Retinal hyperspectral imaging in the 5xFAD mouse model of Alzheimer's disease

Hyperspectral retinal imaging in Alzheimer's disease and age-related macular degeneration: a review

While Alzheimer's disease and other neurodegenerative diseases have traditionally been viewed as brain disorders, there is growing evidence indicating their manifestation in the eyes as well. The retina, being a developmental extension of the brain, represents the only part of the central nervous system that can be noninvasively imaged at a high spatial resolution. The discovery of the specific pathological hallmarks of Alzheimer's disease in the retina of patients holds great promise for disease diagnosis and monitoring, particularly in the early stages where disease progression can potentially be slowed. Among various retinal imaging methods, hyperspectral imaging has garnered significant attention in this field. It offers a label-free approach to detect disease biomarkers, making it especially valuable for large-scale population screening efforts. In this review, we discuss recent advances in the field and outline the current bottlenecks and enabling technologies that could propel this field toward clinical translation.

Retinal hyperspectral imaging in mouse models of Parkinson's disease and healthy aging

Retinal hyperspectral imaging (HSI) is a non-invasive in vivo approach that has shown promise in Alzheimer's disease. Parkinson's disease is another neurodegenerative disease where brain pathobiology such as alpha-synuclein and iron overaccumulation have been implicated in the retina. However, it remains unknown whether HSI is altered in in vivo models of Parkinson's disease, whether it differs from healthy aging, and the mechanisms which drive these changes. To address this, we conducted HSI in two mouse models of Parkinson's disease across different ages; an alpha-synuclein overaccumulation model (hA53T transgenic line M83, A53T) and an iron deposition model (Tau knock out, TauKO). In comparison to wild-type littermates the A53T and TauKO mice both demonstrated increased reflectivity at short wavelengths ~ 450 to 600 nm. In contrast, healthy aging in three background strains exhibited the opposite effect, a decreased reflectance in the short wavelength spectrum. We also demonstrate that the Parkinson's hyperspectral signature is similar to that from an Alzheimer's disease model, 5xFAD mice. Multivariate analyses of HSI were significant when plotted against age. Moreover, when alpha-synuclein, iron or retinal nerve fibre layer thickness were added as a cofactor this improved the R2 values of the correlations in certain groups. This study demonstrates an in vivo hyperspectral signature in Parkinson's disease that is consistent in two mouse models and is distinct from healthy aging. There is also a suggestion that factors including retinal deposition of alpha-synuclein and iron may play a role in driving the Parkinson's disease hyperspectral profile and retinal nerve fibre layer thickness in advanced aging. These findings suggest that HSI may be a promising translation tool in Parkinson's disease.

Hyperspectral retinal imaging biomarkers of ocular and systemic diseases

Hyperspectral imaging is a frontier in the field of medical imaging technology. It enables the simultaneous collection of spectroscopic and spatial data. Structural and physiological information encoded in these data can be used to identify and localise typically elusive biomarkers. Studies of retinal hyperspectral imaging have provided novel insights into disease pathophysiology and new ways of non-invasive diagnosis and monitoring of retinal and systemic diseases. This review provides a concise overview of recent advances in retinal hyperspectral imaging.

