Retinal microvascular impairment in Parkinson's disease with cognitive dysfunction

Optical coherence tomography angiography of the retina and choroid in systemic diseases

Optical coherence tomography angiography (OCTA) has transformed ocular vascular imaging, revealing microvascular changes linked to various systemic diseases. This review explores its applications in diabetes, hypertension, cardiovascular diseases, and neurodegenerative diseases. While OCTA provides a valuable window into the body's microvasculature, interpreting the findings can be complex. Additionally, challenges exist due to the relative non-specificity of its findings where changes observed in OCTA might not be unique to a specific disease, variations between OCTA machines, the lack of a standardized normative database for comparison, and potential image artifacts. Despite these limitations, OCTA holds immense potential for the future. The review highlights promising advancements like quantitative analysis of OCTA images, integration of artificial intelligence for faster and more accurate interpretation, and multi-modal imaging combining OCTA with other techniques for a more comprehensive characterization of the ocular vasculature. Furthermore, OCTA's potential future role in personalized medicine, enabling tailored treatment plans based on individual OCTA findings, community screening programs for early disease detection, and longitudinal studies tracking disease progression over time is also discussed. In conclusion, OCTA presents a significant opportunity to improve our understanding and management of systemic diseases. Addressing current limitations and pursuing these exciting future directions can solidify OCTA as an indispensable tool for diagnosis, monitoring disease progression, and potentially guiding treatment decisions across various systemic health conditions.

Interocular asymmetry of retinal change in Parkinson's disease

PURPOSE

To investigate interocular asymmetry (IA) of retinal structure and vessel density in patients with Parkinson's disease (PD) and normal controls (NC).

METHODS

Seventy-eight subjects including 40 PD patients and 38 NC had completed optical coherence tomography angiography (OCTA) and neurological examinations for three rating scales (UPDRS-III, MMSE and MoCA). The IA was calculated by the absolute value of difference in right and left eyes. The IA of thickness in macular ganglion cell inner-plexiform layer (GCIPL), peripapillary retinal nerve fiber layer (pRNFL), and vessel density of superficial capillary plexus (SCP), deep capillary plexus (DCP), radial peripapillary capillary (RPC) were obtained from OCTA.

RESULTS

The motor-symptom-onset side of eyes showed lower vessel density in parafovea of SCP (51.09 ± 3.46 vs 49.81 ± 4.16, P = 0.03) and superior hemi of perifovea DCP (49.55 ± 5.81 vs 47.33 ± 5.71, = 0.04). The PD patients showed larger IA in thickness of superior half of pRNFL (5.27 [2.67, 10.87] vs 3.08 [1.62, 5.61], P = 0.02) and parafovea GCIPL (2.40[1.25, 6.35] vs 1.40[0.50, 2.45], P = 0.02). No significant interocular asymmetry was found in vessel density between PD and NC. A higher UPDRS-III scale was associated with larger IA in GCIPL (β = 0.093, P = 0.001) and smaller IA in DCP (β = -0.065, P = 0.037).

CONCLUSION

The motor-symptom-onset side of eyes showed more severe loss of macular vessel density than the other side of eyes. The PD patients showed asymmetrical structural change in GCIPL and pRNFL, which showed the potential as the diagnostic biomarker for PD.

Decreased retinal vascular density is associated with cognitive impairment in CADASIL: an optical coherence tomography angiography study

PURPOSE

This study aimed to assess alterations in retinal vascular density in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) patients using optical coherence tomography angiography (OCTA) and investigate their association with MRI and cognitive features.

METHODS

Twenty-five patients with CADASIL and forty healthy controls were evaluated by Cirrus HD-OCT 5000 with AngioPlex OCTA to determine changes in macular retinal vasculature. Retinal vasculature parameters between two groups were compared. The MRI lesion burden and neuropsychological scales were also examined in patients. The association between OCTA parameters and MRI/cognitive features was evaluated using partial Spearman rank correlation.

RESULTS

The vessel density and perfusion density of whole image in macular region (vessel density: t =  - 2.834, p = 0.005; perfusion density: t =  - 2.691, p = 0.007) were significantly decreased in patients with CADASIL. Moreover, vessel density of whole image in macular region was negatively associated with Fazekas scores (ρ =  - 0.457; p = 0.025) and the number of lacunar infractions (ρ =  - 0.425, p = 0.038) after adjustment for age. Decreased macular vessel density and perfusion density of whole image were also associated with MoCA scores (vessel density: ρ = 0.542, p = 0.006; perfusion density: ρ = 0.478, p = 0.018) and other domain-specific neuropsychological tests (p < 0.05) after adjustment for age.

CONCLUSION

Decreased retinal vascular density was associated with increased MRI lesion burden and cognitive impairment in patients with CADASIL. Our findings suggest that the degree of retinal vascular involvement, as demonstrated by OCTA, may be consistent with the severity of MRI lesions and the degree of cognitive impairment in patients.

Segmentation of Low-Light Optical Coherence Tomography Angiography Images under the Constraints of Vascular Network Topology

Optical coherence tomography angiography (OCTA) offers critical insights into the retinal vascular system, yet its full potential is hindered by challenges in precise image segmentation. Current methodologies struggle with imaging artifacts and clarity issues, particularly under low-light conditions and when using various high-speed CMOS sensors. These challenges are particularly pronounced when diagnosing and classifying diseases such as branch vein occlusion (BVO). To address these issues, we have developed a novel network based on topological structure generation, which transitions from superficial to deep retinal layers to enhance OCTA segmentation accuracy. Our approach not only demonstrates improved performance through qualitative visual comparisons and quantitative metric analyses but also effectively mitigates artifacts caused by low-light OCTA, resulting in reduced noise and enhanced clarity of the images. Furthermore, our system introduces a structured methodology for classifying BVO diseases, bridging a critical gap in this field. The primary aim of these advancements is to elevate the quality of OCTA images and bolster the reliability of their segmentation. Initial evaluations suggest that our method holds promise for establishing robust, fine-grained standards in OCTA vascular segmentation and analysis.

