Structural Change Can Be Detected in Advanced-Glaucoma Eyes.

PurposeTo compare spectral-domain optical coherence tomography (SD-OCT) standard structural measures and a new three-dimensional (3D) volume optic nerve head (ONH) change detection method for detecting change over time in severely advanced-glaucoma (open-angle glaucoma [OAG]) patients.MethodsThirty-five eyes of 35 patients with very advanced glaucoma (defined as a visual field mean deviation < -21 dB) and 46 eyes of 30 healthy subjects to estimate aging changes were included. Circumpapillary retinal fiber layer thickness (cpRNFL), minimum rim width (MRW), and macular retinal ganglion cell-inner plexiform layer (GCIPL) thicknesses were measured using the San Diego Automated Layer Segmentation Algorithm (SALSA). Progression was defined as structural loss faster than 95th percentile of healthy eyes. Three-dimensional volume ONH change was estimated using the Bayesian-kernel detection scheme (BKDS), which does not require extensive retinal layer segmentation.ResultsThe number of progressing glaucoma eyes identified was highest for 3D volume BKDS (13, 37%), followed by GCPIL (11, 31%), cpRNFL (4, 11%), and MRW (2, 6%). In advanced-OAG eyes, only the mean rate of GCIPL change reached statistical significance, -0.18 μm/y (P = 0.02); the mean rates of cpRNFL and MRW change were not statistically different from zero. In healthy eyes, the mean rates of cpRNFL, MRW, and GCIPL change were significantly different from zero. (all P < 0.001).ConclusionsGanglion cell-inner plexiform layer and 3D volume BKDS show promise for identifying change in severely advanced glaucoma. These results suggest that structural change can be detected in very advanced disease. Longer follow-up is needed to determine whether changes identified are false positives or true progression

Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

Purpose:To apply computational techniques to wide-angle swept-source optical coherence tomography (SS-OCT) images to identify novel, glaucoma-related structural features and improve detection of glaucoma and prediction of future glaucomatous progression. Methods:Wide-angle SS-OCT, OCT circumpapillary retinal nerve fiber layer (cpRNFL) circle scans spectral-domain (SD)-OCT, standard automated perimetry (SAP), and frequency doubling technology (FDT) visual field tests were completed every 3 months for 2 years from a cohort of 28 healthy participants (56 eyes) and 93 glaucoma participants (179 eyes). RNFL thickness maps were extracted from segmented SS-OCT images and an unsupervised machine learning approach based on principal component analysis (PCA) was used to identify novel structural features. Area under the receiver operating characteristic curve (AUC) was used to assess diagnostic accuracy of RNFL PCA for detecting glaucoma and progression compared to SAP, FDT, and cpRNFL measures. Results:The RNFL PCA features were significantly associated with mean deviation (MD) in both SAP (R2 = 0.49, P < 0.0001) and FDT visual field testing (R2 = 0.48, P < 0.0001), and with mean circumpapillary RNFL thickness (cpRNFLt) from SD-OCT (R2 = 0.58, P < 0.0001). The identified features outperformed each of these measures in detecting glaucoma with an AUC of 0.95 for RNFL PCA compared to an 0.90 for mean cpRNFLt (P = 0.09), 0.86 for SAP MD (P = 0.034), and 0.83 for FDT MD (P = 0.021). Accuracy in predicting progression was also significantly higher for RNFL PCA compared to SAP MD, FDT MD, and mean cpRNFLt (P = 0.046, P = 0.007, and P = 0.044, respectively). Conclusions:A computational approach can identify structural features that improve glaucoma detection and progression prediction

An examination of Australian newspaper coverage of the link between alcohol and cancer 2005 to 2013