Retinal Alterations Predict Early Prodromal Signs of Neurodegenerative Disease

Neurodegenerative diseases are an increasingly common group of diseases that occur late in life with a significant impact on personal, family, and economic life. Among these, Alzheimer's disease (AD) and Parkinson's disease (PD) are the major disorders that lead to mild to severe cognitive and physical impairment and dementia. Interestingly, those diseases may show onset of prodromal symptoms early after middle age. Commonly, the evaluation of these neurodegenerative diseases is based on the detection of biomarkers, where functional and structural magnetic resonance imaging (MRI) have shown a central role in revealing early or prodromal phases, although it can be expensive, time-consuming, and not always available. The aforementioned diseases have a common impact on the visual system due to the pathophysiological mechanisms shared between the eye and the brain. In Parkinson's disease, α-synuclein deposition in the retinal cells, as well as in dopaminergic neurons of the substantia nigra, alters the visual cortex and retinal function, resulting in modifications to the visual field. Similarly, the visual cortex is modified by the neurofibrillary tangles and neuritic amyloid β plaques typically seen in the Alzheimer's disease brain, and this may reflect the accumulation of these biomarkers in the retina during the early stages of the disease, as seen in postmortem retinas of AD patients. In this light, the ophthalmic evaluation of retinal neurodegeneration could become a cost-effective method for the early diagnosis of those diseases, overcoming the limitations of functional and structural imaging of the deep brain. This analysis is commonly used in ophthalmic practice, and interest in it has risen in recent years. This review will discuss the relationship between Alzheimer's disease and Parkinson's disease with retinal degeneration, highlighting how retinal analysis may represent a noninvasive and straightforward method for the early diagnosis of these neurodegenerative diseases.

Hyperspectral Retinal Imaging as a Non-Invasive Marker to Determine Brain Amyloid Status

Background

As an extension of the central nervous system (CNS), the retina shares many similarities with the brain and can manifest signs of various neurological diseases, including Alzheimer's disease (AD).

Objective

To investigate the retinal spectral features and develop a classification model to differentiate individuals with different brain amyloid levels.

Methods

Sixty-six participants with varying brain amyloid-β protein levels were non-invasively imaged using a hyperspectral retinal camera in the wavelength range of 450-900 nm in 5 nm steps. Multiple retina features from the central and superior views were selected and analyzed to identify their variability among individuals with different brain amyloid loads.

Results

The retinal reflectance spectra in the 450-585 nm wavelengths exhibited a significant difference in individuals with increasing brain amyloid. The retinal features in the superior view showed higher inter-subject variability. A classification model was trained to differentiate individuals with varying amyloid levels using the spectra of extracted retinal features. The performance of the spectral classification model was dependent upon retinal features and showed 0.758-0.879 accuracy, 0.718-0.909 sensitivity, 0.764-0.912 specificity, and 0.745-0.891 area under curve for the right eye.

Conclusions

This study highlights the spectral variation of retinal features associated with brain amyloid loads. It also demonstrates the feasibility of the retinal hyperspectral imaging technique as a potential method to identify individuals in the preclinical phase of AD as an inexpensive alternative to brain imaging.

Potential Retinal Biomarkers in Alzheimer's Disease

Alzheimer's disease (AD) represents a major diagnostic challenge, as early detection is crucial for effective intervention. This review examines the diagnostic challenges facing current AD evaluations and explores the emerging field of retinal alterations as early indicators. Recognizing the potential of the retina as a noninvasive window to the brain, we emphasize the importance of identifying retinal biomarkers in the early stages of AD. However, the examination of AD is not without its challenges, as the similarities shared with other retinal diseases introduce complexity in the search for AD-specific markers. In this review, we address the relevance of using the retina for the early diagnosis of AD and the complex challenges associated with the search for AD-specific retinal biomarkers. We provide a comprehensive overview of the current landscape and highlight avenues for progress in AD diagnosis by retinal examination.

Acrolein Induces Retinal Abnormalities of Alzheimer's Disease in Mice

It is reported that retinal abnormities are related to Alzheimer's disease (AD) in patients and animal models. However, it is unclear whether the retinal abnormities appear in the mouse model of sporadic Alzheimer's disease (sAD) induced by acrolein. We investigated the alterations of retinal function and structure, the levels of β-amyloid (Aβ) and phosphorylated Tau (p-Tau) in the retina, and the changes in the retinal vascular system in this mouse model. We demonstrated that the levels of Aβ and p-Tau were increased in the retinas of mice from the acrolein groups. Subsequently, a decreased amplitudes of b-waves in the scotopic and photopic electroretinogram (ERG), decreased thicknesses of the retinal nerve fiber layer (RNFL) in the retina, and slight retinal venous beading were found in the mice induced by acrolein. We propose that sAD mice induced by acrolein showed abnormalities in the retina, which may provide a valuable reference for the study of the retina in sAD.

