Automatic Segmentation of the Left Ventricle in Cardiac MRI Using Local Binary Fitting Model and Dynamic Programming Techniques

Segmentation of the left ventricle is very important to quantitatively analyze global and regional cardiac function from magnetic resonance. The aim of this study is to develop a novel algorithm for segmenting left ventricle on short-axis cardiac magnetic resonance images (MRI) to improve the performance of computer-aided diagnosis (CAD) systems. In this research, an automatic segmentation method for left ventricle is proposed on the basis of local binary fitting (LBF) model and dynamic programming techniques. The validation experiments are performed on a pool of data sets of 45 cases. For both endo- and epi-cardial contours of our results, percentage of good contours is about 93.5%, the average perpendicular distance are about 2 mm. The overlapping dice metric is about 0.91. The regression and determination coefficient between the experts and our proposed method on the LV mass is 1.038 and 0.9033, respectively; they are 1.076 and 0.9386 for ejection fraction (EF). The proposed segmentation method shows the better performance and has great potential in improving the accuracy of computer-aided diagnosis systems in cardiovascular diseases.     

Automatic 4D Reconstruction of Patient-Specific Cardiac Mesh with 1-to-1 Vertex Correspondence from Segmented Contours Lines

We propose an automatic algorithm for the reconstruction of patient-specific cardiac mesh models with 1-to-1 vertex correspondence. In this framework, a series of 3D meshes depicting the endocardial surface of the heart at each time step is constructed, based on a set of border delineated magnetic resonance imaging (MRI) data of the whole cardiac cycle. The key contribution in this work involves a novel reconstruction technique to generate a 4D (i.e., spatial–temporal) model of the heart with 1-to-1 vertex mapping throughout the time frames. The reconstructed 3D model from the first time step is used as a base template model and then deformed to fit the segmented contours from the subsequent time steps. A method to determine a tree-based connectivity relationship is proposed to ensure robust mapping during mesh deformation. The novel feature is the ability to handle intra- and inter-frame 2D topology changes of the contours, which manifests as a series of merging and splitting of contours when the images are viewed either in a spatial or temporal sequence. Our algorithm has been tested on five acquisitions of cardiac MRI and can successfully reconstruct the full 4D heart model in around 30 minutes per subject. The generated 4D heart model conforms very well with the input segmented contours and the mesh element shape is of reasonably good quality. The work is important in the support of downstream computational simulation activities.     

Assessment of Cardiac Function and Myocardial Morphology Using Small Animal Look-locker Inversion Recovery (SALLI) MRI in Rats

Small animal magnetic resonance imaging is an important tool to study cardiac function and changes in myocardial tissue. The high heart rates of small animals (200 to 600 beats/min) have previously limited the role of CMR imaging. Small animal Look-Locker inversion recovery (SALLI) is a T1 mapping sequence for small animals to overcome this problem ¹. T1 maps provide quantitative information about tissue alterations and contrast agent kinetics. It is also possible to detect diffuse myocardial processes such as interstitial fibrosis or edema ^1-6. Furthermore, from a single set of image data, it is possible to examine heart function and myocardial scarring by generating cine and inversion recovery-prepared late gadolinium enhancement-type MR images ¹.The presented video shows step-by-step the procedures to perform small animal CMR imaging. Here it is presented with a healthy Sprague-Dawley rat, however naturally it can be extended to different cardiac small animal models.     

