A Geometrical Approach for Automatic Shape Restoration of the Left Ventricle

Tan, May-Ling; Su, Yi; Lim, Chi Wan; Selvaraj, Senthil Kumar; Zhong, Liang

doi:10.1371/journal.pone.0068615

Cited by 8 publications

(4 citation statements)

References 22 publications

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“…In our earlier study, we have encountered data with large distortion from breath hold motions, which critically undermined the accuracy of function assessment. We proposed the method to recover the distorted shape in [ 29 ]. The registration step in this article could eliminate this distortion before shape modeling.…”

Section: Resultsmentioning

confidence: 99%

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Variational Reconstruction of Left Cardiac Structure from CMR Images

et al. 2015

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Cardiovascular Disease (CVD), accounting for 17% of overall deaths in the USA, is the leading cause of death over the world. Advances in medical imaging techniques make the quantitative assessment of both the anatomy and function of heart possible. The cardiac modeling is an invariable prerequisite for quantitative analysis. In this study, a novel method is proposed to reconstruct the left cardiac structure from multi-planed cardiac magnetic resonance (CMR) images and contours. Routine CMR examination was performed to acquire both long axis and short axis images. Trained technologists delineated the endocardial contours. Multiple sets of two dimensional contours were projected into the three dimensional patient-based coordinate system and registered to each other. The union of the registered point sets was applied a variational surface reconstruction algorithm based on Delaunay triangulation and graph-cuts. The resulting triangulated surfaces were further post-processed. Quantitative evaluation on our method was performed via computing the overlapping ratio between the reconstructed model and the manually delineated long axis contours, which validates our method. We envisage that this method could be used by radiographers and cardiologists to diagnose and assess cardiac function in patients with diverse heart diseases.

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Section: Resultsmentioning

confidence: 99%

“…One group of approaches is image-based approaches [ 26 ]. The other is geometry-based approaches [ 27 – 29 ]. The image-based approaches are inherently inaccurate due to the large slice spacing and the complex nature of images such as the inhomogeneity and non-uniformity as well as the existence of papillary muscles.…”

Section: Methodsmentioning

confidence: 99%

Variational Reconstruction of Left Cardiac Structure from CMR Images

et al. 2015

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“…This restoration is achieved by iterative in-plane translation of both the LV epicardial and endocardial contour vertices via minimization of an objective function based on the principal curvatures of the LV epicardial surface. Further details of the restoration algorithm can be found in our previous publications (Tan et al, 2013 ; Su et al, 2014 ).…”

Section: Methodsmentioning

confidence: 99%

Left Ventricular Wall Stress Is Sensitive Marker of Hypertrophic Cardiomyopathy With Preserved Ejection Fraction

et al. 2018

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Hypertrophic cardiomyopathy (HCM) patients present altered myocardial mechanics due to the hypertrophied ventricular wall and are typically diagnosed by the increase in myocardium wall thickness. This study aimed to quantify regional left ventricular (LV) shape, wall stress and deformation from cardiac magnetic resonance (MR) images in HCM patients and controls, in order to establish superior measures to differentiate HCM from controls. A total of 19 HCM patients and 19 controls underwent cardiac MR scans. The acquired MR images were used to reconstruct 3D LV geometrical models and compute the regional parameters (i.e., wall thickness, curvedness, wall stress, area strain and ejection fraction) based on the standard 16 segment model using our in-house software. HCM patients were further classified into four quartiles based on wall thickness at end diastole (ED) to assess the impact of wall thickness on these regional parameters. There was a significant difference between the HCM patients and controls for all regional parameters (P < 0.001). Wall thickness was greater in HCM patients at the end-diastolic and end-systolic phases, and thickness was most pronounced in segments at the septal regions. A multivariate stepwise selection algorithm identified wall stress index at ED (σi,ED) as the single best independent predictor of HCM (AUC = 0.947). At the cutoff value σi,ED < 1.64, both sensitivity and specificity were 94.7%. This suggests that the end-diastolic wall stress index incorporating regional wall curvature—an index based on mechanical principle—is a sensitive biomarker for HCM diagnosis with potential utility in diagnostic and therapeutic assessment.

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“…This idealized and oversimplified assumption was also used in [ 16 ]. Tan et al [ 17 ] addressed the motion correction problem as the minimization of a certain energy function regarding curvature of the reconstructed LV shape. The assumption used is that the LV shape is convex for most vertices on the surface, which could be inaccurate or incorrect for highly variable cases—in particular, myocardial infarction patients with LV remodeling.…”

Section: Introductionmentioning

confidence: 99%

Correcting motion in multiplanar cardiac magnetic resonance images

et al. 2016

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BackgroundMisalignment in cardiac magnetic resonance (CMR) images can adversely affect three-dimensional left ventricle modelling and downstream quantitative analysis. Currently, there are two types of approaches for dealing with realignment and motion distortion problems, one image based and the other geometry based. Image-based approaches are limited by the inherent non-homogeneity and anisotropy of CMR images. Geometry-based approaches rely on idealized models and over-simplified assumptions. This study was motivated by the need for a robust and effective approach for correcting motion related distortions due to misalignment in CMR images.MethodsA cine cardiac magnetic resonance image sequence was acquired using our routine clinical imaging protocol. The left ventricular endocardium was delineated manually with software assistance on all long and short-axis images. Long and short-axis contours were projected onto a patient-based coordinate system and then realigned using iterative registration. The realigned contour points were used to reconstruct the shape of the left ventricle for quantitative validation.ResultsThe method was tested on five myocardial infarction patients whose images showed substantial misalignment. Realignment time was about 16 seconds per case, using a 2.5 GHz CPU desktop with obvious elimination of the distortion in the reconstructed model. Using the long-axis contour as a reference in evaluating the reconstructed models, it was apparent that the models with realigned contours had better accuracy than the non-realigned ones.ConclusionThis study presents a novel, geometry-based method for correcting motion distortions in CMR images. The method incorporates (1) manual delineation, (2) registration based on a generalized, iterative closest point algorithm, and (3) reconstruction of the shape of the left ventricle for quantitative validation. The effectiveness of our approach is corroborated both visually and by quantitative assessment. We envision the use of our method in current clinical practice as a means of improving accuracy in the evaluation of cardiac function.

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A Geometrical Approach for Automatic Shape Restoration of the Left Ventricle

Cited by 8 publications

References 22 publications

Variational Reconstruction of Left Cardiac Structure from CMR Images

Variational Reconstruction of Left Cardiac Structure from CMR Images

Left Ventricular Wall Stress Is Sensitive Marker of Hypertrophic Cardiomyopathy With Preserved Ejection Fraction

Correcting motion in multiplanar cardiac magnetic resonance images

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