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Cited by in F6Publishing
For: Wáng YXJ, Wang X, Wu P, Wang Y, Chen W, Chen H, Li J. Topics on quantitative liver magnetic resonance imaging. Quant Imaging Med Surg 2019;9:1840-90. [PMID: 31867237 DOI: 10.21037/qims.2019.09.18] [Cited by in Crossref: 9] [Cited by in F6Publishing: 21] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Podgórska J, Pasicz K, Skrzyński W, Gołębiewski B, Kuś P, Jasieniak J, Kiliszczyk A, Rogowska A, Benkert T, Pałucki J, Grabska I, Fabiszewska E, Jagielska B, Kukołowicz P, Cieszanowski A, Giannelli M. Perfusion-Diffusion Ratio: A New IVIM Approach in Differentiating Solid Benign and Malignant Primary Lesions of the Liver. BioMed Research International 2022;2022:1-9. [DOI: 10.1155/2022/2957759] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
2 Hu GW, Zheng CJ, Zhong WX, Zhuang DP, Xiao BH, Wáng YXJ. Usefulness of diffusion derived vessel density computed from a simplified IVIM imaging protocol: An experimental study with rat biliary duct blockage induced liver fibrosis. Magn Reson Imaging 2021;84:115-23. [PMID: 34619291 DOI: 10.1016/j.mri.2021.09.013] [Reference Citation Analysis]
3 Moon CM, Lee YY, Heo SH, Shin SS, Jeong YY. Identification of potential metabolic biomarkers in predicting esophageal varices needing treatment in patients with liver cirrhosis. Sci Rep 2021;11:19684. [PMID: 34608234 DOI: 10.1038/s41598-021-99198-9] [Reference Citation Analysis]
4 Wáng YXJ, Xiao BH, Zheng CJ, Li T, Che-Nordin N, Wang W. More promising results of liver intravoxel incoherent motion imaging analysis for the assessment of nonalcoholic steatohepatitis and fibrosis. Ann Transl Med 2021;9:1283. [PMID: 34532420 DOI: 10.21037/atm-21-3442] [Reference Citation Analysis]
5 Xu H, Zhang N, Yang DW, Ren A, Ren H, Zhang Q, Zhu JX, Li GJ, Yang ZH. Scan Time Reduction in Intravoxel Incoherent Motion Diffusion-Weighted Imaging and Diffusion Kurtosis Imaging of the Abdominal Organs: Using a Simultaneous Multislice Technique With Different Acceleration Factors. J Comput Assist Tomogr 2021. [PMID: 34270482 DOI: 10.1097/RCT.0000000000001189] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
6 Wáng YXJ. Gender-specific liver aging and magnetic resonance imaging. Quant Imaging Med Surg 2021;11:2893-904. [PMID: 34249621 DOI: 10.21037/qims-21-227] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
7 Qiu QT, Zhang J, Duan JH, Wu SZ, Ding JL, Yin Y. Development and validation of radiomics model built by incorporating machine learning for identifying liver fibrosis and early-stage cirrhosis. Chin Med J (Engl) 2020;133:2653-9. [PMID: 33009025 DOI: 10.1097/CM9.0000000000001113] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
8 Qu Z, Yang S, Xing F, Tong R, Yang C, Guo R, Huang J, Lu F, Fu C, Yan X, Hectors S, Gillen K, Wang Y, Liu C, Zhan S, Li J. Magnetic resonance quantitative susceptibility mapping in the evaluation of hepatic fibrosis in chronic liver disease: a feasibility study. Quant Imaging Med Surg 2021;11:1170-83. [PMID: 33816158 DOI: 10.21037/qims-20-720] [Reference Citation Analysis]
9 Cheng Y, Jiang H, Wang H, Tang Q, Liu T. Application of Field-of-View Optimized and Constrained Undistorted Single Shot (FOCUS) with Intravoxel Incoherent Motion (IVIM) in 3T in Locally Advanced Rectal Cancer. Dis Markers 2021;2021:5565902. [PMID: 33936322 DOI: 10.1155/2021/5565902] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
10 Chevallier O, Wáng YXJ, Guillen K, Pellegrinelli J, Cercueil JP, Loffroy R. Evidence of Tri-Exponential Decay for Liver Intravoxel Incoherent Motion MRI: A Review of Published Results and Limitations. Diagnostics (Basel) 2021;11:379. [PMID: 33672277 DOI: 10.3390/diagnostics11020379] [Cited by in Crossref: 3] [Cited by in F6Publishing: 7] [Article Influence: 3.0] [Reference Citation Analysis]
