Association of Antihypertensive Medication with Retinal Nerve Fiber Layer and Ganglion Cell-Inner Plexiform Layer Thickness.

PURPOSE: To evaluate the association between different classes of antihypertensive medication with retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GC-IPL) thickness in a nonglaucomatous multiethnic Asian population. DESIGN: Population-based, cross-sectional study. PARTICIPANTS: A total of 9144 eyes for RNFL analysis (2668 Malays, 3554 Indians, and 2922 Chinese) and 8549 eyes for GC-IPL analysis (2460 Malays, 3230 Indians, and 2859 Chinese) aged 44 to 86 years. METHODS: Participants underwent standardized systemic and ocular examinations and interviewer-administered questionnaires for collection of data on medication and other variables. Intraocular pressure (IOP) readings were obtained by Goldmann applanation tonometry before pupil dilation for fundoscopy and OCT imaging. Blood pressure (BP) was measured with an automatic BP monitor. Mean arterial pressure (MAP) was defined as diastolic BP plus 1/3 (systolic BP - diastolic BP). Regression models were used to investigate the association of antihypertensive medication with OCT measurements of RNFL and GC-IPL. MAIN OUTCOME MEASURES: Average and sectoral RNFL and GC-IPL thickness. RESULTS: After adjusting for age, gender, ethnicity, MAP, IOP, body mass index (BMI), and presence of diabetes, we found that participants taking any type of antihypertensive medication (ß = -0.83; 95% confidence interval [CI], -1.46 to -0.02; P = 0.01), specifically angiotensin-converting enzyme inhibitors (ACEIs) (ß = -1.66; 95% CI, -2.57 to -0.75; P < 0.001) or diuretics (ß = -1.38; 95% CI, -2.59 to -0.17; P < 0.05), had thinner average RNFL in comparison with participants who were not receiving antihypertensive treatment. Use of a greater number of antihypertensive medications was significantly associated with thinner average RNFL (P for trend = 0.001). This association was most evident in the inferior RNFL quadrant in participants using ACEIs (ß = -2.44; 95% CI, -3.99 to -0.89; P = 0.002) or diuretics (ß = -2.76; 95% CI, -4.76 to -0.76; P = 0.007). A similar trend was noted in our analysis of macular GC-IPL thickness. CONCLUSIONS: Use of 2 or more antihypertensive medications, ACEI, and diuretics were associated with a loss of structural markers of retinal ganglion cell health in a multiethnic Asian population.

Techniques and Applications in Skin OCT Analysis.

The skin is the largest organ of our body. Skin disease abnormalities which occur within the skin layers are difficult to examine visually and often require biopsies to make a confirmation on a suspected condition. Such invasive methods are not well-accepted by children and women due to the possibility of scarring. Optical coherence tomography (OCT) is a non-invasive technique enabling in vivo examination of sub-surface skin tissue without the need for excision of tissue. However, one of the challenges in OCT imaging is the interpretation and analysis of OCT images. In this review, we discuss the various methodologies in skin layer segmentation and how it could potentially improve the management of skin diseases. We also present a review of works which use advanced machine learning techniques to achieve layers segmentation and detection of skin diseases. Lastly, current challenges in analysis and applications are also discussed.

Ocular microvascular complications in diabetic retinopathy: insights from machine learning.

INTRODUCTION: Diabetic retinopathy (DR) is a leading cause of preventable blindness among working-age adults, primarily driven by ocular microvascular complications from chronic hyperglycemia. Comprehending the complex relationship between microvascular changes in the eye and disease progression poses challenges, traditional methods assuming linear or logistical relationships may not adequately capture the intricate interactions between these changes and disease advances. Hence, the aim of this study was to evaluate the microvascular involvement of diabetes mellitus (DM) and non-proliferative DR with the implementation of non-parametric machine learning methods. RESEARCH DESIGN AND METHODS: We conducted a retrospective cohort study that included optical coherence tomography angiography (OCTA) images collected from a healthy group (196 eyes), a DM no DR group (120 eyes), a mild DR group (71 eyes), and a moderate DR group (66 eyes). We implemented a non-parametric machine learning method for four classification tasks that used parameters extracted from the OCTA images as predictors: DM no DR versus healthy, mild DR versus DM no DR, moderate DR versus mild DR, and any DR versus no DR. SHapley Additive exPlanations values were used to determine the importance of these parameters in the classification. RESULTS: We found large choriocapillaris flow deficits were the most important for healthy versus DM no DR, and became less important in eyes with mild or moderate DR. The superficial microvasculature was important for the healthy versus DM no DR and mild DR versus moderate DR tasks, but not for the DM no DR versus mild DR task-the stage when deep microvasculature plays an important role. Foveal avascular zone metric was in general less affected, but its involvement increased with worsening DR. CONCLUSIONS: The findings from this study provide valuable insights into the microvascular involvement of DM and DR, facilitating the development of early detection methods and intervention strategies.

