Evaluation of Ocular Perfusion in Alzheimer’s Disease Using Optical Coherence Tomography Angiography

Abstract

Background:

There is increasing evidence for the involvement of cerebrovascular factors in Alzheimer’s disease (AD).

Objective:

To evaluate retinal and optic nerve head perfusion in patients with AD using optical coherence tomography angiography (OCTA), and to analyze the correlations of quantitative OCTA metrics with AD pathology and vascular cerebral lesions in AD patients.

Methods:

36 eyes of 36 patients with AD (study group) and 38 eyes of 38 healthy subjects (control group) were prospectively included in this study. OCTA was performed using RTVue XR Avanti with AngioVue. In addition, patients underwent a detailed ophthalmological and neurological examination including Mini-Mental State Examination, cerebral magnetic resonance imaging, and amyloid-β (Aβ) and tau levels in the cerebrospinal fluid (CSF).

Results:

The flow density in the superficial retinal OCT angiogram of the macula in the study group was significantly lower compared to the control group (p = 0.001). There was a significant correlation between the flow density in the superficial retinal OCT angiogram of the macula, as measured using OCTA, and the Fazekas scale (Spearman’s correlation coefficient = –0.520; p = 0.003). There was no significant correlation between the Aβ or tau levels in the CSF and the flow density data.

Conclusion:

Patients with AD showed a reduced flow density in the radial peripapillary capillaries layer and in the superficial retinal OCT angiogram when compared with healthy controls. The reduced retinal flow density measured using OCTA is not specifically associated with AD pathology but is associated with the vascular cerebral lesions in AD.

Keywords

Alzheimer’s disease flow density optical coherence tomography angiography retinal and optic nerve head perfusion

INTRODUCTION

Dementia is the leading cause of dependence and disability in the elderly population worldwide [1, 2]. Alzheimer’s disease (AD) in particular is a growing worldwide health concern and is the third leading cause of death in the United States [3, 4].

Different studies have shown pathological optical coherence tomography (OCT) findings (especially a retinal nerve fiber layer (RNFL) thinning) in AD [5, 6]. These changes have been hypothesized to occur because of retrograde degeneration of the retinal ganglion cell axons [7]. Kirbas et al. also suggest that neuroretinal atrophy may occur as a result of amyloid-β (Aβ) plaque deposits within the retina [8]. However, the primary pathophysiological link between morphological retinal changes and AD pathology remains unclear. Beside specific neuropathological alterations, AD is indeed associated with vascular alterations [9]. Thus, it is unclear whether morphological retinal changes indicate a primary and specific neurodegeneration or are simply secondary changes due to vascular alterations.

Cerebral small vessel disease is a contributory risk factor for stroke and dementia [10, 11]. Vascular contributions to cognitive impairment and dementia are now extensively evaluated in the spectrum of cognitive impairment. Moreover, the area of clinical interest has recently been extended from the brain to include cerebral blood vessels, shifting the pathophysiological focus to the cerebral microcirculation and cardiovascular function [10, 12]. An important challenge in the diagnosis and research of cerebral small vessel disease is that the affected vessels are too small to be directly visualized in vivo, so that diagnosis has to be based on associated patterns of brain injury [13].

The retina and the optic nerve head (ONH) are parts of the central nervous system [14]. A newly presented extension of structural OCT, referred to as optical coherence tomography angiography (OCTA), enables visualization and quantitative analysis of the retinal vasculature without intravenously injected dye.

The aim of this study was to evaluate retinal and ONH perfusion using OCTA in patients with AD. Moreover, we analyzed the association between quantitative OCTA values and AD biomarkers as well as vascular cerebral lesion in AD patients.

MATERIALS AND METHODS

Participants

A total of 36 AD patients with a Mini-Mental State Examination (MMSE)≥10 and 38 age-matched healthy controls were included in this study. AD was diagnosed according to the 2011 guidelines of the National Institute of Aging-Alzheimer’s Association workgroups [15]. Patients were recruited in the Department of Neurology at the University Hospital Münster, Germany. The study adhered to the tenets of the Declaration of Helsinki and was approved by the Ethics Committee of the University of Muenster, North Rhine Westphalia, Germany. Before performing any imaging, the study protocol was explained in detail and all participants signed an informed consent form.

Subjects with psychiatric, malignant, infectious, or inflammatory diseases or a history of stroke were excluded. None of the patients exhibited features of an acute inflammatory process such as elevated erythrocyte sedimentation rate, CRP, or neutrophil count. Further exclusion criteria were the intake of immunologically relevant drugs. Patients with previous retinal surgery, pre-existing macular pathologies such as age-related macular degeneration, macular hole or macular edema, glaucoma, or any other disease that could potentially cause optic disc atrophy were excluded. Patients with corneal anomalies or dense cataract preventing high-quality imaging were also excluded.