Flow and myocardial interaction: an imaging perspective

Heart failure due to coronary artery disease has considerable morbidity and poor prognosis. An understanding of the underlying mechanics governing myocardial contraction is a prerequisite for interpreting and predicting changes induced by heart disease. Gross changes in contractile behaviour of the myocardium are readily detected with existing techniques. For more subtle changes during early stages of cardiac dysfunction, however, a sensitive method for measuring, as well as a precise criterion for quantifying, normal and impaired myocardial function is required. The purpose of this paper is to outline the role of imaging, particularly cardiovascular magnetic resonance (CMR), for investigating the fundamental relationships between cardiac morphology, function and flow. CMR is emerging as an important clinical tool owing to its safety, versatility and the high-quality images it produces that allow accurate and reproducible quantification of cardiac structure and function. We demonstrate how morphological and functional assessment of the heart can be achieved by CMR and illustrate how blood flow imaging can be used to study flow and structure interaction, particularly for elucidating the underlying haemodynamic significance of directional changes and asymmetries of the cardiac looping. Future outlook on combining imaging with engineering approaches in subject-specific biomechanical simulation is also provided.     

A Novel Atlas-Based Strategy for Understanding Cardiac Dysfunction in Patients with Congenital Heart Disease

Tetralogy of Fallot (TOF) is the most common form of cyanotic congenital heart disease. Infants diagnosed with TOF require surgical interventions to survive into adulthood. However, as a result of postoperative structural malformations and long-term ventricular remodeling, further interventions are often required later in life. To help identify those at risk of disease progression, serial cardiac magnetic resonance (CMR) imaging is used to monitor these patients. However, most of the detailed information on cardiac shape and biomechanics contained in these large four-dimensional (4D) data sets goes unused in clinical practice for lack of efficient and comprehensive quantitative analysis tools. While current global metrics of cardiac size and function, such as indexed ventricular mass and volumes, can identify patients at risk of further complications, they are not adequate to explain the underlying mechanisms causing the postoperative malfunctions, and help cardiologists plan optimal personalized treatments. We are proposing a novel approach that uses 4D ventricular shape models derived from CMR imaging exams to generate statistical atlases of ventricular shape and finite-element models of ventricular biomechanics to identify specific features of cardiac shape and biomechanical properties that explain variations in ventricular function. This study has the potential to discover novel biomarkers that precede adverse ventricular remodeling and dysfunction.     

Volumetric assessment of epicardial adipose tissue with cardiovascular magnetic resonance imaging

Objective: Previous studies determined the amount of epicardial fat by measuring the right ventricular epicardial fat thickness. However, it is not proven whether this one‐dimensional method correlates well with the absolute amount of epicardial fat. In this prospective study, a new cardiovascular magnetic resonance imaging (CMR) method using the three‐dimensional summation of slices method was introduced to assess the total amount of epicardial fat. Research Methods and Procedures: CMR was performed in 43 patients with congestive heart failure and in 28 healthy controls. The absolute amount of epicardial fat was assessed volumetrically in consecutive short‐axis views by means of the modified Simpson's rule. Additionally, the right ventricular epicardial fat thickness was measured in two different imaging planes: long‐axis view (EFT‐4CV) and consecutive short‐axis views (EFT‐SAX). Results: Using the volumetric approach, patients with congestive heart failure had less epicardial fat mass than controls (51 g vs. 65 g, p = 0.01). This finding was supported by EFT‐SAX (2.9 mm vs. 4.3 mm, p < 0.0001) but not by EFT‐4CV (3.5 mm vs. 3.8 mm, p = not significant). Epicardial fat mass correlated moderately with EFT‐SAX in both groups (r = 0.466, p = 0.012 in controls and r = 0.590, p < 0.0001 in patients) and with EFT‐4CV in controls (r = 0.387, p = 0.042). There were no significant differences between EFT‐4CV and EFT‐SAX in controls (4.3 mm vs. 3.8 mm, p = 0.240). However, in the heart failure group, EFT‐4CV was significantly higher compared with EFT‐SAX (3.5 mm vs. 2.9 mm, p = 0.003). Interobserver variability and reproducibility were superior for the volumetric approach compared with thickness measurements. Discussion: Quantitative assessment of epicardial fat mass using the CMR‐based volumetric approach is feasible and yields superior reproducibility compared with conventional methods.     

