From data to diagnosis: skin cancer image datasets for artificial intelligence.

Artificial intelligence (AI) solutions for skin cancer diagnosis continue to gain momentum, edging closer towards broad clinical use. These AI models, particularly deep-learning architectures, require large digital image datasets for development. This review provides an overview of the datasets used to develop AI algorithms and highlights the importance of dataset transparency for the evaluation of algorithm generalizability across varying populations and settings. Current challenges for curation of clinically valuable datasets are detailed, which include dataset shifts arising from demographic variations and differences in data collection methodologies, along with inconsistencies in labelling. These shifts can lead to differential algorithm performance, compromise of clinical utility, and the propagation of discriminatory biases when developed algorithms are implemented in mismatched populations. Limited representation of rare skin cancers and minoritized groups in existing datasets are highlighted, which can further skew algorithm performance. Strategies to address these challenges are presented, which include improving transparency, representation and interoperability. Federated learning and generative methods, which may improve dataset size and diversity without compromising privacy, are also examined. Lastly, we discuss model-level techniques that may address biases entrained through the use of datasets derived from routine clinical care. As the role of AI in skin cancer diagnosis becomes more prominent, ensuring the robustness of underlying datasets is increasingly important.

Classifying Real-world Macroscopic Images in the Primary-Secondary Care Interface using Transfer Learning: Implications for Development of Artificial Intelligence Solutions using Non- dermoscopic Images.

BACKGROUND: Application of deep learning to diagnostic dermatology has been the subject of numerous studies, with some reporting skin lesion classification performance on curated datasets comparable to that of experienced dermatologists. Most skin disease images encountered in clinical settings are macroscopic, without dermoscopic information, and exhibit considerable variability. Further research is necessary to determine the generalisability of deep learning algorithms across populations and acquisition settings. OBJECTIVES: We assessed the extent to which deep learning can generalise to non-dermoscopic datasets acquired at the primary-secondary care interface in the National Health Service (NHS). We explored how to obtain clinically satisfactory performance on non-standardised, real-world local data without availability of large diagnostically labelled local datasets. We measured the impact of pre-training deep learning algorithms on external, public-domain datasets. METHODS: Diagnostic macroscopic image datasets were created from previous referrals from primary to secondary care. These included 2213 images referred from primary care practitioners in NHS Tayside and 1510 images from NHS Forth Valley acquired by medical photographers. Two further datasets with identical diagnostic labels were obtained from public domain sources, namely the International Skin Imaging Collaboration (ISIC) dermoscopic dataset and the SD-260 non-dermoscopic dataset. Deep learning algorithms, specifically SWIN transformers and an EfficientNets, were trained using data from each of these datasets. Algorithms were also fine-tuned on images from the NHS datasets after pre-training on different data combinations, including the larger public domain datasets. ROC curves and area under such curves (AUC) were used to assess performance. RESULTS: SWIN transformers tested on Forth Valley data had AUCs of 0.85 and 0.89 when trained on SD-260 and Forth Valley data, respectively. Training on SD-260 followed by fine-tuning of Forth Valley data gave an AUC of 0.91. Similar effects of pre-training and tuning on local data were observed using Tayside data, and EfficientNets. Pre-training on the larger dermoscopic image dataset (ISIC-2019) provided no additional benefit. CONCLUSIONS: Pre-training on public macroscopic images, followed by tuning to local data, gave promising results. Further improvements are needed to afford deployment in real clinical pathways. Larger datasets local to the target domain might be expected to yield further improved performance.

Assessment of the conjunctival microcirculation in adult patients with cyanotic congenital heart disease compared to healthy controls.