Validity of a new optic disc grading software for use in clinical and epidemiological research.

BACKGROUND: To determine the reliability and agreement of a new optic disc grading software program for use in clinical, epidemiological research. DESIGN: Reliability and agreement study. SAMPLES: 328 monoscopic and 85 stereoscopic optic disc images. METHODS: Optic disc parameters were measured using a new optic disc grading software (Singapore Optic Disc Assessment) that is based on polynomial curve-fitting algorithm. Two graders independently graded 328 monoscopic images to determine intergrader reliability. One grader regraded the images after 1 month to determine intragrader reliability. In addition, 85 stereo optic disc images were separately selected, and vertical cup-to-disc ratios were measured using both the new software and standardized Wisconsin manual stereo-grading method by the same grader 1 month apart. Intraclass correlation coefficient (ICC) and Bland-Altman plot analyses were performed. MAIN OUTCOME MEASURES: Optic disc parameters. RESULTS: The intragrader and intergrader reliability for optic disc measurements using Singapore Optic Disc Assessment was high (ICC ranging from 0.82 to 0.94). The mean differences (95% limits of agreement) for intergrader vertical cup-to-disc ratio measurements were 0.00 (-0.12 to 0.13) and 0.03 (-0.15 to 0.09), respectively. The vertical cup-to-disc ratio agreement between the software and Wisconsin grading method was extremely close (ICC = 0.94). The mean difference (95% limits of agreement) of vertical cup-to-disc ratio measurement between the two methods was 0.03 (-0.09 to 0.16). CONCLUSIONS: Intragrader and intergrader reliability using Singapore Optic Disc Assessment was excellent. This software was highly comparable with standardized stereo-grading method. Singapore Optic Disc Assessment is useful for grading digital optic disc images in clinical, population-based studies.

Towards 'automated gonioscopy': a deep learning algorithm for 360° angle assessment by swept-source optical coherence tomography.

AIMS: To validate a deep learning (DL) algorithm (DLA) for 360° angle assessment on swept-source optical coherence tomography (SS-OCT) (CASIA SS-1000, Tomey Corporation, Nagoya, Japan). METHODS: This was a reliability analysis from a cross-sectional study. An independent test set of 39 936 SS-OCT scans from 312 phakic subjects (128 SS-OCT meridional scans per eye) was analysed. Participants above 50 years with no previous history of intraocular surgery were consecutively recruited from glaucoma clinics. Indentation gonioscopy and dark room SS-OCT were performed. Gonioscopic angle closure was defined as non-visibility of the posterior trabecular meshwork in ≥180° of the angle. For each subject, all images were analysed by a DL-based network based on the VGG-16 architecture, for gonioscopic angle-closure detection. Area under receiver operating characteristic curves (AUCs) and other diagnostic performance indicators were calculated for the DLA (index test) against gonioscopy (reference standard). RESULTS: Approximately 80% of the participants were Chinese, and more than half were women (57.4%). The prevalence of gonioscopic angle closure in this hospital-based sample was 20.2%. After analysing a total of 39 936 SS-OCT scans, the AUC of the DLA was 0.85 (95% CI:0.80 to 0.90, with sensitivity of 83% and a specificity of 87%) to classify gonioscopic angle closure with the optimal cut-off value of >35% of circumferential angle closure. CONCLUSIONS: The DLA exhibited good diagnostic performance for detection of gonioscopic angle closure on 360° SS-OCT scans in a glaucoma clinic setting. Such an algorithm, independent of the identification of the scleral spur, may be the foundation for a non-contact, fast and reproducible 'automated gonioscopy' in future.

