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Pagé G, Bied M, Garteiser P, Van Beers B, Etaix N, Fraschini C, Bel-Brunon A, Gennisson JL. Comparison of ultrasound elastography, magnetic resonance elastography and finite element model to quantify nonlinear shear modulus. Phys Med Biol 2023; 68:205003. [PMID: 37703895 DOI: 10.1088/1361-6560/acf98c] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 09/13/2023] [Indexed: 09/15/2023]
Abstract
Objective. The aim of this study is to validate the estimation of the nonlinear shear modulus (A) from the acoustoelasticity theory with two experimental methods, ultrasound (US) elastography and magnetic resonance elastography (MRE), and a finite element method.Approach. Experiments were performed on agar (2%)-gelatin (8%) phantom considered as homogeneous, elastic and isotropic. Two specific setups were built to ensure a uniaxial stress step by step on the phantom, one for US and a nonmagnetic version for MRE. The stress was controlled identically in both imaging techniques, with a water tank placed on the top of the phantom and filled with increasing masses of water during the experiment. In US, the supersonic shear wave elastography was implemented on an ultrafast US device, driving a 6 MHz linear array to measure shear wave speed. In MRE, a gradient-echo sequence was used in which the three spatial directions of a 40 Hz continuous wave displacement generated with an external driver were encoded successively. Numerically, a finite element method was developed to simulate the propagation of the shear wave in a uniaxially stressed soft medium.Main results. Similar shear moduli were estimated at zero stress using experimental methods,μ0US= 12.3 ± 0.3 kPa andμ0MRE= 11.5 ± 0.7 kPa. Numerical simulations were set with a shear modulus of 12 kPa and the resulting nonlinear shear modulus was found to be -58.1 ± 0.7 kPa. A very good agreement between the finite element model and the experimental models (AUS= -58.9 ± 9.9 kPa andAMRE= -52.8 ± 6.5 kPa) was obtained.Significance. These results show the validity of such nonlinear shear modulus measurement quantification in shear wave elastography. This work paves the way to develop nonlinear elastography technique to get a new biomarker for medical diagnosis.
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Affiliation(s)
- Gwenaël Pagé
- BioMaps, Laboratoire d'Imagerie Biomédicale Multimodale, Université Paris-Saclay, CEA, CNRS UMR 9011, Inserm UMR 1281, Service hospitalier Frédéric Joliot, F-91401 Orsay, France
| | - Marion Bied
- BioMaps, Laboratoire d'Imagerie Biomédicale Multimodale, Université Paris-Saclay, CEA, CNRS UMR 9011, Inserm UMR 1281, Service hospitalier Frédéric Joliot, F-91401 Orsay, France
| | - Philippe Garteiser
- Laboratory of imaging biomarkers, Center for Research on inflammation, UMR 1149, Université Paris-Cité, Inserm, F-75018 Paris, France
| | - Bernard Van Beers
- Laboratory of imaging biomarkers, Center for Research on inflammation, UMR 1149, Université Paris-Cité, Inserm, F-75018 Paris, France
- Department of Radiology, Beaujon university hospital Paris Nord, AP-HP, F-92110 Clichy, France
| | - Nicolas Etaix
- Hologic - Supersonic Imagine, F-13290 Aix en Provence, France
| | | | - Aline Bel-Brunon
- Univ Lyon, INSA Lyon, CNRS, LaMCoS, UMR5259, F-69621 Villeurbanne, France
| | - Jean-Luc Gennisson
- BioMaps, Laboratoire d'Imagerie Biomédicale Multimodale, Université Paris-Saclay, CEA, CNRS UMR 9011, Inserm UMR 1281, Service hospitalier Frédéric Joliot, F-91401 Orsay, France
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Ma S, Wang R, Qiu S, Li R, Yue Q, Sun Q, Chen L, Yan F, Yang GZ, Feng Y. MR Elastography With Optimization-Based Phase Unwrapping and Traveling Wave Expansion-Based Neural Network (TWENN). IEEE TRANSACTIONS ON MEDICAL IMAGING 2023; 42:2631-2642. [PMID: 37030683 DOI: 10.1109/tmi.2023.3261346] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Magnetic Resonance Elastography (MRE) can characterize biomechanical properties of soft tissue for disease diagnosis and treatment planning. However, complicated wavefields acquired from MRE coupled with noise pose challenges for accurate displacement extraction and modulus estimation. Using optimization-based displacement extraction and Traveling Wave Expansion-based Neural Network (TWENN) modulus estimation, we propose a new pipeline for processing MRE images. An objective function with Dual Data Consistency (Dual-DC) has been used to ensure accurate phase unwrapping and displacement extraction. For the estimation of complex wavenumbers, a complex-valued neural network with displacement covariance as an input has been developed. A model of traveling wave expansion is used to generate training datasets for the network with varying levels of noise. The complex shear modulus map is obtained through fusion of multifrequency and multidirectional data. Validation using brain and liver simulation images demonstrates the practical value of the proposed pipeline, which can estimate the biomechanical properties with minimal root-mean-square errors when compared to state-of-the-art methods. Applications of the proposed method for processing MRE images of phantom, brain, and liver reveal clear anatomical features, robustness to noise, and good generalizability of the pipeline.