PURPOSE: Congenital heart disease (CHD) is the most common live birth defect and a proportion of these patients have chronic hypoxia. Chronic hypoxia leads to secondary erythrocytosis resulting in microvascular dysfunction and increased thrombosis risk. The conjunctival microcirculation is easily accessible for imaging and quantitative assessment. It has not previously been studied in adult CHD patients with cyanosis (CCHD). METHODS: We assessed the conjunctival microcirculation and compared CCHD patients and matched healthy controls to determine if there were differences in measured microcirculatory parameters. We acquired images using an iPhone 6s and slit-lamp biomicroscope. Parameters measured included diameter, axial velocity, wall shear rate and blood volume flow. The axial velocity was estimated by applying the 1D + T continuous wavelet transform (CWT). Results are for all vessels as they were not sub-classified into arterioles or venules. RESULTS: 11 CCHD patients and 14 healthy controls were recruited to the study. CCHD patients were markedly more hypoxic compared to the healthy controls (84% vs 98%, p = 0.001). A total of 736 vessels (292 vs 444) were suitable for analysis. Mean microvessel diameter (D) did not significantly differ between the CCHD patients and controls (20.4 ± 2.7 µm vs 20.2 ± 2.6 µm, p = 0.86). Axial velocity (Va) was lower in the CCHD patients (0.47 ± 0.06 mm/s vs 0.53 ± 0.05 mm/s, p = 0.03). Blood volume flow (Q) was lower for CCHD patients (121 ± 30pl/s vs 145 ± 50pl/s, p = 0.65) with the greatest differences observed in vessels >22 µm diameter (216 ± 121pl/s vs 258 ± 154pl/s, p = 0.001). Wall shear rate (WSR) was significantly lower for the CCHD group (153 ± 27 s-1 vs 174 ± 22 s-1, p = 0.04). CONCLUSIONS: This iPhone and slit-lamp combination assessment of conjunctival vessels found lower axial velocity, wall shear rate and in the largest vessel group, lower blood volume flow in chronically hypoxic patients with congenital heart disease. With further study this assessment method may have utility in the evaluation of patients with chronic hypoxia.

Retinal imaging in Alzheimer's disease.

Identifying biomarkers of Alzheimer's disease (AD) will accelerate the understanding of its pathophysiology, facilitate screening and risk stratification, and aid in developing new therapies. Developments in non-invasive retinal imaging technologies, including optical coherence tomography (OCT), OCT angiography and digital retinal photography, have provided a means to study neuronal and vascular structures in the retina in people with AD. Both qualitative and quantitative measurements from these retinal imaging technologies (eg, thinning of peripapillary retinal nerve fibre layer, inner retinal layer, and choroidal layer, reduced capillary density, abnormal vasodilatory response) have been shown to be associated with cognitive function impairment and risk of AD. The development of computer algorithms for respective retinal imaging methods has further enhanced the potential of retinal imaging as a viable tool for rapid, early detection and screening of AD. In this review, we present an update of current retinal imaging techniques and their potential applications in AD research. We also discuss the newer retinal imaging techniques and future directions in this expanding field.

Investigation of associations between retinal microvascular parameters and albuminuria in UK Biobank: a cross-sectional case-control study.

BACKGROUND: Associations between microvascular variation and chronic kidney disease (CKD) have been reported previously. Non-invasive retinal fundus imaging enables evaluation of the microvascular network and may offer insight to systemic risk associated with CKD. METHODS: Retinal microvascular parameters (fractal dimension [FD] - a measure of the complexity of the vascular network, tortuosity, and retinal arteriolar and venular calibre) were quantified from macula-centred fundus images using the Vessel Assessment and Measurement Platform for Images of the REtina (VAMPIRE) version 3.1 (VAMPIRE group, Universities of Dundee and Edinburgh, Scotland) and assessed for associations with renal damage in a case-control study nested within the multi-centre UK Biobank cohort study. Participants were designated cases or controls based on urinary albumin to creatinine ratio (ACR) thresholds. Participants with ACR ≥ 3 mg/mmol (ACR stages A2-A3) were characterised as cases, and those with an ACR < 3 mg/mmol (ACR stage A1) were categorised as controls. Participants were matched on age, sex and ethnic background. RESULTS: Lower FD (less extensive microvascular branching) was associated with a small increase in odds of albuminuria independent of blood pressure, diabetes and other potential confounding variables (odds ratio [OR] 1.18, 95% confidence interval [CI] 1.03-1.34 for arterioles and OR 1.24, CI 1.05-1.47 for venules). Measures of tortuosity or retinal arteriolar and venular calibre were not significantly associated with ACR. CONCLUSIONS: This study supports previously reported associations between retinal microvascular FD and other metabolic disturbances affecting the systemic vasculature. The association between retinal microvascular FD and albuminuria, independent of diabetes and blood pressure, may represent a useful indicator of systemic vascular damage associated with albuminuria.

