PMC:7523471 / 81200-87917 JSONTXT

{"project":"TEST0","denotations":[{"id":"33041751-195-203-816852","span":{"begin":211,"end":215},"obj":"[\"1993028\"]"},{"id":"33041751-235-243-816853","span":{"begin":364,"end":368},"obj":"[\"1993028\"]"},{"id":"33041751-154-162-816854","span":{"begin":525,"end":529},"obj":"[\"11595144\"]"},{"id":"33041751-175-183-816855","span":{"begin":546,"end":550},"obj":"[\"24616709\"]"},{"id":"33041751-195-203-816856","span":{"begin":566,"end":570},"obj":"[\"27847642\"]"},{"id":"33041751-217-225-816857","span":{"begin":588,"end":592},"obj":"[\"28106555\"]"},{"id":"33041751-230-238-816858","span":{"begin":609,"end":613},"obj":"[\"28101398\"]"},{"id":"33041751-232-240-816859","span":{"begin":628,"end":632},"obj":"[\"28282060\"]"},{"id":"33041751-228-236-816860","span":{"begin":648,"end":652},"obj":"[\"28600299\"]"},{"id":"33041751-225-233-816861","span":{"begin":677,"end":681},"obj":"[\"31506524\"]"},{"id":"33041751-228-236-816862","span":{"begin":707,"end":711},"obj":"[\"31415594\"]"},{"id":"33041751-199-207-816863","span":{"begin":995,"end":999},"obj":"[\"20550967\"]"},{"id":"33041751-221-229-816864","span":{"begin":1017,"end":1021},"obj":"[\"22343730\"]"},{"id":"33041751-234-242-816865","span":{"begin":1560,"end":1564},"obj":"[\"17472706\"]"},{"id":"33041751-234-242-816866","span":{"begin":1579,"end":1583},"obj":"[\"20092313\"]"},{"id":"33041751-231-239-816867","span":{"begin":1609,"end":1613},"obj":"[\"20550967\"]"},{"id":"33041751-234-242-816868","span":{"begin":1631,"end":1635},"obj":"[\"22343730\"]"},{"id":"33041751-235-243-816869","span":{"begin":1637,"end":1641},"obj":"[\"28814675\"]"},{"id":"33041751-233-241-816870","span":{"begin":1877,"end":1881},"obj":"[\"22343730\"]"},{"id":"33041751-232-240-816871","span":{"begin":3531,"end":3535},"obj":"[\"28814675\"]"},{"id":"33041751-157-165-816872","span":{"begin":3896,"end":3900},"obj":"[\"28814675\"]"},{"id":"33041751-222-230-816873","span":{"begin":4125,"end":4129},"obj":"[\"28814675\"]"},{"id":"33041751-234-242-816874","span":{"begin":4971,"end":4975},"obj":"[\"27830174\"]"},{"id":"33041751-227-235-816875","span":{"begin":5360,"end":5364},"obj":"[\"31530809\"]"},{"id":"33041751-78-86-816876","span":{"begin":5445,"end":5449},"obj":"[\"31530809\"]"},{"id":"33041751-143-151-816877","span":{"begin":5595,"end":5599},"obj":"[\"25354367\"]"},{"id":"33041751-162-170-816878","span":{"begin":5614,"end":5618},"obj":"[\"27333181\"]"},{"id":"33041751-226-234-816879","span":{"begin":5787,"end":5791},"obj":"[\"31603648\"]"},{"id":"33041751-194-202-816880","span":{"begin":5988,"end":5992},"obj":"[\"31650017\"]"},{"id":"33041751-227-235-816881","span":{"begin":6260,"end":6264},"obj":"[\"30574092\"]"},{"id":"33041751-231-239-816882","span":{"begin":6534,"end":6538},"obj":"[\"30574092\"]"}],"text":"Retinal Imaging\nThe mounting case for AD pathology in the retina has motivated investigations to develop various retinal imaging modalities, beginning with blue-light high-resolution photography by Tsai et al., 1991, which indicated a correlation between Alzheimer’s Disease Assessment Scale (ADAS) scores and optic nerve head changes in AD patients (Tsai et al., 1991).\nFurther studies employed cross-sectional imaging by optical coherence tomography (OCT) or optical coherence tomography angiography (OCTA) (Parisi et al., 2001; Kromer et al., 2014; Cunha et al., 2016; Ferrari et al., 2017; Polans et al., 2017; Polo et al., 2017; Bulut et al., 2018; Janez-Escalada et al., 2019; Salobrar-Garcia et al., 2019), which revealed structural abnormalities and cell neurodegeneration in the retina.