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1.
Eur Ann Otorhinolaryngol Head Neck Dis ; 133 Suppl 1: S66-7, 2016 Jun.
Article in English | MEDLINE | ID: mdl-27246746

ABSTRACT

The volume of the cochlea is a key parameter for electrode-array design. Indeed, it constrains the diameter of the electrode-array for low-traumatic positioning in the scala timpani. The present report shows a model of scala timpani volume extraction from temporal bones images in order to estimate a maximum diameter of an electrode-array. Nine temporal bones were used, and passed to high-resolution computed tomography scan. Using image-processing techniques, scala timpani were extracted from images, and cross-section areas were estimated along cochlear turns. Cochlear implant electrode-array was fitted in these cross-sections. Results show that the electrode-array diameter is small enough to fit in the scala timpani, however the diameter is restricted at the apical part.


Subject(s)
Cochlea/anatomy & histology , Cochlear Implantation/methods , Cochlear Implants , Prosthesis Fitting , Humans , Prosthesis Design , Temporal Bone/diagnostic imaging , Tomography, X-Ray Computed
2.
IEEE Trans Med Imaging ; 34(7): 1436-1451, 2015 Jul.
Article in English | MEDLINE | ID: mdl-25643402

ABSTRACT

Quantification of cardiac deformation and strain with 3D ultrasound takes considerable research efforts. Nevertheless, a widespread use of these techniques in clinical practice is still held back due to the lack of a solid verification process to quantify and compare performance. In this context, the use of fully synthetic sequences has become an established tool for initial in silico evaluation. Nevertheless, the realism of existing simulation techniques is still too limited to represent reliable benchmarking data. Moreover, the fact that different centers typically make use of in-house developed simulation pipelines makes a fair comparison difficult. In this context, this paper introduces a novel pipeline for the generation of synthetic 3D cardiac ultrasound image sequences. State-of-the art solutions in the fields of electromechanical modeling and ultrasound simulation are combined within an original framework that exploits a real ultrasound recording to learn and simulate realistic speckle textures. The simulated images show typical artifacts that make motion tracking in ultrasound challenging. The ground-truth displacement field is available voxelwise and is fully controlled by the electromechanical model. By progressively modifying mechanical and ultrasound parameters, the sensitivity of 3D strain algorithms to pathology and image properties can be evaluated. The proposed pipeline is used to generate an initial library of 8 sequences including healthy and pathological cases, which is made freely accessible to the research community via our project web-page.

3.
J Neurooncol ; 121(2): 381-7, 2015 Jan.
Article in English | MEDLINE | ID: mdl-25370706

ABSTRACT

Biomathematical modeling of glioma growth has been developed to optimize treatments delivery and to evaluate their efficacy. Simulations currently make use of anatomical knowledge from standard MRI atlases. For example, cerebrospinal fluid (CSF) spaces are obtained by automatic thresholding of the MNI atlas, leading to an approximate representation of real anatomy. To correct such inaccuracies, an expert-revised CSF segmentation map of the MNI atlas was built. Several virtual glioma growth patterns of different locations were generated, with and without using the expert-revised version of the MNI atlas. The adequacy between virtual and radiologically observed growth patterns was clearly higher when simulations were based on the expert-revised atlas. This work emphasizes the need for close collaboration between clinicians and researchers in the field of brain tumor modeling.


Subject(s)
Atlases as Topic , Brain Neoplasms/pathology , Brain/pathology , Glioma/pathology , Models, Biological , Brain/physiopathology , Brain Neoplasms/physiopathology , Cerebrospinal Fluid , Computer Simulation , Disease Progression , Glioma/physiopathology , Humans , Magnetic Resonance Imaging/methods
4.
IEEE Trans Med Imaging ; 33(11): 2098-106, 2014 Nov.
Article in English | MEDLINE | ID: mdl-24956282

ABSTRACT

We propose a technique for myocardial motion estimation based on image registration using both B-mode echocardiographic images and tissue Doppler sequences acquired interleaved. The velocity field is modeled continuously using B-splines and the spatiotemporal transform is constrained to be diffeomorphic. Images before scan conversion are used to improve the accuracy of the estimation. The similarity measure includes a model of the speckle pattern distribution of B-mode images. It also penalizes the disagreement between tissue Doppler velocities and the estimated velocity field. Registration accuracy is evaluated and compared to other alternatives using a realistic synthetic dataset, obtaining mean displacement errors of about 1 mm. Finally, the method is demonstrated on data acquired from six volunteers, both at rest and during exercise. Robustness is tested against low image quality and fast heart rates during exercise. Results show that our method provides a robust motion estimate in these situations.