Novel Genetic Locus Influencing Retinal Venular Tortuosity Is Also Associated With Risk of Coronary Artery Disease.

OBJECTIVE: The retina may provide readily accessible imaging biomarkers of global cardiovascular health. Increasing evidence suggests variation in retinal vascular traits is highly heritable. This study aimed to identify the genetic determinants of retinal vascular traits. Approach and Results: We conducted a meta-analysis of genome-wide association studies for quantitative retinal vascular traits derived using semi-automatic image analysis of digital retinal photographs from the GoDARTS (Genetics of Diabetes Audit and Research in Tayside; N=1736) and ORCADES (Orkney Complex Disease Study; N=1358) cohorts. We identified a novel genome-wide significant locus at 19q13 (ACTN4/CAPN12) for retinal venular tortuosity (TortV), and one at 13q34 (COL4A2) for retinal arteriolar tortuosity (TortA); these 2 loci were subsequently confirmed in 3 independent cohorts (Ntotal=1413). In the combined analysis of discovery and replication cohorts, the lead single-nucleotide polymorphism in ACTN4/CAPN12 was rs1808382 (ßs.d.=-0.109; SE=0.015; P=2.39×10-13) and in COL4A2 was rs7991229 (ßs.d.=0.103; SE=0.015; P=4.66×10-12). Notably, the ACTN4/CAPN12 locus associated with TortV is also associated with coronary artery disease, heart rate, and atrial fibrillation. CONCLUSIONS: Genetic determinants of retinal vascular tortuosity are also linked to cardiovascular health. These findings provide a molecular pathophysiological foundation for the use of retinal vascular traits as biomarkers for cardiovascular diseases.

Retinal Vessel Analysis as a Novel Screening Tool to Identify Childhood Acute Lymphoblastic Leukemia Survivors at Risk of Cardiovascular Disease.

BACKGROUND: Microvascular endothelial dysfunction is central to the pathogenesis of cardiovascular disease (CVD). The eye offers direct access for endothelial health assessment via the retinal microvasculature. The aim of the study was to investigate whether image-based retinal vessel analysis is a feasible method of assessing endothelial health in survivors of childhood acute lymphoblastic leukemia (cALL). MATERIALS AND METHODS: Cardiovascular risk factors (CRFs) were estimated using the 30-year Framingham Risk Score in 73 childhood leukemia survivors (median age: 25; median years from diagnosis: 19) and 78 healthy controls (median age: 23). Radial arterial stiffness was measured using pulse wave analyzer, while endothelial activation markers were measured by soluble intercellular adhesion molecule 1 (sICAM-1) and soluble vascular cell adhesion molecule 1 (sVCAM-1). Retinal fundus images were analyzed for central retinal artery/vein equivalents (CRAE/CRVE) and arteriolar-venular ratio (AVR). RESULTS: cALL survivors had higher CRF (P<0.0001), arterial stiffness (P=0.001), and sVCAM-1 (P=0.007) compared with controls. Survivors also had significantly higher CRVE (P=0.021) while AVR was significantly lower (P=0.026) in survivors compared with controls, compatible with endothelial dysfunction. In cALL survivors with intermediate risk for CVD, CRAE, and AVR are significantly lower, while sVCAM-1 and sICAM-1 are significantly higher when compared with survivors with low CVD risk after adjusting with covariates (age, sex, and smoking status). CONCLUSIONS: cALL survivors have an increased risk of CVD compared with age-matched peers. The survivors demonstrated microvasculopathy, as measured by retinal vascular analysis, in addition to physical and biochemical evidence of endothelial dysfunction. These changes predate other measures of CVD. Retinal vessel analysis may be utilized as a robust screening tool for identifying survivors at increased risk for developing CVD.

