Publications by authors named "Pau Medrano-Gracia"

Objective: To examine the association between the medical imaging utilization and information related to patients' socioeconomic, demographic and clinical factors during the patients' ED visits; and to develop predictive models using these associated factors including natural language elements to predict the medical imaging utilization at pediatric ED.

Methods: Pediatric patients' data from the 2012-2016 United States National Hospital Ambulatory Medical Care Survey was included to build the models to predict the use of imaging in children presenting to the ED. Multivariable logistic regression models were built with structured variables such as temperature, heart rate, age, and unstructured variables such as reason for visit, free text nursing notes and combined data available at triage.

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We aimed to compare child body mass index (BMI) in prediction of hypertension in early adulthood with 4 other adiposity indices (waist circumference [WC], waist circumference-to-height ratio [WHtR], waist-to-hip ratio [WHR], and triceps skinfold [TSF]). The cohort from the China Health and Nutrition Survey 1993-2011 consisted of 1444 adults aged 18-36 years who were examined in childhood and early adulthood. Child adiposity indices and adult blood pressure (BP) were transformed into age-, sex-, and survey year-specific Z-scores.

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Left ventricular (LV) mass and volume are important indicators of clinical and pre-clinical disease processes. However, much of the shape information present in modern imaging examinations is currently ignored. Morphometric atlases enable precise quantification of shape and function, but there has been no objective comparison of different atlases in the same cohort.

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This is a consensus document from the European Bifurcation Club concerning bench testing in coronary artery bifurcations. It is intended to provide guidelines for bench assessment of stents and other strategies in coronary bifurcation treatment where the United States Food and Drug Administration (FDA) or International Organization for Standardization (ISO) guidelines are limited or absent. These recommendations provide guidelines rather than a step-by-step manual.

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Continuous advances in imaging technologies enable ever more comprehensive phenotyping of human anatomy and physiology. Concomitant reduction of imaging costs has resulted in widespread use of imaging in large clinical trials and population imaging studies. Magnetic Resonance Imaging (MRI), in particular, offers one-stop-shop multidimensional biomarkers of cardiovascular physiology and pathology.

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We characterized motion attributes arising from LV spatio-temporal analysis of motion distributions in myocardial infarction. Time-varying 3D finite element shape models were obtained in 300 Controls and 300 patients with myocardial infarction. Inter-individual left ventricular shape differences were eliminated using parallel transport to the grand mean of all cases.

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Background: Left ventricular size and shape are important for quantifying cardiac remodeling in response to cardiovascular disease. Geometric remodeling indices have been shown to have prognostic value in predicting adverse events in the clinical literature, but these often describe interrelated shape changes. We developed a novel method for deriving orthogonal remodeling components directly from any (moderately independent) set of clinical remodeling indices.

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Statistical shape modeling is a powerful tool for visualizing and quantifying geometric and functional patterns of the heart. After myocardial infarction (MI), the left ventricle typically remodels in response to physiological challenges. Several methods have been proposed in the literature to describe statistical shape changes.

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During percutaneous coronary intervention, stents are placed in narrowings of the arteries to restore normal blood flow. Despite improvements in stent design, deployment techniques and drug-eluting coatings, restenosis and stent thrombosis remain a significant problem. Population stent design based on statistical shape analysis may improve clinical outcomes.

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Aims: The aim of this study was to define the shape variations, including diameters and angles, of the major coronary artery bifurcations.

Methods And Results: Computed tomographic angiograms from 300 adults with a zero calcium score and no stenoses were segmented for centreline and luminal models. A computational atlas was constructed enabling automatic quantification of 3D angles, diameters and lengths of the coronary tree.

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The hemodynamic influence of vessel shape such as bifurcation angle is not fully understood with clinical and quantitative observations being equivocal. The aim of this study is to use computational modeling to study the hemodynamic effect of shape characteristics, in particular bifurcation angle (BA), for non-stented and stented coronary arteries. Nine bifurcations with angles of 40°, 60° and 80°, representative of ±1 SD of 101 asymptomatic computed tomography angiogram cases (average age 54±8 years; 57 females), were generated for (1) a non-stented idealized, (2) stented idealized, and (3) non-stented patient-specific geometry.

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Purpose: To examine the feasibility of combining computational fluid dynamics (CFD) and dynamically scaled phantom phase-contrast magnetic resonance imaging (PC-MRI) for coronary flow assessment.

