In Vivo Assessment of Retinal Biomarkers by Hyperspectral Imaging: Early Detection of Alzheimer’s Disease

Abstract

A noninvasive and cost-effective means to detect preclinical Alzheimer’s disease (AD) and monitor disease progression would be invaluable. The retina is a developmental extension of the brain and has been viewed as a window to evaluate AD-related pathology. Cross-sectional studies have shown structural changes in the retina of AD patients that include thinning of the retinal nerve-fiber layer and changes in retinal vasculature. However, such changes do not manifest in early stages of the disease nor are they specific biomarkers for AD. Described herein is the utilization of our retinal hyperspectral imaging (rHSI) technique as a biomarker for identification of AD-related early pathological changes in the retina. Specifically, this account concerns the translation of our rHSI technique from animal models to human AD subjects. The underlying principle is Rayleigh light scattering, which is expected from low-order Aβ aggregates present in early pathology. Recruitment was restricted to AD subjects (N = 19) and age-matched controls, with no family history of AD (N = 16). To limit the influence of skin pigmentation, subjects were restricted to those with skin pigmentation values of 2–3 on the Fitzpatrick scale. The largest spectral deviation from control subjects, rHSI signature, was obtained at the MCI stage with MMSE scores ⩾22, suggesting higher sensitivity of this technique in early disease stages. The rHSI signature observed is unaffected by eye pathologies such as glaucoma and cataract. Age of the subjects minimally influenced the spectral signatures. The rHSI technique shows promise for detection of preclinical AD; it is conducted in a truly noninvasive manner, without application of an exogenous label, and is thus potentially suitable for population screening.

Alzheimer’s Retinopathy: Seeing Disease in the Eyes

“…Retinal imaging scores correlated with Aβ burden in the brain (Hadoux et al, 2019). Intriguingly, a similar study from More and colleagues, the team that initially developed the rHSI technique in murine models (More and Vince, 2015;More et al, 2016), found the largest deviation in rHSI signatures between MCI patients and controls, irrespective of other ocular conditions such as cataracts or glaucoma (More et al, 2019). The same technique was able to distinguish cerebral Aβ+ subjects from Aβ− subjects with 85% accuracy based on retinal vascular measures including vessel tortuosity and diameter (Sharafi et al, 2019).…”

Hyperspectral Imaging and the Retina: Worth the Wave?

“…43,78,79 The same authors select retinal regions of interest and compare optical densities in different stages of AD in humans. 81 Alternatively, rather than directly observing differences in spectra, Hadoux et al 56 semiautomatically extracted average spectra from regions of interest in the retinal image and feed these as input into a classification model. A variant of linear discriminant analysis produces a "hyperspectral score" that is assumed to be an estimate for retinal amyloid load.…”

“…When adapted for in vivo human use, an inverse correlation with the Mini-Mental State Exam score was also seen in those lower wavelengths (430-580 nm). 81 Hadoux et al 56 successfully trained a classifier to distinguish between amyloid positron emission tomography positive human participants compared with controls based on the hyperspectral signature of the retina. Last, Sharafi et al 61 reported a significant hyperspectral difference between retinal tissue (containing vessels) in amyloid positive individuals compared with amyloid negative ones.…”

“…77 Indeed, a number of studies on dispersive arrays and TLS extended their spectrum in the near-infrared field. 27,49,56,61,70,78,79,81 Near-infrared light does not damage ocular tissue and is strongly absorbed by water (subretinal fluid) and more important, melanin, although it is not affected by the ocular transparent media and macular pigment. Therefore, it is supposed to be an ideal band to examine choroidal neovascularization, even in the presence of cataract.…”

TheAppNL-G-Fmouse retina is a site for preclinical Alzheimer’s disease diagnosis and research

“…This imaging spectroscopy technique is based on the fact that soluble Aβ aggregates -most likely Aβ42 -interfere with traversing light, leading to Rayleigh light scattering and a characteristic hyperspectral signature, the magnitude of which appear to be proportional to the amount of Aβ present 9,10 . In the past year, following promising post mortem and in vivo studies in both animal and human retinas 9,10,43 , results of the first clinical trial showing that in vivo retinal hyperspectral imaging can discriminate between Aβ PET-positive cases and controls emerged 27 . This, together with our data, suggests that hyperspectral imaging can be used to monitor retinal Aβ accumulation, with the potential to provide quantitative measures of Aβ oligomers.…”