Subject(s)
Echocardiography, Doppler/methods , Heart/physiology , Image Processing, Computer-Assisted/methods , Adult , Female , Heart Ventricles/anatomy & histology , Heart Ventricles/diagnostic imaging , Humans , Male , Movement/physiology , Reproducibility of Results , Ventricular Function/physiology , Young Adult
5.
Med Image Anal ; 17(7): 816-29, 2013 Oct.
Article in English | MEDLINE | ID: mdl-23707227

ABSTRACT

Patient-specific cardiac modeling can help in understanding pathophysiology and therapy planning. However it requires to combine functional and anatomical data in order to build accurate models and to personalize the model geometry, kinematics, electrophysiology and mechanics. Personalizing the electromechanical coupling from medical images is a challenging task. We use the Bestel-Clément-Sorine (BCS) electromechanical model of the heart, which provides reasonable accuracy with a reasonable number of parameters (14 for each ventricle) compared to the available clinical data at the organ level. We propose a personalization strategy from cine MRI data in two steps. We first estimate global parameters with an automatic calibration algorithm based on the Unscented Transform which allows to initialize the parameters while matching the volume and pressure curves. In a second step we locally personalize the contractilities of all AHA (American Heart Association) zones of the left ventricle using the reduced order unscented Kalman filtering on Regional Volumes. This personalization strategy was validated synthetically and tested successfully on eight healthy and three pathological cases.


Subject(s)
Heart Conduction System/physiology , Heart Ventricles/anatomy & histology , Image Interpretation, Computer-Assisted/methods , Magnetic Resonance Imaging, Cine/methods , Models, Cardiovascular , Myocardial Contraction/physiology , Ventricular Function, Left/physiology , Algorithms , Computer Simulation , Excitation Contraction Coupling/physiology , Humans , Image Enhancement/methods , Imaging, Three-Dimensional/methods , Organ Size , Precision Medicine/methods , Reproducibility of Results , Sensitivity and Specificity
6.
IEEE Trans Med Imaging ; 32(9): 1632-46, 2013 Sep.
Article in English | MEDLINE | ID: mdl-23674439

ABSTRACT

This paper evaluates five 3D ultrasound tracking algorithms regarding their ability to quantify abnormal deformation in timing or amplitude. A synthetic database of B-mode image sequences modeling healthy, ischemic and dyssynchrony cases was generated for that purpose. This database is made publicly available to the community. It combines recent advances in electromechanical and ultrasound modeling. For modeling heart mechanics, the Bestel-Clement-Sorine electromechanical model was applied to a realistic geometry. For ultrasound modeling, we applied a fast simulation technique to produce realistic images on a set of scatterers moving according to the electromechanical simulation result. Tracking and strain accuracies were computed and compared for all evaluated algorithms. For tracking, all methods were estimating myocardial displacements with an error below 1 mm on the ischemic sequences. The introduction of a dilated geometry was found to have a significant impact on accuracy. Regarding strain, all methods were able to recover timing differences between segments, as well as low strain values. On all cases, radial strain was found to have a low accuracy in comparison to longitudinal and circumferential components.


Subject(s)
Biomechanical Phenomena/physiology , Echocardiography, Three-Dimensional/methods , Models, Cardiovascular , Algorithms , Computer Simulation , Heart/anatomy & histology , Heart/physiology , Heart/physiopathology , Humans , Myocardial Ischemia/diagnostic imaging , Myocardial Ischemia/pathology , Myocardial Ischemia/physiopathology , Myocardium/pathology , Reproducibility of Results
7.
J Mech Behav Biomed Mater ; 20: 259-71, 2013 Apr.
Article in English | MEDLINE | ID: mdl-23499249

ABSTRACT

Patient-specific cardiac modelling can help in understanding pathophysiology and predict therapy effects. This requires the personalization of the geometry, kinematics, electrophysiology and mechanics. We use the Bestel-Clément-Sorine (BCS) electromechanical model of the heart, which provides reasonable accuracy with a reduced parameter number compared to the available clinical data at the organ level. We propose a preliminary specificity study to determine the relevant global parameters able to differentiate the pathological cases from the healthy controls. To this end, a calibration algorithm on global measurements is developed. This calibration method was tested successfully on 6 volunteers and 2 heart failure cases and enabled to tune up to 7 out of the 14 necessary parameters of the BCS model, from the volume and pressure curves. This specificity study confirmed domain-knowledge that the relaxation rate is impaired in post-myocardial infarction heart failure and the myocardial stiffness is increased in dilated cardiomyopathy heart failures.