Evaluation of different OCT systems in quantitative imaging of human Schlemm's canal.

We examined the performance of human Schlemm's canal (SC) imaging using different OCT devices: CIRRUS 5000 (840 nm, spectral-domain (SD)-OCT), PLEX Elite 9000 (1060 nm, swept-source (SS)-OCT) and CASIA SS-1000 (1310 nm, SS-OCT), and analyzed potential impact factors on visualization and the quantitative assessment of SC morphology in a pilot study. Ten healthy subjects were imaged using three OCT devices by a single experienced operator on the same day. Each eye underwent two cubic scans by each device, one on nasal and the other on temporal quadrant. The B-scan showing the largest SC was manually selected for processing. Four quantitative metrics, including one morphological metric as cross-sectional area (CSA), and three performance metrics as contrast, continuity, and coverage, were derived from the datasets. Repeated-measures ANOVA was used to investigate the difference between these parameters from the three devices (P < 0.05). We found the CSA measured from CIRRUS was significantly larger than PLEX, followed by CASIA. The contrast was highest in CIRRUS, followed by PLEX and CASIA. The coverage was also higher in CIRRUS as compared to PLEX and CASIA. No significant difference was seen in the continuity from the three devices. In summary, we showed the measurements from the three devices were not interchangeable.

Comparison of retinal vessel diameter measurements from swept-source OCT angiography and adaptive optics ophthalmoscope.

BACKGROUND/IMS: To compare the retinal vessel diameter measurements obtained from the swept-source optical coherence tomography angiography (OCTA; Plex Elite 9000, Carl Zeiss Meditec, USA) and adaptive optics ophthalmoscope (AOO; RTX1, Imagine Eyes, France). METHODS: Fifteen healthy subjects, 67% women, mean age (SD) 30.87 (6.19) years, were imaged using OCTA and AOO by a single experienced operator on the same day. Each eye was scanned using two OCTA protocols (3×3 mm2 and 9×9 mm2) and two to five AOO scans (1.2×1.2 mm2). The OCTA and AOO scans were scaled to the same pixel resolution. Two independent graders measured the vessel diameter at the same location on the region-of-interest in the three coregistered scans. Differences in vessel diameter measurements between the scans were assessed. RESULTS: The inter-rater agreement was excellent for vessel diameter measurement in both OCTA protocols (ICC=0.92) and AOO (ICC=0.98). The measured vessel diameter was widest from the OCTA 3×3 mm2 (55.2±16.3 µm), followed by OCTA 9×9 mm2 (54.7±14.3 µm) and narrowest by the AOO (50.5±15.6 µm; p<0.001). Measurements obtained from both OCTA protocols were significantly wider than the AOO scan (OCTA 3×3 mm2: mean difference Δ=4.7 µm, p<0.001; OCTA 9×9 mm2: Δ=4.2 µm, p<0.001). For vessels >45 µm, it appeared to be larger in OCTA 3×3 mm2 scan than the 9×9 mm2 scan (Δ=1.9 µm; p=0.005), while vessels <45 µm appeared smaller in OCTA 3×3 mm2 scan (Δ=-1.3 µm; p=0.009) CONCLUSIONS: The diameter of retinal vessels measured from OCTA scans were generally wider than that obtained from AOO scans. Different OCTA scan protocols may affect the vessel diameter measurements. This needs to be considered when OCTA measures such as vessel density are calculated.

Liver tumour segmentation using contrast-enhanced multi-detector CT data: performance benchmarking of three semiautomated methods.

