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

Retinal capillary density among healthy Egyptian and South Asian students: an optical coherence tomography angiography study

AIM

To compare the macular and optic nerve perfusion and vascular architecture using optical coherence tomography angiography (OCTA) in normal eyes of Egyptian (Caucasians) and South Asian (Asians) volunteers.

METHODS

Cross-sectional analytical OCTA study performed on 90 eyes of South Asian (n=45) and Egyptians (n=45) were analyzed. All participants underwent best-corrected visual acuity test, slit lamp, and fundus examination. OCTA images; macular 6×6 mm2 grid and optic nerve 4.5×4.5 mm2 grid were used to examine the parafoveal and peripapillary regions, respectively.

RESULTS

The mean capillary vessel density (CVD) in macular sectors among South Asians and Egyptians participants were (50.31%±2.53%, 51.2%±5.93%) and (49.71%±3.6%, 51.94%±4.79%) in superficial (SCP) and deep capillary plexuses (DCP), respectively (P>0.05). Mean CVD in both groups was higher in DCP compared to SCP in all sectors but was not significant (P>0.05). Mean foveal CVD increases with an increase in central retinal thickness in both SCP and DCP (P<0.001), among both groups. Mean area of the foveal avascular zone (FAZ) was 0.28±0.09 and 0.27±0.08 mm2 in South Asian and Egyptians, respectively. FAZ area decreases with an increase in the thickness and foveal CVD (P<0.001). Mean CVD in the peripapillary area was 48.23%±5.78% in South Asian and 49.52%±2.38% in Egyptian volunteers. The mean retinal nerve fiber layer thickness was found to be higher in the nasal quadrant among South Asian females than the Egyptian females (P<0.05).

CONCLUSION

No significant racial disparity is found in this study. The findings are helpful for assessing and improving the normative data on the differences in South Asian and Egyptian populations.

Progress in clinical research and applications of retinal vessel quantification technology based on fundus imaging

Retinal blood vessels are the only directly observed blood vessels in the body; changes in them can help effective assess the occurrence and development of ocular and systemic diseases. The specificity and efficiency of retinal vessel quantification technology has improved with the advancement of retinal imaging technologies and artificial intelligence (AI) algorithms; it has garnered attention in clinical research and applications for the diagnosis and treatment of common eye and related systemic diseases. A few articles have reviewed this topic; however, a summary of recent research progress in the field is still needed. This article aimed to provide a comprehensive review of the research and applications of retinal vessel quantification technology in ocular and systemic diseases, which could update clinicians and researchers on the recent progress in this field.

Convolutional Neural Network-Based Automated Quality Assessment of OCT and OCT Angiography Image Maps in Individuals With Neurodegenerative Disease

Purpose

To train and test convolutional neural networks (CNNs) to automate quality assessment of optical coherence tomography (OCT) and OCT angiography (OCTA) images in patients with neurodegenerative disease.

Methods

Patients with neurodegenerative disease were enrolled in the Duke Eye Multimodal Imaging in Neurodegenerative Disease Study. Image inputs were ganglion cell-inner plexiform layer (GC-IPL) thickness maps and fovea-centered 6-mm × 6-mm OCTA scans of the superficial capillary plexus (SCP). Two trained graders manually labeled all images for quality (good versus poor). Interrater reliability (IRR) of manual quality assessment was calculated for a subset of each image type. Images were split into train, validation, and test sets in a 70%/15%/15% split. An AlexNet-based CNN was trained using these labels and evaluated with area under the receiver operating characteristic (AUC) and summaries of the confusion matrix.

Results

A total of 1465 GC-IPL thickness maps (1217 good and 248 poor quality) and 2689 OCTA scans of the SCP (1797 good and 892 poor quality) served as model inputs. The IRR of quality assessment agreement by two graders was 97% and 90% for the GC-IPL maps and OCTA scans, respectively. The AlexNet-based CNNs trained to assess quality of the GC-IPL images and OCTA scans achieved AUCs of 0.990 and 0.832, respectively.

Conclusions

CNNs can be trained to accurately differentiate good- from poor-quality GC-IPL thickness maps and OCTA scans of the macular SCP.

Translational Relevance

Since good-quality retinal images are critical for the accurate assessment of microvasculature and structure, incorporating an automated image quality sorter may obviate the need for manual image review.

Polypoidal Choroidal Vasculopathy: Updates on Risk Factors, Diagnosis, and Treatments

There have been recent advances in basic research and clinical studies in polypoidal choroidal vasculopathy (PCV). A recent, large-scale, population-based study found systemic factors, such as male gender and smoking, were associated with PCV, and a recent systematic review reported plasma C-reactive protein, a systemic biomarker, was associated with PCV. Growing evidence points to an association between pachydrusen, recently proposed extracellular deposits associated with the thick choroid, and the risk of development of PCV. Many recent studies on diagnosis of PCV have focused on applying criteria from noninvasive multimodal retinal imaging without requirement of indocyanine green angiography. There have been attempts to develop deep learning models, a recent subset of artificial intelligence, for detecting PCV from different types of retinal imaging modality. Some of these deep learning models were found to have high performance when they were trained and tested on color retinal images with corresponding images from optical coherence tomography. The treatment of PCV is either a combination therapy using verteporfin photodynamic therapy and anti-vascular endothelial growth factor (VEGF), or anti-VEGF monotherapy, often used with a treat-and-extend regimen. New anti-VEGF agents may provide more durable treatment with similar efficacy, compared with existing anti-VEGF agents. It is not known if they can induce greater closure of polypoidal lesions, in which case, combination therapy may still be a mainstay. Recent evidence supports long-term follow-up of patients with PCV after treatment for early detection of recurrence, particularly in patients with incomplete closure of polypoidal lesions.