Search

Objectives: Impeded diffusion fraction (IDF) is a novel and promising diffusion-weighted imaging (DWI) technique that allows for the detection of various diffusion compartments, including macromolecular coordinated water, free diffusion, perfusion, and cellular free water. This study aims to investigate the clinical potential of IDF-DWI in detecting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: 66 patients were prospectively included. Metrics derived from IDF-DWI and the apparent diffusion coefficient (ADC) were calculated. Multivariate logistic regression was employed to identify clinical risk factors. Diagnostic performance was evaluated using the area under the receiver operating characteristics curve (AUC-ROC), the area under the precision-recall curve (AUC-PR), and the calibration error (cal-error). Additionally, a power analysis was conducted to determine the required sample size. Results: The results suggested a significantly higher fraction of impeded diffusion (FID) originating from IDF-DWI in MVI-positive HCCs (p < 0.001). Moreover, the ADC was found to be significantly lower in MVI-positive HCCs (p = 0.019). Independent risk factors of MVI included larger tumor size and elevated alpha-fetoprotein (AFP) levels. The nomogram model incorporating ADC, FID, tumor size, and AFP level yielded the highest diagnostic accuracy for MVI (AUC-PR = 0.804, AUC-ROC = 0.783, cal-error = 0.044), followed by FID (AUC-PR = 0.693, AUC-ROC = 0.760, cal-error = 0.060) and ADC (AUC-PR = 0.570, AUC-ROC = 0.651, cal-error = 0.164). Conclusion: IDF-DWI shows great potential in noninvasively, accurately, and preoperatively detecting MVI in HCC and may offer clinical benefits for prognostic prediction and determination of treatment strategy. [ABSTRACT FROM AUTHOR]

Purpose: Microvascular invasion (MVI) is a critical factor in predicting the recurrence and prognosis of hepatocellular carcinoma (HCC) after liver transplantation (LT). However, there is a lack of reliable preoperative predictors for MVI. The purpose of this study is to evaluate the potential of an 18F-FDG PET/CT-based nomogram in predicting MVI before LT for HCC. Methods: 83 HCC patients who obtained 18F-FDG PET/CT before LT were included in this retrospective research. To determine the parameters connected to MVI and to create a nomogram for MVI prediction, respectively, Logistic and Cox regression models were applied. Analyses of the calibration curve and receiver operating characteristic (ROC) curves were used to assess the model's capability to differentiate between clinical factors and metabolic data from PET/CT images. Results: Among the 83 patients analyzed, 41% were diagnosed with histologic MVI. Multivariate logistic regression analysis revealed that Child–Pugh stage, alpha-fetoprotein, number of tumors, CT Dmax, and Tumor-to-normal liver uptake ratio (TLR) were significant predictors of MVI. A nomogram was constructed using these predictors, which demonstrated strong calibration with a close agreement between predicted and actual MVI probabilities. The nomogram also showed excellent differentiation with an AUC of 0.965 (95% CI 0.925–1.000). Conclusion: The nomogram based on 18F-FDG PET/CT metabolic characteristics is a reliable preoperative imaging biomarker for predicting MVI in HCC patients before undergoing LT. It has demonstrated excellent efficacy and high clinical applicability. [ABSTRACT FROM AUTHOR]