\nAs mentioned above, the first in vivo imaging of AD hallmark pathology was initially developed and tested in transgenic murine models of AD by Koronyo-Hamaoui and colleagues (Koronyo-Hamaoui et al., 2011; Koronyo et al., 2012). The researchers paired curcumin – a natural and safe fluorochrome that labels Aβ fibrils and oligomers with high affinity and specificity – with a modified rodent retinal optical imaging microscope. Later, this approach was translated to humans and the feasibility to noninvasively detect and quantify individual retinal amyloid plaques was demonstrated in living patients with a modified confocal scanning laser ophthalmoscope following oral administration of highly bioavailable Longvida curcumin (Figures 7A–D; Garcia-Alloza et al., 2007; Gota et al., 2010; Koronyo-Hamaoui et al., 2011; Koronyo et al., 2012, 2017). Studies in murine ADtg models demonstrated the feasibility to longitudinally monitor individual Aβ deposits including their appearance and clearance during disease progression and in response to immune-based therapy (Koronyo et al., 2012).\nFIGURE 7 Proof-of-concept clinical trial shows the feasibility of noninvasive in vivo retinal curcumin-amyloid deposit imaging in AD patients. (A) Representative images of curcumin fluorescence fundography, enabling detection of increased retinal curcumin spots in a living AD patient relative to minimal spots in a cognitively normal (CN) control subject; Regions of interest (ROI) in superotemporal (ST) retinas are demarcated by white rectangles. Scale bar: 400 μm. (A’) Higher magnification image of the ROI with red circles highlighting curcumin-amyloid deposits in peripheral region of AD retina. (A”) Representative postprocessing images used to quantify spot number and fluorescent area (μm2). (B,C) color-coded overlay images from CN (B) and AD (C) retinas with curcumin-positive amyloid deposits above threshold shown in red, spots above 1:1 reference but below threshold shown in green and spots below reference in blue. (D) Representative graph showing number of color-coded spots (described in B,C) in AD retina used to determine retinal amyloid index (RAI) score. (E) Comparison of RAI scores in AD patients (n = 6) and age-matched CN subjects (n = 5). Data shown as group mean ± SEM. **P \u003c 0.005, unpaired 2-tailed Student’s t-test. Reproduced from Koronyo et al. (2017) with permission of ASCI via Copyright Clearance Center. Importantly, in the proof-of-principal clinical trial, this noninvasive amyloid imaging technique revealed a significant 2.1-fold greater retinal amyloid burden, termed as retinal amyloid index (RAI), in a group of 10 AD patients as compared to 6 age-matched healthy controls (Figure 7E; Koronyo et al., 2017). Supported by histological findings, retinal Aβ deposits were often found the mid- and far-periphery of the superior and inferior regions, where previously NFL thinning was reported as more pronounced. Further, amyloid deposits were found above the retinal pigment epithelium in the neurosensory retina, unlike the typical location of drusen (Koronyo et al., 2017). Anecdotal data from 2 AMD patients suggested that retinal curcumin fluorescence signals were diffuse and concentrated at the posterior pole, apparently distinct from findings in the retinas of AD patients (Koronyo et al., 2017). Moreover, results presented at the Alzheimer’s Association International Conference on July 15, 2014, from a large cohort of over 150 MCI, AD, and cognitively normal participants of the Australian Imaging, Biomarker and Lifestyle (AIBL) Study (www.aibl.csiro.au) found that retinal amyloid fluorescence imaging predicted cerebral amyloid burden and was significantly higher in AD patients (Frost et al., 2014).\nExpanding on this work, Kayabasi and colleagues detected abnormal Aβ deposits in 30 MCI patients using fundus autofluorescence imaging (FAF) and OCT (Kayabasi et al., 2014). An additional study utilizing OCT revealed a correlation between retinal inclusion bodies and cortical amyloid burden in pre-clinical patients via florbetapir PET and multiple retinal sd-OCT aggregation markers of possible disease burden (Snyder et al., 2016).