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Is Qualitative Cardiac Perfusion MRI "Good Enough"? [Editorial]

Axel, Leon
PMID: 29747848
ISSN: 1876-7591
CID: 3101252

eCurves: A Temporal Shape Encoding

Bernardis, Elena; Zhang, Yong; Konukoglu, Ender; Ou, Yangming; Javitz, Harold S; Axel, Leon; Metaxas, Dimitris; Desjardins, Benoit; Pohl, Kilian M
OBJECTIVE:This paper presents a framework for temporal shape analysis to capture the shape and changes of anatomical structures from three-dimensional+t(ime) medical scans. METHOD/METHODS:We first encode the shape of a structure at each time point with the spectral signature, i.e., the eigenvalues and eigenfunctions of the Laplace operator. We then expand it to capture morphing shapes by tracking the eigenmodes across time according to the similarity of their eigenfunctions. The similarity metric is motivated by the fact that small-shaped deformations lead to minor changes in the eigenfunctions. Following each eigenmode from the beginning to end results in a set of eigenmode curves representing the shape and its changes over time. RESULTS:We apply our encoding to a cardiac dataset consisting of series of segmentations outlining the right and left ventricles over time. We measure the accuracy of our encoding by training classifiers on discriminating healthy adults from patients that received reconstructive surgery for Tetralogy of Fallot (TOF). The classifiers based on our encoding significantly surpass deformation-based encodings of the right ventricle, the structure most impacted by TOF. CONCLUSION/CONCLUSIONS:The strength of our framework lies in its simplicity: It only assumes pose invariance within a time series but does not assume point-to-point correspondence across time series or a (statistical or physical) model. In addition, it is easy to implement and only depends on a single parameter, i.e., the number of curves.
PMID: 28641243
ISSN: 1558-2531
CID: 3027102

Two-dimensional XD-GRASP provides better image quality than conventional 2D cardiac cine MRI for patients who cannot suspend respiration

Piekarski, Eve; Chitiboi, Teodora; Ramb, Rebecca; Latson, Larry A Jr; Bhatla, Puneet; Feng, Li; Axel, Leon
OBJECTIVES: Residual respiratory motion degrades image quality in conventional cardiac cine MRI (CCMRI). We evaluated whether a free-breathing (FB) radial imaging CCMRI sequence with compressed sensing reconstruction [extradimensional (e.g. cardiac and respiratory phases) golden-angle radial sparse parallel, or XD-GRASP] could provide better image quality than a conventional Cartesian breath-held (BH) sequence in an unselected population of patients undergoing clinical CCMRI. MATERIALS AND METHODS: One hundred one patients who underwent BH and FB imaging in a midventricular short-axis plane at a matching location were included. Visual and quantitative image analysis was performed by two blinded experienced readers, using a five-point qualitative scale to score overall image quality and visual signal-to-noise ratio (SNR) grade, with measures of noise and sharpness. End-diastolic and end-systolic left ventricular areas were also measured and compared for both BH and FB images. RESULTS: Image quality was generally better with the BH cines (overall quality grade for BH vs FB images 4 vs 2.9, p < 0.001; noise 0.06 vs 0.08 p < 0.001; SNR grade 4.1 vs 3, p < 0.001), except for sharpness (p = 0.48). There were no significant differences between BH and FB images regarding end-diastolic or end-systolic areas (p = 0.35 and p = 0.12). Eighteen of the 101 patients had poor BH image quality (grade 1 or 2). In this subgroup, the quality of the FB images was better (p = 0.0032), as was the SNR grade (p = 0.003), but there were no significant differences regarding noise and sharpness (p = 0.45 and p = 0.47). CONCLUSION: Although FB XD-GRASP CCMRI was visually inferior to conventional BH CCMRI in general, it provided improved image quality in the subgroup of patients with respiratory-motion-induced artifacts on BH images.
PMID: 29067539
ISSN: 1352-8661
CID: 2757362

