Rationale and design of the BeyeOMARKER study: prospective evaluation of blood- and eye-based biomarkers for early detection of Alzheimer's disease pathology in the eye clinic.

BACKGROUND: Alzheimer's disease (AD) is a common, complex and multifactorial disease that may require screening across multiple routes of referral to enable early detection and subsequent future implementation of tailored interventions. Blood- and eye-based biomarkers show promise as low-cost, scalable and patient-friendly tools for early AD detection given their ability to provide information on AD pathophysiological changes and manifestations in the retina, respectively. Eye clinics provide an intriguing real-world proof-of-concept setting to evaluate the performance of these potential AD screening tools given the intricate connections between the eye and brain, presumed enrichment for AD pathology in the aging population with eye disorders, and the potential for an accelerated diagnostic pathway for under-recognized patient groups. METHODS: The BeyeOMARKER study is a prospective, observational, longitudinal cohort study aiming to include individuals visiting an eye-clinic. Inclusion criteria entail being ≥ 50 years old and having no prior dementia diagnosis. Excluded eye-conditions include traumatic insults, superficial inflammation, and conditions in surrounding structures of the eye that are not engaged in vision. The BeyeOMARKER cohort (n = 700) will undergo blood collection to assess plasma p-tau217 levels and a brief cognitive screening at the eye clinic. All participants will subsequently be invited for annual longitudinal follow-up including remotely administered cognitive screening and questionnaires. The BeyeOMARKER + cohort (n = 150), consisting of 100 plasma p-tau217 positive participants and 50 matched negative controls selected from the BeyeOMARKER cohort, will additionally undergo Aß-PET and tau-PET, MRI, retinal imaging including hyperspectral imaging (primary), widefield imaging, optical coherence tomography (OCT) and OCT-Angiography (secondary), and cognitive and cortical vision assessments. RESULTS: We aim to implement the current protocol between April 2024 until March 2027. Primary outcomes include the performance of plasma p-tau217 and hyperspectral retinal imaging to detect AD pathology (using Aß- and tau-PET visual read as reference standard) and to detect cognitive decline. Initial follow-up is ~ 2 years but may be extended with additional funding. CONCLUSIONS: We envision that the BeyeOMARKER study will demonstrate the feasibility of early AD detection based on blood- and eye-based biomarkers in alternative screening settings, and will improve our understanding of the eye-brain connection. TRIAL REGISTRATION: The BeyeOMARKER study (Eudamed CIV ID: CIV-NL-23-09-044086; registration date: 19th of March 2024) is approved by the ethical review board of the Amsterdam UMC.

Quality factor based correction for SD-OCT measurements in cataract patients.

PURPOSE: To correct peripapillary retinal nerve fibre layer (pRNFL) measurements performed with spectral domain optical coherence tomography (SD-OCT) for low image quality factor (QF) in patients with cataract, using measurements before and after cataract surgery. METHODS: SD-OCT (Topcon 3DOCT-2000) volume scans of the optic disc of 13 cataract patients were used. A set of three reflective filters with optical density ranging from 0.11 to 0.54 were used. The correlation was calculated between the change in thickness measurements and the change in image quality factor. Changes before and after cataract surgery were analysed. A correction for scans with a lower QF was calculated using an equation which was formulated based on the relationship between the change in thickness measurements and the change in image quality factor. RESULTS: Thirteen right eyes of thirteen cataract patients were included in this study. pRNFL thickness measurements before and after cataract differed significantly (96 versus 99 micron, p < 0.01). Preoperative linear regression lines showed a different slope than postoperative regression lines. Corrected pRNFL thickness measurements of before cataract surgery differed significantly with pRNFL thickness measurements after cataract surgery. CONCLUSIONS: The presence of cataract influences the QF-pRNFL relationship. The lower the image QF, the higher the pRNFL thickness underestimation. We found a rather curvilinear relationship between QF and pRNFL. Our corrected measurements of the pRNFL thickness in case of lower image QF due to cataract still differed significantly from the pRNFL thickness measurements after cataract surgery.

Retinal neurodegeneration may precede microvascular changes characteristic of diabetic retinopathy in diabetes mellitus.

