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Purpose

Glaucoma leads to pathological loss of axons in the retinal nerve fibre layer at the optic nerve head (ONH). This study aimed to develop a strategy for the estimation of the cross-sectional area of the axons in the ONH. Furthermore, improving the estimation of the thickness of the nerve fibre layer, as compared to a method previously published by us.

Methods

In the 3D-OCT image of the ONH, the central limit of the pigment epithelium and the inner limit of the retina, respectively, were identified with deep learning algorithms. The minimal distance was estimated at equidistant angles around the circumference of the ONH. The cross-sectional area was estimated by the computational algorithm. The computational algorithm was applied on 16 non-glaucomatous subjects.

Results

The mean cross-sectional area of the waist of the nerve fibre layer in the ONH was 1.97 ± 0.19 mm². The mean difference in minimal thickness of the waist of the nerve fibre layer between our previous and the current strategies was estimated as CIμ (0.95) 0 ± 1 μm (d.f. = 15).

Conclusions

The developed algorithm demonstrated an undulating cross-sectional area of the nerve fibre layer at the ONH. Compared to studies using radial scans, our algorithm resulted in slightly higher values for cross-sectional area, taking the undulations of the nerve fibre layer at the ONH into account. The new algorithm for estimation of the thickness of the waist of the nerve fibre layer in the ONH yielded estimates of the same order as our previous algorithm.

Purposes: The aim of this study is to investigate the time evolution of active caspase 3 within first 120 h in the rat lens after in vivo exposure to subthreshold dose of UVR-B.

Methods: Twenty three six-week-old female albino Sprague-Dawley rats were exposed to subthreshold dose (1 kJ/m2) of UVR-B unilaterally and sacrificed at 24, 41, 70 and 120 h after exposure. Lenses were enucleated and active caspase 3 was detected by Western Blot. The time evolution of active caspase 3 was then plotted as a function of relative mean difference in active caspase 3 between exposed and nonexposed lenses.

Results: There is expression of active caspase 3 in both exposed and nonexposed lenses but there is no difference in relative mean difference in active caspase 3 between exposed and nonexposed lenses in all four postexposure groups.

Conclusions: Exposure to subthreshold dose of UVR-B does not induce apoptosis in the rat lens in vivo within first 120 h though there is a non-significant increase of active caspase 3 at 120 h. Increase in sample size might reduce the variation level in expression of active caspase 3 in the rat lenses.

Glaucoma is a global disease that leads to blindness due to pathological loss of retinal ganglion cell axons in the optic nerve head (ONH). The presented project aims at improving a computational algorithm for estimating the thickness and surface area of the waist of the nerve fiber layer in the ONH. Our currently developed deep learning AI algorithm meets the need for a morphometric parameter that detects glaucomatous change earlier than current clinical follow-up methods. In 3D OCT image volumes, two different AI algorithms identify the Optic nerve head Pigment epithelium Central Limit (OPCL) and the Inner limit of the Retina Closest Point (IRCP) in a 3D grid. Our computational algorithm includes the undulating surface area of the waist of the ONH, as well as waist thickness. In 16 eyes of 16 non-glaucomatous subjects aged [20;30] years, the mean difference in minimal thickness of the waist of the nerve fiber layer between our previous and the current post-processing strategies was estimated as CI mu(0.95) 0 +/- 1 mu m (D.f. 15). The mean surface area of the waist of the nerve fiber layer in the optic nerve head was 1.97 +/- 0.19 mm(2). Our computational algorithm results in slightly higher values for surface areas compared to published work, but as expected, this may be due to surface undulations of the waist being considered. Estimates of the thickness of the waist of the ONH yields estimates of the same order as our previous computational algorithm.