Magnetic resonance imaging of myocardial strain: A review of current approaches

Chitiboi, Teodora; Axel, Leon
Contraction of the heart is central to its purpose of pumping blood around the body. While simple global function measures (such as the ejection fraction) are most commonly used in the clinical assessment of cardiac function, MRI also provides a range of approaches for quantitatively characterizing regional cardiac function, including the local deformation (or strain) within the heart wall. While they have been around for some years, these methods are still undergoing further technical development, and they have had relatively little clinical evaluation. However, they can provide potentially useful new ways to assess cardiac function, which may be able to contribute to better classification and treatment of heart disease. This article provides some basic background on the physical and physiological factors that determine the motion of the heart, in health and disease and then reviews some of the ways that MRI methods are being developed to image and quantify strain within the myocardium. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017.
PMID: 28471530
ISSN: 1522-2586
CID: 2546652

Abnormal Motion Patterns of the Interventricular Septum

Dwivedi, Aeshita; Axel, Leon
PMID: 29025579
ISSN: 1876-7591
CID: 2731622

Recent Advances in Cardiovascular Magnetic Resonance: Techniques and Applications

Salerno, Michael; Sharif, Behzad; Arheden, Hakan; Kumar, Andreas; Axel, Leon; Li, Debiao; Neubauer, Stefan
Cardiovascular magnetic resonance imaging has become the gold standard for evaluating myocardial function, volumes, and scarring. Additionally, cardiovascular magnetic resonance imaging is unique in its comprehensive tissue characterization, including assessment of myocardial edema, myocardial siderosis, myocardial perfusion, and diffuse myocardial fibrosis. Cardiovascular magnetic resonance imaging has become an indispensable tool in the evaluation of congenital heart disease, heart failure, cardiac masses, pericardial disease, and coronary artery disease. This review will highlight some recent novel cardiovascular magnetic resonance imaging techniques, concepts, and applications.
PMID: 28611116
ISSN: 1942-0080
CID: 2615892

3D Motion Modeling and Reconstruction of Left Ventricle Wall in Cardiac MRI

Yang, Dong; Wu, Pengxiang; Tan, Chaowei; Pohl, Kilian M; Axel, Leon; Metaxas, Dimitris
The analysis of left ventricle (LV) wall motion is a critical step for understanding cardiac functioning mechanisms and clinical diagnosis of ventricular diseases. We present a novel approach for 3D motion modeling and analysis of LV wall in cardiac magnetic resonance imaging (MRI). First, a fully convolutional network (FCN) is deployed to initialize myocardium contours in 2D MR slices. Then, we propose an image registration algorithm to align MR slices in space and minimize the undesirable motion artifacts from inconsistent respiration. Finally, a 3D deformable model is applied to recover the shape and motion of myocardium wall. Utilizing the proposed approach, we can visually analyze 3D LV wall motion, evaluate cardiac global function, and diagnose ventricular diseases.
PMID: 28664198
ISSN: n/a
CID: 3074312

Multi-cycle Reconstruction of Cardiac MRI for the Analysis of Inter-ventricular Septum Motion During Free Breathing

Chitiboi, Teodora; Ramb, Rebecca; Feng, Li; Piekarski, Eve; Tautz, Lennart; Hennemuth, Anja; Axel, Leon
Small variations in left-ventricular preload due to respiration produce measurable changes in cardiac function in normal subjects. We show that this mechanism is altered in patients with reduced ejection fraction (EF), hypertrophy, or volume-loaded right ventricle (RV). We propose a multi-dimensional retrospective image reconstruction, based on an adaptive, soft classification of data into respiratory and cardiac phases, to study these effects.
PMID: 30498813
ISSN: n/a
CID: 3520122


Reynolds, Harmony R; Pasupathy, Sivabaskari; Gandhi, Himali; Tavella, Rosanna; Axel, Leon; Beltrame, John
ISSN: 1558-3597
CID: 2528882


Guandalini, Gustavo; Park, David; Pan, Stephen; Barbhaiya, Chirag; Axel, Leon; Fowler, Steven; Cerrone, Marina; Chinitz, Larry
ISSN: 1558-3597
CID: 2528942