Development and External Validation of [18F]FDG PET-CT-Derived Radiomic Models for Prediction of Abdominal Aortic Aneurysm Growth Rate

Development and External Validation of [18F]FDG PET-CT-Derived Radiomic Models for Prediction of Abdominal Aortic Aneurysm Growth Rate

Objective (1): To develop and validate a machine learning (ML) model using radiomic features (RFs) extracted from [18F]FDG PET-CT to predict abdominal aortic aneurysm (AAA) growth rate. Methods (2): This retrospective study included 98 internal and 55 external AAA patients undergoing [18F]FDG PET-CT...

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Main Authors: Simran Singh Dhesi, Pratik Adusumilli, Nishant Ravikumar, Mohammed A. Waduud, Russell Frood, Alejandro F. Frangi, Garry McDermott, James H. F. Rudd, Yuan Huang, Jonathan R. Boyle, Maysoon Elkhawad, David E. Newby, Nikhil Joshi, Jing Yi Kwan, Patrick Coughlin, Marc A. Bailey, Andrew F. Scarsbrook
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Algorithms
Subjects:
abdominal aortic aneurysm
positron emission tomography–computed tomography
machine learning
radiomics
Online Access:https://www.mdpi.com/1999-4893/18/2/86
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