Comparison of retinal regions-of-interest imaged by OCT for the classification of intermediate AMD

To study whether it is possible to differentiate intermediate age-related macular degeneration (AMD) from healthy controls using partial optical coherence tomography (OCT) data, that is, restricting the input B-scans to certain pre-defined regions of interest (ROIs). A total of 15744 B-scans from 269 intermediate AMD patients and 115 normal subjects were used in this study (split on subject level in 80% train, 10% validation and 10% test). From each OCT B-scan, three ROIs were extracted: retina, complex between retinal pigment epithelium (RPE) and Bruch membrane (BM), and choroid (CHO). These ROIs were obtained using two different methods: masking and cropping. In addition to the six ROIs, the whole OCT B-scan and the binary mask corresponding to the segmentation of the RPE-BM complex were used. For each subset, a convolutional neural network (based on VGG16 architecture and pre-trained on ImageNet) was trained and tested. The performance of the models was evaluated using the area under the receiver operating characteristic (AUROC), accuracy, sensitivity, and specificity. All trained models presented an AUROC, accuracy, sensitivity, and specificity equal to or higher than 0.884, 0.816, 0.685, and 0.644, respectively. The model trained on the whole OCT B-scan presented the best performance (AUROC = 0.983, accuracy = 0.927, sensitivity = 0.862, specificity = 0.913). The models trained on the ROIs obtained with the cropping method led to significantly higher outcomes than those obtained with masking, with the exception of the retinal tissue, where no statistically significant difference was observed between cropping and masking (p = 0.47). This study demonstrated that while using the complete OCT B-scan provided the highest accuracy in classifying intermediate AMD, models trained on specific ROIs such as the RPE-BM complex or the choroid can still achieve high performance

Towards Transparent Linguistic Analysis of Dutch Newspaper Article Genres using Machine Learning

Systematic study of genre in newspapers sheds light on the development of journalism discourse. The genre conventions that can be discerned in a newspaper text signal the underlying discursive norms and practices of journalism as a profession. Historical newspapers are increasingly becoming available thanks to digital newspaper archives (in the Netherlands available through Delpher.nl), providing the opportunity for large-scale empirical research. However, the digital archives do not contain fine-grained genre information that is required for this purpose. Therefore, we use machine learning to automatically assign genre labels to newspaper articles.Machine learning facilitates substantial improvements to the outcomes of existing research by providing increased amounts of enriched data. However, the decision-making process of the machine learning pipeline needs to be verified. Our previous findings (Bilgin et al., 2018) show that accuracy scores alone are not enough to assess the performance of these pipelines and that making an informed choice not only empowers optimal study of the historical development of genre, but also increases the trustworthiness of the results. This work shows that employing a transparent approach driven by model interpretability facilitates fair comparison as well as validation of the underlying decision-making criteria of the machine learning pipelines. The criteria are presented in the form of important features, creating insights on interactions between genre-related linguistic features and bag-of-words features.</p

The inflammatory potential of diet is associated with the risk of age-related eye diseases

Background &amp; aims: Inflammation is involved in the pathogenesis of cataract, age-related macular degeneration (AMD), and possibly open-angle glaucoma (OAG). We assessed whether the inflammatory potential of diet (quantified using the dietary inflammatory index; DII) affects the incidence of these common blinding age-related eye diseases. Serum inflammation markers were investigated as possible mediators.Methods: Participants aged &gt;45 years were selected from the prospective, population-based Rotterdam Study. From 1991 onwards, every 4–5 years, participants underwent extensive eye examinations. At baseline, blood samples and dietary data (using food frequency questionnaires) were collected. The DII was adapted based on the data available. Of the 7436 participants free of eye diseases at baseline, 4036 developed incident eye diseases during follow-up (cataract = 2895, early-intermediate AMD = 891, late AMD = 81, OAG = 169). Results: The adapted DII (aDII) ranged from −4.26 (i.e., anti-inflammatory) to 4.53 (i.e., pro-inflammatory). A higher aDII was significantly associated with increased inflammation. A higher neutrophil-lymphocyte ratio (NLR) was associated with an increased risk of cataract and AMD. Additionally, complement component 3c (C3c) and systemic immune-inflammation index (SII) were associated with increased risks of cataract and late AMD, respectively. Every point increase in the aDII was associated with a 9% increased risk of cataract (Odds ratio [95% confidence interval]: 1.09 [1.04–1.14]). The NLR and C3c partly mediated this association. We also identified associations of the aDII with risk of AMD (early-intermediate AMD, OR [95% CI]: 1.11 [1.03–1.19]; late AMD, OR [95% CI]: 1.24 [1.02–1.53]). The NLR partly mediated these associations. The aDII was not associated with OAG. Conclusions: A pro-inflammatory diet was associated with increased risks of cataract and AMD. Particularly the NLR, a marker of subclinical inflammation, appears to be implicated. These findings are relevant for patients with AMD and substantiate the current recommendations to strive for a healthy lifestyle to prevent blindness.</p

