CT Radiomic Features of the Crystalline Lens and Association with Age, Hypertension and Cerebral White Matter Lesions
Anne Strübing, Estelle Akl, Chris Lappe, Stefan Polei, Oliver Stachs, Tobias Lindner, Mathias Manzke, Sönke Langner, Felix G. Meinel, Marc-André Weber, Thoralf Niendorf, Ebba Beller

TL;DR
This study explores CT-based radiomic features of the eye lens and finds associations with age, white matter lesions, but not hypertension.
Contribution
First study to use CT-based radiomic analysis of the crystalline lens for detecting differences in small vessel disease.
Findings
17 radiomic features were linked to age-related changes in the eye lens.
Three features (ClusterShade, Skewness, DifferenceVariance) showed significant differences in patients with severe white matter lesions.
No significant radiomic features were found between patients with and without hypertension.
Abstract
Background: Radiomic analyses have been extensively explored in oncologic imaging and more recently in neuroimaging. However, radiomic characterization of the crystalline lens using computed tomography has not yet been systematically investigated. Methods: In this retrospective study, semiautomatic segmentation of the eye lens on orbital CT was performed on 112 patients (mean age 48 ± 20 years, 38% female). After radiomics feature extraction, a Boruta feature selection approach based on the random forest algorithm was applied to select the most relevant radiomics features. Severity of white matter lesions were graded according to the Fazekas scale for each patient on axial non-contrast head CT. Results: In total, 17 important features were associated with age-related changes in the eye lens and three important radiomic features for the differentiation between patients with a Fazekas…
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Taxonomy
TopicsRadiomics and Machine Learning in Medical Imaging · Ocular Oncology and Treatments · Retinal Diseases and Treatments