Examinations

All patients underwent a physical and neurological examination by a trained study physician and a detailed neuropsychological examination, assessment of family and medical history, a lumbar puncture, electroencephalogram, event related potentials (P300), and a 3 Tesla magnetic resonance imaging (MRI) of the brain. Two experienced observers blinded to clinical data performed structural MRI analysis. Vascular cerebral white matter lesions were rated on a 3-point scale according to the well-established periventricular score of Fazekas et al. [16].

A full ophthalmic examination was also performed including refraction, best corrected visual acuity, measurement of intraocular pressure, anterior segment examination, and fundus examination. Patients then underwent OCT-A imaging of the macula and the optic nerve head in the same location under the same conditions by an expert examiner.

OCT angiography

OCTA imaging of all subjects was performed with the (RTVue XR Avanti with AngioVue; Optovue Inc, Fremont, CA, USA). This spectral domain OCT system has an A-scan rate of 70,000 scans per second using a light source centered on 840|nm and a bandwidth of 45|nm. OCT-A data were generated using the split-spectrum amplitude-decorrelation angiography algorithm. The OCTA technology has been described elsewhere in detail [17]. In brief, the underlying principle is as follows: As the retina is a stationary object, OCT B-scans acquired successively at the same position will be similar in every respect except for the motion of blood in the retinal vessels. By comparing repeated OCT B-scans of the same retinal area, it is therefore possible to visualize blood flow by looking for differences among the scans on a pixel-by-pixel basis [17]. OCTA imaging of the macula was performed using a 3×3 mm² scan and images of the ONH and the peripapillary area were obtained with a 4.5×4.5 mm² scan. Only OCT-A images of good quality were included, and images with lines or gaps due to poor signal strength or motion artefacts were excluded from the study. The automated segmentation was checked before data analysis.

Satistics

Data management was performed using Microsoft Excel 2013. IBM SPSS ^® Statistics 22 for Windows (IBM Corporation, Somers, NY, USA) was used for statistical analyses. The data was tested for normality distribution using the Shapiro–Wilk test and did not fit a normal distribution. The two groups were therefore compared using the Mann-Whitney U test for non-normally distributed variables, and the degree of correlation between two variables was expressed as the Spearman’s correlation coefficient (rSp.). The data are presented as mean±SD; (median [25, 75 percentile]). Inferential statistics are intended to be exploratory (hypotheses-generating), not confirmatory, and are interpreted accordingly. The chosen level of statistical significance was p < 0.05.

RESULTS

Thirty-six patients with AD (age: 67.97±9.30 (68.50 [63.00, 75.00])), and 38 age-matched control subjects (age: 66.08±10.11 (67.50 [55.75, 76.00]) were prospectively included in the study. The study focused on patients in early stages of AD with a mean MMSE score of 22.32±4.45. Average white matter lesion load on MRI was mild to moderate (mean Fazekas scale 1.77±0.77). Details of the study population for the study and the control group are summarized in Table 1.

Table 1

Characteristics of the study and control groups. Bold, statistically significant differences between the study group and the control group; IOD, intraocular pressure; MMSE, Mini-Mental State Examination

	Study group Mean±SD; (median [25, 75 percentile])	Control group Mean±SD; (median [25, 75 percentile])	p
n	36	38
gender (f/m)	(21/15)	(23/14)
age (y)	67.97±9.30 (68.50 [63.00, 75.00])	66.08±10.11 (67.50 [55.75, 76.00])	0.44
spherical equivalent (D)	1.17±3.96 (0.56 [–0.63, 1.50])	0.43±1.42 (0.38 [–0.50, 1.16])	0.70
IOD (mmHg)	15.89±3.08 (15.50 [14.0, 17.75])	14.53±2.64 (15.00 [12.75, 16.00])	0.10
visual acuity (decimal notation)	0.73±0.23 (0.80 [0.63, 1.0])	0.83±0.20 (0.8 [0.8, 1.0])	0.07
amyloid (pg/ml)	552.54±156.69 (551.00 [465.25, 676.50])
tau-protein (pg/ml)	587.63±295.16(560.00 [497.00, 673])
Fazekas Scale	1.77±0.77 (2.00 [1.00, 2,00])
MMSE (pts)	22.32±4.45 (23.00 [20.00,26.00, 20.00,26.00])

OCTA findings

There was no significant difference between the signal strength index in the AD group and the control group (ONH: study group: 62.97±11.50 (64.00 [54.00, 72.00]), control group: 67.44±8.86 (68.00 [62.88, 74.00]), p = 0.10; macula: study group: 65.81±8.43 (65.50 [60.25, 73.75]), control group: 69.44±8.28 (71.00 [65.42, 75.75]), p = 0.06)).