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Mohammed S, Kozlowski P, Salcudean S. Phase-regularized and displacement-regularized compressed sensing for fast magnetic resonance elastography. NMR IN BIOMEDICINE 2023; 36:e4899. [PMID: 36628624 DOI: 10.1002/nbm.4899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 12/12/2022] [Accepted: 01/01/2023] [Indexed: 06/15/2023]
Abstract
Liver magnetic resonance elastography (MRE) is a noninvasive stiffness measurement technique that captures the tissue displacement in the phase of the signal. To limit the scanning time to a single breath-hold, liver MRE usually involves advanced readout techniques such as simultaneous multislice (SMS) or multishot methods. Furthermore, all these readout techniques require additional in-plane acceleration using either parallel imaging capabilities, such as sensitivity encoding (SENSE), or k -space undersampling, such as compressed sensing (CS). However, these methods apply a single regularization function on the complex image. This study aims to design and evaluate methods that use separate regularization on the magnitude and phase of MRE to exploit their distinct spatiotemporal characteristics. Specifically, we introduce two compressed sensing methods. The first method, termed phase-regularized compressed sensing (PRCS), applies a two-dimensional total variation (TV) prior to the magnitude and two-dimensional wavelet regularization to the phase. The second method, termed displacement-regularized compressed sensing (DRCS), exploits the spatiotemporal redundancy using 3D total variation on the magnitude. Additionally, DRCS includes a displacement fitting function to apply wavelet regularization to the displacement phasor. Both DRCS and PRCS were evaluated with different levels of compression factors in three datasets: an in silico abdomen dataset, an in vitro tissue-mimicking phantom, and an in vivo liver dataset. The reconstructed images were compared with the full sampled reconstruction, zero-filling reconstruction, wavelet-regularized compressed sensing, and a low rank plus sparse reconstruction. The metrics used for quantitative evaluation were the structural similarity index (SSIM) of magnitude (M-SSIM), displacement (D-SSIM), and shear modulus (S-SSIM), and mean shear modulus. Results from highly undersampled in silico and in vitro datasets demonstrate that the DRCS method provides higher reconstruction quality than the conventional compressed sensing method for a wide range of stiffness values. Notably, DRCS provides 24% and 22% increase in D-SSIM compared with CS for the in silico and in vitro datasets, respectively. Comparison with liver stiffness measured from full sampled data and highly undersampled data (CR=4) demonstrates that the DRCS method provided the strongest correlation ( R 2 =0.95), second-lowest mean bias (-0.18 kPa, lowest for CS with -0.16 kPa), and lowest coefficient of variation (CV=3.6%). Our results demonstrate the potential of using DRCS to improve the reconstruction quality of accelerated MRE.
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Affiliation(s)
- Shahed Mohammed
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada
| | - Piotr Kozlowski
- Department of Radiology, University of British Columbia, Vancouver, Canada
| | - Septimiu Salcudean
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada
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Yushchenko M, Sarracanie M, Salameh N. Fast acquisition of propagating waves in humans with low-field MRI: Toward accessible MR elastography. SCIENCE ADVANCES 2022; 8:eabo5739. [PMID: 36083901 PMCID: PMC9462689 DOI: 10.1126/sciadv.abo5739] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 07/22/2022] [Indexed: 05/29/2023]
Abstract
Most commonly used at clinical magnetic fields (1.5 to 3 T), magnetic resonance elastography (MRE) captures mechanical wave propagation to reconstruct the mechanical properties of soft tissue with MRI. However, in terms of noninvasively assessing disease progression in a broad range of organs (e.g., liver, breast, skeletal muscle, and brain), its accessibility is limited and its robustness is challenged when magnetic susceptibility differences are encountered. Low-field MRE offers an opportunity to overcome these issues, and yet it has never been demonstrated in vivo in humans with magnetic fields <1.5 T mainly because of the long acquisition times required to achieve a sufficient signal-to-noise ratio. Here, we describe a method to accelerate 3D motion-sensitized MR scans at 0.1 T using only 10% k-space sampling combined with a high-performance detector and an efficient encoding acquisition strategy. Its application is demonstrated in vivo in the human forearm for a single motion-encoding direction in less than 1 min.
