{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T23:46:50Z","timestamp":1776210410374,"version":"3.50.1"},"reference-count":33,"publisher":"Georg Thieme Verlag KG","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Rofo"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Pulmonary diseases can be analyzed with computed tomography (CT) with regard to their severity, distribution, and morphology. Up to now, this has mainly been done descriptively by radiologists, resulting in a high variance of results. Standardized structured reporting has the great potential to systematically record pulmonary changes and make them available for machine-readable reuse. However, it is still unclear how these structured findings can be analyzed in a simple and communicable way. The aim of this study was therefore to develop a method for comprehensible visualization and to apply it to a quality-assured data set.<\/jats:p>\n                  <jats:p>For the retrospective evaluation, chest CTs of patients from a total of 15 different disease groups such as infectious diseases, structural and vascular lung diseases, malignant lung diseases, and pleural diseases were included monocentrically. Structured reporting was performed in the RACOON infrastructure using the RECO (Phase 1) template. The systematically reported changes were evaluated both for relative frequency and for location, severity, distribution, and specific additional criteria. The results were summarized into a \u201cCT fingerprint\u201d using a self-developed visual RGB schema and systematically evaluated regarding the differences across the disease groups.<\/jats:p>\n                  <jats:p>A total of 359 patients were included. The relative frequency of pathological CT changes shows some overlap between the disease groups. In particular, the differentiation of subgroups is therefore limited. The use of fingerprints allows for better differentiation, as here not only the frequency but also the severity, localization, and distribution of the CT changes and additional criteria are taken into account. For instance, pneumonias can be differentiated depending on the causative pathogen: Based on the frequency distribution of pathological CT changes alone, Covid-19 pneumonia can be quickly classified as a pneumonia, particularly as a subgroup of viral pneumonia, but it is not possible to clearly differentiate it from other viral pneumonias. In contrast, visual analysis of the CT fingerprint allows for a better distinction. Overall, each of the 15 diseases shows an individual fingerprint.<\/jats:p>\n                  <jats:p>CT fingerprints enable the visualization and differentiation of pulmonary diseases based on typical CT patterns, making them a potential contribution to pandemic preparedness.<\/jats:p>","DOI":"10.1055\/a-2818-5917","type":"journal-article","created":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T22:50:14Z","timestamp":1776207014000},"source":"Crossref","is-referenced-by-count":0,"title":["CT Fingerprinting of Pulmonary Diseases: A Visual Analysis of Structured Reporting in RACOON-RECO"],"prefix":"10.1055","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-0612-4977","authenticated-orcid":false,"given":"Maximilian","family":"Bachl","sequence":"additional","affiliation":[{"name":"Institute of Radiology, Erlangen University Hospital, Erlangen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Theresa","family":"R\u00fcttinger","sequence":"additional","affiliation":[{"name":"Institute of Radiology, Erlangen University Hospital, Erlangen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lisa","family":"Siegler","sequence":"additional","affiliation":[{"name":"Institute of Radiology, Erlangen University Hospital, Erlangen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maximilian","family":"Sch\u00f6niger","sequence":"additional","affiliation":[{"name":"Institute of Radiology, Erlangen University Hospital, Erlangen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sebastian","family":"Arndt","sequence":"additional","affiliation":[{"name":"Institute of Radiology, Erlangen University Hospital, Erlangen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lorenz A.","family":"Kapsner","sequence":"additional","affiliation":[{"name":"Institute of Radiology, Erlangen University Hospital, Erlangen, Germany"},{"name":"Medical Centre for Information and Communication Technology, Erlangen University Hospital, Erlangen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Uder","sequence":"additional","affiliation":[{"name":"Institute of Radiology, Erlangen University Hospital, Erlangen, Germany"},{"name":"Imaging Science Institute Erlangen, Erlangen University Hospital, Erlangen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2540-850X","authenticated-orcid":false,"given":"Matthias Stefan","family":"May","sequence":"additional","affiliation":[{"name":"Institute of Radiology, Erlangen University Hospital, Erlangen, Germany"},{"name":"Imaging Science Institute Erlangen, Erlangen University Hospital, Erlangen, 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