The present project aims at developing a fully automatic software for estimation of the waist of the nerve fiber layer in the Optic Nerve Head (ONH) angularly resolved in the frontal plane as a tool for morphometric monitoring of glaucoma. The waist of the nerve fiber layer is here defined as Pigment epithelium central limit –Inner limit of the retina – Minimal Distance, (PIMD). 3D representations of the ONH were collected with high resolution OCT in young not glaucomatous eyes and glaucomatous eyes. An improved tool for manual annotation was developed in Python. This tool was found user friendly and to provide sufficiently precise manual annotation. PIMD was automatically estimated with a software consisting of one AI model for detection of the inner limit of the retina and another AI model for localization of the Optic nerve head Pigment epithelium Central limit (OPCL). In the current project, the AI model for OPCL localization was retrained with new data manually annotated with the improved tool for manual annotation both in not glaucomatous eyes and in glaucomatous eyes. Finally, automatic annotations were compared to 3 annotations made by 3 independent annotators in an independent subset of both the not glaucomatous and the glaucomatous eyes. It was found that the fully automatic estimation of PIMD-angle overlapped the 3 manual annotators with small variation among the manual annotators. Considering interobserver variation, the improved tool for manual annotation provided less variation than our original annotation tool in not glaucomatous eyes suggesting that variation in glaucomatous eyes is due to variable pathological anatomy, difficult to annotate without error. The small relative variation in relation to the substantial overall loss of PIMD in the glaucomatous eyes compared to the not glaucomatous eyes suggests that our software for fully automatic estimation of PIMD-angle can now be implemented clinically for monitoring of glaucoma progression.

Purpose To estimate the sources of variation for Pigment epithelium central limit-Inner limit of the retina Minimal Distance averaged over 2 pi (PIMD-2 pi), and further to analyse their consequences for clinical measurements of glaucoma. Methods Forty subjects with early to moderate stage glaucoma were included. Three SD-OCT volumes of the optic nerve head (ONH) were captured at two occasions. Each volume was segmented three times for PIMD-2 pi. The magnitude of the sources of variation for PIMD-2 pi measurements was estimated with an analysis of variance. Results A 95% confidence interval for mean PIMD-2 pi was estimated to 215 +/- 12 mu m (df = 38). The estimated variance for subjects was 1280 mu m(2). The within-subject estimated variance for occasions, volumes and segmentations was 10 mu m(2), 30 mu m(2) and 40 mu m(2), respectively. The within-subject variances were used to model follow-up of PIMD-2 pi over time. A linear loss rate of 0.05 of baseline PIMD-2 pi/year was assumed. A significant PIMD-2 pi change could be detected in approximately 16-18 months with evenly spaced visits every 4 or 6 months. Conclusions Due to the small within-subject estimated variances, a clinically undesirable PIMD-2 pi change from baseline can be detected in approximately 18 months. Detection of significant PIMD-2 pi loss in a subject requires knowledge of normal age loss and measurement variability.

The present study aimed to develop a strategy for evaluation of instant PIMD-2 pi measurements as a basis for clinical monitoring of glaucoma. PIMD-2 pi is a morphometric measure of the waist of the nerve fiber layer at the optic nerve head (ONH). Clinical measurements of PIMD-2 pi in patients with early to moderate stage glaucoma demonstrated a high variability among subjects. The high variability among subjects renders comparison of instant PIMD-2 pi measurements to tolerance limits for normality derived from a normative database inefficient. It is suggested to instead compare sequential measurements of PIMD-2 pi within a patient. Initially, the difference between an instant measurement and the average of previous measurements can be compared to tolerance limits for difference between measurements within subject. Once, a potential loss of PIMD-2 pi is detected, a sufficient number of measurements within a sufficiently wide time interval can be used to estimate the PIMD-2 pi loss rate with regression and the deviation of the estimated loss rate can be evaluated as a 95 % confidence interval for the loss rate. If the upper confidence limit excludes 0, a significant loss rate has been detected. The currently proposed strategy has the potential to detect glaucoma earlier than the current gold standard, computer perimetry, with less inconvenience for the patient.

Purpose: 1) To estimate the threshold dose and the time evolution for cataract induction by near infrared radiation (IRR) in seconds exposure time domain; 2) to determine the ocular temperature development during the threshold exposure; 3) to investigate if near IRR induces cumulative lens damage considering irradiance exposure time reciprocity; 4) to experimentally estimate the temperature in the lens indirectly from the measurement of temperature-induced light scattering increase.

