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1. Value of aortic volumes assessed by automated segmentation of 3D MRI data in patients with thoracic aortic dilatation: A case-control study

Author: Thomas Dietenbeck, Kevin Bouaou, Sophia Houriez-Gombaud-Saintonge, Jia Guo, Umit Gencer, Etienne Charpentier, Alain Giron, Alain De Cesare, Vincent Nguyen, Antonio Gallo, Samia Boussouar, Nicoletta Pasi, Gilles Soulat, Alban Redheuil, Elie Mousseaux, and Nadjia Kachenoura
Subjects: Radiological and Ultrasound Technology, Radiology, Nuclear Medicine and imaging, General Medicine
Published: 2023
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2. Aortic Stiffness Measured from Either 2D/4D Flow and Cine MRI or Applanation Tonometry in Coronary Artery Disease: A Case–Control Study

Author: Lan-Anh Nguyen, Sophia Houriez-Gombaud-Saintonge, Etienne Puymirat, Umit Gencer, Thomas Dietenbeck, Kevin Bouaou, Alain De Cesare, Emilie Bollache, Elie Mousseaux, Nadjia Kachenoura, and Gilles Soulat
Subjects: MRI, PWV, 4D flow, coronary artery disease, General Medicine
Abstract: Background and objective: Aortic stiffness can be evaluated by aortic distensibility or pulse wave velocity (PWV) using applanation tonometry, 2D phase contrast (PC) MRI and the emerging 4D flow MRI. However, such MRI tools may reach their technical limitations in populations with cardiovascular disease. Accordingly, this work focuses on the diagnostic value of aortic stiffness evaluated either by applanation tonometry or MRI in high-risk coronary artery disease (CAD) patients. Methods: 35 patients with a multivessel CAD and a myocardial infarction treated 1 year before were prospectively recruited and compared with 18 controls with equivalent age and sex distribution. Ascending aorta distensibility and aortic arch 2D PWV were estimated along with 4D PWV. Furthermore, applanation tonometry carotid-to-femoral PWV (cf PWV) was recorded immediately after MRI. Results: While no significant changes were found for aortic distensibility; cf PWV, 2D PWV and 4D PWV were significantly higher in CAD patients than controls (12.7 ± 2.9 vs. 9.6 ± 1.1; 11.0 ± 3.4 vs. 8.0 ± 2.05 and 17.3 ± 4.0 vs. 8.7 ± 2.5 m·s−1 respectively, p < 0.001). The receiver operating characteristic (ROC) analysis performed to assess the ability of stiffness indices to separate CAD subjects from controls revealed the highest area under the curve (AUC) for 4D PWV (0.97) with an optimal threshold of 12.9 m·s−1 (sensitivity of 88.6% and specificity of 94.4%). Conclusions: PWV estimated from 4D flow MRI showed the best diagnostic performances in identifying severe stable CAD patients from age and sex-matched controls, as compared to 2D flow MRI PWV, cf PWV and aortic distensibility.
Published: 2023
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3. Deep Learning-based Automated Aortic Area and Distensibility Assessment: The Multi-Ethnic Study of Atherosclerosis (MESA)

Author: Vivek P. Jani, Nadjia Kachenoura, Alban Redheuil, Gisela Teixido-Tura, Kevin Bouaou, Emilie Bollache, Elie Mousseaux, Alain De Cesare, Shelby Kutty, Colin O. Wu, David A. Bluemke, Joao A. C. Lima, Bharath Ambale-Venkatesh, Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Bollache, Emilie
Subjects: Radiological and Ultrasound Technology, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Image and Video Processing (eess.IV), Electrical Engineering and Systems Science - Image and Video Processing, Atherosclerosis, Magnetic Resonance Imaging, Quantitative Biology - Quantitative Methods, Article, Computer Science Applications, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, Deep Learning, FOS: Biological sciences, FOS: Electrical engineering, electronic engineering, information engineering, cardiovascular system, Humans, Radiology, Nuclear Medicine and imaging, Quantitative Methods (q-bio.QM), Algorithms, Aorta
Abstract: This study applies convolutional neural network (CNN)-based automatic segmentation and distensibility measurement of the ascending and descending aorta from 2D phase-contrast cine magnetic resonance imaging (PC-cine MRI) within the large MESA cohort with subsequent assessment on an external cohort of thoracic aortic aneurysm (TAA) patients. 2D PC-cine MRI images of the ascending and descending aorta at the pulmonary artery bifurcation from the MESA study were included. Train, validation, and internal test sets consisted of 1123 studies (24282 images), 374 studies (8067 images), and 375 studies (8069 images), respectively. An external test set of TAAs consisted of 37 studies (3224 images). A U-Net based CNN was constructed, and performance was evaluated utilizing dice coefficient (for segmentation) and concordance correlation coefficients (CCC) of aortic geometric parameters by comparing to manual segmentation and parameter estimation. Dice coefficients for aorta segmentation were 97.6% (CI: 97.5%-97.6%) and 93.6% (84.6%-96.7%) on the internal and external test of TAAs, respectively. CCC for comparison of manual and CNN maximum and minimum ascending aortic areas were 0.97 and 0.95, respectively, on the internal test set and 0.997 and 0.995, respectively, for the external test. CCCs for maximum and minimum descending aortic areas were 0.96 and 0. 98, respectively, on the internal test set and 0.93 and 0.93, respectively, on the external test set. We successfully developed and validated a U-Net based ascending and descending aortic segmentation and distensibility quantification model in a large multi-ethnic database and in an external cohort of TAA patients., 25 pages, 5 figures
Published: 2021
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4. Analysis of aortic pressure fields from 4D flow MRI in healthy volunteers: Associations with age and left ventricular remodeling

Author: Ioannis Bargiotas, Alban Redheuil, Kevin Bouaou, Nadjia Kachenoura, Gilles Soulat, Elie Mousseaux, Emilie Bollache, Sophia Houriez-Gombaud-Saintonge, Alain Giron, Emmanuel Messas, Thomas Dietenbeck, Alain De Cesare, Umit Gencer, Didier Lucor, and Damian Craiem
Subjects: medicine.medical_specialty, education.field_of_study, Aorta, business.industry, Population, medicine.disease, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Afterload, Internal medicine, medicine.artery, Ascending aorta, Arterial stiffness, medicine, Cardiology, Aortic pressure, Radiology, Nuclear Medicine and imaging, education, Ventricular remodeling, business, Pulse wave velocity
Abstract: Background: Aging-related arterial stiffness is associated with substantial changes in global and local arterial pressures. The subsequent early return of reflected pressure waves leads to an elevated left ventricular (LV) afterload and ultimately to a deleterious concentric LV remodeling. Purpose: To compute aortic time-resolved pressure fields of healthy subjects from 4D flow MRI and to define relevant pressure-based markers while investigating their relationship with age, LV remodeling, as well as tonometric augmentation index (AIx) and pulse wave velocity (PWV). Study type: Retrospective. Population: Forty-seven healthy subjects (age: 49.5 ± 18 years, 24 women). Field strength/sequence: 3 T/4D flow MRI. Assessment: Spatiotemporal pressure fields were computed by integrating velocity-derived pressure gradients using Navier-Stokes equations, while assuming zero pressure at the sino-tubular junction. To quantify aortic pressure spatiotemporal variations, we defined the following markers: 1) volumetric aortic pressure propagation rates ΔP E1 /ΔV and ΔP E2 /ΔV, representing variations of early and late systolic relative pressure peaks along the aorta, respectively, according to the cumulated aortic volume; 2) ΔA PE1-PE2 defined in four aortic regions as the absolute difference between early and late systolic relative pressure peaks amplitude. Statistical tests: Linear regression, Wilcoxon rank sum test, Bland-Altman analysis, and intraclass correlation coefficients (ICC). Results: Spatiotemporal variations of aortic pressure peaks were moderately to highly reproducible (ICC ≥0.50) and decreased significantly with age, in terms of absolute magnitude: ΔP E1 /ΔV (r = 0.70, P 0.39, P < 0.005). ΔP E1 /ΔV was associated with LV remodeling (r = 0.53, P < 0.001) and ascending aorta ΔA PE1-PE2 was associated with AIx (r = -0.59, P < 0.001). Both associations were independent of age and systolic blood pressures. Only weak associations were found between pressure indices and PWV (r ≤ 0.40). Data conclusion: 4D flow MRI relative aortic pressures were consistent with physiological knowledge as demonstrated by their significant volumetric and temporal variations with age and their independent association with LV remodeling and augmentation index. Level of Evidence 2 Technical Efficacy Stage 3 J. Magn. Reson. Imaging 2019;50:982-993.
Published: 2019
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5. Comprehensive assessment of local and regional aortic stiffness in patients with tricuspid or bicuspid aortic valve aortopathy using magnetic resonance imaging

Author: Sophia Houriez-Gombaud-Saintonge, Etienne Charpentier, Gilles Soulat, Nadjia Kachenoura, Alain De Cesare, Ariel Pascaner, Elie Mousseaux, Thomas Dietenbeck, Kevin Bouaou, Umit Gencer, Yasmina Chenoune, Damian Craiem, Emilie Bollache, Mariano E. Casciaro, Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), ESME Sudria [Paris], Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Hôpital Européen Georges Pompidou [APHP] (HEGP), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)
Subjects: Aortic valve, medicine.medical_specialty, bicuspid aortic valve, pulse wave velocity, Heart Valve Diseases, 030204 cardiovascular system & hematology, Pulse Wave Analysis, 03 medical and health sciences, 0302 clinical medicine, Bicuspid aortic valve, Vascular Stiffness, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Bicuspid Aortic Valve Disease, medicine.artery, Internal medicine, Medicine, Humans, 030212 general & internal medicine, Pulse wave velocity, Aorta, medicine.diagnostic_test, business.industry, thoracic aorta dilation, Magnetic resonance imaging, medicine.disease, Magnetic Resonance Imaging, medicine.anatomical_structure, arterial stiffness, Aortic valve stenosis, Aortic Valve, Case-Control Studies, Arterial stiffness, Cardiology, cardiovascular system, Aortic stiffness, Cardiology and Cardiovascular Medicine, business, MRI
Abstract: International audience; BackgroundWe aimed to provide a comprehensive aortic stiffness description using magnetic resonance imaging (MRI) in patients with ascending thoracic aorta aneurysm and tricuspid (TAV-ATAA) or bicuspid (BAV) aortic valve.MethodsThis case-control study included 18 TAV-ATAA and 19 BAV patients, with no aortic valve stenosis/severe regurgitation, who were 1:1 age-, gender- and central blood pressures (BP)-matched to healthy volunteers. Each underwent simultaneous aortic MRI and BP measurements. 3D anatomical MRI provided aortic diameters. Stiffness indices included: regional ascending (AA) and descending (DA) aorta pulse wave velocity (PWV) from 4D flow MRI; local AA and DA strain, distensibility and theoretical Bramwell-Hill (BH) model-based PWV, as well as regional arch PWV from 2D flow MRI.ResultsPatient groups had significantly higher maximal AA diameter (median[interquartile range], TAV-ATAA: 47.5[42.0–51.3]mm, BAV: 45.0[41.0–47.0]mm) than their respective controls (29.1[26.8–31.8] and 28.1[26.0–32.0]mm, p
Published: 2020
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6. Comparison of different methods for the estimation of aortic pulse wave velocity from 4D flow cardiovascular magnetic resonance