\nNoninvasive in vivo retinal hyperspectral imaging (rHSI) has also recently been employed in patients and controls. One study found significant differences in the retinal reflectance spectra of MCI patients with high Aβ burden, confirmed by brain PET imaging, as compared to age-matched controls, validated in an independent cohort with a second hyperspectral camera (Hadoux et al., 2019). 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).\nFinally, a recent multimodal approach including visual performance tests, advanced retinal imaging, and full-field electroretinogram (ERG) in 69 cognitively impaired subjects revealed sensitivity of the combined approach to cognitive decline (Cabrera DeBuc et al., 2018). Although more robust investigations are needed to validate these findings, this study supports the association of retinal geometric vascular and functional parameters with physiological changes in the retina in cognitively impaired individuals (Cabrera DeBuc et al., 2018). Future tools should assess whether a combination of these multimodal methods with specific retinal amyloid imaging will allow for earlier and/or more accurate assessment of AD."}

{"project":"2_test","denotations":[{"id":"33041751-1993028-38666638","span":{"begin":211,"end":215},"obj":"1993028"},{"id":"33041751-1993028-38666639","span":{"begin":364,"end":368},"obj":"1993028"},{"id":"33041751-11595144-38666640","span":{"begin":525,"end":529},"obj":"11595144"},{"id":"33041751-24616709-38666641","span":{"begin":546,"end":550},"obj":"24616709"},{"id":"33041751-27847642-38666642","span":{"begin":566,"end":570},"obj":"27847642"},{"id":"33041751-28106555-38666643","span":{"begin":588,"end":592},"obj":"28106555"},{"id":"33041751-28101398-38666644","span":{"begin":609,"end":613},"obj":"28101398"},{"id":"33041751-28282060-38666645","span":{"begin":628,"end":632},"obj":"28282060"},{"id":"33041751-28600299-38666646","span":{"begin":648,"end":652},"obj":"28600299"},{"id":"33041751-31506524-38666647","span":{"begin":677,"end":681},"obj":"31506524"},{"id":"33041751-31415594-38666648","span":{"begin":707,"end":711},"obj":"31415594"},{"id":"33041751-20550967-38666649","span":{"begin":995,"end":999},"obj":"20550967"},{"id":"33041751-22343730-38666650","span":{"begin":1017,"end":1021},"obj":"22343730"},{"id":"33041751-17472706-38666651","span":{"begin":1560,"end":1564},"obj":"17472706"},{"id":"33041751-20092313-38666652","span":{"begin":1579,"end":1583},"obj":"20092313"},{"id":"33041751-20550967-38666653","span":{"begin":1609,"end":1613},"obj":"20550967"},{"id":"33041751-22343730-38666654","span":{"begin":1631,"end":1635},"obj":"22343730"},{"id":"33041751-28814675-38666655","span":{"begin":1637,"end":1641},"obj":"28814675"},{"id":"33041751-22343730-38666656","span":{"begin":1877,"end":1881},"obj":"22343730"},{"id":"33041751-28814675-38666657","span":{"begin":3531,"end":3535},"obj":"28814675"},{"id":"33041751-28814675-38666658","span":{"begin":3896,"end":3900},"obj":"28814675"},{"id":"33041751-28814675-38666659","span":{"begin":4125,"end":4129},"obj":"28814675"},{"id":"33041751-27830174-38666660","span":{"begin":4971,"end":4975},"obj":"27830174"},{"id":"33041751-31530809-38666661","span":{"begin":5360,"end":5364},"obj":"31530809"},{"id":"33041751-31530809-38666662","span":{"begin":5445,"end":5449},"obj":"31530809"},{"id":"33041751-25354367-38666663","span":{"begin":5595,"end":5599},"obj":"25354367"},{"id":"33041751-27333181-38666664","span":{"begin":5614,"end":5618},"obj":"27333181"},{"id":"33041751-31603648-38666665","span":{"begin":5787,"end":5791},"obj":"31603648"},{"id":"33041751-31650017-38666666","span":{"begin":5988,"end":5992},"obj":"31650017"},{"id":"33041751-30574092-38666667","span":{"begin":6260,"end":6264},"obj":"30574092"},{"id":"33041751-30574092-38666668","span":{"begin":6534,"end":6538},"obj":"30574092"}],"text":"Retinal