{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T11:15:08Z","timestamp":1787915708413,"version":"build-2784847793"},"reference-count":89,"publisher":"Oxford University Press (OUP)","issue":"1184","license":[{"start":{"date-parts":[[2025,7,12]],"date-time":"2025-07-12T00:00:00Z","timestamp":1752278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01HL142625"],"award-info":[{"award-number":["R01HL142625"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The Roy J. Carver Charitable Trust","award":["19-5154"],"award-info":[{"award-number":["19-5154"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Chronic obstructive pulmonary disease (COPD) is a heterogeneous condition with complicated structural and functional impairments. For decades now, chest CT has been used to quantify various abnormalities related to COPD. More recently, with the newer data-driven approaches, biomarker development and validation have evolved rapidly. Studies now target multiple anatomical structures including lung parenchyma, the airways, the vasculature, and the fissures to better characterize COPD. This review explores the evolution of chest CT biomarkers in COPD, beginning with traditional thresholding approaches that quantify emphysema and airway dimensions. We then highlight some of the texture analysis efforts that have been made over the years for subtyping lung tissue. We also discuss image registration-based biomarkers that have enabled spatially-aware mechanisms for understanding local abnormalities within the lungs. More recently, deep learning has enabled automated biomarker extraction, offering improved precision in phenotype characterization and outcome prediction. We highlight the most recent of these approaches as well. Despite these advancements, several challenges remain in terms of dataset heterogeneity, model generalizability, and clinical interpretability. This review lastly provides a structured overview of these limitations and highlights future potential of CT biomarkers in personalized COPD management.<\/jats:p>","DOI":"10.1093\/bjr\/tqaf160","type":"journal-article","created":{"date-parts":[[2025,7,12]],"date-time":"2025-07-12T16:45:55Z","timestamp":1752338755000},"page":"1438-1447","source":"Crossref","is-referenced-by-count":5,"title":["Seeing is believing\u2014on the utility of CT in phenotyping chronic obstructive pulmonary disease"],"prefix":"10.1093","volume":"99","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2422-2639","authenticated-orcid":false,"given":"Hira A","family":"Awan","sequence":"first","affiliation":[{"name":"The Roy J. Carver Department of Biomedical Engineering, The University of Iowa , Iowa City, IA 52242,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad F A","family":"Chaudhary","sequence":"additional","affiliation":[{"name":"Division of Pulmonary, Allergy and Critical Care Medicine, Center for Lung Analytics and Imaging Research (CLAIR), Heersink School of Medicine, The University of Alabama at Birmingham , Birmingham, AL 35294,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph M","family":"Reinhardt","sequence":"additional","affiliation":[{"name":"The Roy J. Carver Department of Biomedical Engineering, The University of Iowa , Iowa City, IA 52242,","place":["United States"]},{"name":"Department of Radiology, The University of Iowa , Iowa City, IA 52242,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,7,12]]},"reference":[{"key":"2026072203070167700_tqaf160-B1","doi-asserted-by":"crossref","first-page":"e2346598","DOI":"10.1001\/jamanetworkopen.2023.46598","article-title":"Global burden of chronic obstructive pulmonary disease through 2050","volume":"6","author":"Boers","year":"2023","journal-title":"JAMA Network Open"},{"key":"2026072203070167700_tqaf160-B2","doi-asserted-by":"crossref","first-page":"1222","DOI":"10.1002\/cpt.1540","article-title":"Review of drug development guidance to treat chronic obstructive pulmonary disease: US and EU perspectives","volume":"106","author":"van Haarst","year":"2019","journal-title":"Clin Pharmacol Ther"},{"key":"2026072203070167700_tqaf160-B3","first-page":"384","article-title":"COPDGene\u00ae 2019: redefining the diagnosis of chronic obstructive pulmonary disease","volume":"6","author":"Lowe","year":"2019","journal-title":"Chronic Obstr Pulm Dis"},{"key":"2026072203070167700_tqaf160-B4","doi-asserted-by":"crossref","first-page":"32","DOI":"10.3109\/15412550903499522","article-title":"Genetic epidemiology of COPD (COPDGene) study design","volume":"7","author":"Regan","year":"2010","journal-title":"COPD"},{"key":"2026072203070167700_tqaf160-B5","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1136\/thoraxjnl-2013-203897","article-title":"Design of the subpopulations and intermediate outcomes in COPD study (SPIROMICS)","volume":"69","author":"Couper","year":"2014","journal-title":"Thorax"},{"key":"2026072203070167700_tqaf160-B6","first-page":"444","article-title":"Design of the SPIROMICS study of early COPD progression: SOURCE study","volume":"11","author":"Curtis","year":"2024","journal-title":"Chronic Obstr Pulm Dis"},{"key":"2026072203070167700_tqaf160-B7","doi-asserted-by":"crossref","first-page":"1208","DOI":"10.1164\/rccm.202307-1203OC","article-title":"Structural predictors of lung function decline in young smokers with normal spirometry","volume":"209","author":"Ritchie","year":"2024","journal-title":"Am J Respir Crit Care Med"},{"key":"2026072203070167700_tqaf160-B8","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1183\/09031936.00111707","article-title":"Evaluation of COPD longitudinally to identify predictive surrogate end-points (ECLIPSE)","volume":"31","author":"Vestbo","year":"2008","journal-title":"Eur Res J"},{"key":"2026072203070167700_tqaf160-B9"},{"key":"2026072203070167700_tqaf160-B10","doi-asserted-by":"crossref","first-page":"20211364","DOI":"10.1259\/bjr.20211364","article-title":"Origins of and lessons from quantitative functional X-ray computed tomography of the lung","volume":"95","author":"Hoffman","year":"2022","journal-title":"Br J Radiol"},{"key":"2026072203070167700_tqaf160-B11","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1148\/radiol.12111270","article-title":"Chronic obstructive pulmonary disease: CT quantification of airways disease","volume":"265","author":"Hackx","year":"2012","journal-title":"Radiology"},{"key":"2026072203070167700_tqaf160-B12","doi-asserted-by":"crossref","first-page":"S286","DOI":"10.1513\/AnnalsATS.201807-475MG","article-title":"Back to the box: using lung volumes to predict susceptibility to develop chronic obstructive pulmonary disease among smokers","volume":"15","author":"Zeng","year":"2018","journal-title":"Annals ATS"},{"key":"2026072203070167700_tqaf160-B13","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.3346\/jkms.2015.30.10.1459","article-title":"The prognostic value of residual volume\/total lung capacity in patients with chronic obstructive pulmonary disease","volume":"30","author":"Shin","year":"2015","journal-title":"J Korean Med Sci"},{"key":"2026072203070167700_tqaf160-B14","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1378\/chest.94.4.782","article-title":"\u201cDensity mask\u201d. 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