Authors
Wenying Liu, Juan Peng, Jie Zou, Jingyuan Zhong, Xingyue Li, Jiabing Huang, Lianggeng Gong
Published in
Journal of thoracic disease. Volume 18. Issue 8. Pages 936. Aug 31, 2026. Epub Aug 28, 2026.
Abstract
Displacement of calcification stands out as the most easily observable imaging feature on non-contrast computed tomography (NCCT). This study aimed to develop and evaluate the diagnostic accuracy of a combined model for acute aortic syndrome (AAS) by integrating inward migration of calcification and other NCCT-derived imaging features.
The data of 69 patients with 120 lesions of inward migration of calcification who underwent chest or abdominal NCCT due to unexplained chest or abdominal pain were analyzed retrospectively. The presence or absence of AAS and its subtypes were confirmed through thoracoabdominal computed tomography angiography (CTA). The distance from the migrated calcification to the aortic adventitia and other imaging parameters were measured and recorded. Generalized estimating equations (GEE) were used to analyze imaging and clinical differences between the AAS-positive and AAS-negative groups, as well as among different AAS subtypes. The area under the receiver operating characteristic curve (AUC) evaluated diagnostic efficacy.
Finally, four indicators (D-dimer, the distance from migrated calcification to the aortic adventitia, the mean diameter-to-distance ratio and linear high-density) were identified as significant predictors of AAS. And the combined model incorporating the four indicators exhibited superior performance in detecting AAS (AUC =0.908, 95% confidence interval: 0.846-0.970). Notably, the distance was significantly higher in the aortic dissection (AD) group compared to the intramural hematoma (IMH) group and penetrating atherosclerotic ulcer (PAU) group, and the mean diameter-to-distance ratio was lower in the AD group compared with the IMH group.
NCCT emerges as a potential screening tool for AAS. The combined model based on the displacement of calcification on NCCT is valuable for diagnosing AAS.
PMID:
42724681
Bibliographic data and abstract were imported from PubMed on 11 Sep 2026.
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