Imaging\nThe mounting case for AD pathology in the retina has motivated investigations to develop various retinal imaging modalities, beginning with blue-light high-resolution photography by Tsai et al., 1991, which indicated a correlation between Alzheimer’s Disease Assessment Scale (ADAS) scores and optic nerve head changes in AD patients (Tsai et al., 1991).\nFurther studies employed cross-sectional imaging by optical coherence tomography (OCT) or optical coherence tomography angiography (OCTA) (Parisi et al., 2001; Kromer et al., 2014; Cunha et al., 2016; Ferrari et al., 2017; Polans et al., 2017; Polo et al., 2017; Bulut et al., 2018; Janez-Escalada et al., 2019; Salobrar-Garcia et al., 2019), which revealed structural abnormalities and cell neurodegeneration in the retina.\nAs mentioned above, the first in vivo imaging of AD hallmark pathology was initially developed and tested in transgenic murine models of AD by Koronyo-Hamaoui and colleagues (Koronyo-Hamaoui et al., 2011; Koronyo et al., 2012). The researchers paired curcumin – a natural and safe fluorochrome that labels Aβ fibrils and oligomers with high affinity and specificity – with a modified rodent retinal optical imaging microscope. Later, this approach was translated to humans and the feasibility to noninvasively detect and quantify individual retinal amyloid plaques was demonstrated in living patients with a modified confocal scanning laser ophthalmoscope following oral administration of highly bioavailable Longvida curcumin (Figures 7A–D; Garcia-Alloza et al., 2007; Gota et al., 2010; Koronyo-Hamaoui et al., 2011; Koronyo et al., 2012, 2017). Studies in murine ADtg models demonstrated the feasibility to longitudinally monitor individual Aβ deposits including their appearance and clearance during disease progression and in response to immune-based therapy (Koronyo et al., 2012).\nFIGURE 7 Proof-of-concept clinical trial shows the feasibility of noninvasive in vivo retinal curcumin-amyloid deposit imaging in AD patients. (A) Representative images of curcumin fluorescence fundography, enabling detection of increased retinal curcumin spots in a living AD patient relative to minimal spots in a cognitively normal (CN) control subject; Regions of interest (ROI) in superotemporal (ST) retinas are demarcated by white rectangles. Scale bar: 400 μm. (A’) Higher magnification image of the ROI with red circles highlighting curcumin-amyloid deposits in peripheral region of AD retina. (A”) Representative postprocessing images used to quantify spot number and fluorescent area (μm2). (B,C) color-coded overlay images from CN (B) and AD (C) retinas with curcumin-positive amyloid deposits above threshold shown in red, spots above 1:1 reference but below threshold shown in green and spots below reference in blue. (D) Representative graph showing number of color-coded spots (described in B,C) in AD retina used to determine retinal amyloid index (RAI) score. (E) Comparison of RAI scores in AD patients (n = 6) and age-matched CN subjects (n = 5). Data shown as group mean ± SEM. **P \u003c 0.005, unpaired 2-tailed Student’s t-test. Reproduced from Koronyo et al. (2017) with permission of ASCI via Copyright Clearance Center. Importantly, in the proof-of-principal clinical trial, this noninvasive amyloid imaging technique revealed a significant 2.1-fold greater retinal amyloid burden, termed as retinal amyloid index (RAI), in a group of 10 AD patients as compared to 6 age-matched healthy controls (Figure 7E; Koronyo et al., 