Retinal electrophysiology in central nervous system disorders. A review of human and mouse studies

The retina and brain share similar neurochemistry and neurodevelopmental origins, with the retina, often viewed as a "window to the brain." With retinal measures of structure and function becoming easier to obtain in clinical populations there is a growing interest in using retinal findings as potential biomarkers for disorders affecting the central nervous system. Functional retinal biomarkers, such as the electroretinogram, show promise in neurological disorders, despite having limitations imposed by the existence of overlapping genetic markers, clinical traits or the effects of medications that may reduce their specificity in some conditions. This narrative review summarizes the principal functional retinal findings in central nervous system disorders and related mouse models and provides a background to the main excitatory and inhibitory retinal neurotransmitters that have been implicated to explain the visual electrophysiological findings. These changes in retinal neurochemistry may contribute to our understanding of these conditions based on the findings of retinal electrophysiological tests such as the flash, pattern, multifocal electroretinograms, and electro-oculogram. It is likely that future applications of signal analysis and machine learning algorithms will offer new insights into the pathophysiology, classification, and progression of these clinical disorders including autism, attention deficit/hyperactivity disorder, bipolar disorder, schizophrenia, depression, Parkinson's, and Alzheimer's disease. New clinical applications of visual electrophysiology to this field may lead to earlier, more accurate diagnoses and better targeted therapeutic interventions benefiting individual patients and clinicians managing these individuals and their families.

Label-free hyperspectral imaging and deep-learning prediction of retinal amyloid β-protein and phosphorylated tau

Alzheimer's disease (AD) is a major risk for the aging population. The pathological hallmarks of AD-an abnormal deposition of amyloid β-protein (Aβ) and phosphorylated tau (pTau)-have been demonstrated in the retinas of AD patients, including in prodromal patients with mild cognitive impairment (MCI). Aβ pathology, especially the accumulation of the amyloidogenic 42-residue long alloform (Aβ42), is considered an early and specific sign of AD, and together with tauopathy, confirms AD diagnosis. To visualize retinal Aβ and pTau, state-of-the-art methods use fluorescence. However, administering contrast agents complicates the imaging procedure. To address this problem from fundamentals, ex-vivo studies were performed to develop a label-free hyperspectral imaging method to detect the spectral signatures of Aβ42 and pS396-Tau, and predicted their abundance in retinal cross-sections. For the first time, we reported the spectral signature of pTau and demonstrated an accurate prediction of Aβ and pTau distribution powered by deep learning. We expect our finding will lay the groundwork for label-free detection of AD.

Review on the Application of Hyperspectral Imaging Technology of the Exposed Cortex in Cerebral Surgery

The study of brain science is vital to human health. The application of hyperspectral imaging in biomedical fields has grown dramatically in recent years due to their unique optical imaging method and multidimensional information acquisition. Hyperspectral imaging technology can acquire two-dimensional spatial information and one-dimensional spectral information of biological samples simultaneously, covering the ultraviolet, visible and infrared spectral ranges with high spectral resolution, which can provide diagnostic information about the physiological, morphological and biochemical components of tissues and organs. This technology also presents finer spectral features for brain imaging studies, and further provides more auxiliary information for cerebral disease research. This paper reviews the recent advance of hyperspectral imaging in cerebral diagnosis. Firstly, the experimental setup, image acquisition and pre-processing, and analysis methods of hyperspectral technology were introduced. Secondly, the latest research progress and applications of hyperspectral imaging in brain tissue metabolism, hemodynamics, and brain cancer diagnosis in recent years were summarized briefly. Finally, the limitations of the application of hyperspectral imaging in cerebral disease diagnosis field were analyzed, and the future development direction was proposed.