A preliminary study of the local biomechanical environment of liver tumors in vivo

Ma, Shengyuan; Zhu, Mingqing; Xia, Xiaolong; Guo, Liang; Genin, Guy M.; Sacks, Michael S.; Gao, Mingyuan; Mutic, Sasa; Hu, Yanle; Hu, Chun Hong; Feng, Yuan

doi:10.1002/mp.13434

Cited by 4 publications

(1 citation statement)

References 40 publications

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“…Cazoulat et al (2021) demonstrated that the lung stress map derived from the FEM-based deformable image registration (DIR) was significantly correlated with a ventilation Tc-99m SPECT image. Several studies have estimated the elasticity of the liver tissue with natural motion using biomechanics (Watanabe et al 2010, Ma et al 2019. In one recent study, the authors constructed an FEM-based biomechanical model that estimates the liver elasticity map using respiratory-induced liver displacement from routine clinical four-dimensional computed tomography (CT) (Fujimoto et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Assessing liver fibrosis distribution through liver elasticity estimates obtained using a biomechanical model of respiratory motion with magnetic resonance elastography

Fujimoto¹,

Shiinoki²,

Yuasa³

et al. 2022

Phys. Med. Biol.

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Objective: This study aimed to produce a three-dimensional liver elasticity map using the finite element method (FEM) and respiration-induced motion captured by T1-weighted magnetic resonance images (FEM-E-map) and to evaluate whether FEM-E-maps can be an imaging biomarker comparable to magnetic resonance elastography (MRE) for assessing the distribution and severity of liver fibrosis. Approach: We enrolled 14 patients who underwent MRI and MRE. T1-weighted MR images were acquired during shallow inspiration and expiration breath-holding, and the displacement vector field (DVF) between two images was calculated using deformable image registration. FEM-E-maps were constructed using FEM and DVF. First, three Poisson’s ratio settings (0.45, 0.49, and 0.499995) were validated and optimized to minimize the difference in liver elasticity between the FEM-E-map and MRE. Then, the whole and regional liver elasticity values estimated using FEM-E-maps were compared with those obtained from MRE using Pearson’s correlation coefficients. Spearman rank correlations and chi-square histograms were used to compare the voxel-level elasticity distribution. Main results: The optimal Poisson’s ratio was 0.49. Whole liver elasticity estimated using FEM-E-maps was strongly correlated with that measured using MRE (r = 0.96). For regional liver elasticity, the correlation was 0.84 for the right lobe and 0.82 for the left lobe. Spearman analysis revealed a moderate correlation for the voxel-level elasticity distribution between FEM-E-maps and MRE (0.61 ± 0.10). The small chi-square distances between the two histograms (0.11 ± 0.07) indicated good agreement. Significance: FEM-E-maps represent a potential imaging biomarker for visualizing the distribution of liver fibrosis using only T1-weighted images obtained with a common MR scanner, without any additional examination or special elastography equipment. However, additional studies including comparisons with biopsy findings are required to verify the reliability of this method for clinical application.

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Section: Introductionmentioning

confidence: 99%

Assessing liver fibrosis distribution through liver elasticity estimates obtained using a biomechanical model of respiratory motion with magnetic resonance elastography

Fujimoto¹,

Shiinoki²,

Yuasa³

et al. 2022

Phys. Med. Biol.

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Correlation analysis of structural and biomechanical properties of hepatocellular carcinoma tissue

Chen

Yang

et al. 2022

Journal of Biomechanics

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A Novel Finite Element Model to Assess the Effect of Solid Stress Inside Tumors on Elastographic Normal Strains and Fluid Pressure

Islam

Righetti

2019

Journal of Engineering and Science in Medical Diagnostics and Therapy

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Ultrasound elastography is a noninvasive imaging modality used to assess the mechanical behavior of tissues, including cancers. Analytical and finite element (FE) models are useful and effective tools to understand the mechanical behavior of cancers and predict elastographic parameters under different testing conditions. A number of analytical and FE models to describe the mechanical behavior of cancers in elastography have been reported in the literature. However, none of these models consider the presence of solid stress (SS) inside the cancer, a clinically significant mechanical parameter with an influential role in cancer initiation, progression, and metastasis. In this paper, we develop an FE model applicable to cancers, which include both SS and elevated interstitial fluid pressure (IFP). This model is then used to assess the effects of these mechanical parameters on the normal strains and the fluid pressure, estimated using ultrasound poroelastography. Our results indicate that SS creates space-dependent changes in the strains and fluid pressure inside the tumor. This is in contrast to the effects produced by IFP on the strains and fluid pressure, which are uniformly distributed across the cancer. The developed model can help elucidating the role of SS on elastographic parameters and images. It may also provide a means to indirectly obtain information about the SS from the observed changes in the experimental elastographic images.

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A preliminary study of the local biomechanical environment of liver tumors in vivo

Cited by 4 publications

References 40 publications

Assessing liver fibrosis distribution through liver elasticity estimates obtained using a biomechanical model of respiratory motion with magnetic resonance elastography

Assessing liver fibrosis distribution through liver elasticity estimates obtained using a biomechanical model of respiratory motion with magnetic resonance elastography

Correlation analysis of structural and biomechanical properties of hepatocellular carcinoma tissue

A Novel Finite Element Model to Assess the Effect of Solid Stress Inside Tumors on Elastographic Normal Strains and Fluid Pressure

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