Quantitative assessment of the conjunctival microcirculation using a smartphone and slit-lamp biomicroscope.

PURPOSE: The conjunctival microcirculation is a readily-accessible vascular bed for quantitative haemodynamic assessment and has been studied previously using a digital charge-coupled device (CCD). Smartphone video imaging of the conjunctiva, and haemodynamic parameter quantification, represents a novel approach. We report the feasibility of smartphone video acquisition and subsequent haemodynamic measure quantification via semi-automated means. METHODS: Using an Apple iPhone 6 s and a Topcon SL-D4 slit-lamp biomicroscope, we obtained videos of the conjunctival microcirculation in 4 fields of view per patient, for 17 low cardiovascular risk patients. After image registration and processing, we quantified the diameter, mean axial velocity, mean blood volume flow, and wall shear rate for each vessel studied. Vessels were grouped into quartiles based on their diameter i.e. group 1 (<11 µm), 2 (11-16 µm), 3 (16-22 µm) and 4 (>22 µm). RESULTS: From the 17 healthy controls (mean QRISK3 6.6%), we obtained quantifiable haemodynamics from 626 vessel segments. The mean diameter of microvessels, across all sites, was 21.1µm (range 5.8-58 µm). Mean axial velocity was 0.50mm/s (range 0.11-1mm/s) and there was a modestly positive correlation (r 0.322) seen with increasing diameter, best appreciated when comparing group 4 to the remaining groups (p < .0001). Blood volume flow (mean 145.61pl/s, range 7.05-1178.81pl/s) was strongly correlated with increasing diameter (r 0.943, p < .0001) and wall shear rate (mean 157.31 s-1, range 37.37-841.66 s-1) negatively correlated with increasing diameter (r - 0.703, p < .0001). CONCLUSIONS: We, for the first time, report the successful assessment and quantification of the conjunctival microcirculatory haemodynamics using a smartphone-based system.

VAMPIRE® fundus image analysis algorithms: Validation and diagnostic relevance in hypertensive cats.

OBJECTIVES: To validate a retinal imaging software named VAMPIRE® (Vascular Assay and Measurement Platform for Images of the Retina) in feline patients and test the clinical utility in hypertensive cats. ANIMALS STUDIED: One hundred and five healthy cats were enrolled. They represented the normal dataset used in the validation (group 1). Forty-three hypertensive cats with no noticeable retinal abnormalities were enrolled for the clinical validity of the software (group 2). PROCEDURES: Eleven points (4 veins, 4 arteries, and 3 arterial bifurcations) were measured for each digital image. Repeatability and reproducibility of measurements were assessed using two independent operators. Data were statistically analyzed by the Mann-Whiney and Tukey box plot. Significance was considered when P < 0.05. RESULTS: Two hundred and ten retinal images were analyzed for a total of 2310 measurements. Total mean was 9.1 and 6.1 pixels for veins and arteries, respectively. First, second, and third arteriolar bifurcations angles were 73.6°, 76.9°, and 85.4°, respectively. A comparison between groups 1 and 2 showed a statistically significant reduction in arteriolar diameter (mean 3.3 pixels) and branch angle (55°, 47.8° and 59.9°) associated with increasing vein diameter (mean 24.15 pixels). CONCLUSIONS: Current image analysis techniques used in human medicine were investigated in terms of extending their use to veterinary medicine. The VAMPIRE® algorithm proved useful for an objective diagnosis of retinal vasculature changes secondary to systemic hypertension in cats, and could be an additional diagnostic test for feline systemic hypertension.

Ultra-Widefield Imaging of the Retinal Macrovasculature in Parkinson Disease Versus Controls With Normal Cognition Using Alpha-Shapes Analysis.

