METHODS: Twenty-seven right eyes (24 females and 3 males) of 27 myopic schoolchildren aged between 13 and 15 years were included in this study. The measurements of central refraction, peripheral refraction (between 35° temporal and 35° nasal visual field in 5° steps), and lag of accommodation were conducted using the Grand-Seiko WR-5100K open-field autorefractometer initially without correction (WC), followed by with correction using four different addition powers of Proclear® multifocal D-Design contact lens in random sequence. Axial length was measured using a handheld probe ultrasound A-scan (Tomey AL-2000).
RESULTS: The relative peripheral refractive error showed high hyperopic defocus of +1.08 ± 1.24 D at 35° nasal and +1.06 ± 1.06 D at 35° temporal visual field WC. All Proclear multifocal contact lenses (MFCLs) decreased the peripheral hyperopic defocus with increasing addition powers (F [2.938, 47.001] = 13.317, P < 0.001). However, only +3.00 D addition and +3.50 D addition (P = 0.001) could invert the peripheral hyperopic defocus into peripheral myopic defocus. Apart from that, the +3.00 D addition lens showed the lowest lag of accommodation (+1.10 ± 0.83 D) among the other MFCL adds (P = 0.002).
CONCLUSION: A +3.00 D addition Proclear MFCL is the optimal addition power that can invert the pattern of peripheral hyperopic defocus into myopic defocus.
METHODS: A prospective study was carried out on 32 healthy subjects (control group) and 60 diabetic patients. The diabetic patients were divided into 2 groups. Group 1 comprised of 30 patients without diabetic retinopathy (DR) and group 2 had 30 patients with mild non-proliferative DR. A full-threshold microperimetry of the central 10° of retina (the macula) was performed on all subjects, utilizing 32 points with the MP-1. The relationship between light sensitivity and HbA1c value was calculated using linear regression analysis.
RESULTS: Total mean sensitivity at 10° for group 1 without DR, group 2 with mild NPDR and control group were 18.67±0.83, 17.98±1.42 and 19.45±0.34 (dB), respectively. There was a significant difference in total mean retinal sensitivity at 10° between the 3 groups (F(2,89)=18.14, p=0.001). A simple linear regression was calculated to predict HbA1c based on retinal sensitivity. A significant regression equation was found (F(1,90)=107.61, p=0.0001, with an R2 of 0.545). The linear regression analysis revealed that there was a 0.64dB decline in mean retinal sensitivity within the central 10° diameter with an increase of 1mmHg of HbA1c.
CONCLUSION: Retinal sensitivity at the central 10° of the macula is affected by changes in HbA1c values.
METHODS: Thirty nine eyes of 39 new keratoconus patients were selected and randomly fitted with two types of RGP contact lenses. Group 1 had 21 eyes with regular rigid gas-permeable (RRGP) contact lens and rest 18 eyes were in group 2 with specially designed rigid gas-permeable (SRGP) contact lens. Corneal cell morphology was evaluated using a slit scanning confocal microscope at no-lens wear and after 1y of contact lens wearing.
RESULTS: After 1y of contact lens wearing in group 1, the mean anterior and posterior stromal keratocyte density were significantly less (P=0.006 and P=0.001, respectively) compared to no-lens wear. The mean cell area of anterior and posterior stromal keratocyte were also significantly different (P=0.005 and P=0.001) from no-lens wear. The anterior and posterior stromal haze increased by 18.74% and 23.81%, respectively after 1y of contact lens wearing. Whereas in group 2, statistically significant changes were observed only in cell density & area of anterior stroma (P=0.001 and P=0.001, respectively) after 1y. While, level of anterior and posterior stromal haze increased by 16.67% and 11.11% after 1y of contact lens wearing. Polymegathism and pleomorphism also increased after 1y of contact lens wearing in both the contact lens groups.
CONCLUSION: Confocal microscopy observation shows the significant alterations in corneal cell morphology of keratoconic corneas wearing contact lenses especially in group 1. The type of contact lens must be carefully selected to minimize changes in corneal cell morphology.
METHODS: A cross-sectional study was conducted to evaluate the corneal cell morphology of 47 keratoconus patients and 32 healthy eyes without any ocular disease. New keratoconus patients with different disease severities and without any other ocular co-morbidity were recruited from the ophthalmology department of a public hospital in Malaysia from June 2013 to May 2014. Corneal cell morphology was evaluated using an in vivo slit-scanning confocal microscope. Qualitative and quantitative data were analysed using a grading scale and the Nidek Advanced Visual Information System software, respectively.
RESULTS: The corneal cell morphology of patients with keratoconus was significantly different from that of healthy eyes except in endothelial cell density (P = 0.072). In the keratoconus group, increased level of stromal haze, alterations such as the elongation of keratocyte nuclei and clustering of cells at the anterior stroma, and dark bands in the posterior stroma were observed with increased severity of the disease. The mean anterior and posterior stromal keratocyte densities and cell areas among the different stages of keratoconus were significantly different (P < 0.001 and P = 0.044, respectively). However, the changes observed in the endothelium were not significantly different (P > 0.05) among the three stages of keratoconus.
CONCLUSION: Confocal microscopy observation showed significant changes in corneal cell morphology in keratoconic cornea from normal healthy cornea. Analysis also showed significant changes in different severities of keratoconus. Understanding the corneal cell morphology changes in keratoconus may help in the long-term monitoring and management of keratoconus.
METHODS: The pterygium screening system was tested on two normal eye databases (UBIRIS and MILES) and two pterygium databases (Australia Pterygium and Brazil Pterygium). This system comprises four modules: (i) a preprocessing module to enhance the pterygium tissue using HSV-Sigmoid; (ii) a segmentation module to differentiate the corneal region and the pterygium tissue; (iii) a feature extraction module to extract corneal features using circularity ratio, Haralick's circularity, eccentricity, and solidity; and (iv) a classification module to identify the presence or absence of pterygium. System performance was evaluated using support vector machine (SVM) and artificial neural network.
RESULTS: The three-step frame differencing technique was introduced in the corneal segmentation module. The output image successfully covered the region of interest with an average accuracy of 0.9127. The performance of the proposed system using SVM provided the most promising results of 88.7%, 88.3%, and 95.6% for sensitivity, specificity, and area under the curve, respectively.
CONCLUSION: A basic platform for computer-aided pterygium screening was successfully developed using the proposed modules. The proposed system can classify pterygium and non-pterygium cases reasonably well. In our future work, a standard grading system will be developed to identify the severity of pterygium cases. This system is expected to increase the awareness of communities in rural areas on pterygium.