Research Article| Volume 382, P91-95, July 01, 2023

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Identification of acute aortic syndromes based on cross-sectional variability of Hounsfield units


      • We examined if cross-sectional Hounsfield Units (HU) variability allow reliable identification of aortic dissections including IMH.
      • 362 patients presenting with acute chest pain or respiratory distress were included.
      • the aorta was segmented and HU measurements were made at cross-sections in the ascending and descending aorta.
      • maximum difference in HUs at any one location was significantly higher for Acute Aortic Syndromes (AAS) subjects than controls.
      • cross-sectional variability of HU reliably identifies aortic dissection including IMH and could be feasible for an automated identification algorithm.



      A characteristic feature of communicating aortic dissections (CD) is the dissection flap between the true and false lumen. However, in intramural hematomas (IMH) a flap is not visible. We aimed to determine if cross-sectional HU variability allow reliable identification of aortic dissections including IMH.


      We included 362 patients presenting with acute chest pain (CP) or respiratory distress (RD) and underwent contrast-enhanced CTA with or without ECG-gating. In the derivation group we included 72 CP patients with and 74 without AAS. In the validation group we included 108 CP or RD patients with and 108 without AAS. The adventitial border of the aorta was visually identified and measurements were performed at 6 locations along the ascending and descending aorta. At each cross-section 5 circular ROI measurements of HU were made and the maximum HU difference calculated.


      In the derivation and validation group the maximum difference in HUs at any one location was significantly higher for AAS subjects than controls (validation group: median = 128.5 vs. 34.0, p-value Wilcoxon two-sample test <0.001). In the validation group, the estimated AUC was 0.939 with 95% CIs of [0.906, 0.972], indicating that the maximum difference in HUs is a strong predictor of AAS (p < 0.001).


      Our data provide evidence that cross-sectional variability of Hounsfield Unit reliably identifies aortic dissection including IMH in dedicated ECG-gated aorta scans but also non-gated chest CTs with limited aortic contrast enhancement. These results suggest that this approach could be feasible for an automated algorithm for identification of AAS.



      AAS (Acute Aortic Syndrome), AUC (Area under the Curve), AD (Aortic Dissection), CD (Communication Dissection), CP (Chest Pain), IMH (Intramural Hematoma), HU (Hounsfield Unit), PE (Pulmonary Embolism), RD (Respiratory Distress)
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      Linked Article

      • CT features of acute aortic syndromes: A groundwork for AI and the future of photon-counting technology
        International Journal of Cardiology
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          Acute aortic syndromes (AAS) represent a major cause of morbidity and mortality, with an estimated incidence just short of 10 cases every 100,000 individuals in Western countries, currently on the rise. The mortality rate from AAS is relevant, nearing 50% by two weeks from symptom onset for patients with type A aortic dissection (AD) [1]. However, symptoms of AAS are not specific, including chest pain and respiratory distress, and may be misattributed to other pathologic entities which warrant different treatment options [2].
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