Patient oriented graph-based image segmentation

Despite increased image quality including medical imaging, image segmentation continues to represent a major bottleneck in practical applications due to noise and lack of contrast. In this paper, we present a new methodology to segment noisy, low contrast medical images, with a view to developing practical applications. Firstly, the contrast of the image is enhanced and then a modified graph-based method is followed. This paper has mainly two contributions: (1) a contrast enhancement stage performed by suitably utilizing the noise present in the medical data. This step is achieved through stochastic resonance theory applied in the wavelet domain and (2) a new weighting function is proposed for traditional graph-based approaches. Both qualitative (by our clinicians/radiologists) and quantitative evaluation performed on publicly available computed tomography (CT) (MICCAI 2007 Grand Challenge workshop database) and cardiac magnetic resonance (CMR) databases reflect the potential of the proposed method even in the presence of tumors/papillary muscles.     

Heart rate variability--a shape analysis of Lorenz plots

A new quantitative geometrical method to analyse heart rate variability is presented. The standard image analysis techniques were applied to the grey scale images of Lorenz plots, and the outlines of the attractor areas were determined via a contour following procedure based on a maze walking algorithm. For graphs of simple compact shape, the attractor region contours were described in terms of Fourier coefficients.     

An Active Contour Model for the Segmentation of Images with Intensity Inhomogeneities and Bias Field Estimation

Intensity inhomogeneity causes many difficulties in image segmentation and the understanding of magnetic resonance (MR) images. Bias correction is an important method for addressing the intensity inhomogeneity of MR images before quantitative analysis. In this paper, a modified model is developed for segmenting images with intensity inhomogeneity and estimating the bias field simultaneously. In the modified model, a clustering criterion energy function is defined by considering the difference between the measured image and estimated image in local region. By using this difference in local region, the modified method can obtain accurate segmentation results and an accurate estimation of the bias field. The energy function is incorporated into a level set formulation with a level set regularization term, and the energy minimization is conducted by a level set evolution process. The proposed model first appeared as a two-phase model and then extended to a multi-phase one. The experimental results demonstrate the advantages of our model in terms of accuracy and insensitivity to the location of the initial contours. In particular, our method has been applied to various synthetic and real images with desirable results.     

Magnetic resonance imaging of progressive cardiomyopathic changes in the db/db mouse

The db/db mouse is a well-established model of diabetes. Previous reports have documented contractile dysfunction (i.e., cardiomyopathy) in these animals, although the extant literature provides limited insights into cardiac structure and function as they change over time. To better elucidate the natural history of cardiomyopathy in db/db mice, we performed cardiac magnetic resonance (CMR) scans on these animals. CMR imaging was conducted with a 4.7-T magnet on female db/db mice and control db/+ littermates at 5, 9, 13, 17, and 22 wk of age. Gated gradient echo sequences were used to obtain cineographic short-axis slices from apex to base. From these images left ventricular (LV) mass (LVM), wall thickness, end-diastolic volume (LVEDV), and ejection fraction (LVEF) were determined. Additionally, cardiac [(18)F]fluorodeoxyglucose ([(18)F]FDG) PET scanning, pressure-volume loops, and real-time quantitative PCR on db/db myocardium were performed. Relative to control, db/db mice developed significant increases in LVM and wall thickness as early as 9 wk of age. LVEDV diverged slightly later, at 13 wk. Interestingly, compared with the baseline level, LVEF in the db/db group did not decrease significantly until 22 wk. Additionally, [(18)F]FDG metabolic imaging showed a 40% decrease in glucose uptake in db/db mice. Furthermore, contractile dysfunction was observed in 15-wk db/db mice undergoing pressure-volume loops. Finally, real-time quantitative PCR revealed an age-dependent recapitulation of the fetal gene program, consistent with a myopathic process. In summary, as assessed by CMR, db/db mice develop characteristic structural and functional changes consistent with cardiomyopathy.     