OBJECTIVE: Automatic tumour segmentation and volumetry is useful in cancer staging and treatment outcome assessment. This paper presents a performance benchmarking study on liver tumour segmentation for three semiautomatic algorithms: 2D region growing with knowledge-based constraints (A1), 2D voxel classification with propagational learning (A2) and Bayesian rule-based 3D region growing (A3). METHODS: CT data from 30 patients were studied, and 47 liver tumours were isolated and manually segmented by experts to obtain the reference standard. Four datasets with ten tumours were used for algorithm training and the remaining 37 tumours for testing. Three evaluation metrics, relative absolute volume difference (RAVD), volumetric overlap error (VOE) and average symmetric surface distance (ASSD), were computed based on computerised and reference segmentations. RESULTS: A1, A2 and A3 obtained mean/median RAVD scores of 17.93/10.53%, 17.92/9.61% and 34.74/28.75%, mean/median VOEs of 30.47/26.79%, 25.70/22.64% and 39.95/38.54%, and mean/median ASSDs of 2.05/1.41 mm, 1.57/1.15 mm and 4.12/3.41 mm, respectively. For each metric, we obtained significantly lower values of A1 and A2 than A3 (P < 0.01), suggesting that A1 and A2 outperformed A3. CONCLUSIONS: Compared with the reference standard, the overall performance of A1 and A2 is promising. Further development and validation is necessary before reliable tumour segmentation and volumetry can be widely used clinically.

Three-dimensional choroidal vessel network quantification using swept source optical coherence tomography.

Precise three-dimensional segmentation of choroidal vessels helps us understand the development and progression of multiple ocular diseases, such as agerelated macular degeneration and pathological myopia. Here we propose a novel automatic choroidal vessel segmentation framework for swept source optical coherence tomography (SS-OCT) to visualize and quantify three-dimensional choroidal vessel networks. Retinal pigment epithelium (RPE) was delineated from volumetric data and enface frames along the depth were extracted under the RPE. Choroidal vessels on the first enface frame were labeled by adaptive thresholding and each subsequent frame was segmented via segment propagation from the frame above and was in turn used as the reference for the next frame. Choroid boundary was determined by structural similarity index between adjacent frames. The framework was tested on 33 mm SS-OCT volumes acquired by a prototype SS-OCT system (PlexElite 9000, Zeiss Meditec, Dublin, CA, US), and vessel metrics including perfusion density, vessel density and mean vessel diameter were computed. Results from human subjects (N = 8) and non-human primates (N = 6) were summarized.Clinical Relevance- Accurate 3D choroid vessel segmentation can help clinicians better quantify blood perfusion which can lead to improved diagnosis and management of retinal eye diseases.

Volumetric Choroidal Segmentation Using Sequential Deep Learning Approach in High Myopia Subjects.

Many ocular diseases are associated with choroidal changes. Therefore, it is crucial to be able to segment the choroid to study its properties. Previous methods for choroidal segmentation have focused on single cross-sectional scans. Volumetric choroidal segmentation has yet to be widely reported. In this paper, we propose a sequential segmentation approach using a variation of U-Net with a bidirectional C-LSTM(Convolutional Long Short Term Memory) module in the bottleneck region. The model is evaluated on volumetric scans from 40 high myopia subjects, obtained using SS-OCT(Swept Source Optical Coherence Tomography). A comparison with other U-Net-based variants is also presented. The results demonstrate that volumetric segmentation of the choroid can be achieved with an accuracy of IoU(Intersection over Union) 0.92.Clinical relevance- This deep learning approach can automatically segment the choroidal volume, which can enable better evaluation and monitoring at ocular diseases.

Localization of Anatomical Features in Vascular-enhanced Enface OCT Images.

Optical coherence tomography (OCT) allows in vivo volumetric imaging of the eye. Identification and localization of anatomical features in enface OCT are important steps in OCT-based image analysis. However the visibility of anatomical features in both structural OCT or vascular OCT angiography is limited. In this paper, we propose to use vascular-enhanced enface OCT image for the concurrent detection of anatomical features, using a FasterRCNN object detection framework based on convolutional networks. Transfer learning was applied to adapt pre-trained models as the backbone networks. Models were evaluated on a dataset of 419 images. The results showed that VGG-FasterRCNN achieved a mean average precision 0.77, with localization errors of 0.18 ± 0.10 mm and 0.24 ± 0.13 mm for the macula and optic disc respectively. The results are promising and suggest that this network could potentially be used to automatically and concurrently detect anatomical features.Clinical Relevance- Localization of anatomical features in enface OCT is needed for the automation of OCT image analysis protocols. The use of fast detection networks could potentially suggest image-based real-time tracking during image acquisition.

Approaches to quantify optical coherence tomography angiography metrics.