Purpose: Varying diffusion curvature (VDC) MRI is an emerging diffusion-weighted imaging (DWI) technique that can capture non-Gaussian diffusion behavior and reflect tissue heterogeneity. However, its clinical utility has hardly been evaluated. We aimed to investigate the value of the VDC technique in noninvasively assessing microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: 74 patients with HCCs, including 39 MVI-positive and 35 MVI-negative HCCs were included into this prospective study. Quantitative metrics between subgroups, clinical risk factors, as well as diagnostic performance were evaluated. The power analysis was also carried out to determine the statistical power. Results: MVI-positive HCCs exhibited significantly higher VDC-derived structural heterogeneity measure, D1 (0.680 ± 0.100 × 10–3 vs 0.572 ± 0.148 × 10–3 mm2/s, p = 0.001) and lower apparent diffusion coefficient (ADC) (1.350 ± 0.166 × 10–3 vs 1.471 ± 0.322 × 10–3 mm2/s, p = 0.0495) compared to MVI-negative HCCs. No statistical significance was observed for VDC-derived diffusion coefficient, D0 between the subgroups (p = 0.562). Tumor size (odds ratio (OR) = 1.242) and alpha-fetoprotein (AFP) (OR = 2.527) were identified as risk factors for MVI. A predictive nomogram was constructed based on D1, ADC, tumor size, and AFP, which exhibited the highest diagnostic accuracy (AUC = 0.817), followed by D1 (AUC = 0.753) and ADC (AUC = 0.647). The diagnostic performance of the nomogram-based model was also validated by the calibration curve and decision curve. Conclusion: VDC can aid in the noninvasive and preoperative diagnosis of HCC with MVI, which may result in the clinical benefit in terms of prognostic prediction and clinical decision-making. [ABSTRACT FROM AUTHOR]

Purpose: Microvascular invasion (MVI) is a significant prognostic factor in combined hepatocellular cholangiocarcinoma (cHCC-CCA). However, its diagnosis relies on postoperative histopathologic analysis. This study aims to identify preoperative inflammatory biomarkers and MR-imaging features that can predict MVI in cHCC-CCA. Methods: This retrospective study enrolled 119 patients with histopathologically confirmed cHCC-CCA between January 2016 and December 2021. Two radiologists, unaware of the clinical data, independently reviewed all MR image features. Univariable and multivariable analyses were performed to determine the independent predictors for MVI among inflammatory biomarkers and MRI characteristics. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the diagnostic performance. Results: Multivariable logistic regression analysis identified four variables significantly associated with MVI (p < 0.05), including two inflammatory biomarkers [albumin-to-alkaline phosphatase ratio (AAPR) and aspartate aminotransferase-to-neutrophil ratio index (ANRI)] and two MRI features (non-smooth tumor margin and arterial phase peritumoral enhancement). A combined model for predicting MVI was constructed based on these four variables, with an AUC of 0.802 (95% CI 0.719–0.870). The diagnostic efficiency of the combined model was higher than that of the imaging model. Conclusion: Inflammatory biomarkers and MRI features could be potential predictors for MVI in cHCC-CCA. The combined model, derived from inflammatory biomarkers and MRI features, showed good performance in preoperatively predicting MVI in cHCC-CCA patients. [ABSTRACT FROM AUTHOR]

Purpose: To develop a nomogram based on preoperative clinical and magnetic resonance imaging (MRI) features for the microvascular invasion (MVI) status in solitary intrahepatic mass-forming cholangiocarcinoma (sIMCC) and to evaluate whether it could predict recurrence-free survival (RFS). Methods: We included 115 cases who experienced MRI examinations for sIMCC with R0 resection. The preoperative clinical and MRI features were extracted. Independent predictors related to MVI+ were evaluated by stepwise multivariate logistic regression, and a nomogram was constructed. A receiver operating characteristic (ROC) curve was used to assess the predictive ability. All patients were classified into high- and low-risk groups of MVI. Then, the correlations of the nomogram with RFS in patents with sIMCC were analyzed by Kaplan–Meier method. Results: The occurrence rate of MVI+ was 38.3% (44/115). The preoperative independent predictors of MVI+ were carbohydrate antigen 19-9 > 37 U/ml, tumor size > 5 cm, and an ill-defined tumor boundary. Integrating these predictors, the nomogram exerted a favorable diagnostic performance with areas under the ROC curve of 0.767 (95% confidence interval [CI] 0.654–0.881) in the development cohort, and 0.760 (95% CI 0.591–0.929) in the validation cohort. In the RFS analysis, significant differences were observed between the high- and low-risk MVI groups (6-month RFS rates: 64.5% vs. 78.8% and 46.7% vs. 82.4% in the development and validation cohorts, respectively) (P < 0.05). Conclusions: A nomogram based on clinical and MRI features is a potential biomarker of MVI and may be a potent method to classify the risk of recurrence in patients with sIMCC. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the potential of radiomics analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in preoperatively predicting microvascular invasion (MVI) in patients with combined hepatocellular-cholangiocarcinoma (cHCC-CC) before surgery. Methods: A cohort of 91 patients with histologically confirmed cHCC-CC who underwent preoperative liver DCE-MRI were enrolled and divided into a training cohort (27 MVI-positive and 37 MVI-negative) and a validation cohort (11 MVI-positive and 16 MVI-negative). Clinical characteristics and MR features of the patients were evaluated. Radiomics features were extracted from DCE-MRI, and a radiomics signature was built using the least absolute shrinkage and selection operator (LASSO) algorithm in the training cohort. Prediction performance of the developed radiomics signature was evaluated by utilizing the receiver operating characteristic (ROC) analysis. Results: Larger tumor size and higher Radscore were associated with the presence of MVI in the training cohort (p = 0.026 and < 0.001, respectively), and theses findings were also confirmed in the validation cohort (p = 0.040 and 0.001, respectively). The developed radiomics signature, composed of 4 stable radiomics features, showed high prediction performance in both the training cohort (AUC = 0.866, 95% CI 0.757–0.938, p < 0.001) and validation cohort (AUC = 0.841, 95% CI 0.650–0.952, p < 0.001). Conclusions: The radiomics signature developed from DCE-MRI can be a reliable imaging biomarker to preoperatively predict MVI in cHCC-CC. [ABSTRACT FROM AUTHOR]

