Assessment of Microvascular Invasion of Hepatocellular Carcinoma with Diffusion Kurtosis Imaging.

Purpose To evaluate the potential role of diffusion kurtosis imaging and conventional magnetic resonance (MR) imaging findings including standard monoexponential model of diffusion-weighted imaging and morphologic features for preoperative prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Materials and Methods Institutional review board approval and written informed consent were obtained. Between September 2015 and November 2016, 84 patients (median age, 54 years; range, 29-79 years) with 92 histopathologically confirmed HCCs (40 MVI-positive lesions and 52 MVI-negative lesions) were analyzed. Preoperative MR imaging examinations including diffusion kurtosis imaging (b values: 0, 200, 500, 1000, 1500, and 2000 sec/mm2) were performed and kurtosis, diffusivity, and apparent diffusion coefficient maps were calculated. Morphologic features of conventional MR images were also evaluated. Univariate and multivariate logistic regression analyses were used to evaluate the relative value of these parameters as potential predictors of MVI. Results Features significantly related to MVI of HCC at univariate analysis were increased mean kurtosis value (P < .001), decreased mean diffusivity value (P = .033) and apparent diffusion coefficient value (P = .011), and presence of infiltrative border with irregular shape (P = .005) and irregular circumferential enhancement (P = .026). At multivariate analysis, mean kurtosis value (odds ratio, 6.25; P = .001), as well as irregular circumferential enhancement (odds ratio, 6.92; P = .046), were independent risk factors for MVI of HCC. The mean kurtosis value for MVI of HCC showed an area under the receiver operating characteristic curve of 0.784 (optimal cutoff value was 0.917). Conclusion Higher mean kurtosis values in combination with irregular circumferential enhancement are potential predictive biomarkers for MVI of HCC. © RSNA, 2017.

Whole-tumor MRI histogram analyses of hepatocellular carcinoma: Correlations with Ki-67 labeling index.

PURPOSE: To evaluate whether whole-tumor histogram-derived parameters for an apparent diffusion coefficient (ADC) map and contrast-enhanced magnetic resonance imaging (MRI) could aid in assessing Ki-67 labeling index (LI) of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: In all, 57 patients with HCC who underwent pretreatment MRI with a 3T MR scanner were included retrospectively. Histogram parameters including mean, median, standard deviation, skewness, kurtosis, and percentiles (5th , 25th , 75th , 95th ) were derived from the ADC map and MR enhancement. Correlations between histogram parameters and Ki-67 LI were evaluated and differences between low Ki-67 (≤10%) and high Ki-67 (>10%) groups were assessed. RESULTS: Mean, median, 5th , 25th , 75th percentiles of ADC, and mean, median, 25th , 75th , 95th percentiles of enhancement of arterial phase (AP) demonstrated significant inverse correlations with Ki-67 LI (rho up to -0.48 for ADC, -0.43 for AP) and showed significant differences between low and high Ki-67 groups (P < 0.001-0.04). Areas under the receiver operator characteristics (ROC) curve for identification of high Ki-67 were 0.78, 0.77, 0.79, 0.82, and 0.76 for mean, median, 5th , 25th , 75th percentiles of ADC, respectively, and 0.74, 0.81, 0.76, 0.82, 0.69 for mean, median, 25th , 75th , 95th percentiles of AP, respectively. CONCLUSION: Histogram-derived parameters of ADC and AP were potentially helpful for predicting Ki-67 LI of HCC. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:383-392.

A model incorporating clinicopathologic and liver imaging reporting and data system-based magnetic resonance imaging features to identify hepatocellular carcinoma in LR-M observations.

PURPOSE: To evaluate the predictive value of a combination model of Liver Imaging Reporting and Data System (LI-RADS)-based magnetic resonance imaging (MRI) and clinicopathologic features to identify atypical hepatocellular carcinoma (HCC) in LI-RADS category M (LR-M) observations. METHODS: A total of 105 patients with HCC based on surgery or biopsy who underwent preoperative MRI were retrospectively reviewed in the training group from hospital-1 between December 2016 and November 2020. The LI-RADS-based MRI features and clinicopathologic data were compared between LR-M HCC and non-HCC groups. Univariate and least absolute shrinkage and selection operator regression analyses were used to select the features. Binary logistic regression analysis was then conducted to estimate potential predictors of atypical HCC. A predictive nomogram was established based on the combination of MRI and clinicopathologic features and further validated using an independent external set of data from hospital-2. RESULTS: Of 113 observations from 105 patients (mean age, 61 years; 77 men) in the training set, 47 (41.59%) were classified as LR-M HCC. Following multivariate analysis, aspartate aminotransferase >40 U/L [odds ratio (OR): 4.65], alpha-fetoprotein >20 ng/mL (OR: 13.04), surface retraction (OR: 0.16), enhancing capsule (OR: 5.24), blood products in mass (OR: 8.2), and iso/hypoenhancement on delayed phase (OR: 10.26) were found to be independently correlated with LR-M HCC. The corresponding area under the curve for a combined model-based nomogram was 0.95 in the training patients (n = 113) and 0.90 in the validation cohort (n = 53). CONCLUSION: The combined model incorporating clinicopathologic and MRI features demonstrated a satisfactory prediction result for LR-M HCC.

