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Abstract #5180

Automatic Aorta Quantification and Aneurysm Detection using 3D Deep Learning on Large-scale Non-Cardiac-Gated MRI

Thanh-Duc Nguyen1, Saurabh Garg1, Nasrin Akbari1, Saqib Basar1, Sean London2, Yosef Chodakiewitz2, Rajpaul Attariwala1,2, and Sam Hashemi1,2
1Voxelwise Imaging Technology Inc., Vancouver, BC, Canada, 2Prenuvo, Vancouver, BC, Canada

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Cardiovascular, Aorta quantificationWe present a validated AI technique for quantification of whole aorta diameter from non-cardiac-gated MRI. The mean absolute error between AI-predicted and radiologist-reported diameter is less than 0.27 and 0.249 cm, while Pearson correlation is 0.72 for the ascending (p-value=0.0002) and 0.74 for the descending aorta (p-values=0.0012). SVM classifiers indicated that a 3.15 cm (AUC=0.93) threshold is used to detect a descending aortic aneurysm while a 4.3 cm (AUC=0.92) threshold is used for ascending aortic aneurysm. Large-scale analysis on 3485 individuals showed aortic diameter to increase with age in male and female populations.

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Keywords