Author: Nadjia Kachenoura, Alain De Cesare, Gilles Soulat, Emilie Bollache, Alban Redheuil, Ioannis Bargiotas, Kevin Bouaou, Umit Gencer, Emmanuel Messas, Damian Craiem, Thomas Dietenbeck, Elie Mousseaux, Sophia Houriez-Gombaud-Saintonge, Alain Giron, Yasmina Chenoune, Sorbonne Université (SU), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), ESME Sudria [Paris], Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Centre de Mathématiques et de Leurs Applications (CMLA), École normale supérieure - Cachan (ENS Cachan)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay, École normale supérieure - Cachan (ENS Cachan), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET), Universidad Favaloro, and Favaloro Foundation
Subjects: Male, lcsh:Diseases of the circulatory (Cardiovascular) system, Aging, Time Factors, 4D flow CMR, [SDV]Life Sciences [q-bio], 030204 cardiovascular system & hematology, 030218 nuclear medicine & medical imaging, AGING, 0302 clinical medicine, Pulse wave velocity, Ingeniería Médica, Aorta, Observer Variation, Radiological and Ultrasound Technology, Age Factors, Aortic stiffness, AORTIC STIFFNESS, Steady-state free precession imaging, Middle Aged, Healthy Volunteers, Descending aorta, Cardiology, cardiovascular system, Female, Cardiology and Cardiovascular Medicine, Blood Flow Velocity, circulatory and respiratory physiology, Adult, medicine.medical_specialty, Magnetic Resonance Imaging, Cine, INGENIERÍAS Y TECNOLOGÍAS, Pulse Wave Analysis, 03 medical and health sciences, Vascular Stiffness, 4D FLOW CMR, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Predictive Value of Tests, medicine.artery, Internal medicine, Ascending aorta, Image Interpretation, Computer-Assisted, medicine, Humans, Radiology, Nuclear Medicine and imaging, cardiovascular diseases, PULSE WAVE VELOCITY, Angiology, Aged, Retrospective Studies, Reproducibility, business.industry, Research, purl.org/becyt/ford/2.6 [https], Reproducibility of Results, purl.org/becyt/ford/2 [https], lcsh:RC666-701, Regional Blood Flow, business, Magnetic Resonance Angiography
Abstract: Background: Arterial pulse wave velocity (PWV) is associated with increased mortality in aging and disease. Several studies have shown the accuracy of applanation tonometry carotid-femoral PWV (Cf-PWV) and the relevance of evaluating central aorta stiffness using 2D cardiovascular magnetic resonance (CMR) to estimate PWV, and aortic distensibility-derived PWV through the theoretical Bramwell-Hill model (BH-PWV). Our aim was to compare various methods of aortic PWV (aoPWV) estimation from 4D flow CMR, in terms of associations with age, Cf-PWV, BH-PWV and left ventricular (LV) mass-to-volume ratio while evaluating inter-observer reproducibility and robustness to temporal resolution. Methods: We studied 47 healthy subjects (49.5 ± 18 years) who underwent Cf-PWV and CMR including aortic 4D flow CMR as well as 2D cine SSFP for BH-PWV and LV mass-to-volume ratio estimation. The aorta was semi-automatically segmented from 4D flow data, and mean velocity waveforms were estimated in 25 planes perpendicular to the aortic centerline. 4D flow CMR aoPWV was calculated: using velocity curves at two locations, namely ascending aorta (AAo) and distal descending aorta (DAo) aorta (S1, 2D-like strategy), or using all velocity curves along the entire aortic centreline (3D-like strategies) with iterative transit time (TT) estimates (S2) or a plane fitting of velocity curves systolic upslope (S3). For S1 and S2, TT was calculated using three approaches: cross-correlation (TTc), wavelets (TTw) and Fourier transforms (TTf). Intra-class correlation coefficients (ICC) and Bland-Altman biases (BA) were used to evaluate inter-observer reproducibility and effect of lower temporal resolution. Results: 4D flow CMR aoPWV estimates were significantly (p < 0.05) correlated to the CMR-independent Cf-PWV, BH-PWV, age and LV mass-to-volume ratio, with the strongest correlations for the 3D-like strategy using wavelets TT (S2-TTw) (R = 0.62, 0.65, 0.77 and 0.52, respectively, all p < 0.001). S2-TTw was also highly reproducible (ICC = 0.99, BA = 0.09 m/s) and robust to lower temporal resolution (ICC = 0.97, BA = 0.15 m/s). Conclusions: Reproducible 4D flow CMR aoPWV estimates can be obtained using full 3D aortic coverage. Such 4D flow CMR stiffness measures were significantly associated with Cf-PWV, BH-PWV, age and LV mass-to-volume ratio, with a slight superiority of the 3D strategy using wavelets transit time (S2-TTw). Fil: Houriez Gombaud-Saintonge, Sophia. Inserm; Francia Fil: Mousseaux, Elie. Hopital Europeen Georges Pompidou; Francia Fil: Bargiotas, Ioannis. Université Paris-Saclay; Francia. Centre National de la Recherche Scientifique; Francia Fil: De Cesare, Alain. Université Pierre et Marie Curie; Francia. Inserm; Francia. Centre National de la Recherche Scientifique; Francia Fil: Dietenbeck, Thomas. Inserm; Francia. Centre National de la Recherche Scientifique; Francia Fil: Bouaou, Kevin. Inserm; Francia. Centre National de la Recherche Scientifique; Francia Fil: Redheuil, Alban. Inserm; Francia. Centre National de la Recherche Scientifique; Francia Fil: Soulat, Gilles. Hopital Europeen Georges Pompidou; Francia Fil: Giron, Alain. Inserm; Francia. Centre National de la Recherche Scientifique; Francia Fil: Gencer, Umit. Hopital Europeen Georges Pompidou; Francia Fil: 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; Argentina Fil: Messas, Emmanuel. Hopital Europeen Georges Pompidou; Francia Fil: Bollache, Emilie. Inserm; Francia. Centre National de la Recherche Scientifique; Francia Fil: Chenoune, Yasmina. No especifíca; Fil: Kachenoura, Nadjia. Inserm; Francia. Centre National de la Recherche Scientifique; Francia
Published: 2019
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7. Comparison of MR T1 and T2 mapping parameters to characterize myocardial and skeletal muscle involvement in systemic idiopathic inflammatory myopathy (IIM)

Author: Jerome Lamy, Philippe Cluzel, Olivier Benveniste, Adrian Thomas Huber, Tania Bacoyannis, Alain De Cesare, Mathieux Kerneis, Charles Roux, Aude Rigolet, Yves Allenbach, Alban Redheuil, Nadjia Kachenoura, Marine Bravetti, Khaoula Bouazizi, Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU), Institut de cardiologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Service de radiologie cardiovasculaire et interventionnelle [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), University of Bern, Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Service de médecine interne [CHU Pitié-Salpétrière], Centre de Recherche en Myologie, Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Service de Cardiologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), and Centre de recherche en Myologie – U974 SU-INSERM
Subjects: Male, medicine.medical_specialty, Relaxometry, Myocarditis, [SDV]Life Sciences [q-bio], Magnetic Resonance Imaging, Cine, 610 Medicine & health, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Predictive Value of Tests, Internal medicine, Extracellular fluid, Humans, Medicine, Radiology, Nuclear Medicine and imaging, Muscle, Skeletal, Retrospective Studies, Neuroradiology, Myositis, medicine.diagnostic_test, biology, business.industry, Myocardium, Ultrasound, Skeletal muscle, Magnetic resonance imaging, General Medicine, Middle Aged, medicine.disease, Troponin, medicine.anatomical_structure, ROC Curve, Case-Control Studies, 030220 oncology & carcinogenesis, Cardiology, biology.protein, Female, Radiology, business
Abstract: To compare the performance of magnetic resonance (MR) relaxometry parameters to discriminate myocardial and skeletal muscle inflammation in idiopathic inflammatory myopathy (IIM) patients from healthy controls. For this retrospective case-control study, 20 consecutive IIM patients (54 ± 18 years, 11 females) with cardiac involvement (troponin level > 50 ng/l) and 20 healthy controls (47 ± 12 years, 9 females) were included. All patients without cardiac MR imaging
Published: 2019
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8. Quantification of tumor perfusion using dynamic contrast-enhanced ultrasound: impact of mathematical modeling

Author: Maxime Doury, S. Lori Bridal, Alexandre Dizeux, Alain De Cesare, Frédérique Frouin, Claire Pellot-Barakat, and Olivier Lucidarme
Subjects: Normalization (statistics), Perfusion Imaging, Contrast Media, Blood volume, 030218 nuclear medicine & medical imaging, Carcinoma, Lewis Lung, Mice, 03 medical and health sciences, 0302 clinical medicine, Tumor perfusion, Animals, Radiology, Nuclear Medicine and imaging, Mouse tumor, Ultrasonography, Mathematics, Mice, Inbred BALB C, Blood Volume, Radiological and Ultrasound Technology, business.industry, Ultrasound, Blood flow, Models, Theoretical, Dynamic contrast, 030220 oncology & carcinogenesis, business, Nuclear medicine, Perfusion, Algorithms
Abstract: Dynamic contrast-enhanced ultrasound has been proposed to monitor tumor therapy, as a complement to volume measurements. To assess the variability of perfusion parameters in ideal conditions, four consecutive test-retest studies were acquired in a mouse tumor model, using controlled injections. The impact of mathematical modeling on parameter variability was then investigated. Coefficients of variation (CV) of tissue blood volume (BV) and tissue blood flow (BF) based-parameters were estimated inside 32 sub-regions of the tumors, comparing the log-normal (LN) model with a one-compartment model fed by an arterial input function (AIF) and improved by the introduction of a time delay parameter. Relative perfusion parameters were also estimated by normalization of the LN parameters and normalization of the one-compartment parameters estimated with the AIF, using a reference tissue (RT) region. A direct estimation (rRTd) of relative parameters, based on the one-compartment model without using the AIF, was also obtained by using the kinetics inside the RT region. Results of test-retest studies show that absolute regional parameters have high CV, whatever the approach, with median values of about 30% for BV, and 40% for BF. The positive impact of normalization was established, showing a coherent estimation of relative parameters, with reduced CV (about 20% for BV and 30% for BF using the rRTd approach). These values were significantly lower (p
Published: 2017
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9. Evaluation of Left Ventricular Diastolic Function Using 4D Flow Magnetic Resonance Imaging

Author: Sophia Houriez-Gombaud-Saintonge, Alain Giron, Gilles Soulat, Elie Mousseaux, Jerome Lamy, Alban Redheuil, Yasmina Chenoune, Emilie Bollache, Alain De Cesare, Umit Gencer, Kevin Bouaou, Thomas Dietenbeck, Youssef Alattar, and Nadjia Kachenoura
Subjects: medicine.medical_specialty, Aorta, business.industry, Ultrasound, Healthy subjects, 030204 cardiovascular system & hematology, Mr imaging, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, Internal medicine, medicine.artery, Mitral valve, cardiovascular system, Cardiology, Medicine, Diastolic function, Aortic stiffness, business, Pulse wave velocity
Abstract: Aim: to 1) evaluate the ability of 4D flow MRI to assess left ventricular (LV) diastolic function, as compared to ultrasound (US), 2) analyse simultaneously LV filling and aortic stiffness in aging. Method: We studied 36 healthy subjects (52±18 years) who underwent MRI and US exams. A custom software was used for LV segmentation and calculation of transmitral flow-rate curves in a 4D flow MRI stack of slices located between the mitral valve and the apex and perpendicular to the LV long axis. Finally, the early (E) and late (A) flow-rate peaks were automatically detected and the E/A ratio was computed. Aortic pulse wave velocity (PWV) was also calculated from the 4D flow images. Results: A significant and high correlation was found between 4D flow and US E/A (R=0.71, p 4D =-0.87, p US =-0.69, p
Published: 2018
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10. Kinetic index combining native and postcontrast myocardial T1 in hypertrophic cardiomyopathy

Author: Gilles Soulat, Scott Reid, Alain De Cesare, Laila Besson-Hajji, Nadjia Kachenoura, Golmehr Ashrafpoor, Alban Redheuil, Elie Mousseaux, Albert Hagège, and Martin J. Graves
Subjects: medicine.medical_specialty, Receiver operating characteristic, business.industry, Myocardial hypertrophy, Internal medicine, Cardiology, medicine, Hypertrophic cardiomyopathy, Radiology, Nuclear Medicine and imaging, business, medicine.disease, Left ventricular wall
Abstract: Background To evaluate ability of pre- and postcontrast apparent T1* indices, as well as their combination to characterize myocardial structural changes in hypertrophic cardiomyopathy (HCM). Methods Study protocol was approved by institutional review board and informed consent was obtained. T1 mapping was performed using MOLLI sequence (1.5T magnet) on: (i) tubes with known T1 and varied heart-rates (HR), (ii) 17 HCM (55 ± 15 years) and 18 controls (49 ± 16 years), before contrast and every 5 min over 20 min postcontrast. Global and segmental native T1 (T1*Native), extracellular volume (ECV) and percentage of decrease in myocardial T1* (T1*decay = 100·[1-T1*Post-contrast/T1*Native]) were estimated. Correlation coefficients of associations between T1 and LV indices, such as left ventricular wall thickness (WT) and mass index (LVMi) were provided. Receiver operator curve analysis was performed on per-patient basis to assess ability of T1* indices to identify HCM. Results While up to a T1* of 1000 ms the effect of HR was minor, it was more pronounced above 1000 ms. T1*Native (754 ± 76 ms versus 1014 ± 130 ms, P 0.51/ > 0.45(P < 0.05) for T1*decay5, 20min). T1*Native (97.1%) and T1*decay (91.2%) characterized HCM with higher accuracy (P < 0.02) than ECV (69%). Conclusion T1*Native and T1*decay were able to characterize HCM more accurately than ECV, even in the absence of myocardial hypertrophy and late-gadolinium enhancement. J. Magn. Reson. Imaging 2015.
Published: 2015
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11. Non-invasive differentiation of idiopathic inflammatory myopathy with cardiac involvement from acute viral myocarditis using cardiovascular magnetic resonance imaging T1 and T2 mapping

Author: Adrian T. Huber, Marine Bravetti, Jérôme Lamy, Tania Bacoyannis, Charles Roux, Alain de Cesare, Aude Rigolet, Olivier Benveniste, Yves Allenbach, Mathieu Kerneis, Philippe Cluzel, Nadjia Kachenoura, Alban Redheuil, Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut de cardiologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Service de radiologie cardiovasculaire et interventionnelle [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), University of Bern, Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Service de médecine interne [CHU Pitié-Salpétrière], Centre de Recherche en Myologie, Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Service de Cardiologie [CHU Pitié-Salpêtrière], AH received a research grant from the Helmut-Hartweg-Foundation of the Swiss Academy of Medical Sciences (SAMS). JL received a research grant from the Institute of Cardiometabolism and Nutrition (ICAN). The project was financially supported by the Institut Universitaire d’Ingénierie en Santé (IUIS)., BMC, BMC, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Service de Radiologie cardiovasculaire et interventionnelle [CHU Pitié-Salpêtrière], Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), and Centre de recherche en Myologie – U974 SU-INSERM
Subjects: Adult, Male, lcsh:Diseases of the circulatory (Cardiovascular) system, [SDV]Life Sciences [q-bio], Magnetic Resonance Imaging, Cine, Skeletal muscle, 610 Medicine & health, Diagnosis, Differential, Young Adult, Predictive Value of Tests, CMR T1/T2 mapping, Humans, Muscle, Skeletal, Aged, Retrospective Studies, Myositis, Research, Heart, Middle Aged, Thorax, Systemic myositis, [SDV] Life Sciences [q-bio], Myocarditis, Cardiac inflammation, lcsh:RC666-701, Female, Extracellular volume
Abstract: International audience; BACKGROUND:Idiopathic inflammatory myopathy (IIM) is a group of autoimmune diseases with systemic myositis which may involve the myocardium. Cardiac involvement in IIM, although often subclinical, may mimic clinical manifestations of acute viral myocarditis (AVM). Our aim was to investigate the usefulness of the combined analysis of cardiovascular magnetic resonance (CMR) T1 and T2 mapping parameters measured both in the myocardium and in the thoracic skeletal muscles to differentiate AVM from IIM cardiac involvement.METHODS:Sixty subjects were included in this retrospective study (36 male, age 45 ± 16 years): twenty patients with AVM, twenty patients with IIM and cardiac involvement and twenty healthy controls. Study participants underwent CMR imaging with modified Look-Locker inversion-recovery (MOLLI) T1 mapping and 3-point balanced steady-state-free precession T2 mapping. Relaxation times were quantified after endocardial and epicardial delineation on basal and medial short-axis slices, as well as in different thoracic skeletal muscle groups present in the CMR field-of-view. ROC-Analysis was performed to assess the ability of mapping indices to discriminate the study groups.RESULTS:Mapping parameters in the thoracic skeletal muscles were able to discriminate between AVM and IIM patients. Best skeletal muscle parameters to identify IIM from AVM patients were reduced post-contrast T1 and increased extracellular volume (ECV), resulting in an area under the ROC curve (AUC) of 0.95 for post-contrast T1 and 0.96 for ECV. Conversely, myocardial mapping parameters did not discriminate IIM from AVM patients but increased native T1 (AUC 0.89 for AVM; 0.84 for IIM) and increased T2 (AUC 0.82 for AVM; 0.88 for IIM) could differentiate both patient groups from healthy controls.CONCLUSION:CMR myocardial mapping detects cardiac inflammation in AVM and IIM compared to normal myocardium in healthy controls but does not differentiate IIM from AVM. However, thoracic skeletal muscle mapping was able to accurately discern IIM from AVM.
Published: 2018
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12. Scan-rescan reproducibility of ventricular and atrial MRI feature tracking strain