Objective: To investigate the diagnostic value of early dynamic 18F-FDG PET/CT(ED 18F-FDG PET/CT) combined with conventional whole-body 18F-FDG PET/CT(WB 18F-FDG PET/CT) in hepatocellular carcinoma (HCC), as well as the difference of early dynamic blood flow parameters and maximum standardized uptake value (SUVmax) in HCC patients with/without liver cirrhosis or microvascular invasion (MVI). Methods: Twenty-two consecutive patients (mean age 57.8 years) with 28 established HCC lesions (mean size 4.5 cm) underwent a blood flow study with an 18F-FDG dynamic scan divided into 24 sequences of 5 s each and a standard PET/CT scan. On the ED PET/CT study, an experienced PET/CT physician obtained volumes of interest (VOIs) where three blood flow estimates (time to peak [TTP], blood flow [BF], and hepatic perfusion index [HPI]) were calculated. On the WB PET/CT study, a VOI was placed on the fused scan for each HCC and maximum standardized uptake value (SUVmax) was obtained. Comparison of blood flow estimates, SUVmax, and tumor/background ratio (TNR) was performed among HCCs with and without angioinvasion, as well as HCCs in cirrhotic and non-cirrhotic liver. Results: Compared with WB 18F-FDG PET/CT alone, ED combined with WB 18F-FDG PET/CT can significantly increase the detection rate of moderately differentiated and poorly differentiated HCCs (both P < 0.05). HPI was higher in HCCs in patients with liver cirrhosis than those without liver cirrhosis (P = 0.044). There was no significant difference in TTP, BF, SUVmax, or TNR between HCCs in patients with liver cirrhosis and those without liver cirrhosis. There was no significant difference in blood flow estimates or SUVmax in background liver parenchyma between patients with and those without cirrhosis. TTP was shorter in HCCs with MVI than without MVI (P = 0.046). There was no significant difference in BF, HPI, SUVmax, or TNR between HCCs with MVI and without MVI. There was no significant difference in blood flow estimates or SUVmax in background liver parenchyma between patients with and those without MVI. Conclusion: ED combined with WB 18F-FDG PET/CT can significantly increase the detection rate of moderately differentiated and poorly differentiated HCCs. HPI was significantly higher in HCCs in patients with liver cirrhosis than those without liver cirrhosis. TTP was significantly shorter in HCCs with MVI than without MVI. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this retrospective study was to develop and validate a preoperative nomogram for predicting microvascular invasion (MVI) in patients with intrahepatic mass-forming cholangiocarcinoma (IMCC) based on magnetic resonance imaging (MRI). Methods: In this retrospective study, 224 consecutive patients with clinicopathologically confirmed IMCC were enrolled. Patients whose data were collected from February 2010 to December 2020 were randomly divided into the training (131 patients) and internal validation (51 patients) datasets. The data from January 2021 to November 2021 (42 patients) were allocated to the time-independent validation dataset. Univariate and multivariate forward logistic regression analyses were used to identify preoperative MRI features that were significantly related to MVI, which were then used to develop the nomogram. We used the area under the receiver operating characteristic curve (AUC) and calibration curve to evaluate the performance of the nomogram. Results: Interobserver agreement of MRI qualitative features was good to excellent, with κ values of 0.613–0.882. Multivariate analyses indicated that the following variables were independent predictors of MVI: multiple tumours (odds ratio [OR]) = 4.819, 95% confidence interval [CI] 1.562–14.864, P = 0.006), ill-defined margin (OR = 6.922, 95% CI 2.883–16.633, P < 0.001), and carbohydrate antigen 19–9 (CA 19–9) > 37 U/ml (OR = 2.890, 95% CI 1.211–6.897, P = 0.017). A nomogram incorporating these factors was established using well-fitted calibration curves. The nomogram showed good diagnostic efficacy for MVI, with AUC values of 0.838, 0.819, and 0.874 for the training, internal validation, and time-independent validation datasets, respectively. Conclusion: A nomogram constructed using independent factors, namely the presence of multiple tumours, ill-defined margins, and CA 19–9 > 37 U/ml could predict the presence of MVI. This can facilitate personalised therapeutic strategy and clinical management in patients with IMCC. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to analyze imaging features based on preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the identification of vessels encapsulating tumor clusters (VETC)-microvascular invasion (MVI) in hepatocellular carcinoma (HCC), VM-HCC pattern. Methods: Patients who underwent hepatectomy and preoperative DCE-MRI between January 2015 and March 2021 were retrospectively analyzed. Clinical and imaging features related to VM-HCC (VETC + /MVI-, VETC-/MVI +, VETC + /MVI +) and Non-VM-HCC (VETC-/MVI-) were determined by multivariable logistic regression analyses. Early and overall recurrence were determined using the Kaplan–Meier survival curve. Indicators of early and overall recurrence were identified using the Cox proportional hazard regression model. Results: In total, 221 patients (177 men, 44 women; median age, 60 years; interquartile range, 52–66 years) were evaluated. The multivariable logistic regression analyses revealed fetoprotein > 400 ng/mL (odds ratio [OR] = 2.17, 95% confidence interval [CI] 1.07, 4.41, p = 0.033), intratumor vascularity (OR 2.15, 95% CI 1.07, 4.31, p = 0.031), and enhancement pattern (OR 2.71, 95% CI 1.17, 6.03, p = 0.019) as independent predictors of VM-HCC. In Kaplan–Meier survival analysis, intratumor vascularity was associated with early and overall recurrence (p < 0.05). Conclusion: Based on DCE-MRI, intratumor vascularity can be used to characterize VM-HCC and is of prognostic significance for recurrence in patients with HCC. [ABSTRACT FROM AUTHOR]

