Figure - available from: Therapeutic Advances in Chronic Disease
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Ganglion cell layer thickness maps from a segmented SD-OCT scan of the macula from the right eye of a healthy (left) and ON (right) patient. The segmented GCL is selected in this example, demonstrating superior loss of ganglion cells and corresponding thinning. GCL, ganglion cell layer; ON, optic neuritis; SD-OCT, spectral domain optical coherence tomography.
Source publication
Considering the retina as an extension of the brain provides a platform from which to study diseases of the nervous system. Taking advantage of the clear optical media of the eye and ever-increasing resolution of modern imaging techniques, retinal morphology can now be visualized at a cellular level in vivo. This has provided a multitude of possibl...
Citations
... 10,11 In recent years, retinal degeneration in patients with PD has received widespread research attention and has become one of the research hotspots in the field of neurodegenerative diseases. 12 It has been confirmed that retinal degeneration is present in the early stage of PD. 13 Further, retinal degeneration is strongly associated with the course and severity of PD. Retinal degeneration is an important cause of nonmotor symptomatic visual dysfunction in PD. 14 It has been demonstrated that neurodegenerative lesions can propagate bidirectionally along neuronal projections in the visual pathway. ...
... 25 It has been demonstrated that the deposition of phosphorylated α-syn in the retina occurs in parallel with Lewy body lesions in the brain tissue in the early stages of PD. 26 As PD progresses, α-syn is deposited in the retina which causes progressive apoptosis of ganglion cells and results in retinal degeneration. 12 In addition, dynamic changes in retinal microvascular morphology accompanied by pathological accumulation of α-syn deposits have been observed. The above findings suggest that retinal microvascular pathology is an important pathophysiological marker in PD. 27 Therefore, the retina may be closely related to the onset and progression of PD, as it is a potential predisposing factor outside the CNS. ...
Degeneration of the retina is intrinsically associated with the pathogenesis and progression of neurodegenerative diseases. However, the cellular and molecular mechanisms underlying the association between neurodegeneration and retinal degeneration are still under exploration due to the complexity of the connectivity network of the nervous system. In this study, RNA-seq data from the brains of model retinitis pigmentosa (RP) mice and previously studied Parkinson’s disease (PD) mice were analyzed to explore the commonalities between retinal degenerative and neurodegenerative diseases. Differentially expressed genes in RP were compared with neurodegenerative disease-related genes and intersecting genes were identified, including Cnr1 and Septin14. These genes were verified by quantitative real-time reverse transcription PCR and Western blotting experiments. The key proteins CNR1 and SEPTIN14 were found to be potential cotherapeutic targets for retinal degeneration and neurodegenerative disease. In conclusion, understanding the commonalities between retinal degenerative diseases and neurodegenerative processes in the brain will not only facilitate the interpretation of the underlying pathomechanisms but also contribute to early diagnosis and the development of new therapeutic strategies.
... Parkinson's disease (PD) is among the most prevalent neurodegenerative disorders (1), the incidence of which has been steadily rising in recent years. In the early stages of PD, symptoms are typically quite mild, making it challenging for physicians to establish a definitive diagnosis (2). During the prodromal phase, PD patients may present with nonmotor symptoms such as a diminished sense of olfaction and cognitive deficits (3). ...
... Consequently, early diagnosis and detection of PD are of paramount importance (6). An efficient early diagnosis enables the timely detection of health issues and the implementation of intervention to minimize the severe health risks associated with the disease (1,2). ...
Background
Parkinson’s disease (PD) is an irreversible, chronic degenerative disease of the central nervous system, potentially associated with cerebral white matter (WM) lesions. Investigating the microstructural alterations within the WM in the early stages of PD can help to identify the disease early and enable intervention to reduce the associated serious threats to health.
Methods
This study selected 227 cases from the Parkinson’s Progression Markers Initiative (PPMI) database, including 152 de novo PD patients and 75 normal controls (NC). Whole-brain voxel analysis of the WM was performed using the tract-based spatial statistics (TBSS) method. The WM regions with statistically significant differences (P<0.05) between the PD and NC groups were identified and used as masks. The mask was applied to each case’s fractional anisotropy (FA) image to extract voxel values as feature vectors. Geometric dimensionality reduction was then applied to eliminate redundant values in the feature vectors. Subsequently, the cases were randomly divided into a training group (158 cases, including 103 PD patients and 55 NC) and a test group (69 cases, including 49 PD patients and 20 NC). The least absolute shrinkage and selection operator (LASSO) regression algorithm was employed to extract the minimal set of relevant features, then the random forest (RF) algorithm was utilized for classification using 5-fold cross validation. The resulting model was further integrated with clinical factors to create a comprehensive prediction model.
