A fiber orientation model of the human heart using classical histological methods, magnetic resonance imaging and interpolation techniques

Theofilogiannakos, Efstratios K.; Theofilogiannakos, G. K.; Anogeianaki, A.; Danias, P.G.; Zairi, Hassen; Zaraboukas, Thomas; Stergiou-Michailidou, V.; Kallaras, Konstantinos; Anogianakis, G.

doi:10.1109/cic.2008.4749039

Cited by 4 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As shown in previous cardiac tissue histology studies [2, 3], the myofiber morphology has been considered as multiple myocyte arrangements separated by extensive planes. The orientations of pig cardiac myofibers are imaged using the high frequency ultrasound imaging system, which are shown as the bright regions in Figure 4.…”

Section: Resultsmentioning

confidence: 99%

“…However, the distribution of cardiac myofiber orientations is complex in the heart and is difficult to image and to quantify. There were previous research efforts in this area by using the histology analysis methods [2, 3]. Currently, magnetic resonance diffusion tensor imaging (MR-DTI) is used as a popular method to extract myocardial fiber orientation [4–6].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Extracting cardiac myofiber orientations from high frequency ultrasound images

et al. 2013

View full text Add to dashboard Cite

Cardiac myofiber plays an important role in stress mechanism during heart beating periods. The orientation of myofibers decides the effects of the stress distribution and the whole heart deformation. It is important to image and quantitatively extract these orientations for understanding the cardiac physiological and pathological mechanism and for diagnosis of chronic diseases. Ultrasound has been wildly used in cardiac diagnosis because of its ability of performing dynamic and noninvasive imaging and because of its low cost. An extraction method is proposed to automatically detect the cardiac myofiber orientations from high frequency ultrasound images. First, heart walls containing myofibers are imaged by B-mode high frequency (>20 MHz) ultrasound imaging. Second, myofiber orientations are extracted from ultrasound images using the proposed method that combines a nonlinear anisotropic diffusion filter, Canny edge detector, Hough transform, and K-means clustering. This method is validated by the results of ultrasound data from phantoms and pig hearts.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Extracting cardiac myofiber orientations from high frequency ultrasound images

et al. 2013

View full text Add to dashboard Cite

show abstract

“…Finally, the two 3D models, each one derived by the respective anatomical (MRI) and histological slices, can be easily combined into one single 3D tetrahedral mesh. Each tetrahedron of this high-quality mesh contains only one vector (Theofilogiannakos et al 2008). In Figure 6, we present, in a form of an image atlas, the fibre orientation of 2D anatomical slides of an intact post-mortem heart after its process in FibreCad.…”

Section: Fibrecadmentioning

confidence: 99%

“…Then starting from the fibre on slice 1, we move -rotate and scale the fibre until it matches with the one in slice 2. In this way, we can define all the fibres at any interstage slice (Theofilogiannakos et al 2008). Finally, the two 3D models, each one derived by the respective anatomical (MRI) and histological slices, can be easily combined into one single 3D tetrahedral mesh.…”

Section: Fibrecadmentioning

confidence: 99%

A semi-automated approach towards generating three-dimensional mesh of the heart using a hybrid MRI/histology database

Theofilogiannakos

Danias

et al. 2011

Computer Methods in Biomechanics and Biomedical Engineering

Self Cite

View full text Add to dashboard Cite

Both the forward and inverse problems of electrocardiography rely on the precise modelling of the anatomic and electrical properties of the thoracic tissues. This, in turn, requires good knowledge of the electrical anisotropy as well as conductivity inhomogeneity of the heart, lungs and the rest of the thorax. Cardiac electrical anisotropy is related to its microstructure (fibre length, density and orientation). We hereby present detailed three-dimensional (3D) meshes of the thorax and heart, using image data from contiguous 2D magnetic resonance (MR) imaging slices as well as a realistic 3D cardiac fibre orientation model that derives its data from high-resolution ex vivo human heart MR images and from histology specimens of heart tissue. Using specific software, we integrated the 3D thorax and heart meshes in one that addresses the related modelling requirements for the solution of the forward and inverse problems of electrocardiography.

show abstract

“…5 Early efforts were made to directly measure the fiber orientations from histology slices of ex vivo hearts. 6,7 Manual operation and significant time were required for the process. Furthermore, the accuracy could not be guaranteed because of tissue deformations.…”

Section: Introductionmentioning

confidence: 99%

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

Qin

Fei

2015

Med. Phys.

View full text Add to dashboard Cite

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.

show abstract

A fiber orientation model of the human heart using classical histological methods, magnetic resonance imaging and interpolation techniques

Cited by 4 publications

References 8 publications

Extracting cardiac myofiber orientations from high frequency ultrasound images

Extracting cardiac myofiber orientations from high frequency ultrasound images

A semi-automated approach towards generating three-dimensional mesh of the heart using a hybrid MRI/histology database

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

Contact Info

Product

Resources

About