Tracking of regions-of-interest in myocardial contrast echocardiography

Malpica, Norberto; Santos, A.; Zuluaga, Miguel Ángel; Ledesma, M.J.; Perez, Esther; Ma, García-Fernández; Desco, Manuel

doi:10.1016/j.ultrasmedbio.2003.11.007

Cited by 31 publications

(14 citation statements)

References 22 publications

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“…This software provides angle-independent 2D strain based on speckle tracking. [21][22][23] For the quantification of radial and circumferential strain, the software was applied on parasternal short-axis views, while for the quantification of longitudinal strain, the same software was applied on apical views. More specifically, XStrain 24 relies on a "feature tracking" algorithm and, in order to improve the border tracking results, it combines speckle tracking based with other information such as tissue-to-blood border detection, the periodicity of the cardiac cycle and the fact that the cardiac borders maintain their own "overall spatial coherence" over time.…”

Section: Myocardial Deformation In Acute Myocarditismentioning

confidence: 99%

Myocardial Deformation in Acute Myocarditis With Normal Left Ventricular Wall Motion - A Cardiac Magnetic Resonance and 2-Dimensional Strain Echocardiographic Study -

Bella

Gaeta

Pingitore

et al. 2010

Circ J

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Background:The aim of our study was to assess longitudinal (L), circumferential (C) and radial (R) strain (S) of the left ventricle (LV) in patients with acute myocarditis and preserved LV wall motion. Methods and Results:Of the 26 male patients that were enrolled, 13 patients (26±8 years) suffered from acute myocarditis and 13 (25±2 years) were healthy participants (controls). Both patients and controls underwent cardiac magnetic resonance (CMR) and 2-dimensional S imaging (2D-S) echocardiography on the same day. Myocardial strains (RS, LS and CS) were quantified by 2D-S. In patients with myocarditis, a delayed enhancement (DE) CMR study was performed to identify damaged myocardial segments. In the myocarditis group there was a significant LS reduction compared with controls (-25±7 vs -20±7, P<0.0001), whereas no difference was found between the 2 groups concerning CS and RS. Subepicardial DE areas were found in 12 of 13 patients. Segments with DE showed a significantly lower LS in comparison with segments without DE (-19±4 vs -23±6, P<0.0001). In contrast, no difference in CS and RS was found when comparing segments with DE vs segments without DE. Conclusions:In patients with acute myocarditis, evidence of subepicardial damage and no wall motion abnormalities, longitudinal deformation is diffusely impaired, whereas circumferential impairment is regionally sited in the areas of subepicardial damage. (Circ J 2010; 74: 1205 - 1213

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Section: Myocardial Deformation In Acute Myocarditismentioning

confidence: 99%

Myocardial Deformation in Acute Myocarditis With Normal Left Ventricular Wall Motion - A Cardiac Magnetic Resonance and 2-Dimensional Strain Echocardiographic Study -

Bella

Gaeta

Pingitore

et al. 2010

Circ J

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“…They fall in the general category known as Optical Flow, in advanced image analysis 3,4 . They are commonly referred as Speckle Tracking in echographic imaging when such velocities are used to follow physiological motion 5,6 but also apply to any other image modality such as CMR where these methods are referred as feature tracking or border tracking. …”

Section: Introductionmentioning

confidence: 99%

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

Hor

Baumann

Pedrizzetti³

et al. 2011

JoVE

140

122

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Purpose: An accurate and practical method to measure parameters like strain in myocardial tissue is of great clinical value, since it has been shown, that strain is a more sensitive and earlier marker for contractile dysfunction than the frequently used parameter EF. Current technologies for CMR are time consuming and difficult to implement in clinical practice. Feature tracking is a technology that can lead to more automization and robustness of quantitative analysis of medical images with less time consumption than comparable methods.Methods: An automatic or manual input in a single phase serves as an initialization from which the system starts to track the displacement of individual patterns representing anatomical structures over time. The specialty of this method is that the images do not need to be manipulated in any way beforehand like e.g. tagging of CMR images.Results: The method is very well suited for tracking muscular tissue and with this allowing quantitative elaboration of myocardium and also blood flow.Conclusions: This new method offers a robust and time saving procedure to quantify myocardial tissue and blood with displacement, velocity and deformation parameters on regular sequences of CMR imaging. It therefore can be implemented in clinical practice.

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“…In other words, the first frame is used as a spatial reference. In clinical applications typically an end-diastolic frame is chosen as the reference frame [4,12].…”

Section: Problem Definitionmentioning

confidence: 99%

“…Basal septal seg (BS) 16 Apical lateral seg (AL) 11,12 Midlateral seg (ML) 5,6 Basal lateral seg (BL) …”

Section: Standard Number Area 17unclassified

Automatic detection of coronary artery disease using registration of ultrasound images of the heart (echocardiography)

Masaeli¹,

Alavi²

2016

Turk J Elec Eng & Comp Sci

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Coronary artery diseases cause more than half of all deaths in the world. Obviously, early identification is an important way to control coronary artery disease that is diagnosed by measurement and scoring the general and regional movement of the left ventricle of heart (normal, hypokinetic, and akinetic). The most common method of imaging the heart using ultrasound is called echocardiography. Using this method accurate views of the heart walls, valves, and beginning of main arteries can be obtained. Due to the difficulty of the interpretation of these images, the length of time required, and errors in manual methods, an automated analysis method is required. In line with this goal, in this paper we have calculated the displacement field in a cycle of heart motion from two-dimensional echocardiography images. To do this, a frame is usually chosen as the reference frame and then all images in a cycle are mapped to it with a mathematical equation. The main idea is to find a semilocal spatiotemporal parametric model for deformation created in a cardiac cycle with nonrigid registration using B-spline functions as an optimization problem that effectively corrects differences due to movements by minimizing the difference between current frame and a reference frame. Motion estimation accuracy is measured using sum of squares differences. We use a gradient-descent algorithm and multiresolution method to acquire the coefficients in the motion model. The accuracy of the proposed method is assessed using a synthesis sequence of cardiac cycles produced with the simulation software Field II. This algorithm can be applied for the clinical analysis of the regional left ventricle and then movement parameters and threshold values for the scoring of each section can be extracted. The algorithm represents the significant difference between a part of a normal heart and an unhealthy heart and shows the potential of the clinical applications of the proposed method.

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Tracking of regions-of-interest in myocardial contrast echocardiography

Cited by 31 publications

References 22 publications

Myocardial Deformation in Acute Myocarditis With Normal Left Ventricular Wall Motion - A Cardiac Magnetic Resonance and 2-Dimensional Strain Echocardiographic Study -

Myocardial Deformation in Acute Myocarditis With Normal Left Ventricular Wall Motion - A Cardiac Magnetic Resonance and 2-Dimensional Strain Echocardiographic Study -

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

Automatic detection of coronary artery disease using registration of ultrasound images of the heart (echocardiography)

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