Results
In comparison to the NC group, the FA values in PD patients exhibited a statistically significant decrease (P<0.05), indicating the presence of widespread WM lesions across multiple brain regions. Moreover, the PD prediction model, constructed based on these WM lesion regions, yielded prediction accuracy (ACC) and area under the receiver operating characteristic (ROC) curve (AUC) values of 0.778 and 0.865 in the validation set, and 0.783 and 0.831 in the test set, respectively. Furthermore, the performance of the integrated model showed some improvement, with ACC and AUC values in the test set reaching 0.804 and 0.844, respectively.
Conclusions
The quantitative calculation of WM lesion area on FA images using the TBSS method can serve as a neuroimaging biomarker for diagnosing and predicting early PD at the individual level. When integrated with clinical variables, the predictive performance improves.
... For example, if pressure in the brain increases due to hypertension or a brain tumor, it can cause swelling of the optic nerve, which can be seen through an eye examination. 10,11 Therefore, an inexpensive, five-minute eye scan can accurately assess the amount of brain damage in people with stroke and offer clues about how quickly the disease is progressing. 12 The purpose of our study is to determine an association between HTRP and stroke. ...
... A glaucoma-like phenotype in the eye, resulting in the degeneration of the optic nerve is common in many neurodegenerative diseases (AD (101-104); PD (105,106); ALS (107,108); MS (103,109)). This topic has been reviewed more extensively in (110). Metabolic dysfunction is now recognized as an important disease component across many neurodegenerative diseases, particularly the loss of NAD homeostasis, increased mitochondrial dysfunction, and a metabolic switch towards alternative energy sources. ...
Glaucoma is the leading cause of irreversible blindness. Current treatment options are limited and often only slow disease progression. Metabolic dysfunction has recently been recognized as a key early and persistent mechanism in glaucoma pathophysiology. Several intrinsic metabolic dysfunctions have been identified and treated in retinal ganglion cells to provide neuroprotection. Growing pre-clinical and clinical evidence has confirmed that metabolic alterations in glaucoma are widespread, occurring across visual system tissues, in ocular fluids, in blood/serum, and at the level of genomic and mitochondrial DNA. This suggests that metabolic dysfunction is not constrained to retinal ganglion cells and that metabolic alterations extrinsic to retinal ganglion cells may contribute to their metabolic compromise. Retinal ganglion cells are reliant on glial metabolic support under normal physiological conditions, but the implications of metabolic dysfunction in glia are underexplored. We highlight emerging evidence that has demonstrated metabolic alterations occurring within glia in glaucoma, and how this may affect neuro-glial metabolic coupling and the metabolic vulnerability of retinal ganglion cells. In other neurodegenerative diseases which share features with glaucoma, several other glial metabolic alterations have been identified, suggesting that similar mechanisms and therapeutic targets may exist in glaucoma.
... Serving as a "window to the brain, " the link between the retina and the brain has been established clinically, histologically, and through technological devices such as optical coherence tomography (OCT) . There is growing evidence supporting the incorporation of OCT technology into clinical settings managing neurological diseases (Yap et al., 2019;Snyder et al., 2021;Xie et al., 2022). ...
Purpose
We explored the interaction of optical coherence tomography (OCT) parameters and white matter hyperintensities with cognitive measures in our older adult cohort.
Methods
This observational study enrolled participants who underwent a comprehensive neuropsychological battery, structural 3-T brain magnetic resonance imaging (MRI), visual acuity examination, and OCT imaging. Cerebral small vessel disease (CSVD) markers were read on MR images; lacune, cerebral microbleeds (CMB), white matter hyperintensities (WMH), and enlarged perivascular spaces (EPVS), were defined according to the STRIVE standards. Retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thicknesses (μm) were measured on the OCT tool.
Results
Older adults with cognitive impairment (CI) showed lower RNFL ( p = 0.001), GCIPL ( p = 0.009) thicknesses, and lower hippocampal volume ( p = 0.004) when compared to non-cognitively impaired (NCI). RNFL ( p = 0.006) and GCIPL thicknesses ( p = 0.032) correlated with MoCA scores. GCIPL thickness ( p = 0.037), total WMH ( p = 0.003), PWMH ( p = 0.041), and DWMH ( p = 0.001) correlated with hippocampal volume in our older adults after adjusting for covariates. With hippocampal volume as the outcome, a significant interaction ( p < 0.05) between GCIPL and PWMH and total WMH was observed in our older adults.
Conclusion
Both GCIPL thinning and higher WMH burden (especially PWMH) are associated with hippocampal volume and older adults with both pathologies are more susceptible to subclinical cognitive decline.
... In the domain of neuro-ophthalmology, the measurement of changes to this tissue can provide a unique opportunity for an early diagnosis and treatment of these diseases, helping to mitigate the progressive degeneration and improving patient care and quality of life [3]. Changes to the human retina have been shown to correlate with the effects that these diseases present on the neurological tissue [4], [5]. Thanks to the transparency of the optic medium, this makes it possible to study the progression of ND by directly observing changes to the ocular neurological tissue. ...
