Artikel ; Online: Assessing the role of an artificial intelligence assessment tool for thoracic aorta diameter on routine chest CT.
The British journal of radiology
2023 Band 96, Heft 1151, Seite(n) 20220853
Abstract: Objective: To assess the diagnostic accuracy and clinical impact of automated artificial intelligence (AI) measurement of thoracic aorta diameter on routine chest CT.: Methods: A single-centre retrospective study involving three cohorts. 210 ... ...
Abstract | Objective: To assess the diagnostic accuracy and clinical impact of automated artificial intelligence (AI) measurement of thoracic aorta diameter on routine chest CT. Methods: A single-centre retrospective study involving three cohorts. 210 consecutive ECG-gated CT aorta scans (mean age 75 ± 13) underwent automated analysis (AI-Rad Companion Chest CT, Siemens) and were compared to a reference standard of specialist cardiothoracic radiologists for accuracy measuring aortic diameter. A repeated measures analysis tested reporting consistency in a second cohort (29 patients, mean age 61 ± 17) of immediate sequential pre-contrast and contrast CT aorta acquisitions. Potential clinical impact was assessed in a third cohort of 197 routine CT chests (mean age 66 ± 15) to document potential clinical impact. Results: AI analysis produced a full report in 387/436 (89%) and a partial report in 421/436 (97%). Manual Conclusion: AI has good agreement with expert readers at the mid-ascending aorta and has high specificity, but low sensitivity, at detecting dilated aortas on non-dedicated chest CTs. Advances in knowledge: An AI tool may improve the detection of previously unknown thoracic aorta dilatation on chest CTs |
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Mesh-Begriff(e) | Humans ; Middle Aged ; Aged ; Aged, 80 and over ; Adult ; Aorta, Thoracic/diagnostic imaging ; Artificial Intelligence ; Retrospective Studies ; Tomography, X-Ray Computed/methods ; Aorta ; Aortic Diseases/diagnostic imaging |
Sprache | Englisch |
Erscheinungsdatum | 2023-07-26 |
Erscheinungsland | England |
Dokumenttyp | Journal Article |
ZDB-ID | 2982-8 |
ISSN | 1748-880X ; 0007-1285 |
ISSN (online) | 1748-880X |
ISSN | 0007-1285 |
DOI | 10.1259/bjr.20220853 |
Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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