Retinal OCT speckle as a biomarker for glaucoma diagnosis and staging

• Type: Article in International Scientific Journal
• Date: 2023

Authors

Vaz, PG (Author) Other; Brea, LS (Author) Other; Silva, VB (Author) Other; van Eijgen, J (Author) Other; Stalmans, I (Author) Other; Cardoso, J (Author) Other; van Walsum, T (Author) Other; Klein, S (Author) Other; Breda, JB (Author) FMUP; De Jesus, DA (Author) Other

Journal

Title: Computerized Medical Imaging and Graphics

Vol. 108

ISSN: 0895-6111

Publisher: Elsevier

Indexing

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Other information

Authenticus ID: P-00Y-HH0

DOI: 10.1016/j.compmedimag.2023.102256

Abstract (EN): This paper presents a novel image analysis strategy that increases the potential of macular Optical Coherence Tomography (OCT) by using speckle features as biomarkers in different stages of glaucoma.A large pool of features (480) were computed for a subset of macular OCT volumes of the Leuven eye study cohort. The dataset contained 258 subjects that were divided into four groups based on their glaucoma severity: Healthy (56), Mild (94), Moderate (48), and Severe (60). The OCT speckle features were categorized as statistical properties, statistical distributions, contrast, spatial gray-level dependence matrices, and frequency domain features. The averaged thicknesses of ten retinal layers were also collected. Kruskal-Wallis H test and multivariable regression models were used to infer the most significant features related to glaucoma severity classification and to the correlation with visual field mean deviation.Four features were selected as being the most relevant: the ganglion cell layer (GCL) and the inner plexiform layer (IPL) thicknesses, and two OCT speckle features, the data skewness computed on the retinal nerve fiber layer (RNFL) and the scale parameter (������) of the generalized gamma distribution fitted to the GCL data. Based on a significance level of 0.05, the regression models revealed that RNFL skewness exhibited the highest significance among the features considered for glaucoma severity staging (p-values of 8.6 x10-6 for the logistic model and 2.8 x 10-7 for the linear model). Furthermore, it demonstrated a strong negative correlation with the visual field mean deviation (������ = -0.64). The post hoc analysis revealed that, when distinguishing healthy controls from glaucoma subjects, GCL thickness is the most relevant feature (p-value of 8.7 x 10-5). Conversely, when comparing the Mild versus Moderate stages of glaucoma, RNFL skewness emerged as the only feature exhibiting statistical significance (p-value = 0.001).This work shows that macular OCT speckle contains information that is currently not used in clinical practice, and not only complements structural measurements (thickness) but also has a potential for glaucoma staging.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11