Estimation of imaging biomarker's progression in post-infarct patients using cross-sectional data

International audienceMany uncertainties remain about the relation between post-infarct scars and ventricular arrhythmia. Most post-infarct patients suffer scar-related arrhythmia several years after the infarct event suggesting that scar remodeling is a process that might require years until the affected tissue becomes arrhythmogenic. In clinical practice, a simple time-based rule is often used to assess risk and stratify patients. In other cases, left ventricular ejection fraction (LVEF) impairment is also taken into account but it is known to be suboptimal. More information is needed to better stratify patients and prescribe appropriate individualized treatments. In this paper we propose to use probabilistic disease progression modeling to obtain an image-based data-driven description of the in-farct maturation process. Our approach includes monotonic constraints in order to impose a regular behaviour on the biomarkers' trajectories. 49 post-MI patients underwent Computed Tomography (CT) and Late Gadolinium Enhanced Cardiac Magnetic Resonance (LGE-CMR) scans. Image-derived biomarkers were computed such as LVEF, LGE-CMR scar volume, fat volume, and size of areas with a different degree of left ven-tricular wall narrowing, from moderate to severe. We show that the model is able to estimate a plausible progression of post-infarct scar maturation. According to our results there is a progressive thinning process observable only with CT imaging; intramural fat appears in a late stage; LGE-CMR scar volume almost does not change and LVEF slightly changes during the scar maturation process

3D global and regional patterns of human fetal subplate growth determined in utero

The waiting period of subplate evolution is a critical phase for the proper formation of neural connections in the brain. During this time, which corresponds to 15 to 24 postconceptual weeks (PCW) in the human fetus, thalamocortical and cortico-cortical afferents wait in and are in part guided by molecules embedded in the extracellular matrix of the subplate. Recent advances in fetal MRI techniques now allow us to study the developing brain anatomy in 3D from in utero imaging. We describe a reliable segmentation protocol to delineate the boundaries of the subplate from T2-W MRI. The reliability of the protocol was evaluated in terms of intra-rater reproducibility on a subset of the subjects. We also present the first 3D quantitative analyses of temporal changes in subplate volume, thickness, and contrast from 18 to 24 PCW. Our analysis shows that firstly, global subplate volume increases in proportion with the supratentorial volume; the subplate remained approximately one-third of supratentorial volume. Secondly, we found both global and regional growth in subplate thickness and a linear increase in the median and maximum subplate thickness through the waiting period. Furthermore, we found that posterior regions—specifically the occipital pole, ventral occipito-temporal region, and planum temporale—of the developing brain underwent the most statistically significant increases in subplate thickness. During this period, the thickest region was the developing somatosensory/motor cortex. The subplate growth patterns reported here may be used as a baseline for comparison to abnormal fetal brain development

Phosphomimetic Modulation of eNOS Improves Myocardial Reperfusion and Mimics Cardiac Postconditioning in Mice

Objective: Myocardial infarction resulting from ischemia-reperfusion injury can be reduced by cardiac postconditioning, in which blood flow is restored intermittently prior to full reperfusion. Although key molecular mechanisms and prosurvival pathways involved in postconditioning have been identified, a direct role for eNOS-derived NO in improving regional myocardial perfusion has not been shown. The objective of this study is to measure, with high temporal and spatial resolution, regional myocardial perfusion during ischemia-reperfusion and postconditioning, in order to determine the contribution of regional blood flow effects of NO to infarct size and protection. Methods and Results: We used myocardial contrast echocardiography to measure regional myocardial blood flow in mice over time. Reperfusion after myocardial ischemia-reperfusion injury is improved by postconditioning, as well as by phosphomimetic eNOS modulation. Knock-in mice expressing a phosphomimetic S1176D form of eNOS showed improved myocardial reperfusion and significantly reduced infarct size. eNOS knock-out mice failed to show cardioprotection from postconditioning. The size of the no-reflow zone following ischemia-reperfusion is substantially reduced by postconditioning and by the phosphomimetic eNOS mutation. Conclusions and Significance: Using myocardial contrast echocardiography, we show that temporal dynamics of regional myocardial perfusion restoration contribute to reduced infarct size after postconditioning. eNOS has direct effects on myocardial blood flow following ischemia-reperfusion, with reduction in the size of the no-reflow zone. These results have important implications for ongoing clinical trials on cardioprotection, because the degree of protective benefit may be significantly influenced by the regional hemodynamic effects of eNOS-derived NO.American Heart Association (Predoctoral Fellowship)National Institutes of Health (U.S.) (R01 NS33335)National Institutes of Health (U.S.) (R01 HL57818

