Pauline H. B. Kok

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.

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.

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.

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.

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.

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.

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)).

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

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.

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.

Standardised disturbance of the optical coherence tomography signal has varying effects on the scan quality assessment when comparing four devices

Optical coherence tomography (OCT) has become a successful application in ophthalmology. Time-domain OCT (Stratus, Carl Zeiss Meditec) has been overtaken by spectral-domain OCT (SDOCT) which has major advances in imaging speed, sensitivity and image resolution.1 ,2 Several SDOCT devices are commercially available. In this small study, we assessed the change in subjective image quality and image quality parameter (IQP) provided by four different SDOCT devices using artificial filters simulating optical eye media disturbances. In four healthy subjects, single non-averaged B-scans of the macula were acquired using four commercially available SDOCT systems: 1. 3D OCT-1000 MarkII (Topcon Medical Systems, Inc, Oakland, New Jersey, USA): Software V.3.21, 27.000 A-scans per second, superluminescent diode 840 nm light source, 5–6 micron axial resolution, ‘Q-factor’ IQP scale 0–100. 2. Cirrus HD-OCT (Carl Zeiss Meditec, Dublin, California, USA): Software V.2.0, 27.000 A-scans per second, superluminescent diode 840 nm light source, 5 micron axial resolution, ‘Signal Strength’ IQP scale 0–10. 3. RTVue OCT (Optovue, Inc, Fremont, California, …