respectively. Automation of CT-based static and Δ_LV metrics of rib morphology and significant evidence of age-related changes and sex-bias establish a novel and effective tool to investigate the influence of different risk factors and comorbidities in patients with chronic lung disease and their impacts on disease progression and clinical outcomes.

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Syed Ahmed Nadeem, Alejandro P. Comellas, Eric A. Hoffman, and Punam K. Saha "Automated detection of ribs in chest CT scans and assessment of changes in their morphology between Total Lung Capacity (TLC) and Residual Volume (RV)", Proc. SPIE 12468, Medical Imaging 2023: Biomedical Applications in Molecular, Structural, and Functional Imaging, 124680H (10 April 2023); https://doi.org/10.1117/12.2653941

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