Diabetic retinopathy (DR) has long been recognized as a microvasculopathy, but retinal diabetic neuropathy (RDN), characterized by inner retinal neurodegeneration, also occurs in people with diabetes mellitus (DM). We report that in 45 people with DM and no to minimal DR there was significant, progressive loss of the nerve fiber layer (NFL) (0.25 µm/y) and the ganglion cell (GC)/inner plexiform layer (0.29 µm/y) on optical coherence tomography analysis (OCT) over a 4-y period, independent of glycated hemoglobin, age, and sex. The NFL was significantly thinner (17.3 µm) in the eyes of six donors with DM than in the eyes of six similarly aged control donors (30.4 µm), although retinal capillary density did not differ in the two groups. We confirmed significant, progressive inner retinal thinning in streptozotocin-induced "type 1" and B6.BKS(D)-Lepr(db)/J "type 2" diabetic mouse models on OCT; immunohistochemistry in type 1 mice showed GC loss but no difference in pericyte density or acellular capillaries. The results suggest that RDN may precede the established clinical and morphometric vascular changes caused by DM and represent a paradigm shift in our understanding of ocular diabetic complications.

Optical density filters modeling media opacities cause decreased SD-OCT retinal layer thickness measurements with inter- and intra-individual variation.

PURPOSE: To assess the effect of media opacities on thickness measurements of the peripapillary retinal nerve fibre layer (pRNFL) and macular inner retinal layer (mIRL) performed with spectral-domain optical coherence tomography (SD-OCT) using a set of filters with known optical density. METHODS: Spectral-domain optical coherence tomography volume scans of the optic disc and the macular area were performed in 18 healthy volunteers, using Topcon-3DOCT-1000 Mark II. A set of five filters with optical density ranging from 0.04 to 0.69 was used. The correlation was calculated between the percentage change in thickness measurements (%ΔpRNFL and %ΔmIRL) and the change in optical density. All scans and measurements were performed in duplicate by one operator. RESULTS: Eighteen right eyes of 18 healthy volunteers were included in this study. Percentage decrease in pRNFL and mIRL thickness correlated with change in optical density (Spearman's rho r = 0.82; p < 0.001 and r = 0.89; p < 0.001, respectively). The measured decrease in pRNFL thickness differed from the decrease in mIRL thickness, not only between individuals, but also within the same individual. CONCLUSIONS: Optical coherence tomography thickness measurements of both pRNFL and mIRL are influenced by image degradation caused by optical density filters as a model for media opacities. An underestimation of the thickness of these layers was observed, caused by a shift of retinal layer boundary placement due to image quality loss. This underestimation is not the same for each individual and also differed between the pRNFL and mIRL thickness measurements. These individual and interindividual differences demonstrate that an individual approach will be necessary to correct for this underestimation per layer.

Anomalous relation between axial length and retinal thickness in amblyopic children.

PURPOSE: To investigate the relationship between retinal thickness and axial length in amblyopic eyes compared to healthy eyes. METHODS: In this observational, transversal study, 36 amblyopic children and 30 healthy controls underwent full ophthalmological and orthoptic examinations, volume scanning of the macula with spectral domain optical coherence tomography (3D OCT-1000; Topcon Corporation, Tokyo, Japan), and measuring of axial length using the IOLMaster (Carl Zeiss Meditec AG, Jena, Germany). The average pericentral retinal thickness was calculated. RESULTS: A strong correlation was observed between the axial lengths of both eyes in the control group (R = 0.98, P < 0.01) and between the axial lengths of the amblyopic and fellow eye in the amblyopic group (R = 0.77, P < 0.01); the amblyopic and their fellow eyes were significantly shorter than the nonamblyopic control eyes. The pericentral retinal thickness of both eyes of an individual is highly correlated in nonamblyopic controls (R = 0.92, P < 0.01) and in amblyopic children (R = 0.82, P < 0.01). There is no significant difference in mean pericentral retinal thickness between healthy, amblyopic, and fellow eyes. In healthy eyes a moderate inverse correlation exists between axial length and pericentral retinal thickness (R = -0.41, P = 0.02); this relationship was not found in the amblyopic eyes or the normal fellow eye. CONCLUSIONS: In this patient cohort, there was an anomalous relation between the axial length and the pericentral retinal thickness in both amblyopic and their fellow eyes.