There was no difference in the area of the foveal avascular zone, as measured in the superficial/deep OCT-angiogram of the macula, between the two groups (superficial: study group: 0.28±0.08 mm² (0.28 [0.22, 0.36] mm²)); control group: 0.28±0.09 mm² (0.28 [0.22, 0.36] mm²); p = 0.86; deep: study group: 0.32±0.10 mm² (0.34, [0.24, 0.38] mm²); control group: 0.33±0.14 mm² (0.34 [0.26, 0.40] mm²), p = 0.89).

The flow density (whole en face) in the ONH (radial peripapillary capillaries, RPC) and in the superficial retinal OCT angiogram of the macula in the study group was significantly lower compared to the control group (RPC: study group: 53.07±3.80% (53.34 [50.37, 56.35]%); control group: 55.39±3.70% (55.55 [53.67, 57.68]%); p = 0.015; macula: study group: 48.77±3.92% (49.58 [45.05, 51.91]%), control group: 51.64±3.28% (52.49 [49.91, 54.04]%) p = 0.001) (Fig. 1). Flow density data in the ONH, and retinal OCT angiogram of the macula are summarized in Table 2.

Fig. 1.

The superficial retinal OCT angiograms of the macula (A) and color-coded vessel density maps (B) in a healthy control and in a patient with Alzheimer’s disease. The foveal flow density (diameter of 1 mm, small white circle), parafoveal flow density (diameter from 1 mm to 2.5 mm) and flow density whole en face (the average flow density of the entire 2.5 mm circle) were analyzed.

Fig. 2.

Correlation between the flow density obtained in the superficial OCT angiogram of the macula and the Fazekas scale.

Table 2

Values of flow density (%) obtained in the regions indicated. Bold, statistically significant differences between the two groups

	Study group Mean±SD; (median [25,75 percentile])	Control group Mean±SD; (median [25,75 percentile])	p
OCT-A superficial
whole en face	48.77±3.92 (49.58 [45.05, 51.91])	51.64±3.28 (52.49 [49.91, 54.04])	0.001
fovea	29.40±5.72 (29.35 [25.94, 32.50])	31.06±5.35 (31.72 [26.63, 34.42])	0.171
parafovea	50.93±4.05 (52.60 [47.21, 53.92])	53.55±3.31 (53.73 [51.97, 55,78])	0.003
OCT-A deep
whole en face	55.35±3.16 (56.13 [52.75, 58.12])	56.72±2.21 (57.02 [55.53, 57.93])	0.090
fovea	31.21±6.60 (29–97 [26.49, 35.27])	29.32±6.67 (29.22 [25.09, 32.14])	0.234
parafovea	57.97±3.30 (59.20 [54.83, 60.60])	58.38±4.64 (59.15 [57.90, 60.37])	0.339
OCT-A Disc
whole en face	53.07±3.80 (53.34 [50.37, 56.35])	55.39±3.70 (55.55 [53.67, 57.68])	0.015
peripapillary	60.89±4.51 (61.27 [59.17,64.41])	62.83±3.98 (63.85 [60.37, 65.34])	0.067

Association of octa alterations with ad pathology and vascular cerebral lesions

There was a negative correlation between the flow density in the superficial retinal OCT angiogram of the macula as measured using OCTA and the Fazekas scale (Spearman’s correlation coefficient = –0.520; p = 0.003), indicating that a higher vascular cerebral lesion load was associated with a reduced flow density in the superficial retinal OCT angiogram (Table 3, Fig. 2). However, we found no significant correlation between the established AD biomarkers (Aβ or tau levels) in the cerebrospinal fluid (CSF) or between a cognitive screening test (MMSE values) and flow density (Table 3).

Table 3

Spearman correlations between the flow density obtained in the superficial retinal OCT angiogram and amyloid-β, tau Protein, Mini-Mental State Examination (MMSE) and Fazekas scale. Spearman, Spearman correlation coefficient; Bold, statistically significant results

		Flow density (whole en face)	Flow density (parafovea)
CSF Amyloid-β pg/ml	r Spearman	0.125	0.099
	p-value	0.527	0.615
CSF Total Tau Protein pg/ml	r Spearman	0.257	0.256
	p-value	0.196	0.198
MMSE	r Spearman	0.068	0.014
	p-value	0.715	0.940
Fazekas scale	r Spearman	–0.520	–0.514
	p-value	0.003	0.004

