Mapping cardiac fiber orientations from high-resolution DTI to high-frequency 3D ultrasound

Qin, Xulei; Wang, Silun; Shen, Ming; Zhang, Xiaodong; Wagner, Mary B.; Fei, Baowei

doi:10.1117/12.2043821

Cited by 13 publications

(15 citation statements)

References 35 publications

(26 reference statements)

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“…The complex structural organization of cardiac fibers and the spatial arrangement of cardiomyocytes in laminar sheetlets significantly contribute to cardiac function and contractile ejection patterns [14]. Indirect estimation of local cardiac fiber orientation using the procedure of mapping the cardiac fiber from DTI data has been done by MRI and ultrasound [16, 46, 47]. …”

Section: Cardiac Fiber and Heart Failurementioning

confidence: 99%

“…Ultrasound is often used in clinical cardiac examinations because it can provide real-time functional information regarding heart values and, similar to most three-dimensional imaging techniques, it has the capability to provide the geometry and motion information of the heart [103]. However, ultrasound cannot do so while supplying information regarding the cardiac fiber orientation [46]. Information regarding cardiac fibers must be wrapped to the ultrasound volume in order to supply useful information regarding the stress distributions and electric action spreading.…”

Section: Ultrasound Imagingmentioning

confidence: 99%

“…Geometries of the heart extracted from MRI are translated to ultrasound by rigid and deformable registration [46]. Deformation fields take into account both geometries from MRI and ultrasound after registration.…”

Section: Ultrasound Imagingmentioning

confidence: 99%

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Imaging technologies for cardiac fiber and heart failure: a review

2018

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There has been an increasing interest in studying cardiac fibers in order to improve the current knowledge regarding the mechanical and physiological properties of the heart during heart failure (HF), particularly early HF. Having a thorough understanding of the changes in cardiac fiber orientation may provide new insight into the mechanisms behind the progression of left ventricular (LV) remodeling and HF. We conducted a systematic review on various technologies for imaging cardiac fibers and its link to HF. This review covers literature reports from 1900 to 2017. PubMed and Google Scholar databases were searched using the keywords “cardiac fiber” and “heart failure” or “myofiber” and “heart failure.” This review highlights imaging methodologies, including magnetic resonance diffusion tensor imaging (MR-DTI), ultrasound, and other imaging technologies as well as their potential applications in basic and translational research on the development and progression of HF. MR-DTI and ultrasound have been most useful and significant in evaluating cardiac fibers and HF. New imaging technologies that have the ability to measure cardiac fiber orientations and identify structural and functional information of the heart will advance basic research and clinical diagnoses of HF.

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Section: Cardiac Fiber and Heart Failurementioning

confidence: 99%

Section: Ultrasound Imagingmentioning

confidence: 99%

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Imaging technologies for cardiac fiber and heart failure: a review

2018

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“…26,27,35,36 Since different ultrasound imaging directions lead to different segmental intensities, prior to the simulation, the architectures of rat hearts acquired from MRI were first registered to the corresponding real ultrasound volume. There are two steps for the registration: (1) registration between structural MRI geometries and the real ultrasound ones using a rigid transformation based on the location of the apex and papillary muscles 37 and (2) relocation and reorientation of DTI-derived fiber orientations using the rigid transformation.…”

