Utilize este identificador para referenciar este registo: https://hdl.handle.net/10316/111992
Título: Retinal OCT speckle as a biomarker for glaucoma diagnosis and staging
Autor: Vaz, Pedro G. 
Brea, Luisa Sanchez
Silva, Vânia Bastos 
van Eijgen, Jan
Stalmans, Ingeborg
Cardoso, João 
van Walsum, Theo
Klein, Stefan
Barbosa Breda, João
Andrade De Jesus, Danilo
Palavras-chave: OCT; Speckle; Glaucoma; Staging
Data: Set-2023
Editora: Elsevier
Projeto: UIDP/04559/2020 
UIDB/04559/2020 
PTDC/EMD-TLM/30295/2017 
Título da revista, periódico, livro ou evento: Computerized Medical Imaging and Graphics
Volume: 108
Resumo: 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 (a) 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 8.6×10-6 for the logistic model and 2.8×10-7 for the linear model). Furthermore, it demonstrated a strong negative correlation with the visual field mean deviation (ρ=-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 8.7×10-5). 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.
URI: https://hdl.handle.net/10316/111992
DOI: 10.1016/j.compmedimag.2023.102256
Direitos: openAccess
Aparece nas coleções:FCTUC Física - Artigos em Revistas Internacionais
LIBPhys - Artigos em Revistas Internacionais

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