Uncovering of intraspecies macular heterogeneity in cynomolgus monkeys using hybrid machine learning optical coherence tomography image segmentation

The fovea is a depression in the center of the macula and is the site of the highest visual acuity. Optical coherence tomography (OCT) has contributed considerably in elucidating the pathologic changes in the fovea and is now being considered as an accompanying imaging method in drug development, such as antivascular endothelial growth factor and its safety profiling. Because animal numbers are limited in preclinical studies and automatized image evaluation tools have not yet been routinely employed, essential reference data describing the morphologic variations in macular thickness in laboratory cynomolgus monkeys are sparse to nonexistent. A hybrid machine learning algorithm was applied for automated OCT image processing and measurements of central retina thickness and surface area values. Morphological variations and the effects of sex and geographical origin were determined. Based on our findings, the fovea parameters are specific to the geographic origin. Despite morphological similarities among cynomolgus monkeys, considerable variations in the foveolar contour, even within the same species but from different geographic origins, were found. The results of the reference database show that not only the entire retinal thickness, but also the macular subfields, should be considered when designing preclinical studies and in the interpretation of foveal data

Validation of automated artificial intelligence segmentation of optical coherence tomography images

PURPOSE To benchmark the human and machine performance of spectral-domain (SD) and swept-source (SS) optical coherence tomography (OCT) image segmentation, i.e., pixel-wise classification, for the compartments vitreous, retina, choroid, sclera. METHODS A convolutional neural network (CNN) was trained on OCT B-scan images annotated by a senior ground truth expert retina specialist to segment the posterior eye compartments. Independent benchmark data sets (30 SDOCT and 30 SSOCT) were manually segmented by three classes of graders with varying levels of ophthalmic proficiencies. Nine graders contributed to benchmark an additional 60 images in three consecutive runs. Inter-human and intra-human class agreement was measured and compared to the CNN results. RESULTS The CNN training data consisted of a total of 6210 manually segmented images derived from 2070 B-scans (1046 SDOCT and 1024 SSOCT; 630 C-Scans). The CNN segmentation revealed a high agreement with all grader groups. For all compartments and groups, the mean Intersection over Union (IOU) score of CNN compartmentalization versus group graders' compartmentalization was higher than the mean score for intra-grader group comparison. CONCLUSION The proposed deep learning segmentation algorithm (CNN) for automated eye compartment segmentation in OCT B-scans (SDOCT and SSOCT) is on par with manual segmentations by human graders

Unraveling the deep learning gearbox in optical coherence tomography image segmentation towards explainable artificial intelligence

Machine learning has greatly facilitated the analysis of medical data, while the internal operations usually remain intransparent. To better comprehend these opaque procedures, a convolutional neural network for optical coherence tomography image segmentation was enhanced with a Traceable Relevance Explainability (T-REX) technique. The proposed application was based on three components: ground truth generation by multiple graders, calculation of Hamming distances among graders and the machine learning algorithm, as well as a smart data visualization ('neural recording'). An overall average variability of 1.75% between the human graders and the algorithm was found, slightly minor to 2.02% among human graders. The ambiguity in ground truth had noteworthy impact on machine learning results, which could be visualized. The convolutional neural network balanced between graders and allowed for modifiable predictions dependent on the compartment. Using the proposed T-REX setup, machine learning processes could be rendered more transparent and understandable, possibly leading to optimized applications

Safety and Feasibility of a Novel Sparse Optical Coherence Tomography Device for Patient-Delivered Retina Home Monitoring

Purpose To study a novel and fast optical coherence tomography (OCT) device for home-based monitoring in age-related macular degeneration (AMD) in a small sample yielding sparse OCT (spOCT) data and to compare the device to a commercially available reference device. Methods In this prospective study, both eyes of 31 participants with AMD were included. The subjects underwent scanning with an OCT prototype and a spectral-domain OCT to compare the accuracy of the central retinal thickness (CRT) measurements. Results Sixty-two eyes in 31 participants (21 females and 10 males) were included. The mean age was 79.6 years (age range, 69-92 years). The mean difference in the CRT measurements between the devices was 4.52 μm (SD ± 20.0 μm; range, -65.6 to 41.5 μm). The inter- and intrarater reliability coefficients of the OCT prototype were both >0.95. The laser power delivered was <0.54 mW for spOCT and <1.4 mW for SDOCT. No adverse events were reported, and the visual acuity before and after the measurements was stable. Conclusion This study demonstrated the safety and feasibility of this home-based OCT monitoring under real-life conditions, and it provided evidence for the potential clinical benefit of the device. Translational Relevance The newly developed spOCT is a valid and readily available retina scanner. It could be applied as a portable self-measuring OCT system. Its use may facilitate the sustainable monitoring of chronic retinal diseases by providing easily accessible and continuous retinal monitoring

Racial differences in systemic sclerosis disease presentation: a European Scleroderma Trials and Research group study