The relationship between the optical density of cataract and its influence on retinal nerve fibre layer thickness measured with spectral domain optical coherence tomography.

PURPOSE: The purpose of this study was to model the influence of cataract on Spectral Domain Optical Coherence Tomography (SDOCT) image quality and Retinal Nerve Fibre Layer (RNFL) thickness measurements. METHODS: SDOCT images, made with two different devices (3DOCT-1000, Topcon and Cirrus HD-OCT), before and after cataract surgery were compared and judged against measurements from normal subjects using artificial filters simulating the effects of cataract. Optical density of the images was calculated based on a mathematical model described previously. RESULTS: In total, forty-eight eyes were included for pre- and postoperative cataract extraction measurements. OCT image quality significantly (p < 0.001) improved postoperative and postoperative RNFL thickness was significantly (p < 0.001) thicker in both groups of patients. The measurements using artificial filters showed a rather precise linear relation between change in filter induced optical density and change in RNFL thickness (R = 0.941, p < 0.001 for 3DOCT-1000 and R = 0.785, p < 0.001 for Cirrus HD-OCT). For the patient groups, the relation was less marked, 3DOCT-1000 Rs = 0.697, p < 0.03 and Cirrus HD-OCT Rs = 0.444, p < 0.03. The predictive potential based on the found linear relationship between OCT-effective optical density of cataract and the cataract-induced underestimation was however limited, and mean difference ± SD between predicted and measured RNFL thickness were 1.68 ± 7.55 (3DOCT-1000) and 3.71 ± 2.97 (Cirrus HD-OCT) micron. CONCLUSIONS: A linear relationship exists between OCT-effective optical density of cataract and underestimation of RNFL thickness measured with OCT. This finding holds promise to correct for cataract-induced changes in RNFL measurements, but will differ for each type of OCT device.

Variability in photocoagulation treatment of diabetic macular oedema.

PURPOSE: To establish whether differences in the assessment of diabetic macular oedema (DME) with either optical coherence tomography (OCT) or stereoscopic biomicroscopy lead to variability in the photocoagulation treatment of DME. METHODS: The differences in the assessment of DME with either OCT or stereoscopic biomicroscopy were analysed by calculating the surface areas and the overlap of retinal thickening. Photocoagulation treatment plans of retinal specialists were compared by evaluating the number and location of planned laser spots. RESULTS: The threshold for and dosage of photocoagulation differ depending upon whether the basis of retinal thickness diagnosis is clinical observation or OCT. The overlap in laser spot location based on the assessment of DME with OCT or biomicroscopy averages 51%. Among retinal specialists, the treatment plans differed in the laser spot count by six- to 11-fold. CONCLUSION: Diabetic macular oedema photocoagulation treatment threshold and dosage of laser spots differ depending on whether thickness assessments are based on stereoscopic slit-lamp biomicroscopy or OCT. In addition, retinal specialists differed in the number and placement of planned laser spots even when given identical information concerning DME and treatable lesions. This variability in the photocoagulation treatment of DME could lead to differences in patient outcome and laser study results.

Early neurodegeneration in the retina of type 2 diabetic patients.

PURPOSE: The purpose of this study was to determine whether diabetes type 2 causes thinning of retinal layers as a sign of neurodegeneration and to investigate the possible relationship between this thinning and duration of diabetes mellitus, diabetic retinopathy (DR) status, age, sex, and glycemic control (HbA1c). METHODS: Mean layer thickness was calculated for retinal layers following automated segmentation of spectral domain optical coherence tomography images of diabetic patients with no or minimal DR and compared with controls. To determine the relationship between layer thickness and diabetes duration, DR status, age, sex, and HbA1c, a multiple linear regression analysis was used. RESULTS: In the pericentral area of the macula, the retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), and inner plexiform layer (IPL) were thinner in patients with minimal DR compared to controls (respective difference 1.9 µm, 95% confidence interval [CI] 0.3-3.5 µm; 5.2 µm, 95% CI 1.0-9.3 µm; 4.5 µm, 95% CI 2.2-6.7 µm). In the peripheral area of the macula, the RNFL and IPL were thinner in patients with minimal DR compared to controls (respective difference 3.2 µm, 95% CI 0.1-6.4 µm; 3.3 µm, 95% CI 1.2-5.4 µm). Multiple linear regression analysis showed DR status to be the only significant explanatory variable (R = 0.31, P = 0.03) for this retinal thinning. CONCLUSIONS: This study demonstrated thinner inner retinal layers in the macula of type 2 diabetic patients with minimal DR than in controls. These results support the concept that early DR includes a neurodegenerative component.

