Retinal microvascular biomarker extraction on fundus images from the Maastricht study using supervised deep learning

Retinal fundus imaging enables detailed visualization of the microvascular structure in the retina of the human eye. Geometrical features, related to vessel caliber, tortuosity and bifurcations, have been identified as potential biomarkers for a variety of A.J, including (pre)diabetes and hypertension. A pipeline of automated unsupervised image analysis methods for extraction of such features from retinal fundus images has previously been developed and evaluated [1]. However, the current computationally expensive pipeline takes 24 minutes to process a single image, which impedes implementation in a screening setting. In the present work, we approximate the pipeline using a deep neural network that enables processing of a single image in a few seconds. We use a model that contains approximately 23 million trainable parameters and we train it with color fundus images from the Maastricht Study, a population-based cohort study with extensive phenotyping, that focuses on the etiology, complications and comorbidities of Type 2 Diabetes Mellitus. The set comprises 10668 images from 2872 subjects taken from both left and right eyes and are centered either on the fovea or on the optic disc. We design the model to simultaneously output four global biomarkers that represent key vessel geometries: Central Retinal Arteriolar Equivalent (CRAE), Central Retinal Venular Equivalent (CRVE), global tortuosity and asymmetry ratio of the bifurcations. The outputs from the original pipeline are used as training labels. Eighty percent of the data is used for training, while the remainder is used to evaluate the performance of the model. We obtain a substantial speed-up, requiring only 5 seconds to process an image. Intraclass correlation coefficient between the predictions of the model and the results of the pipeline showed strong correlation (0.86 - 0.91) for three of four biomarkers and moderate correlation (0.42) for one biomarker. To visualize what regions in the fundus images contribute to the model predictions, we create class activation maps. The maps show clearly that the local activations overlap with the vascular tree. It is able to differentiate between arterioles and venules around the optic disc when predicting CRAE and CRVE. Moreover, local high and low tortuous regions are clearly identified, verifying that the model is sensitive to key structures in the retina

The Prague Spring Competition In The Bassoon Cathegory

This thesis offers a complex overview of the Prague Spring International Music Competition with a detailed focus on the basssoon category

Physical Activity Is Associated With Glucose Tolerance Independent of Microvascular Function: The Maastricht Study

Context and Objective: Moderate-to-vigorous physical activity (MVPA) and physical fitness (PF) are positively associated with glucose tolerance. Such associations may be partly conditioned by microvascular function, which is a common correlate to MVPA, PF, and glucose tolerance. To test this hypothesis, the present study sought to investigate independent associations of MVPA and PF with glucose tolerance and to what extent these associations are mediated by microvascular function. Design, Setting, Participants, and Outcome Measures: Data from The Maastricht Study were used (n = 512 for MVPA and n = 488 for PF analyses; mean age, 59 [SD = 9] y, 52 % men). Glucose tolerance was assessed by 2-hour postload plasma glucose levels (2hPG). The total number of weekly hours of MVPA was estimated with the Community Healthy Activities Model Program for Seniors questionnaire. Walking speed during the 6-minute walk test was used to evaluate PF. Microvascular function was determined by postocclusive capillary recruitment and flowmotion with capillaroscopy and laser Doppler flowmetry in skin microcirculation. Results: In univariate analyses, MVPA, PF, and microvascular function variables were associated with 2hPG. MVPA (n = 512, β = −0.056, P = .019) and PF (n = 488, β = −0.368, P = .006) remained associated with 2hPG after adjustment for established cardio-metabolic risk factors and history of cardiovascular disease; addition of microvascular function variables as potential mediators did not materially change the associations of MVPA (β = −0.054, P = .024) and PF (β = −0.364, P = .006) with 2hPG. No mediation effects of microvascular function variables were detected. Conclusions: MVPA and PF were independently associated with 2hPG, irrespective of established risk factors and generalized microvascular function. The possibility that specific microvascular functions, eg, insulin-mediated vasodilation, influence the association of MVPA and PF with 2hPG needs further investigation. Abstract In a large population-based cohort study, microvascular function does not mediate the association of MVPA and PF with glucose tolerance, irrespective of established cardiometabolic risk factors