Subject(s)
Algorithms , Heart Conduction System/physiopathology , Heart Diseases/physiopathology , Magnetic Resonance Imaging, Cine/methods , Models, Cardiovascular , Myocardial Contraction , Myocardium/pathology , Calibration , Computer Simulation , Humans , Pilot Projects , Reproducibility of Results , Sensitivity and Specificity
8.
Med Biol Eng Comput ; 51(11): 1235-50, 2013 Nov.
Article in English | MEDLINE | ID: mdl-23430328

ABSTRACT

This manuscript describes our recent developments towards better understanding of the mechanisms amenable to cardiac resynchronization therapy response. We report the results from a full multimodal dataset corresponding to eight patients from the euHeart project. The datasets include echocardiography, MRI and electrophysiological studies. We investigate two aspects. The first one focuses on pre-operative multimodal image data. From 2D echocardiography and 3D tagged MRI images, we compute atlas based dyssynchrony indices. We complement these indices with presence and extent of scar tissue and correlate them with CRT response. The second one focuses on computational models. We use pre-operative imaging to generate a patient-specific computational model. We show results of a fully automatic personalized electromechanical simulation. By case-per-case discussion of the results, we highlight the potential and key issues of this multimodal pipeline for the understanding of the mechanisms of CRT response and a better patient selection.


Subject(s)
Cardiac Resynchronization Therapy , Electrocardiography , Imaging, Three-Dimensional , Magnetic Resonance Imaging , Models, Cardiovascular , Precision Medicine , Adult , Aged , Computer Simulation , Humans , Middle Aged , Patient Selection
9.
Med Image Anal ; 16(1): 201-15, 2012 Jan.
Article in English | MEDLINE | ID: mdl-21920797

ABSTRACT

Cardiac resynchronisation therapy (CRT) is an effective treatment for patients with congestive heart failure and a wide QRS complex. However, up to 30% of patients are non-responders to therapy in terms of exercise capacity or left ventricular reverse remodelling. A number of controversies still remain surrounding patient selection, targeted lead implantation and optimisation of this important treatment. The development of biophysical models to predict the response to CRT represents a potential strategy to address these issues. In this article, we present how the personalisation of an electromechanical model of the myocardium can predict the acute haemodynamic changes associated with CRT. In order to introduce such an approach as a clinical application, we needed to design models that can be individualised from images and electrophysiological mapping of the left ventricle. In this paper the personalisation of the anatomy, the electrophysiology, the kinematics and the mechanics are described. The acute effects of pacing on pressure development were predicted with the in silico model for several pacing conditions on two patients, achieving good agreement with invasive haemodynamic measurements: the mean error on dP/dt(max) is 47.5±35mmHgs(-1), less than 5% error. These promising results demonstrate the potential of physiological models personalised from images and electrophysiology signals to improve patient selection and plan CRT.


Subject(s)
Body Surface Potential Mapping/methods , Heart Conduction System/physiopathology , Models, Cardiovascular , Myocardial Contraction , Therapy, Computer-Assisted/methods , Ventricular Dysfunction, Left/prevention & control , Ventricular Dysfunction, Left/physiopathology , Aged , Computer Simulation , Diagnosis, Computer-Assisted/methods , Female , Humans , Male , Pilot Projects , Treatment Outcome , Ventricular Dysfunction, Left/diagnosis
10.
IEEE Trans Med Imaging ; 30(9): 1605-16, 2011 Sep.
Article in English | MEDLINE | ID: mdl-21880565

