Search

Purpose: To evaluate and compare the temporal changes in pulse waveform parameters of ocular blood flow (OBF) between non-habitual and habitual groups due to caffeine intake., Method: This study was conducted on 19 healthy subjects (non-habitual 8; habitual 11), non-smoking and between 21 and 30 years of age. Using laser speckle flowgraphy (LSFG), three areas of optical nerve head were analyzed which are vessel, tissue, and overall, each with ten pulse waveform parameters, namely mean blur rate (MBR), fluctuation, skew, blowout score (BOS), blowout time (BOT), rising rate, falling rate, flow acceleration index (FAI), acceleration time index (ATI), and resistive index (RI). Two-way mixed ANOVA was used to determine the difference between every two groups where p < 0.05 is considered significant., Result: There were significant differences between the two groups in several ocular pulse waveform parameters, namely MBR (overall, vessel, tissue), BOT (overall), rising rate (overall), and falling rate (vessel), all with p < 0.05. In addition, the ocular pulse waveform parameters, i.e., MBR (overall), skew (tissue), and BOT (tissue) showed significant temporal changes within the non-habitual group, but not within the habitual group. The temporal changes in parameters MBR (vessel, tissue), skew (overall, vessel), BOT (overall, vessel), rising rate (overall), falling rate (overall, vessel), and FAI (tissue) were significant for both groups (habitual and non-habitual) in response to caffeine intake., Conclusion: The experiment results demonstrated caffeine does modulate OBF significantly and response differently in non-habitual and habitual groups. Among all ten parameters, MBR and BOT were identified as the suitable biomarkers to differentiate between the two groups.

We describe a computer-aided measuring tool, named parapapillary atrophy and optic disc region assessment (PANDORA), for automated detection and quantification of both the parapapillary atrophy (PPA) and the optic disc (OD) regions in two-dimensional color retinal fundus images. The OD region is segmented using a combination of edge detection and ellipse fitting methods. The PPA region is identified by the presence of bright pixels in the temporal zone of the OD, and it is segmented using a sequence of techniques, including a modified Chan-Vese approach, thresholding, scanning filter, and multiseed region growing. PANDORA has been tested with 133 color retinal images (82 with PPA; 51 without PPA) drawn randomly from the Lothian Birth Cohort (LBC) database, together with a "ground truth" estimate from an ophthalmologist. The PPA detection rate is 89.47% with a sensitivity of 0.83 and a specificity of 1. The mean accuracy in defining the OD region is 81.31% (SD=10.45) when PPA is present and 95.32% (SD=4.36) when PPA is absent. The mean accuracy in defining the PPA region is 73.57% (SD=11.62). PANDORA demonstrates for the first time how to quantify the OD and PPA regions using two-dimensional fundus images, enabling ophthalmologists to study ocular diseases related to PPA using a standard fundus camera.

Purpose: A computer-aided measuring tool was devised to automatically detect and quantify both the parapapillary atrophy (PPA) and the optic disc (OD) regions in two-dimensional color fundus images of the retina., Methods: The OD region was segmented using the Chan-Vese model with a shape restraint. This region was then removed from the image (OD+PPA), which was cropped in a modified Chan-Vese approach, producing a first-order estimation of the PPA region. Its boundary is subsequently refined by using thresholding, a scanning filter, and multiseed region-growing methods. Dual channels (blue and red) in the red-green-blue space are used to minimize the interference effects of blood vessels and artifacts., Results: The software was tested on 94 randomly selected images of eyes with PPA from 66 subjects of a well-characterized cohort database. Our proposed algorithm achieved a mean accuracy level of 93.8% (SD 5.26) and 94.0% (SD 5.88) in estimating the size of the PPA and OD respectively, compared with the ground estimate defined by an ophthalmologist. In terms of correlation between the data of the ground estimate and our estimation, we obtained a correlation coefficient of 0.98 for both the PPA and the OD., Conclusions: This software offers a means of quantifying the size of PPA on two-dimensional fundus images for the first time. The proposed algorithm is capable of detecting and quantifying PPA and OD regions repeatedly, with a mean accuracy of >93%, and could also provide additional information, such as the transverse and conjugate diameter of OD, which may be useful in eye-screening.