Heartbeat-induced axial motion artifacts in optical coherence tomography measurements of the retina.

PURPOSE: To investigate the cause of axial eye motion artifacts that occur in optical coherence tomography (OCT) imaging of the retina. Understanding the cause of these motions can lead to improved OCT image quality and therefore better diagnoses. METHODS: Twenty-seven measurements were performed on 5 subjects. Spectral domain OCT images at the macula were collected over periods up to 30 seconds. The axial shift of every average A-scan was calculated with respect to the previous average A-scan by calculating the cross-correlation. The frequency spectrum of the calculated shifts versus time was determined. The heart rate was determined from blood pressure measurements at the finger using an optical blood pressure detector. The fundamental frequency and higher order harmonics of the axial OCT shift were compared with the frequency spectrum of blood pressure data. In addition, simultaneous registration of the movement of the cornea and the retina was performed with a dual reference arm OCT setup, and movements of the head were also analyzed. RESULTS: A correlation of 0.90 was found between the fundamental frequency in the axial OCT shift and the heart rate. Cornea and retina move simultaneously in the axial direction. The entire head moves with the same amplitude as the retina. CONCLUSIONS: Axial motion artifacts during OCT volume scanning of the retina are caused by movements of the whole head induced by the heartbeat.

Association of visual function and ganglion cell layer thickness in patients with diabetes mellitus type 1 and no or minimal diabetic retinopathy.

Diabetic retinopathy (DR) classically presents with micro-aneurysms, small haemorrhages and/or lipoprotein exudates. Several studies have indicated that neural loss occurs in DR even before vascular damage can be observed. This study evaluated the possible relationship between structure (spectral domain-optical coherence tomography) and function (Rarebit visual field test) in patients with type 1 diabetes mellitus and no or minimal diabetic retinopathy (DR). Results demonstrated loss of macular visual function and corresponding thinning of the ganglion cell layer (GCL) in the pericentral area of the macula of diabetic patients (Rs = 0.65, p < 0.001). In multivariable logistic regression analysis, GCL thickness remained an independent predictor of decreased visual function (OR 1.5, 95% CI 1.1-2.1). Early DR seems to include a neurodegenerative component.

Decreased retinal ganglion cell layer thickness in patients with type 1 diabetes.

PURPOSE. To determine which retinal layers are most affected by diabetes and contribute to thinning of the inner retina and to investigate the relationship between retinal layer thickness (LT) and diabetes duration, diabetic retinopathy (DR) status, age, glycosylated hemoglobin (HbA1c), and the sex of the individual, in patients with type 1 diabetes who have no or minimal DR. METHODS. Mean LT was calculated for the individual retinal layers after automated segmentation of spectral domain-optical coherence tomography scans of patients with diabetes and compared with that in control subjects. Multiple linear regression analysis was used to determine the relationship between LT and HbA1c, age, sex, diabetes duration, and DR status. RESULTS. In patients with minimal DR, the mean ganglion cell layer (GCL) in the pericentral area was 5.1 mum thinner (95% confidence interval [CI], 1.1-9.1 mum), and in the peripheral macula, the mean retinal nerve fiber layer (RNFL) was 3.7 mum thinner (95% CI, 1.3-6.1 mum) than in the control subjects. There was a significant linear correlation (R = 0.53, P < 0.01) between GCL thickness and diabetes duration in the pooled group of patients. Multiple linear regression analysis (R = 0.62, P < 0.01) showed that DR status was the most important explanatory variable. CONCLUSIONS. This study demonstrates GCL thinning in the pericentral area and corresponding loss of RNFL thickness in the peripheral macula in patients with type 1 diabetes and no or minimal DR compared with control subjects. These results support the concept that diabetes has an early neurodegenerative effect on the retina, which occurs even though the vascular component of DR is minimal.