Purpose: To investigate retinal vascular characteristics using ultra-widefield (UWF) scanning laser ophthalmoscopy in Parkinson disease (PD). Methods: Individuals with an expert-confirmed clinical diagnosis of PD and controls with normal cognition without PD underwent Optos California UWF imaging. Patients with diabetes, uncontrolled hypertension, glaucoma, dementia, other movement disorders, or known retinal or optic nerve pathology were excluded. Images were analyzed using Vasculature Assessment and Measurement Platform for Images of the Retina (VAMPIRE-UWF) software, which describes retinal vessel width gradient and tortuosity, provides vascular network fractal dimensions, and conducts alpha-shape analysis to further characterize vascular morphology (complexity, Opαmin; spread, OpA). Results: In the PD cohort, 53 eyes of 38 subjects were assessed; in the control cohort, 51 eyes of 33 subjects were assessed. Eyes with PD had more tortuous retinal arteries in the superotemporal quadrant (P = 0.043). In eyes with PD, alpha-shape analysis revealed decreased OpA, indicating less retinal vasculature spread compared to controls (P = 0.032). Opαmin was decreased in PD (P = 0.044), suggesting increased vascular network complexity. No differences were observed in fractal dimension in any region of interest. Conclusions: This pilot study suggests that retinal vasculature assessment on UWF images using alpha-shape analysis reveals differences in retinal vascular network spread and complexity in PD and may be a more sensitive metric compared to fractal dimension. Translational Relevance: Retinal vasculature assessment using these novel methods may be useful in understanding ocular manifestations of PD and the development of retinal biomarkers.

PallorMetrics: Software for Automatically Quantifying Optic Disc Pallor in Fundus Photographs, and Associations With Peripapillary RNFL Thickness.

Purpose: We sough to develop an automatic method of quantifying optic disc pallor in fundus photographs and determine associations with peripapillary retinal nerve fiber layer (pRNFL) thickness. Methods: We used deep learning to segment the optic disc, fovea, and vessels in fundus photographs, and measured pallor. We assessed the relationship between pallor and pRNFL thickness derived from optical coherence tomography scans in 118 participants. Separately, we used images diagnosed by clinical inspection as pale (n = 45) and assessed how measurements compared with healthy controls (n = 46). We also developed automatic rejection thresholds and tested the software for robustness to camera type, image format, and resolution. Results: We developed software that automatically quantified disc pallor across several zones in fundus photographs. Pallor was associated with pRNFL thickness globally (ß = -9.81; standard error [SE] = 3.16; P < 0.05), in the temporal inferior zone (ß = -29.78; SE = 8.32; P < 0.01), with the nasal/temporal ratio (ß = 0.88; SE = 0.34; P < 0.05), and in the whole disc (ß = -8.22; SE = 2.92; P < 0.05). Furthermore, pallor was significantly higher in the patient group. Last, we demonstrate the analysis to be robust to camera type, image format, and resolution. Conclusions: We developed software that automatically locates and quantifies disc pallor in fundus photographs and found associations between pallor measurements and pRNFL thickness. Translational Relevance: We think our method will be useful for the identification, monitoring, and progression of diseases characterized by disc pallor and optic atrophy, including glaucoma, compression, and potentially in neurodegenerative disorders.

The Scottish Medical Imaging Archive: 57.3 Million Radiology Studies Linked to Their Medical Records.

Keywords: MRI, Imaging Sequences, Ultrasound, Mammography, CT, Angiography, Conventional Radiography Published under a CC BY 4.0 license. See also the commentary by Whitman and Vining in this issue.

The persistence of knuckle creases during finger flexion for the identification of perpetrators from digital images of their hands.