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The effects of geometry on stiffness measurements in high-field magnetic resonance elastography: A study on rodent cardiac phantoms. J Mech Behav Biomed Mater 2022; 133:105302. [DOI: 10.1016/j.jmbbm.2022.105302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 05/06/2022] [Accepted: 05/27/2022] [Indexed: 11/18/2022]
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Du Q, Bel-Brunon A, Lambert SA, Hamila N. Numerical simulation of wave propagation through interfaces using the extended finite element method for magnetic resonance elastography. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2022; 151:3481. [PMID: 35649898 PMCID: PMC9381142 DOI: 10.1121/10.0011392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Magnetic resonance elastography (MRE) is an elasticity imaging technique for quantitatively assessing the stiffness of human tissues. In MRE, finite element method (FEM) is widely used for modeling wave propagation and stiffness reconstruction. However, in front of inclusions with complex interfaces, FEM can become burdensome in terms of the model partition and computationally expensive. In this work, we implement a formulation of FEM, known as the eXtended finite element method (XFEM), which is a method used for modeling discontinuity like crack and heterogeneity. Using a level-set method, it makes the interface independent of the mesh, thus relieving the meshing efforts. We investigate this method in two studies: wave propagation across an oblique linear interface and stiffness reconstruction of a random-shape inclusion. In the first study, numerical results by XFEM and FEM models revealing the wave conversion rules at linear interface are presented and successfully compared to the theoretical predictions. The second study, investigated in a pseudo-practical application, demonstrates further the applicability of XFEM in MRE and the convenience, accuracy, and speed of XFEM with respect to FEM. XFEM can be regarded as a promising alternative to FEM for inclusion modeling in MRE.
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Affiliation(s)
- Quanshangze Du
- Univ Lyon, INSA Lyon, CNRS, LaMCoS, UMR5259, 69621 Villeurbanne, France
| | - Aline Bel-Brunon
- Univ Lyon, INSA Lyon, CNRS, LaMCoS, UMR5259, 69621 Villeurbanne, France
- Electronic mail:
| | - Simon Auguste Lambert
- Université de Lyon, INSA Lyon, Université Claude Bernard Lyon 1, Ecole Centrale de Lyon, CNRS, Ampère UMR5005, Villeurbanne, France
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Triolo E, Khegai O, Ozkaya E, Rossi N, Alipour A, Fleysher L, Balchandani P, Kurt M. Design, Construction, and Implementation of a Magnetic Resonance Elastography Actuator for Research Purposes. Curr Protoc 2022; 2:e379. [PMID: 35286023 PMCID: PMC9517172 DOI: 10.1002/cpz1.379] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Magnetic resonance elastography (MRE) is a technique for determining the mechanical response of soft materials using applied harmonic deformation of the material and a motion-sensitive magnetic resonance imaging sequence. This technique can elucidate significant information about the health and development of human tissue such as liver and brain, and has been used on phantom models (e.g., agar, silicone) to determine their suitability for use as a mechanical surrogate for human tissues in experimental models. The applied harmonic deformation used in MRE is generated by an actuator, transmitted in bursts of a specified duration, and synchronized with the magnetic resonance signal excitation. These actuators are most often a pneumatic design (common for human tissues or phantoms) or a piezoelectric design (common for small animal tissues or phantoms). Here, we describe how to design and assemble both a pneumatic and a piezoelectric MRE actuator for research purposes. For each of these actuator types, we discuss displacement requirements, end-effector options and challenges, electronics and electronic-driving requirements and considerations, and full MRE implementation. We also discuss how to choose the actuator type, size, and power based on the intended material and use. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Design, construction, and implementation of a convertible pneumatic MRE actuator for use with tissues and phantom models Basic Protocol 2: Design, construction, and implementation of a piezoelectric MRE actuator for localized excitation in phantom models.