... Furthermore, its non-invasiveness, along with the high resolution volumetric visualisation that OCT enables without the need of contrast agents, makes it an attractive alternative to brain imaging for the diagnosis and assessment of ND. Because of this, several studies have focused on finding biomarkers that allow the assessment of these diseases from OCT images [4], [5], [14], [15]. Specifically, clinical studies have found associations between changes in the retinal layers and the progression of patients of Alzheimer's Disease (AD) [16]- [20], in patients of Parkinson's Disease (PD) [18], [21], [22], and in patients of Multiple Sclerosis (MS) [23]- [25], among others. ...
Retinal Optical Coherence Tomography (OCT) allows the non-invasive direct observation of the central nervous system, enabling the measurement and extraction of biomarkers from neural tissue that can be helpful in the assessment of ocular, systemic and Neurological Disorders (ND). Deep learning models can be trained to segment the retinal layers for biomarker extraction. However, the onset of ND can have an impact on the neural tissue, which can lead to the degraded performance of models not exposed to images displaying signs of disease during training. We present a fully automatic approach for the retinal layer segmentation in multiple neurodegenerative disorder scenarios, using an annotated dataset of patients of the most prevalent NDs: Alzheimer's disease, Parkinson's disease, multiple sclerosis and essential tremor, along with healthy control patients. Furthermore, we present a two-part, comprehensive study on the effects of ND on the performance of these models. The results show that images of healthy patients may not be sufficient for the robust training of automated segmentation models intended for the analysis of ND patients, and that using images representative of different NDs can increase the model performance. These results indicate that the presence or absence of patients of ND in datasets should be taken into account when training deep learning models for retinal layer segmentation, and that the proposed approach can provide a valuable tool for the robust and reliable diagnosis in multiple scenarios of ND.
... The use of the noninvasive OCT test to measure thickness as an MS biomarker would reduce the need for many invasive tests and would facilitate early diagnosis. This would allow earlier initiation of treatment for patients, thus improving their quality of life (Yap et al., 2019). ...
Purpose:
The macular ganglion cell layer (mGCL) is a strong potential biomarker of axonal degeneration in multiple sclerosis (MS). For this reason, this study aims to develop a computer-aided method to facilitate diagnosis and prognosis in MS.
Methods:
This paper combines a cross-sectional study of 72 MS patients and 30 healthy control subjects for diagnosis and a 10-year longitudinal study of the same MS patients for the prediction of disability progression, during which the mGCL was measured using optical coherence tomography (OCT). Deep neural networks were used as an automatic classifier.
Results:
For MS diagnosis, greatest accuracy (90.3%) was achieved using 17 features as inputs. The neural network architecture comprised the input layer, two hidden layers and the output layer with softmax activation. For the prediction of disability progression 8 years later, accuracy of 81.9% was achieved with a neural network comprising two hidden layers and 400 epochs.
Conclusion:
We present evidence that by applying deep learning techniques to clinical and mGCL thickness data it is possible to identify MS and predict the course of the disease. This approach potentially constitutes a non-invasive, low-cost, easy-to-implement and effective method.
... It is known that the retina contains optical neurons that are directly linked to the brain, so it follows that biomarkers for many neurological diseases, such as Alzheimer's disease (AD), Parkinson's, and multiple sclerosis can be seen through retinal imaging. 273 Amyloid beta (Ab) peptide has been identified in the brains of people with AD and is a known biomarker. Similarly, autopsy of patients with AD shows high concentration of Ab in the retina. ...
Significance:
Spectral imaging, which includes hyperspectral and multispectral imaging, can provide images in numerous wavelength bands within and beyond the visible light spectrum. Emerging technologies that enable compact, portable spectral imaging cameras can facilitate new applications in biomedical imaging.
Aim:
With this review paper, researchers will (1) understand the technological trends of upcoming spectral cameras, (2) understand new specific applications that portable spectral imaging unlocked, and (3) evaluate proper spectral imaging systems for their specific applications.
Approach:
We performed a comprehensive literature review in three databases (Scopus, PubMed, and Web of Science). We included only fully realized systems with definable dimensions. To best accommodate many different definitions of "compact," we included a table of dimensions and weights for systems that met our definition.
Results:
There is a wide variety of contributions from industry, academic, and hobbyist spaces. A variety of new engineering approaches, such as Fabry-Perot interferometers, spectrally resolved detector array (mosaic array), microelectro-mechanical systems, 3D printing, light-emitting diodes, and smartphones, were used in the construction of compact spectral imaging cameras. In bioimaging applications, these compact devices were used for in vivo and ex vivo diagnosis and surgical settings.
