Preoperative assessment of microvascular invasion of hepatocellular carcinoma using non-Gaussian diffusion-weighted imaging with a fractional order calculus model: A pilot study.

PURPOSE: To assess the clinical potential of a set of new diffusion parameters (D, ß, and µ) derived from fractional order calculus (FROC) diffusion model in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: Between January 2019 to November 2020, a total of 63 patients with HCC were enrolled in this study. Diffusion-weighted images were acquired by using ten b-values (0-2000 s/mm2). The FROC model parameters including diffusion coefficient (D), fractional order parameter (ß), a microstructural quantity (µ) together with a conventional apparent diffusion coefficient (ADC) were calculated. Intraclass coefficients were calculated for assessing the agreement of parameters quantified by two radiologists. The differences of these values between the MVI-positive and MVI-negative HCC groups were compared by using independent sample t-test or the Mann-Whitney U test. Then the parameters showing significant differences between subgroups, including the ß and D, were integrated to develop a comprehensive predictive model via binary logistic regression. The diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis. RESULTS: Among all the studied diffusion parameters, significant differences were found in D, ß, and ADC between the MVI-positive and MVI-negative groups. MVI-positive HCCs showed significantly higher ß values (0.65 ± 0.17 vs. 0.51 ± 0.13, P = 0.001), along with lower D values (0.84 ± 0.11 µm2/ms vs. 1.03 ± 0.13 µm2/ms, P < 0.001) and lower ADC values (1.38 ± 0.46 µm2/ms vs. 2.09 ± 0.70 µm2/ms, P < 0.001) than those of MVI-negative HCCs. According to the ROC analysis, the combination of D and ß demonstrated the largest area under the ROC curve (0.920) compared with individual parameters (D: 0.912; ß: 0.733; and ADC: 0.831) for differentiating MVI-positive from MVI-negative HCCs. CONCLUSIONS: The FROC parameters can be used as noninvasive quantitative imaging markers for preoperatively predicting the MVI status of HCCs.

Dynamic contrast-enhanced (DCE) MRI assessment of microvascular characteristics in the murine orthotopic pancreatic cancer model.

OBJECT: The aim of this study was to assess the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI)-derived pharmacokinetic parameters between two contrast agents in a murine orthotopic pancreatic cancer model and to evaluate the tumor heterogeneity and the potential association between kinetic parameters and angiogenic markers such as the microvessel density (MVD) and vascular endothelial growth factor (VEGF) expression by immunohistochemistry. MATERIALS AND METHODS: Human pancreatic adenocarcinoma cell line MIAPaCa-2 was injected into the pancreas of BALB/C nu/nu mice. DCE-MRI was performed using Gd-DTPA and Gd-EOB-DTPA. Quantitative and semi-quantitative vascular parameters (K(trans), Kep, Ve and AUC) were calculated by using a dedicated postprocessing software program. Values were compared with tumor rim, tumor core and the entire tumor. The MVD and VEGF expressions between tumor rim and tumor core were also compared. RESULTS: There were no significant differences in K(trans), Kep, Ve, and AUC values of the three groups when using Gd-DTPA. However there were significant differences in K(trans), Kep, and AUC values of the three groups when using Gd-EOB-DTPA (P=0.014, 0.022, 0.007, respectively), in addition, the K(trans) and Kep values of tumor core were significantly lower than those of the entire tumor (adjusted P=0.014 and 0.027, respectively), the AUC values of core were significantly lower than those of the entire tumor and rim (adjusted P=0.039 and 0.009, respectively). Immunohistology results revealed that MVD and VEGF expression in the tumor rim was significantly higher than that in the core. There was positive correlation between AUC and MVD, VEGF. CONCLUSION: The murine orthotopic pancreatic cancer model provides an ideal animal model to study human pancreatic cancer. It can more sensitively semi-quantitatively and quantitatively analyze tumor angiogenesis through selecting the albumin-binding contrast agent.

Standardized ultrasound hepatic/renal ratio and hepatic attenuation rate to quantify liver fat content: an improvement method.

Accurate measures of liver fat content are essential for investigating the role of hepatic steatosis in the pathophysiology of multiple metabolic disorders. No traditional imaging methods can accurately quantify liver fat content. [(1)H]-magnetic resonance spectroscopy (MRS) is restricted in large-scale studies because of the practical and technological issues. Previous attempts on computer-aided ultrasound quantification of liver fat content varied in method, and the ultrasound quantitative parameters measured from different ultrasound machines were hardly comparable. We aimed to establish and validate a simple and propagable method for quantitative assessment of liver fat content based on the combination of standardized ultrasound quantitative parameters, using [(1)H]-MRS as gold standard. Totally 127 participants were examined with both ultrasonography (US) and [(1)H]-MRS. Ultrasound hepatic/renal echo-intensity ratio (H/R) and ultrasound hepatic echo-intensity attenuation rate (HA) were obtained from ordinary ultrasound images using computer program. Both parameters were standardized using a tissue-mimicking phantom before analysis. Standardized ultrasound H/R and HA were positively correlated with the liver fat content by [(1)H]-MRS (r = 0.884, P < 0.001 and r = 0.711, P < 0.001, respectively). Linear regression analysis showed ultrasound H/R could modestly predict the amount of liver fat (adjusted explained variance 78.0%, P < 0.001). The addition of ultrasound HA slightly improved the adjusted explained variance to 79.8%. Difference of estimated liver fat contents between different ultrasound machines and operators was reasonably well. Thus, computer-aided US is a valid method to estimate liver fat content and can be applied extensively after standardization of ultrasound quantitative parameters.