Conference proceeding
Automated detection of ribs in chest CT scans and assessment of changes in their morphology between Total Lung Capacity (TLC) and Residual Volume (RV)
Vol.12468, pp.124680H-124680H-9
04/10/2023
DOI: 10.1117/12.2653941
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 (ΔLV) 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 ΔLV 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 ΔLV in the anterior-posterior diameter of the 5th rib with losses of 8.4 and 4.0% for males and females, respectively. Automation of CT-based static and ΔLV 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.
Details
- Title: Subtitle
- Automated detection of ribs in chest CT scans and assessment of changes in their morphology between Total Lung Capacity (TLC) and Residual Volume (RV)
- Creators
- Syed Ahmed Nadeem - University of IowaAlejandro P. Comellas - University of IowaEric A. Hoffman - University of IowaPunam K. Saha - University of Iowa
- Contributors
- Barjor S. Gimi (Editor) - Tufts Medical Ctr. (United States)Andrzej Krol (Editor) - SUNY Upstate Medical University
- Resource Type
- Conference proceeding
- Publication Details
- Vol.12468, pp.124680H-124680H-9
- Publisher
- SPIE
- DOI
- 10.1117/12.2653941
- ISSN
- 1605-7422
- Language
- English
- Date published
- 04/10/2023
- Academic Unit
- ICTS; Electrical and Computer Engineering; Roy J. Carver Department of Biomedical Engineering; Internal Medicine; Radiology; Pulmonary, Critical Care, and Occupational Medicine
- Record Identifier
- 9984413076502771
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