单位:[1]Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ[2]Department of Bioengineering, Stanford University, Stanford, CA[3]Department of Biomedical Engineering, University of Arizona, Tucson, AZ[4]Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China医技科室影像中心放射科首都医科大学附属北京友谊医院[5]Department of Radiology, Stanford University, Stanford, CA[6]Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY
BACKGROUND AND PURPOSE: The brain's stiffness measurements from magnetic resonance elastography (MRE) strongly depend on actuation frequencies, which makes cross-study comparisons challenging. We performed a preliminary study to acquire optimal sets of actuation frequencies to accurately obtain rheological parameters for the whole brain (WB), white matter (WM), and gray matter (GM). METHODS: Six healthy volunteers aged between 26 and 72 years old went through MRE with a modified single-shot spin-echo echo planar imaging pulse sequence embedded with motion encoding gradients on a 3T scanner. Frequency-independent brain material properties and best-fit material model were determined from the frequency-dependent brain tissue response data (20 -80 Hz), by comparing four different linear viscoelastic material models (Maxwell, Kelvin-Voigt, Springpot, and Zener). During the material fitting, spatial averaging of complex shear moduli (G*) obtained under single actuation frequency was performed, and then rheological parameters were acquired. Since clinical scan time is limited, a combination of three actuation frequencies that would provide the most accurate approximation and lowest fitting error was determined for WB, WM, and GM by optimizing for the lowest Bayesian information criterion (BIC). RESULTS: BIC scores for the Zener and Springpot models showed these models approximate the multifrequency response of the tissue best. The best-fit frequency combinations for the reference Zener and Springpot models were identified to be 30-60-70 and 30-40-80 Hz, respectively, for the WB. CONCLUSIONS: Optimal sets of actuation frequencies to accurately obtain rheological parameters for WB, WM, and GM were determined from shear moduli measurements obtained via 3-dimensional direct inversion. We believe that our study is a first-step in developing a region-specific multifrequency MRE protocol for the human brain.
基金:
Stanford Child Health Research Institute; Thrasher Research Foundation; NIHUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [EB001981, 1R21NS111415-01]; NSF DCSD [1826270]; General ElectricGeneral Electric
语种:
外文
被引次数:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2018]版:
大类|4 区医学
小类|4 区临床神经病学4 区神经成像4 区核医学
最新[2025]版:
大类|3 区医学
小类|3 区核医学4 区临床神经病学4 区神经成像
JCR分区:
出版当年[2017]版:
Q3CLINICAL NEUROLOGYQ3RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGINGQ3NEUROIMAGING
最新[2023]版:
Q2RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGINGQ3CLINICAL NEUROLOGYQ3NEUROIMAGING
第一作者单位:[1]Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ[6]Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY[*1]Department of Mechanical Engineering, Stevens Institute of Technology, 1 Castle Point Terrace, McLean Hall, Room 525, Hoboken, NJ 07030
通讯作者:
通讯机构:[1]Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ[6]Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY[*1]Department of Mechanical Engineering, Stevens Institute of Technology, 1 Castle Point Terrace, McLean Hall, Room 525, Hoboken, NJ 07030
推荐引用方式(GB/T 7714):
Kurt Mehmet,Wu Lyndia,Laksari Kaveh,et al.Optimization of a Multifrequency Magnetic Resonance Elastography Protocol for the Human Brain[J].JOURNAL of NEUROIMAGING.2019,29(4):440-446.doi:10.1111/jon.12619.
APA:
Kurt, Mehmet,Wu, Lyndia,Laksari, Kaveh,Ozkaya, Efe,Suar, Zeynep M....&Wintermark, Max.(2019).Optimization of a Multifrequency Magnetic Resonance Elastography Protocol for the Human Brain.JOURNAL of NEUROIMAGING,29,(4)
MLA:
Kurt, Mehmet,et al."Optimization of a Multifrequency Magnetic Resonance Elastography Protocol for the Human Brain".JOURNAL of NEUROIMAGING 29..4(2019):440-446