Carotid Intima Media Thickness Reference Intervals for a Healthy Argentinean Population Aged 11-81 Years.

Reference intervals (RIs) of carotid intima media thickness (CIMT) from large healthy population are still lacking in Latin America. The aim of this study was to determine CIMT RIs in a cohort of 1012 healthy subjects from Argentina. We evaluated if RIs for males and females and for left and right carotids were necessary. Second, mean and standard deviation (SD) age-related equations were obtained for left, right, and average (left + right)/2) CIMT using parametric regression methods based on fractional polynomials, in order to obtain age-specific percentiles curves. Age-specific percentile curves were obtained. Males showed higher A-CIMT (0.577 ± 0.003 mm versus 0.566 ± 0.004 mm, P = 0.039) in comparison with females. For males, the equations were as follows: A-CIMT mean = 0.42 + 8.14 × 10-5⁎Age2; A-CIMT SD = 5.9 × 10-2 + 1.09 × 10-5⁎Age2. For females, they were as follows: A-CIMT mean = 0.40 + 8.20 × 10-5⁎Age2; A-CIMT SD = 4.67 × 10-2 + 1.63 × 10-5⁎Age2. Our study provides the largest database concerning RIs of CIMT in healthy people in Argentina. Specific RIs and percentiles of CIMT for children, adolescents, and adults are now available according to age and gender, for right and left common carotid arteries.

Validation of an Open-Source Tool for Measuring Carotid Lumen Diameter and Intima-Media Thickness.

In low- and middle-income regions, a relatively large number of deaths occur from cardiovascular disease or stroke. Carotid intima-media thickness (cIMT) and carotid lumen diameter (cLD) are strong indicators of cardiovascular event risk and stenosis severity, respectively. The interactive open-source software described here, Cimtool, is based on active contours for measuring these indicators in clinical practice and thus helping in preventive diagnosis and treatment. Cimtool was validated using carotid phantoms and real images obtained using ultrasound. Expert users measured cIMT and cLD in regular practice and also with Cimtool. The results obtained with Cimtool were then compared with the results for the manual approach in terms of measurement agreement, time spent on the measurements and usability. Intra-observer variability when using Cimtool was also analyzed. Statistical analysis revealed strong agreement between the manual method and Cimtool (p > 0.01 for cIMT and cLD). The correlation coefficient for both cIMT and cLD measurements was r > 0.9. Moreover, this software allowed the users to spend considerably less time on each measurement (3.5 min per study versus 50 s with Cimtool on average). An open-source, interactive, validated tool for measuring cIMT and cLD clinically was thus developed. Compared with the manual approach, Cimtool's straightforward measurement flow allows the user to spend less time per measurement and has less standard deviation. The coefficients of variation for measurements and intra-observer variability were lower than those reported for recent automated approaches, even with low-quality images.

Proliferative diabetic retinopathy characterization based on fractal features: Evaluation on a publicly available dataset.

PURPOSE: Diabetic retinopathy (DR) is one of the most widespread causes of preventable blindness in the world. The most dangerous stage of this condition is proliferative DR (PDR), in which the risk of vision loss is high and treatments are less effective. Fractal features of the retinal vasculature have been previously explored as potential biomarkers of DR, yet the current literature is inconclusive with respect to their correlation with PDR. In this study, we experimentally assess their discrimination ability to recognize PDR cases. METHODS: A statistical analysis of the viability of using three reference fractal characterization schemes - namely box, information, and correlation dimensions - to identify patients with PDR is presented. These descriptors are also evaluated as input features for training ℓ1 and ℓ2 regularized logistic regression classifiers, to estimate their performance. RESULTS: Our results on MESSIDOR, a public dataset of 1200 fundus photographs, indicate that patients with PDR are more likely to exhibit a higher fractal dimension than healthy subjects or patients with mild levels of DR (P≤1.3×10-2). Moreover, a supervised classifier trained with both fractal measurements and red lesion-based features reports an area under the ROC curve of 0.93 for PDR screening and 0.96 for detecting patients with optic disc neovascularizations. CONCLUSIONS: The fractal dimension of the vasculature increases with the level of DR. Furthermore, PDR screening using multiscale fractal measurements is more feasible than using their derived fractal dimensions. Code and further resources are provided at https://github.com/ignaciorlando/fundus-fractal-analysis.

Comments on "A Closed-Form Solution to Tensor Voting: Theory and Applications".

We comment on a paper that describes a closed-form formulation to Tensor Voting, a technique to perceptually group clouds of points, usually applied to infer features in images. The authors proved an analytic solution to the technique, a highly relevant contribution considering that the original formulation required numerical integration, a time-consuming task. Their work constitutes the first closed-form expression for the Tensor Voting framework. In this work we first observe that the proposed formulation leads to unexpected results which do not satisfy the constraints for a Tensor Voting output, hence they cannot be interpreted. Given that the closed-form expression is said to be an analytic equivalent solution, unexpected outputs should not be encountered unless there are flaws in the proof. We analyzed the underlying math to find which were the causes of these unexpected results. In this commentary we show that their proposal does not in fact provide a proper analytic solution to Tensor Voting and we indicate the flaws in the proof.