Retinal Ganglion Cell Complex Changes Using Spectral Domain Optical Coherence Tomography in Diabetic Patients Without Retinopathy
Retinal Ganglion Cell Complex Changes Using Spectral Domain Optical Coherence Tomography in Diabetic Patients Without Retinopathy
Neuroretinal damage in diabetes produces functional abnormalities such as the loss of chromatic discrimination,contrast sensitivity and dark adaptation. These alterations can be detected by means of electrophysiological studies in diabetic patients with diabetes duration of less than two years, i.e. before microvascular lesions can be detected in ophthalmologic examination. Neurodegeneration seems to be a generalized process that occurs throughout the macula and is not confined to local abnormalities, in the cases with visible signs of retinopathy.
The debate is still open as to whether diabetic retinal neuropathy is the effect of vascular diabetic retinopathy or is primarily caused by direct neurologic damage from chronic hyperglycemia. The hypothesis that diabetes causes retinal neuro-pathy independent of retinopathy is intriguing and potentially links retinal neuropathy to other diabetic neuropathies.
Neuroretinal degeneration initiates and/or activates several metabolic and signalling pathways which participates in the microangiopathic process as well as in the disruption of the blood-retinal barrier which is a crucial element in the pathogenesis of diabetic retinopathy.
Retinal ganglion cells are the earliest cells affected and have the highest rate of apoptosis. However, an elevated rate of apoptosis has been also observed in the outer nuclear layer (photoreceptors) and in the retinal pigment epithelium (RPE). The use of spectral domain OCT (SD-OCT) makes it possible to measure the thickness of individual layers at higher resolution and indicates that the thinning of the inner retina in the macula is primarily due to loss of ganglion cells.
This was a prospective case-control study conducted from October 2012 to April 2013 at Kasr Al-ainy hospital- cairo university.
The subjects were divided into two groups; Group 1 consists of diabetic patients free from diabetic retinopathy (45 eyes). Group 2 consists of non-diabetic subjects, free from any ocular pathology(21 eyes).
All subjects were subjected to full medical and ophthalmological history, refraction, best corrected visual acuity (according to the snellen visual acuity chart and recorded in decimals), slit lamp examination (including measuring the intraocular pressure by Goldman applanation tonometer), dilated fundus examination by binocular indirect slit-lamp biomicroscopy and measuring of the retinal ganglion cell complex (GCC) thickness and the central foveal thickness (CFT) using the RTVue® SD-OCT (Optovue, Inc.) at the LASER unit, Kasr Al-ainy hospital.
In addition; diabetic patients were subjected to fundus fluorescein angiography to exclude diabetic changes that could be missed on clinical examination and measuring level of HbA1C in blood at kasr Al-ainy hospital chemical pathology unit.
Mapping of the GCC using the RTVue GCC scan consists of 15 vertical line scans covering a 7mm square region. The GCC scan centers at 1mm temporal to fovea center for better coverage of the temporal region.
The GCC thickness values are analyzed and compared to an extensive age-matched normative database. If the patient's values are outside the normal range, the measurement is color-coded appropriately. The Deviation Map shows the percent loss from normal as determined by the normative database. The significance Map shows regions where the change from normal reaches statistical significance. (Figure 1) Focal Loss Volume (FLV) and Global Loss Volume (GLV) are two parameters that provide quantitative measures for the amount of significant GCC loss. GLV measures the average amount of GCC loss over the entire GCC map. FLV measures the average amount of focal loss over the entire GCC map, it is the total sum of significant GCC loss (in volume) divided by the map area. As such it provides a percent of significant tissue loss for volume. FLV detects focal loss using a pattern deviation map to correct for overall absolute changes [5].
Statistical analysis included comparison of numerical variables between the study groups was done using Student t test for independent samples in normally distributed data and Mann Whitney U test for independent samples in non-normal data. For comparing categorical data, Chi square (2) test was performed. Exact test was used instead when the expected frequency is less than 5. Within group comparison between superior and inferior GCC was done using McNemar test. Agreement was tested using kappa statistic. Correlation between various variables was done using Spearman rank correlation equation. All statistical calculations were done using computer programs SPSS (Statistical Package for the Social Science; SPSS Inc., Chicago, IL, USA) version 15 for Microsoft Windows.
Inclusion Criteria:
Exclusion criteria included;