{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T02:44:56Z","timestamp":1772765096999,"version":"3.50.1"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T00:00:00Z","timestamp":1732838400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T00:00:00Z","timestamp":1732838400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur Radiol"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n The assessment of bronchus\u2013artery (BA) metrics on chest CT is important for detecting airway abnormalities. It is less clear how BA metrics are dependent on lung volume.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n CTs were obtained from a COPDGene substudy investigating the impact of radiation dose on lung density. Patients with chronic obstructive pulmonary disease underwent a full-dose and a reduced-dose CT in the same imaging session. CTs were automatically analyzed by measuring diameters of the bronchial outer edge (B<\/jats:italic>\n out<\/jats:sub>), bronchial inner wall (B<\/jats:italic>\n in<\/jats:sub>), artery (A<\/jats:italic>), and bronchial wall thickness (B<\/jats:italic>\n wt<\/jats:sub>) from segmental (G<\/jats:italic>\n 0<\/jats:sub>) and distal generations. BA ratios were computed: B<\/jats:italic>\n out<\/jats:sub>\/A<\/jats:italic>, B<\/jats:italic>\n in<\/jats:sub>\/A<\/jats:italic>, B<\/jats:italic>\n wt<\/jats:sub>\/A<\/jats:italic>, and bronchial wall area\/bronchial outer area (B<\/jats:italic>\n wa<\/jats:sub>\/B<\/jats:italic>\n oa<\/jats:sub>). The total lung volume of the CT (TLC-CT) was computed. Differences between the volumes between the two CTs were expressed as % of the highest TLC-CT (\u0394TLC-CT%). For the BA metrics of each CT, we computed the median of measurements in G1\u20136.<\/jats:sub> Mixed-effect models were used to investigate the influence of TLC-CT on BA metrics adjusted for dose protocol.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n One thousand three hundred nineteen patients with a mean (SD) age of 64.4 (8.7) years were included. Three hundred twenty-nine (124) BA pairs were analyzed per CT. No significant difference was found for TLC-CT in relation to dose (p<\/jats:italic>\u2009=\u20090.17). A \u0394TLC-CT% of >10% (found in 121, 9%) led to 0.03 and 0.05 decreases in B<\/jats:italic>\n out<\/jats:sub>\/A<\/jats:italic> and B<\/jats:italic>\n in<\/jats:sub>\/A<\/jats:italic> and 0.008 and 0.11 decrease in log (B<\/jats:italic>\n wt<\/jats:sub>\/A<\/jats:italic>) and log (B<\/jats:italic>\n wa<\/jats:sub>\/B<\/jats:italic>\n oa<\/jats:sub>), and a 0.03 increase in B<\/jats:italic>\n in<\/jats:sub> and 0.06, 0.12, and 0.04 decrease in B<\/jats:italic>\n out<\/jats:sub>, log (B<\/jats:italic>\n wt<\/jats:sub>), and log (A<\/jats:italic>) (all p<\/jats:italic>\u2009<\u20090.001).<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Variations in TLC over 10% between time points significantly influence bronchial dimensions, affecting BA metrics. Standardizing volumes is recommended for sensitive tracking of airway disease changes over time.<\/jats:p>\n <\/jats:sec>\n \n Key Points<\/jats:title>\n \n \n Question<\/jats:italic>\n <\/jats:bold>\n Are BA metrics dependent on total lung capacity (TLC), and if so, how<\/jats:italic>?<\/jats:p>\n \n \n Findings<\/jats:italic>\n <\/jats:bold>\n TLC variations over 10% between time points significantly influence bronchial dimensions, affecting BA metrics. Variations below 10% between CT scans have little effect on BA metrics<\/jats:italic>.<\/jats:p>\n \n \n Clinical relevance<\/jats:italic>\n <\/jats:bold>\n Small lung volume differences between chest CTs have little impact on bronchus and artery metrics; it is imperative to standardize chest CT lung volumes to ensure precise diagnosis and monitoring of airway disease<\/jats:italic>.<\/jats:p>\n <\/jats:sec>","DOI":"10.1007\/s00330-024-11126-3","type":"journal-article","created":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T17:42:50Z","timestamp":1732902170000},"page":"2990-2998","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Effect of inspiratory lung volume on bronchial and arterial dimensions and ratios on chest computed tomography in patients with chronic obstructive pulmonary disease"],"prefix":"10.1007","volume":"35","author":[{"given":"Yuxin","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rudolfs","family":"Latisenko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David A.","family":"Lynch","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pierluigi","family":"Ciet","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jean-Paul","family":"Charbonnier","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5628-6667","authenticated-orcid":false,"given":"Harm A. 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J.-P.C. is an employee and shareholder at Thirona. H.A.W.M.T. is a chief medical officer at Thirona. The remaining authors declare no conflicts of interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"One of the authors has significant statistical expertise.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Written informed consent was obtained from all subjects (patients) in this study.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Institutional Review Board approval was obtained.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Some study subjects or cohorts have been previously reported in Hatt et al Radiol Cardiothorac Imaging 2021. This dataset was collected previously including 21 centers in the COPDGene study. This dataset was not previously analyzed with the automatic bronchus\u2013artery analysis. In the previous study, the dataset consisted of 1205 patients collected retrospectively by a COPDGene substudy (Hatt et al Radiol Cardiothorac Imaging 2021) who underwent FD and RD CT image acquisition protocols. The previous study aimed to evaluate the reproducibility and predicted clinical outcomes of CT-based quantitative lung density measurements using FD and RD scans. CT attenuation at the 15th percentile of the lung CT histogram (Perc15) was computed for all 2410 CTs. In the recent study, the dataset consisted of 1319 patients. The primary aim of the current study is to assess the effect of inspiratory lung volume on BA metrics. The acquisition of the FD and RD CTs per patient, performed within a short time interval in the same imaging session, allowed us to investigate the relationship between inspiratory lung volume on BA metrics. 2638 inspiratory CTs were automatically analyzed by LungQ. For segmental (G0) and distal generations, we measured bronchial outer edge diameter (Bout), bronchial inner wall diameter (Bin), Bwt, and diameter of the adjacent artery (A). From these parameters, we computed the following ratios: Bout\/A, Bin\/A, Bwt\/A, and bronchial wall area\/bronchial outer area (Bwa\/Boa). Furthermore, total lung volume was obtained from the same software package.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}