Regularly incremented phase encoding – MR fingerprinting (RIPE‐MRF) for enhanced motion artifact suppression in preclinical cartesian MR fingerprinting

Anderson, Christian E.; Wang, Charlie Y.; Gu, Yuning; Darrah, Rebecca J.; Griswold, Mark A.; Yu, Xin; Flask, Chris A.

doi:10.1002/mrm.26865

Cited by 21 publications

(31 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Anderson et al addressed the need for respiratory and pulsatile motion correction in Cartesian MRF. The proposed RIPE‐MRF method linearly incremented the phase‐encoding line in k ‐space to add temporal incoherence to the motion.…”

Section: Current Sequence Challengesmentioning

confidence: 99%

“…The proposed RIPE‐MRF method linearly incremented the phase‐encoding line in k ‐space to add temporal incoherence to the motion. RIPE‐MRF reduced the artifact‐to‐noise ratio without increasing the acquisition time . The authors noted that additional work is needed in regions of high frequency pulsatility and rapid motion …”

Section: Current Sequence Challengesmentioning

confidence: 99%

See 1 more Smart Citation

Magnetic resonance fingerprinting Part 1: Potential uses, current challenges, and recommendations

Poorman

Martin

et al. 2019

Magnetic Resonance Imaging

Self Cite

View full text Add to dashboard Cite

Magnetic resonance fingerprinting (MRF) is a powerful quantitative MRI technique capable of acquiring multiple property maps simultaneously in a short timeframe. The MRF framework has been adapted to a wide variety of clinical applications, but faces challenges in technical development, and to date has only demonstrated repeatability and reproducibility in small studies. In this review, we discuss the current implementations of MRF and their use in a clinical setting. Based on this analysis, we highlight areas of need that must be addressed before MRF can be fully adopted into the clinic and make recommendations to the MRF community on standardization and validation strategies of MRF techniques. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:675–692.

show abstract

Section: Current Sequence Challengesmentioning

confidence: 99%

Section: Current Sequence Challengesmentioning

confidence: 99%

Magnetic resonance fingerprinting Part 1: Potential uses, current challenges, and recommendations

Poorman

Martin

et al. 2019

Magnetic Resonance Imaging

Self Cite

View full text Add to dashboard Cite

show abstract

“…An alternative approach introduced gating in MRF as a form of motion compensation. Another approach that has been proposed to minimize motion artifacts is to modify the sampling order such that motion produces incoherent artifacts …”

Section: Introductionmentioning

confidence: 99%

“…21,22 Some preliminary works have observed sensitivity to motion during the acquisition in MRF. [23][24][25][26][27] Initial approaches for motion compensation/ correction in MRF have also been investigated. In one study, 23 MRF motion correction was achieved by iteratively identifying corrupted time points, estimating motion, and enforcing data consistency.…”

mentioning

confidence: 99%

“…Another approach that has been proposed to minimize motion artifacts is to modify the sampling order such that motion produces incoherent artifacts. 27 Low-rank approaches reconstruct compressed images from all acquired data, as mentioned above. In the presence of motion, these reconstructions may introduce motion artifacts (e.g., ghosting and blurring) in addition to quantitative errors attributed to misregistration between time-point images.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Rigid motion‐corrected magnetic resonance fingerprinting

Cruz

Jaubert

Schneider

et al. 2018

Magnetic Resonance in Med

View full text Add to dashboard Cite

show abstract

Magnetic resonance fingerprinting: from evolution to clinical applications

Hsieh

Svalbe

2020

J of Medical Radiation Sci

View full text Add to dashboard Cite

In 2013, Magnetic Resonance Fingerprinting (MRF) emerged as a method for fast, quantitative Magnetic Resonance Imaging. This paper reviews the current status of MRF up to early 2020 and aims to highlight the advantages MRF can offer medical imaging professionals. By acquiring scan data as pseudorandom samples, MRF elicits a unique signal evolution, or 'fingerprint', from each tissue type. It matches 'randomised' free induction decay acquisitions against precomputed simulated tissue responses to generate a set of quantitative images of T 1 , T 2 and proton density (PD) with co-registered voxels, rather than as traditional relative T 1-and T 2-weighted images. MRF numeric pixel values retain accuracy and reproducibility between 2% and 8%. MRF acquisition is robust to strong undersampling of k-space. Scan sequences have been optimised to suppress sub-sampling artefacts, while artificial intelligence and machine learning techniques have been employed to increase matching speed and precision. MRF promises improved patient comfort with reduced scan times and fewer image artefacts. Quantitative MRF data could be used to define population-wide numeric biomarkers that classify normal versus diseased tissue. Certification of clinical centres for MRF scan repeatability would permit numeric comparison of sequential images for any individual patient and the pooling of multiple patient images across large, cross-site imaging studies. MRF has to date shown promising results in early clinical trials, demonstrating reliable differentiation between malignant and benign prostate conditions, and normal and sclerotic hippocampal tissue. MRF is now undergoing small-scale trials at several sites across the world; moving it closer to routine clinical application.

show abstract

Regularly incremented phase encoding – MR fingerprinting (RIPE‐MRF) for enhanced motion artifact suppression in preclinical cartesian MR fingerprinting

Abstract: These results show that the RIPE-MRF method can provide effective motion artifact suppression with minimal impact on T and T accuracy for in vivo small animal MRI studies. Magn Reson Med 79:2176-2182, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Cited by 21 publications

References 47 publications

Magnetic resonance fingerprinting Part 1: Potential uses, current challenges, and recommendations

Magnetic resonance fingerprinting Part 1: Potential uses, current challenges, and recommendations

Rigid motion‐corrected magnetic resonance fingerprinting

Magnetic resonance fingerprinting: from evolution to clinical applications

Contact Info

Product

Resources

About