Author: Adrian Thomas Huber, Benoit Diebold, Morgane Evin, Nadjia Kachenoura, Gilles Soulat, Alban Redheuil, Elie Mousseaux, Alain Giron, Jerome Lamy, Alain De Cesare, Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Service de radiologie cardio-vasculaire [CHU HEGP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Institut de cardiologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Service de radiologie cardiovasculaire et interventionnelle [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Paris-Centre de Recherche Cardiovasculaire (PARCC - UMR-S U970), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris, Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Pitié-Salpêtrière [APHP], and Service d'imagerie cardiovasculaire et de radiologie interventionnelle [CHU Pitié-Salpêtrière]
Subjects: Male, Heart Ventricles, Heart chamber, Left atrium, Magnetic Resonance Imaging, Cine, MAGNETIC RESONANCE IMAGING, Health Informatics, 030204 cardiovascular system & hematology, COEUR, 030218 nuclear medicine & medical imaging, MEDECINE, 03 medical and health sciences, 0302 clinical medicine, EVALUATION, DEFORMATION, REPRODUCIBILITY, medicine, Image Processing, Computer-Assisted, Humans, Heart Atria, CINETIQUE, Aged, Reproducibility, medicine.diagnostic_test, Strain (chemistry), REPRODUCTIBILITE, business.industry, HEART CHAMBERS, Reproducibility of Results, Magnetic resonance imaging, Middle Aged, FEATURE TRACKING, Computer Science Applications, MYOCARDIAL STRAIN, medicine.anatomical_structure, Fractional area change, Radial motion, Feature tracking, Female, [SDV.IB]Life Sciences [q-bio]/Bioengineering, ETUDE CLINIQUE, Nuclear medicine, business, Algorithms, IMAGERIE A RESONNANCE MAGNETIQUE
Abstract: Background A feature tracking (FT) was designed to simultaneously extract myocardial strains in main cardiac chambers from cine MRI images. Its inter-observer and scan-rescan reproducibility was assessed and sample sizes required to detect predefined longitudinal changes in strain values were provided. Method FT was applied on left (LV) and right (RV) ventricles as well as left atrium (LA) of 21 individuals (66 ± 10 years) who underwent 2 MRIs 2 weeks apart. Global peaks for radial, circumferential, longitudinal strains, radial motion fraction (Mr), fractional area change (FAC) and tricuspid annular plane excursion (TAPSE) were estimated. Inter-operator and inter-exam reproducibility were evaluated using coefficients of variations (CV) and intra-class correlation coefficients (ICC). Results Reproducibility of all measurements were good to excellent for inter-operator (LV:CV 0.91; RV:CV 0.86; LA:CV 0.85) and inter-study (LV:CV 0.65; RV:CV 0.71; LA:CV 0.83) evaluations. Reasonable sample sizes are required to detect a longitudinal difference of 10–15% in strain values (LV:5 to 33 individuals, RV:14 to 62 individuals, LA:4 to 65 individuals). Conclusions FT-based functional evaluation of main heart chamber deformation from cine MRI is repeatable and thus suitable for follow-up. Strain measurements may help for the joint clinical evaluation of LV, RV or LA implication in various cardiomyopathies.
Published: 2018
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13. 5.6 Aortic Pressure Behind Flow Disorganization in Aneurismal Aorta: a Magnetic Resonance Imaging Study

Author: Ioannis Bargiotas, Didier Lucor, Sophia Houriez—Gombaud-Saintonge, Emilie Bollache, Umit Gencer, Kevin Bouaou, Elie Mousseaux, Alban Redheuil, Nadjia Kachenoura, Alain De Cesare, Gilles Soulat, Thomas Dietenbeck, and Alain Giron
Subjects: lcsh:Diseases of the circulatory (Cardiovascular) system, Aorta, lcsh:Specialties of internal medicine, medicine.diagnostic_test, business.industry, Magnetic resonance imaging, General Medicine, Nuclear magnetic resonance, Flow (mathematics), lcsh:RC581-951, lcsh:RC666-701, medicine.artery, Aortic pressure, medicine, business
Abstract: Purpose: Understanding and prediction of ascending thoracic aortic aneurysms (ATAA) progression are not well established yet and aortic dissection is frequently occurring on normally sized and mildly dilated aortas. Despite known theoretical associations between pressures and blood flow patterns there are no studies focusing on their simultaneous evaluation. Our aim was to propose a comprehensive and quantitative evaluation of pressure-flow-wall interplay from 4D flow MRI in the setting of aortic dilation. Methods: We studied 12 patients with ATAA (67 ± 14 years, 7 males) and 12 healthy subjects (63 ± 12 years, 8 males) who underwent 4D flow MRI. The segmented velocity fields were used to estimate: 1) local ascending aorta (AA) pressure changes from Navier-Stokes-derived relative pressure maps (AADP, mmHg), 2) AA wall shear stress (AAWSS, Pa) by estimating local velocity derivatives at the aortic borders, 3) aortic flow vorticity using the λ2 method (AAV, s-1). Results: AA local pressure change (AADP) was significantly associated with both AAV (r = 0.55, p = 0.006) and AAWSS (r = 0.69, p < 0.001) and both associations remained significant after adjustment for diameter, age and BSA (p = 0.007 and p = 0.003 respectively). Such positive associations indicate that local pressure variations affect local blood flow, generating flow current from high to low pressures and subsequently vortices with the underlying stress exerted on the AA wall. Conclusion: Local variations in aortic pressures, measured using 4D flow MRI, are associated with flow disorganization as quantified by vorticity and with the increase in the stress exerted on the aortic wall, as quantified by wall shear stress.
Published: 2020
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14. MR and applanation tonometry derived aortic impedance: Association with aging and left ventricular remodeling

Author: Nadjia Kachenoura, Elie Mousseaux, Ioannis Bargiotas, Emilie Bollache, Alban Redheuil, Alain De Cesare, and Alain Giron
Subjects: medicine.medical_specialty, medicine.diagnostic_test, business.industry, Pulsatile flow, Magnetic resonance imaging, 030204 cardiovascular system & hematology, medicine.disease, Characteristic impedance, 030218 nuclear medicine & medical imaging, Reflection Magnitude, Compliance (physiology), 03 medical and health sciences, 0302 clinical medicine, Afterload, Internal medicine, medicine, Cardiology, Radiology, Nuclear Medicine and imaging, Ventricular remodeling, business, Pulse wave velocity
Abstract: Purpose We sought to noninvasively estimate aortic impedance indices from MR and tonometric data. Materials and Methods MR aortic velocity-encoded and carotid applanation tonometry pressure data of 70 healthy subjects (19–79 years) were used to calculate the following indices from impedance spectrum: (i) characteristic impedance (Zc) reflecting pulsatile component of left ventricular (LV) afterload, (ii) frequency of the minimal impedance magnitude related to arterial compliance (FMIN), (iii) total peripheral resistance (TPR) related to steady LV load, (iv) impedance oscillatory index (ZINDEX) related to proximal reflections, and (v) reflection magnitude (RM). Associations with age and LV remodeling (LV mass/end-diastolic volume) were investigated using multivariate analysis. Results All indices except Zc were associated with age independent of subjects characteristics and systolic blood pressures. They were all significantly associated with the well-established carotid-femoral pulse wave velocity (r ≥ 0.29; P < 0.01). However, such associations were not independent of age. Pulsatile index Zc was independently associated with carotid pulse pressure (r = 0.53, P < 0.001). Moreover, conversely to conventional stiffness indices, Zc and TPR were independently associated with LV remodeling (r = 0.30, r = 0.43, respectively, P < 0.01). Conclusion We estimated aortic impedance from velocity-encoded MR and tonometry data resulting in reliable impedance and reflection indices as confirmed by their significant and independent associations with age and LV remodeling. J. Magn. Reson. Imaging 2015;41:781–787. © 2014 Wiley Periodicals, Inc.
Published: 2014
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15. Relative Aortic Blood Pressure Using 4D Flow MRI: Associations with Age and Aortic Tapering

Author: Alain De Cesare, Alban Redheuil, Kevin Bouaou, Thomas Dietenbeck, Gilles Soulat, Ioannis Bargiotas, Didier Lucor, Umit Gencer, Damian Craiem, Elie Mousseaux, Nadjia Kachenoura, Sophia Houriez-Gombaud-Saintonge, Alain Giron, Laboratoire d'Imagerie Biomédicale [Paris] (LIB), and Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Aortic valve, Aorta, medicine.medical_specialty, Peak systolic pressure, Cardiac cycle, business.industry, Tapering, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, [SPI]Engineering Sciences [physics], 0302 clinical medicine, Blood pressure, medicine.anatomical_structure, medicine.artery, Internal medicine, medicine, Cardiology, Aortic pressure, business, 030217 neurology & neurosurgery, Pressure gradient
Abstract: MRI 4D flow velocity is used to evaluate relative blood pressures in the aorta throughout the cardiac cycle. This (3D+t) pressure mapping is used to assess: 1) relationship between trans-aortic pressure gradient with age and aortic tapering (proximal to distal narrowing in lumen area), 2) effect of temporal resolution. We studied 47 healthy subjects (49±17.6 years, 24 men) who underwent 4D flow MRI, among them 20 were reconstructed in 20 and 50 phases per cardiac cycle. Pressure gradients maps were estimated from velocity fields using the Navier-Stokes equations. Relative pressures were calculated using an iterative algorithm while considering a zero pressure at the aortic valve. Distal (DA) to proximal (PA) aortic pressure gradient decreased with age (r=0.60, p
Published: 2017
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16. Assessment of Aortic Pulse Wave Velocity Using 4D Flow Magnetic Resonance Imaging: Methods Comparison

Author: Gilles Soulat, Nadjia Kachenoura, Damian Craiem, Elie Mousseaux, Thomas Dietenbeck, Alban Redheuil, Alain De Cesare, Kevin Bouaou, Umit Gencer, Yasmina Chenoune, Sophia Houriez-Gombaud-Saintonge, Ioannis Bargiotas, Laboratoire d'Imagerie Biomédicale [Paris] (LIB), and Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Physics, Aorta, medicine.diagnostic_test, Transit time, Magnetic resonance imaging, 030204 cardiovascular system & hematology, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, [SPI]Engineering Sciences [physics], 0302 clinical medicine, Nuclear magnetic resonance, Wavelet, Method comparison, Temporal resolution, medicine.artery, Descending aorta, medicine, Pulse wave velocity
Abstract: Purpose: Compare various methods of transit time (TT) and consequently aortic Pulse Wave Velocity (aoPWV) estimation from 4D MRI (aoPWV=aortic length/TT), in terms of associations with age and Bramwell-Hill (BH aoPWV). Method: We studied 43 healthy subjects (48±17 yrs.) who had aortic 4DFlow MRI. Three strategies were used to estimate aoPWV: (S1) using flow curves in two aortic locations to calculate TT (ascending (AA) and distal descending aorta (dDA)) as a 2D-like strategy, (S2 and S3) using flow curves of the entire aortic path-line between dDA and AA to estimate TT with various methods: cross-correlation; Fourier and Wavelet or aoPVW by fitting a plan on the systolic upslope of flow curves. Results: Expected associations with age were found for the three strategies with strongest correlations for 3D-like strategies than 2D-like strategy (S2:r=0.75, S3:r=0.72, p
Published: 2017
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17. Regularized linear resolution of a one-compartment model to improve the reproducibility of perfusion parameters in CEUS

Author: Alexandre Dizeux, Alain De Cesare, Frédérique Frouin, Maxime Doury, Lori Bridal, and Olivier Lucidarme
Subjects: Normalization (statistics), Reproducibility, business.industry, Reference tissue, Ultrasound, Tumor therapy, 01 natural sciences, 030218 nuclear medicine & medical imaging, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Mouse tumor, 0101 mathematics, business, Linear resolution, Perfusion, Mathematics, Biomedical engineering
Abstract: Contrast-enhanced ultrasound (CEUS) has been proposed to monitor tumor therapy, in complement to size measurements. Estimating reliable perfusion parameters from CEUS studies is essential in order to propose adapted therapy options according to the parameter values. The variability of these parameters was assessed in an ideal case of consecutive test-retest CEUS studies, in a mouse tumor model. The impact of mathematical modeling on parameter variability was investigated on these data. Four models were compared in 32 tumor sub-regions: the log-normal model (LN), the relative LN model (rLN) where parameters of LN are normalized by the parameters estimated inside a reference tissue (RT) region, a linear resolution of a one-compartment model based on the RT (rLin), a modified version of rLin implementing regularization (rLinReg) to ensure coherent results between the different sub-regions of the tumor. Results show that LN model had highest coefficients of variation. The positive impact of normalization using RT (rLN) was established, showing reduced coefficients of variation. The rLin approach showed large variations especially for flow parameters. Its regularization version, rLinReg, greatly improved parameter reproducibility while providing coherent results between the sub-regions. In conclusion,the rLinReg approach provided the smallest coefficients of variations and should be preferred for estimating perfusion parameters in CEUS.
Published: 2016
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18. Pulmonary artery stiffness is independently associated with right ventricular mass and function: a cardiac MR imaging study

