Serum vitamin D level alterations in retinal vascular occlusions

AIM

To evaluate serum vitamin D levels in sub-types of retinal vascular occlusions and compare the levels in ischemic and non-ischemic presentations.

METHODS

This study included 50 patients of retinal vascular occlusions comprising central retinal vein occlusion, branch retinal vein occlusion, central retinal artery occlusion, branch retinal artery occlusion (study group) diagnosed on basis of clinical characteristics as well as investigations and an age and gender-matched healthy control group (control group). The study group was further classified into ischemic and non-ischemic subtypes and serum vitamin D levels were analysed and compared.

RESULTS

There were 50 patients of various sub-types of retinal vascular occlusions comprising 13 cases of CRVO, 30 cases of BRVO, 05 cases of CRAO, 02 cases of BRAO and 50 age and sex-matched controls. Mean BCVA and CMT in RVO patients was +1.12 log MAR, 346.72 ± 27.93 µm while in control group was +0.37 log MAR, 236.22 ± 3.71 µm which were statistically significant (p = 0.004; p = 0.002). The mean serum vitamin D value in study group was 18.39 ng/dl as compared to 32.31 ng/dl in control group which was statistically significant (p = 0.001). The difference in the baseline vitamin D value between the ischemic and non -ischemic sub groups among total vascular occlusion was found to be statistically significant (p = 0.010). However, baseline vitamin D levels difference among ischemic and non-ischemic cases in individual sub-types of vascular occlusion was statistically insignificant.

CONCLUSION

High prevalence of low serum vitamin D levels is seen in patients of retinal vascular occlusion spectrum diseases. Moreover, ischemic types of retinal vascular occlusion have significantly lower serum vitamin D levels as compared to non - ischemic despite having fewer no of patients in arterial occlusion sub-types. Therefore, vitamin D supplements may be considered as possible future targeted therapy in optimizing the severity of disease.

Folate and retinal vascular diseases

Folate, a pteroylglutamic acid derivative, participates in fundamental cellular metabolism. Homocysteine, an amino acid, serves as an intermediate of the methionine cycle and can be converted back to methionine. Hyperhomocysteinemia is a recognized risk factor for atherosclerotic and cardiovascular diseases. In recent decades, elevated plasma homocysteine levels and low folate status have been observed in many patients with retinal vascular diseases, such as retinal vascular occlusions, diabetic retinopathy, and age-related degeneration. Homocysteine-induced toxicity toward vascular endothelial cells might participate in the formation of retinal vascular diseases. Folate is an important dietary determinant of homocysteine. Folate deficiency is the most common cause of hyperhomocysteinemia. Folate supplementation can eliminate excess homocysteine in plasma. In in vitro experiments, folic acid had a protective effect on vascular endothelial cells against high glucose. Many studies have explored the relationship between folate and various retinal vascular diseases. This review summarizes the most important findings that lead to the conclusion that folic acid supplementation might be a protective treatment in patients with retinal vascular diseases with high homocysteine or glucose status. More research is still needed to validate the effect of folate and its supplementation in retinal vascular diseases.

DeepDrRVO: A GAN-auxiliary two-step masked transformer framework benefits early recognition and differential diagnosis of retinal vascular occlusion from color fundus photographs

Retinal vascular occlusion (RVO) are common causes of visual impairment. Accurate recognition and differential diagnosis of RVO are unmet medical needs for determining appropriate treatments and health care to properly manage the ocular condition and minimize the damaging effects. To leverage deep learning as a potential solution to detect RVO reliably, we developed a deep learning model on color fundus photographs (CFPs) using a two-step masked SwinTransformer with a Few-Sample Generator (FSG)-auxiliary training framework (called DeepDrRVO) for early and differential RVO diagnosis. The DeepDrRVO was trained on the training set from the in-house cohort and achieved consistently high performance in early recognition and differential diagnosis of RVO in the validation set from the in-house cohort with an accuracy of 86.3%, and other three independent multi-center cohorts with the accuracy of 92.6%, 90.8%, and 100%. Further comparative analysis showed that the proposed DeepDrRVO outperforms conventional state-of-the-art classification models, such as ResNet18, ResNet50d, MobileNetv3, and EfficientNetb1. These results highlight the potential benefits of the deep learning model in automatic early RVO detection and differential diagnosis for improving clinical outcomes and providing insights into diagnosing other ocular diseases with a few-shot learning challenge. The DeepDrRVO is publicly available on https://github.com/ZhouSunLab-Workshops/DeepDrRVO.

Differences in the multicolour imaging features between the superficial and deep vascular occlusions

Purpose To describe the multicolour imaging (MI) findings in superficial and deep vascular plexus occlusions.

METHODS

In this retrospective observational study, patients diagnosed with central retinal artery and branch retinal artery occlusion, cotton-wool spot, paracentral acute middle maculopathy and acute macular neuroretinopathy between January 2018 and June 2019 were included. Colour fundus photograph, optical coherence tomography and MI of these patients were analysed.

RESULTS

A total of 41 eyes of 40 patients were included in this study. In eyes with central retinal artery occlusion, MI showed white areas in the retina with orange foveal centre. In eyes with branch retinal artery occlusion, MI showed white area along the affected retinal quadrant without an orange foveal centre. In pure superficial vascular plexus occlusions as in cotton-wool spots, the lesion was identified on MI as a white lesion. On MI, paracentral acute middle maculopathy showed parafoveal white areas with orange foveal centre while acute macular neuroretinopathy on MI parafoveal greyish-white areas with normal foveal centre.

CONCLUSION

En-face images using MI technology can provide yet another way to identify the level of retinal vasculature involvement which complements the existing gold standard of optical coherence tomography imaging.