Purpose: Evaluation of perfusion CT and dual-energy CT (DECT) quantitative parameters for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) prior to surgery. Methods: This prospective single-center study included fifty-six patients (44 men; median age 67; range 31–84) who provided written informed consent. Inclusion criteria were (1) treatment-naïve patients with a diagnosis of HCC, (2) an indication for hepatic resection, and (3) available arterial DECT phase and perfusion CT (GE revolution HD-GSI). Iodine concentrations (IC), arterial density (AD), and 9 quantitative perfusion parameters for HCC were correlated to pathological results. Radiological parameters based principal component analysis (PCA), corroborated by unsupervised heatmap classification, was meant to deliver a model for predicting MVI in HCC. Survival analysis was performed using univariable log-rank test and multivariable Cox model, both censored at time of relapse. Results: 58 HCC lesions were analyzed (median size 42.3 mm; range of 20–140). PCA showed that the radiological model was predictive of tumor grade (p = 0.01), intratumoral MVI (p = 0.004), peritumoral MVI (p = 0.04), MTM (macrotrabecular-massive) subtype (p = 0.02), and capsular invasion (p = 0.02) in HCC. Heatmap classification of HCC showed tumor heterogeneity, stratified into three main clusters according to the risk of relapse. Survival analysis confirmed that permeability surface-area product (PS) was the only significant independent parameter, among all quantitative tumoral CT parameters, for predicting a risk of relapse (Cox p value = 0.004). Conclusion: A perfusion CT and DECT-based quantitative imaging profile can provide a diagnosis of histological MVI in HCC. PS is an independent parameter for relapse. Clinical trials: ClinicalTrials.gov: NCT03754192. [ABSTRACT FROM AUTHOR]