Selective loss of inner retinal layer thickness in type 1 diabetic patients with minimal diabetic retinopathy.

PURPOSE: To determine whether type 1 diabetes preferentially affects the inner retinal layers by comparing the thickness of six retinal layers in type 1 diabetic patients who have no or minimal diabetic retinopathy (DR) with those of age- and sex-matched healthy controls. METHODS: Fifty-seven patients with type 1 diabetes with no (n = 32) or minimal (n = 25) DR underwent full ophthalmic examination, stereoscopic fundus photography, and optical coherence tomography (OCT). After automated segmentation of intraretinal layers of the OCT images, mean thickness was calculated for six layers of the retina in the fovea, the pericentral area, and the peripheral area of the central macula and were compared with those of an age- and sex-matched control group. RESULTS: In patients with minimal DR, the mean ganglion cell/inner plexiform layer was 2.7 microm thinner (95% confidence interval [CI], 2.1-4.3 microm) and the mean inner nuclear layer was 1.1 microm thinner (95% CI, 0.1-2.1 microm) in the pericentral area of the central macula compared to those of age-matched controls. In the peripheral area, the mean ganglion cell/inner plexiform layer remained significantly thinner. No other layers showed a significant difference. CONCLUSIONS: Thinning of the total retina in type 1 diabetic patients with minimal retinopathy compared with healthy controls is attributed to a selective thinning of inner retinal layers and supports the concept that early DR includes a neurodegenerative component.

A model for the effect of disturbances in the optical media on the OCT image quality.

PURPOSE: The loss of quality of optical coherence tomography (OCT) images resulting from disturbances in the optical media has been modeled. METHODS: OCT measurements were performed in two healthy volunteers using time domain (TD)-OCT (StratusOCT; Carl Zeiss Meditec, Dublin, CA). Optical disturbances were approached in three ways simulated with filters. The studied effects were: light attenuation (absorptive and reflective filters), refractive aberrations (defocusing lenses), and light scattering/straylight (scattering filters). The same examiner scanned the subjects with the filters placed in front of the eye. The signal strength (SS) values of the scans were then collected. The strength of the filters were expressed in optical density (OD), determined for the 830 nm central wavelength of the OCT, (OD(lambda=830)). RESULTS: A linear relationship has been found between the OD(lambda=830) of the absorptive and reflective filters and the SS of the corresponding OCT images. Assuming that reduction of light from the OCT scanning spot on the retina is the critical factor, this light loss was determined for the scattering filters and defocusing lenses. A comparable linear relationship was found between the SS value and the OD(lambda=830) of these filters. CONCLUSIONS: The model indicates that the loss of OCT image quality in patients with disturbances in the optical media is explained by attenuation of the light in the OCT scanning spot on the retina. A linear relationship between the SS and the single pass logarithmic attenuation of the OCT signal is shown, according to SS=constant-(9.9 [-9.4 to -10.6] x OD(lambda=830)).

A new and validated CT-based method for the calculation of orbital soft tissue volumes.

PURPOSE: There is no consensus as how to calculate orbital soft tissue volume based on CT or MRI scans. The authors sought to validate their technique and to assess the intraobserver and interobserver variability of their calculations of bony orbital volume (OV), orbital fat volume (FV), and extraocular muscle volume (MV) on CT scans of humans. METHODS: The authors calculated these volumes with the use of a manual segmentation technique on CT scans with commercially available software. Two observers (one of them masked) calculated the orbital soft tissue volumes in a CT scan of a phantom constructed of dry skull, butter, and chicken muscle. These calculations were compared with previously taken standard volume measurements of these materials. Repetitive calculations on one CT scan by the same observer were compared. Soft tissue volumes taken from 10 orbital CT scans were calculated by two observers and compared. From the data acquired, intraobserver and interobserver variability was calculated. RESULTS: Outcomes of these calculations using this software approximated the volumes of the phantom measured with standardized techniques. Accuracy of the phantom calculations between the two observers varied from +0.7% to -0.7% for FV and between -1.5% and -2.2% for MV. Mean differences between the repeated calculations were smaller than 5%. The intraclass correlation coefficient varied from 0.961 to 0.999. CONCLUSIONS: Calculating orbital soft tissue volume using a manual segmentation technique for CT scans is a reliable and accurate tool.