Thoracic aorta calcium detection and quantification using convolutional neural networks in a large cohort of intermediate-risk patients

Arterial calcification is an independent predictor of cardiovascular disease (CVD) events whereas thoracic aorta calcium (TAC) detection might anticipate extracoronary outcomes. In this work, we trained six convolutional neural networks (CNNs) to detect aortic calcifications and to automate the TAC score assessment in intermediate CVD risk patients. Cardiac computed tomography images from 1415 patients were analyzed together with their aortic geometry previously assessed. Orthogonal patches centered in each aortic candidate lesion were reconstructed and a dataset with 19,790 images (61% positives) was built. Three single-input 2D CNNs were trained using axial, coronal and sagittal patches together with two multi-input 2.5D CNNs combining the orthogonal patches and identifying their best regional combination (BRC) in terms of lesion location. Aortic calcifications were concentrated in the descending (66%) and aortic arch (26%) portions. The BRC of axial patches to detect ascending or aortic arch lesions and sagittal images for the descending portion had the best performance: 0.954 F1-Score, 98.4% sensitivity, 87% of the subjects correctly classified in their TAC category and an average false positive TAC score per patient of 30. A CNN that combined axial and sagittal patches depending on the candidate aortic location ensured an accurate TAC score prediction.Fil: Guilenea, Federico Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional, Trasplante y Bioingeniería. Fundación Favaloro. Instituto de Medicina Traslacional, Trasplante y Bioingeniería; ArgentinaFil: Casciaro, Mariano Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional, Trasplante y Bioingeniería. Fundación Favaloro. Instituto de Medicina Traslacional, Trasplante y Bioingeniería; ArgentinaFil: Pascaner, Ariel Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional, Trasplante y Bioingeniería. Fundación Favaloro. Instituto de Medicina Traslacional, Trasplante y Bioingeniería; ArgentinaFil: Soulat, Gilles. Hopital Europeen Georges Pompidou; FranciaFil: Mousseaux, Elie. Hopital Europeen Georges Pompidou; FranciaFil: Craiem, Damian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional, Trasplante y Bioingeniería. Fundación Favaloro. Instituto de Medicina Traslacional, Trasplante y Bioingeniería; Argentin

Fractional calculus applied to model arterial viscoelasticity

Arterial viscoelasticity can be described using stress-relaxation experiments. To fit these curves, models with springs and dashpots, based on differential equations, were widely studied. However, uniaxial tests in arteries show particular shapes with an initial steep decay and a slow asymptotic relaxation. Recently, fractional order derivatives were used to conceive a new component called spring-pot that interpolates between pure elastic and viscous behaviors. In this work we modified a standard linear solid model replacing a dashpot with a spring-pot of order α. We tested the fractional model in human arterial segments. Results showed an accurate relaxation response during 1-hour with least squares errors below 1%. Fractional orders α were 0.2-0.4, justifying the extra parameter. Moreover, the adapted parameters allowed us to predict frequency responses that were similar to reported Complex Elastic Moduli in arteries. Our results indicate that fractional models should be considered as real alternatives to model arterial viscoelasticity

Carotid wall stress calculated with continuous intima-media thickness assessment using B-mode ultrasound

Cardiovascular risk is normally assessed using clinical risk factors but it can be refined using non-invasive infra-clinical markers. Intima-Media Thickness (IMT) is recognized as an early indicator of cardiovascular disease. Carotid Wall Stress (CWS) can be calculated using arterial pressure and carotid size (diameter and IMT). Generally, IMT is measured during diastole when it reaches its maximum value. However, it changes during the cardiac cycle and a time-dependant waveform can be obtained using B-mode ultrasound images. In this work we calculated CWS considering three different approaches for IMT assessment: (i) constant IMT (standard diastolic value), (ii) estimated IMT from diameter waveform (assuming a constant cross-sectional wall area) and (iii) continuously measured IMT. Our results showed that maximum wall stress depends on the IMT estimation method. Systolic CWS progressively increased using the three approaches (p<0.024). We conclude that maximum CWS is highly dependent on wall thickness and accurate IMT measures during systole should be encouraged.Fil: Pascaner, Ariel Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Favaloro; ArgentinaFil: Craiem, Damian. Universidad Favaloro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Casciaro, Mariano Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Favaloro; ArgentinaFil: Danielo, R.. Fundación Favaloro; ArgentinaFil: Graf Caride, Diego Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Favaloro; ArgentinaFil: Guevara, E.. Fundación Favaloro; Argentin

Fractional-order viscoelasticity applied to describe uniaxial stress relaxation of human arteries.