MR features based on LI-RADS identify cytokeratin 19 status of hepatocellular carcinomas.

OBJECTIVE: To retrospectively evaluate the value of MR features based on Liver Imaging Reporting and Data System (LI-RADS ver.2017) for identifying the status of cytokeratin (CK) 19 expression of HCC before surgery. METHODS: A total of 201 patients with 207 HCCs who underwent MR imaging were reviewed retrospectively. MR features based on LI-RADS ver.2017 as well as clinical data were compared between CK19-positive (n = 51) and CK19-negative (n = 156) HCCs groups. Potential predictive parameters were identified by univariate and multivariate logistic regression analysis and diagnostic odds ratios (ORs) were recorded. RESULTS: MR features including targetoid appearance (p = 0.001) was more frequently observed while non-peripheral "washout" (p < 0.0001) and non-rim arterial phase hyper-enhancement (p < 0.0001) were found less frequently in CK19-positive HCCs compared to CK19-negative HCCs. At multivariate analysis, serum alphafetoprotein (AFP)>20 ng/ml (OR = 5.9) and targetoid appearance (OR = 4.2) and non-peripheral "washout" (OR = 0.2) were significant independent predictors of CK19-positive HCCs. CONCLUSION: Targetoid appearance and absence non-peripheral "washout" combined with elevated AFP were useful for differentiating CK19-positive HCCs from CK19-negative HCC.

Different MR features for differentiation of intrahepatic mass-forming cholangiocarcinoma from hepatocellular carcinoma according to tumor size.

OBJECTIVE: To identify reliable magnetic resonance (MR) features for distinguishing mass-forming type of intrahepatic cholangiocarcinoma (IMCC) from hepatocellular carcinoma (HCC) based on tumor size. METHODS: This retrospective study included 395 patients with pathologically confirmed IMCCs (n = 180) and HCCs (n = 215) who underwent pre-operative contrast-enhanced MRI including diffusion-weighted imaging (DWI). MR features were evaluated and clinical data were also recorded. All the characteristics were compared in small (≤3 cm) and large tumor (>3 cm) groups by univariate analysis and subsequently calculated by multivariable logistic regression analysis. RESULTS: Multivariable analysis revealed that rim arterial phase hyperenhancement [odds ratios (ORs) = 13.16], biliary dilation (OR = 23.42) and CA19-9 (OR = 21.45) were significant predictors of large IMCCs (n = 138), and washout appearance (OR = 0.036), enhancing capsule appearance (OR = 0.039), fat in mass (OR = 0.057), chronic liver disease (OR = 0.088) and alpha fetoprotein (OR = 0.019) were more frequently found in large HCCs (n = 143). For small IMCCs (n = 42) and HCCs (n = 72), rim arterial phase hyperenhancement (OR = 9.68), target appearance at DWI (OR = 12.51), alpha fetoprotein (OR = 0.12) and sex (OR = 0.20) were independent predictors in multivariate analysis. CONCLUSION: Valuable MR features and clinical factors varied for differential diagnosis of IMCCs and HCCs according to tumor size. Advances in knowledge: MR features for differential diagnosis of large IMCC and HCC (>3 cm) are in keeping with that recommended by LI-RADS. However, for small IMCCs and HCCs (≤3 cm), only rim enhancement on arterial phase and target appearance at DWI are reliable predictors.

Feasibility of histogram analysis of susceptibility-weighted MRI for staging of liver fibrosis.

PURPOSE: We aimed to evaluate whether histogram analysis of susceptibility-weighted imaging (SWI) could quantify liver fibrosis grade in patients with chronic liver disease (CLD). METHODS: Fifty-three patients with CLD who underwent multi-echo SWI (TEs of 2.5, 5, and 10 ms) were included. Histogram analysis of SWI images were performed and mean, variance, skewness, kurtosis, and the 1st, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared. For significant parameters, further receiver operating characteristic (ROC) analyses were performed to evaluate the potential diagnostic performance for differentiating liver fibrosis stages. RESULTS: The number of patients in each pathologic fibrosis grade was 7, 3, 5, 5, and 33 for F0, F1, F2, F3, and F4, respectively. The results of variance (TE: 10 ms), 90th percentile (TE: 10 ms), and 99th percentile (TE: 10 and 5 ms) in F0-F3 group were significantly lower than in F4 group, with areas under the ROC curves (AUCs) of 0.84 for variance and 0.70-0.73 for the 90th and 99th percentiles, respectively. The results of variance (TE: 10 and 5 ms), 99th percentile (TE: 10 ms), and skewness (TE: 2.5 and 5 ms) in F0-F2 group were smaller than those of F3/F4 group, with AUCs of 0.88 and 0.69 for variance (TE: 10 and 5 ms, respectively), 0.68 for 99th percentile (TE: 10 ms), and 0.73 and 0.68 for skewness (TE: 2.5 and 5 ms, respectively). CONCLUSION: Magnetic resonance histogram analysis of SWI, particularly the variance, is promising for predicting advanced liver fibrosis and cirrhosis.