Classification of calcified regions in atherosclerotic lesions of the carotid artery in computed tomography angiography images

The identification of atherosclerotic plaque components, extraction and analysis of their morphology represent an important role towards the prediction of cardiovascular events. In this article, the classification of regions representing calcified components in computed tomography angiography (CTA) images of the carotid artery is tackled. The proposed classification model has two main steps: the classification per pixel and the classification per region. Features extracted from each pixel inside the carotid artery are submitted to four classifiers in order to determine the correct class, i.e. calcification or non-calcification. Then, geometrical and intensity features extracted from each candidate region resulting from the pixel classification step are submitted to the classification per region in order to determine the correct regions of calcified components. In order to evaluate the classification accuracy, the results of the proposed classification model were compared against ground truths of calcifications obtained from micro-computed tomography images of excised atherosclerotic plaques that were registered with in vivo CTA images. The average values of the Spearman correlation coefficient obtained by the linear discriminant classifier were higher than 0.80 for the relative volume of the calcified components. Moreover, the average values of the absolute error between the relative volumes of the classified calcium regions and the ones calculated from the corresponding ground truths were lower than 3%. The new classification model seems to be adequate as an auxiliary diagnostic tool for identifying calcifications and allowing their morphology assessment. (c) 2019, Springer-Verlag London Ltd., part of Springer Nature

Manifestaciones Clínicas del Síndrome Post-Covid 19

En marzo del año 2020 fue declarada por la Organización Mundial de la Salud una pandemia provocada por la COVID-19, enfermedad producida por un nuevo coronavirus llamado SARS-Cov-2 que ha provocado la infección de millones de personas alrededor de todo el orbe. La mayor parte de los pacientes convalecientes del COVID-19 refieren una serie de manifestaciones clínicas después de la fase aguda de la enfermedad que pueden ser muy variables y provocar la disfunción de uno o varios órganos y a este grupo de síntomas se le conoce como el síndrome post-Covid-19.Debido al aumento de personas que padecen este síndrome se hace necesario por las autoridades sanitarias diseñar mecanismos que permitan una asistencia médica con grupos multidisciplinarios bien coordinados para evitar un aumento de la progresión de los síntomas en el paciente

Automatic segmentation of the lumen region in intravascular images of the coronary artery

Image assessment of the arterial system plays an important role in the diagnosis of cardiovascular diseases. The segmentation of the lumen and media-adventitia in intravascular (IVUS) images of the coronary artery is the first step towards the evaluation of the morphology of the vessel under analysis and theidentification of possible atherosclerotic lesions. In this study, a fully automatic method for the segmentation of the lumen in IVUS images of the coronary artery is presented. The proposed method relies on theK-means algorithm and the mean roundness to identify the region corresponding to the potential lumen.An approach to identify and eliminate side branches on bifurcations is also proposed to delimit the areawith the potential lumen regions. Additionally, an active contour model is applied to refine the contourof the lumen region. In order to evaluate the segmentation accuracy, the results of the proposed methodwere compared against manual delineations made by two experts in 326 IVUS images of the coronaryartery. The average values of the Jaccard measure, Hausdorff distance, percentage of area difference andDice coefficient were 0.88 ± 0.06, 0.29 ± 0.17 mm, 0.09 ± 0.07 and 0.94 ± 0.04, respectively, in 324IVUS images successfully segmented. Additionally, a comparison with the studies found in the literatureshowed that the proposed method is slight better than the majority of the related methods that havebeen proposed. Hence, the new automatic segmentation method is shown to be effective in detecting thelumen in IVUS images without using complex solutions and user interaction

Lumen segmentation in magnetic resonance images of the carotid artery

Investigation of the carotid artery plays an important role in the diagnosis of cerebrovascular events. Segmentation of the lumen and vessel wall in Magnetic Resonance (MR) images is the first step towards evaluating any possible cardiovascular diseases like atherosclerosis. However, the automatic segmentation of the lumen is still a challenge due to the low quality of the images and the presence of other elements such as stenosis and malformations that compromise the accuracy of the results. In this article, a method to identify the location of the lumen without user interaction is presented. The proposed method uses the modified mean roundness to calculate the circularity index of the regions identified by the K-means algorithm and return the one with the maximum value, i.e. the potential lumen region. Then, an active contour is employed to refine the boundary of this region. The method achieved an average Dice coefficient of 0.78 +/- 0.14 and 0.61 +/- 0.21 in 181 3D-T1-weighted and 181 proton density-weighted MR images, respectively. The results show that this method is promising for the correct identification and location of the lumen even in images corrupted by noise