The analysis of knuckle creases is part of the multifactorial assessment of digital images of the hand used to assist in the identification of perpetrators captured in images depicting child sexual abuse and other offending behaviours. To quantify the impact of finger flexion on the appearance of the dorsal knuckle creases associated with the proximal interphalangeal joint (PIP) joint in digital images, the collection of knuckle crease images, at different points of flexion, was facilitated through an app-based Citizen Science project, Knuckle Down ID. A method of knuckle crease classification was adapted to assess the images collected and was used to assess the impact of finger flexion on the frequency of different knuckle crease features observed in manual analysis. The results show that the adapted methodology had good intra-observer repeatability when the entire method was assessed (ICC.81). Specifically, the recording of the knuckle crease features had good inter-observer reliability (ICC.99) whereas the tracing aspect of the methodology was less repeatable (DSC of whole trace.24). The impact of flexion on the recorded frequency of knuckle creases was shown to be significant (p = .00). However, when comparing two hands at different points of flexion, only when comparing fingers held at 0° vs 45° (p = .04) as well as fingers held at 90° vs any other finger position was the differences in the knuckle crease feature frequencies significant (p = .00). The comparison of knuckle crease image pairs at 20° of hyperflexion vs 0° (p = .10) and 20° of hyperflexion vs 45° (p = .09) showed that the difference in knuckle crease feature frequencies was not significant. This has implications for examiners and improves understanding of the limitations of the 1:1 comparison of knuckle creases in casework evidence in which perpetrator's hands are unconstrained.

Self-supervised monocular depth estimation for high field of view colonoscopy cameras.

Optical colonoscopy is the gold standard procedure to detect colorectal cancer, the fourth most common cancer in the United Kingdom. Up to 22%-28% of polyps can be missed during the procedure that is associated with interval cancer. A vision-based autonomous soft endorobot for colonoscopy can drastically improve the accuracy of the procedure by inspecting the colon more systematically with reduced discomfort. A three-dimensional understanding of the environment is essential for robot navigation and can also improve the adenoma detection rate. Monocular depth estimation with deep learning methods has progressed substantially, but collecting ground-truth depth maps remains a challenge as no 3D camera can be fitted to a standard colonoscope. This work addresses this issue by using a self-supervised monocular depth estimation model that directly learns depth from video sequences with view synthesis. In addition, our model accommodates wide field-of-view cameras typically used in colonoscopy and specific challenges such as deformable surfaces, specular lighting, non-Lambertian surfaces, and high occlusion. We performed qualitative analysis on a synthetic data set, a quantitative examination of the colonoscopy training model, and real colonoscopy videos in near real-time.

Lower fractal dimension of retinal vessel for patients with Birdshot chorioretinopathy.

PURPOSE: To identify the retinal vessel vasculature parameters associated with birdshot chorioretinopathy (BSCR). METHODS: This retrospective observational study included 28 prevalent cases of BSCR with a median time from diagnosis of 6 years and 28 controls matched for age, arterial hypertension, diabetes and refraction. Forty-five-degree fundus images of both dilated eyes were acquired with a fundus camera (Canon CR-2, Tokyo, Japan). The summary diameter of the arterial retinal vessels (central retinal artery equivalent, CRAE), venous retinal vessels (central retinal vein equivalent, CRVE), vascular tortuosity and fractal dimension (FD) were measured using VAMPIRE software. Retinal vasculitis was characterized using fluorescein angiography and active choroiditis using indocyanine green angiography. RESULTS: At baseline, BSCR was associated with lower FD compared with matched controls (mean difference, -0.04; 95% confidence interval [CI], -0.06 to -0.02, p < 0.001). No other VAMPIRE parameters (CRAE, CRVE, arterial and venous tortuosity) differed. Among BSCR patients, retinal vein vasculitis was associated with higher CRAE (mean difference, 21 µ; 95% CI, 2.6-40, p = 0.03), venous tortuosity (geometric mean ratio, 1.79; 95% CI, 1.18-2.72, p = 0.007) and FD (mean difference, -0.04; 95% CI, -0.06 to -0.01, p = 0.007). Resolution of retinal vein vasculitis during follow-up was paralleled by decrease in CRAE, CRVE and venous tortuosity values and increase in venous FD, respectively. CONCLUSION: BSCR is associated with lower FD value, suggesting that chronic retinal inflammation induces microvascular remodelling. Efficient treatment of retinal vasculitis may reverse changes in retinal vascular parameters. Changes in retinal vascular parameters could be potentially useful for assessing patients with BSCR disease.