ABSTRACT

Cardiac remodelling plays a crucial role in heart diseases. Analyzing how the heart grows and remodels over time can provide precious insights into pathological mechanisms, eventually resulting in quantitative metrics for disease evaluation and therapy planning. This study aims to quantify the regional impacts of valve regurgitation and heart growth upon the end-diastolic right ventricle (RV) in patients with tetralogy of Fallot, a severe congenital heart defect. The ultimate goal is to determine, among clinical variables, predictors for the RV shape from which a statistical model that predicts RV remodelling is built. Our approach relies on a forward model based on currents and a diffeomorphic surface registration algorithm to estimate an unbiased template. Local effects of RV regurgitation upon the RV shape were assessed with Principal Component Analysis (PCA) and cross-sectional multivariate design. A generative 3-D model of RV growth was then estimated using partial least squares (PLS) and canonical correlation analysis (CCA). Applied on a retrospective population of 49 patients, cross-effects between growth and pathology could be identified. Qualitatively, the statistical findings were found realistic by cardiologists. 10-fold cross-validation demonstrated a promising generalization and stability of the growth model. Compared to PCA regression, PLS was more compact, more precise and provided better predictions.


Subject(s)
Heart Ventricles/growth & development , Heart Ventricles/pathology , Models, Cardiovascular , Models, Statistical , Tetralogy of Fallot/pathology , Ventricular Dysfunction, Right/pathology , Ventricular Remodeling , Adult , Aged , Female , Humans , Least-Squares Analysis , Magnetic Resonance Imaging , Male , Middle Aged , Principal Component Analysis , Retrospective Studies
11.
Prog Biophys Mol Biol ; 107(1): 122-33, 2011 Oct.
Article in English | MEDLINE | ID: mdl-21791225

ABSTRACT

Computational models of the heart at various scales and levels of complexity have been independently developed, parameterised and validated using a wide range of experimental data for over four decades. However, despite remarkable progress, the lack of coordinated efforts to compare and combine these computational models has limited their impact on the numerous open questions in cardiac physiology. To address this issue, a comprehensive dataset has previously been made available to the community that contains the cardiac anatomy and fibre orientations from magnetic resonance imaging as well as epicardial transmembrane potentials from optical mapping measured on a perfused ex-vivo porcine heart. This data was used to develop and customize four models of cardiac electrophysiology with different level of details, including a personalized fast conduction Purkinje system, a maximum a posteriori estimation of the 3D distribution of transmembrane potential, the personalization of a simplified reaction-diffusion model, and a detailed biophysical model with generic conduction parameters. This study proposes the integration of these four models into a single modelling and simulation pipeline, after analyzing their common features and discrepancies. The proposed integrated pipeline demonstrates an increase prediction power of depolarization isochrones in different pacing conditions.


Subject(s)
Electrophysiological Phenomena , Heart/physiology , Magnetic Resonance Imaging , Models, Biological , Animals , Biophysical Phenomena , Diffusion , Heart/anatomy & histology , In Vitro Techniques , Membrane Potentials , Pericardium/anatomy & histology , Pericardium/cytology , Pericardium/physiology , Purkinje Fibers/anatomy & histology , Purkinje Fibers/cytology , Purkinje Fibers/physiology , Reproducibility of Results , Swine , Systems Integration , Time Factors
12.
Article in English | MEDLINE | ID: mdl-20879343

ABSTRACT

Despite recent efforts in cardiac electrophysiology modelling, there is still a strong need to make macroscopic models usable in planning and assistance of the clinical procedures. This requires model personalisation i.e. estimation of patient-specific model parameters and computations compatible with clinical constraints. Fast macroscopic models allow a quick estimation of the tissue conductivity, but are often unreliable in prediction of arrhythmias. On the other side, complex biophysical models are quite expensive for the tissue conductivity estimation, but are well suited for arrhythmia predictions. Here we present a coupled personalisation framework, which combines the benefits of the two models. A fast Eikonal (EK) model is used to estimate the conductivity parameters, which are then used to set the parameters of a biophysical model, the Mitchell-Schaeffer (MS) model. Additional parameters related to Action Potential Duration (APD) and APD restitution curves for the tissue are estimated for the MS model. This framework is applied to a clinical dataset provided with an hybrid X-Ray/MR imaging on an ischemic patient. This personalised MS Model is then used for in silico simulation of clinical Ventricular Tachycardia (VT) stimulation protocol to predict the induction of VT. This proof of concept opens up possibilities of using VT induction modelling directly in the intervention room, in order to plan the radio-frequency ablation lines.