2017). Supported by histological findings, retinal Aβ deposits were often found the mid- and far-periphery of the superior and inferior regions, where previously NFL thinning was reported as more pronounced. Further, amyloid deposits were found above the retinal pigment epithelium in the neurosensory retina, unlike the typical location of drusen (Koronyo et al., 2017). Anecdotal data from 2 AMD patients suggested that retinal curcumin fluorescence signals were diffuse and concentrated at the posterior pole, apparently distinct from findings in the retinas of AD patients (Koronyo et al., 2017). Moreover, results presented at the Alzheimer’s Association International Conference on July 15, 2014, from a large cohort of over 150 MCI, AD, and cognitively normal participants of the Australian Imaging, Biomarker and Lifestyle (AIBL) Study (www.aibl.csiro.au) found that retinal amyloid fluorescence imaging predicted cerebral amyloid burden and was significantly higher in AD patients (Frost et al., 2014).\nExpanding on this work, Kayabasi and colleagues detected abnormal Aβ deposits in 30 MCI patients using fundus autofluorescence imaging (FAF) and OCT (Kayabasi et al., 2014). An additional study utilizing OCT revealed a correlation between retinal inclusion bodies and cortical amyloid burden in pre-clinical patients via florbetapir PET and multiple retinal sd-OCT aggregation markers of possible disease burden (Snyder et al., 2016).\nNoninvasive in vivo retinal hyperspectral imaging (rHSI) has also recently been employed in patients and controls. One study found significant differences in the retinal reflectance spectra of MCI patients with high Aβ burden, confirmed by brain PET imaging, as compared to age-matched controls, validated in an independent cohort with a second hyperspectral camera (Hadoux et al., 2019). 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).\nFinally, a recent multimodal approach including visual performance tests, advanced retinal imaging, and full-field electroretinogram (ERG) in 69 cognitively impaired subjects revealed sensitivity of the combined approach to cognitive decline (Cabrera DeBuc et al., 2018). Although more robust investigations are needed to validate these findings, this study supports the association of retinal geometric vascular and functional parameters with physiological changes in the retina in cognitively impaired individuals (Cabrera DeBuc et al., 2018). Future tools should assess whether a combination of these multimodal methods with specific retinal amyloid imaging will allow for earlier and/or more accurate assessment of AD."}

{"project":"0_colil","denotations":[{"id":"33041751-1993028-816852","span":{"begin":211,"end":215},"obj":"1993028"},{"id":"33041751-1993028-816853","span":{"begin":364,"end":368},"obj":"1993028"},{"id":"33041751-11595144-816854","span":{"begin":525,"end":529},"obj":"11595144"},{"id":"33041751-24616709-816855","span":{"begin":546,"end":550},"obj":"24616709"},{"id":"33041751-27847642-816856","span":{"begin":566,"end":570},"obj":"27847642"},{"id":"33041751-28106555-816857","span":{"begin":588,"end":592},"obj":"28106555"},{"id":"33041751-28101398-816858","span":{"begin":609,"end":613},"obj":"28101398"},{"id":"33041751-28282060-816859","span":{"begin":628,"end":632},"obj":"28282060"},{"id":"33041751-28600299-816860","span":{"begin":648,"end":652},"obj":"28600299"},{"id":"33041751-31506524-816861","span":{"begin":677,"end":681},"obj":"31506524"},{"id":"33041751-31415594-816862","span":{"begin":707,"end":711},"obj":"31415594"},{"id":"33041751-20550967-816863","span":{"begin":995,"end":999},"obj":"20550967"},{"id":"33041751-22343730-816864","span":{"begin":1017,"end":1021},"obj":"22343730"},{"id":"33041751-17472706-816865","span":{"begin":1560,"end":1564},"obj":"17472706"