Comparison of Color Fundus Photography and Multicolor Fundus Imaging for Detection of Lesions in Diabetic Retinopathy and Retinal Vein Occlusion

Diagnostic application in streptozotocin-induced diabetic retinopathy rats: A study based on Raman spectroscopy and machine learning

Vision impairment caused by diabetic retinopathy (DR) is often irreversible, making early-stage diagnosis imperative. Raman spectroscopy emerges as a powerful tool, capable of providing molecular fingerprints of tissues. This study employs RS to detect ex vivo retinal tissue from diabetic rats at various stages of the disease. Transmission electron microscopy was utilized to reveal the ultrastructural changes in retinal tissue. Following spectral preprocessing of the acquired data, the random forest and orthogonal partial least squares-discriminant analysis algorithms were employed for spectral data analysis. The entirety of Raman spectra and all annotated bands accurately and distinctly differentiate all animal groups, and can identify significant molecules from the spectral data. Bands at 524, 1335, 543, and 435 cm-1 were found to be associated with the preproliferative phase of DR. Bands at 1045 and 1335 cm-1 were found to be associated with early stages of DR.

Multicolor imaging: Current clinical applications

Multicolor (MC) imaging is an innovative pseudocolor fundus imaging modality based on confocal scanning laser ophthalmoscopy. It effectively scans the retina at different depths to create a composite image. The green reflectance image depicts the middle retinal while blue reflectance image provides images of the retinal surface. The infrared reflectance image depicts retinal structures at the level of outer retina and choroid. We systematically analyze published case reports, case series, and original articles on MC imaging where it has helped in discovering additional clinical features of retinal diseases not readily apparent on conventional color fundus photography and played a role in monitoring the response to treatment.

Distinctive Imaging Characteristics of Retinal and Cerebral Vessels between Central and Branch Retinal Vein Occlusion by MRI and AI-Based Image Analyzer

Retinal vessels have been good predictive and prognostic imaging biomarkers for systemic or eye diseases. Numerous studies have shown that the two retinal vein occlusion entities may correlate with cardiovascular and cerebrovascular events or primary open-angle glaucoma. This study aims to investigate if there is a disparity in the correlations between branch RVO (BRVO) and central RVO (CRVO) with systemic disorders or POAG, thus explaining the pathogenic difference between BRVO and CRVO. This retrospective case-control study enrolled 59 RVO subjects (118 eyes), including 25 CRVO and 34 BRVO subjects, who received routine eye and brain MRI examinations. The geometric characteristics of the caliber of the retinal and cerebral blood vessels and the optic nerve subarachnoid space width (ONSASW) were measured. Multivariable logistic regression analysis showed that ONSASW at 3 mm behind the globe (p = 0.044) and the relative retinal venular calibers (p = 0.031) were independent risk factors for the CRVO-affected eyes group in comparison with the BRVO-affected eyes group after adjusting for age, duration of hypertension, BMI, and IOP. In the CRVO-affected eyes, narrower relative retinal arteriolar calibers (p = 0.041) and wider relative venular calibers (p = 0.011) were independent risk factors compared with the CRVO-contralateral normal eyes when adjusting for IOP. We concluded that BRVO may be more associated with cerebrovascular diseases, and CRVO may be correlated with primary angle glaucoma. The geometric characteristics difference between the retinal and cerebrovascular may explain the pathological difference between CRVO and BRVO.