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Affiliation(s)
- E.R. Triolo
- University of Washington, Dept. of Mechanical Engineering (3900 E Stevens Way NE Seattle, WA 98195)
| | - O. Khegai
- Icahn School of Medicine at Mount Sinai, BioMedical Engineering and Imaging Institute (1470 Madison Ave, New York City, NY 10029)
| | - E. Ozkaya
- Icahn School of Medicine at Mount Sinai, BioMedical Engineering and Imaging Institute (1470 Madison Ave, New York City, NY 10029)
| | - N. Rossi
- Stevens Institute of Technology, Dept. of Mechanical Engineering (1 Castle Point Terrace, Hoboken, NJ 07030)
| | - A. Alipour
- Icahn School of Medicine at Mount Sinai, BioMedical Engineering and Imaging Institute (1470 Madison Ave, New York City, NY 10029)
| | - L. Fleysher
- Icahn School of Medicine at Mount Sinai, BioMedical Engineering and Imaging Institute (1470 Madison Ave, New York City, NY 10029)
| | - P. Balchandani
- Icahn School of Medicine at Mount Sinai, BioMedical Engineering and Imaging Institute (1470 Madison Ave, New York City, NY 10029)
| | - M. Kurt
- University of Washington, Dept. of Mechanical Engineering (3900 E Stevens Way NE Seattle, WA 98195)
- Icahn School of Medicine at Mount Sinai, BioMedical Engineering and Imaging Institute (1470 Madison Ave, New York City, NY 10029)
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McGrath DM, Bradley CR, Francis ST. In silicoevaluation and optimisation of magnetic resonance elastography of the liver. Phys Med Biol 2021; 66. [PMID: 34678798 DOI: 10.1088/1361-6560/ac3263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 10/22/2021] [Indexed: 11/11/2022]
Abstract
Objective.Magnetic resonance elastography (MRE) is widely adopted as a biomarker of liver fibrosis. However,in vivoMRE accuracy is difficult to assess.Approach.Finite element model (FEM) simulation was employed to evaluate liver MRE accuracy and inform methodological optimisation. MRE data was simulated in a 3D FEM of the human torso including the liver, and compared with spin-echo echo-planar imaging MRE acquisitions. The simulated MRE results were compared with the ground truth magnitude of the complex shear modulus (∣G*∣) for varying: (1) ground truth liver ∣G*∣; (2) simulated imaging resolution; (3) added noise; (4) data smoothing. Motion and strain-based signal-to-noise (SNR) metrics were evaluated on the simulated data as a means to select higher-quality voxels for preparation of acquired MRE summary statistics of ∣G*∣.Main results.The simulated MRE accuracy for a given ground truth ∣G*∣ was found to be a function of imaging resolution, motion-SNR and smoothing. At typical imaging resolutions, it was found that due to under-sampling of the MRE wave-field, combined with motion-related noise, the reconstructed simulated ∣G*∣ could contain errors on the scale of the difference between liver fibrosis stages, e.g. 54% error for ground truth ∣G*∣ = 1 kPa. Optimum imaging resolutions were identified for given ground truth ∣G*∣ and motion-SNR levels.Significance.This study provides important knowledge on the accuracy and optimisation of liver MRE. For example, for motion-SNR ≤ 5, to distinguish between liver ∣G*∣ of 2 and 3 kPa (i.e. early-stage liver fibrosis) it was predicted that the optimum isotropic voxel size is 4-6 mm.