Author: Alain De Cesare, Ajay Gandhi, Antonio de Marvao, Rui Buzaco, Declan P. O'Regan, Marina Quinlan, Tamara Diamond, Laura Monje Garcia, Giuliana Durighel, Pawel Tokarczuk, Stuart A. Cook, and Timothy J W Dawes
Subjects: Adult, Male, medicine.medical_specialty, Pathology, Heart Ventricles, Ventricular Dysfunction, Right, Pulmonary Artery, 030204 cardiovascular system & hematology, 030218 nuclear medicine & medical imaging, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine.artery, medicine, Humans, Radiology, Nuclear Medicine and imaging, Prospective Studies, Pulse wave velocity, Original Research, medicine.diagnostic_test, business.industry, Myocardial feature, Stiffness, Magnetic resonance imaging, Middle Aged, Magnetic Resonance Imaging, Mr imaging, Pulmonary artery, cardiovascular system, Cardiology, Right ventricular mass, Female, medicine.symptom, business
Abstract: Purpose To determine the relationship between pulmonary artery (PA) stiffness and both right ventricular (RV) mass and function with cardiac magnetic resonance (MR) imaging. Materials and Methods The study was approved by the local research ethics committee, and all participants gave written informed consent. Cardiac MR imaging was performed at 1.5 T in 156 healthy volunteers (63% women; age range, 19-61 years; mean age, 36.1 years). High-temporal-resolution phase-contrast imaging was performed in the main and right PAs. Pulmonary pulse wave velocity (PWV) was determined by the interval between arterial systolic upslopes. RV function was assessed with feature tracking to derive peak systolic strain and strain rate, as well as peak early-diastolic strain rate. RV volumes, ejection fraction (RVEF), and mass were measured from the cine images. The association of pulmonary PWV with RV function and mass was quantified with univariate linear regression. Interstudy repeatability was assessed with intraclass correlation. Results The repeatability coefficient for pulmonary PWV was 0.96. Increases in pulmonary PWV and RVEF were associated with increases in age (r = 0.32, P.001 and r = 0.18, P = .025, respectively). After adjusting for age (P = .090), body surface area (P = .073), and sex (P = .005), pulmonary PWV demonstrated an independent positive association with RVEF (r = 0.34, P = .026). Significant associations were also seen with RV mass (r = 0.41, P = .004), RV radial strain (r = 0.38, P = .022), and strain rate (r = 0.35, P = .002), and independent negative associations were seen with radial (r = 0.27, P = .003), longitudinal (r = 0.40, P = .007), and circumferential (r = 0.31, P = .005) peak early-diastolic strain rate with the same covariates. Conclusion Pulmonary PWV is reliably assessed with cardiac MR imaging. In subjects with no known cardiovascular disease, increasing PA stiffness is associated with increasing age and is also moderately associated with both RV mass and function after controlling for age, body surface area, and sex. (©) RSNA, 2016 Online supplemental material is available for this article.
Published: 2016

19. Automated estimation of aortic strain from steady-state free-precession and phase contrast MR images

Author: Claire Pellot-Barakat, Nadjia Kachenoura, Alain De Cesare, Elie Mousseaux, Alain Herment, Martin J. Graves, Valentina Taviani, Frédérique Frouin, and Muriel Lefort
Subjects: Physics, Aorta, medicine.diagnostic_test, Strain (chemistry), Steady-state free precession imaging, 030204 cardiovascular system & hematology, Magnetic resonance angiography, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Nuclear magnetic resonance, medicine.artery, Descending aorta, Ascending aorta, cardiovascular system, medicine, Thoracic aorta, Radiology, Nuclear Medicine and imaging, Pulse wave velocity
Abstract: The strain values extracted from steady-state free-precession (SSFP) and phase contrast (PC) images acquired with a 1.5T scanner on a compliant flow phantom and within the thoracic aorta of 52 healthy subjects were compared. Aortic data were acquired perpendicular to the aorta at the level of the pulmonary artery bifurcation. Cross sectional areas were obtained by using an automatic and robust segmentation method. While a good correlation (r = 0.99) was found between the aortic areas extracted from SSFP and PC sequences, a lower correlation (r = 0.71) was found between the corresponding aortic strain values. Strain values estimated using SSFP and PC sequences were equally correlated with age. Interobserver reproducibility was better for SSFP than for PC. Strain values in the ascending and descending aorta were better correlated for SSFP (r = 0.8) than for PC (r = 0.65) and fitted with the expectation of a larger strain in the ascending aorta when using SSFP. The spatial and temporal resolutions of the acquisitions had a minor influence upon the estimated strain values. Thus, if PC acquisitions can be used to estimate both pulse wave velocity and aortic strain, an additional SSFP sequence may be useful to improve the accuracy in estimating the aortic strain.
Published: 2010
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20. Estimation of aortic pulse wave transit time in MRI using complex wavelet cross-spectrum analysis

Author: Alain De Cesare, Elie Mousseaux, Emilie Bollache, Wen-Chung Yu, Ioannis Bargiotas, Alban Redheuil, Joao A.C. Lima, Bharath Ambale Venkatesh, and Nadjia Kachenoura
Subjects: Cardiac cycle, medicine.disease, Wavelet, Descending aorta, medicine.artery, Temporal resolution, medicine, Arterial stiffness, Time domain, Cross-spectrum, Pulse wave velocity, Simulation, Biomedical engineering, Mathematics
Abstract: Aortic pulse wave velocity (PWV) increases with arterial stiffness and aging and predicts cardiovascular mortality. It is commonly estimated using applanation tonometry at carotid and femoral arterial sites (cfPWV). Although cardiovascular MRI offers reliable segmental measurement of arterial length, accurate transit time (TT) determination between flow curves remains a challenge. We developed a wavelet-based method, which enables temporal localization of signal frequencies, to estimate TT by the weighted phase difference between ascending and descending aorta flow curves. We compared this approach in terms of linear correlations with age, cfPWV and effects of decreasing temporal resolution by factors of 2, 3 and 4, with previous methods which 1) restrict their analysis to systolic upslope (time domain upslopes-archPWVTU) and 2) decompose into harmonics flow curves from the whole cardiac cycle (Fourier-based-archPWVF-robust to low temporal resolution). We studied 71 healthy subjects (45±15 years, 29 females) who underwent MRI velocity acquisitions and cfPWV measurements. Wavelet method provided the highest linear correlations with age and cfPWV and was the most robust to low temporal resolutions. Wavelet method might help to overcome current limitations related to MRI low temporal resolution.
Published: 2015
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21. Left atrium MRI 4D-flow in atrial fibrillation: Association with LA function

Author: Morgane Evin, Carine Defrance, Alain De Cesare, Fraser M. Callaghan, Nadjia Kachenoura, Philippe Cluzel, Stuart M. Grieve, Alban Redheuil, Laboratoire d'Imagerie Biomédicale [Paris] (LIB), and Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Physics, medicine.medical_specialty, Contraction (grammar), medicine.diagnostic_test, Cardiac cycle, Left atrium, Magnetic resonance imaging, Atrial fibrillation, Vorticity, medicine.disease, [SPI]Engineering Sciences [physics], medicine.anatomical_structure, Internal medicine, medicine, Cardiology, Dilation (morphology), Thrombus
Abstract: Left atrium (LA) is a principal site of thrombus formation inducing thromboembolic events, which have been associated with LA low flow velocities. Recent developments in magnetic resonance imaging (MRI) 4D flow analysis enable a non-invasive visualization of LA flow patterns. Our main objective was to investigate modifications of the main vortices in the LA with regards to LA functional indices in 4 patients with atrial fibrillation (AF) and 6 healthy volunteers. Vorticity threshold and Q-criterion indices were computed from the centered vorticity calculation on filtered 4D velocity MRI images. Phasic LA longitudinal strains were computed on cine MRI images using LA feature tracking algorithm. LA dilation in AF came along with a drop in LA longitudinal strains. Best correlations between LA flow and functional changes were found for velocity vs. longitudinal strains corresponding to reservoir and LA contraction phases (r=0.69 and r=0.81, p
Published: 2015
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22. Age-specific changes in left ventricular diastolic function: A velocity-encoded magnetic resonance imaging study

Author: Magalie Ladouceur, Elie Mousseaux, Benoit Diebold, Ludivine Perdrix, Golmehr Ashrafpoor, Alban Redheuil, Emilie Bollache, Nadjia Kachenoura, Carine Defrance, Alain De Cesare, Arshid Azarine, Alain Giron, Laboratoire d'Imagerie Biomédicale (LIB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Service de radiologie cardio-vasculaire [CHU HEGP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Université Pierre et Marie Curie - Paris 6 (UPMC)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Institut de cardiologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Service de radiologie cardiovasculaire et interventionnelle [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Service de cardiologie [CHU HEGP], Paris-Centre de Recherche Cardiovasculaire (PARCC - UMR-S U970), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Service de Radiologie cardiovasculaire et interventionnelle [CHU Pitié-Salpêtrière], Gestionnaire, Hal Sorbonne Université, Laboratoire d'Imagerie Biomédicale [Paris] (LIB), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)
Subjects: Adult, Male, medicine.medical_specialty, Aging, Heart Ventricles, [SDV]Life Sciences [q-bio], Cardiomyopathy, Diastole, Magnetic Resonance Imaging, Cine, 030204 cardiovascular system & hematology, Ventricular Function, Left, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Internal medicine, medicine, Humans, Radiology, Nuclear Medicine and imaging, Diastolic function, Neuroradiology, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, medicine.diagnostic_test, business.industry, Ultrasound, Age Factors, Magnetic resonance imaging, General Medicine, Middle Aged, medicine.disease, Healthy Volunteers, [SDV] Life Sciences [q-bio], Blood pressure, Cardiology, Female, Radiology, Isovolumic relaxation time, business, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract: Our objectives were to assess the ability of phasecontrast MRI (PC-MRI) to detect sub-clinical age-related variations of left ventricular (LV) diastolic parameters and thus to provide age-related reference ranges currently available for echocardiography but not for MRI-PC, and to identify independent associates of such variations. We studied 100 healthy volunteers (age = 42 ± 15years, 50 females) who had MRI with simultaneous blood pressure measurements. LV mass and volumes were assessed. Semiautomated analysis of PC-MRI data provided: 1) early transmitral (Ef) and atrial (Af) peak filling flow-rates (ml/s) and filling volume (FV), 2) deceleration time (DT), isovolumic relaxation time (IVRT), and 3) early myocardial longitudinal (E’) peak velocity. MRI-PC diastolic parameters were reproducible as reflected by low coefficients of variations (ranged between 0.31 to 6.26 %). Peak myocardial velocity E’ (r = −0.63, p
Published: 2015
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23. MR and applanation tonometry derived aortic impedance: Association with aging and left ventricular remodeling

Author: Ioannis, Bargiotas, Emilie, Bollache, Elie, Mousseaux, Alain, Giron, Alain, de Cesare, Alban, Redheuil, Nadjia, Kachenoura, Laboratoire d'Imagerie Biomédicale (LIB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Paris-Centre de Recherche Cardiovasculaire (PARCC - UMR-S U970), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Université Pierre et Marie Curie - Paris 6 (UPMC)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Institut de cardiologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Service de radiologie cardiovasculaire et interventionnelle [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)
Subjects: Adult, Male, left ventricular remodeling, Aging, Ventricular Remodeling, Manometry, Heart Ventricles, Blood Pressure, Middle Aged, Young Adult, Electric Impedance, Humans, magnetic resonance imaging, Female, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], aortic impedance, reflections, Aorta, Blood Flow Velocity, Aged
Abstract: International audience; Purpose: We sought to noninvasively estimate aortic impedance indices from MR and tonometric data.Materials and methods: MR aortic velocity-encoded and carotid applanation tonometry pressure data of 70 healthy subjects (19-79 years) were used to calculate the following indices from impedance spectrum: (i) characteristic impedance (Zc) reflecting pulsatile component of left ventricular (LV) afterload, (ii) frequency of the minimal impedance magnitude related to arterial compliance (FMIN ), (iii) total peripheral resistance (TPR) related to steady LV load, (iv) impedance oscillatory index (ZINDEX ) related to proximal reflections, and (v) reflection magnitude (RM). Associations with age and LV remodeling (LV mass/end-diastolic volume) were investigated using multivariate analysis.Results: All indices except Zc were associated with age independent of subjects characteristics and systolic blood pressures. They were all significantly associated with the well-established carotid-femoral pulse wave velocity (r ≥ 0.29; P < 0.01). However, such associations were not independent of age. Pulsatile index Zc was independently associated with carotid pulse pressure (r = 0.53, P < 0.001). Moreover, conversely to conventional stiffness indices, Zc and TPR were independently associated with LV remodeling (r = 0.30, r = 0.43, respectively, P < 0.01).Conclusion: We estimated aortic impedance from velocity-encoded MR and tonometry data resulting in reliable impedance and reflection indices as confirmed by their significant and independent associations with age and LV remodeling.
Published: 2015
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24. Modeling anisotropic undersampling of magnetic resonance angiographies and reconstruction of a high-resolution isotropic volume using half-quadratic regularization techniques

Author: Elie Mousseaux, Alain Herment, Alain De Cesare, Mila Nikolova, Isabelle Bloch, and Elodie Roullot
Subjects: business.industry, Iterative method, Fast Fourier transform, Image processing, Iterative reconstruction, Regularization (mathematics), Control and Systems Engineering, Undersampling, Conjugate gradient method, Signal Processing, Computer vision, Computer Vision and Pattern Recognition, Artificial intelligence, Electrical and Electronic Engineering, business, Algorithm, Image resolution, Software, Mathematics
Abstract: In this paper we address the problem of reconstructing a high resolution volumic image from several low resolution data sets. A solution to this problem is proposed in the particular framework of magnetic resonance angiography (MRA), where the resolution is limited by a trade-off between the spatial resolution and the acquisition time, both being proportional to the number of samples acquired in k-space. For this purpose only the meaningful spatial frequencies of the 3D k-space of the vessel are acquired, which is achieved using successive acquisitions with decreased spatial resolution, leading to highly anisotropic data sets in one or two specific directions. The reconstruction of the MRA volume from these data sets relies on an edge-preserving regularization method and leads to two different implementations: the first one is based on a conjugate gradient algorithm, and the second one on half-quadratic developments. The hyper parameters of the method were experimentally determined using a set of simulated data, and promising results were obtained on aorta and carotid artery acquisitions, where on the one hand a good fidelity to the acquired data is maintained, and on the other hand homogeneous areas are smooth and edges are well preserved. Half-quadratic regularization proved to be particularly well adapted to the MRA problem and leads to a fast iterative algorithm requiring only scalar and FFT computations.
Published: 2004
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25. How to estimate aortic characteristic impedance from magnetic resonance and applanation tonometry data?