Review of Large Carnivore Conservation: Integrating Science and Policy in the North American West

The management and conservation of large carnivores is of worldwide concern and is as much about human values, interactions, and governance as carnivore biology. Susan Clark and Murray Rutherford continue their work on coexisting with large carnivores ( Clark et al. 2005 ) with a new edited volume Large Carnivore Conservation: Integrating Science and Policy in the North American West . Large Carnivore Conservation that expands on the same themes as their previous work with case studies from Arizona to the Yukon. While focusing on the North American West, Clark and Rutherford hope to provide a holistic approach to carnivore management in general

Biopsy prostate cancer perineural invasion and tumour load are associated with positive posterolateral margins at radical prostatectomy:implications for planning of nerve-sparing surgery

Aims: Radical prostatectomy (RP) for prostate cancer is frequently complicated by erectile dysfunction and urinary incontinence. However, sparing of the nerve bundles adjacent to the posterolateral sides of the prostate reduces the number of complications at the risk of positive surgical margins. Preoperative selection of men eligible for safe, nerve-sparing surgery is therefore needed. Our aim was to identify pathological factors associated with positive posterolateral surgical margins in men undergoing bilateral nerve-sparing RP. Methods and results: Prostate cancer patients undergoing RP with standardised intra-operative surgical margin assessment according to the NeuroSAFE technique were included. Preoperative biopsies were reviewed for grade group (GG), cribriform and/or intraductal carcinoma (CR/IDC), perineural invasion (PNI), cumulative tumour length and extraprostatic extension (EPE). Of 624 included patients, 573 (91.8%) received NeuroSAFE bilaterally and 51 (8.2%) unilaterally, resulting in a total of 1197 intraoperative posterolateral surgical margin assessments. Side-specific biopsy findings were correlated to ipsilateral NeuroSAFE outcome. Higher biopsy GG, CR/IDC, PNI, EPE, number of positive biopsies and cumulative tumour length were all associated with positive posterolateral margins. In multivariable bivariate logistic regression, ipsilateral PNI [odds ratio (OR) = 2.98, 95% confidence interval (CI) = 1.62–5.48; P &lt; 0.001] and percentage of positive cores (OR = 1.18, 95% CI = 1.08–1.29; P &lt; 0.001) were significant predictors for a positive posterolateral margin, while GG and CR/IDC were not. Conclusions: Ipsilateral PNI and percentage of positive cores were significant predictors for a positive posterolateral surgical margin at RP. Biopsy PNI and tumour volume can therefore support clinical decision-making on the level of nerve-sparing surgery in prostate cancer patients.</p

Performance of classification systems for age-related macular degeneration in the rotterdam study

Purpose: To compare frequently used classification systems for age-related macular degeneration(AMD) in their abilty to predictlate AMD. Methods:Intotal,9066participantsfromthepopulation-basedRotterdamStudywere followedupforprogressionofAMDduringastudyperiodupto30years.AMDlesions weregradedoncolorfundusphotographsafterconfirmationonotherimagemodalities andgroupedatbaselineaccordingtosixclassificationsystems.LateAMDwasdefinedas geographicatrophyorchoroidalneovascularization.Incidencerate(IR)andcumulative incidence(CuI)oflateAMDwerecalculated,andKaplan-Meierplotsandareaunderthe operating characteristics curves(AUCs)wereconstructed. Results: A total of 186 persons developed incident late AMD during a mean follow-up timeof8.7years.TheAREDSsimplifiedscaleshowedthehighestIRforlateAMDat104 cases/1000 py for ages 75 years. The 3-Continent harmonization classification provided the most stable progression. Drusen area >10% ETDRS grid (hazard ratio 30.05, 95% confidence interval [CI] 19.25–46.91) was most prognostic of progression. The highest AUC of late AMD (0.8372, 95% CI: 0.8070-0.8673) was achieved when all AMD features present at base line were included. Conclusions: Highest turnover rates from intermediate to late AMD were provided by the AREDS simplified scale and the Rotterdam classification. The 3-Continent harmonization classification showed the most stable progression. All features, especially drusenarea,contribute to late AMD prediction. Translational Relevance: Findings will help stakeholders select appropriate classification systems for screening,deep learning algorithms, or trials