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Affiliation(s)
- Deirdre M McGrath
- Sir Peter Mansfield Imaging Centre, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.,NIHR Nottingham Biomedical Research Centre, Radiological Sciences, Division of Clinical Neuroscience, Queens Medical Centre, Nottingham, NG7 2UH, United Kingdom
| | - Christopher R Bradley
- Sir Peter Mansfield Imaging Centre, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.,NIHR Nottingham Biomedical Research Centre, Radiological Sciences, Division of Clinical Neuroscience, Queens Medical Centre, Nottingham, NG7 2UH, United Kingdom
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.,NIHR Nottingham Biomedical Research Centre, Radiological Sciences, Division of Clinical Neuroscience, Queens Medical Centre, Nottingham, NG7 2UH, United Kingdom
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Practical and clinical applications of pancreatic magnetic resonance elastography: a systematic review. Abdom Radiol (NY) 2021; 46:4744-4764. [PMID: 34076721 DOI: 10.1007/s00261-021-03143-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 05/20/2021] [Accepted: 05/22/2021] [Indexed: 12/13/2022]
Abstract
Magnetic resonance elastography (MRE) is a non-invasive technique suitable for assessing mechanical properties of tissues, i.e., stiffness. MRE of the pancreas is relatively new, but recently an increasing number of studies have successfully assessed pancreas diseases with MRE aiming to differentiate healthy from pathological pancreatic tissue with or without fibrosis. This review will systematically describe the practical and clinical applications of pancreatic MRE. We conducted a systematic literature search with a pre-specified search strategy using PubMed and Embase according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. English peer-reviewed articles applying MRE of the pancreas were included. Two independent reviewers assessed the studies. The literature search yielded 14 studies. The pancreatic stiffness for healthy volunteers ranged from 1.11. to 1.21 kPa at a driver frequency of 40 Hz. In benign tumors, the stiffness values were slightly higher or sometimes even lower (range 0.78 to 2.00 kPa), compared to the healthy pancreas parenchyma whereas, in malignant tumors, the stiffness values tended to be higher (1.42 to 6.06 kPa). The pancreatic stiffness was increased in both acute (median: 1.99 kPa) and chronic pancreatitis (> 1.50 kPa). MRE is a promising technique for detecting and quantifying pancreatic stiffness. It is related to fibrosis and seems to be useful in assessing treatment response and clinical follow-up of pancreatic diseases. However, most of the described practical settings were characterized by a lack of uniformity and inconsistency in reporting standards across studies. Harmonization between centers is necessary to achieve more consensus and optimization of pancreatic MRE protocols.
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Khodayi-Mehr R, Urban MW, Zavlanos MM, Aquino W. Plane wave elastography: a frequency-domain ultrasound shear wave elastography approach. Phys Med Biol 2021; 66. [PMID: 34140433 DOI: 10.1088/1361-6560/ac01b8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 05/14/2021] [Indexed: 12/19/2022]
Abstract
In this paper, we propose plane wave elastography (PWE), a novel ultrasound shear wave elastography (SWE) approach. Currently, commercial methods for SWE rely on directional filtering based on the prior knowledge of the wave propagation direction, to remove complicated wave patterns formed due to reflection and refraction. The result is a set of decomposed directional waves that are separately analyzed to construct shear modulus fields that are then combined through compounding. Instead, PWE relies on a rigorous representation of the wave propagation using the frequency-domain scalar wave equation to automatically select appropriate propagation directions and simultaneously reconstruct shear modulus fields. Specifically, assuming a homogeneous, isotropic, incompressible, linear-elastic medium, we represent the solution of the wave equation using a linear combination of plane waves propagating in arbitrary directions. Given this closed-form solution, we formulate the SWE problem as a nonlinear least-squares optimization problem which can be solved very efficiently. Through numerous phantom studies, we show that PWE can handle complicated waveforms without prior filtering and is competitive with state-of-the-art that requires prior filtering based on the knowledge of propagation directions.
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Affiliation(s)
- Reza Khodayi-Mehr
- Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, United States of America
| | - Matthew W Urban
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, United States of America
| | - Michael M Zavlanos
- Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, United States of America
| | - Wilkins Aquino
- Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, United States of America
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Zeng Q, Honarvar M, Schneider C, Mohammad SK, Lobo J, Pang EHT, Lau KT, Hu C, Jago J, Erb SR, Rohling R, Salcudean SE. Three-Dimensional Multi-Frequency Shear Wave Absolute Vibro-Elastography (3D S-WAVE) With a Matrix Array Transducer: Implementation and Preliminary In Vivo Study of the Liver. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:648-660. [PMID: 33108283 DOI: 10.1109/tmi.2020.3034065] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Magnetic resonance elastography (MRE) is commonly regarded as the imaging-based gold-standard for liver fibrosis staging, comparable to biopsy. While ultrasound-based elastography methods for liver fibrosis staging have been developed, they are confined to a 1D or a 2D region of interest and to a limited depth. 3D Shear Wave Absolute Vibro-Elastography (S-WAVE) is a steady-state, external excitation, volumetric elastography technique that is similar to MRE, but has the additional advantage of multi-frequency excitation. We present a novel ultrasound matrix array implementation of S-WAVE that takes advantage of 3D imaging. We use a matrix array transducer to sample axial multi-frequency steady-state tissue motion over a volume, using a Color Power Angiography sequence. Tissue motion with the frequency components {40,50,60} and {45,55,65} Hz are acquired over a (90° lateral) × (40° elevational) × (16 cm depth) sector with an acquisition time of 12 seconds. We compute the elasticity map in 3D using local spatial frequency estimation. We characterize this new approach in tissue phantoms against measurements obtained with transient elastography and MRE. Six healthy volunteers and eight patients with chronic liver disease were imaged. Their MRE and S-WAVE volumes were aligned using T1 to B-mode registration for direct comparison in common regions of interest. S-WAVE and MRE results are correlated with R2 = 0.92, while MRE and TE results are correlated with R2 = 0.71. Our findings show that S-WAVE with matrix array has the potential to deliver a similar assessment of liver fibrosis as MRE in a more accessible, inexpensive way, to a broader set of patients.