Author: Nadjia Kachenoura, Alain De Cesare, Alban Redheuil, Mourad Bensalah, Didier Lucor, Alain Giron, Ioannis Bargiotas, Elie Mousseaux, Emilie Bollache, Bargiotas, Ioannis, Laboratoire d'Imagerie Biomédicale (LIB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut Jean le Rond d'Alembert (DALEMBERT), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Institut de cardiologie [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Paris-Centre de Recherche Cardiovasculaire (PARCC - UMR-S U970), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), and Laboratoire d'Imagerie Biomédicale [Paris] (LIB)
Subjects: Applanation tonometry, Adult, Male, medicine.medical_specialty, Magnetic Resonance Spectroscopy, Physiology, Manometry, Systole, Pulsatile flow, Blood Pressure, Characteristic impedance, Pressure waveform, Internal medicine, medicine.artery, Ascending aorta, Internal Medicine, medicine, Electric Impedance, Humans, Aorta, Aged, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], medicine.diagnostic_test, business.industry, Mean age, Magnetic resonance imaging, Middle Aged, medicine.anatomical_structure, Ventricle, Hypertension, Cardiology, Female, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Cardiology and Cardiovascular Medicine, business
Abstract: International audience; Objectives: Compare seven previous methods for the estimation of aortic characteristic impedance, which contributes to left ventricle pulsatile load, from phase-contrast cardiovascular magnetic resonance (CMR) and applanation tonometry data.Methods: We studied 77 healthy (43 ± 16 years) individuals and 16 hypertensive (61 ± 9 years) patients, who consecutively underwent ascending aorta CMR and carotid tonometry, resulting in flow and pressure waveforms, respectively. Characteristic impedance was semi-automatically estimated in time domain from these latter waveforms, using seven methods. The methods were based on the following: methods 1-4, magnitudes at specific times; method 5, early-systolic up-slope; method 6, time-derivatives peak; and method 7, pressure-flow loop early-systolic slope.Results: Aortic characteristic impedance was significantly increased in hypertensive patients when compared to elderly controls (n = 32) with a similar mean age of (59 ± 8 years) when using methods based on 95% of peak flow, up-slopes, and derivatives peaks (P < 0.05). When considering healthy individuals, impedance indices were significantly correlated to central pulse pressure for all methods (P < 0.005). Finally, characteristic impedance was correlated to the frequency-domain reference values (r > 0.65, P < 0.0001), with a slight superiority for the same three methods as above (r > 0.82, P < 0.0001).Conclusions: This is the first study demonstrating phase-contrast CMR and tonometry usefulness in aortic characteristic impedance temporal estimation. Methods based on 95% of peak flow, as well as those based on derivative peaks and up-slopes, which are fast and independent of curve preprocessing, were slightly superior. They can be easily integrated in a clinical workflow and may help to understand the complementarity of this pulsatile index with other CMR aortic geometry and stiffness measures in the setting of left ventricle-aortic coupling.
Published: 2015
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26. Geometry is a major determinant of flow reversal in proximal aorta

Author: Nadjia Kachenoura, Laurent Macron, Alban Redheuill, Elie Mousseaux, Alain Giron, Alain De Cesare, Mourad Bensalah, Muriel Lefort, Emilie Bollache, Laboratoire d'Imagerie Biomédicale (LIB), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), Paris-Centre de Recherche Cardiovasculaire (PARCC - UMR-S U970), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Service de radiologie cardio-vasculaire [CHU HEGP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Hôpital Européen Georges Pompidou [APHP] (HEGP), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: Adult, Male, medicine.medical_specialty, Materials science, Magnetic Resonance Spectroscopy, Physiology, [SDV]Life Sciences [q-bio], Blood Pressure, Pulse Wave Analysis, aortic flow reversal, Nuclear magnetic resonance, Vascular Stiffness, Physiology (medical), medicine.artery, medicine, magnetic resonance imaging, Humans, Aorta, Aged, medicine.diagnostic_test, aging, Magnetic resonance imaging, Middle Aged, medicine.disease, Surgery, arterial stiffness, Cross-Sectional Studies, Flow (mathematics), Regional Blood Flow, Multivariate Analysis, Arterial stiffness, Female, Cardiology and Cardiovascular Medicine, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Mathematics
Abstract: The aim of this study is to quantify aortic backward flow (BF) using phase-contrast cardiovascular magnetic resonance (PC-CMR) and to study its associations with age, indexes of arterial stiffness, and geometry. Although PC-CMR blood flow studies showed a simultaneous presence of BF and forward flow (FF) in the ascending aorta (AA), the relationship between aortic flows and aging as well as arterial stiffness and geometry in healthy volunteers has never been reported. We studied 96 healthy subjects [47 women, 39 ± 15 yr old (19–79 yr)]. Aortic stiffness [arch pulse wave velocity (PWVAO), AA distensibility], geometry (AA diameter and arch length), and parameters related to AA BF and FF (volumes, peaks, and onset times) were estimated from CMR. Applanation tonometry carotid-femoral pulse-wave velocity (PWVCF), carotid augmentation index, and time to return of the reflected pressure wave were assessed. Whereas FF parameters remained unchanged, BF onset time shortened significantly ( R2 = 0.18, P < 0.0001) and BF volume and BF-to-FF peaks ratio increased significantly ( R2 = 0.38 and R2 = 0.44, respectively, P < 0.0001) with aging. These two latter BF indexes were also related to stiffness indexes (PWVCF, R2 > 0.30; PWVAO, R2 > 0.24; and distensibility, R2 > 0.20, P < 0.001), augmentation index ( R2 > 0.20, P < 0.001), and aortic geometry (AA diameter, R2 > 0.58; and arch length, R2 > 0.31, P < 0.001). In multivariate analysis, aortic diameter was the strongest independent correlate of BF beyond age effect. In conclusion, AA BF estimated using PC-CMR increased significantly in terms of magnitude and volume and appeared earlier with aging and was mostly determined by aortic geometry. Thus BF indexes could be relevant markers of subclinical arterial wall alterations.
Published: 2014
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27. Spatial regularization of flow patterns in magnetic resonance velocity mapping

Author: Philippe Dumee, Jaeeprs Bittoun, Andrew Todd-Pokropek, Alain Herment, Elie Mousseaux, Alain De Cesare, and O. Jolivet
Subjects: Physics, medicine.diagnostic_test, Pixel, Mean squared error, Image quality, business.industry, Noise reduction, Mathematical analysis, Magnetic resonance imaging, Velocimetry, Classification of discontinuities, Regularization (mathematics), medicine, Radiology, Nuclear Medicine and imaging, Nuclear medicine, business
Abstract: A technique dedicated to spatial regularization of magnetic resonance (MR) velocity data has been implemented to improve flow image quality. It is assumed that neighboring flow-velocity pixels are partially correlated, although large-velocity discontinuities remain possible. Increasing MR signal magnitude due to the in-flow effect also is used to enhance further reliability of the estimated velocity. By using an eight-step Fourier-encoding approach, 162 "reference" velocity images acquired in the ascending aorta from six healthy volunteers were compared with "raw" and "regularized" images that were computed from only two gradient steps. The mean square error decreased from 0.12 m(2) x s(-2) to 0.06 m(2) x s(-2) (P < 10-9) for velocity pixel values and from 1929 ml(2) x s(-2) to 1336 ml(2) x s(-2) (P < 0.01) for instantaneous flow rates. The regularization of two-step data sets provides the same velocity image quality as that found after using three-step data sets without regularization. The method can be applied to phase-velocity data sets of any MR technique to reduce velocity noise. J. Magn. Reson. Imaging 1999;10:851-860.
Published: 1999
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28. Improved estimation of the left ventricular ejection fraction using a combination of independent automated segmentation results in cardiovascular magnetic resonance imaging

Author: jessica lebenberg, Alain Lalande, Patrick Clarysse, Irène Buvat, Christopher Casta, Alexandre Cochet, Constantin Constantinides, Jean Cousty, Alain de Cesare, Stéphanie Jehan-Besson, Muriel Lefort, Laurent Najman, Elodie Roullot, Laurent Sarry, Christophe Tilmant, Frédérique Frouin, Mireille Garreau, Lebenberg, Jessica, Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales (MOTIVATE), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service Hospitalier Frédéric Joliot (SHFJ), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, ESME Sudria, Pôle de Recherche en Ingénierie Appliquée à la Médecine (PRIAM), ESME Sudria [Paris]-ESME Sudria [Paris], Laboratoire d'Informatique Gaspard-Monge (LIGM), Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM), Image Science for Interventional Techniques (ISIT), Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Centre National de la Recherche Scientifique (CNRS), Institut Pascal (IP), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-SIGMA Clermont (SIGMA Clermont)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC)-ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique (CNRS), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire d'Imagerie Fonctionnelle ( LIF ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), 1 - Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales ( MOTIVATE ), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Service Hospitalier Frédéric Joliot ( SHFJ ), Direction de Recherche Fondamentale (CEA) ( DRF (CEA) ), Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay, Pôle de Recherche en Ingénierie Appliquée à la Médecine ( PRIAM ), Laboratoire d'Informatique Gaspard-Monge ( LIGM ), Université Paris-Est Marne-la-Vallée ( UPEM ) -École des Ponts ParisTech ( ENPC ) -ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique ( CNRS ), Image Science for Interventional Techniques ( ISIT ), Université d'Auvergne - Clermont-Ferrand I ( UdA ) -Clermont Université-Centre National de la Recherche Scientifique ( CNRS ), Institut Pascal ( IP ), Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ) -Sigma CLERMONT ( Sigma CLERMONT ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire Traitement du Signal et de l'Image ( LTSI ), Université de Rennes 1 ( UR1 ), and Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National de la Santé et de la Recherche Médicale ( INSERM )
Subjects: [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, [ SDV.MHEP.CSC ] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system
Abstract: —This work aimed at combining different segmenta-tion approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method. Then, we used an unsupervised statistical evaluation, the extended Regression Without Truth (eRWT) that ranks different methods according to their accuracy in estimating a specific biomarker in a population. The segmentation accuracy was evaluated by focusing on the left ventricular ejection fraction (LVEF) estimate resulting from the LV contour delineation using a public cardiac cine MRI database. Eight different segmentation methods, including three expert delineations, were studied, and sixteen combinations of the five automated methods were investigated. The supervised and unsupervised evaluations demonstrated that in most cases, STAPLE results provided better estimates of the LVEF than individual automated segmentation methods. In addition, LVEF obtained with STAPLE were within inter-expert variability. Overall, combining different automated segmentation methods improved the reliability of the segmenta-tion result compared to that obtained using an individual method
Published: 2014

29. Definition of a mutual reference shape based on information theory and active contours

Author: Stéphanie Jehan-Besson, Christophe Tilmant, Alain de Cesare, Alain Lalande, Alexandre Cochet, Jean Cousty, Jessica Lebenberg, Muriel Lefort, Patrick Clarysse, Régis Clouard, Laurent Najman, Laurent Sarry, Frédérique Frouin, Mireille Garreau, Equipe Image - Laboratoire GREYC - UMR6072, Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS), Institut Pascal (IP), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-SIGMA Clermont (SIGMA Clermont)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique Gaspard-Monge (LIGM), Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC)-ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique (CNRS), Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales (MOTIVATE), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Image Science for Interventional Techniques (ISIT), Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Centre National de la Recherche Scientifique (CNRS), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Action MediEval (Medical Image segmentation Evaluation) du GDR Stic Santé, Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen ( GREYC ), Université de Caen Normandie ( UNICAEN ), Normandie Université ( NU ) -Normandie Université ( NU ) -Ecole Nationale Supérieure d'Ingénieurs de Caen ( ENSICAEN ), Normandie Université ( NU ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Caen Normandie ( UNICAEN ), Normandie Université ( NU ) -Centre National de la Recherche Scientifique ( CNRS ), Institut Pascal ( IP ), Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ) -Sigma CLERMONT ( Sigma CLERMONT ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'Imagerie Fonctionnelle ( LIF ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'Informatique Gaspard-Monge ( LIGM ), Université Paris-Est Marne-la-Vallée ( UPEM ) -École des Ponts ParisTech ( ENPC ) -ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique ( CNRS ), 1 - Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales ( MOTIVATE ), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Image Science for Interventional Techniques ( ISIT ), Université d'Auvergne - Clermont-Ferrand I ( UdA ) -Clermont Université-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire Traitement du Signal et de l'Image ( LTSI ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Jehan-Besson, Stéphanie, and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)
Subjects: [ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing, segmentation evaluation, [ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, average shape, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, active contours, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], shape gradients, Image processing, cardiac MRI, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [ INFO.INFO-TI ] Computer Science [cs]/Image Processing, shape optimization, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, information theory
Abstract: In this paper, we propose to consider the estimation of a reference shape from a set of different segmentation results using both active contours and information theory. The reference shape is then defined as the minimum of a criterion that benefits from both the mutual information and the joint entropy of the input segmentations. This energy criterion is here justified using similarities between information theory quantities and area measures, and presented in a continuous variational framework. This framework brings out some interesting evaluation measures such as the specificity and sensitivity. In order to solve this shape optimization problem, shape derivatives are computed for each term of the criterion and interpreted as an evolution equation of an active contour. A mutual shape is then estimated together with the sensitivity and specificity. Some synthetical examples allow us to cast the light on the difference between our mutual shape and an average shape. The applicability and robustness of our framework has also been tested for the evaluation of different segmentation methods of the left ventricular cavity from cardiac MRI.
Published: 2013