Cardiac glucose utilization in mice with mutated alpha- and beta-thyroid hormone receptors

Abnormal thyroid function is usually associated with altered cardiac function. Mutations in the thyroid hormone (TH)-binding region of the TH beta-receptor (TRbeta) that eliminate its TH-binding ability lead to the thyroid hormone resistance syndrome (RTH) in humans, which is characterized by high blood TH levels, goiter, hyperactivity, and tachycardia. Mice with "knock-in" mutations in the TH alpha-receptor (TRalpha) or TRbeta that remove their TH-binding ability have been developed, and those with the mutated TRbeta (TRbeta(PV/PV)) appear to provide a model for RTH. These two types of mutants show different effects on cerebral energy metabolism, e.g., negligible change in glucose utilization (CMR(Glc)) in TRbeta(PV/PV) mice and markedly reduced CMR(Glc), like that found in cretinous rats, in the mice (TRalpha(PV/+)) with the knock-in mutation of the TRalpha gene. Studies in knockout mice have indicated that the TRalpha may also influence heart rate. Because mutations in both receptor genes appear to affect some parameters of cardiac function and because cardiac functional activity and energy metabolism are linked, we measured heart glucose utilization (HMR(Glc)) in both the TRbeta(PV/PV) and TRalpha(PV/+) mutants. Compared with values in normal wild-type mice, HMR(Glc) was reduced (-77 to -95%) in TRalpha(PV/+) mutants and increased (87 to 340%) in TRbeta(PV/PV) mutants, the degree depending on the region of the heart. Thus the TRalpha(PV/+) and TRbeta(PV/PV) mutations lead, respectively, to opposite effects on energy metabolism in the heart that are consistent with the bradycardia seen in hypothyroidism and the tachycardia associated with hyperthyroidism and RTH.     

Noninvasive Cardiac Flow Assessment Using High Speed Magnetic Resonance Fluid Motion Tracking

Cardiovascular diseases can be diagnosed by assessing abnormal flow behavior in the heart. We introduce, for the first time, a magnetic resonance imaging-based diagnostic that produces sectional flow maps of cardiac chambers, and presents cardiac analysis based on the flow information. Using steady-state free precession magnetic resonance images of blood, we demonstrate intensity contrast between asynchronous and synchronous proton spins. Turbulent blood flow in cardiac chambers contains asynchronous blood proton spins whose concentration affects the signal intensities that are registered onto the magnetic resonance images. Application of intensity flow tracking based on their non-uniform signal concentrations provides a flow field map of the blood motion. We verify this theory in a patient with an atrial septal defect whose chamber blood flow vortices vary in speed of rotation before and after septal occlusion. Based on the measurement of cardiac flow vorticity in our implementation, we establish a relationship between atrial vorticity and septal defect. The developed system has the potential to be used as a prognostic and investigative tool for assessment of cardiac abnormalities, and can be exploited in parallel to examining myocardial defects using steady-state free precession magnetic resonance images of the heart.     

Persistence length of human cardiac α-tropomyosin measured by single molecule direct probe microscopy

α-Tropomyosin (αTm) is the predominant tropomyosin isoform in adult human heart and constitutes a major component in Ca2?-regulated systolic contraction of cardiac muscle. We present here the first direct probe images of WT human cardiac αTm by atomic force microscopy, and quantify its mechanical flexibility with three independent analysis methods. Single molecules of bacterially-expressed human cardiac αTm were imaged on poly-lysine coated mica and their contours were analyzed. Analysis of tangent-angle (θ(s)) correlation along molecular contours, second moment of tangent angles (<θ2(s)>), and end-to-end length (L(e-e)) distributions respectively yielded values of persistence length (L(p)) of 41-46 nm, 40-45 nm, and 42-52 nm, corresponding to 1-1.3 molecular contour lengths (L(c)). We also demonstrate that a sufficiently large population, with at least 100 molecules, is required for a reliable L(p) measurement of αTm in single molecule studies. Our estimate that L(p) for αTm is only slightly longer than L(c) is consistent with a previous study showing there is little spread of cooperative activation into near-neighbor regulatory units of cardiac thin filaments. The L(p) determined here for human cardiac αTm perhaps represents an evolutionarily tuned optimum between Ca2? sensitivity and cooperativity in cardiac thin filaments and likely constitutes an essential parameter for normal function in the human heart.     