Optical coherence tomography (OCT) has revolutionized the field of ophthalmology in the last three decades. As an OCT extension, OCT angiography (OCTA) utilizes a fast OCT system to detect motion contrast in ocular tissue and provides a three-dimensional representation of the ocular vasculature in a non-invasive, dye-free manner. The first OCT machine equipped with OCTA function was approved by U.S. Food and Drug Administration in 2016 and now it is widely applied in clinics. To date, numerous methods have been developed to aid OCTA interpretation and quantification. In this review, we focused on the workflow of OCTA-based interpretation, beginning from the generation of the OCTA images using signal decorrelation, which we divided into intensity-based, phase-based and phasor-based methods. We further discussed methods used to address image artifacts that are commonly observed in clinical settings, to the algorithms for image enhancement, binarization, and OCTA metrics extraction. We believe a better grasp of these technical aspects of OCTA will enhance the understanding of the technology and its potential application in disease diagnosis and management. Moreover, future studies will also explore the use of ocular OCTA as a window to link ocular vasculature to the function of other organs such as the kidney and brain.

Automatic Glaucoma Detection from Stereo Fundus Images.

This paper proposes a new method for automatic detection of glaucoma from stereo pair of fundus images. The basis for detecting glaucoma is using the optic cup-to-disc area ratio, where the surface area of the optic cup is segmented from the disparity map estimated from the stereo fundus image pair. More specifically, we first estimate the disparity map from the stereo image pair. Then, the optic disc is segmented from one of the stereo image. Based upon the location of the optic disc, we perform an active contour segmentation on the disparity map to segment the optic cup. Thereafter, we can compute the optic cup-to-disc area ratio by dividing the area (i.e. the total number of pixels) of the segmented optic cup region to that of the segmented optic disc region. Our experimental results using the available test dataset shows the efficacy of our proposed approach.

Longitudinal Structural and Microvascular Observation in RCS Rat Eyes Using Optical Coherence Tomography Angiography.

Purpose: To evaluate the change of retinal thickness and ocular microvasculature in a rat model of retinitis pigmentosa using swept source optical coherence tomography angiography (SS-OCTA). Methods: Three-weeks-old Royal College of Surgeons (RCS) rats (n = 8) and age-matched control rats (n = 14) were imaged by a prototype SS-OCTA system. Follow-up measurements occurred every three weeks on six RCS rats until week 18, and cross-sectional measurements were conducted on control rats. Thicknesses of different retinal layers and the total retina were measured. The enface angiograms from superficial vascular plexiform (SVP) and deep capillary plexiform (DCP) were analyzed, and the image sharpness was also extracted from the choroidal angiograms. Immunohistochemical analysis was done in the RCS rats after week 18, as well as in three-week-old RCS rats and age-matched controls. Results: In RCS rats, the thicknesses of the ganglion cell complex, the nuclear layer, the debris/photoreceptor layer and the total retina decreased over the weeks (P < 0.001). The SVP metrics remained unchanged whereas the DCP metrics decreased significantly over the weeks (P < 0.001). The immunohistochemical analysis confirmed our OCTA findings of capillary dropout in the DCP. The choroidal plexus appeared indistinct initially due to scattering of light at the intact retinal pigment epithelium (RPE) and became more visible after week nine probably due to RPE degeneration. Loss of choriocapillaris was visualized at week 18. In control rats, no vascular change was detected, but nuclear layers, photoreceptor layers and total retina showed slight thinning with age (P < 0.001). Conclusions: Photoreceptor degeneration in RCS rats was associated with the loss of capillaries in DCP, but not in SVP. The OCTA imaging allows for the characterization of structural and angiographic changes in rodent models.

Quantitative Microvascular Analysis With Wide-Field Optical Coherence Tomography Angiography in Eyes With Diabetic Retinopathy.

