This study introduces an automatic deep-learning-based approach to diabetic retinopathy (DR) severity assessment by integrating two modalities: Ultra-Widefield Color Fundus Photography (UWF-CFP) from the CLARUS 500 device (Carl Zeiss Meditec Inc., Dublin, CA, USA) and a comprehensive set of clinical data from the EVIRED project. We propose a framework that combines the information from 2D UWF-CFP images and a set of 76 tabular features, including demographic, biochemical, and clinical parameters, to enhance the classification accuracy of DR stages. Our model uses advanced machine learning techniques to address the complexities of synthesizing heterogeneous data types, providing a holistic view of patient health status. Results indicate that this fusion outperforms traditional methods that rely solely on imaging or clinical data, suggesting a robust model which can provide practitioners with a supportive second opinion on DR severity, particularly useful in screening workflows. We measured a multiclass accuracy of 63.4% and kappa of 0.807 for our fusion model which is 2.1% higher in accuracy and 0.022 higher in kappa compared to the image unimodal classifier. Several interpretation methods are used to provide practitioners with an inside view of the workings of classification methods and allow them to discover the most important clinical features.
Fourier-domain (FD) optical coherence tomography (OCT) depends on broadband sources to maximize axial resolution and image quality. However, these lasers significantly drive device cost or may be unavailable at desired wavelength and bandwidth ranges. A potential solution lies in integrating multiple, more affordable sources with lower individual bandwidth into a single system. However, difficulties arise if the resulting spectrum exhibits discontinuities. In this letter, we present a method that can combine OCT images from a flexible number of spectra with arbitrary, possibly non-overlapping gaps using a neural network. Compared to low-resolution input images, reconstructed B-scans are super-resolved, preserve even fine and low-contrast details and edges, and exhibit strong noise reduction that increases with the band gap. The proposed method could thereby provide a major step towards high-quality OCT imaging using spectrally disjoint, low-bandwidth sources. In broadband settings, it can be directly applied as a Fourier-domain masked autoencoder for self-supervised image quality enhancement.
Background/Objectives: Diabetic macular edema is caused by disruptions in the blood-retinal barrier, resulting in leakage and inflammation, appearing in optical coherence tomography as retinal fluid, hard exudates, and hyper-reflective foci. This study aimed to assess volumetric changes in hyper-reflective foci and hard exudates in faricimab-treated diabetic macular edema in real-world practice. Methods: This retrospective longitudinal study included forty-four eyes with faricimab-treated diabetic macular edema and follow-up of ≥40 weeks. Optical coherence tomography scans were analyzed at baseline, post-loading, 6 months and 1 year. Hyper-reflective foci and hard exudates were quantified across macular subfields using a machine-learning algorithm with manual correction. Outcomes included volumetric changes, best-corrected visual acuity, and central subfield thickness. Early morphologic responders were defined post-loading by ≥20% central subfield thickness reduction and/or central subfield thickness below 280 µm. Results: At 1 year, hyper-reflective foci and hard exudate volumes significantly decreased in the central subfield (median differences: -0.025 nL, p = 0.00028; -0.119 nL, p = 0.00025) and outer ring (-0.178 nL, p = 0.00041; -0.612 nL, p = 0.014). Hard exudate volume significantly decreased in the inner ring (-0.740 nL, p < 0.0001). Best-corrected visual acuity and central subfield thickness improved significantly (-0.10 logarithm of the minimum angle of resolution (logMAR), p = 0.0018; -48 µm, p < 0.0001). Total hyper-reflective foci volumes were similar between responders and non-responders. In contrast, hard exudate burden remained numerically higher in non-responders. Conclusions: During the year following the switch to faricimab, HRF and HE burden decreased alongside visual and anatomical improvement. HRF volumes were descriptively similar between early CST responders and non-responders, whereas HE burden remained numerically higher in non-responders.