Viscoelastic models can be used to better understand arterial wall mechanics in physiological and pathological conditions. The arterial wall reveals very slow time-dependent decays in uniaxial stress-relaxation experiments, coherent with weak power-law functions. Quasi-linear viscoelastic (QLV) theory was successfully applied to modeling such responses, but an accurate estimation of the reduced relaxation function parameters can be very difficult. In this work, an alternative relaxation function based on fractional calculus theory is proposed to describe stress relaxation experiments in strips cut from healthy human aortas. Stress relaxation (1 h) was registered at three incremental stress levels. The novel relaxation function with three parameters was integrated into the QLV theory to fit experimental data. It was based in a modified Voigt model, including a fractional element of order α, called spring–pot. The stressrelaxation predictionwas accurate and fast. Sensitivity plots for each parameter presented a minimum near their optimal values. Least-squares errors remained below 2%. Values of order α = 0.1–0.3 confirmed a predominant elastic behavior. The other two parameters of the model can be associated to elastic and viscous constants that explain the time course of the observed relaxation function. The fractional-order model integrated into the QLV theory proved to capture the essential features of the arterial wall mechanical response

Simulation of the arterial elasticity influence on the Ambulatory Arterial Stiffness Index AASI

Recientemente se propuso un índice de rigidez arterial denominado AASI (Ambulatory Arterial Stiffness Index) derivado de mediciones ambulatorias de presión arterial durante 24 horas. Su asociación como índice de rigidez y la infl uencia estadística de la dispersión en los valores presivos continúa bajo discusión. Proponemos estudiar estas controversias en el contexto de un modelo estadístico. Se realizó una simulación con valores similares a los de pacientes de arterias normales, rígidas y compliantes, utilizando 3 curvas exponenciales presión-diámetro. Se generaron diámetros pulsátiles aleatorios siguiendo distribuciones normales y se obtuvieron presiones sistólicas y diastólicas en tiempos paramétricos equivalentes a 24 horas. Se calculó el AASI como uno menos la pendiente de la regresión de presión arterial sistólica y diastólica. El AASI del grupo normal resultó 0,42, aumentó a 0,50 en el rígido y disminuyó a 0,34 en el compliante (siempre con r2>0,9). Disminuir la dispersión del rango de presiones provocó una disminución de r2 en la regresión de la nube de puntos de presión sistólica y diastólica, aumentando artifi cialmente el AASI. Por primera vez la elasticidad no-lineal de la pared arterial ayuda a explicar la asociación del AASI como índice de rigidez arterial. La simulación corrobora que la dispersión de los valores presivos condicionan el cálculo del AASI debido a su naturaleza estadística.Recently, an arterial stiffness index called AASI (Ambulatory Arterial Stiffness Index) calculated from ambulatory blood pressure measurements during 24 hours was proposed. The associations with arterial stiffness and the pressure dispersion dependence remain under discussion. We propose to study these controversies in a statistical model framework. A simulation was performed including values similar to the ones in patients with normal, rigid and compliant arteries. Three exponential curves of pressure-diameter were simulated. Based on diameters randomly generated following normal distributions, systolic and diastolic pressures were calculated in a 24h parametric time. AASI was calculated as one minus the slope of the regression of systolic to diastolic pressure. The AASI for the normal group was 0,42, increased to 0,50 in the rigid group and decreased to 0,34 in the compliant case (always r2>0,9). A dispersion decrease in the pressure values was followed by an r2 decrease in the diastolic vs systolic pressure regression, artifi cially increasing AASI. For the fi rst time the non-linearity of the arterial wall helps to explain the association of AASI with a stiffness index. The simulation corroborates that 24 h pressure variability conditions AASI values due to its statistical nature

Acute type B aortic dissection risk predictors: Thoracic aorta anatomic variables

