Robustness of MR Elastography in the Healthy Brain: Repeatability, Reliability, and Effect of Different Reconstruction Methods
- PMID: 33403750
- DOI: 10.1002/jmri.27475
Robustness of MR Elastography in the Healthy Brain: Repeatability, Reliability, and Effect of Different Reconstruction Methods
Abstract
Background: Changes in brain stiffness can be an important biomarker for neurological disease. Magnetic resonance elastography (MRE) quantifies tissue stiffness, but the results vary between acquisition and reconstruction methods.
Purpose: To measure MRE repeatability and estimate the effect of different reconstruction methods and varying data quality on estimated brain stiffness.
Study type: Prospective.
Subjects: Fifteen healthy subjects.
Field strength/sequence: 3T MRI, gradient-echo elastography sequence with a 50 Hz vibration frequency.
Assessment: Imaging was performed twice in each subject. Images were reconstructed using a curl-based and a finite-element-model (FEM)-based method. Stiffness was measured in the whole brain, in white matter, and in four cortical and four deep gray matter regions. Repeatability coefficients (RC), intraclass correlation coefficients (ICC), and coefficients of variation (CV) were calculated. MRE data quality was quantified by the ratio between shear waves and compressional waves.
Statistical tests: Median values with range are presented. Reconstruction methods were compared using paired Wilcoxon signed-rank tests, and Spearman's rank correlation was calculated between MRE data quality and stiffness. Holm-Bonferroni corrections were employed to adjust for multiple comparisons.
Results: In the whole brain, CV was 4.3% and 3.8% for the curl and the FEM reconstruction, respectively, with 4.0-12.8% for subregions. Whole-brain ICC was 0.60-0.74, ranging from 0.20 to 0.89 in different regions. RC for the whole brain was 0.14 kPa and 0.17 kPa for the curl and FEM methods, respectively. FEM reconstruction resulted in 39% higher stiffness than the curl reconstruction (P < 0.05). MRE data quality, defined as shear-compression wave ratio, was higher in peripheral regions than in central regions of the brain (P < 0.05). No significant correlations were observed between MRE data quality and stiffness estimates.
Data conclusion: MRE of the human brain is a robust technique in terms of repeatability. Caution is warranted when comparing stiffness values obtained with different techniques.
Level of evidence: 1 TECHNICAL EFFICACY STAGE: 1.
Keywords: MR elastography; human brain; reconstruction; repeatability; shear modulus; stiffness.
© 2021 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC. on behalf of International Society for Magnetic Resonance in Medicine.
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References
-
- Murphy MC, Huston J 3rd, Ehman RL. MR elastography of the brain and its application in neurological diseases. Neuroimage 2019;187:176-183.
-
- Bunevicius A, Schregel K, Sinkus R, Golby A, Patz S. Review: MR elastography of brain tumors. Neuroimage Clin 2019;25:102109.
-
- Muthupillai R, Ehman RL. Magnetic resonance elastography. Nat Med 1996;2(5):601-603.
-
- Pepin KM, Ehman RL, McGee KP. Magnetic resonance elastography (MRE) in cancer: Technique, analysis, and applications. Prog Nucl Magn Reson Spectrosc 2015;90-91:32-48.
-
- Venkatesh SK, Yin M, Ehman RL. Magnetic resonance elastography of liver: Technique, analysis, and clinical applications. J Magn Reson Imaging 2013;37(3):544-555.
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