30. Obesity has divergent effects on aortic stiffness in young and old adults

Author: Alun D. Hughes, Tamara Diamond, Alain De Cesare, Timothy J W Dawes, Declan P. O'Regan, Ben Corden, Giuliana Durighel, Niall G Keenan, Antonio de Marvao, Stuart A. Cook, Robert Steiner MRI Unit, Imperial College London, Department of Cardiology, Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), International Centre for Circulatory Health, and BMC, Ed.
Subjects: Aortic arch, lcsh:Diseases of the circulatory (Cardiovascular) system, medicine.medical_specialty, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Overweight, Body fat percentage, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Internal medicine, medicine.artery, medicine, Radiology, Nuclear Medicine and imaging, 10. No inequality, Pulse wave velocity, ComputingMilieux_MISCELLANEOUS, Medicine(all), Radiological and Ultrasound Technology, business.industry, medicine.disease, 3. Good health, Surgery, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Blood pressure, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, lcsh:RC666-701, Poster Presentation, cardiovascular system, Cardiology, Arterial stiffness, Aortic stiffness, medicine.symptom, Cardiology and Cardiovascular Medicine, business, Bioelectrical impedance analysis
Abstract: Background Aortic pulse wave velocity (PWV), a measure of central arterial stiffness, is an independent predictor of cardiovascular and all-cause mortality and has been associated with numerous cardiovascular risk factors. However, data on the association between obesity and aortic stiffness have been mixed, with some studies showing a positive association, others a negative association and others apposing effects between the sexes. Methods 221 adult volunteers (127 female, age range 18-72 years, mean 40.3 years) were recruited via advertisement. Exclusion criteria included a history of cardiovascularrelated disease, including hypertension, hypercholesterolemia and diabetes. Aortic arch PWV was calculated from the three dimensional vessel length and the transit time between the flow waveforms in the ascending and descending aorta, assessed using Magnetic Resonance Imaging (MRI). Total body fat mass was measured with multi-frequency bioelectrical impedance analysis. Results Multiple linear regression analyses showed that, when age, sex and systolic blood pressure were adjusted for, higher body fat percentage was associated with lower aortic PWV (p = 0.004). These effects were similar for both men and women (p = 0.60 for a sex by body fat interaction). Further analysis revealed a significant age by body fat interaction (p < 0.001, see figure 1) such that, in young adults obesity predicted a lower PWV whereas in older adults obesity predicted a higher PWV. Conclusions The effect of obesity on aortic stiffness is age-dependant: in older adults being overweight predicts stiffer central arteries but it younger adults it predicts less stiff arteries. This finding helps explain the previously inconsistent findings within the literature and may relate to morphological and physiological differences between similar levels of obesity at different ages. Funding
Published: 2013

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

Author: Nadjia Kachenoura, Alban Redheuil, Elie Mousseaux, Emilie Bollache, Zoubir M Bensalah, Alain De Cesare, BMC, Ed., Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), Radiologie, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Ambroise Paré [AP-HP], Service de radiologie, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)
Subjects: Aortic arch, medicine.medical_specialty, lcsh:Diseases of the circulatory (Cardiovascular) system, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, 030204 cardiovascular system & hematology, Asymptomatic, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, medicine.artery, Internal medicine, Ascending aorta, medicine, Radiology, Nuclear Medicine and imaging, Pulse wave velocity, Angiology, Medicine(all), Radiological and Ultrasound Technology, medicine.diagnostic_test, business.industry, Magnetic resonance imaging, medicine.disease, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, Flow (mathematics), lcsh:RC666-701, Poster Presentation, Arterial stiffness, Cardiology, medicine.symptom, Cardiology and Cardiovascular Medicine, business
Abstract: International audience; Our 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.
Published: 2012
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32. Comparison of different segmentation approaches without using gold standard. Application to the estimation of the left ventricle ejection fraction from cardiac cine MRI sequences

Author: Patrick Clarysse, Jessica Lebenberg, Christopher Casta, Alain Lalande, Frédérique Frouin, Alexandre Cochet, Stéphanie Jehan-Besson, Alain De Cesare, Laurent Najman, Constantin Constantinides, Jean Cousty, Christophe Tilmant, Muriel Lefort, Irène Buvat, Elodie Roullot, Mireille Garreau, Laurent Sarry, Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), Imagerie et Modélisation en Neurobiologie et Cancérologie (IMNC (UMR_8165)), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales (MOTIVATE), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique Gaspard-Monge (LIGM), Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC)-ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique (CNRS), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Equipe Image - Laboratoire GREYC - UMR6072, Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des sciences et matériaux pour l'électronique et d'automatique (LASMEA), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Centre National de la Recherche Scientifique (CNRS), PRIAM, ESME-Sudria, Image Science for Interventional Techniques (ISIT), Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Centre National de la Recherche Scientifique (CNRS), The authors gratefully acknowledge the GdR2647 Stic-Santé for its support to the MedIEvalaction., Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU), Laboratoire d'Imagerie Fonctionnelle ( LIF ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Imagerie et Modélisation en Neurobiologie et Cancérologie ( IMNC ), Centre National de la Recherche Scientifique ( CNRS ) -Université Paris Diderot - Paris 7 ( UPD7 ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Université Paris-Sud - Paris 11 ( UP11 ), Laboratoire Traitement du Signal et de l'Image ( LTSI ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), 1 - Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales ( MOTIVATE ), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Laboratoire d'Informatique Gaspard-Monge ( LIGM ), Université Paris-Est Marne-la-Vallée ( UPEM ) -École des Ponts ParisTech ( ENPC ) -ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen ( GREYC ), Université de Caen Normandie ( UNICAEN ), Normandie Université ( NU ) -Normandie Université ( NU ) -Ecole Nationale Supérieure d'Ingénieurs de Caen ( ENSICAEN ), Normandie Université ( NU ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Caen Normandie ( UNICAEN ), Normandie Université ( NU ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire des sciences et matériaux pour l'électronique et d'automatique ( LASMEA ), Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ) -Centre National de la Recherche Scientifique ( CNRS ), Image Science for Interventional Techniques ( ISIT ), Université d'Auvergne - Clermont-Ferrand I ( UdA ) -Clermont Université-Centre National de la Recherche Scientifique ( CNRS ), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Senhadji, Lotfi, Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Subjects: MESH : Ventricular Function, Left, [ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, 02 engineering and technology, MESH: Regression Analysis, Ventricular Function, Left, Article, MESH: Ventricular Function, Left, 030218 nuclear medicine & medical imaging, MESH: Magnetic Resonance Imaging, 03 medical and health sciences, MESH : Heart, 0302 clinical medicine, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, MESH : Magnetic Resonance Imaging, MESH : Regression Analysis, 0202 electrical engineering, electronic engineering, information engineering, Humans, Medicine, Segmentation, [ SDV.IB ] Life Sciences [q-bio]/Bioengineering, Reliability (statistics), [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, [SDV.IB] Life Sciences [q-bio]/Bioengineering, Ejection fraction, MESH: Humans, business.industry, MESH : Humans, Heart, Regression analysis, Pattern recognition, Image segmentation, Gold standard (test), Magnetic Resonance Imaging, MESH: Heart, medicine.anatomical_structure, Ventricle, Regression Analysis, A priori and a posteriori, 020201 artificial intelligence & image processing, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Artificial intelligence, business, Nuclear medicine, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; A statistical method is proposed to compare several estimates of a relevant clinical parameter when no gold standard is available. The method is illustrated by considering the left ventricle ejection fraction derived from cardiac magnetic resonance images and computed using seven approaches with different degrees of automation. The proposed method did not use any a priori regarding with the reliability of each method and its degree of automation. The results showed that the most accurate estimates of the ejection fraction were obtained using manual segmentations, followed by the semiautomatic methods, while the methods with the least user input yielded the least accurate ejection fraction estimates. These results were consistent with the expected performance of the estimation methods, suggesting that the proposed statistical approach might be helpful to assess the performance of estimation methods on clinical data for which no gold standard is available.
Published: 2011
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33. Automated 3D measurements of the aortic length using the Hough transform

Author: Claire Pellot-Barakat, Muriel Lefort, Elie Mousseaux, Alain De Cesare, Alain Herment, Frédérique Frouin, Laboratoire d'Imagerie Fonctionnelle ( LIF ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Service de radiologie cardio-vasculaire [CHU HEGP], Assistance publique - Hôpitaux de Paris (AP-HP)-Hôpital Européen Georges Pompidou [APHP] ( HEGP ), Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), and BMC, Ed.
Subjects: Aortic arch, medicine.medical_specialty, lcsh:Diseases of the circulatory (Cardiovascular) system, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, computer.software_genre, 030218 nuclear medicine & medical imaging, Hough transform, law.invention, 03 medical and health sciences, 0302 clinical medicine, Text mining, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, law, medicine.artery, Medicine, Radiology, Nuclear Medicine and imaging, Computer vision, ComputingMilieux_MISCELLANEOUS, [ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging, Angiology, Medicine(all), Aorta, Radiological and Ultrasound Technology, business.industry, [ SDV.MHEP.CSC ] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Sagittal plane, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, medicine.anatomical_structure, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, Single view, lcsh:RC666-701, Poster Presentation, cardiovascular system, Data mining, Artificial intelligence, Cardiology and Cardiovascular Medicine, business, computer
Abstract: A 3D estimation of the length of the aortic arch using sagittal and axial acquisitions is proposed and compared with the conventional 2D method using a single view of the aorta.
Published: 2011
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34. Consistency of aortic distensibility and pulse wave velocity estimates with respect to the Bramwell-Hill theoretical model: a cardiovascular magnetic resonance study

Author: Elie Mousseaux, Anas Dogui, Nadjia Kachenoura, Muriel Lefort, Alain Herment, Alain De Cesare, Frédérique Frouin, Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de radiologie cardio-vasculaire [CHU HEGP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), and BMC, Ed.
Subjects: Aortic arch, lcsh:Diseases of the circulatory (Cardiovascular) system, MESH: Models, Cardiovascular, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Pulsatile flow, MESH: Automation, Laboratory, 030204 cardiovascular system & hematology, MESH: Observer Variation, 030218 nuclear medicine & medical imaging, 0302 clinical medicine, Pulse wave velocity, Aorta, Observer Variation, Medicine(all), MESH: Middle Aged, Radiological and Ultrasound Technology, Models, Cardiovascular, MESH: Manometry, MESH: Aorta, MESH: Blood Flow Velocity, MESH: Magnetic Resonance Imaging, Cine, Middle Aged, MESH: Predictive Value of Tests, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Pulse pressure, Femoral Artery, MESH: Reproducibility of Results, Carotid Arteries, MESH: Young Adult, Pulsatile Flow, MESH: Pulsatile Flow, cardiovascular system, Cardiology, Aortic stiffness, Cardiology and Cardiovascular Medicine, Blood Flow Velocity, MESH: Femoral Artery, Adult, medicine.medical_specialty, Manometry, Magnetic Resonance Imaging, Cine, Young Adult, 03 medical and health sciences, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Predictive Value of Tests, medicine.artery, Internal medicine, Image Interpretation, Computer-Assisted, Ascending aorta, medicine, Humans, Radiology, Nuclear Medicine and imaging, Automation, Laboratory, MESH: Carotid Arteries, MESH: Humans, business.industry, Research, Reproducibility of Results, MESH: Adult, medicine.disease, Elasticity, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, lcsh:RC666-701, MESH: Elasticity, Arterial stiffness, business, MESH: Image Interpretation, Computer-Assisted
Abstract: Background Arterial stiffness is considered as an independent predictor of cardiovascular mortality, and is increasingly used in clinical practice. This study aimed at evaluating the consistency of the automated estimation of regional and local aortic stiffness indices from cardiovascular magnetic resonance (CMR) data. Results Forty-six healthy subjects underwent carotid-femoral pulse wave velocity measurements (CF_PWV) by applanation tonometry and CMR with steady-state free-precession and phase contrast acquisitions at the level of the aortic arch. These data were used for the automated evaluation of the aortic arch pulse wave velocity (Arch_PWV), and the ascending aorta distensibility (AA_Distc, AA_Distb), which were estimated from ascending aorta strain (AA_Strain) combined with either carotid or brachial pulse pressure. The local ascending aorta pulse wave velocity AA_PWVc and AA_PWVb were estimated respectively from these carotid and brachial derived distensibility indices according to the Bramwell-Hill theoretical model, and were compared with the Arch_PWV. In addition, a reproducibility analysis of AA_PWV measurement and its comparison with the standard CF_PWV was performed. Characterization according to the Bramwell-Hill equation resulted in good correlations between Arch_PWV and both local distensibility indices AA_Distc (r = 0.71, p < 0.001) and AA_Distb (r = 0.60, p < 0.001); and between Arch_PWV and both theoretical local indices AA_PWVc (r = 0.78, p < 0.001) and AA_PWVb (r = 0.78, p < 0.001). Furthermore, the Arch_PWV was well related to CF_PWV (r = 0.69, p < 0.001) and its estimation was highly reproducible (inter-operator variability: 7.1%). Conclusions The present work confirmed the consistency and robustness of the regional index Arch_PWV and the local indices AA_Distc and AA_Distb according to the theoretical model, as well as to the well established measurement of CF_PWV, demonstrating the relevance of the regional and local CMR indices.
Published: 2011
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35. 285 – Transposition of the great arteries is associated with increased ascending aorta stiffness

Author: Magalie Ladouceur, Laurence Iserin, Elie Mousseaux, Alain De Cesare, Daniel Sidi, Alain Herment, and M. Lefort
Subjects: Aorta, medicine.medical_specialty, business.industry, Diastole, Anatomy, Pulse pressure, Great arteries, medicine.artery, Descending aorta, Internal medicine, Ascending aorta, cardiovascular system, Cardiology, Medicine, Aortic stiffness, business, Cardiology and Cardiovascular Medicine, Pulse wave velocity
Abstract: BackgroundTransposition of the great arteries (TGA) is the consequences of abnormal aorticopulmonary septation. Animal embryonic data indicate that septation and elastogenesis are related events. It was showed that carotid artery is markedly and constitutionally stiffer in patients with TGA.Objectiveto assess aortic dimensions and aortic elasticity in patients with TGA using magnetic resonance imaging (MRI).MethodsMRI was performed in 29 patients with simple TGA operated by an atrial switch procedure (22 male; mean age 29 ± 4 years) and 29 age and gender-matched healthy subjects.ResultsTGA patients showed aortic root dilatation (7.7±2.1 vs 6.2±1.2cm∑, p = 0, 0018, in systole, and 6.8±2.1 vs 5.0±1.2cm∑, p = 0.0003, in diastole, at tubular level), reduced aortic root distension (13.5±5.9 vs 24.3±11.7, p
Published: 2011
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36. Estimation d'une forme mutuelle pour l'évaluation de la segmentation en imagerie cardiaque