We believe that the vulnerability of the subjects to aortic diseases may be influenced by geometrical risk factors. Your valuable comments give us the chance to better explain this hypothesis. We have shown a thoracic aorta enlargement and unfolding process with ageing [1], that accelerates with hypertension [2]. We share your concerns regarding the determination of reference values for the normal aortic size. After conducting a principal component analysis, we found 80% of the total geometric variability explained by changes in aortic size, arch unfolding and asymmetry [3]. To investigate the association between aortic diseases and geometry, we assessed thoracic aorta calcium, showing that it was associated with aortic morphology, particularly in the descending aorta [4]. At that point, an important question arose: Are aortic diseases a consequence or the cause of these geometrical changes? [4]. Similarly, is the aortic arch enlargement responsible for the dissection or the consequence of the acute event? [5]. As Shirali et al., we excluded from the multivariate model all the descending aorta geometric variables. However, the abrupt reduction of the descending aorta lumen, forcing blood to flow through the true lumen, could raise blood pressure and induce an ascending aorta expansion. To further investigate this issue, we measured the diameter of the ascending aorta in patients from the dissection group after an endovascular aortic repair procedure (n = 24). No significant changes in the diameter of the ascending aorta were observed after the surgery, suggesting that the dilatation existed before the dissection onset.Fil: Craiem, Damian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay; Argentin

Development and evaluation of new 3D geometric analysis tools to prevent and treat aortic diseases

Les nouvelles technologies d'imagerie basées sur la tomodensitométrie en coupe permettent l'évaluation de très haute qualité de la structure 3D de l'aorte thoracique. La reconstruction virtuelle et les modèles géométriques de l'aorte sont indispensables à l'exploitation des images dont le temps de traitement manuel reste cependant considérable et les outils numériques insuffisants ou inadaptés pour mesurer correctement sa morphologie. L'aorte n'est pas un simple tube de conduction du sang mais un organe de régulation de la pulsatilité des ondes de pression provoquées par l'éjection cardiaque. Ses désordres biomécaniques peuvent accélérer la formation de calcifications dans sa paroi et entrainer des risques de graves complications, comme les anévrismes et les dissections. La réparation aortique basée sur l'implantation d'endoprothèses est en pleine évolution et requiert des renseignements morphologiques précis pour en améliorer le taux de succès. Notre objectif a été d'étudier la géométrie tridimensionnelle de l'aorte en développant des algorithmes appropriés. Une plateforme informatique a été conçue et testée pour étudier trois pathologies de l'aorte: l'athérosclérose calcifiée, l'anévrisme et la dissection. L'hypothèse du travail a été que la géométrie spécifique des artères de chaque individu joue un rôle complémentaire à celui des facteurs de risque traditionnels dans le développement de ces pathologies. Notre premier travail a montré que trois facteurs résument 80% de la variabilité géométrique de l'aorte thoracique: le volume aortique, le déroulement et la symétrie de l'arche aortique, avec des taux de variabilité respectifs de 46%, 22% et 12%. Dans deux travaux suivants, nous avons montré que les calcifications de l'aorte thoracique se concentrent principalement dans la crosse et dans le segment descendant proximal, et que cette distribution était associée à la morphologie de l'aorte indépendamment de l'âge, du sexe, de la surface corporelle et des facteurs de risque traditionnels. Le quatrième travail a montré que le score de dépôt calcique dans toute l'aorte thoracique incluant la crosse était plus étroitement associé aux complications non-cardiaques, vasculaires périphériques et cérébrales, que le score traditionnel de calcium coronaire. Il faut noter que la crosse aortique n'est pas visualisée dans les études de routine de calcium coronaire sans injection. Le cinquième travail décrit un modèle déformable capable de segmenter la lumière aortique dans un contexte pathologique. Il a été appliqué pour étudier de façon automatisée la taille d'un anévrisme abdominal avant et après la pose d'une endoprothèse. Dans le dernier travail, la méthode précédente a été adaptée pour étudier la géométrie aortique des patients atteints de dissection comparativement à un groupe témoin de patients qui en étaient indemnes. Trois variables géométriques ont été identifiées dans le modèle de prédiction du risque de dissection: le diamètre de la crosse, la longueur de l'aorte thoracique et l'âge. En conclusion, nos résultats montrent que les maladies aortiques sont étroitement associées à la géométrie de l'aorte indépendamment des facteurs de risque traditionnels. Les algorithmes que nous avons développés ouvrent la voie à l'automatisation et à une réduction de la variabilité des mesures.New imaging technologies, including those associated with multislice computed tomography, allow to evaluate the structure of the thoracic aorta in 3D with an impressive resolution. Aortic virtual reconstruction and geometric modeling are essential for imaging evaluation because manual measurements are time-consuming, and the available tools still need to be adapted to complex aortic morphologies. The aorta is more than a simple tubular conduit vessel for blood. It also regulates the pulsatile pressure waves that are injected into the arterial system by the left ventricle. The biomechanical disorders produced by these waves can accelerate the formation of calcium deposits within the arterial wall. Furthermore, they are thought to be responsible for severe aortic complications, including aneurysms and dissections. Endovascular aortic repair is a modern technique based on the implantation of an endograft to restore the normal blood flow. Precise morphological measurements are required to improve this technique, for both surgery planning and patient follow up. Our objective was to develop original algorithms to study the aortic geometry in 3D. A computing platform was designed and tested to analyze three main aortic pathologies: calcified atherosclerosis, aneurysms and dissections. The hypothesis of our study was that the individual arterial geometry of a subject plays a complementary role in the development of vascular pathologies beyond traditional risk factors. Our first work revealed that 80% of the total geometric variability in the thoracic aorta might be explained using 3 factors: the aortic volume, the aortic arc unfolding and its asymmetry. Variability percentages accounted for 46%, 22% and 12%, respectively. The next 2 works, showed that calcifications in the thoracic aorta were concentrated in the aortic arch and in the proximal descending segment. This spatial distribution was associated with aortic morphology, independently of age, sex, body surface area and traditional risk factors. Our fourth article revealed that calcium deposits in the entire thoracic aorta (including the aortic arch) was associated with non-cardiac events, beyond the standard coronary artery calcium score. It is noteworthy that the aortic arch region is systematically excluded from standard scans. Our fifth manuscript described a novel deformable model applied to the aortic segmentation under pathological contexts. It was used to estimate the size and shape of abdominal aneurysms before and after endograft implantation. In the last work, this method was adapted to study the geometry of the thoracic aorta of patients with an aortic dissection with respect to a control group. Three anatomic variables were identified for the risk prediction model: the aortic arch diameter, the thoracic aortic length and the age of the patient. In conclusion, our results show that aortic diseases are closely associated with aortic geometry, independently from traditional risk factors. The developed algorithms improved the automation of measurements and reduced the variability of the estimations

