Estimation of hepatic fat fraction using modified Dixon magnetic resonance imaging techniques: effect of liver cirrhosis

Min, Jeeyoung; Park, Hee Sun; Kim, Young Jun; Yu, Mi Hye; Jung, Sung Il; Jeon, Hae Jeong

doi:10.1016/j.clinimag.2018.02.002

Cited by 6 publications

(4 citation statements)

References 31 publications

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“…Furthermore, MRS could not acquire images during the breath-hold time, and a physicist was needed to conduct complex post-processing with specific analysis software[16,35]. However, the HISTO sequence we performed in the present study allowed rapid and simple processing for image acquisition in a single 15 s breath hold[27,36]. In addition, both MRI and MRS assess liver triglyceride content by the relative volume of fat protons.…”

Section: Discussionmentioning

confidence: 99%

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Accuracy of multi-echo Dixon sequence in quantification of hepatic steatosis in Chinese children and adolescents

Zhao

Gan

Zhou

et al. 2019

WJG

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BACKGROUND Nonalcoholic fatty liver disease (NAFLD) is currently the outstanding cause of chronic liver disease in children and adolescents, especially in overweight and obese groups. Liver biopsy is the reference standard to diagnose NAFLD but invasive, thus it is not the best choice in clinical diagnosis and follow-up. Magnetic resonance (MR) is widely used in clinical trials to noninvasively quantify liver fat content in adults and children in foreign countries. While currently, it is rarely used in Chinese children and adolescents. We postulated that quantifying hepatic steatosis by MR could be extended to children and adolescents in China. AIM To investigate the accuracy of MR imaging (MRI) in quantifying liver fat with MR spectroscopy (MRS) as a reference. A secondary goal was to assess the prevalence of NAFLD in overweight and obese Chinese children and adolescents. METHODS There were 86 children and adolescents enrolled in this study, including 65 overweight and obese children and 21 healthy children. The participants underwent MRI and MRS. MRI and MRS were performed using multi-echo Dixon and HISTO sequences, respectively, to calculate hepatic proton density fat fraction (PDFF). Hepatic steatosis was diagnosed using MRS-PDFF > 5% as the threshold. Spearman’s analysis was used to evaluate the correlation between MRI and MRS. The agreement between these two methods was assessed by Bland-Altman analysis. RESULTS The MRI-PDFF in the MRS region of interest and the entire liver was 9.9% ± 10.3% with a range of 0.3%-39.9%, and 10.6% ± 9.4% with a range of 1.9%-38.9%, respectively. The MRS-PDFF was 9.1% ± 10.0%, with a range of 0.5%-37.8%. The incidence of hepatic steatosis detected by MRS-PDFF was 46.5% (40/86) of all participants, all of whom belonged to the overweight and obese group. Spearman’s analysis indicated an excellent correlation between multi-echo Dixon and MRS ( r > 0.9, P < 0.01). Bland-Altman analysis also demonstrated a good agreement between these two methods. CONCLUSION Multi-echo Dixon shows an excellent correlation and agreement with MRS in quantifying liver fat content and could be a potential tool to detect hepatic steatosis in Chinese children and adolescents.

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Section: Discussionmentioning

confidence: 99%

“…Multi-echo gradient echo sequences (ME Dixon; Siemens Healthcare, Erlangen, Germany) and online reconstruction (VIBE-Dixon; Siemens Healthcare, Erlangen, Germany) were performed with T2* correction[14,27]. A low flip angle (4°) was used to minimize the effects of T1 weighting[28,29].…”

Section: Methodsmentioning

confidence: 99%

Accuracy of multi-echo Dixon sequence in quantification of hepatic steatosis in Chinese children and adolescents

Zhao

Gan

Zhou

et al. 2019

WJG

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“…2 A large number of methods have been developed to suppress fat signal, or separate water and fat images for MR imaging and spectroscopy, including short TI inversion recovery (STIR) technique 3,4 that takes advantage of the shorter longitudinal relaxation time T 1 of fat, chemical shift selectivity (CHESS) fat saturation technique, 5 water excitation imaging, 6 and chemical shift-based Dixon water-fat separation techniques. [7][8][9][10] For some diagnostic purposes, such as bone marrow disease, 11 adrenal adenomas, 12 and fatty liver, 13 quantitative information on fat content and the ratio of water and fat can provide some auxiliary diagnosticinformation for doctors, resulting in the widespread application of Dixon methods 7,9 that can simultaneously obtain water-only and fat-only images. Severe B 0 field inhomogeneity presented a challenge for many early separation methods.…”

Section: Introductionmentioning

confidence: 99%

“…For some diagnostic purposes, such as bone marrow disease, 11 adrenal adenomas, 12 and fatty liver, 13 quantitative information on fat content and the ratio of water and fat can provide some auxiliary diagnosticinformation for doctors, resulting in the widespread application of Dixon methods 7,9 that can simultaneously obtain water‐only and fat‐only images. Severe B 0 field inhomogeneity presented a challenge for many early separation methods.…”

Section: Introductionmentioning

confidence: 99%

Robust water–fat separation based on deep learning model exploring multi‐echo nature of mGRE

Liu

Zhao

et al. 2020

Magnetic Resonance in Med

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Purpose To design a new deep learning network for fast and accurate water–fat separation by exploring the correlations between multiple echoes in multi‐echo gradient‐recalled echo (mGRE) sequence and evaluate the generalization capabilities of the network for different echo times, field inhomogeneities, and imaging regions. Methods A new multi‐echo bidirectional convolutional residual network (MEBCRN) was designed to separate water and fat images in a fast and accurate manner for the mGRE data. This new MEBCRN network contains 2 main modules, the first 1 is the feature extraction module, which learns the correlations between consecutive echoes, and the other one is the water–fat separation module that processes the feature information extracted from the feature extraction module. The multi‐layer feature fusion (MLFF) mechanism and residual structure were adopted in the water–fat separation module to increase separation accuracy and robustness. Moreover, we trained the network using in vivo abdomen images and tested it on the abdomen, knee, and wrist images. Results The results showed that the proposed network could separate water and fat images accurately. The comparison of the proposed network and other deep learning methods shows the advantage in both quantitative metrics and robustness for different TEs, field inhomogeneities, and images acquired for various imaging regions. Conclusion The proposed network could learn the correlations between consecutive echoes and separate water and fat images effectively. The deep learning method has certain generalization capabilities for TEs and field inhomogeneity. Although the network was trained only in vivo abdomen images, it could be applied for different imaging regions.

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Analysis of muscle, hip, and subcutaneous fat in osteoporosis patients with varying degrees of fracture risk using 3T Chemical Shift Encoded MRI

et al. 2020

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Estimation of hepatic fat fraction using modified Dixon magnetic resonance imaging techniques: effect of liver cirrhosis

Cited by 6 publications

References 31 publications

Accuracy of multi-echo Dixon sequence in quantification of hepatic steatosis in Chinese children and adolescents

Accuracy of multi-echo Dixon sequence in quantification of hepatic steatosis in Chinese children and adolescents

Robust water–fat separation based on deep learning model exploring multi‐echo nature of mGRE

Analysis of muscle, hip, and subcutaneous fat in osteoporosis patients with varying degrees of fracture risk using 3T Chemical Shift Encoded MRI

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