Aortic shape variation after frozen elephant trunk procedure predicts aortic events: Principal component analysis...

Area of Science:

• Cardiovascular Surgery
• Medical Imaging
• Machine Learning

Background:

• The frozen elephant trunk (FET) procedure is a key technique for treating type A aortic dissection and complex aortic arch pathologies.
• The long-term implications of aortic shape following FET repair are not fully understood.
• Understanding 3D aortic shape variations is crucial for predicting patient outcomes.

Purpose of the Study:

• To employ machine learning for a detailed description of 3D aortic shape variations post-FET repair.
• To correlate these shape variations with the occurrence of aortic events.

Main Methods:

• Computed tomography angiography (CTA) data from 93 patients undergoing FET repair were used.
• Patient-specific aortic models and centerlines were generated.
• Principal component analysis (PCA) was applied to aortic centerlines to identify shape modulators and scores, which were then correlated with adverse aortic events.

Main Results:

• The first three principal components explained 74.5% of the total aortic shape variance.
• These components represented variations in arch height-to-length ratio, isthmus angle, and anterior-posterior arch tilt.
• A significant association was found between the aortic angle at the isthmus (second principal component) and the occurrence of aortic events (HR 0.98, P=0.046).

Conclusions:

• The angulation at the aortic isthmus, as described by the second principal component, is associated with adverse aortic events.
• Further investigation into aortic shape variations, considering biomechanical properties and hemodynamics, is warranted.
• This study provides a quantitative method for assessing aortic shape post-FET repair and its clinical relevance.