Combination of snapshot hyperspectral retinal imaging and optical coherence tomography to identify Alzheimer’s disease patients

Lemmens, Sophie; Craenendonck, Toon Van; Eijgen, Jan Van; Groef, Lies De; Bruffaerts, Rose; Jesus, Danilo Andrade De; Charle, Wouter; Jayapala, Murali; Sunaric-Mégevand, Gordana; Standaert, Arnout; Theunis, Jan; Keer, Karel Van; Vandenbulcke, Mathieu; Moons, Lieve; Vandenberghe, Rik; Boever, Patrick De; Stalmans, Ingeborg

doi:10.1186/s13195-020-00715-1

Cited by 49 publications

(49 citation statements)

References 60 publications

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“…However, since some of these vascular findings are commonly observed in retinal degenerative and inflammatory diseases, it is important to also consider AD-specific hallmark biomarkers such as Aβ and (p)tau for accurate diagnosis. Finally, with the recent development of retinal amyloid imaging ( Koronyo et al, 2017 ; Dumitrascu et al, 2020 ; Ngolab et al, 2021 ), pericyte imaging ( Schallek et al, 2013 ), OCTA and OCT-leakage ( Cunha-Vaz et al, 2016 ; Cunha-Vaz, 2017 ), hyperspectral imaging ( Hadoux et al, 2019 ; More et al, 2019 ; Lemmens et al, 2020 ), and FFA ( Marmor and Ravin, 2011 ), future studies may pave a the way for next-generation non-invasive ophthalmic imaging technologies to facilitate AD monitoring and diagnosis.…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, multiple biochemical and histological studies corroborated these findings of Aβ deposits in the human AD retina ( den Haan et al, 2018a ; Grimaldi et al, 2019 ; Lee S. et al, 2020 ; Qiu et al, 2020 ) and further described retinal pTau, Aβ 40 and Aβ 42 accumulation, inflammation, and correlations between retinal and cerebral Aβ levels in AD patients ( Alexandrov et al, 2011 ; Schon et al, 2012 ; den Haan et al, 2018b ; Grimaldi et al, 2019 ; Lee S. et al, 2020 ; Qiu et al, 2020 ; Schultz et al, 2020 ; Shi et al, 2020b ). More recently, in vivo retinal amyloid imaging in living MCI and AD patients was achieved via either retinal curcumin-enhanced fluorescence and SLO imaging or hyperspectral imaging ( Hadoux et al, 2019 ; More et al, 2019 ; Dumitrascu et al, 2020 ; Lemmens et al, 2020 ; Ngolab et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

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Retinal Vasculopathy in Alzheimer’s Disease

et al. 2021

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The retina has been increasingly investigated as a site of Alzheimer’s disease (AD) manifestation for over a decade. Early reports documented degeneration of retinal ganglion cells and their axonal projections. Our group provided the first evidence of the key pathological hallmarks of AD, amyloid β-protein (Aβ) plaques including vascular Aβ deposits, in the retina of AD and mild cognitively impaired (MCI) patients. Subsequent studies validated these findings and further identified electroretinography and vision deficits, retinal (p)tau and inflammation, intracellular Aβ accumulation, and retinal ganglion cell-subtype degeneration surrounding Aβ plaques in these patients. Our data suggest that the brain and retina follow a similar trajectory during AD progression, probably due to their common embryonic origin and anatomical proximity. However, the retina is the only CNS organ feasible for direct, repeated, and non-invasive ophthalmic examination with ultra-high spatial resolution and sensitivity. Neurovascular unit integrity is key to maintaining normal CNS function and cerebral vascular abnormalities are increasingly recognized as early and pivotal factors driving cognitive impairment in AD. Likewise, retinal vascular abnormalities such as changes in vessel density and fractal dimensions, blood flow, foveal avascular zone, curvature tortuosity, and arteriole-to-venule ratio were described in AD patients including early-stage cases. A rapidly growing number of reports have suggested that cerebral and retinal vasculopathy are tightly associated with cognitive deficits in AD patients and animal models. Importantly, we recently identified early and progressive deficiency in retinal vascular platelet-derived growth factor receptor-β (PDGFRβ) expression and pericyte loss that were associated with retinal vascular amyloidosis and cerebral amyloid angiopathy in MCI and AD patients. Other studies utilizing optical coherence tomography (OCT), retinal amyloid-fluorescence imaging and retinal hyperspectral imaging have made significant progress in visualizing and quantifying AD pathology through the retina. With new advances in OCT angiography, OCT leakage, scanning laser microscopy, fluorescein angiography and adaptive optics imaging, future studies focusing on retinal vascular AD pathologies could transform non-invasive pre-clinical AD diagnosis and monitoring.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Retinal Vasculopathy in Alzheimer’s Disease