Published online: 24 July 2017Background: Alcohol is a Class-1 carcinogen but public awareness of the link between alcohol and cancer is low. The news media is a popular, readily-accessible source of health information and plays a key role in shaping public opinion and influencing policy-makers. Examination of how the link between alcohol and cancer is presented in Australian print media could inform public health advocacy efforts to raise awareness of this modifiable cancer risk factor. Method: This study provides a summative qualitative content analysis of 1502 articles that included information about a link between alcohol and cancer, as reported within Australian newspaper media (2005–2013). We use descriptive statistics to examine the prominence of reports, the nature and content of claims regarding the link between alcohol and cancer, and the source of information noted in each article. Results: Articles were distributed throughout newspapers, most appearing within the main (first) section. The link between alcohol and cancer tended not to appear early in articles, and rarely featured in headlines. 95% of articles included a claim that alcohol causes cancer, 5% that alcohol prevented or did not cause cancer, 1% included both. Generally, the amount of alcohol that would cause or prevent cancer was unspecified or open to subjective interpretation. Coverage increased over time, primarily within community/free papers. The claim that alcohol causes cancer often named a specific cancer, did not name a specific alcohol, was infrequently the focus of articles (typically subsumed within an article on general health issues), and cited various health-promoting (including advocacy) organisations as information sources. Articles that included the converse also tended not to focus on that point, often named a specific type of alcohol, and most cited research institutions or generic ‘research’ as sources. Half of all articles involved repetition of materials, and most confirmed that alcohol caused cancer. Conclusions: Information about a link between alcohol and cancer is available in the Australian newsprint media, but may be hidden within and thus overshadowed by other health-related stories. Strategic collaboration between health promoting organisations, and exploitation of ‘churnalism’ and journalists’ preferences for ready-made ‘copy’ may facilitate increased presence and accuracy of the alcohol-cancer message.Jaklin Eliott, Andrew John Forster, Joshua McDonough, Kathryn Bowd and Shona Crab

Direct and indirect effects of fire on microbial communities in a pyrodiverse dry-sclerophyll forest

Fire is one of the predominant drivers of the structural and functional dynamics of forest ecosystems. In recent years, novel fire regimes have posed a major challenge to the management of pyrodiverse forests. While previous research efforts have focused on quantifying the impacts of fire on above-ground forest biodiversity, how microbial communities respond to fire is less understood, despite their functional significance. Here, we describe the effects of time since fire, fire frequency and their interaction on soil and leaf litter fungal and bacterial communities from the pyrodiverse, Eucalyptus pilularis forests of south-eastern Australia. Using structural equation models, we also elucidate how fire can influence these communities both directly and indirectly through biotic-abiotic interactions. Our results demonstrate that fire is a key driver of litter and soil bacterial and fungal communities, with effects most pronounced for soil fungal communities. Notably, recently burnt forest hosted lower abundances of symbiotic ectomycorrhizal fungi and Acidobacteria in the soil, and basidiomycetous fungi and Actinobacteriota in the litter. Compared with low fire frequencies, high fire frequency increased soil fungal plant pathogens, but reduced Actinobacteriota. The majority of fire effects on microbial communities were mediated by fire-induced changes in litter and soil abiotic properties. For instance, recent and more frequent fire was associated with reduced soil sulphur, which led to an increase in soil fungal plant pathogens and saprotrophic fungi in these sites. Pathogenic fungi also increased in recently burnt forests that had a low fire frequency, mediated by a decline in litter carbon and an increase in soil pH in these sites. Synthesis. Our findings indicate that predicted increases in the frequency of fire may select for specific microbial communities directly and indirectly through ecological interactions, which may have functional implications for plants (increase in pathogens, decrease in symbionts), decomposition rates (declines in Actinobacteriota and Acidobacteriota) and carbon storage (decrease in ectomycorrhizal fungi). In the face of predicted shifts in wildfire regimes, which may exacerbate fire-induced changes in microbial communities, adaptive fire management and monitoring is required to address the potential functional implications of fire-altered microbial communities

Glaucomatous Patterns in Frequency Doubling Technology (FDT) Perimetry Data Identified by Unsupervised Machine Learning Classifiers