Purpose Spectral-domain OCT angiography (SD-OCTA) scans were tested in an algorithm developed for use with swept-source OCT angiography (SS-OCTA) scans to determine if SD-OCTA scans yielded similar results for the detection and measurement of persistent choroidal hypertransmission defects (hyperTDs). Design Retrospective study. Participants Forty pairs of scans from 32 patients with late-stage nonexudative age-related macular degeneration (AMD). Methods Patients underwent both SD-OCTA and SS-OCTA imaging at the same visit using the 6 x 6 mm OCTA scan patterns. Using a semiautomatic algorithm that helped with outlining the hyperTDs, 2 graders independently validated persistent hyperTDs, which are defined as having a greatest linear dimension >= 250 mu m on the en face images generated using a slab extending from 64 to 400 mu m beneath Bruch's membrane. The number of lesions and square root (sqrt) total area of the hyperTDs were obtained from the algorithm using each imaging method. Main Outcome Measures The mean sqrt area measurements and the number of hyperTDs were compared. Results The number of lesions and sqrt total area of the hyperTDs were highly concordant between the 2 instruments (r(c) = 0.969 and r(c) = 0.999, respectively). The mean number of hyperTDs was 4.3 +/- 3.1 for SD-OCTA scans and 4.5 +/- 3.3 for SS-OCTA scans (P = 0.06). The mean sqrt total area measurements were 1.16 +/- 0.64 mm for the SD-OCTA scans and 1.17 +/- 0.65 mm for the SS-OCTA scans (P < 0.001). Because of the small standard error of the differences, the mean difference between the scans was statistically significant but not clinically significant. Conclusions Spectral-domain OCTA scans provide similar results to SS-OCTA scans when used to obtain the number and area measurements of persistent hyperTDs through a semiautomated algorithm previously developed for SS-OCTA. This facilitates the detection of atrophy with a more widely available scan pattern and the longitudinal study of early to late-stage AMD.
PURPOSE:To update the recommended guidelines when quantifying choriocapillaris (CC) flow deficits (FDs) in eyes with age-related macular degeneration (AMD) using swept-source optical coherence tomography angiography (SS-OCTA). DESIGN:Evidence-based perspective. METHODS:Review of literature and experience of authors. RESULTS:A current challenge when quantifying CC FDs using SS-OCTA is the implementation of an objective compensation strategy to adjust for the signal attenuation arising under drusen in eyes with AMD. Our previous compensation strategy was used as a general approach to adjust for the OCTA signal attenuation associated with most drusen. However, the variability of the OCTA signal loss under drusen necessitated a more objective strategy that could be tailored to each case. We propose a compensation strategy using a parameter gamma (γ) that allows for the selection of an appropriate compensation level. The optimal γ value is identified as the one producing the most homogeneous OCT signal across the whole CC structural slab. This approach minimizes the possibility that areas of decreased flow in the compensated CC flow image might reflect drusen-related or compensation-related artifacts rather than true deficits. Additional lesions that present unique challenges when quantifying CC FDs include the presence of choroidal hypotransmission defects (hypoTDs) caused by calcified drusen and hyperreflective foci as well as choroidal hypertransmission defects (hyperTDs) caused by foci of atrophy. We recommend identifying and outlining these regions on an en face sub-retinal pigment epithelium (subRPE) slab with segmentation boundaries between 64 and 400 µm beneath the Bruch membrane (BM). The hypoTDs should be excluded from CC quantification because of the lack of significant OCTA signal, whereas the hyperTDs should be excluded from being compensated because doing so can artifactually increase the percentage of CC FDs. CONCLUSIONS:The analysis of CC FDs in AMD requires special attention to drusen, hypoTDs, and hyperTDs to avoid introducing artifacts. By properly adjusting the compensation levels under drusen and adjusting the quantification of CC FDs by accounting for hyperTDs and hypoTDs, researchers interested in measuring CC FDs in AMD can have greater confidence in their measurements, particularly when investigating the role of CC flow impairment in AMD progression.