},{"id":"33041751-20092313-816866","span":{"begin":1579,"end":1583},"obj":"20092313"},{"id":"33041751-20550967-816867","span":{"begin":1609,"end":1613},"obj":"20550967"},{"id":"33041751-22343730-816868","span":{"begin":1631,"end":1635},"obj":"22343730"},{"id":"33041751-28814675-816869","span":{"begin":1637,"end":1641},"obj":"28814675"},{"id":"33041751-22343730-816870","span":{"begin":1877,"end":1881},"obj":"22343730"},{"id":"33041751-28814675-816871","span":{"begin":3531,"end":3535},"obj":"28814675"},{"id":"33041751-28814675-816872","span":{"begin":3896,"end":3900},"obj":"28814675"},{"id":"33041751-28814675-816873","span":{"begin":4125,"end":4129},"obj":"28814675"},{"id":"33041751-27830174-816874","span":{"begin":4971,"end":4975},"obj":"27830174"},{"id":"33041751-31530809-816875","span":{"begin":5360,"end":5364},"obj":"31530809"},{"id":"33041751-31530809-816876","span":{"begin":5445,"end":5449},"obj":"31530809"},{"id":"33041751-25354367-816877","span":{"begin":5595,"end":5599},"obj":"25354367"},{"id":"33041751-27333181-816878","span":{"begin":5614,"end":5618},"obj":"27333181"},{"id":"33041751-31603648-816879","span":{"begin":5787,"end":5791},"obj":"31603648"},{"id":"33041751-31650017-816880","span":{"begin":5988,"end":5992},"obj":"31650017"},{"id":"33041751-30574092-816881","span":{"begin":6260,"end":6264},"obj":"30574092"},{"id":"33041751-30574092-816882","span":{"begin":6534,"end":6538},"obj":"30574092"}],"text":"Retinal Imaging\nThe mounting case for AD pathology in the retina has motivated investigations to develop various retinal imaging modalities, beginning with blue-light high-resolution photography by Tsai et al., 1991, which indicated a correlation between Alzheimer’s Disease Assessment Scale (ADAS) scores and optic nerve head changes in AD patients (Tsai et al., 1991).\nFurther studies employed cross-sectional imaging by optical coherence tomography (OCT) or optical coherence tomography angiography (OCTA) (Parisi et al., 2001; Kromer et al., 2014; Cunha et al., 2016; Ferrari et al., 2017; Polans et al., 2017; Polo et al., 2017; Bulut et al., 2018; Janez-Escalada et al., 2019; Salobrar-Garcia et al., 2019), which revealed structural abnormalities and cell neurodegeneration in the retina.\nAs mentioned above, the first in vivo imaging of AD hallmark pathology was initially developed and tested in transgenic murine models of AD by Koronyo-Hamaoui and colleagues (Koronyo-Hamaoui et al., 2011; Koronyo et al., 2012). The researchers paired curcumin – a natural and safe fluorochrome that labels Aβ fibrils and oligomers with high affinity and specificity – with a modified rodent retinal optical imaging microscope. Later, this approach was translated to humans and the feasibility to noninvasively detect and quantify individual retinal amyloid plaques was demonstrated in living patients with a modified confocal scanning laser ophthalmoscope following oral administration of highly bioavailable Longvida curcumin (Figures 7A–D; Garcia-Alloza et al., 2007; Gota et al., 2010; Koronyo-Hamaoui et al., 2011; Koronyo et al., 2012, 2017). Studies in murine ADtg models demonstrated the feasibility to longitudinally monitor individual Aβ deposits including their appearance and clearance during disease progression and in response to immune-based therapy (Koronyo et al., 2012).