11 Kovač JD, Daković M, Janković A, Mitrović M, Dugalić V, Galun D, Đurić-Stefanović A, Mašulović D. The role of quantitative diffusion-weighted imaging in characterization of hypovascular liver lesions: A prospective comparison of intravoxel incoherent motion derived parameters and apparent diffusion coefficient. PLoS One 2021;16:e0247301. [PMID: 33606753 DOI: 10.1371/journal.pone.0247301] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
12 Wáng YXJ. Observed paradoxical perfusion fraction elevation in steatotic liver: An example of intravoxel incoherent motion modeling of the perfusion component constrained by the diffusion component. NMR Biomed 2021;34:e4488. [PMID: 33559161 DOI: 10.1002/nbm.4488] [Cited by in Crossref: 1] [Cited by in F6Publishing: 8] [Article Influence: 1.0] [Reference Citation Analysis]
13 Zhou N, Hu A, Shi Z, Wang X, Zhu Q, Zhou Q, Ma J, Zhao F, Kong W, He J. Inter-observer agreement of computed tomography and magnetic resonance imaging on gross tumor volume delineation of intrahepatic cholangiocarcinoma: an initial study. Quant Imaging Med Surg 2021;11:579-85. [PMID: 33532258 DOI: 10.21037/qims-19-1093] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
14 Zhu Y, Zhou Y, Zhang W, Xue L, Li Y, Jiang J, Zhong Y, Wang S, Jiang L. Value of quantitative dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging in predicting extramural venous invasion in locally advanced gastric cancer and prognostic significance. Quant Imaging Med Surg 2021;11:328-40. [PMID: 33392032 DOI: 10.21037/qims-20-246] [Cited by in F6Publishing: 8] [Reference Citation Analysis]
15 Huang H, Zheng CJ, Wang LF, Che-Nordin N, Wáng YXJ. Age and gender dependence of liver diffusion parameters and the possibility that intravoxel incoherent motion modeling of the perfusion component is constrained by the diffusion component. NMR Biomed 2021;34:e4449. [PMID: 33354829 DOI: 10.1002/nbm.4449] [Cited by in Crossref: 2] [Cited by in F6Publishing: 8] [Article Influence: 1.0] [Reference Citation Analysis]
16 Zhao F, Zhou N, Wang JL, Zhou H, Zou LQ, Zhong WX, He J, Zheng CJ, Yan SX, Wáng YXJ. Collagen deposition in the liver is strongly and positively associated with T1rho elongation while fat deposition is associated with T1rho shortening: an experimental study of methionine and choline-deficient (MCD) diet rat model. Quant Imaging Med Surg 2020;10:2307-21. [PMID: 33269229 DOI: 10.21037/qims-20-651] [Cited by in F6Publishing: 7] [Reference Citation Analysis]
17 Huber FA, Del Grande F, Rizzo S, Guglielmi G, Guggenberger R. MRI in the assessment of adipose tissues and muscle composition: how to use it. Quant Imaging Med Surg 2020;10:1636-49. [PMID: 32742957 DOI: 10.21037/qims.2020.02.06] [Cited by in Crossref: 2] [Cited by in F6Publishing: 6] [Article Influence: 1.0] [Reference Citation Analysis]
18 Fan M, Xing Z, Du Y, Pan L, Sun Y, He X. Quantitative assessment of renal allograft pathologic changes: comparisons of mono-exponential and bi-exponential models using diffusion-weighted imaging. Quant Imaging Med Surg 2020;10:1286-97. [PMID: 32550137 DOI: 10.21037/qims-19-985a] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
19 Xiao BH, Huang H, Wang LF, Qiu SW, Guo SW, Wáng YXJ. Diffusion MRI Derived per Area Vessel Density as a Surrogate Biomarker for Detecting Viral Hepatitis B-Induced Liver Fibrosis: A Proof-of-Concept Study. SLAS Technol 2020;25:474-83. [PMID: 32292088 DOI: 10.1177/2472630320915838] [Cited by in Crossref: 3] [Cited by in F6Publishing: 7] [Article Influence: 1.5] [Reference Citation Analysis]
20 Verde F, Romeo V, Maurea S. Advanced liver imaging using MR to predict outcomes in chronic liver disease: a shift from morphology to function liver assessment. Quant Imaging Med Surg 2020;10:805-7. [PMID: 32269940 DOI: 10.21037/qims.2020.02.03] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
21 Ma J, Wang F, Zhang W, Wang L, Yang X, Qian Y, Huang J, Wang J, Yang J. Percutaneous cryoablation for the treatment of liver cancer at special sites: an assessment of efficacy and safety. Quant Imaging Med Surg. 2019;9:1948-1957. [PMID: 31929967 DOI: 10.21037/qims.2019.11.12] [Cited by in Crossref: 6] [Cited by in F6Publishing: 9] [Article Influence: 2.0] [Reference Citation Analysis]