A review of computational methods applied for identification and quantification of atherosclerotic plaques in images

Evaluation of the composition of atherosclerotic plaques in images is an important task to determine their pathophysiology. Visual analysis is still as the most basic and often approach to determine the morphology of the atherosclerotic plaques. In addition, computer-aided methods have also been developed for identification of features such as echogenicity, texture and surface in such plaques. In this article, a review of the most important methodologies that have been developed to identify the main components of atherosclerotic plaques in images is presented. Hence, computational algorithms that take into consideration the analysis of the plaques echogenicity, image processing techniques, clustering algorithms and supervised classification used for segmentation, i.e. identification, of the atherosclerotic plaque components in ultrasound, computerized tomography and magnetic resonance images are introduced. The main contribution of this paper is to provide a categorization of the most important studies related to the segmentation of atherosclerotic plaques and its components in images acquired by the most used imaging modalities. In addition, the effectiveness and drawbacks of each methodology as well as future researches concerning the segmentation and classification of the atherosclerotic lesions are also discussed

Using a distance map and an active contour model to segment the carotid artery boundary from the lumen contour in proton density weighted magnetic resonance images

Segmentation methods have assumed an important role in image-based diagnosis of several cardiovascular diseases. Particularly, the segmentation of the boundary of the carotid artery is demanded in the detection and characterization of atherosclerosis and assessment of the disease progression. In this article, a fully automatic approach for the segmentation of the carotid artery boundary in Proton Density Weighted Magnetic Resonance Images is presented. The approach relies on the expansion of the lumen contour based on a distance map built using the gray-weighted distance relative to the center of the identified lumen region in the image under analysis. Then, a Snake model with a modified weighted external energy based on the combination of a balloon force along with a Gradient Vector Flow-based external energy is applied to the expanded contour towards the correct boundary of the carotid artery. The average values of the Dice coefficient, Polyline distance, mean contour distance and centroid distance found in the segmentation of 139 carotid arteries were 0.83 ± 0.11, 2.70 ± 1.69 pixels, 2.79 ± 1.89 pixels and 3.44 ± 2.82 pixels, respectively. The segmentation results of the proposed approach were also compared against the ones obtained by related approaches found in the literature, which confirmed the outstanding performance of the new approach. Additionally, the proposed weighted external energy for the Snake model was shown to be also robust to carotid arteries with large thickness and weak boundary image edges. (c) 202

Oral cleft prevention programa (OCPP)

Background: Oral clefts are one of the most common birth defects with significant medical, psychosocial, and economic ramifications. Oral clefts have a complex etiology with genetic and environmental risk factors. There are suggestive results for decreased risks of cleft occurrence and recurrence with folic acid supplements taken at preconception and during pregnancy with a stronger evidence for higher than lower doses in preventing recurrence. Yet previous studies have suffered from considerable design limitations particularly non-randomization into treatment. There is also well-documented effectiveness for folic acid in preventing neural tube defect occurrence at 0.4 mg and recurrence with 4 mg. Given the substantial burden of clefting on the individual and the family and the supportive data for the effectiveness of folic acid supplementation as well as its low cost, a randomized clinical trial of the effectiveness of high versus low dose folic acid for prevention of cleft recurrence is warranted. Methods/design: This study will assess the effect of 4 mg and 0.4 mg doses of folic acid, taken on a daily basis during preconception and up to 3 months of pregnancy by women who are at risk of having a child with nonsyndromic cleft lip with/without palate (NSCL/P), on the recurrence of NSCL/P. The total sample will include about 6,000 women (that either have NSCL/P or that have at least one child with NSCL/P) randomly assigned to the 4 mg and the 0.4 mg folic acid study groups. The study will also compare the recurrence rates of NSCL/P in the total sample of subjects, as well as the two study groups (4mg, 0.4 mg) to that of a historical control group. The study has been approved by IRBs (ethics committees) of all involved sites. Results will be disseminated through publications and presentations at scientific meetings. Discussion: The costs related to oral clefts are high, including long term psychological and socio-economic effects. This study provides an opportunity for huge savings in not only money but the overall quality of life. This may help establish more specific clinical guidelines for oral cleft prevention so that the intervention can be better tailored for at-risk women