Importance: Wide-field optical coherence tomographic angiography (OCTA) may provide insights to peripheral capillary dropout in eyes with diabetic retinopathy (DR). Objective: To describe the diagnostic performance of wide-field OCTA with and without large vessel removal for assessment of DR in persons with diabetes. Design, Setting, and Participants: This case-control study was performed from April 26, 2018, to April 8, 2019, at a single tertiary eye center in Singapore. Case patients were those with type 2 diabetes for more than 5 years and bilateral DR diagnosed by fundus imaging; control participants included those with no self-reported history of diabetes, a fasting glucose level within the normal range in the past year, and no ocular pathologic findings. A wide-field (12 × 12-mm2) fovea-centered scan was performed using a prototype swept source OCTA system. Retinal microvasculature was examined by separating the angiograms into large vessels, capillaries, and capillary dropout regions. Main Outcomes and Measures: Area under the receiver operating characteristic curve (AUC) for DR severity discrimination using wide-field vascular metrics. Retinal perfusion density (RPD), capillary perfusion density (CPD), large vessel density (LVD), and capillary dropout density (CDD) were calculated. Low-contrast regions were excluded from the calculation. Results: A total of 49 eyes in 27 control participants (17 male [63.0%]; mean [SD] age, 59.96 [7.63] years; age range, 44-79 years) and 76 eyes in 47 patients with diabetes (29 male [61.7%]; mean [SD] age, 64.36 [8.08] years; range, 41-79 years) were included. Among eyes in patients with diabetes, 23 were in those with diabetes but no DR, 25 in those with mild nonproliferative DR, and 28 in those with moderate to severe nonproliferative DR. There was no difference in RPD, CPD, LVD, and CDD between the control group and the group with diabetes and no DR. There was a stepwise decrease in RPD, CPD, and CDD in the diabetes with no DR, mild nonproliferative DR, and moderate to severe nonproliferative DR groups, whereas LVD was not associated with DR staging. The nonproliferative DR group had decreased RPD, CPD, and CDD compared with the control group. The CPD had higher AUCs than RPD for discriminating diabetes with nonproliferative DR (combined mild and moderate to severe nonproliferative DR) vs no DM (AUC, 0.92 [95% CI, 0.87-0.98] vs 0.89 [95% CI, 0.83-0.95], P = .01), diabetes with no DR vs mild nonproliferative DR (AUC, 0.81 [95% CI, 0.68-0.94] vs 0.77 [95% CI, 0.64-0.91], P = .18), and mild nonproliferative DR vs moderate to severe nonproliferative DR (AUC, 0.82 [95% CI, 0.71-0.94] vs 0.78 [95% CI, 0.65-0.91], P = .01) but similar AUCs for no DM vs diabetes with no DR. The total perfusion density and CPD in wide-field OCTA had better discriminative power than the central 6 × 6-mm2 field (CPD, 0.89 [95% CI, 0.83-0.95] vs 0.84 [95% CI, 0.77-0.92], P = .06; total perfusion density, 0.93 [95% CI, 0.87-0.98] vs 0.90 [95% CI, 0.83-0.96], P = .06). Conclusions and Relevance: The findings suggest that wide-field OCTA provides information on microvascular perfusion and may be useful for detecting predominant peripheral capillary dropout in eyes with nonproliferative DR. A vascular selectivity approach excluding the large vessels may improve the discriminative power for different stages of DR.

Comparison of a commercial spectral-domain OCT and swept-source OCT based on an angiography scan for measuring circumpapillary retinal nerve fibre layer thickness.

BACKGROUND/AIMS: To assess the agreement in measuring retinal nerve fibre layer (RNFL) thickness between spectral-domain (SD; Cirrus HD, Carl Zeiss Meditec, USA) optical coherence tomography (OCT) and swept-source (SS; Plex Elite 9000, Carl Zeiss Meditec) OCT using an OCT angiography (OCTA) scanning protocol. METHODS: 57 participants (12 glaucomatous, 8 ocular hypertensive and 74 normal eyes) were scanned with two OCT instruments by a single experienced operator on the same day. Circumpapillary RNFL thicknesses were automatically segmented for SD-OCT and manually segmented for SS-OCTA scans. Agreement of global RNFL thickness, as well as average thickness in four quadrants was assessed using intraclass correlation coefficients (ICCs). RESULTS: There was excellent agreement in the inferior and superior quadrants and the global (all ICC >0.90), followed by good agreement in the temporal (ICC=0.79) and nasal (ICC=0.73) quadrants. The ICC values were similar in the subgroups except within the ocular hypertension group, where the nasal quadrant was less agreeable (ICC=0.31). SS-OCTA-derived RNFL thickness was on average 3 µm thicker than SD-OCT, particularly in the nasal (69.7±11.5 µm vs 66.3±9.3 µm; p<0.001) and temporal (75.6±13.7 µm vs 67.9±12.3 µm; p<0.001) quadrants. CONCLUSIONS: RNFL measurements taken with SS-OCTA have good-to-excellent agreement with SD-OCT, which suggests that the RNFL thickness can be sufficiently extracted from wide-field OCTA scans.