Purpose: To investigate whether systemic inflammatory biomarkers compared with the imaging features interpreted by radiologists can offer complementary value for predicting the risk of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). Methods: A total of 156 patients with histologically confirmed HCC between Jan 2018 and Dec 2020 were retrospectively enrolled in the primary cohort. Preoperative clinical-inflammatory biomarkers and MR imaging of the patients were recorded and then evaluated as an inflammatory score (Inflam-score) and imaging feature score (Radio-score). Six Inflam-scores and 12 Radio-scores were determined from each patient by univariate analysis. Logistic regression was performed to select risk factors for MVI and establish a predictive nomogram. Decision curve analysis was applied to estimate the incremental value of the Inflam-score to the Radio-score for predicting MVI. Results: Four Radio-scores and 2 Inflam-scores, namely, larger tumor size, non-smooth tumor margin, presence of satellite nodules, presence of peritumoral enhance, higher neutrophil–lymphocyte ratio (NLR), and lower prognostic nutritional index (PNI), were significantly associated with MVI (p < 0.05). An MVI risk prediction nomogram was then constructed with an area under the curve (AUC) of 0.868 (95% CI 0.806–0.931). Adding Inflam-scores to Radio-scores improved the sensitivity of the model from 60.9 to 80.4% in receiver operating characteristic (ROC) curve analysis and led to a net benefit in decision curve analysis. Conclusion: Systemic inflammatory biomarkers are complementary tools that provide additional benefit to conventional imaging estimation for predicting MVI in HCC patients. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the predictive value of gadoxetic acid-enhanced MRI features (focused on Liver Imaging Reporting and Data System (LI-RADS) v2018 features and non-LI-RADS imaging features) for microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Methods: From October 2018 to December 2020, 134 patients who underwent gadoxetic acid-enhanced MRI with a pathological diagnosis of HCC after hepatectomy were enrolled in this retrospective study. Two radiologists assessed the pre-hepatectomy LI-RADS v2018 imaging features and non-LI-RADS features to identify independent predictors of MVI of HCC with a logistic regression model. Results: Four MRI features were found to be independent predictors of MVI: corona enhancement [odds ratio (OR) 5.787; 95% confidence interval (CI) 1.180, 28.369; p = 0.030], mosaic architecture (OR 7.097; 95% CI 1.299, 38.783; p = 0.024), nonsmooth tumor margin (OR 13.131; 95% CI 3.950, 43.649; p < 0.001), and peritumoral hypointensity on hepatobiliary phase (HBP) (OR 33.123; 95% CI 2.897, 378.688; p = 0.005). When one of four imaging features was present, the sensitivity was 93.2% (41/44), and the specificity was 71.1% (64/90). Conclusion: The four imaging features including corona enhancement, mosaic architecture, nonsmooth tumor margin, and peritumoral hypointensity on HBP can be used as preoperative imaging biomarkers for predicting MVI in patients at high risk for HCC. When one of the four imaging features is present, MVI can be predicted with a sensitivity > 90%. [ABSTRACT FROM AUTHOR]