A hybrid graph-based approach for right ventricle segmentation in cardiac MRI by long axis information transition

Right ventricle segmentation is a challenging task in cardiac image analysis due to its complex anatomy and huge shape variations. In this paper, we proposed a semi-automatic approach by incorporating the right ventricle region and shape information into livewire framework and using one slice segmentation result for the segmentation of adjacent slices. The region term is created using our previously proposed region growing algorithm combined with the SUSAN edge detector while the shape prior is obtained by forming a signed distance function (SDF) from a set of binary masks of the right ventricle and applying PCA on them. Short axis slices are divided into two groups: primary and secondary slices. A primary slice is segmented by the proposed modified livewire and the livewire seeds are transited to a pre-processed version of upper and lower slices (secondary) to find new seed positions in these slices. The shortest path algorithm is applied on each pair of seeds for segmentation. This method is applied on 48 MR patients (from MICCAI’12 Right Ventricle Segmentation Challenge) and yielded an average Dice Metric of 0.937 ± 0.58 and the Hausdorff Distance of 5.16 ± 2.88 mm for endocardium segmentation. The correlation with the ground truth contours were measured as 0.99, 0.98, and 0.93 for EDV, ESV and EF respectively. The qualitative and quantitative results declare that the proposed method outperforms the state-of-the-art methods that uses the same dataset and the cardiac global functional parameters are calculated robustly by the proposed method.     

Estimation of the longitudinal axis of line symmetrical soft bodies by stereophotogrammetry

The three-dimensional (3-D) position of rigid body segments is generally determined by stereophotogrammetry: the position of markers or marker-trees, fixed onto the rigid body, is identified in each of at least 2 images.Soft bodies like the tongue of a snake are not rigid and difficult to attach marker onto. Therefore, a method is developed to estimate the 3-D position of the central axis from the digitised contours.The 3-D finite spatial curve representing the tongue axis is described by a function of a fourth variable t,tin[0,1]. The projection of this line [x(t),y(t),z(t)], a polynomial curve of a user-defined order, was fitted onto minimally 2 recorded images by means of direct linear transformation. The result is an optimally estimated finite spatial curve defined by the polynomial parameters. The method is applicable for all line symmetrical organs or segments.     

Comparative study on the performance of textural image features for active contour segmentation

We present a computerized method for the semi-automatic detection of contours in ultrasound images.The novelty of our study is the introduction of a fast and efficient image function relating to parametric active contour models.This new function is a combination of the gray-level information and first-order statistical features,called standard deviation parameters.In a comprehensive study,the developed algorithm and the efficiency of segmentation were first tested for synthetic images.Tests were also performed on breast and liver ultrasound images.The proposed method was compared with the watershed approach to show its efficiency.The performance of the segmentation was estimated using the area error rate.Using the standard deviation textural feature and a 5×5 kernel,our curve evolution was able to produce results close to the minimal area error rate(namely 8.88% for breast images and 10.82% for liver images).The image resolution was evaluated using the contrast-to-gradient method.The experiments showed promising segmentation results.     

Evaluation of hypertrophic cardiomyopathy: new horizons for CMR?

Cardiac magnetic resonance imaging (CMR) is an accurate and reliable means of evaluating cardiac morphology, ventricular function, and myocardial perfusion, both for the left and the right ventricle thereby covering a whole spectrum of cardiac diseases. 1 CMR is therefore very well suited for identifying and characterising patients with various manifestations of left ventricular hypertrophy (LVH).