4 research outputs found

    Reference database of total retinal vessel surface area derived from volume-rendered optical coherence tomography angiography

    Get PDF
    Optical coherence tomography angiography (OCTA) enables three-dimensional, high-resolution, depth-resolved flow to be distinguished from non-vessel tissue signals in the retina. Thus, it enables the quantification of the 3D surface area of the retinal vessel signal. Despite the widespread use of OCTA, no representative spatially rendered reference vessel surface area data are published. In this study, the OCTA vessel surface areas in 203 eyes of 107 healthy participants were measured in the 3D domain. A Generalized Linear Model (GLM) model analysis was performed to investigate the effects of sex, age, spherical equivalent, axial length, and visual acuity on the OCTA vessel surface area. The mean overall vessel surface area was 54.53 mm2 (range from 27.03 to 88.7 mm2). OCTA vessel surface area was slightly negatively correlated with age. However, the GLM model analysis identified axial length as having the strongest effect on OCTA vessel surface area. No significant correlations were found for sex or between left and right eyes. This is the first study to characterize three-dimensional vascular parameters in a population based on OCTA with respect to the vessel surface area

    Anterior-Segment Swept-Source Ocular Coherence Tomography and Scheimpflug Imaging Agreement for Keratometry and Pupil Measurements in Healthy Eyes

    No full text
    This study examines agreement between the devices Anterion® and Pentacam HR® used for corneal and pupil measurements in healthy eyes. The parameters compared between the two devices were: anterior Km (D), anterior K2 (D), anterior K1 (D), anterior K1 axis (°), anterior astigmatism (D), anterior K max (D), posterior Km (D), posterior K2 (D), posterior K1 (D), posterior K1 axis (°), posterior astigmatism (D), CCT (µm), thinnest point thickness (µm), thinnest point X-coordinate (mm), thinnest point Y-coordinate (mm), pupil diameter (mm), pupil center-corneal vertex distance (mm) (angle kappa), pupil centroid angle (°), pupil centroid X-coordinate (mm), and pupil centroid Y-coordinate (mm). The Student’s t test for independent samples identified significant differences (p < 0.005) between devices for the measurements anterior and posterior flat K axis, posterior flat K, steep K, and mean K. For these last three measurements, although significant, none of the differences were clinically relevant. Corneal power and thickness measurements except Kf axis showed excellent agreement between Anterion and Pentacam. In a clinical setting we would not recommend the interchangeable use of Pentacam and Anterion for measurement of pupil parameters

    Retinal vessel volume reference database derived from volume-rendered optical coherence tomography angiography

    No full text
    Abstract Optical coherence tomography angiography (OCTA) enables three-dimensional reconstruction of the functional blood vessels in the retina. Therefore, it enables the quantification of 3D retinal vessel parameters such as surface area and vessel volume. In spite of the widespread use of OCTA, no representative volume-rendered vessel volume (VV) data are published to date. In this study, OCTA 3 × 3 mm macular cubes were processed with volume-rendering techniques to measure VV in 203 eyes from 107 healthy volunteers. Generalized linear models (GLM) were constructed to assess the impact of age, gender, visual acuity (VA), spherical equivalent (SE), and axial length (AL) on VV. Overall mean VV was 0.23 ± 0.05mm3. Age and axial length showed a negative correlation with VV. However, GLM model analysis found that AL exerted the most pronounced influence on VV. No statistically significant associations were identified between gender or between left and right eyes. This is the first study to assess 3D OCTA VV and its naturally occurring variations in a large series of healthy subjects. It offers novel insights into the characterization of normal retinal vascular anatomy in healthy individuals, contributing to a valuable reference for future research in this field

    Radiomics-Based Assessment of OCT Angiography Images for Diabetic Retinopathy Diagnosis

    No full text
    Purpose: To evaluate the diagnostic accuracy of machine learning (ML) techniques applied to radiomic features extracted from OCT and OCT angiography (OCTA) images for diabetes mellitus (DM), diabetic retinopathy (DR), and referable DR (R-DR) diagnosis. Design: Cross-sectional analysis of a retinal image dataset from a previous prospective OCTA study (ClinicalTrials.gov NCT03422965). Participants: Patients with type 1 DM and controls included in the progenitor study. Methods: Radiomic features were extracted from fundus retinographies, OCT, and OCTA images in each study eye. Logistic regression, linear discriminant analysis, support vector classifier (SVC)-linear, SVC-radial basis function, and random forest models were created to evaluate their diagnostic accuracy for DM, DR, and R-DR diagnosis in all image types. Main Outcome Measures: Area under the receiver operating characteristic curve (AUC) mean and standard deviation for each ML model and each individual and combined image types. Results: A dataset of 726 eyes (439 individuals) were included. For DM diagnosis, the greatest AUC was observed for OCT (0.82, 0.03). For DR detection, the greatest AUC was observed for OCTA (0.77, 0.03), especially in the 3 × 3 mm superficial capillary plexus OCTA scan (0.76, 0.04). For R-DR diagnosis, the greatest AUC was observed for OCTA (0.87, 0.12) and the deep capillary plexus OCTA scan (0.86, 0.08). The addition of clinical variables (age, sex, etc.) improved most models AUC for DM, DR and R-DR diagnosis. The performance of the models was similar in unilateral and bilateral eyes image datasets. Conclusions: Radiomics extracted from OCT and OCTA images allow identification of patients with DM, DR, and R-DR using standard ML classifiers. OCT was the best test for DM diagnosis, OCTA for DR and R-DR diagnosis and the addition of clinical variables improved most models. This pioneer study demonstrates that radiomics-based ML techniques applied to OCT and OCTA images may be an option for DR screening in patients with type 1 DM. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references
    corecore