Subject(s)
Body Surface Potential Mapping/methods , Heart Conduction System/physiopathology , Models, Cardiovascular , Myocardial Ischemia/diagnosis , Myocardial Ischemia/physiopathology , Tachycardia, Ventricular/diagnosis , Tachycardia, Ventricular/physiopathology , Computer Simulation , Diagnosis, Computer-Assisted/methods , Humans , Myocardial Ischemia/complications , Tachycardia, Ventricular/complications
13.
Article in English | MEDLINE | ID: mdl-20879371

ABSTRACT

Non-linear image registration is a standard approach to track soft tissues in medical images. By estimating spatial transformations between images, visible structures can be followed over time. For clinical applications the model of transformation must be consistent with the properties of the biological tissue, such as incompressibility. LogDemons is a fast non-linear registration algorithm that provides diffusion-like diffeomorphic transformations parameterised by stationary velocity fields. Yet, its use for tissue tracking has been limited because of the ad-hoc Gaussian regularisation that prevents implementing other transformation models. In this paper, we propose a mathematical formulation of demons regularisation that fits into LogDemons framework. This formulation enables to ensure volume-preserving deformations by minimising the energy functional directly under the linear divergence-free constraint, yielding little computational overhead. Tests on synthetic incompressible fields showed that our approach outperforms the original logDemons in terms of incompressible deformation recovery. The algorithm showed promising results on one patient for the automatic recovery of myocardium strain from cardiac anatomical and 3D tagged MRI.


Subject(s)
Algorithms , Heart/anatomy & histology , Image Interpretation, Computer-Assisted/methods , Magnetic Resonance Imaging, Cine/methods , Pattern Recognition, Automated/methods , Subtraction Technique , Image Enhancement/methods , Reproducibility of Results , Sensitivity and Specificity , Signal Processing, Computer-Assisted
15.
Med Image Comput Comput Assist Interv ; 11(Pt 1): 678-85, 2008.
Article in English | MEDLINE | ID: mdl-18979805

ABSTRACT

Despite important recent efforts in cardiac electrophysiology modelling, there is still a strong need for validating macroscopic models, that are well suited for diagnosis and treatment planning. In this paper we present a method to adjust the parameters of a macroscopic electrophysiology model on depolarisation and repolarisation maps obtained ex-vivo from optical imaging. With this imaging technique, optical fluorescence data are recorded with high spatial and temporal resolution on a large healthy porcine heart. A model of the myocardium is built from the MR images of the same heart, which also integrates the myocardial fibre orientation measured with DTI. We then present the first quantitative adjustment of a personalised volumetric model of the myocardium.


Subject(s)
Body Surface Potential Mapping/methods , Heart Conduction System/anatomy & histology , Heart Conduction System/physiology , Image Interpretation, Computer-Assisted/methods , Microscopy, Fluorescence/methods , Models, Cardiovascular , Subtraction Technique , Animals , Computer Simulation , Models, Anatomic , Swine
16.
Comput Aided Surg ; 12(1): 43-52, 2007 Jan.
Article in English | MEDLINE | ID: mdl-17364658

ABSTRACT

This paper presents a method for tessellating tissue boundaries and their interiors, given as input a map consisting of relevant tissue classes of the head, in order to produce anatomical models for finite-element-based simulation of endoscopic pituitary surgery. Our surface meshing method is based on the simplex model, which is initialized by duality from the topologically accurate results of the Marching Cubes algorithm, and which affords explicit control over mesh scale, while using tissue information to adhere to relevant boundaries. Our mesh scale strategy is spatially varying, based on the distance to a central point or linearized surgical path. The tetrahedralization stage also features a spatially varying mesh scale, consistent with that of the surface mesh.


Subject(s)
Computer Simulation , Endoscopy , Head/anatomy & histology , Models, Anatomic , Pituitary Gland/surgery , Algorithms , Head/surgery , Humans , Mathematics
17.
Stud Health Technol Inform ; 125: 13-8, 2007.
Article in English | MEDLINE | ID: mdl-17377224

ABSTRACT

SOFA is a new open source framework primarily targeted at medical simulation research. Based on an advanced software architecture, it allows to (1) create complex and evolving simulations by combining new algorithms with algorithms already included in SOFA; (2) modify most parameters of the simulation--deformable behavior, surface representation, solver, constraints, collision algorithm, etc.--by simply editing an XML file; (3) build complex models from simpler ones using a scene-graph description; (4) efficiently simulate the dynamics of interacting objects using abstract equation solvers; and (5) reuse and easily compare a variety of available methods. In this paper we highlight the key concepts of the SOFA architecture and illustrate its potential through a series of examples.