Purpose: The variational Bayesian independent component analysis-mixture model (VIM), an unsupervised machine-learning classifier, was used to automatically separate Matrix Frequency Doubling Technology (FDT) perimetry data into clusters of healthy and glaucomatous eyes, and to identify axes representing statistically independent patterns of defect in the glaucoma clusters. Methods: FDT measurements were obtained from 1,190 eyes with normal FDT results and 786 eyes with abnormal FDT results from the UCSD-based Diagnostic Innovations in Glaucoma Study (DIGS) and African Descent and Glaucoma Evaluation Study (ADAGES). For all eyes, VIM input was 52 threshold test points from the 24-2 test pattern, plus age. Results: FDT mean deviation was -1.00 dB (S.D. = 2.80 dB) and -5.57 dB (S.D. = 5.09 dB) in FDT-normal eyes and FDT-abnormal eyes, respectively (p<0.001). VIM identified meaningful clusters of FDT data and positioned a set of statistically independent axes through the mean of each cluster. The optimal VIM model separated the FDT fields into 3 clusters. Cluster N contained primarily normal fields (1109/1190, specificity 93.1%) and clusters G(1) and G(2) combined, contained primarily abnormal fields (651/786, sensitivity 82.8%). For clusters G(1) and G(2) the optimal number of axes were 2 and 5, respectively. Patterns automatically generated along axes within the glaucoma clusters were similar to those known to be indicative of glaucoma. Fields located farther from the normal mean on each glaucoma axis showed increasing field defect severity. Conclusions: VIM successfully separated FDT fields from healthy and glaucoma eyes without a priori information about class membership, and identified familiar glaucomatous patterns of loss.open0

Integration and fusion of standard automated perimetry and optical coherence tomography data for improved automated glaucoma diagnostics

<p>Abstract</p> <p>Background</p> <p>The performance of glaucoma diagnostic systems could be conceivably improved by the integration of functional and structural test measurements that provide relevant and complementary information for reaching a diagnosis. The purpose of this study was to investigate the performance of data fusion methods and techniques for simple combination of Standard Automated Perimetry (SAP) and Optical Coherence Tomography (OCT) data for the diagnosis of glaucoma using Artificial Neural Networks (ANNs).</p> <p>Methods</p> <p>Humphrey 24-2 SITA standard SAP and StratusOCT tests were prospectively collected from a randomly selected population of 125 healthy persons and 135 patients with glaucomatous optic nerve heads and used as input for the ANNs. We tested commercially available standard parameters as well as novel ones (fused OCT and SAP data) that exploit the spatial relationship between visual field areas and sectors of the OCT peripapillary scan circle. We evaluated the performance of these SAP and OCT derived parameters both separately and in combination.</p> <p>Results</p> <p>The diagnostic accuracy from a combination of fused SAP and OCT data (95.39%) was higher than that of the best conventional parameters of either instrument, i.e. SAP Glaucoma Hemifield Test (p < 0.001) and OCT Retinal Nerve Fiber Layer Thickness ≥ 1 quadrant (p = 0.031). Fused OCT and combined fused OCT and SAP data provided similar Area under the Receiver Operating Characteristic Curve (AROC) values of 0.978 that were significantly larger (p = 0.047) compared to ANNs using SAP parameters alone (AROC = 0.945). On the other hand, ANNs based on the OCT parameters (AROC = 0.970) did not perform significantly worse than the ANNs based on the fused or combined forms of input data. The use of fused input increased the number of tests that were correctly classified by both SAP and OCT based ANNs.</p> <p>Conclusions</p> <p>Compared to the use of SAP parameters, input from the combination of fused OCT and SAP parameters, and from fused OCT data, significantly increased the performance of ANNs. Integrating parameters by including a priori relevant information through data fusion may improve ANN classification accuracy compared to currently available methods.</p

Effects of Age on Optical Coherence Tomography Measurements of Healthy Retinal Nerve Fiber Layer, Macula, and Optic Nerve Head