Conclusions:
Compact and ultracompact spectral imagers are the future of spectral imaging systems. Researchers in the bioimaging fields are building systems that are low-cost, fast in acquisition time, and mobile enough to be handheld.
... Recently, many studies have reported decreased retinal nerve fiber layer (RNFL) thickness associated with various neurological and neurodegenerative diseases. This has been observed in AD, minimal cognitive impairment (Ono et al., 1988;Howland, 1990;Philippou and Joubert, 2013;Bozzoni et al., 2016), multiple sclerosis (Pugdahl et al., 2007;Sharma et al., 2011), Parkinson's disease (Moss et al., 2012), diffuse Lewy body disease (DLB; Cerveró et al., 2019), and Wilson's disease (Yap et al., 2019). Furthermore, in AD, the retina shows the presence of amyloid beta protein and tau aggregates, neurodegeneration, glial reactivity, and altered vascularity (Gupta et al., 2021). ...
Introduction
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive loss of motor neuron function. Although ophthalmic deficits are not considered a classic symptom of ALS, recent studies suggest that changes in retinal cells, similar to those in the spinal cord motor neurons, have been observed in postmortem human tissues and animal models.
Methods
In this study, we examined by immunofluorescence analysis the retinal cell layers of sporadic ALS patients in post-mortem retinal slices. We evaluated the presence of cytoplasmic TDP-43 and SQSTM1/p62 aggregates, activation of the apoptotic pathway, and microglia and astrocytes reactivity.
Results
We found in the retinal ganglion cell layer of ALS patients the increase of mislocalized TDP-43, SQSTM1/p62 aggregates, activation of cleaved caspase-3, and microglia density, suggesting that retinal changes can be used as an additional diagnostic tool for ALS.
Discussion
The retina is considered part of the central nervous system, and neurodegenerative changes in the brain may be accompanied by structural and possibly functional changes in the neuroretina and ocular vasculature. Therefore, using in vivo retinal biomarkers as an additional diagnostic tool for ALS may provide an opportunity to longitudinally monitor individuals and therapies over time in a noninvasive and cost-effective manner.
... (2017b) further supports this study as they found a significant association between OCT findings and the degree of cortical atrophy in patients with AD. Overall whilst retinal changes are being studied extensively in AD, retinal thinning is not AD-specific and is observed in other neurodegenerative diseases Yap et al., 2019). excluded in both AD and control subjects in the entry criteria, it is possible that confounding ocular co-morbidities such as glaucoma, high myopia, macular degeneration, epiretinal membranes, and systemic conditions such as diabetes and hypertension may not have been adequately excluded in some cases. ...
Examining the retinal tissue has the potential to provide a unique method and technique to quantify Alzheimer’s disease-related changes in participants at various stages of the disease. In this meta-analysis, we aimed to investigate the association of various optical coherence tomography parameters with Alzheimer’s disease and whether retinal measurements can be used to differentiate between Alzheimer’s disease and control subjects. Scientific databases including Google Scholar, Web of Science, and PubMed were systematically searched for published articles that evaluated retinal nerve fiber layer thickness and retinal microvascular network in Alzheimer’s disease and control subjects. Seventy-three studies (5850 participants, including 2249 Alzheimer’s disease patients and 3601 controls) were included in this meta-analysis. Relative to controls, Alzheimer’s disease patients had a significantly lower global retinal nerve fiber layer thickness (standardized mean difference [SMD] = –0.79, 95% confidence intervals [CI]: –1.03 to –0.54, P < 0.00001) as well as each quadrant being thinner in Alzheimer’s disease versus controls. Regarding macular parameters, values measured by optical coherence tomography were significantly lower in Alzheimer’s disease than controls for macular thickness (pooled SMD: –0.44, 95% CI: –0.67 to –0.20, P = 0.0003), foveal thickness (pooled SMD = –0.39, 95% CI: –0.58 to –0.19, P < 0.0001), ganglion cell inner plexiform layer (SMD = –1.26, 95% CI: –2.24 to –0.27, P = 0.01) and macular volume (pooled SMD = –0.41, 95% CI –0.76 to –0.07, P = 0.02). Analysis using optical coherence tomography angiography parameters revealed mixed results between Alzheimer’s disease and controls. Superficial vessel density (pooled SMD = –0.42, 95% CI: –0.68 to –0.17, P = 0.0001) and deep vessel density (pooled SMD = –0.46, 95% CI: –0.75 to –0.18, P = 0.001) were found to be thinner in Alzheimer’s disease patients whereas the foveal avascular zone (SMD = 0.84, 95% CI: 0.17–1.51, P = 0.01) was larger in controls. Vascular density and thickness of various retinal layers were decreased in Alzheimer’s disease patients compared to controls. Our results provide evidence for optical coherence tomography technology having the potential to detect retinal and microvascular changes in patients diagnosed with Alzheimer’s disease and aid in monitoring and early diagnosis methods.