Objectives. Racial factors play a significant role in SSc. We evaluated differences in SSc presentations between white patients (WP), Asian patients (AP) and black patients (BP) and analysed the effects of geographical locations.Methods. SSc characteristics of patients from the EUSTAR cohort were cross-sectionally compared across racial groups using survival and multiple logistic regression analyses.Results. The study included 9162 WP, 341 AP and 181 BP. AP developed the first non-RP feature faster than WP but slower than BP. AP were less frequently anti-centromere (ACA; odds ratio (OR) = 0.4, P &lt; 0.001) and more frequently anti-topoisomerase-I autoantibodies (ATA) positive (OR = 1.2, P = 0.068), while BP were less likely to be ACA and ATA positive than were WP [OR(ACA) = 0.3, P &lt; 0.001; OR(ATA) = 0.5, P = 0.020]. AP had less often (OR = 0.7, P = 0.06) and BP more often (OR = 2.7, P &lt; 0.001) diffuse skin involvement than had WP.AP and BP were more likely to have pulmonary hypertension [OR(AP) = 2.6, P &lt; 0.001; OR(BP) = 2.7, P = 0.03 vs WP] and a reduced forced vital capacity [OR(AP) = 2.5, P &lt; 0.001; OR(BP) = 2.4, P &lt; 0.004] than were WP. AP more often had an impaired diffusing capacity of the lung than had BP and WP [OR(AP vs BP) = 1.9, P = 0.038; OR(AP vs WP) = 2.4, P &lt; 0.001]. After RP onset, AP and BP had a higher hazard to die than had WP [hazard ratio (HR) (AP) = 1.6, P = 0.011; HR(BP) = 2.1, P &lt; 0.001].Conclusion. Compared with WP, and mostly independent of geographical location, AP have a faster and earlier disease onset with high prevalences of ATA, pulmonary hypertension and forced vital capacity impairment and higher mortality. BP had the fastest disease onset, a high prevalence of diffuse skin involvement and nominally the highest mortality

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Vasoactive peptides as biomarkers for the prediction of retinopathy of prematurity.

BACKGROUND Retinopathy of prematurity (ROP) is a major complication in preterm infants. We assessed if plasma levels of midregional pro-atrial natriuretic peptide (MR-proANP) and C-terminal pro-endothelin-1 (CT-proET1) serve as early markers for subsequent ROP development in preterm infants <32 weeks gestation. METHODS Prospective, two-centre, observational cohort study. MR-proANP and CT-proET1 were measured on day seven of life. Associations with ROP ≥ stage II were investigated by univariable and multivariable logistic regression models. RESULTS We included 224 infants born at median (IQR) 29.6 (27.1-30.8) weeks gestation and birth weight of 1160 (860-1435) g. Nineteen patients developed ROP ≥ stage II. MR-proANP and CT-proET1 levels were higher in these infants (median (IQR) 864 (659-1564) pmol/L and 348 (300-382) pmol/L, respectively) compared to infants without ROP (median (IQR) 299 (210-502) pmol/L and 196 (156-268) pmol/L, respectively; both P < 0.001). MR-proANP and CT-proET1 levels were significantly associated with ROP ≥ stage II in univariable logistic regression models and after adjusting for co-factors, including gestational age and birth weight z-score. CONCLUSIONS MR-proANP and CT-proET1 measured on day seven of life are strongly associated with ROP ≥ stage II in very preterm infants and might improve early prediction of ROP in the future. IMPACT Plasma levels of midregional pro-atrial natriuretic peptide and C-terminal pro-endothelin-1 measured on day seven of life in very preterm infants show a strong association with development of retinopathy of prematurity ≥ stage II. Both biomarkers have the potential to improve early prediction of retinopathy of prematurity. Vasoactive peptides might allow to reduce the proportion of screened infants substantially

En face optical coherence tomography imaging ellipsoid zone regeneration in laser-induced and solar maculopathies

The purpose of the study was to analyze imaging findings in spectral domain en face optical coherence tomography (SD OCT) in patients with laser-induced and solar maculopathies focusing on the possible regeneration of the ellipsoid zone. In a retrospective case series of 3 patients (4 eyes) with solar maculopathy and 2 patients (3 eyes) with laser-induced maculopathy who underwent a comprehensive ocular examination, ellipsoid zone (EZ) was segmented from SD OCT data. Evaluation of EZ in en face OCT revealed a hyporeflective lesion surrounded by a hyperreflective border. The area of EZ alteration was measured manually in en face OCT. All patients showed partial EZ regeneration. Mean EZ alteration decreased from 0.12 mm$^{2}$ (range: 0.05-0.32) at baseline to 0.07 mm$^{2}$ (range: 0.01-0.22) at last follow-up (p = 0.018, mean follow-up: 372 days; range: 115-592). Mean best visual acuity (BVA) improved from 20/36 at baseline to 20/30 (p = 0.018). In conclusion, en face OCT imaging clearly delineated the area of EZ alteration in patients with laser-induced and solar maculopathies. Follow-up showed significant reformation of the EZ as well as improvement of BVA