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Hu L, Shan X. Enhanced complex local frequency elastography method for tumor viscoelastic shear modulus reconstruction. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2020; 195:105605. [PMID: 32580075 DOI: 10.1016/j.cmpb.2020.105605] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2020] [Accepted: 06/07/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND AND OBJECTIVES The Mayo Clinic provides a magnetic resonance (MR) elastography software named MRE Wave, which uses the conventional local frequency elastography (LFE) method. However, MRE Wave is unable to supply complex viscoelasticity maps for elastography. We sought to improve the local frequency estimation algorithm used in LFE, which we refer to as the Enhanced Complex Local Frequency Elastography (EC-LFE) algorithm. METHODS The proposed algorithm uses wave equations under the hypotheses of being linear, isotropic, and locally homogeneous. Two 2D simulation models were used to investigate the accuracy and sensitivity of the EC-LFE algorithm for detecting small tumors. The corresponding statistical parameters were the relative root mean square (RMS) error and contrast-to-noise ratio (CNR). EC-LFE was investigated with two different parameter sets, one with an optimally chosen parameter ξ (EC-LFE Adj, for short) and the other with ξ = 0 (EC-LFE0). We compared the MRE Wave and the EC-LFE using series signal-to-noise (SNR) wave data. RESULTS The elasticity RMS error of the MRE Wave software was about 1%, and that of the EC-LFE0 and EC-LFE Adj were about 0.2%. The elasticity standard deviation of the MRE Wave software was about 3% of the mean value, and those of the EC-LFE0 and EC-LFE Adj were about 1% of the mean value. The elasticity CNR value of EC-LFE0 reached 1.93 times that of the MRE Wave in the region of small tumors (less than 10-point sampling). The viscosity RMS errors of the EC-LFE0 could be less than 5%. CONCLUSION Compared to conventional methods, the EC-LFE was more accurate and sensitive for small tumor detection and exhibited higher noise immunity. The improved algorithm output more parameters and outperformed than the MRE Wave, thereby rendering them more suitable for clinical applications.
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Affiliation(s)
- Liangliang Hu
- School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology, Hefei, Anhui, China.
| | - Xiang Shan
- School of Medical Imaging, Xuzhou Medical University, Xuzhou, Jiangsu, China
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Hu L. Requirements for accurate estimation of shear modulus by magnetic resonance elastography: A computational comparative study. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2020; 192:105437. [PMID: 32182441 DOI: 10.1016/j.cmpb.2020.105437] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 03/01/2020] [Accepted: 03/04/2020] [Indexed: 06/10/2023]
Abstract
BACKGROUND Magnetic resonance (MR) elastography is a non-destructive method of measuring biological tissue and is conducive to the early detection of tumors. Researchers usually set different assumptions according to different research objects, then establish and solve wave equations to estimate the shear modulus. Establishing a more reasonable model for a measured object estimates a more accurate shear modulus. Different assumptions of the mathematical model, and the method used to solve the wave equation causes deviation of the estimation. OBJECTIVE This study focused on shear modulus deviations caused by differences in calculation methods. The author demonstrated a method to ensure that the measuring range of the selected reconstruction algorithm with selected drive frequency covers the elasticity range of the target tissue. It is hoped to arouse the interest of researchers to introduce new transform domain methods to the field of MR elastography. METHOD In linear, isotropic and local homogeneity assumptions, the typical representative of two different calculation methods are algebraic inversion of the differential equation (AIDE) algorithm and local frequency elastography (LFE) algorithm. To compare the accuracy of these calculation methods, the author adopted a digital phantom that can set the parameter values accurately. It is assumed that the phantom tissue was linear and isotropic, and that the driving wave was sinusoidal. The displacement distribution of waves in the tissue was calculated by the finite element simulation method in two different resolutions with the signal-to-noise ratio (SNR) set to 40 dB and the threshold of relative mean error (RME) no more than 10%. The wavelength-to-pixel-size ratios of the two methods under the setting threshold of RME were compared. RESULTS The lower threshold of wavelength-to-pixel-size ratio for AIDE was close to 10, while that for LFE was nearly 2 (the limitation of Shannon's law) under the setting precision. Thus, the measuring range of the AIDE method was less than that of LFE at the same experimental conditions. CONCLUSION The driving frequency selection range of the spatial frequency domain method is wider than that of the spatial domain method. It is worthwhile for researchers to devote more time to introducing new transformation domain method for MR elastography.