Section: A4 Data Preprocessingmentioning

confidence: 99%

Simulating cardiac ultrasound image based on MR diffusion tensor imaging

et al. 2015

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Purpose: Cardiac ultrasound simulation can have important applications in the design of ultrasound systems, understanding the interaction effect between ultrasound and tissue and setting the ground truth for validating quantification methods. Current ultrasound simulation methods fail to simulate the myocardial intensity anisotropies. New simulation methods are needed in order to simulate realistic ultrasound images of the heart. Methods: The proposed cardiac ultrasound image simulation method is based on diffusion tensor imaging (DTI) data of the heart. The method utilizes both the cardiac geometry and the fiber orientation information to simulate the anisotropic intensities in B-mode ultrasound images. Before the simulation procedure, the geometry and fiber orientations of the heart are obtained from high-resolution structural MRI and DTI data, respectively. The simulation includes two important steps. First, the backscatter coefficients of the point scatterers inside the myocardium are processed according to the fiber orientations using an anisotropic model. Second, the cardiac ultrasound images are simulated with anisotropic myocardial intensities. The proposed method was also compared with two other nonanisotropic intensity methods using 50 B-mode ultrasound image volumes of five different rat hearts. The simulated images were also compared with the ultrasound images of a diseased rat heart in vivo. A new segmental evaluation method is proposed to validate the simulation results. The average relative errors (AREs) of five parameters, i.e., mean intensity, Rayleigh distribution parameter σ, and first, second, and third quartiles, were utilized as the evaluation metrics. The simulated images were quantitatively compared with real ultrasound images in both ex vivo and in vivo experiments. Results: The proposed ultrasound image simulation method can realistically simulate cardiac ultrasound images of the heart using high-resolution MR-DTI data. The AREs of their proposed method are 19% for the mean intensity, 17.7% for the scale parameter of Rayleigh distribution, 36.8% for the first quartile of the image intensities, 25.2% for the second quartile, and 19.9% for the third quartile. In contrast, the errors of the other two methods are generally five times more than those of their proposed method. Conclusions: The proposed simulation method uses MR-DTI data and realistically generates cardiac ultrasound images with anisotropic intensities inside the myocardium. The ultrasound simulation method could provide a tool for many potential research and clinical applications in cardiac ultrasound imaging. C 2015 American Association of Physicists in Medicine.

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“…Previously, we mapped cardiac fiber orientations from DTI to 3D ultrasound volume, but the DTI data were still acquired from the same target heart rather than from an existed template and only registration errors were evaluated. 29 Therefore, this paper provided a DTI template-based framework to estimate the personalized cardiac fiber orientations from 3D ultrasound. It estimated the cardiac fiber orientations of the target heart by deforming the fiber orientations of the template heart, based on the deformation field of the registration between the ultrasound geometry of the target heart and the MRI geometry of the template heart.…”

Section: Introductionmentioning

confidence: 99%

DTI template-based estimation of cardiac fiber orientations from 3D ultrasound

Qin

Fei

2015

Med. Phys.

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Purpose: Cardiac muscle fibers directly affect the mechanical, physiological, and pathological properties of the heart. Patient-specific quantification of cardiac fiber orientations is an important but difficult problem in cardiac imaging research. In this study, the authors proposed a cardiac fiber orientation estimation method based on three-dimensional (3D) ultrasound images and a cardiac fiber template that was obtained from magnetic resonance diffusion tensor imaging (DTI). Methods: A DTI template-based framework was developed to estimate cardiac fiber orientations from 3D ultrasound images using an animal model. It estimated the cardiac fiber orientations of the target heart by deforming the fiber orientations of the template heart, based on the deformation field of the registration between the ultrasound geometry of the target heart and the MRI geometry of the template heart. In the experiments, the animal hearts were imaged by high-frequency ultrasound, T1-weighted MRI, and high-resolution DTI. Results: The proposed method was evaluated by four different parameters: Dice similarity coefficient (DSC), target errors, acute angle error (AAE), and inclination angle error (IAE). Its ability of estimating cardiac fiber orientations was first validated by a public database. Then, the performance of the proposed method on 3D ultrasound data was evaluated by an acquired database. Their average values were 95.4% ± 2.0% for the DSC of geometric registrations, 21.0• ± 0.76• for AAE, and 19.4• ± 1.2• for IAE of fiber orientation estimations. Furthermore, the feasibility of this framework was also performed on 3D ultrasound images of a beating heart. Conclusions: The proposed framework demonstrated the feasibility of using 3D ultrasound imaging to estimate cardiac fiber orientation of in vivo beating hearts and its further improvements could contribute to understanding the dynamic mechanism of the beating heart and has the potential to help diagnosis and therapy of heart disease. C 2015 American Association of Physicists in Medicine.

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Mapping cardiac fiber orientations from high-resolution DTI to high-frequency 3D ultrasound

Cited by 13 publications

References 35 publications

Imaging technologies for cardiac fiber and heart failure: a review

Imaging technologies for cardiac fiber and heart failure: a review

Simulating cardiac ultrasound image based on MR diffusion tensor imaging

DTI template-based estimation of cardiac fiber orientations from 3D ultrasound

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