Vascular response of the bulbar conjunctiva to diabetes and elevated blood pressure

Division of Optometry and Visual Science, City University London, Londinium, England, United Kingdom
Ophthalmology (Impact Factor: 5.56). 10/2005; 112(10):1801-8. DOI: 10.1016/j.ophtha.2005.04.030
Source: PubMed

ABSTRACT Retinovascular changes associated with diabetes have been clearly documented; changes in vessels of the conjunctiva are less well described. We examined changes in conjunctival vessel morphologic features in participants with and without diabetes.
Case-control study.
Fifty-three patients with diabetes (17 with type 1 diabetes, 36 with type 2 diabetes) and 60 controls (all aged 20-94 years).
Digital red-free conjunctival images were captured and an automated computer algorithm was used to derive indices that describe the morphologic features of vessels of the conjunctiva. Percentage differences in vessel indices were adjusted for age, gender, blood pressure, and smoking status.
Mean vessel diameter (micrometers) and vessel density (square millimeters of vessel per square centimeter of bulbar conjunctiva).
A strong positive association between the duration of diabetes and overall mean vessel width was observed (P<0.001), resulting from changes in larger vessels (>80 mum in width). Conversely, the duration of diabetes showed a strong inverse association with vessel area (P<0.001) that appeared to be driven by the trend observed in smaller vessels (<40 mum in width). A 25% reduction (95% confidence interval [CI], -35% to -13%; P<0.001) in vessel density in those with type 1 diabetes and a 14% reduction (95% CI, -24% to -3%; P = 0.016) in those with type 2 diabetes, compared with controls, was observed. Mean vessel widths were 11% (95% CI, 4%-17%; P = 0.001) wider in type 1 and 5% (95% CI, 0%-10%; P = 0.073) wider in those with type 2 diabetes compared with controls. The difference in magnitude of effect for type 1 and type 2 diabetes compared with controls was explained by duration of diabetes. Grade of diabetic retinopathy and elevated blood pressure showed similar but less strong associations with vessel indices.
Loss of capillaries and macrovessel dilation in the conjunctiva associated with diabetes compares with well-known vessel changes in the retina. Associations between morphologic changes in the conjunctiva and elevated blood pressure were similar but less strong; this may show that diabetic angiopathy predominates in those with both diabetes and elevated blood pressure.

1 Bookmark
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Purpose. To evaluate potential risk factors for developing tube shunt exposure in glaucoma patients. Patients and Methods. Forty-one cases from 41 patients that had tube shunt exposure from 1996 to 2005 were identified from the Robert Cizik Eye Clinic and Bascom Palmer Eye Institute. Each case was matched with 2 controls of the same gender and with tube shunts implanted within 6 months of the index case. Conditional logistic regression was used to determine risk factors. Results. The study cohort includes a total of 121 eyes from 121 patients. The mean age was 63.6 ± 19.7 years, ranging from 1 to 96 years. The average time to exposure was 19.29 ± 23.75 months (range 0.36-85.74 months). Risk factors associated with tube exposure were Hispanic ethnicity (P = 0.0115; OR = 3.6; 95% CI, 1.3-9.7), neovascular glaucoma (P = 0.0064; OR = 28.5; 95% CI, 2.6-316.9), previous trabeculectomy (P = 0.0070; OR = 5.3; 95% CI, 1.6-17.7), and combined surgery (P = 0.0381; OR = 3.7; 95% CI, 1.1-12.7). Conclusions. Hispanic ethnicity, neovascular glaucoma, previous trabeculectomy, and combined surgery were identified as potential risk factors for tube shunt exposure. These potential risk factors should be considered when determining the indication for performing tube shunt implantation and the frequency of long-term followup.
    Journal of Ophthalmology 01/2013; 2013:196215. DOI:10.1155/2013/196215 · 1.94 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Biometrics is the science of recognizing people based on their physical or behavioral traits such as face, fingerprints, iris, and voice. Among these characteristics, ocular biometrics has gained popularity due to the significant progress made in iris recognition. However, iris recognition is unfavorably influenced by the non-frontal gaze direction of the eye with respect to the acquisition device. In such scenarios, additional parts of the eye, such as the sclera (the white of the eye) may be of significance. In this article, we investigate the use of the sclera texture and vasculature patterns evident in the sclera as a potential biometric. Iris patterns are better discerned in the near infrared spectrum (NIR) while vasculature patterns are better discerned in the visible spectrum (RGB). Therefore, multispectral images of the eye, consisting of both NIR and RGB channels, are used in this work in order to ensure that both the iris and the vasculature patterns are imaged. The contributions of this work include: (a) the assembling of a multispectral eye database to initiate research on this topic; (b) the design of a novel algorithm for sclera segmentation based on a normalized sclera index measure; and (c) the evaluation of three different feature extraction and matching schemes on the assembled database in order to examine the potential of utilizing the sclera and the accompanying vasculature pattern as biometric cues. Experimental results convey the potential of this biometric in an ocular-based recognition system.
    Pattern Recognition Letters 10/2012; 33(14):1860–1869. DOI:10.1016/j.patrec.2011.11.006 · 1.06 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents an approach to extract curvilinear structures (lines) and their widths from two-dimensional images with high accuracy. Models for asymmetric parabolic and Gaussian line profiles are proposed. These types of lines occur frequently in applications. Scale-space descriptions of parabolic and Gaussian lines are derived in closed form. A detailed analysis of these scale-space descriptions shows that parabolic and Gaussian lines are biased more significantly than the well-known asymmetric bar-shaped lines by the partial derivatives of the Gaussian filters that are used to extract the lines. A bias function is constructed that relates the parameters of the lines to biased measurements that can be extracted from the image. It is shown that this bias function can be inverted. This is used to derive an algorithm to remove the bias from the line positions and widths. Examples on synthetic and real images show the high subpixel accuracy that can be achieved with the proposed algorithm. In particular, the line extractor is tested on a publicly available data set that includes manually labeled ground truth. The results on this data set show that very accurate results can be achieved on real data if the appropriate line model is used.
    Computer Vision and Image Understanding 02/2013; 117(2):97–112. DOI:10.1016/j.cviu.2012.08.007 · 1.36 Impact Factor

Full-text (2 Sources)

Available from
Oct 13, 2014