Dissolving Triamcinolone-Embedded Microneedles for the Treatment of Keloids: A Single-Blinded Intra-Individual Controlled Clinical Trial.

INTRODUCTION: Keloids are a prevalent chronic skin disorder with significant psychosocial morbidity. Intralesional corticosteroid injections are the first-line treatment but are painful and require repeated injections by medical professionals. Dissolving microneedles are a novel method of cutaneous drug delivery that induces minimal/no pain and can be self-administered. The objective of the study was to evaluate the efficacy and safety of triamcinolone-embedded dissolving microneedles in treatment of keloids. METHODS: This was a single-blind, intra-individual controlled two-phase clinical trial of 8-week duration each. Two keloids per subject were selected for (1) once-daily 2-min application with microneedles for 4 weeks, followed by no treatment for the next 4 weeks, or (2) non-intervention as control. Primary outcome was change in keloid volume as assessed by a high-resolution 3D scanner. RESULTS: There was significant reduction in keloid volume compared with controls after 4 weeks of treatment. This reduction was greater with a higher dosage of triamcinolone used. CONCLUSIONS: Once-daily application of dissolving triamcinolone-embedded microneedles significantly reduced the volume of keloids. The treatment was safe, can be self-administered and can serve as an alternative for patients unsuitable for conventional treatments. TRIAL REGISTRATION: Trial Registry: Health Science Authority (Singapore) Clinical Trials Register Registration number: 2015/00440.

In vivo corneal endothelium imaging using ultrahigh resolution OCT.

We investigate the influence of optical coherence tomography (OCT) system resolution on high-quality in vivo en face corneal endothelial cell images of the monkey eye, to allow for quantitative analysis of cell density. We vary the lateral resolution of the ultrahigh resolution (UHR) OCT system (centered at 850 nm) by using different objectives, and the axial resolution by windowing the source spectrum. By suppressing the motion of the animal, we are able to obtain a high-quality en face corneal endothelial cell map in vivo using UHR OCT for the first time with a lateral resolution of 3.1 µm. Increasing lateral resolution did not result in a better image quality but a smaller field of view (FOV), and the axial resolution had little impact on the visualization of corneal endothelial cells. Quantitative analysis of cell density was performed on in vivo en face OCT images of corneal endothelial cells, and the results are in agreement with previously reported data. Our study may offer a practical guideline for designing OCT systems that allow for in vivo corneal endothelial cell imaging with high quality.

Three-dimensional graph-based skin layer segmentation in optical coherence tomography images for roughness estimation.

Automatic skin layer segmentation in optical coherence tomography (OCT) images is important for a topographic assessment of skin or skin disease detection. However, existing methods cannot deal with the problem of shadowing in OCT images due to the presence of hair, scales, etc. In this work, we propose a method to segment the topmost layer of the skin (or the skin surface) using 3D graphs with a novel cost function to deal with shadowing in OCT images. 3D graph cuts use context information across B-scans when segmenting the skin surface, which improves the segmentation as compared to segmenting each B-scan separately. The proposed method reduces the segmentation error by more than 20% as compared to the best performing related work. The method has been applied to roughness estimation and shows a high correlation with a manual assessment. Promising results demonstrate the usefulness of the proposed method for skin layer segmentation and roughness estimation in both normal OCT images and OCT images with shadowing.

Glaucoma classification from retina optical coherence tomography angiogram.

This paper presents a new method for classification of retina into glaucoma and non-glaucoma cases based on optical coherence tomography angiogram (OCTA). The key idea here is to analyze the retinal microvasculature in the optic disc area of an enface OCTA for glaucoma classification. To facilitate this analysis, we propose a way to extract a so-called "optic disc microvasculature" region and then propose several features that will be extracted from this microvasculature region. A machine classifier is then trained using the designated features and subsequently used to classify the OCTA data. We show that our proposed approach works well on the tested dataset.