et al. 2021

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“…The pathology of AD in the retina appears to mirror the disease in the brain 9 – 16 . Specifically, the retina of AD patients exhibits neuronal and pericyte cell loss along with retinal manifestation of AD pathological hallmarks—amyloid β-protein (Aβ) plaques and hyperphosphorylated tau (p-Tau) 9 – 13 , 16 – 27 . Similarly, numerous studies examining the retina of sporadic and transgenic animal models of AD have reported the existence of Aβ deposits and tauopathy that are linked with inflammation and neurodegeneration 9 , 14 , 15 , 28 – 41 .…”

Section: Introductionmentioning

confidence: 99%

Color and contrast vision in mouse models of aging and Alzheimer’s disease using a novel visual-stimuli four-arm maze

Vit

Fuchs

Angel

et al. 2021

Sci Rep

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We introduce a novel visual-stimuli four-arm maze (ViS4M) equipped with spectrally- and intensity-controlled LED emitters and dynamic grayscale objects that relies on innate exploratory behavior to assess color and contrast vision in mice. Its application to detect visual impairments during normal aging and over the course of Alzheimer’s disease (AD) is evaluated in wild-type (WT) and transgenic APPSWE/PS1∆E9 murine models of AD (AD+) across an array of irradiance, chromaticity, and contrast conditions. Substantial color and contrast-mode alternation deficits appear in AD+ mice at an age when hippocampal-based memory and learning is still intact. Profiling of timespan, entries and transition patterns between the different arms uncovers variable AD-associated impairments in contrast sensitivity and color discrimination, reminiscent of tritanomalous defects documented in AD patients. Transition deficits are found in aged WT mice in the absence of alternation decline. Overall, ViS4M is a versatile, controlled device to measure color and contrast-related vision in aged and diseased mice.

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“…Another method, hyperspectral retinal imaging (HSI), which uses a multi- spectral light source, could also identify the specific wavelength of light reflected from amyloids b-proteins 46 . The DL model predicting AD from HSI images still rendered considerable accuracy with a limited sample size of 39 participants (17 AD patients vs 22 normal controls) 47 . Despite the small sample size, significant clinical connections and customized AI models could minimize this disadvantage.…”

Section: Discussionmentioning

confidence: 99%

Detection of Systemic Diseases From Ocular Images Using Artificial Intelligence: A Systematic Review

Peng

Tseng

Tham

et al. 2022

Asia-Pacific Journal of Ophthalmology

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Purpose: Despite the huge investment in health care, there is still a lack of precise and easily accessible screening systems. With proven associations to many systemic diseases, the eye could potentially provide a credible perspective as a novel screening tool. This systematic review aims to summarize the current applications of ocular image–based artificial intelligence on the detection of systemic diseases and suggest future trends for systemic disease screening. Methods: A systematic search was conducted on September 1, 2021, using 3 databases—PubMed, Google Scholar, and Web of Science library. Date restrictions were not imposed and search terms covering ocular images, systemic diseases, and artificial intelligence aspects were used. Results: Thirty-three papers were included in this systematic review. A spectrum of target diseases was observed, and this included but was not limited to cardio-cerebrovascular diseases, central nervous system diseases, renal dysfunctions, and hepatological diseases. Additionally, one- third of the papers included risk factor predictions for the respective systemic diseases. Conclusions: Ocular image – based artificial intelligence possesses potential diagnostic power to screen various systemic diseases and has also demonstrated the ability to detect Alzheimer and chronic kidney diseases at early stages. Further research is needed to validate these models for real-world implementation.

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Combination of snapshot hyperspectral retinal imaging and optical coherence tomography to identify Alzheimer’s disease patients

Cited by 49 publications

References 60 publications

Retinal Vasculopathy in Alzheimer’s Disease

Retinal Vasculopathy in Alzheimer’s Disease

Color and contrast vision in mouse models of aging and Alzheimer’s disease using a novel visual-stimuli four-arm maze

Detection of Systemic Diseases From Ocular Images Using Artificial Intelligence: A Systematic Review

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