Optical Coherence Tomography Angiography: Revolutionizing Clinical Diagnostics and Treatment in Central Nervous System Disease

Optical coherence tomography angiography (OCTA), as a new generation of non-invasive and efficient fundus imaging technology, can provide non-invasive assessment of vascular lesions in the retina and choroid. In terms of anatomy and development, the retina is referred to as an extension of the central nervous system (CNS). CNS diseases are closely related to changes in fundus structure and blood vessels, and direct visualization of fundus structure and blood vessels provides an effective "window" for CNS research. This has important practical significance for identifying the characteristic changes of various CNS diseases on OCTA in the future, and plays a key role in promoting early screening, diagnosis, and monitoring of disease progression in CNS diseases. This article reviews relevant fundus studies by comparing and summarizing the unique advantages and existing limitations of OCTA in various CNS disease patients, in order to demonstrate the clinical significance of OCTA in the diagnosis and treatment of CNS diseases.

Optical coherence tomography angiography measurements in Parkinson's disease: A systematic review and meta-analysis

Optical coherence tomography angiography (OCT-A) is an ocular imaging technology that has emerged as a non-invasive tool to evaluate retinal microvascular changes in neurodegenerative diseases including Parkinson's disease (PD) and Alzheimer's disease. While several studies have reported on the presence of pathologic retinal microvascular alterations in PD, the utility of OCT-A as a biomarker for PD evaluation is still unclear. A systematic review and meta-analysis were performed to explore the current evidence for the role of OCT-A in PD published up until June 2022. PubMed, Scopus, and Web of Science databases were used to systematically identify relevant papers and a meta-analysis was conducted using Stata16 software according to the level of heterogeneity applying a random- or fixed-effect model. Thirteen studies of 925 eyes in the PD group and 1501 eyes in the control group assessing OCT-A findings in PD patients were included. The meta-analyses revealed that the foveal region of PD patients had a significantly lower vessel density in the superficial capillary plexus (SCP) compared to healthy controls but that there were no significant differences in the foveal avascular zone, the SCP in whole, parafoveal, and perifoveal regions, and deep capillary plexus. OCT-A metrics may act as a potential biomarker for a more accurate and early PD diagnosis. Still, the OCT-A algorithms and interchangeability between OCT-A devices require further standardization to draw clinical conclusions regarding their utility.

Central retinal microvasculature damage is associated with orthostatic hypotension in Parkinson's disease

Orthostatic hypotension (OH) is a common non-motor symptom in Parkinson's disease (PD). OH can cause cerebral and retinal hypoperfusion and is associated with microvascular damage in PD. Optical coherence tomography angiography (OCTA) is a non-invasive technology that can be used to visualize the retinal microvasculature and detect microvascular damage in PD. In the present study, 51 PD patients (OH+, n = 20, 37 eyes; OH-, n = 32, 61 eyes) and 51 healthy controls (100 eyes) were evaluated. The Unified Parkinson's Disease Rating Scale III, Hoehn and Yahr scale, Montreal Cognitive Assessment, levodopa equivalent daily dose, and vascular risk factors, including hypertension, diabetes, and dyslipidemia, were investigated. PD patients underwent a head-up tilt (HUT) test. The PD patients had a lower superficial retinal capillary plexus (SRCP) density in the central region than control patients. The PDOH+ group had lower vessel density in the SRCP of the central region compared with the control group and lower vessel density in the DRCP of the central region than the PDOH- and control groups. The changes in systolic and diastolic blood pressure during the HUT test in PD patients showed a negative correlation with the vessel density in the DRCP central region. The presence of OH was a critical factor associated with central microvasculature damage in PD. These findings indicate that OCTA can be a useful and non-invasive tool for detecting microvasculature damage in PD patients.

Retinal OCTA Image Segmentation Based on Global Contrastive Learning

The automatic segmentation of retinal vessels is of great significance for the analysis and diagnosis of retinal related diseases. However, the imbalanced data in retinal vascular images remain a great challenge. Current image segmentation methods based on deep learning almost always focus on local information in a single image while ignoring the global information of the entire dataset. To solve the problem of data imbalance in optical coherence tomography angiography (OCTA) datasets, this paper proposes a medical image segmentation method (contrastive OCTA segmentation net, COSNet) based on global contrastive learning. First, the feature extraction module extracts the features of OCTA image input and maps them to the segment head and the multilayer perceptron (MLP) head, respectively. Second, a contrastive learning module saves the pixel queue and pixel embedding of each category in the feature map into the memory bank, generates sample pairs through a mixed sampling strategy to construct a new contrastive loss function, and forces the network to learn local information and global information simultaneously. Finally, the segmented image is fine tuned to restore positional information of deep vessels. The experimental results show the proposed method can improve the accuracy (ACC), the area under the curve (AUC), and other evaluation indexes of image segmentation compared with the existing methods. This method could accomplish segmentation tasks in imbalanced data and extend to other segmentation tasks.