Magnetic Resonance Elastography of the Breast

Xydeas, T.; Siegmann, K. C.; Sinkus, Ralph; Krainick-Strobel, U.; Miller, Stephan; Claussen, Claus D.

doi:10.1097/01.rli.0000166940.72971.4a

Cited by 70 publications

(31 citation statements)

References 29 publications

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“…In a similar study involving 15 healthy volunteers, 15 patients with malignant tumors, and 5 patients with benign lesions, malignant lesions were found to be significantly stiffer than benign lesions, normal breast parenchyma, and adipose tissue (119). Early work looking at the correlation between MRE and CE-MRI in a study involving 20 patients showed good distinction between benign and malignant lesion stiffness which agreed with the morphologic and dynamic data (120). A more recent study involving 68 patients with 39 malignant lesions and 29 benign lesions, and using a more sophisticated elastographic inversion algorithm, reported that while CE-MRI alone had a sensitivity of nearly 100%, but a specificity of 40% and an AUC of 0.88, the elastography results alone provided an AUC of about 0.91, and the combination of CE-MRI and MRE resulted in an AUC of around 0.96 (28).…”

Section: Breast Mresupporting

confidence: 57%

Review of MR elastography applications and recent developments

Glaser

Manduca

Ehman

2012

Magnetic Resonance Imaging

212

156

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The technique of MR elastography (MRE) has emerged as a useful modality for quantitatively imaging the mechanical properties of soft tissues in vivo. Recently, MRE has been introduced as a clinical tool for evaluating chronic liver disease, but many other potential applications are being explored. These applications include measuring tissue changes associated with diseases of the liver, breast, brain, heart, and skeletal muscle including both focal lesions (e.g., hepatic, breast, and brain tumors) and diffuse diseases (e.g., fibrosis and multiple sclerosis). The purpose of this review article is to summarize some of the recent developments of MRE and to highlight some emerging applications.

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Section: Breast Mresupporting

confidence: 57%

Review of MR elastography applications and recent developments

Glaser

Manduca

Ehman

2012

Magnetic Resonance Imaging

212

156

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“…Figure 6 demonstrates that the conventional approach to image reconstruction (NP) employed in breast elastography (Van Houten et al , 2003; Xydeas et al , 2005; Oberai et al , 2009) is not viable in vascular applications—which implies that the ill-posed nature of the inverse elasticity problem is a bigger issue in vascular elastography, perhaps because the incompressibility of soft tissues presents additional problems. More specifically, in vascular elastography the displacement is determined almost entirely by incompressibility and the displacement of the inner vessel wall, and is nearly independent of other mechanical parameters; this lack of sensitivity makes the inverse problem more challenging.…”

Section: Discussionmentioning

confidence: 99%

Investigating the impact of spatial priors on the performance of model-based IVUS elastography

Richards

Doyley

2011

Phys. Med. Biol.

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This paper describes methods that provide pre-requisite information for computing circumferential stress in modulus elastograms recovered from vascular tissue—information that could help cardiologists detect life-threatening plaques and predict their propensity to rupture. The modulus recovery process is an ill-posed problem; therefore additional information is needed to provide useful elastograms. In this work, prior geometrical information was used to impose hard or soft constraints on the reconstruction process. We conducted simulation and phantom studies to evaluate and compare modulus elastograms computed with soft and hard constraints versus those computed without any prior information. The results revealed that (1) the contrast-to-noise ratio of modulus elastograms achieved using the soft prior and hard prior reconstruction methods exceeded those computed without any prior information; (2) the soft prior and hard prior reconstruction methods could tolerate up to 8 % measurement noise; and (3) the performance of soft and hard prior modulus elastogram degraded when incomplete spatial priors were employed. This work demonstrates that including spatial priors in the reconstruction process should improve the performance of model-based elastography, and the soft prior approach should enhance the robustness of the reconstruction process to errors in the geometrical information.

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“…The large attenuation effects in MRE can have a significant impact in some areas ([1]), and visualizing viscosity information has been tried for MRE ([21], [24], [25]). Fig.…”

Section: Discussionmentioning

confidence: 99%

Shear Modulus Decomposition Algorithm in Magnetic Resonance Elastography

Kwon

Park

Nam

et al. 2009

IEEE Trans. Med. Imaging

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Magnetic resonance elastography (MRE) is an imaging modality capable of visualizing the elastic properties of an object using MRI measurements of transverse acoustic strain waves induced in the object by a harmonically oscillating mechanical vibration. Various algorithms have been designed to determine the mechanical properties of the object under the assumptions of linear elasticity, isotropic and local homogeneity. One of the challenging problems in MRE is to reduce the noise effects and to maintain contrast in the reconstructed shear modulus images. In this paper, we propose a new algorithm designed to reduce the degree of noise amplification in the reconstructed shear modulus images without the assumption of local homogeneity. Investigating the relation between the measured displacement data and the stress wave vector, the proposed algorithm uses an iterative reconstruction formula based on a decomposition of the stress wave vector. Numerical simulation experiments and real experiments with agarose gel phantoms and human liver data demonstrate that the proposed algorithm is more robust to noise compared to standard inversion algorithms and stably determines the shear modulus.

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Magnetic Resonance Elastography of the Breast

Abstract: A good separation exists between benign and malignant lesions in elasticity, corresponding with specific signal intensity and morphologic data. Further clinical studies with a larger number of patients are needed for extended validation.

Cited by 70 publications

References 29 publications

Review of MR elastography applications and recent developments

Review of MR elastography applications and recent developments

Investigating the impact of spatial priors on the performance of model-based IVUS elastography

Shear Modulus Decomposition Algorithm in Magnetic Resonance Elastography

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