Author: Stéphanie Jehan-Besson, Christophe Tilmant, Alain de Cesare, Frédérique Frouin, Laurent Najman, Alain Lalande, Laurent Sarry, Christopher Casta, Patrick Clarysse, Constantin Constantinidés, Jean Cousty, Muriel Lefort, Alexandre Cochet, Mireille Garreau, Laboratoire d'Informatique Gaspard-Monge (LIGM), Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC)-ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique Gaspard-Monge ( LIGM ), Université Paris-Est Marne-la-Vallée ( UPEM ) -École des Ponts ParisTech ( ENPC ) -ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique ( CNRS ), Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM), and Najman, Laurent
Subjects: [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], [ INFO.INFO-CL ] Computer Science [cs]/Computation and Language [cs.CL], [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
Abstract: To appear; National audience
Published: 2011

37. Automated estimation of aortic strain from steady-state free-precession and phase contrast MR images

Author: Alain, Herment, Muriel, Lefort, Nadjia, Kachenoura, Alain, De Cesare, Valentina, Taviani, Martin J, Graves, Claire, Pellot-Barakat, Frédérique, Frouin, Elie, Mousseaux, Gestionnaire, Hal Sorbonne Université, Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), Cambridge University Hospitals - NHS (CUH), University of Cambridge [UK] (CAM), Service de radiologie cardio-vasculaire [CHU HEGP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)
Subjects: Adult, Male, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Adolescent, Phantoms, Imaging, [SDV]Life Sciences [q-bio], Reproducibility of Results, Aorta, Thoracic, Middle Aged, Image Enhancement, Sensitivity and Specificity, [SDV] Life Sciences [q-bio], Young Adult, Elastic Modulus, Image Interpretation, Computer-Assisted, cardiovascular system, Elasticity Imaging Techniques, Humans, Female, Microscopy, Phase-Contrast, Magnetic Resonance Angiography, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Aged
Abstract: International audience; The strain values extracted from steady-state free-precession (SSFP) and phase contrast (PC) images acquired with a 1.5T scanner on a compliant flow phantom and within the thoracic aorta of 52 healthy subjects were compared. Aortic data were acquired perpendicular to the aorta at the level of the pulmonary artery bifurcation. Cross sectional areas were obtained by using an automatic and robust segmentation method. While a good correlation (r = 0.99) was found between the aortic areas extracted from SSFP and PC sequences, a lower correlation (r = 0.71) was found between the corresponding aortic strain values. Strain values estimated using SSFP and PC sequences were equally correlated with age. Interobserver reproducibility was better for SSFP than for PC. Strain values in the ascending and descending aorta were better correlated for SSFP (r = 0.8) than for PC (r = 0.65) and fitted with the expectation of a larger strain in the ascending aorta when using SSFP. The spatial and temporal resolutions of the acquisitions had a minor influence upon the estimated strain values. Thus, if PC acquisitions can be used to estimate both pulse wave velocity and aortic strain, an additional SSFP sequence may be useful to improve the accuracy in estimating the aortic strain.
Published: 2011
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38. Reduced Ascending Aortic Strain and Distensibility Earliest Manifestations of Vascular Aging in Humans

Author: Alban Redheuil, Alain De Cesare, Joao A.C. Lima, Elie Mousseaux, Wen Chung Yu, Raymond T. Yan, Nadjia Kachenoura, Colin O. Wu, and David A. Bluemke
Subjects: Aortic arch, Male, Aging, Blood Pressure, 030204 cardiovascular system & hematology, 030218 nuclear medicine & medical imaging, 0302 clinical medicine, Risk Factors, Pulse wave velocity, Aorta, Aged, 80 and over, Age Factors, Anatomy, Middle Aged, Magnetic Resonance Imaging, 3. Good health, Pulse pressure, Vasodilation, medicine.anatomical_structure, Pulsatile Flow, Cardiology, cardiovascular system, Female, Blood Flow Velocity, Adult, medicine.medical_specialty, Manometry, Article, Sampling Studies, 03 medical and health sciences, Young Adult, Internal medicine, medicine.artery, Heart rate, Internal Medicine, medicine, Humans, Aged, Probability, Analysis of Variance, business.industry, Blood Pressure Determination, medicine.disease, Elasticity, Blood pressure, Vasoconstriction, Arterial stiffness, Vascular resistance, Vascular Resistance, business
Abstract: Arterial stiffness predicts cardiovascular events beyond traditional risk factors. However, the relationship with aging of novel noninvasive measures of aortic function by MRI and their interrelationship with established markers of vascular stiffness remain unclear and currently limit their potential impact. Our aim was to compare age-related changes of central measures of aortic function with carotid distensibility, global carotid–femoral pulse wave velocity, and wave reflections. We determined aortic strain, distensibility, and aortic arch pulse wave velocity by MRI, carotid distensibility by ultrasound, and carotid–femoral pulse wave velocity by tonometry in 111 asymptomatic subjects (54 men, age range: 20 to 84 years). Central pressures were used to calculate aortic distensibility. Peripheral and central pulse pressure, augmentation index, and carotid–femoral pulse wave velocity increased with age, but aortic strain and aortic arch PWV were most closely and specifically related to aging. Ascending aortic (AA) strain and distensibility decreased, respectively, by 5.3±0.5% ( R 2 =0.54, P −1 ×10 −3 ( R 2 =0.62, P R 2 =0.60, P
Published: 2010

39. Automated left ventricular diastolic function evaluation from phase-contrast cardiovascular magnetic resonance and comparison with Doppler echocardiography

Author: Muriel Lefort, Alban Redheuil, Ludivine Perdrix, Elie Mousseaux, Magalie Ladouceur, Alain Herment, Stephanie Clement-Guinaudeau, Nadjia Kachenoura, Alain De Cesare, Emilie Bollache, Carine Defrance, Benoit Diebold, BMC, Ed., Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de Radiologie [CHU HEGP], Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), and NK is supported by a grant from 'la Fondation Lefoulon-Delalande-Institut de France'.
Subjects: Male, lcsh:Diseases of the circulatory (Cardiovascular) system, MESH: Echocardiography, Doppler, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Contrast Media, MESH: Automation, Laboratory, 030204 cardiovascular system & hematology, Doppler echocardiography, MESH: Observer Variation, Severity of Illness Index, MESH: Stroke Volume, Ventricular Function, Left, MESH: Ventricular Function, Left, 030218 nuclear medicine & medical imaging, MESH: Magnetic Resonance Imaging, Ventricular Dysfunction, Left, 0302 clinical medicine, MESH: Aged, 80 and over, Diastole, MESH: Early Diagnosis, MESH: Ventricular Dysfunction, Left, MESH: Aortic Valve Stenosis, Aged, 80 and over, Observer Variation, Medicine(all), MESH: Aged, MESH: Myocardial Perfusion Imaging, MESH: Middle Aged, Radiological and Ultrasound Technology, medicine.diagnostic_test, MESH: Diastole, MESH: Paris, Myocardial Perfusion Imaging, Stroke volume, MESH: Blood Flow Velocity, Middle Aged, Magnetic Resonance Imaging, MESH: Case-Control Studies, Echocardiography, Doppler, MESH: Predictive Value of Tests, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, MESH: Reproducibility of Results, MESH: Young Adult, Aortic valve stenosis, Cardiology, Female, Radiology, Cardiology and Cardiovascular Medicine, Blood Flow Velocity, Adult, medicine.medical_specialty, Paris, MESH: Coronary Circulation, Sensitivity and Specificity, 03 medical and health sciences, Myocardial perfusion imaging, Young Adult, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Predictive Value of Tests, Internal medicine, Coronary Circulation, MESH: Severity of Illness Index, MESH: Contrast Media, medicine, Humans, Radiology, Nuclear Medicine and imaging, Aged, Automation, Laboratory, MESH: Humans, E/A ratio, business.industry, Research, Reproducibility of Results, Magnetic resonance imaging, Stroke Volume, MESH: Adult, Aortic Valve Stenosis, MESH: ROC Curve, medicine.disease, MESH: Sensitivity and Specificity, MESH: Male, Early Diagnosis, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, ROC Curve, lcsh:RC666-701, Heart failure, Case-Control Studies, business, MESH: Female
Abstract: Background Early detection of diastolic dysfunction is crucial for patients with incipient heart failure. Although this evaluation could be performed from phase-contrast (PC) cardiovascular magnetic resonance (CMR) data, its usefulness in clinical routine is not yet established, mainly because the interpretation of such data remains mostly based on manual post-processing. Accordingly, our goal was to develop a robust process to automatically estimate velocity and flow rate-related diastolic parameters from PC-CMR data and to test the consistency of these parameters against echocardiography as well as their ability to characterize left ventricular (LV) diastolic dysfunction. Results We studied 35 controls and 18 patients with severe aortic valve stenosis and preserved LV ejection fraction who had PC-CMR and Doppler echocardiography exams on the same day. PC-CMR mitral flow and myocardial velocity data were analyzed using custom software for semi-automated extraction of diastolic parameters. Inter-operator reproducibility of flow pattern segmentation and functional parameters was assessed on a sub-group of 30 subjects. The mean percentage of overlap between the transmitral flow segmentations performed by two independent operators was 99.7 ± 1.6%, resulting in a small variability ( 0.71) and receiver operating characteristic (ROC) analysis revealed their ability to separate patients from controls, with sensitivity > 0.80, specificity > 0.80 and accuracy > 0.85. Slight superiority in terms of correlation with echocardiography (r = 0.81) and accuracy to detect LV abnormalities (sensitivity > 0.83, specificity > 0.91 and accuracy > 0.89) was found for the PC-CMR flow-rate related parameters. Conclusions A fast and reproducible technique for flow and myocardial PC-CMR data analysis was successfully used on controls and patients to extract consistent velocity-related diastolic parameters, as well as flow rate-related parameters. This technique provides a valuable addition to established CMR tools in the evaluation and the management of patients with diastolic dysfunction.
Published: 2010
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40. Automated segmentation of the aorta from phase contrast MR images: Validation against expert tracing in healthy volunteers and in patients with a dilated aorta

Author: Mourad Bensalah, Anas Dogui, Muriel Lefort, Nadjia Kachenoura, Alain De Cesare, Elie Mousseaux, Frédérique Frouin, Alain Herment, Gestionnaire, Hal Sorbonne Université, Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Université Pierre et Marie Curie - Paris 6 (UPMC)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Service de radiologie cardio-vasculaire [CHU HEGP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), and Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)
Subjects: Scanner, medicine.medical_specialty, Phase contrast microscopy, [SDV]Life Sciences [q-bio], Aortic Diseases, Lumen (anatomy), Aorta, Thoracic, 030204 cardiovascular system & hematology, Tracing, Pattern Recognition, Automated, 030218 nuclear medicine & medical imaging, law.invention, Automation, 03 medical and health sciences, 0302 clinical medicine, law, medicine.artery, medicine, Humans, Radiology, Nuclear Medicine and imaging, Segmentation, Aorta, Observer Variation, Models, Statistical, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, medicine.diagnostic_test, business.industry, Reproducibility of Results, Magnetic resonance imaging, Magnetic Resonance Imaging, [SDV] Life Sciences [q-bio], Case-Control Studies, Descending aorta, Regression Analysis, Radiology, business, Nuclear medicine, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract: Purpose: To assess if segmentation of the aorta can be accurately achieved using the modulus image of phase contrast (PC) magnetic resonance (MR) acquisitions. Materials and Methods: PC image sequences containing both the ascending and descending aorta of 52 subjects were acquired using three different MR scanners. An automated segmentation technique, based on a 2D+t deformable surface that takes into account the features of PC aortic images, such as flow-related effects, was developed. The study was designed to: 1) assess the variability of our approach and its robustness to the type of MR scanner, and 2) determine its sensitivity to aortic dilation and its accuracy against an expert manual tracing. Results: Interobserver variability in the lumen area was 0.59 ± 0.92% for the automated approach versus 10.09 ± 8.29% for manual segmentation. The mean Dice overlap measure was 0.945 ± 0.014. The method was robust to the aortic size and highly correlated (r = 0.99) with the manual tracing in terms of aortic area and diameter. Conclusion: A fast and robust automated segmentation of the aortic lumen was developed and successfully tested on images provided by various MR scanners and acquired on healthy volunteers as well as on patients with a dilated aorta. J. Magn. Reson. Imaging 2010;31:881–888. ©2010 Wiley-Liss, Inc.
Published: 2010
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41. Pulse wave velocity in the aortic arch is the strongest predictor of left ventricular concentric remodeling in subjects with different levels of cardiovascular risk

Author: Elie Mousseaux, Alain De Cesare, Raymond T. Yan, Joao Ac Lima, Alban Redheuil, Wen Chung Yu, and David A. Bluemke
Subjects: Aortic arch, medicine.medical_specialty, Pulse Wave Velocity, Concentric, Augmentation Index, medicine.artery, Internal medicine, Aortic Stiffness, Medicine, Radiology, Nuclear Medicine and imaging, Pulse wave velocity, Angiology, Medicine(all), Leave Ventricular Mass, Aortic Arch, Radiological and Ultrasound Technology, business.industry, musculoskeletal system, medicine.disease, Pulse pressure, Heart failure, Poster Presentation, cardiovascular system, Arterial stiffness, Cardiology, Aortic stiffness, Cardiology and Cardiovascular Medicine, business, human activities, circulatory and respiratory physiology
Abstract: Increased systolic blood pressure (SBP), pulse pressure (PP) and left ventricular (LV) concentric remodeling are associated with aging and increased cardiovascular risk. The aortic arch accounts for most of the vascular buffering function and is primarily involved in arterial stiffening and complications. Mechanisms of heart failure during aging and the role of aortic-ventricular stiffening and interaction need clarification. In particular, the importance of the aortic arch on central arterial stiffness remains unclear.
Published: 2009

