Mathieu De Craene

Infarct Localization From Myocardial Deformation: Prediction and Uncertainty Quantification by Regression From a Low-Dimensional Space

Diagnosing and localizing myocardial infarct is crucial for early patient management and therapy planning. We propose a new method for predicting the location of myocardial infarct from local wall deformation, which has value for risk stratification from routine examinations such as (3D) echocardiography. The pipeline combines non-linear dimensionality reduction of deformation patterns and two multi-scale kernel regressions. Confidence in the diagnosis is assessed by a map of local uncertainties, which integrates plausible infarct locations generated from the space of reduced dimensionality. These concepts were tested on 500 synthetic cases generated from a realistic cardiac electromechanical model, and 108 pairs of 3D echocardiographic sequences and delayed-enhancement magnetic resonance images from real cases. Infarct prediction is made at a spatial resolution around 4 mm, more than 10 times smaller than the current diagnosis, made regionally. Our method is accurate, and significantly outperforms the clinically-used thresholding of the deformation patterns (on real data: sensitivity/specificity of 0.828/0.804, area under the curve: 0.909 versus 0.742 for the most predictive strain component). Uncertainty adds value to refine the diagnosis and eventually re-examine suspicious cases.Diagnosing and localizing myocardial infarct is crucial for early patient management and therapy planning. We propose a new method for predicting the location of myocardial infarct from local wall deformation, which has value for risk stratification from routine examinations such as (3D) echocardiography. The pipeline combines non-linear dimensionality reduction of deformation patterns and two multi-scale kernel regressions. Confidence in the diagnosis is assessed by a map of local uncertainties, which integrates plausible infarct locations generated from the space of reduced dimensionality. These concepts were tested on 500 synthetic cases generated from a realistic cardiac electromechanical model, and 108 pairs of 3D echocardiographic sequences and delayed-enhancement magnetic resonance images from real cases. Infarct prediction is made at a spatial resolution around 4 mm, more than 10 times smaller than the current diagnosis, made regionally. Our method is accurate, and significantly outperforms the clinically-used thresholding of the deformation patterns (on real data: sensitivity/specificity of 0.828/0.804, area under the curve: 0.909 versus 0.742 for the most predictive strain component). Uncertainty adds value to refine the diagnosis and eventually re-examine suspicious cases.

3D harmonic phase tracking with anatomical regularization

This paper presents a novel algorithm that extends HARP to handle 3D tagged MRI images. HARP results were regularized by an original regularization framework defined in an anatomical space of coordinates. In the meantime, myocardium incompressibility was integrated in order to correct the radial strain which is reported to be more challenging to recover. Both the tracking and regularization of LV displacements were done on a volumetric mesh to be computationally efficient. Also, a window-weighted regression method was extended to cardiac motion tracking which helps maintain a low complexity even at finer scales. On healthy volunteers, the tracking accuracy was found to be as accurate as the best candidates of a recent benchmark. Strain accuracy was evaluated on synthetic data, showing low bias and strain errors under 5% (excluding outliers) for longitudinal and circumferential strains, while the second and third quartiles of the radial strain errors are in the (-5%,5%) range. In clinical data, strain dispersion was shown to correlate with the extent of transmural fibrosis. Also, reduced deformation values were found inside infarcted segments.

Diagnostic Value of Three-Dimensional Contrast-Enhanced Echocardiography for Left Ventricular Volume and Ejection Fraction Measurement in Patients With Poor Acoustic Windows: A Comparison of Echocardiography and Magnetic Resonance Imaging

BACKGROUNDnThree-dimensional echocardiography (3DE) is a reliable and reproducible tool for assessing left ventricular (LV) function but remains sensitive to patient echogenicity. Contrast-enhanced 3DE (C3DE) has the potential to improve quantification in challenging patients. The aim of this study was to evaluate the impact of temporal resolution, spatial resolution, and image dynamic range on LV function assessed using C3DE compared with cardiac magnetic resonance imaging (MRI) in patients with poor echogenicity.nnnMETHODSnForty-one patients with poor echogenicity who underwent two-dimensional echocardiography (2DE), 3DE, C3DE, and MRI were retrospectively investigated.nnnRESULTSnBefore contrast injection, 24 patients had three or more nonvisible segments. Three cases of 2DE and 12 cases of 3DE were not suitable for quantification. LV end-diastolic volumes were systematically underestimated by 2DE (142 ± 58 mL), 3DE (146 ± 69 mL), and C3DE (172 ± 61 mL) compared with MRI (216 ± 85 mL) (P < .001). Similar results were found for LV end-systolic volumes (81 ± 65 mL for 2DE, 82 ± 69 mL for 3DE, and 102 ± 80 mL for C3DE vs 129 ± 94 mL for MRI; P < .001). C3DE provided the best agreement with MRI (Lin concordance correlation coefficients of 0.67, 0.93, and 0.99, respectively, for end-diastolic volume, end-systolic volume, and ejection fraction) as well as the best measurement reproducibility. Finally, ultrasound settings had no significant effect on LV volumes and ejection fraction measurements.nnnCONCLUSIONSnIn these patients with poor ultrasound image quality, C3DE, regardless of instrument settings, outperformed 2DE and 3DE to assess LV volumes and ejection fraction and can thus be proposed as an acceptable alternative when MRI cannot be performed in this subgroup.

