{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T20:13:12Z","timestamp":1790712792241,"version":"4.1.0"},"reference-count":12,"publisher":"Oxford University Press (OUP)","issue":"1186","license":[{"start":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T00:00:00Z","timestamp":1782691200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Airway imaging guidelines for primary ciliary dyskinesia (PCD) are currently limited. Given the progressive nature of this disease, standardized imaging protocols, particularly at key clinical milestones such as diagnosis, routine reviews, and exacerbations, may improve monitoring of disease progression, support comparison of outcomes across centers, and provide robust parameters for clinical trials.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>To document current practices, we conducted a global survey of PCD clinicians. An online questionnaire was distributed via international PCD networks, covering imaging use at diagnosis, during routine assessments, and at exacerbations treated with oral or intravenous antibiotics. Responses were received from 120 clinicians across 90 centers in 33 countries. Modalities assessed included X-ray, CT scans, MRI, and ultrasound, with analyses stratified by center type and size.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>At diagnosis, 94% of clinicians reported using imaging. Chest X-ray was most common for children under 5\u2009years (55%), whereas CT was preferred for older patients (66%). During routine assessments, 67.5% of clinicians used imaging, but timing and modality varied, with CT more frequent in pediatric and mixed centers. Imaging during exacerbations differed by treatment route: chest X-ray was the most common modality, used by 57.1% for oral antibiotic-treated episodes and 73.3% for intravenous episodes. CT use was higher with intravenous treatment (15.8% vs. 4.2%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Although practices varied, consistent trends at diagnosis and follow-up highlight opportunities for consensus.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Advances in knowledge<\/jats:title>\n                    <jats:p>Standardized imaging protocols could enhance clinical care, enable meaningful research comparisons, and improve outcomes in PCD.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bjr\/tqag156","type":"journal-article","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T16:42:53Z","timestamp":1782751373000},"page":"2105-2109","source":"Crossref","is-referenced-by-count":0,"title":["Airway imaging practices in primary ciliary dyskinesia: a global survey to guide standardized guidelines"],"prefix":"10.1093","volume":"99","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6129-9075","authenticated-orcid":false,"given":"Phil","family":"Robinson","sequence":"first","affiliation":[{"name":"Department of Respiratory and Sleep Medicine, Royal Children\u2019s Hospital , Melbourne 3052,","place":["Australia"]},{"name":"Respiratory Research group, Murdoch Children\u2019s Research Group , Melbourne 3052,","place":["Australia"]},{"name":"Department of Paediatrics, University of Melbourne , Melbourne 3052,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Megumi","family":"Yokote","sequence":"additional","affiliation":[{"name":"Department of Paediatrics, University of Melbourne , Melbourne 3052,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ophir","family":"Bar-On","sequence":"additional","affiliation":[{"name":"Department of Respiratory and Sleep Medicine, Royal Children\u2019s Hospital , Melbourne 3052,","place":["Australia"]},{"name":"Respiratory Research group, Murdoch Children\u2019s Research Group , Melbourne 3052,","place":["Australia"]},{"name":"Faculty of Medical & Health Sciences, Tel-Aviv University , Tel Aviv 6997801,","place":["Israel"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,6,29]]},"reference":[{"key":"2026092915470431000_tqag156-B1","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1002\/ppul.23304","article-title":"Genetic disorders of mucociliary clearance consortium. Diagnosis, monitoring, and treatment of primary ciliary dyskinesia: PCD foundation consensus recommendations based on state-of-the-art review","volume":"51","author":"Shapiro","year":"2016","journal-title":"Pediatr