Methods: Before exposure, 6-weeks-old albino rats were anesthetized and the pupils of both eyes were dilated. Then the animals were unilaterally exposed to 1090 nm IRR within the pupil area. Temperature was recorded with thermocouples placed in the selected positions of the eye. At the planned post-exposure time, the animal was sacrificed and the lenses were extracted for measurements of forward light scattering and macroscopic imaging (Paper I-III). In Paper IV, the lens was extracted from six-weeks-old albino Sprague-Dawley female rats and put into a temperature-controlled cuvette filled with balanced salt solution. Altogether, 80 lenses were equally divided on four temperature groups, 37, 40, 43 and 46 ºC. Each lens was exposed for 5 minutes to temperature depending on group belonging while the intensity of forward light scattering was recorded.

Results: The in vivo exposure to 197 W/cm² 1090 nm IRR required a minimum 8 s for cataract induction. There was approximately 16 h delay between exposure and light scattering development in the lens. The same radiant exposure was found to cause a temperature increase of 10 °C at the limbus and 26 °C close to the retina. The in vivo exposure to 96 W/cm² 1090 nm IRR with exposure time up to 1 h resulted in an average temperature elevation of 7 °C at the limbus with the cornea humidified and no significant light scattering was induced one week after exposure. Arrhenius equation implies that the natural logarithm of the inclination coefficient for light scattering increase is linearly dependent on the inverse of the temperature. The proportionality constant and the intercept, estimated as CI(0.95)s, were 9.6±2.4 x10³ K and 22.8±7.7. Further, it implies that if averaging 20 measurements of inclination coefficients in a new experiment at constant heat load, the confidence limits for prediction of temperature correspond to ±1.9 °C.

Conclusions: It is indicated that IRR at 1090 nm produces thermal but not cumulatively photochemical cataract, probably by indirect heat conduction from absorption in tissues surrounding the lens. Applying the Arrhenius equation the in vivo temperature in the lens can be determined retrospectively with sufficient resolution.

The current study aims to experimentally estimate the temperature in the lens due to heat load indirectly from the measurement of increase rate of temperature-induced light scattering. The lens was extracted from Sprague-Dawley rats and put into a temperature-controlled cuvette filled with balanced salt solution. Altogether, 80 lenses were equally divided on four temperature groups. Each lens was exposed for 5 minutes to temperature depending on group belonging while the intensity of forward light scattering was recorded. The inclination coefficient of light scattering increase at the temperature 37, 40, 43, and 46 ºC was estimated as a CI(0.95), 3.1±0.8, 4.4±0.8, 5.5±0.9 and 7.0±0.8 x10^-4 tEDC/s, respectively. The Arrhenius equation implies that the natural logarithm of the inclination coefficient is linearly dependent on the inverse of the temperature. The proportionality constant and the intercept were 9.6±2.4 x10³ K and 22.8±7.7. The activation energy was 8.0±2.0 x10¹ kJ·mol^-1. The current experiment implies that if averaging 20 measurements of inclination coefficients in a new experiment at constant heat load, the confidence limits for predicted temperature correspond to ±1.9 °C. With the proportionality constant and the intercept estimated in the current experiment, the in vivo temperature in the lens can be determined retrospectively with sufficient resolution.

Visual quantification and classification of fluorescent signals is the gold standard in microscopy. The purpose of this study was to develop an automated method to delineate cells and to quantify expression of fluorescent signal of biomarkers in each nucleus and cytoplasm of lens epithelial cells in a histological section. A region of interest representing the lens epithelium was manually demarcated in each input image. Thereafter, individual cell nuclei within the region of interest were automatically delineated based on watershed segmentation and thresholding with an algorithm developed in Matlab™. Fluorescence signal was quantified within nuclei, cytoplasms and juxtaposed backgrounds. The classification of cells as labelled or not labelled was based on comparison of the fluorescence signal within cells with local background. The classification rule was thereafter optimized as compared with visual classification of a limited dataset. The performance of the automated classification was evaluated by asking 11 independent blinded observers to classify all cells (n = 395) in one lens image. Time consumed by the automatic algorithm and visual classification of cells was recorded. On an average, 77% of the cells were correctly classified as compared with the majority vote of the visual observers. The average agreement among visual observers was 83%. However, variation among visual observers was high, and agreement between two visual observers was as low as 71% in the worst case. Automated classification was on average 10 times faster than visual scoring. The presented method enables objective and fast detection of lens epithelial cells and quantification of expression of fluorescent signal with an accuracy comparable with the variability among visual observers.