Purpose: Microvascular invasion (MVI), which is difficult to diagnose before surgery, is a major factor affecting postoperative recurrence in patients with hepatocellular carcinoma (HCC). The relationship between the radiological tumor capsule and MVI is controversial. This study aimed to evaluate the association between the tumor capsule and MVI. Methods: We searched Medline (by PubMed) and Embase (by OvidSP). Two review authors independently screened titles and abstracts, selected studies about MVI prediction with radiologic tumor capsule and studies with enough data for extracted, assessed the methodological quality and collected data. Summary results were presented as the diagnostic odds ratio (DOR), sensitivity, specificity, and 95% confidence interval. Results: Fifteen studies with 2038 patients were included; fourteen studies, including 1331 patients, with no significant heterogeneity indicated no relationship between absent tumor capsule and MVI [DOR = 0.90 (0.64, 1.26)]. Six studies, including 541 patients, with no significant heterogeneity showed incomplete capsule could be used to predict MVI of HCC preoperatively [DOR = 1.85 (1.13, 3.04)]. The overall sensitivity and specificity estimate were 0.50 (0.37, 0.64) and 0.64 (0.53, 0.74), respectively. Eight studies, including 1349 patients, with highly significant heterogeneity revealed that complete capsule could be a protective factor for MVI [DOR = 1.97 (1.01, 3.86)]. Conclusions: For MVI of HCC, incomplete tumor capsule is a risk factor, while a complete tumor capsule might be a protective factor. However, absent capsule doesn't show significant relationship with MVI. This might be due to combination of the risk and protective effects of present capsule in MVI. [ABSTRACT FROM AUTHOR]

Purpose: To assess major and ancillary parameters that could be correlated with Microvascular Invasion (MIV) and with histologic grade of HCC. Materials and methods: In this retrospective study, we assessed 62 patients (14 women–48 men; mean age, 63 years; range 38–80 years) that underwent hepatic resection for HCC. All patients were subject to Multidetector computed tomography (MDCT); 40 to Magnetic Resonance (MR) study. The radiologist assessed major and ancillary features according to LIRADS (v. 2018) and reported any radiological accessory findings if detected. Results: No major feature showed statistically significant differences and correlation with grading. Mean ADC value was correlated with grading and with MIV status. No major feature was correlated to MIV; progressive contrast enhancement and satellite nodules showed statistically different percentages with respect to the presence of MIV, so as at the monovariate correlation analysis, satellite nodules were correlated with the presence of MIV. At multivariate regression analysis, no factor proved to be strong predictors of grading while progressive contrast enhancement and satellite nodules were significantly associated with the MIV. Conclusion: Mean ADC value is correlated to HCC grading and MIV status. Progressive contrast enhancement and the presence of satellite nodules are correlated to MIV status. [ABSTRACT FROM AUTHOR]

Purpose: To investigate whether pre-operative gadoxetic acid-enhanced MRI can predict early recurrence after curative resection of single HCC using image features and texture analysis.Materials and methods: 179 patients with single HCC and who underwent pre-operative MRI were included. Two reviewers analyzed MR findings, including the tumor margin, peritumoral enhancement, peritumoral hypointensity on the hepatobiliary phase (HBP), diffusion restriction, capsule, tumoral fat, washout, portal-vein thrombus, signal intensity on HBP, and satellite nodule. Texture analysis on the HBP was also quantified. A multivariate analysis was used to identify predictive factors for early recurrence, microvascular invasion (MVI), and the tumor grade.Results: For early recurrence, satellite nodule, peritumoral hypointensity, absence of capsule, and GLCM ASM were predictors (P < 0.05). For MVI, satellite nodule, peritumoral hypointensity, washout, and sphericity were predictors (P < 0.05). Satellite nodules, peritumoral hypointensity, diffusion restriction, and iso to high signal intensity on HBP were predictor for higher tumor grade (P < 0.05). Satellite nodules and peritumoral hypointensity were important showed common predictors for early recurrence, MVI, and grade (P < 0.05). The sensitivity and specificity for satellite nodule were 47.36% and 96.25%. When added texture variables to MRI findings, the diagnostic performance for predicting early recurrence is improved from 0.7 (SD 0.604-0.790) to 0.83 (SD 0.787-0.894).Conclusion: MR finding, including satellite nodule and peritumoral hypointensity on the HBP, as well as the texture parameters are useful to predict not only early recurrence, but also MVI and higher grade. [ABSTRACT FROM AUTHOR]