42. Regularized estimation of contrast agent attenuation to improve the imaging of microbubbles in small animal studies

Author: Alain De Cesare, Sébastien Mulé, Frédérique Frouin, Alain Herment, and Olivier Lucidarme
Subjects: Materials science, Acoustics and Ultrasonics, Biophysics, Contrast Media, Mice, Nude, For Attenuation Correction, Kidney, Wilms Tumor, Mice, Animals, Scattering, Radiation, Radiology, Nuclear Medicine and imaging, Microbubbles, Radiological and Ultrasound Technology, business.industry, Attenuation, Ultrasound, Echogenicity, Image Enhancement, Kidney Neoplasms, Ultrasonography, Doppler, Pulsed, Models, Animal, Female, business, Nuclear medicine, Artifacts, Perfusion, Correction for attenuation, Algorithms, Biomedical engineering, Contrast-enhanced ultrasound
Abstract: Quantitative analysis of tissue perfusion using contrast-enhanced ultrasound is still limited by shadowing, which is caused by inadequate compensation for microbubble contrast agent attenuation. Many previous methods have been developed for attenuation correction in soft tissues. However, no method has been proposed to correct for microbubble attenuation in vivo. In this article, a model to estimate microbubble attenuation is presented, using the time-intensity variation in a highly echogenic distal area without contrast uptake. This model is based on the assumption that a linear relationship holds between local microbubble attenuation and local backscatter. The model was applied to 12 murine renal perfusion studies. Parametric images of microbubble attenuation were generated, corresponding to dynamic contrast agent-specific sequences without shadowing. Contrast uptake kinetics consistent with the physiology were retrieved in all perfused areas. This method therefore proved to be of potential interest in the quantification of tissue perfusion in small animal studies.
Published: 2007

43. Calculation of left ventricle relative pressure distribution in MRI using acceleration data

Author: Jacques Bittoun, Alain De Cesare, Alain Herment, O. Jolivet, Fanny Buyens, Elie Mousseaux, and Jean-Pierre Tasu
Subjects: Curl (mathematics), Pixel, Mathematical analysis, Acceleration, Hemodynamics, Geometry, Magnetic Resonance Imaging, Ventricular Function, Left, medicine.anatomical_structure, Ventricle, Region of interest, medicine, Ventricular pressure, Image Processing, Computer-Assisted, Ventricular Pressure, Humans, Radiology, Nuclear Medicine and imaging, Boundary value problem, Pressure gradient, Algorithms, Blood Flow Velocity, Mathematics
Abstract: Measurements of pressure variations within the cardiac chambers could provide important information for clinical assessments of cardiovascular function. In this work an MRI method for evaluating spatial distributions of intracardiac relative pressure is presented. We first calculated pressure gradients from MR maps of blood acceleration by applying the NS equation. We then used an original algorithm to compute pressure distribution in a region of interest (ROI) by minimizing the pressure gradient curl so that the result in a given pixel is independent of the integration path. The method was assessed in five healthy volunteers by means of MR 2D maps of the blood acceleration in the left ventricle (LV) during ejection and filling phases. The pressure variations calculated from acceleration mapping fit the known physiological variations better than those based on velocity maps acquired in the same volunteers. Furthermore, the optimization algorithm presented here produced the same results as iterative algorithms proposed by other authors, but in much less time and without requiring adjustable parameters or boundary conditions.
Published: 2005

44. Using an adaptive semiautomated self-evaluated registration technique to analyze MRI data for myocardial perfusion assessment

Author: Sylvie Philipp-Foliguet, Alain De Cesare, Marc Janier, Thierry Delzescaux, Alain Herment, Andrew Todd-Pokropek, and Frédérique Frouin
Subjects: Male, medicine.medical_specialty, Image registration, Coronary Circulation, medicine, Image Processing, Computer-Assisted, Humans, Radiology, Nuclear Medicine and imaging, Multislice, Radionuclide Imaging, Aged, medicine.diagnostic_test, business.industry, Coronary Stenosis, Magnetic resonance imaging, Heart, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Coronary arteries, Radiography, Stenosis, medicine.anatomical_structure, Positron emission tomography, Feasibility Studies, Female, Radiology, business, Nuclear medicine, Perfusion, Artery
Abstract: Purpose To validate the adaptive semiautomated self-evaluated registration technique (ASSERT) followed by factor analysis of medical image sequence (FAMIS) for analyzing myocardial perfusion using magnetic resonance imaging (MRI) images. Materials and Methods Eleven patients having a significant stenosis of at least one coronary artery detected by coronarography were examined by thallium tomoscintigraphy and perfusion MRI (first-pass of Gd-DTPA-BMA) at rest and under pharmacologic stress. The MRI images were analyzed by ASSERT to correct for rigid motion in the acquisition plane and to reject those images that were severely deformed or acquired outside the slice plane. The images thus obtained were analyzed by FAMIS. The resulting factor images representing myocardial perfusion were read to identify the ischemic territories corresponding to left anterior descending coronary arteries and right coronary arteries. Results ASSERT allowed automatic correction for motion and the exclusion of images that could not be registered. The ischemic territories, identified from the factor images of the myocardium, agreed with those identified by coronarography and tomoscintigraphy for 20 of the 22 territories. Conclusion The results demonstrate the feasibility of analyzing myocardial perfusion using MRI acquisition and treating the resulting images by ASSERT and FAMIS. Extending this method to multislice examinations will enable evaluation of the perfusion of the whole myocardium. J. Magn. Reson. Imaging 2003;18:681–690. © 2003 Wiley-Liss, Inc.
Published: 2003

45. Estimation of the Diastolic Intraventricular Relative Pressures Using MRI Acceleration Measurements

Author: Elie Mousseaux, Fanny Balleux, Alain Herment, Jean-Pierre Tasu, O. Jolivet, and Alain De Cesare
Subjects: Acceleration, Quadratic equation, medicine.anatomical_structure, Region of interest, Ventricle, Computation, Mathematical analysis, medicine, Geometry, Derivative, Function (mathematics), Energy (signal processing), Mathematics
Abstract: This paper presents a method to determine noninvasively relative pressures from magnetic resonance (MR) acceleration and velocity data. The technique is based on the complete Navier-Stokes equation associated with the direct measurement of the total acceleration, defined as the sum of the velocity derivative vs. time and the convective acceleration. It consists of determinining relative pressures by constructing a minimization problem of a quadratic energy function. The original ways of discretisation and computation allow to estimate relative pressures independently of a path of integration. The algorithm is applied to compute relative pressures over the diastolic filling of the left ventricle (LV) within a region of interest delineating the left atrium (LA) and the LV.
Published: 2003
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46. 3D Regularisation and Segmentation of Factor Volumes to Process PET H2 15O Myocardial Perfusion Studies

Author: Pascal Merlet, Vincent Frouin, Paté Boubacar, Andrew Todd-Pokropek, Alain Herment, Frédérique Frouin, and Alain De Cesare
Subjects: Reproducibility, medicine.anatomical_structure, Myocardial perfusion study, Ventricle, business.industry, 3d image processing, medicine, Segmentation, Blood flow, Nuclear medicine, business, Perfusion, Biomedical engineering
Abstract: A 3D image processing methodto increase reproducibility in the handling of PET myocardial perfusion studies is proposed. It is basedon the 3D regularization of factor volumes, which are estimated by FAMIS (Factor Analysis of Medical Image Sequences). The resulting regularized factor volumes correspond to right and left cavities and to perfused tissues. They are then submitted to a C-means classification, looking for 4 clusters. Some rules of connectivity are applied to the resulting clusters to achieve the segmentation of heart cavities and myocardium. Thereafter, kinetics in the left ventricle and in the myocardium can be computed from the previously determined volumes of interest, and myocardial blood flow (MBF) is estimated by a conventional compartmental analysis.
Published: 2001
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47. P2.14 ESTIMATION OF AORTIC ARCH PULSE WAVE VELOCITY IN MRI USING COMPLEX WAVELET CROSS-SPECTRUM

Author: Gilles Soulat, Alain De Cesare, Alban Redheuil, Nadjia Kachenoura, Elie Mousseaux, Ioannis Bargiotas, and Emilie Bollache
Subjects: Aortic arch, business.industry, Acoustics, Specialties of internal medicine, General Medicine, Wavelet, RC581-951, RC666-701, medicine.artery, medicine, Diseases of the circulatory (Cardiovascular) system, business, Cross-spectrum, Pulse wave velocity
Published: 2014
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48. Segmentation of X-ray images by discontinuity detections in a spline model

Author: Alain De Cesare, Pierre Peronneau, Rachid Zeboudj, and Alain Herment
Subjects: Segmentation-based object categorization, business.industry, MathematicsofComputing_NUMERICALANALYSIS, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Scale-space segmentation, Image segmentation, Spline (mathematics), Tensor product, Image texture, Computer Science::Computer Vision and Pattern Recognition, Computer vision, Segmentation, Artificial intelligence, Thin plate spline, business, ComputingMethodologies_COMPUTERGRAPHICS, Mathematics
Abstract: Image modelization is achieved using a bidimensional spline defined as the tensor product of univariate spline functions which minimize an energy function. The image is segmented by searching for the regions between which a discontinuity brings an optimal energy gain. The segmentation is robust, fast and does not need image pre-processing.
Published: 1992
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49. A reference free approach for the comparative evaluation of eight segmentation methods for the estimation of the left ventricular ejection fraction in cardiac MRI

Author: Alain Lalande, Jessica Lebenberg, Irène Buvat, Patrick Clarysse, Christopher Casta, Alexandre Cochet, Constantin Constantinidès, Jean Cousty, Alain de Cesare, Stéphanie Jehan-Besson, Muriel Lefort, Laurent Najman, Elodie Roullot, Laurent Sarry, Christophe Tilmant, Mireille Garreau, Frédérique Frouin, Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), Imagerie et Modélisation en Neurobiologie et Cancérologie (IMNC (UMR_8165)), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales (MOTIVATE), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique Gaspard-Monge (LIGM), Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC)-ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique (CNRS), Equipe Image - Laboratoire GREYC - UMR6072, Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS), ESME Sudria, Pôle de Recherche en Ingénierie Appliquée à la Médecine (PRIAM), ESME Sudria [Paris]-ESME Sudria [Paris], Image Science for Interventional Techniques (ISIT), Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Centre National de la Recherche Scientifique (CNRS), Laboratoire des sciences et matériaux pour l'électronique et d'automatique (LASMEA), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'Imagerie Fonctionnelle ( LIF ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Imagerie et Modélisation en Neurobiologie et Cancérologie ( IMNC ), Centre National de la Recherche Scientifique ( CNRS ) -Université Paris Diderot - Paris 7 ( UPD7 ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Université Paris-Sud - Paris 11 ( UP11 ), 1 - Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales ( MOTIVATE ), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Laboratoire d'Informatique Gaspard-Monge ( LIGM ), Université Paris-Est Marne-la-Vallée ( UPEM ) -École des Ponts ParisTech ( ENPC ) -ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique ( CNRS ), Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen ( GREYC ), Université de Caen Normandie ( UNICAEN ), Normandie Université ( NU ) -Normandie Université ( NU ) -Ecole Nationale Supérieure d'Ingénieurs de Caen ( ENSICAEN ), Normandie Université ( NU ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Caen Normandie ( UNICAEN ), Normandie Université ( NU ) -Centre National de la Recherche Scientifique ( CNRS ), Pôle de Recherche en Ingénierie Appliquée à la Médecine ( PRIAM ), Image Science for Interventional Techniques ( ISIT ), Université d'Auvergne - Clermont-Ferrand I ( UdA ) -Clermont Université-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire des sciences et matériaux pour l'électronique et d'automatique ( LASMEA ), Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire Traitement du Signal et de l'Image ( LTSI ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Lalande, Alain, Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), and Normandie Université (NU)
Subjects: [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], [ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [ INFO.INFO-TI ] Computer Science [cs]/Image Processing, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging
Abstract: International audience; Objective evaluation and comparison of segmentation algorithms for medical imaging is still a challenging issue. The most frequently used evaluation method consists in comparing the segmentation with a manual delineation. Since obtaining such manual segmentation can be tedious, we proposed a method based on the "extended Regression Without Truth" approach (eRWT)(1). This approach is applied to the comparative evaluation of 8 segmentation algorithms with different degrees of automation from the estimated left ventricular ejection fraction (LVEF).

50. Intraventricular ejection pressure gradient derived from acceleration measurement by phase contrast CMR as a new marker of left ventricular contractility: feasibility study and preliminary results in dilated cardiomyopathy

Author: Elie Mousseaux, Alain De Cesare, Nadjia Kachenoura, Arshid Azarine, Laurent Macron, Golmehr Ashrafpoor, Alban Redheuil, Emilie Bollache, BMC, Ed., Service de Radiologie Cardiovasculaire Diagnostique et Interventionnelle, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Laboratoire d'Imagerie Fonctionnelle (LIF), and Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: Inotrope, lcsh:Diseases of the circulatory (Cardiovascular) system, medicine.medical_specialty, Contraction (grammar), [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Phase contrast microscopy, 030218 nuclear medicine & medical imaging, law.invention, 03 medical and health sciences, 0302 clinical medicine, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, law, Internal medicine, medicine, Radiology, Nuclear Medicine and imaging, cardiovascular diseases, Pressure gradient, ComputingMilieux_MISCELLANEOUS, Angiology, Medicine(all), Ejection fraction, Radiological and Ultrasound Technology, business.industry, Dilated cardiomyopathy, medicine.disease, Left ventricular contractility, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, lcsh:RC666-701, Poster Presentation, cardiovascular system, Cardiology, Cardiology and Cardiovascular Medicine, business
Abstract: Background Intra-ventricular pressure gradient along the direction of the outflow tract is generated by the impulse response of the myocardial contraction. This spatial pressure gradient, derived from the maximal acceleration estimates within the left ventricular (LV) ejection flow, has been validated in vitro by using MRI and was found strongly related to the inotropic state of the LV as demonstrated in animal and human echocardiographic studies. This acceleration may be less dependant on load conditions than others LV systolic function parameters, especially LV ejection fraction (LVEF). Aim: (1) to evaluate the feasibility of LV ejection flow acceleration (Acc) estimates by spatial and temporal derivative of velocities recorded by CMR using phase contrast sequence, (2) to compare the acceleration values to LVEF in patients with Dilated Cardiomyopathy (LVEF
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