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Assessment of Shape-based Features Ability to Predict the Ascending Aortic Aneurysm Growth by Leonardo Geronzi; Pascal Haigron; Antonio Martinez; Kexin Yan; Michel Rochette; Aline Bel-Brunon; Jean Porterie; Siyu Lin; Diana Marcela Marin-Castrillon; Alain Lalande; Olivier Bouchot; Morgan Daniel; Pierre Escrig; Jacques Tomasi; Pier Paolo Valentini; Marco Evangelos Biancolini is a Medicine article available to read on EtoBox.
What is Assessment of Shape-based Features Ability to Predict the Ascending Aortic Aneurysm Growth about?
The current guidelines for the ascending aortic aneurysm (AsAA) treatment recommend surgery mainly according to the maximum diameter assessment. This criterion has already proven to be often inefficient in identifying patients at high risk of aneurysm growth and rupture. In this study, we propose a method to compute a set of local shape features that, in addition to the maximum diameter __D__, are intended to improve the classification performances for the ascending aortic aneurysm growth risk assessment. Apart from __D__, these are the ratio __DCR__ between __D__ and the length of the ascending aorta centerline, the ratio __EILR__ between the length of the external and the internal lines and the tortuosity __T__. 50 patients with two 3D acquisitions at least 6 months apart were segmented and the growth rate (GR) with the shape features related to the first exam computed. The correlation between them has been investigated. After, the dataset was divided into two classes according to the growth rate value. We used six different classifiers with input data exclusively from the first exam to predict the class to which each patient belonged. A first classification was performed using o
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- Author
- Leonardo Geronzi; Pascal Haigron; Antonio Martinez; Kexin Yan; Michel Rochette; Aline Bel-Brunon; Jean Porterie; Siyu Lin; Diana Marcela Marin-Castrillon; Alain Lalande; Olivier Bouchot; Morgan Daniel; Pierre Escrig; Jacques Tomasi; Pier Paolo Valentini; Marco Evangelos Biancolini
- Publisher
- Frontiers Media SA
- Published
- 2023
- Language
- EN
- Field
- Medicine (Health Sciences)