Background: Histologic microvascular invasion (MVI) substantially worsens the prognosis of patients with hepatocellular carcinoma, and can only be diagnosed postoperatively. Preoperative assessment of MVI by imaging has been focused on tumor-related features, while peritumoral imaging features have been indicated elsewhere to be more accurate. The aim of the present study is to evaluate the association between peritumoral imaging features and MVI.Methods: Literature search was performed using the PubMed, Embase, and Cochrane Library databases. Summary results of the association between peritumoral imaging features and MVI were presented as the odds ratio (OR) and the 95% confidence interval. Meta-regression and subgroup analyses were performed when heterogeneity was detected. Diagnostic accuracy analysis was also conducted for identified features.Results: Ten studies were included in the analysis. Moderate and low heterogeneities were found among the seven studies on peritumoral enhancement and four studies on peritumoral hypointensity on HBP, respectively. Summary results revealed a significant association between MVI and peritumoral enhancement (OR 4.04 [2.23, 7.32], p < 0.05), and peritumoral hypointensity on HBP (OR 10.62 [5.31, 21.26], p < 0.05). Diagnostic accuracy analysis revealed high specificity (0.90-0.94) but low sensitivity (0.29-0.40) for both features to assess MVI.Conclusion: The two peritumoral imaging features are significantly associated with MVI. The two features highly suggest MVI only when present with a high false negative rate. Promotion of their diagnostic efficiency can be a worthwhile task for future research. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate whether ADC similarity can predict microvascular invasion (MVI) in patients with bifocal hepatocellular carcinoma (HCC).Materials and Methods: Between January 2015 and September 2015, 51 patients with two HCC lesions were included. All patients underwent conventional magnetic resonance imaging including diffusion-weighted imaging (DWI) before the HCC lesions were surgically resected; the tumor specimens were examined histopathologically. Similarity between two HCC lesions regarding DWI signal intensity (SI) and ADC value was calculated as the difference between the two lesions: Value Similarity = [1-(|valuelarge lesion-valuesmall lesion|)/(valuelarge lesion + valuesmall lesion)] × 100%. Univariate and multivariate logistic regression analyses were performed to assess the presence of MVI.Results: Risk factors significantly related to MVI of bifocal HCC in univariate analysis were cirrhosis (P = 0.010), histological grade (P = 0.040), DWI SI similarity (P = 0.027) and ADC similarity (P = 0.003). In multivariate analysis, cirrhosis (odds ratio 0.068, P = 0.022) and ADC similarity (odds ratio 1.204, P = 0.008) were independent risk factors for MVI of bifocal HCC.Conclusion: In patients with two HCC lesions, highly similar ADC values for the two HCC lesions may be a preoperative predictor of MVI. [ABSTRACT FROM AUTHOR]

Purpose: This study was to evaluate the role of quantitative perfusion analysis of 3-dimensional (3D) contrast-enhanced ultrasound (CEUS) in detecting microvascular invasion (MVI) of liver tumor in vivo. Methods: VX2 tumors were implanted in the livers of sixteen New Zealand rabbits. On day 10, real-time 3D CEUS was performed, and the real-time dynamic images were analyzed using online quantification software. The animals were sacrificed and sent for pathology examinations. According to the gold standard of pathology, the animals were divided into an MVI group and a group without MVI (non-MVI group). Time-intensity curves (TICs) were obtained for the VX2 tumors and the surrounding liver parenchyma, and the parameters peak intensity (PI), mean transit time (MTT), and time to peak (TTP) were compared within and between the MVI and non-MVI groups. Results: The TTP and MTT of the VX2 tumors were significantly faster than those of the surrounding liver parenchyma in both MVI and non-MVI groups. The PI of the VX2 tumors was significantly lower than that of the surrounding liver parenchyma in the non-MVI group but not the MVI group. The TTP and MTT of the VX2 tumors and surrounding liver parenchyma were not significantly different in the MVI group compared with the non-MVI group, whereas the ΔPI (the PI ratio between the VX2 liver tumors and the reference liver parenchyma) of the VX2 tumors in the MVI group was larger than that in the non-MVI group. VX2 tumors with MVI present different hemodynamic parameters, with a larger ΔPI than tumors without MVI. Conclusions: Our data suggest that quantitative perfusion analysis of 3D CEUS might be a promising method for predicting MVI in liver tumors. [ABSTRACT FROM AUTHOR]