Distinguishing acute from chronic aortic dissections using CT imaging features

Area of Science:

• Radiology
• Cardiovascular Imaging
• Thoracic Imaging

Background:

• Aortic dissection is a serious condition requiring accurate diagnosis.
• Differentiating acute from chronic aortic dissection is crucial for patient management.
• Computed tomography (CT) is a primary imaging modality for aortic dissection.

Purpose of the Study:

• To compare CT imaging features between acute aortic dissection (AAD) and chronic aortic dissection (CAD).
• To develop and validate a predictive model for distinguishing AAD from CAD using CT features.

Main Methods:

• Retrospective review of 120 CT scans from 105 patients with aortic dissection.
• Analysis of various imaging features, including flap characteristics and false lumen (FL) attributes.
• Statistical comparison of feature frequencies between AAD and CAD groups.
• Development and testing of a predictive model on an independent set of 120 CT scans.

Main Results:

• Significant differences in CT features were observed between AAD and CAD.
• AAD features included periaortic soft tissue opacity, curved, and mobile flaps.
• CAD features included thick flaps, FL calcification, FL thrombus, dilated FL, and curling tear edges.
• The predictive model achieved high accuracy (AUC 0.98) in differentiating dissection chronicity.

Conclusions:

• CT imaging features reliably differentiate acute from chronic aortic dissections.
• A combination of specific CT findings can accurately predict the chronicity of aortic dissection.
• This predictive model can aid in clinical decision-making for patients with aortic dissection.