scholarly journals Magnetic Resonance Diffusion Kurtosis Imaging versus Diffusion-Weighted Imaging in Evaluating the Pathological Grade of Hepatocellular Carcinoma

2020 ◽  
Vol Volume 12 ◽  
pp. 5147-5158
Author(s):  
Guang-Zhi Wang ◽  
Ling-Fei Guo ◽  
Gui-Hua Gao ◽  
Yao Li ◽  
Xi-Zhen Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Magnetic Resonance ◽  
Diffusion Weighted Imaging ◽  
Diffusion Kurtosis Imaging ◽  
Pathological Grade ◽  
Diffusion Weighted ◽  
Diffusion Kurtosis

scholarly journals Diffusion Kurtosis MR Imaging versus Conventional Diffusion-Weighted Imaging for Distinguishing Hepatocellular Carcinoma from Benign Hepatic Nodules

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Yingmei Jia ◽  
Huasong Cai ◽  
Meng Wang ◽  
Yanji Luo ◽  
Ling Xu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Diffusion Weighted Imaging ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Hepatocellular Adenoma ◽  
Diffusion Kurtosis Imaging ◽  
Adc Value ◽  
Diffusion Weighted ◽  
Benign Nodules ◽  
Diffusion Kurtosis

Objectives. To assess the efficacy of diffusion kurtosis imaging (DKI) and compare DKI-derived parameters with conventional diffusion-weighted imaging (DWI) for distinguishing hepatocellular carcinoma (HCC) from benign hepatic nodules including focal nodular hyperplasia (FNH), hemangioma, and hepatocellular adenoma (HCA). Materials and Methods. 151 patients with 182 hepatic nodules (114 HCCs and 68 benign nodules including 33 FNHs, 29 hemangiomas, and 6 HCAs) were analyzed. Preoperative MRI examinations including DKI (b values: 0, 200, 500, 800, 1500, and 2000 sec/mm2) were performed, and kurtosis (K), diffusivity (D), and apparent diffusion coefficient (ADC) were calculated. The efficacy of DKI-derived parameters K, D, and ADC for distinguishing HCC from these benign nodules was analyzed. Results. ROC (receiver operating characteristic curve) analysis showed the optimal cutoff values of ADC, D, and K for identification of these benign nodules, and HCCs were 1.295 (area under the curve (AUC): 0.826; sensitivity 80.6%; specificity 70.8%), 1.787 (AUC: 0.770; sensitivity 83.6%; specificity 59.6%), and 1.002 (AUC: 0.761; sensitivity 65.5%; specificity 79.0%), respectively. Statistically significant differences were found in ADC, D, and K values between groups of HCC-FNH and HCC-hemangioma (P<0.05). There were significant differences in K and ADC values between groups of FNH-hemangioma and HCA-hemangioma (P<0.05), respectively. Using logistic regression analysis, a regression equation was obtained: LogitP=−1.982X1+1.385X3+1.948(X1: ADC; X3: K), and odds ratios (OR) were 0.138 (95% confidence interval (CI): 0.052, 0.367), and 8.996 (95% CI: 0.970, 16.460), respectively. Conclusion. Both ADC value and DKI-derived parameters K and D values have demonstrated a higher preoperative efficacy in distinguishing HCC from FNH, hemangioma, and HCA. No evidence was shown to suggest D or K value was superior to the ADC value.

scholarly journals Quantitative Measurement of Diffusion-weighted Imaging Signal Using Expression-controlled Aquaporin-4 Cells: Comparative Study of 2-compartment and Diffusion Kurtosis Imaging Models

2021 ◽  
Author(s):  
Akiko Imaizumi ◽  
Takayuki Obata ◽  
Jeff Kershaw ◽  
Yasuhiko Tachibana ◽  
Yoichiro Abe ◽  
...  
Keyword(s):  
Cell Membrane ◽  
Water Permeability ◽  
Diffusion Weighted Imaging ◽  
Aquaporin 4 ◽  
Diffusion Kurtosis Imaging ◽  
Parameter Estimates ◽  
Aqp4 Expression ◽  
Diffusion Weighted ◽  
Diffusion Kurtosis ◽  
And Diffusion

Purpose: The purpose of this study was to compare parameter estimates for the 2-compartment (2Comp) and diffusion kurtosis imaging (DKm) models obtained from diffusion-weighted imaging (DWI) of aquaporin-4 (AQP4) expression-controlled cells, and to look for biomarkers that indicate differences in the cell membrane water permeability. Methods: DWI was performed on AQP4-expressing and non-expressing cells and the signal was analyzed with the 2Comp and DKm models. For the 2Comp model, the diffusion coefficients (Df, Ds) and volume fractions (Ff, Fs, Ff=1-Fs) of the fast and slow compartments were estimated. For the DKm model, estimates of the diffusion kurtosis (K) and corrected diffusion coefficient (D) were obtained. Results: For the 2Comp model, Ds and Fs showed clear differences between AQP4-expressing and non-expressing cells. Fs was also sensitive to cell density. There was no clear relationship with the cell type for the DKm parameters. Conclusions: Changes to cell membrane water permeability due to AQP4 expression affected DWI of cell suspensions. For the 2Comp and DKm models, Ds was the parameter most sensitive to differences in AQP4 expression.

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