Purpose—To determine the effects of age on global and sectoral peripapillary retinal nerve fiber layer (RNFL), macular thicknesses and optic nerve head (ONH) parameters in healthy subjects using optical coherence tomography (OCT). Design—Retrospective, cross-sectional observational study. Participants—226 eyes from 124 healthy subjects were included. Methods—Healthy subjects were scanned using the Fast RNFL, Fast Macula, and Fast ONH scan patterns on a Stratus OCT. All global and sectoral RNFL and macular parameters and global ONH parameters were modeled in terms of age using linear mixed effects models. Normalized slopes were also calculated by dividing the slopes by the mean value of the OCT parameter for inter-parameter comparison. Main Outcome Measures—Slope of each OCT parameter across age. Results—All global and sectoral RNFL thickness parameters statistically significantly decreased with increasing age, except for the temporal quadrant and clock hours 8-10, which were not statistically different from a slope of zero. Highest absolute slopes were in the inferior and superior quadrant RNFL and clock hour 1 (superior nasal). Normalized slopes showed similar rate in all sectors except for the temporal clock hours (8-10). All macular thickness parameters statistically significantly decreased with increasing age, except for the central fovea sector, which had a slight positive slope that was not statistically significant. The nasal outer sector had the greatest absolute slope. Normalized macular slope in the outer ring was similar to the normalized slopes in the RNFL. Normalized inner ring had shallower slope than the outer ring with similar rate in all quadrants. Disc area remained nearly constant across the ages, but cup area increased and rim area decreased with age, both of which were statistically significant. Conclusions—Global and regional changes due to the effects of age on RNFL, macula and ONH OCT measurements should be considered when assessing eyes over time.National Institutes of Health (U.S.) (R01-EY13178-09)National Institutes of Health (U.S.) (R01-EY11289-23)National Institutes of Health (U.S.) (P30-EY008098

Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs

The ability of deep learning architectures to identify glaucomatous optic neuropathy (GON) in fundus photographs was evaluated. A large database of fundus photographs (n = 14,822) from a racially and ethnically diverse group of individuals (over 33% of African descent) was evaluated by expert reviewers and classified as GON or healthy. Several deep learning architectures and the impact of transfer learning were evaluated. The best performing model achieved an overall area under receiver operating characteristic (AUC) of 0.91 in distinguishing GON eyes from healthy eyes. It also achieved an AUC of 0.97 for identifying GON eyes with moderate-to-severe functional loss and 0.89 for GON eyes with mild functional loss. A sensitivity of 88% at a set 95% specificity was achieved in detecting moderate-to-severe GON. In all cases, transfer improved performance and reduced training time. Model visualizations indicate that these deep learning models relied on, in part, anatomical features in the inferior and superior regions of the optic disc, areas commonly used by clinicians to diagnose GON. The results suggest that deep learning-based assessment of fundus images could be useful in clinical decision support systems and in the automation of large-scale glaucoma detection and screening programs

Retinal nerve fibre layer thickness profile in normal eyes using third-generation optical coherence tomography

Aims To establish four normal retinal nerve fibre layer (RNFL) thickness radial profiles based on third-generation optical coherence tomography (OCT) and to compare them with previously reported histologic measurements.Methods A total of 20 normal eyes were studied. A circular scan was adjusted to the size of the optic disc and three scans were performed with this radius and every 200 mu m thereafter, up to a distance of 1400 mu m. Four different radial sections (superotemporal, superonasal, inferonasal, and inferotemporal) were studied to establish RNFL thickness OCT profiles. Additionally, two radial scans orientated at 45 and 1351 crossing the optic disc centre were performed in six of 20 eyes, and RNFL thickness was measured at disc margin.Results Quadrant location and distance from disc margin interaction in RNFL thickness was statistically significant (P < 0.001). the RNFL thickness decreased (P < 0.001) as the distance from the disc margin increased for all sections. the measurements automatically generated by the OCT built-in software were thinner (P < 0.001) than histologic ones close to the disc margin.Conclusions Four normal OCT RNFL profiles were established and compared with histological data obtained from the same area. RNFL measurements assessed by OCT 3 were significantly thinner close to the optic disc margin.Hosp Olhos Araraquara, Glaucoma Sect, BR-14802530 Araraquara, SP, BrazilHosp Olhos Araraquara, Retina Diagnost & Treatment Div, BR-14802530 Araraquara, SP, BrazilUniversidade Federal de São Paulo, São Paulo, BrazilUSP, Inst Fis Sao Carlos, Sao Carlos, SP, BrazilUniv So Calif, Doheny Eye Inst, Dept Ophthalmol, Los Angeles, CA USAUniversidade Federal de São Paulo, São Paulo, BrazilWeb of Scienc