DualTrack Technology Improves Optical Coherence Tomography Angiography Image Quality

Macular Ischemia Quantification Using Deep-Learning Denoised Optical Coherence Tomography Angiography in Branch Retinal Vein Occlusion

Purpose

To examine whether deep-learning denoised optical coherence tomography angiography (OCTA) images could enhance automated macular ischemia quantification in branch retinal vein occlusion (BRVO).

Methods

This retrospective, single-center, cross-sectional study enrolled 74 patients with BRVO and 46 age-matched healthy subjects. The severity of macular ischemia was graded as mild, moderate, or severe. Denoised OCTA images were produced using a neural network model. Quantitative parameters derived from denoised images, including vessel density and nonperfusion area, were compared with those derived from the OCTA machine. The main outcome measures were correlations between quantitative parameters, and areas under receiver operating characteristic curves (AUCs) in classifying the severity of the macular ischemia.

Results

The vessel density and nonperfusion area from denoised images were correlated strongly with the corresponding parameters from machine-derived images in control eyes and BRVO eyes with mild or moderate macular ischemia (all P < 0.001). However, no such correlation was found in eyes with severe macular ischemia. The vessel density and nonperfusion area from denoised images had significantly larger area under receiver operating characteristic curve than those derived from the original images in classifying moderate versus severe macular ischemia (0.927 vs 0.802 [P = 0.042] and 0.946 vs 0.797, [P = 0.022], respectively). There were no significant differences in the areas under receiver operating characteristic curve between the denoised images and the machine-derived parameters in classifying control versus BRVO, and mild versus moderate macular ischemia.

Conclusions

A neural network model is useful for removing speckle noise on OCTA images and facilitating the automated grading of macular ischemia in eyes with BRVO.

Translational Relevance

Deep-learning denoised optical coherence tomography angiography images could enhance automated macular ischemia quantification.

OCT angiography metrics predict intradialytic hypotension episodes in chronic hemodialysis patients: a pilot, prospective study

In chronic hemodialysis (HD) patients, intradialytic hypotension (IDH) is a complication that increases mortality risk. We run a pilot study to analyzing possible relationships between optical coherence tomography angiography (OCT-A) metrics and IDH with the aim of evaluating if OCT-A could represent a useful tool to stratify the hypotensive risk in dialysis patients. A total of 35 eyes (35 patients) were analyzed. OCT-A was performed before and after a single dialysis session. We performed OCT-A 3 × 3 mm and 6 × 6 mm scanning area focused on the fovea centralis. Patients were then followed up to 30 days (10 HD sessions) and a total of 73 IDHs were recorded, with 12 patients (60%) experiencing at least one IDH. Different OCT-A parameters were reduced after dialysis: central choroid thickness (CCT), 6 × 6 mm foveal whole vessel density (VD) of superficial capillary plexus (SPC) and 6 × 6 mm foveal VD of deep capillary plexus (DCP). At logistic regression analysis, IDH was positively associated with baseline foveal VD of SCP and DCP, while an inverse association was found with the choroid. In Kaplan–Meier analyses of patients categorized according to the ROC-derived optimal thresholds, CCT, the 3 × 3 foveal VD of SCP, the 3 × 3 mm and 6 × 6 mm foveal VD of DCP and the 6 × 6 mm foveal VD of SCP were strongly associated with a higher risk of IDH over the 30-days follow-up. In HD patients, a single OCT-A measurement may represent a non-invasive, rapid tool to evaluate the compliance of vascular bed to HD stress and to stratify the risk of IDH in the short term.

Optical Coherence Tomography Angiography Quality Across Three Multicenter Clinical Studies of Diabetic Retinopathy

Purpose

To explore optical coherence tomography angiography (OCTA) quality and associated factors in multicenter clinical studies.

Methods

OCTA scans were obtained from participants with diabetic retinopathy from three DRCR Retina Network clinical studies using the Optovue AngioVue and ZEISS AngioPlex. Macular (3 × 3 mm and 6 × 6 mm) and optic nerve scans were captured. Quality was assessed by the Casey Reading Center. Scans were considered "poor" if the signal strength index (SSI) was less than 55 (AngioVue) or 7 (AngioPlex) or if excess motion, media opacities, beam defocus, incorrect axial position, or other artifacts were present.

Results

Included were 7539 scans from 787 eyes (461 participants). Sixty-one percent of scans were considered "good" (n = 4630). Of the 3 × 3-mm (n = 2294), 6 × 6-mm (n = 2705), and optic nerve scans (n = 2540), 62%, 63%, and 59%, respectively, were good. Differences in percentage of good scans by machine were not identified (61% of 6216 for the AngioVue and 63% of 1323 for the AngioPlex). The primary reason for poor scans was low SSI for the AngioVue (67%) and excess motion for the AngioPlex (47%). Good scans were associated with younger age (60 ± 12 years vs. 65 ± 11 years; P < 0.001), male gender (64% of males had good scans vs. 57% female; P = 0.007), and better visual acuity (ETDRS letter score 86.5 ± 6.4 [approximate Snellen equivalent 20/20] vs. 81.6 ± 9.7 [approximate Snellen equivalent 20/25]; P < 0.001).

Conclusions

Scan quality or analysis must be improved for OCTA metrics to be used as outcomes in future research.

Translational Relevance

Clinicians and researchers should be aware that poor SSI and artifacts are common issues for OCTA images.