\nFIGURE 7 Proof-of-concept clinical trial shows the feasibility of noninvasive in vivo retinal curcumin-amyloid deposit imaging in AD patients. (A) Representative images of curcumin fluorescence fundography, enabling detection of increased retinal curcumin spots in a living AD patient relative to minimal spots in a cognitively normal (CN) control subject; Regions of interest (ROI) in superotemporal (ST) retinas are demarcated by white rectangles. Scale bar: 400 μm. (A’) Higher magnification image of the ROI with red circles highlighting curcumin-amyloid deposits in peripheral region of AD retina. (A”) Representative postprocessing images used to quantify spot number and fluorescent area (μm2). (B,C) color-coded overlay images from CN (B) and AD (C) retinas with curcumin-positive amyloid deposits above threshold shown in red, spots above 1:1 reference but below threshold shown in green and spots below reference in blue. (D) Representative graph showing number of color-coded spots (described in B,C) in AD retina used to determine retinal amyloid index (RAI) score. (E) Comparison of RAI scores in AD patients (n = 6) and age-matched CN subjects (n = 5). Data shown as group mean ± SEM. **P \u003c 0.005, unpaired 2-tailed Student’s t-test. Reproduced from Koronyo et al. (2017) with permission of ASCI via Copyright Clearance Center. Importantly, in the proof-of-principal clinical trial, this noninvasive amyloid imaging technique revealed a significant 2.1-fold greater retinal amyloid burden, termed as retinal amyloid index (RAI), in a group of 10 AD patients as compared to 6 age-matched healthy controls (Figure 7E; Koronyo et al., 2017). Supported by histological findings, retinal Aβ deposits were often found the mid- and far-periphery of the superior and inferior regions, where previously NFL thinning was reported as more pronounced. Further, amyloid deposits were found above the retinal pigment epithelium in the neurosensory retina, unlike the typical location of drusen (Koronyo et al., 2017). Anecdotal data from 2 AMD patients suggested that retinal curcumin fluorescence signals were diffuse and concentrated at the posterior pole, apparently distinct from findings in the retinas of AD patients (Koronyo et al., 2017). Moreover, results presented at the Alzheimer’s Association International Conference on July 15, 2014, from a large cohort of over 150 MCI, AD, and cognitively normal participants of the Australian Imaging, Biomarker and Lifestyle (AIBL) Study (www.aibl.csiro.au) found that retinal amyloid fluorescence imaging predicted cerebral amyloid burden and was significantly higher in AD patients (Frost et al., 2014).\nExpanding on this work, Kayabasi and colleagues detected abnormal Aβ deposits in 30 MCI patients using fundus autofluorescence imaging (FAF) and OCT (Kayabasi et al., 2014). An additional study utilizing OCT revealed a correlation between retinal inclusion bodies and cortical amyloid burden in pre-clinical patients via florbetapir PET and multiple retinal sd-OCT aggregation markers of possible disease burden (Snyder et al., 2016).\nNoninvasive in vivo retinal hyperspectral imaging (rHSI) has also recently been employed in patients and controls. One study found significant differences in the retinal reflectance spectra of MCI patients with high Aβ burden, confirmed by brain PET imaging, as compared to age-matched controls, validated in an independent cohort with a second hyperspectral camera (Hadoux et al., 2019). 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).\nFinally, a recent multimodal approach including visual performance tests, advanced retinal imaging, and full-field electroretinogram (ERG) in 69 cognitively impaired subjects revealed sensitivity of the combined approach to cognitive decline (Cabrera DeBuc et al., 2018). Although more robust investigations are needed to validate these findings, this study supports the association of retinal geometric vascular and functional parameters with physiological changes in the retina in cognitively impaired individuals (Cabrera DeBuc et al., 2018). Future tools should assess whether a combination of these multimodal methods with specific retinal amyloid imaging will allow for earlier and/or more accurate assessment of AD."}