Pulmonol"},{"key":"2026092915470431000_tqag156-B2","doi-asserted-by":"crossref","DOI":"10.1542\/peds.2015-1784","article-title":"Clinical practice guidelines from the cystic fibrosis foundation for preschoolers with cystic fibrosis","volume":"137","author":"Lahiri","year":"2016","journal-title":"Pediatrics"},{"key":"2026092915470431000_tqag156-B3","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.jcf.2018.02.006","article-title":"ECFS best practice guidelines: the 2018 revision","volume":"17","author":"Castellani","year":"2018","journal-title":"J Cyst Fibros"},{"key":"2026092915470431000_tqag156-B4","doi-asserted-by":"publisher","first-page":"1564156","DOI":"10.3389\/fped.2025.1564156","article-title":"Beyond the present: current and future perspectives on the role of infections in pediatric PCD","volume":"13","author":"Frohlich","year":"2025","journal-title":"Front Pediatr"},{"key":"2026092915470431000_tqag156-B5","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.prrv.2015.10.002","article-title":"Treatment recommendations in primary ciliary dyskinesia","volume":"18","author":"Polineni","year":"2016","journal-title":"Paediatr Respir Rev"},{"key":"2026092915470431000_tqag156-B6"},{"key":"2026092915470431000_tqag156-B7","doi-asserted-by":"publisher","first-page":"00147","DOI":"10.1183\/23120541.00147-2018","article-title":"Pulmonary exacerbations in patients with primary ciliary dyskinesia: an expert consensus definition for use in clinical trials","volume":"5","author":"Lucas","year":"2019","journal-title":"ERJ Open Res"},{"key":"2026092915470431000_tqag156-B8","doi-asserted-by":"publisher","first-page":"i9","DOI":"10.1136\/bmjqs-2013-002378","article-title":"The cystic fibrosis foundation patient registry as a tool for use in quality improvement","volume":"23 (Suppl. 1)","author":"Schechter","year":"2014","journal-title":"BMJ Quality & Safety"},{"key":"2026092915470431000_tqag156-B9","doi-asserted-by":"publisher","first-page":"7039","DOI":"10.3390\/jcm12227039","article-title":"The diagnostic utility of artificial intelligence-guided computed tomography-based severity scores for predicting short-term clinical outcomes in adults with COVID-19 pneumonia","volume":"12","author":"Atceken","year":"2023","journal-title":"J Clin Med"},{"key":"2026092915470431000_tqag156-B10","doi-asserted-by":"crossref","first-page":"2188","DOI":"10.1007\/s00330-021-08365-z","article-title":"A fully automatic artificial intelligence\u2013based CT image analysis system for accurate detection, diagnosis, and quantitative severity evaluation of pulmonary tuberculosis","volume":"3","author":"Yan","year":"2022","journal-title":"Eur Radiol"},{"key":"2026092915470431000_tqag156-B11","doi-asserted-by":"publisher","first-page":"993","DOI":"10.3390\/jpm11100993","article-title":"Artificial intelligence and COVID-19 using chest CT scan and chest X-ray images: machine learning and deep learning approaches for diagnosis and treatment","volume":"11","author":"Fusco","year":"2021","journal-title":"J Pers Med"},{"key":"2026092915470431000_tqag156-B12","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1378\/chest.13-0588","article-title":"Automated CT scan scores of bronchiectasis and air trapping in cystic fibrosis","volume":"145","author":"DeBoer","year":"2014","journal-title":"Chest"}],"container-title":["British Journal of Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bjr\/advance-article-pdf\/doi\/10.1093\/bjr\/tqag156\/68645659\/tqag156.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bjr\/article-pdf\/99\/1186\/2105\/68645659\/tqag156.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bjr\/article-pdf\/99\/1186\/2105\/68645659\/tqag156.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T19:47:09Z","timestamp":1790711229000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bjr\/article\/99\/1186\/2105\/8721563"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,29]]},"references-count":12,"journal-issue":{"issue":"1186","published-online":{"date-parts":[[2026,6,29]]},"published-print":{"date-parts":[[2026,10,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bjr\/tqag156","relation":{},"ISSN":["0007-1285","1748-880X"],"issn-type":[{"value":"0007-1285","type":"print"},{"value":"1748-880X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,10]]},"published":{"date-parts":[[2026,6,29]]}}}