Simultaneous pressure-volume measurements using optical sensors and MRI 1 for left ventricle function assessment during animal experiment 2

International audienceSimultaneous pressure and volume measurements enable the extraction of valuable parameters for left ventricle function assessment. Cardiac MR has proven to be the most accurate method for volume estimation. Nonetheless, measuring pressure simultaneously during MRI acquisitions remains a challenge given the magnetic nature of the widely used pressure transducers. In this study we show the feasibility of simultaneous in vivo pressure-volume acquisitions with MRI using optical pressure sensors. Pressure-volume loops were calculated while inducing three inotropic states in a sheep and functional indices were extracted, using single beat loops, to characterize systolic and diastolic performance. Functional indices evolved as expected in response to positive inotropic stimuli. The end-systolic elastance, representing the contractility index, the diastolic myocardium compliance, and the cardiac work efficiency all increased when inducing inotropic state enhancement. The association of MRI and optical pressure sensors within the left ventricle successfully enabled pressure-volume loop analysis after having respective data simultaneously recorded during the experimentation without the need to move the animal between each inotropic state

The 3d left ventricular geometry integrated in myocardial wall stress estimation is more sensitive than end diastolic mass/volume ratio to characterize afterload-related left ventricular remodeling

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Ascending aorta backward flow parameters estimated from phase-contrast cardiovascular magnetic resonance data: new indices of arterial aging

International audienceOur purpose was to estimate volume and flow rate parameters related to the backward flow in the ascending aorta (AA) using phase-contrast cardiovascular magnetic resonance (PC-CMR) and to evaluate their relationships with age and with well established arterial stiffness indices including wave reflection parameters in an asymptomatic group without overt cardiovascular disease

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

Evaluation of aortic valve stenosis from Phase-Contrast Magnetic Resonance data using a new automated segmentation and analysis method: Comparison against Doppler Echocardiography

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