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Affiliation(s)
- Liangliang Hu
- School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology, Tunxi Road 193, Hefei, China.
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Zeng W, Gordon-Wylie SW, Tan L, Solamen L, McGarry MDJ, Weaver JB, Paulsen KD. Nonlinear Inversion MR Elastography With Low-Frequency Actuation. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:1775-1784. [PMID: 31825863 PMCID: PMC7313386 DOI: 10.1109/tmi.2019.2958212] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Magnetic resonance elastography (MRE) has been developed to noninvasively reconstruct mechanical properties for tissue and tissue-like materials over a frequency range of 10 ~200 Hz. In this work, low frequency (1~1.5 Hz) MRE activations were employed to estimate mechanical property distributions of simulated data and experimental phantoms. Nonlinear inversion (NLI) MRE algorithms based on viscoelastic and poroelastic material models were used to solve the inverse problems and recover images of the shear modulus and hydraulic conductivity. Data from a simulated phantom containing an inclusion with property contrast was carried out to study the feasibility of our low frequency actuated approach. To verify the stability of NLI algorithms for low frequency actuation, different levels of synthetic noise were added to the displacement data. Spatial distributions and property values were recovered well for noise level less than 5%. For the presented experimental phantom reconstructions with regularizations, the computed storage moduli from viscoelastic and poroelastic MRE gave similar results. Contrast was detected between inclusions and background in recovered hydraulic conductivity images. Results and findings confirm the feasibility of future in vivo neuroimaging examinations using natural cerebrovascular pulsations at cardiac frequencies, which can eliminate specialized equipment for high frequency actuation.
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Mura J, Schrank F, Sack I. An analytical solution to the dispersion‐by‐inversion problem in magnetic resonance elastography. Magn Reson Med 2020; 84:61-71. [DOI: 10.1002/mrm.28247] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 01/16/2020] [Accepted: 02/17/2020] [Indexed: 12/13/2022]
Affiliation(s)
- Joaquin Mura
- Department of Mechanical Engineering Universidad Técnica Federico Santa María Santiago Chile
| | - Felix Schrank
- Department of Radiology Charité ‐ Universitätsmedizin Berlin Germany
| | - Ingolf Sack
- Department of Radiology Charité ‐ Universitätsmedizin Berlin Germany
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Horeh MD, Asif A, Rivaz H. Analytical Minimization-Based Regularized Subpixel Shear-Wave Tracking for Ultrasound Elastography. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2019; 66:285-296. [PMID: 30530321 DOI: 10.1109/tuffc.2018.2885460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Ultrasound elastography is a convenient and affordable method for imaging mechanical properties of tissue, which are often correlated with pathologies. An emerging novel elastography technique applies an external acoustic radiation force to generate a shear wave in the tissue and uses ultrasound imaging to track the shear wave. Accurate tracking of the small tissue motion is a critical step in shear-wave elastography (SWE), but it is challenging due to various sources of noise in the ultrasound data. We formulate tissue displacement estimation as an optimization problem and propose two computationally efficient approaches to estimate the displacement field. The first algorithm is referred to as dynamic programming analytic minimization (DPAM), which utilizes first-order Taylor series expansion of the highly nonlinear cost function to allow for its efficient optimization, and was previously proposed for quasistatic elastography. The second algorithm is a novel technique that utilizes second-order derivatives of the nonlinear cost function. We call the new algorithm second-order analytic minimization elastography (SESAME). We compare DPAM and SESAME to the standard normalized cross correlation (NCC) approach in the context of displacement and speed estimation of wave propagation in SWE. The results of micrometer-order displacement estimation in a uniform simulation phantom illustrate that SESAME outperforms DPAM, which in turn outperforms NCC in terms of signal-to-noise ratio (SNR) and jitter. In addition, the relative difference between true and reconstructed shear modulus (averaged over excitations at different focal depths and several scatterer realizations at each depth) is approximately 3.41%, 1.12%, and 1.01%, respectively, for NCC, DPAM, and SESAME. The performance of the proposed methods is also assessed with real data acquired using a tissue-mimicking phantom, wherein, in comparison to NCC, DPAM and SESAME improve the SNR of displacement estimates by 7.6 and 9.5 dB, respectively. Experimental results on a tissue-mimicking phantom also show that shear modulus reconstruction substantially improved with the proposed DPAM technique over NCC and with some further improvement achieved by utilizing the second-order Taylor series approximation in SESAME instead of the first-order DPAM.