Subject(s)
Computer Simulation , Education, Medical , Software Design , Algorithms , United States
18.
IEEE Trans Med Imaging ; 25(5): 612-25, 2006 May.
Article in English | MEDLINE | ID: mdl-16689265

ABSTRACT

This paper presents a new three-dimensional electromechanical model of the two cardiac ventricles designed both for the simulation of their electrical and mechanical activity, and for the segmentation of time series of medical images. First, we present the volumetric biomechanical models built. Then the transmembrane potential propagation is simulated, based on FitzHugh-Nagumo reaction-diffusion equations. The myocardium contraction is modeled through a constitutive law including an electromechanical coupling. Simulation of a cardiac cycle, with boundary conditions representing blood pressure and volume constraints, leads to the correct estimation of global and local parameters of the cardiac function. This model enables the introduction of pathologies and the simulation of electrophysiology interventions. Moreover, it can be used for cardiac image analysis. A new proactive deformable model of the heart is introduced to segment the two ventricles in time series of cardiac images. Preliminary results indicate that this proactive model, which integrates a priori knowledge on the cardiac anatomy and on its dynamical behavior, can improve the accuracy and robustness of the extraction of functional parameters from cardiac images even in the presence of noisy or sparse data. Such a model also allows the simulation of cardiovascular pathologies in order to test therapy strategies and to plan interventions.


Subject(s)
Heart Conduction System/anatomy & histology , Heart Conduction System/physiology , Heart Ventricles/anatomy & histology , Image Interpretation, Computer-Assisted/methods , Models, Cardiovascular , Myocardial Contraction/physiology , Ventricular Function , Body Surface Potential Mapping/methods , Computer Simulation , Humans , Models, Anatomic
19.
Stud Health Technol Inform ; 119: 22-7, 2006.
Article in English | MEDLINE | ID: mdl-16404006

ABSTRACT

This paper presents a method for tessellating tissue boundaries and their interiors, given as input a tissue map consisting of relevant classes of the head, in order to produce anatomical models for finite element-based simulation of endoscopic pituitary surgery. Our surface meshing method is based on the simplex model, which is initialized by duality from the topologically accurate results of the Marching Cubes algorithm, and which features explicit control over mesh scale, while using tissue information to adhere to relevant boundaries. Our mesh scale strategy is spatially varying, based on the distance to a central point or linearized surgical path. The tetrahedralization stage also features a spatially varying mesh scale, consistent with that of the surface mesh.


Subject(s)
Computer Simulation , Endoscopy , Head , Models, Anatomic , Pituitary Gland/surgery , Tomography, X-Ray Computed/methods , Algorithms , Humans , User-Computer Interface
20.
Med Image Anal ; 9(5): 467-80, 2005 Oct.
Article in English | MEDLINE | ID: mdl-16006170

ABSTRACT

Simulating cardiac electromechanical activity is of great interest for a better understanding of pathologies and for therapy planning. Design and validation of such models is difficult due to the lack of clinical data. XMR systems are a new type of interventional facility in which patients can be rapidly transferred between X-ray and MR systems. Our goal is to design and validate an electromechanical model of the myocardium using XMR imaging. The proposed model is computationally fast and uses clinically observable parameters. We present the integration of anatomy, electrophysiology, and motion from patient data. Pathologies are introduced in the model and simulations are compared to measured data. Initial qualitative comparison on the two clinical cases presented is encouraging. Once fully validated, these models will make it possible to simulate different interventional strategies.


Subject(s)
Heart Ventricles/physiopathology , Magnetic Resonance Imaging/methods , Models, Cardiovascular , Myocardial Contraction , Tomography, X-Ray Computed/methods , Ventricular Dysfunction, Left/diagnosis , Ventricular Dysfunction, Left/physiopathology , Algorithms , Computer Simulation , Heart Ventricles/diagnostic imaging , Heart Ventricles/pathology , Humans , Image Interpretation, Computer-Assisted/methods , Subtraction Technique , Ventricular Dysfunction, Left/diagnostic imaging , Ventricular Dysfunction, Left/pathology
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