Effects of pupil dilation with topical 0.5% tropicamide on retinal vascular parameters assessed by VAMPIRE® software in healthy cats.

Our study investigates the effects of mydriasis obtained with topical 0.5% tropicamide on retinal vascular parameters evaluated in cats using the retinal imaging software: Vascular Assessment and Measurement Platform for Images of the Retina (VAMPIRE®). Forty client-owned healthy adult cats were included in the study. Topical 0.5% tropicamide was applied to dilate only the right pupil. The left eye was used as a control. Before dilation (T0), infrared pupillometry of both pupils was performed and fundus oculi images were taken from both eyes. Right eye fundus images were then captured 30 min after topical application of tropicamide (T30), when mydriasis was achieved. The retinal vessel widths (3 arteries and 3 veins) were measured with VAMPIRE® in four standard measurement areas (SMA) identified with the letters A, B, C, D. Average value of the 3 vessel widths was used. After normality assessment, the t-test was used to analyse the mean difference in vascular parameters of the left and right eyes at T0 and T30, with p set <0.05. The two eyes showed no statistical differences in pupil and vascular parameter measurements at T0. At T30, only one artery measurement of the right eye (SMA A-peripapillary area) showed a small but statistically significant mean vasoconstriction of approximately 4%. The results indicate that local application of 0.5% tropicamide seems to be associated with a small retinal arteriolar vasoconstriction as assessed by VAMPIRE® in cats. However, this change is minimal, and should not affect the interpretation of the results when VAMPIRE® is used.

Feasibility of Automated Gonioscopy Imaging in Clinical Practice.

PRCIS: Automated gonioscopy provided good-quality images of the anterior chamber angle. There was a short learning curve for operators, and the examination was well tolerated by patients. Patients expressed a preference for automated gonioscopy compared with traditional gonioscopy. PURPOSE: The purpose of this study was to assess the feasibility of using a desktop automated gonioscopy camera in glaucoma clinics by examining patient tolerability, ease of use, and image quality and comparing patient preference compared with traditional gonioscopy. PATIENTS AND METHODS: A prospective study was conducted in a university hospital clinic. Traditional gonioscopy was performed followed by imaging of the iridocorneal angle (ICA) using the Nidek GS-1 camera by 2 glaucoma specialists. Participants were asked to rate the comfort of automated gonioscopy and which method they preferred. The clinicians graded the ease of acquisition for each patient, and the image quality was reviewed by a grader. RESULTS: Forty-three eyes of 25 participants were included. Sixty-eight percent of participants viewed automated gonioscopy as "extremely comfortable," and the remainder reported it "comfortable". Forty percent preferred automated gonioscopy compared with traditional gonioscopy, while 52% were equivocal. Clinicians scored 32% of participants as "somewhat difficult" to the image. In 46% of eyes, good-quality photographs were obtained for 360 degrees of the ICA. Only 1 eye had no parts of the ICA clearly visible. Seventy-four percent of eyes had at least half of the ICA clearly visible in all 4 quadrants. CONCLUSION: Automated gonioscopy provided good-quality images of the ICA for most patients. It was often not possible to image the entire 360 degrees at the first attempt, but the examination was comfortable for patients, and only 8% preferred traditional gonioscopy to the automated photographic examination.

Retinal vessel architecture and geometry are not impaired in normal-tension glaucoma.

To investigate the associations between retinal vessel parameters and normal-tension glaucoma (NTG). We conducted a case-control study with a prospective cohort, allowing to record 23 cases of NTG. We matched NTG patient with one primary open-angle glaucoma (POAG) and one control per case by age, systemic hypertension, diabetes, and refraction. Central retinal artery equivalent (CRAE), central retinal venule equivalent (CRVE), Arteriole-To-Venule ratio (AVR), Fractal Dimension and tortuosity of the vascular network were measured using VAMPIRE software. Our sample consisted of 23 NTG, 23 POAG, and 23 control individuals, with a median age of 65 years (25-75th percentile, 56-74). No significant differences were observed in median values for CRAE (130.6 µm (25-75th percentile, 122.8; 137.0) for NTG, 128.4 µm (124.0; 132.9) for POAG, and 135.3 µm (123.3; 144.8) for controls, P = .23), CRVE (172.1 µm (160.0; 188.3), 172.8 µm (163.3; 181.6), and 175.9 µm (167.6; 188.4), P = .43), AVR (0.76, 0.75, 0.74, P = .71), tortuosity and fractal parameters across study groups. Vascular morphological parameters were not significantly associated with retinal nerve fiber layer thickness or mean deviation for the NTG and POAG groups. Our results suggest that vascular dysregulation in NTG does not modify the architecture and geometry of the retinal vessel network.

