Add like
Add dislike
Add to saved papers

A bayesian method for accelerated magnetic resonance elastography of the liver.

PURPOSE: Magnetic resonance elastography is a noninvasive tool for quantifying soft tissue stiffness. Magnetic resonance elastography has been adopted as a clinical method for staging liver fibrosis. However, the application of liver magnetic resonance elastography requires multiple lengthy breath-holds. We propose a new data acquisition and processing method to reduce magnetic resonance elastography scan time.

METHODS: A Bayesian image reconstruction method that uses transform sparsity and magnitude consistency across different phase offsets to recover images from highly undersampled data is proposed. The method is validated using retrospectively down-sampled phantom data and prospectively down-sampled in vivo data (N = 86).

RESULTS: The proposed technique allows accurate quantification of mean liver stiffness up to an acceleration factor of R = 6, enabling acquisition of a slice in 4.3 s. Bland-Altman analysis indicates that the proposed technique (R = 6) has a bias of -0.04 kPa and limits of agreement of -0.36 to + 0.28 kPa when compared with traditional generalized autocalibrating partial parallel acquisition reconstruction (R = 1.4).

CONCLUSION: By exploiting transform sparsity and magnitude consistency, accurate quantification of mean stiffness in the liver can be obtained at an acceleration rate of up to R = 6. This potentially enables the collection of three to four liver slices, as per clinical protocol, within a single breath-hold. Magn Reson Med 80:1178-1188, 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app