Cortical Thinning in Patients with Recent Onset Post-Traumatic Stress Disorder after a Single Prolonged Trauma Exposure

Most of magnetic resonance imaging (MRI) studies about post-traumatic stress disorder (PTSD) focused primarily on measuring of small brain structure volume or regional brain volume changes. There were rare reports investigating cortical thickness alterations in recent onset PTSD. Recent advances in computational analysis made it possible to measure cortical thickness in a fully automatic way, along with voxel-based morphometry (VBM) that enables an exploration of global structural changes throughout the brain by applying statistical parametric mapping (SPM) to high-resolution MRI. In this paper, Laplacian method was utilized to estimate cortical thickness after automatic segmentation of gray matter from MR images under SPM. Then thickness maps were analyzed by SPM8. Comparison between 10 survivors from a mining disaster with recent onset PTSD and 10 survivors without PTSD from the same trauma indicates cortical thinning in the left parietal lobe, right inferior frontal gyrus, and right parahippocampal gyrus. The regional cortical thickness of the right inferior frontal gyrus showed a significant negative correlation with the CAPS score in the patients with PTSD. Our study suggests that shape-related cortical thickness analysis may be more sensitive than volumetric analysis to subtle alteration at early stage of PTSD

Subspace Procrustes Analysis

Abstract. Procrustes Analysis (PA) has been a popular technique to align and build 2-D statistical models of shapes. Given a set of 2-D shapes PA is applied to remove rigid transformations. Then, a non-rigid 2-D model is computed by modeling (e.g., PCA) the residual. Although PA has been widely used, it has several limitations for modeling 2-D shapes: occluded landmarks and missing data can result in local minima solutions, and there is no guarantee that the 2-D shapes provide a uni-form sampling of the 3-D space of rotations for the object. To address previous issues, this paper proposes Subspace PA (SPA). Given several instances of a 3-D object, SPA computes the mean and a 2-D subspace that can simultaneously model all rigid and non-rigid deformations of the 3-D object. We propose a discrete (DSPA) and continuous (CSPA) for-mulation for SPA, assuming that 3-D samples of an object are provided. DSPA extends the traditional PA, and produces unbiased 2-D models by uniformly sampling different views of the 3-D object. CSPA provides a continuous approach to uniformly sample the space of 3-D rotations, being more efficient in space and time. Experiments using SPA to learn 2-D models of bodies from motion capture data illustrate the benefits of our approach.

Elastic shape analysis of boundaries of planar objects with multiple components and arbitrary topologies

We consider boundaries of planar objects as level set distance functions and present a Riemannian metric for their comparison and analysis. The metric is based on a parameterization-invariant framework for shape analysis of quadrilateral surfaces. Most previous Riemannian formulations of 2D shape analysis are restricted to curves that can be parameterized with a single parameter domain. However, 2D shapes may contain multiple connected components and many internal details that cannot be captured with such parameterizations. In this paper we propose to register planar curves of arbitrary topologies by utilizing the re-parameterization group of quadrilateral surfaces. The criterion used for computing this registration is a proper distance, which can be used to quantify differences between the level set functions and is especially useful in classification. We demonstrate this framework with multiple examples using toy curves, medical imaging data, subsets of the TOSCA data set, 2D hand-drawn sketches, and a 2D version of the SHREC07 data set. We demonstrate that our method outperforms the state-of-the-art in the classification of 2D sketches and performs well compared to other state-of-the-art methods on complex planar shapes

Variational methods in shape analysis

The analysis of shapes as elements in a frequently infinite-dimensional space of shapes has attracted increasing attention over the last decade. There are pioneering contributions in the theoretical foundation of shape space as a Riemannian manifold as well as path-breaking applications to quantitative shape comparison, shape recognition, and shape statistics. The aim of this chapter is to adopt a primarily physical perspective on the space of shapes and to relate this to the prevailing geometric perspective. Indeed, we here consider shapes given as boundary contours of volumetric objects, which consist either of a viscous fluid or an elastic solid. In the first case, shapes are transformed into each other via viscous transport of fluid material, and the flow naturally generates a connecting path in the space of shapes. The viscous dissipation rate—the rate at which energy is converted into heat due to friction—can be defined as a metric on an associated Riemannian manifold. Hence, via the computation of shortest transport paths one defines a distance measure between shapes