Artificial Intelligence-based CT Assessment of Bronchiectasis : The COPDGene Study
Background CT is the standard method used to assess bronchiectasis. A higher airway-to-artery diameter ratio (AAR) is typically used to identify enlarged bronchi and bronchiectasis; however, current imaging methods are limited in assessing the extent of this metric in CT scans. Purpose To determine the extent of AARs using an artificial intelligence-based chest CT and assess the association of AARs with exacerbations over time. Materials and Methods In a secondary analysis of ever-smokers from the prospective, observational, multicenter COPDGene study, AARs were quantified using an artificial intelligence tool. The percentage of airways with AAR greater than 1 (a measure of airway dilatation) in each participant on chest CT scans was determined. Pulmonary exacerbations were prospectively determined through biannual follow-up (from July 2009 to September 2021). Multivariable zero-inflated regression models were used to assess the association between the percentage of airways with AAR greater than 1 and the total number of pulmonary exacerbations over follow-up. Covariates included demographics, lung function, and conventional CT parameters. Results Among 4192 participants (median age, 59 years; IQR, 52-67 years; 1878 men [45%]), 1834 had chronic obstructive pulmonary disease (COPD). During a 10-year follow-up and in adjusted models, the percentage of airways with AARs greater than 1 (quartile 4 vs 1) was associated with a higher total number of exacerbations (risk ratio [RR], 1.08; 95% CI: 1.02, 1.15; P = .01). In participants meeting clinical and imaging criteria of bronchiectasis (ie, clinical manifestations with ≥3% of AARs >1) versus those who did not, the RR was 1.37 (95% CI: 1.31, 1.43; P < .001). Among participants with COPD, the corresponding RRs were 1.10 (95% CI: 1.02, 1.18; P = .02) and 1.32 (95% CI: 1.26, 1.39; P < .001), respectively. Conclusion In ever-smokers with chronic obstructive pulmonary disease, artificial intelligence-based CT measures of bronchiectasis were associated with more exacerbations over time. Clinical trial registration no. NCT00608764 © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Schiebler and Seo in this issue.
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
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Zur Gesamtaufnahme - volume:307 |
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| Enthalten in: |
Radiology - 307(2023), 1 vom: 20. Apr., Seite e221109 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Díaz, Alejandro A [VerfasserIn] |
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Journal Article |
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Date Completed 22.02.2024 Date Revised 22.02.2024 published: Print-Electronic CommentIn: Radiology. 2022 Dec 13;:222675. - PMID 36511811 Citation Status MEDLINE |
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| doi: |
10.1148/radiol.221109 |
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NLM35023888X |
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| 100 | 1 | |a Díaz, Alejandro A |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Artificial Intelligence-based CT Assessment of Bronchiectasis |b The COPDGene Study |
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| 500 | |a Date Completed 22.02.2024 | ||
| 500 | |a Date Revised 22.02.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a CommentIn: Radiology. 2022 Dec 13;:222675. - PMID 36511811 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Background CT is the standard method used to assess bronchiectasis. A higher airway-to-artery diameter ratio (AAR) is typically used to identify enlarged bronchi and bronchiectasis; however, current imaging methods are limited in assessing the extent of this metric in CT scans. Purpose To determine the extent of AARs using an artificial intelligence-based chest CT and assess the association of AARs with exacerbations over time. Materials and Methods In a secondary analysis of ever-smokers from the prospective, observational, multicenter COPDGene study, AARs were quantified using an artificial intelligence tool. The percentage of airways with AAR greater than 1 (a measure of airway dilatation) in each participant on chest CT scans was determined. Pulmonary exacerbations were prospectively determined through biannual follow-up (from July 2009 to September 2021). Multivariable zero-inflated regression models were used to assess the association between the percentage of airways with AAR greater than 1 and the total number of pulmonary exacerbations over follow-up. Covariates included demographics, lung function, and conventional CT parameters. Results Among 4192 participants (median age, 59 years; IQR, 52-67 years; 1878 men [45%]), 1834 had chronic obstructive pulmonary disease (COPD). During a 10-year follow-up and in adjusted models, the percentage of airways with AARs greater than 1 (quartile 4 vs 1) was associated with a higher total number of exacerbations (risk ratio [RR], 1.08; 95% CI: 1.02, 1.15; P = .01). In participants meeting clinical and imaging criteria of bronchiectasis (ie, clinical manifestations with ≥3% of AARs >1) versus those who did not, the RR was 1.37 (95% CI: 1.31, 1.43; P < .001). Among participants with COPD, the corresponding RRs were 1.10 (95% CI: 1.02, 1.18; P = .02) and 1.32 (95% CI: 1.26, 1.39; P < .001), respectively. Conclusion In ever-smokers with chronic obstructive pulmonary disease, artificial intelligence-based CT measures of bronchiectasis were associated with more exacerbations over time. Clinical trial registration no. NCT00608764 © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Schiebler and Seo in this issue | ||
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| 700 | 1 | |a Wang, Wei |e verfasserin |4 aut | |
| 700 | 1 | |a San José Estépar, Rubén |e verfasserin |4 aut | |
| 700 | 1 | |a Yen, Andrew |e verfasserin |4 aut | |
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