Automatic Segmentation of Osteonal Microstructure in Human Cortical Bone Using Deep Learning: A Proof of Concept.

Cortical bone microstructure assessment in biological and forensic anthropology can assist with the estimation of age-at-death and animal-human differentiation, for example. Osteonal structures within cortical bone are the key feature under analysis, with osteon frequency and metric parameters providing crucial information for the assessment. Currently, the histomorphological assessment consists of a time-consuming manual process for which specific training is required. Our work investigates the feasibility of automatic analysis of human bone microstructure images through the application of deep learning. In this paper, we use a U-Net architecture to address the semantic segmentation of such images into three classes: intact osteons, fragmentary osteons, and background. Data augmentation was used to avoid overfitting. We evaluated our fully automatic approach using a sample of 99 microphotographs. The contours of intact and fragmentary osteons were traced manually to provide ground truth. The Dice coefficients were 0.73 for intact osteons, 0.38 for fragmented osteons, and 0.81 for background, giving an average of 0.64. The Dice coefficient of the binary classification osteon-background was 0.82. Although further refinement of the initial model and tests with larger datasets are needed, this study provides, to the best of our knowledge, the first proof of concept for the use of computer vision and deep learning for differentiating both intact and fragmentary osteons in human cortical bone. This approach has the potential to widen and facilitate the use of histomorphological assessment in the biological and forensic anthropology communities.

Assessment of Indices of Conjunctival Microvascular Function in Patients With and Without Obstructive Coronary Artery Disease.

BACKGROUND: Atherosclerotic heart disease often remains asymptomatic until presentation with a major adverse cardiovascular event. Primary preventive therapies improve outcomes, but conventional screening often misattributes risk. Vascular imaging can be utilised to detect atherosclerosis, but often involves ionising radiation. The conjunctiva is a readily accessible vascular network allowing non-invasive hemodynamic evaluation. AIM: To compare conjunctival microcirculatory function in patients with and without obstructive coronary artery disease. METHODS: We compared the conjunctival microcirculation of myocardial infarction patients (MI-cohort) to controls with no obstructive coronary artery disease (NO-CAD cohort). Conjunctival imaging was performed using a smartphone and slit-lamp biomicroscope combination. Microvascular indices of axial (Va) and cross-sectional (Vcs) velocity; blood flow rate (Q); and wall shear rate (WSR) were compared in all conjunctival vessels between 5 and 45 µm in diameter. RESULTS: A total of 127 patients were recruited (66 MI vs 61 NO-CAD) and 3602 conjunctival vessels analysed (2414 MI vs 1188 NO-CAD). Mean Va, Vcs and Q were significantly lower in the MI vs NO-CAD cohort (Va 0.50 ± 0.17 mm/s vs 0.55 ± 0.15 mm/s, p < 0.001; Vcs 0.35 ± 0.12 mm/s vs 0.38 ± 0.10 mm/s, p < 0.001; Q 154 ± 116 pl/s vs 198 ± 130 pl/s, p < 0.001). To correct for differences in mean vessel diameter, WSR was compared in 10-36 µm vessels (3268/3602 vessels) and was lower in the MI-cohort (134 ± 64 s-1 vs 140 ± 63 s-1, p = 0.002). CONCLUSIONS: Conjunctival microcirculatory alterations can be observed in patients with obstructive coronary artery disease. The conjunctival microvasculature merits further evaluation in cardiovascular risk screening.