Detecting stiff masses using strain‐encoded (SENC) imaging

Osman, Nael F.

doi:10.1002/mrm.10376

Cited by 35 publications

(27 citation statements)

References 17 publications

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“…Manual palpation can be thought of as a static elasticity assessment technique. Static compressions are widely employed for elasticity imaging and the techniques that use static forces include strain-encoding imaging (Osman, 2003), elastography (Ophir, 1991) and stimulated-echo elasticity imaging (Chenevert et al, 1998; Steele et al, 2000). Dynamic excitation techniques induce vibrations, usually in the range of 50 to 500 Hz, and image the propagation of the waves produced by the excitation throughout the tissue.…”

Section: Elasticity Imagingmentioning

confidence: 99%

Magnetic resonance elastography: A review

2010

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Magnetic Resonance Elastography (MRE) is a rapidly developing technology for quantitatively assessing the mechanical properties of tissue. The technology can be considered to be an imaging-based counterpart to palpation, commonly used by physicians to diagnose and characterize diseases. The success of palpation as a diagnostic method is based on the fact that the mechanical properties of tissues are often dramatically affected by the presence of disease processes such as cancer, inflammation, and fibrosis. MRE obtains information about the stiffness of tissue by assessing the propagation of mechanical waves through the tissue with a special magnetic resonance imaging (MRI) technique. The technique essentially involves three steps: generating shear waves in the tissue,acquiring MR images depicting the propagation of the induced shear waves andprocessing the images of the shear waves to generate quantitative maps of tissue stiffness, called elastograms. MRE is already being used clinically for the assessment of patients with chronic liver diseases and is emerging as a safe, reliable and noninvasive alternative to liver biopsy for staging hepatic fibrosis. MRE is also being investigated for application to pathologies of other organs including the brain, breast, blood vessels, heart, kidneys, lungs and skeletal muscle. The purpose of this review article is to introduce this technology to clinical anatomists and to summarize some of the current clinical applications that are being pursued.

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Section: Elasticity Imagingmentioning

confidence: 99%

Magnetic resonance elastography: A review

2010

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“…Four main approaches have been introduced for the assessment of myocardial mechanics including tagging [2-4], displacement encoding with stimulated echoes (DENSE) [5-8], strain encoding (SENC) [9] and tissue phase mapping (TPM) [10-14], which has also been introduced as phase contrast velocity encoded imaging [15,16] of tissue.…”

Section: Introductionmentioning

confidence: 99%

Acceleration of tissue phase mapping by k-t BLAST: a detailed analysis of the influence of k-t-BLAST for the quantification of myocardial motion at 3T

Lutz

Bornstedt

Manzke

et al. 2011

Journal of Cardiovascular Magnetic Resonance

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BackgroundThe assessment of myocardial motion with tissue phase mapping (TPM) provides high spatiotemporal resolution and quantitative motion information in three directions. Today, whole volume coverage of the heart by TPM encoding at high spatial and temporal resolution is limited by long data acquisition times. Therefore, a significant increase in imaging speed without deterioration of the quantitative motion information is required. For this purpose, the k-t BLAST acceleration technique was combined with TPM black-blood functional imaging of the heart. Different k-t factors were evaluated with respect to their impact on the quantitative assessment of cardiac motion.ResultsIt is demonstrated that a k-t BLAST factor of two can be used with a marginal, but statistically significant deterioration of the quantitative motion data. Further increasing the k-t acceleration causes substantial alteration of the peak velocities and the motion pattern, but the temporal behavior of the contraction is well maintained up to an acceleration factor of six.ConclusionsThe application of k-t BLAST for the acceleration of TPM appears feasible. A reduction of the acquisition time of almost 45% could be achieved without substantial loss of quantitative motion information.

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“…A silicone gel soft tissue phantom was developed to represent deformation modes expected in the human upper arm due to external compression (see Figure 1), as such the phantom resembles a cylindrical soft tissue region containing a stiff bonelike core. The gel (SYLGARD 527 A&B Dow Corning, MI, USA) has similar MR [26] and mechanical [17] properties to human soft tissue and has been used in numerous MR imagingbased studies on soft tissue biomechanics [21,24,[27][28][29][30][31][32][33][34]. Embedded in the gel are contrasting spherical polyoxymethylene balls of 3 ± 0.05 mm diameter (The Precision Plastic Ball Co Ltd, Addingham, UK).…”

Section: The Tissue Phantommentioning

confidence: 99%

Evaluation of a Validation Method for MR Imaging-Based Motion Tracking Using Image Simulation

Moerman

Kerskens

Lally

et al. 2009

EURASIP J. Adv. Signal Process.

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Magnetic Resonance (MR) imaging-based motion and deformation tracking techniques combined with finite element (FE) analysis are a powerful method for soft tissue constitutive model parameter identification. However, deriving deformation data from MR images is complex and generally requires validation. In this paper a validation method is presented based on a silicone gel phantom containing contrasting spherical markers. Tracking of these markers provides a direct measure of deformation. Validation of in vivo medical imaging techniques is often challenging due to the lack of appropriate reference data and the validation method may lack an appropriate reference. This paper evaluates a validation method using simulated MR image data. This provided an appropriate reference and allowed different error sources to be studied independently and allowed evaluation of the method for various signal-to-noise ratios (SNRs). The geometric bias error was between 0-5.560 × 10 −3 voxels while the noisy magnitude MR image simulations demonstrated errors under 0.1161 voxels (SNR: 5-35).

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Detecting stiff masses using strain‐encoded (SENC) imaging

Cited by 35 publications

References 17 publications

Magnetic resonance elastography: A review

Magnetic resonance elastography: A review

Acceleration of tissue phase mapping by k-t BLAST: a detailed analysis of the influence of k-t-BLAST for the quantification of myocardial motion at 3T

Evaluation of a Validation Method for MR Imaging-Based Motion Tracking Using Image Simulation

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