Materials And Methods: Left main coronary bifurcations segmented from computed tomography with bifurcation angles of 33°, 68°, and 117° were scaled-up ∼7× and 3D printed. Steady coronary flow was reproduced in these phantoms using the principle of dynamic similarity to preserve the true-scale Reynolds number, using blood analog fluid and a pump circuit in a 3T MRI scanner.

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Background: The infection rate of syphilis in China has increased dramatically in recent decades, becoming a serious public health concern. Early prediction of syphilis is therefore of great importance for heath planning and management.

Methods: In this paper, we analyzed surveillance time series data for primary, secondary, tertiary, congenital and latent syphilis in mainland China from 2005 to 2012.

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The majority of patients with angina or heart failure have coronary artery disease. Left main bifurcations are particularly susceptible to pathological narrowing. Flow is a major factor of atheroma development, but limitations in imaging technology such as spatio-temporal resolution, signal-to-noise ratio (SNRv), and imaging artefacts prevent in vivo investigations.

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Background: Although adverse left ventricular shape changes (remodeling) after myocardial infarction (MI) are predictive of morbidity and mortality, current clinical assessment is limited to simple mass and volume measures, or dimension ratios such as length to width ratio. We hypothesized that information maximizing component analysis (IMCA), a supervised feature extraction method, can provide more efficient and sensitive indices of overall remodeling.

Methods: IMCA was compared to linear discriminant analysis (LDA), both supervised methods, to extract the most discriminatory global shape changes associated with remodeling after MI.

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Stent induced hemodynamic changes in the coronary arteries are associated with higher risk of adverse clinical outcome. The purpose of this study was to evaluate the impact of stent design on wall shear stress (WSS), time average WSS, and WSS gradient (WSSG), in idealized stent geometries using computational fluid dynamics. Strut spacing, thickness, luminal protrusion, and malapposition were systematically investigated and a comparison made between two commercially available stents (Omega and Biomatrix).

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Large-scale population-based imaging studies of preclinical and clinical heart disease are becoming possible due to the advent of standardized robust non-invasive imaging methods and infrastructure for big data analysis. This gives an exciting opportunity to gain new information about the development and progression of heart disease across population groups. However, the large amount of image data and prohibitive time required for image analysis present challenges for obtaining useful derived data from the images.

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Describing the detailed statistical anatomy of the coronary artery tree is important for determining the aetiology of heart disease. A number of studies have investigated geometrical features and have found that these correlate with clinical outcomes, e.g.

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The burden of heart disease is rapidly worsening due to the increasing prevalence of obesity and diabetes. Data sharing and open database resources for heart health informatics are important for advancing our understanding of cardiovascular function, disease progression and therapeutics. Data sharing enables valuable information, often obtained at considerable expense and effort, to be reused beyond the specific objectives of the original study.

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Myocardial infarction leads to changes in the geometry (remodeling) of the left ventricle (LV) of the heart. The degree and type of remodeling provides important diagnostic information for the therapeutic management of ischemic heart disease. In this paper, we present a novel analysis framework for characterizing remodeling after myocardial infarction, using LV shape descriptors derived from atlas-based shape models.

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Background: Although left ventricular cardiac geometric indices such as size and sphericity characterize adverse remodeling and have prognostic value in symptomatic patients, little is known of shape distributions in subclinical populations. We sought to quantify shape variation across a large number of asymptomatic volunteers, and examine differences among sub-cohorts.

Methods: An atlas was constructed comprising 1,991 cardiovascular magnetic resonance (CMR) cases contributed from the Multi-Ethnic Study of Atherosclerosis baseline examination.

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Heart shape and function are major determinants of disease severity and predictors of future morbidity and mortality. Many studies now rely on non-invasive cardiac imaging techniques to quantify structural and functional changes. Statistical anatomical modeling of heart shape and motion provides a new tool for the quantification and evaluation of heart disease.

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A collaborative framework was initiated to establish a community resource of ground truth segmentations from cardiac MRI. Multi-site, multi-vendor cardiac MRI datasets comprising 95 patients (73 men, 22 women; mean age 62.73±11.

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Background: Cardiovascular imaging studies generate a wealth of data which is typically used only for individual study endpoints. By pooling data from multiple sources, quantitative comparisons can be made of regional wall motion abnormalities between different cohorts, enabling reuse of valuable data. Atlas-based analysis provides precise quantification of shape and motion differences between disease groups and normal subjects.

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Motivation: Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes.

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