Detailed Evaluation of Five 3D Speckle Tracking Algorithms Using Synthetic Echocardiographic Recordings

A plethora of techniques for cardiac deformation imaging with 3D ultrasound, typically referred to as 3D speckle tracking techniques, are available from academia and industry. Although the benefits of single methods over alternative ones have been reported in separate publications, the intrinsic differences in the data and definitions used makes it hard to compare the relative performance of different solutions. To address this issue, we have recently proposed a framework to simulate realistic 3D echocardiographic recordings and used it to generate a common set of ground-truth data for 3D speckle tracking algorithms, which was made available online. The aim of this study was therefore to use the newly developed database to contrast non-commercial speckle tracking solutions from research groups with leading expertise in the field. The five techniques involved cover the most representative families of existing approaches, namely block-matching, radio-frequency tracking, optical flow and elastic image registration. The techniques were contrasted in terms of tracking and strain accuracy. The feasibility of the obtained strain measurements to diagnose pathology was also tested for ischemia and dyssynchrony.

Which reorientation framework for the atlas-based comparison of motion from cardiac image sequences?

The present paper builds upon recent advances in the spatiotemporal alignment of cardiac sequences to construct a statistical atlas of normal motion. Comparing cardiac sequences requires considering both the temporal component (changes along the sequences) and the inter-subject one. The objective here is to understand the changes in the comparison of myocardial velocities depending on (1) the chosen reorientation action (finite strain [local rotation only], local rotation and isotropic scaling, or full Jacobian matrix using the push-forward) and (2) the chosen system of coordinates (Lagrangian, Eulerian, or if a compromise between both [e.g. hybrid-Eulerian] is possible). Myocardial velocities are estimated locally using speckle tracking on echocardiographic (US) sequences, then aligned to a reference timescale, and finally reoriented to the anatomical reference according to the chosen reorientation framework. The methodology was applied to 2D US sequences in a 4-chamber view from 71 healthy volunteers. Experiments highlight the limitations of the hybrid-Eulerian scheme, showing that the intra-subject transformation should be taken into account, and discuss the options to perform the inter-subject one.

Temporal diffeomorphic free form deformation to quantify changes induced by left and right bundle branch block and pacing

This paper presents motion and deformation quantification results obtained from synthetic and in vitro phantom data provided by the second cardiac Motion Analysis Challenge at STACOM-MICCAI. We applied the Temporal Diffeomorphic Free Form Deformation (TDFFD) algorithm to the datasets. This algorithm builds upon a diffeomorphic version of the FFD, to provide a 3D+t continuous and differentiable transform. The similarity metric includes a comparison between consecutive images, and between a reference and each of the following images. n nMotion and strain accuracy were evaluated on synthetic 3D ultrasound sequences with known ground truth motion. Experiments were also conducted on in vitro acquisitions.

Coil compaction and aneurysm growth: image-based quantification using non-rigid registration

Endovascular treatment of intracranial aneurysms is a minimally-invasive technique recognized as a valid alternative to surgical clipping. However, endovascular treatment can be associated to aneurysm recurrence, either due to coil compaction or aneurysm growth. The quantification of coil compaction or aneurysm growth is usually performed by manual measurements or visual inspection of images from consecutive follow-ups. Manual measurements permit to detect large global deformation but might have insufficient accuracy for detecting subtle or more local changes between images. Image inspection permits to detect a residual neck in the aneurysm but do not differentiate aneurysm growth from coil compaction. In this paper, we propose to quantify independently coil compaction and aneurysm growth using non-rigid image registration. Local changes of volume between images at successive time points are identified using the Jacobian of the non-rigid transformation. Two different non-rigid registration strategies are applied in order to explore the sensitivity of Jacobian-based volume changes against the registration method, FFD registration based on mutual information and Demons. This volume-variation measure has been applied to four patients of which a series of 3D Rotational Angiography (3DRA) images obtained at different controls separated from two months to two years were available. The evolution of coil and aneurysm volumes along the period has been obtained separately, which allows distinguishing between coil compaction and aneurysm growth. On the four cases studied in this paper, aneurysm recurrence was always associated to aneurysm growth, as opposed to strict coil compaction.

Elastic registration vs. block matching for quantification of cardiac function with 3D ultrasound: Initial results of a direct comparison in silico based on a new evaluation pipeline

This paper presents a comparison between block matching and elastic registration for the estimation of cardiac deformation and strain from 3D ultrasound. The comparison study exploits a new evaluation pipeline recently developed by the authors. The pipeline generates synthetic sequences that are extremely similar to real ultrasound recording while the synthetic cardiac motion is fully controlled by an electro-mechanical model of the heart. Hereto, five synthetic sequences were generated corresponding to one healthy heart and four ischemic ones. Elastic registration returned both the smaller tracking errors and the most robust strain estimates. Although with limitations, this study brings further evidence that the new technique might be ready for extensive clinical testing.

Improved Myocardial Motion Estimation Combining Tissue Doppler and B-Mode Echocardiographic Images

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.

Manifold learning characterization of abnormal myocardial motion patterns: application to CRT-Induced changes

The present paper aims at quantifying the evolution of a given motion pattern under cardiac resynchronization therapy (CRT). It builds upon techniques for population-based cardiac motion quantification (statistical atlases, for inter-sequence spatiotemporal alignment and the definition of normal/abnormal motion). Manifold learning is used on spatiotemporal maps of myocardial motion abnormalities to represent a given abnormal pattern and to compare any individual to that pattern. The methodology was applied to 2D echocardiographic sequences in a 4-chamber view from 108 subjects (21 healthy volunteers and 87 CRT candidates) at baseline, with pacing ON, and at 12 months follow-up. Experiments confirmed that recovery of a normal motion pattern is a necessary but not sufficient condition for CRT response.