DISCUSSION

The retina is a part of the central nervous system. During embryonic development, it is a direct extension of the brain and is therefore seen as a “window to the brain” [14]. Data obtained from the retina may therefore be of evident value for developing biomarkers of AD, especially as the retina may undergo similar pathological changes [18]. Multiple studies have demonstrated a reduced RNFL thickness in patients with AD [5, 6]. One study also showed that the RNFL thickness measured using structural OCT is inversely correlated with the duration of disease as well as disease severity [18]. OCTA is a novel noninvasive technology, which enables the visualization of retinal and choroidal vasculature without intravenously injected dye. OCTA also allows quantitative analysis of the retinal perfusion. This imaging technique is accurate, reproducible, and can be performed easily and quickly. Over the last two years quantitative analysis of retinal perfusion using OCTA has been evaluated in ocular and systemic diseases and also in different animal models [19 –23].

There is increasing evidence for the involvement of cerebrovascular factors not only in vascular causes of cognitive impairment but also in AD [24, 25]. Different neuroimaging studies using imaging technologies such as single-photon emission computed tomography and arterial spin labeling MRI have demonstrated an altered cerebral blood flow in AD [26 –28]. These observations support the contention that beside amyloid-or tau pathology there is also diffuse microvascular disease associated with AD [25, 29]. The reduced brain capillary density in AD might be associated with the Aβ accumulations on capillaries [30 –33]. Furthermore, vascular dysfunction seems to play a crucial role in the pathogenesis of AD and changes in cerebral perfusion are present long before the development of the clinical symptoms of AD [9]. This hypothesis might also explain the disparity between clinical and pathological phenotypes and why, in two individuals with the same extent of AD neuropathology, one may be demented while the other remains cognitively intact. Dementia is often characterized as being caused by one of several major diseases, such as AD. The clinicopathological studies of dementia demonstrate that multiple pathologic processes often coexist. Beside AD pathology, the other most common pathologies associated with brain aging are cerebrovascular diseases, which expend the cognitive reserve in patients with AD pathology and could lead to the clinical manifestation of dementia symptoms [34, 35].

In the current study, the flow density in the superficial retinal OCT angiogram was significantly lower in patients with AD compared with healthy controls, even in early stages of the disease. This is in line with results presented in the literature. Bulut et al. demonstrated using OCTA a reduced retinal vascular density in the macula and explained the differences by the decreased angiogenesis due to the binding of VEGF to Aβ and the accumulation of Aβ deposits in the internal vessel walls, leading to a decreased blood flow in AD patients [33]. Moreover, in the study presented here, we demonstrate a reduced vessel density in the RPC layer of the ONH, showing that vascular abnormalities in AD patients are not restricted to the macula. The differences in the deep retinal OCT angiogram of the macula did not reach the significance level. OCTA imaging in the deep retinal OCT angiogram is affected by projection artefacts and therefore the quantification of flow density is more challenging and the repeatability was found to be weaker compared with that of the superficial retinal OCT angiogram [36 –38].

The Fazekas scale is a well-established value that quantifies white matter lesions in the periventricular and subcortical region on a 0 to 3 scale. It has a significant impact on the diagnosis of a vascular component during the diagnostic workup [16 , 40]. To our knowledge, this is the first study to demonstrate a significant correlation between the Fazekas score and retinal flow density as measured using OCTA. Even more interesting is the fact that we found no correlation between flow density and the established biomarkers of AD, Aβ or tau levels in the CSF. OCTA is a non-contact technology, which is more cost effective than MRI and can be performed quickly and easy, particularly in dementia patients.

Finally, it is important to mention that a reduced ocular perfusion could also have been the cause for the RNFL thinning observed in patients with AD in different studies in the literature [5 –8]. With the structural OCT used by these authors, it was not possible to consider the vascular aspect of the changes observed, and this should be taken into account when assessing the results presented.

Our study is not without limitations: First, it is a cross-sectional study. We cannot therefore comment on the value of flow density measurements for evaluation of disease progression. Further studies with a longitudinal design and with a comparison of AD patients and patients with mainly vascular cerebral lesions (or vascular dementia) are warranted. A second limitation is the sample size. However, the patients included in the current study were thoroughly examined, accounting a rather homogeneous study population.

In conclusion we demonstrate an altered microcirculation in the macula and ONH of patients with AD. The reduced retinal flow density was associated with the vascular cerebral component in AD, but not with clinically significant neuropsychological neurocognitive deficits or AD pathology, indicating that OCTA could be used as a valid marker of vascular cerebral lesions in AD, but not as a marker of specific AD pathology.

Footnotes

ACKNOWLEDGMENTS

We acknowledge support by Open Access Publication Fund of University of Muenster.

Authors’ disclosures available online ().

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