Towards automatic measurement of anteversion and neck-shaft angles in human femurs using CT images

Automatic assessment of human femur morphology may provide useful clinical information with regard to hip and knee surgery, prosthesis design and management of hip instability. To this end, neck-shaft and anteversion angles are usually used. We propose a full automatic method to estimate these angles in human femurs. Multislice CT images from 18 dried bones were analysed. The algorithm fits 3D cylinders to different regions of the bone to estimate the angles. A manual segmentation and a conventional angle assessment were used for validation. We found anteversion angle as 20 ± 7° and neck-shaft angle as 130 ± 9°. Mean distances from femur surface to cylinders were 5.5 ± 0.6, 3.5 ± 0.6 and 2.4 ± 0.4 mm for condyles, diaphysis and neck regions, respectively. Automatic and conventional angles were positively correlated (r(2)>0.85). Manual and automatic segmentations did not differ. The method was fast and 100% reproducible. A robust in vivo segmentation algorithm should be integrated to advance towards a clinically compliant methodology.Fil: Casciaro, Mariano Ezequiel. Universidad Favaloro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Craiem, Damian. Universidad Favaloro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Fractional order models of viscoelasticity as an alternative in the analysis of red blood cell (RBC) membrane mechanics

New lumped-element models of red blood cell mechanics can be constructed using fractional order generalizations of springs and dashpots. Such 'spring-pots' exhibit a fractional order viscoelastic behavior that captures a wide spectrum of experimental results through power-law expressions in both the time and frequency domains. The system dynamics is fully described by linear fractional order differential equations derived from first order stress-strain relationships using the tools of fractional calculus. Changes in the composition or structure of the membrane are conveniently expressed in the fractional order of the model system. This approach provides a concise way to describe and quantify the biomechanical behavior of membranes, cells and tissues.Fil: Craiem, Damian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Favaloro; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Magin, Richard L.. University of Illinois at Chicago ; Estados Unido