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Application of Magnetic Resonance Imaging in Liver Biomechanics: A Systematic Review.

作者信息

Seyedpour Seyed M, Nabati Mehdi, Lambers Lena, Nafisi Sara, Tautenhahn Hans-Michael, Sack Ingolf, Reichenbach Jürgen R, Ricken Tim

机构信息

Institute of Mechanics, Structural Analysis and Dynamics, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Stuttgart, Germany.

Biomechanics Lab, Institute of Mechanics, Structural Analysis and Dynamics, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Stuttgart, Germany.

出版信息

Front Physiol. 2021 Sep 22;12:733393. doi: 10.3389/fphys.2021.733393. eCollection 2021.


DOI:10.3389/fphys.2021.733393
PMID:34630152
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8493836/
Abstract

MRI-based biomechanical studies can provide a deep understanding of the mechanisms governing liver function, its mechanical performance but also liver diseases. In addition, comprehensive modeling of the liver can help improve liver disease treatment. Furthermore, such studies demonstrate the beginning of an engineering-level approach to how the liver disease affects material properties and liver function. Aimed at researchers in the field of MRI-based liver simulation, research articles pertinent to MRI-based liver modeling were identified, reviewed, and summarized systematically. Various MRI applications for liver biomechanics are highlighted, and the limitations of different viscoelastic models used in magnetic resonance elastography are addressed. The clinical application of the simulations and the diseases studied are also discussed. Based on the developed questionnaire, the papers' quality was assessed, and of the 46 reviewed papers, 32 papers were determined to be of high-quality. Due to the lack of the suitable material models for different liver diseases studied by magnetic resonance elastography, researchers may consider the effect of liver diseases on constitutive models. In the future, research groups may incorporate various aspects of machine learning (ML) into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b3/8493836/dd4667330002/fphys-12-733393-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b3/8493836/b66bdd833a2a/fphys-12-733393-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b3/8493836/dd4667330002/fphys-12-733393-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b3/8493836/b66bdd833a2a/fphys-12-733393-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b3/8493836/dd4667330002/fphys-12-733393-g0002.jpg

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本文引用的文献

[1]
Poroelasticity as a Model of Soft Tissue Structure: Hydraulic Permeability Reconstruction for Magnetic Resonance Elastography in Silico.

Front Phys. 2021-1

[2]
Automated Analysis of Multiparametric Magnetic Resonance Imaging/Magnetic Resonance Elastography Exams for Prediction of Nonalcoholic Steatohepatitis.

J Magn Reson Imaging. 2021-7

[3]
Impact of tumor-parenchyma biomechanics on liver metastatic progression: a multi-model approach.

Sci Rep. 2021-1-18

[4]
MR elastography: Principles, guidelines, and terminology.

Magn Reson Med. 2021-5

[5]
Elastography imaging: the 30 year perspective.

Phys Med Biol. 2020-12-21

[6]
Distinguishing pancreatic cancer and autoimmune pancreatitis with in vivo tomoelastography.

Eur Radiol. 2021-5

[7]
Liver Stiffness by Magnetic Resonance Elastography Predicts Future Cirrhosis, Decompensation, and Death in NAFLD.

Clin Gastroenterol Hepatol. 2021-9

[8]
Modeling of Nanotherapy Response as a Function of the Tumor Microenvironment: Focus on Liver Metastasis.

Front Bioeng Biotechnol. 2020-8-19

[9]
Ultrasound-based liver elastography: current results and future perspectives.

Abdom Radiol (NY). 2020-11

[10]
Audit of eliminating biopsy for presumed fibroadenomas with benign ultrasound greyscale and shear-wave elastography findings in women aged 25-39 years.

Clin Radiol. 2020-11

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