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Bertalan G, Guo J, Tzschätzsch H, Klein C, Barnhill E, Sack I, Braun J. Fast tomoelastography of the mouse brain by multifrequency single‐shot MR elastography. Magn Reson Med 2018; 81:2676-2687. [DOI: 10.1002/mrm.27586] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Revised: 10/04/2018] [Accepted: 10/07/2018] [Indexed: 12/13/2022]
Affiliation(s)
- Gergely Bertalan
- Department of Radiology Charité–Universitätsmedizin Berlin, Campus Charité MitteBerlin Germany
| | - Jing Guo
- Department of Radiology Charité–Universitätsmedizin Berlin, Campus Charité MitteBerlin Germany
| | - Heiko Tzschätzsch
- Department of Radiology Charité–Universitätsmedizin Berlin, Campus Charité MitteBerlin Germany
| | - Charlotte Klein
- Department of Neurology Charité–Universitätsmedizin Berlin, Campus Charité MitteBerlin Germany
| | - Eric Barnhill
- Department of Radiology Charité–Universitätsmedizin Berlin, Campus Charité MitteBerlin Germany
| | - Ingolf Sack
- Department of Radiology Charité–Universitätsmedizin Berlin, Campus Charité MitteBerlin Germany
| | - Jürgen Braun
- Institute of Medical Informatics Charité–Universitätsmedizin Berlin, Campus Benjamin FranklinBerlin Germany
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Bilasse M, Chatelin S, Altmeyer G, Marouf A, Vappou J, Charpentier I. A 2D finite element model for shear wave propagation in biological soft tissues: Application to magnetic resonance elastography. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2018; 34:e3102. [PMID: 29740972 DOI: 10.1002/cnm.3102] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Accepted: 04/19/2018] [Indexed: 06/08/2023]
Abstract
Dynamic elastography is a virtual palpation tool that aims at investigating the mechanical response of biological soft tissues in vivo. The objective of this study is to develop a finite element model (FEM) with low computational cost for reproducing realistically wave propagation for magnetic resonance elastography in heterogeneous soft tissues. Based on the first-order shear deformation theory for moderately thick structures, this model is developed and validated through comparison with analytical formulations of wave propagating in heterogeneous, viscoelastic infinite medium. This 2D-FEM is then compared to experimental data and a 3D-FEM using a commercial software. Our FEM is a powerful promising tool for investigations of magnetic resonance elastography.
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Affiliation(s)
- M Bilasse
- ICube, University of Strasbourg, UMR 7357 CNRS, 1 Place de l'Hôpital, 67000, Strasbourg, France
- École Catholique d'Arts et Métiers ECAM Strasbourg-Europe, 2 Rue de Madrid, 67300, Schiltigheim, France
| | - S Chatelin
- ICube, University of Strasbourg, UMR 7357 CNRS, 1 Place de l'Hôpital, 67000, Strasbourg, France
| | - G Altmeyer
- ICube, University of Strasbourg, UMR 7357 CNRS, 1 Place de l'Hôpital, 67000, Strasbourg, France
- École Catholique d'Arts et Métiers ECAM Strasbourg-Europe, 2 Rue de Madrid, 67300, Schiltigheim, France
| | - A Marouf
- ICube, University of Strasbourg, UMR 7357 CNRS, 1 Place de l'Hôpital, 67000, Strasbourg, France
| | - J Vappou
- ICube, University of Strasbourg, UMR 7357 CNRS, 1 Place de l'Hôpital, 67000, Strasbourg, France
| | - I Charpentier
- ICube, University of Strasbourg, UMR 7357 CNRS, 1 Place de l'Hôpital, 67000, Strasbourg, France
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