Prediction of microvascular invasion of hepatocellular carcinoma with preoperative diffusion-weighted imaging: A comparison of mean and minimum apparent diffusion coefficient values

Preoperative and postoperative MRI-based models versus clinical staging systems for predicting early recurrence in hepatocellular carcinoma

BACKGROUND

To predict the early recurrence of HCC patients who received radical resection using preoperative variables based on Gd-EOB-DTPA enhanced MRI, followed by the comparison with the postoperative model and clinical staging systems.

METHODS

One hundred and twenty-nine HCC patients who received radical resection were categorized into the early recurrence group (n = 48) and the early recurrence-free group (n = 81). Through COX regression analysis, statistically significant variables of laboratory, pathologic, and Gd-EOB-DTPA enhanced MRI results were identified. The preoperative and postoperative models were established to predict early recurrence, and the prognostic performances and differences were compared between the two models and clinical staging systems.

RESULTS

Six variables were incorporated into the preoperative model, including alpha-fetoprotein (AFP) level, aspartate aminotransferase/platelet ratio index (APRI), rim arterial phase hyperenhancement (rim APHE), peritumoral hypointensity on hepatobiliary phase (HBP), CERHBP (tumor-to-liver SI ratio on hepatobiliary phase imaging), and ADC value. Moreover, the postoperative model was developed by adding microvascular invasion (MVI) and histological grade. The C-index of the preoperative model and postoperative model were 0.889 and 0.901 (p = 0.211) respectively. Using receiver operating characteristic curve analysis (ROC) and decision curve analysis (DCA), it was determined that the innovative models we developed had superior predictive capabilities for early recurrence in comparison to current clinical staging systems. HCC patients who received radical resection were stratified into low-, medium-, and high-risk groups on the basis of the preoperative and postoperative models.

CONCLUSION

The preoperative and postoperative MRI-based models built in this study were more competent compared with clinical staging systems to predict the early recurrence in hepatocellular carcinoma.

Preoperative prediction of VETC in hepatocellular carcinoma using non-Gaussian diffusion-weighted imaging at high b values: a pilot study

Background

Vessels encapsulating tumor clusters (VETC) have been considered an important cause of hepatocellular carcinoma (HCC) metastasis.

Purpose

To compare the potential of various diffusion parameters derived from the monoexponential model and four non-Gaussian models (DKI, SEM, FROC, and CTRW) in preoperatively predicting the VETC of HCC.

Methods

86 HCC patients (40 VETC-positive and 46 VETC-negative) were prospectively enrolled. Diffusion-weighted images were acquired using six b-values (range from 0 to 3000 s/mm2). Various diffusion parameters derived from diffusion kurtosis (DK), stretched-exponential (SE), fractional-order calculus (FROC), and continuous-time random walk (CTRW) models, together with the conventional apparent diffusion coefficient (ADC) derived from the monoexponential model were calculated. All parameters were compared between VETC-positive and VETC-negative groups using an independent sample t-test or Mann-Whitney U test, and then the parameters with significant differences between the two groups were combined to establish a predictive model by binary logistic regression. Receiver operating characteristic (ROC) analyses were used to assess diagnostic performance.

Results

Among all studied diffusion parameters, only DKI_K and CTRW_α significantly differed between groups (P=0.002 and 0.004, respectively). For predicting the presence of VETC in HCC patients, the combination of DKI_K and CTRW_α had the larger area under the ROC curve (AUC) than the two parameters individually (AUC=0.747 vs. 0.678 and 0.672, respectively).

Conclusion

DKI_K and CTRW_α outperformed traditional ADC for predicting the VETC of HCC.

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, β, 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 (β), 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 β 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, β, and ADC between the MVI-positive and MVI-negative groups. MVI-positive HCCs showed significantly higher β 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 β demonstrated the largest area under the ROC curve (0.920) compared with individual parameters (D: 0.912; β: 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.

Diagnostic Accuracy of the Apparent Diffusion Coefficient for Microvascular Invasion in Hepatocellular Carcinoma: A Meta-analysis

BACKGROUND AND AIMS

Microvascular invasion (MVI) is a major risk factor for the early recurrence of hepatocellular carcinoma (HCC) and it seriously worsens the prognosis. Accurate preoperative evaluation of the presence of MVI could greatly benefit the treatment management and prognosis prediction of HCC patients. The study aim was to evaluate the diagnostic performance of the apparent diffusion coefficient (ADC), a quantitative parameter for the preoperative diagnosis MVI in HCC patients.

METHODS

Original articles about diffusion-weighted imaging (DWI) and/or intravoxel incoherent motion (IVIM) conducted on a 3.0 or 1.5 Tesla magnetic resonance imaging (MRI) system indexed through January 17, 2021were collected from MEDLINE/PubMed, Web of Science, EMBASE, and the Cochrane Library. Methodological quality was evaluated using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). The pooled sensitivity, specificity, and summary area under the receiver operating characteristic curve (AUROC) were calculated, and meta-regression analysis was performed using a bivariate random effects model through a meta-analysis.

RESULTS

Nine original articles with a total of 988 HCCs were included. Most studies had low bias risk and minimal applicability concerns. The pooled sensitivity, specificity and AUROC of the ADC value were 73%, 70%, and 0.78, respectively. The time interval between the index test and the reference standard was identified as a possible source of heterogeneity by subgroup meta-regression analysis.

CONCLUSIONS

Meta-analysis showed that the ADC value had moderate accuracy for predicting MVI in HCC. The time interval accounted for the heterogeneity.

The clinical value of dual-energy computed tomography and diffusion-weighted imaging in the context of liver cancer: A narrative review

The dual-energy computed tomography (DECT) and diffusion-weighted magnetic resonance imaging (DWI-MRI) are used to diagnose liver cancer. The clinical value of these two examination methods needs to be further summarized. We collected and summarized relevant literature published from 2011 to 2021. The diagnostic performance of DECT was assessed between conventional computed tomography and DWI-MRI. DWI-MRI had a 69% sensitivity for detecting small hepatocellular carcinoma (HCC) lesions and a 60% diagnostic specificity for differentiating between types of HCC lesions. DECT had a sensitivity to small liver lesions (<1 cm) of 69%, and the diagnostic specificity for HCC and metastasis was about 60%. DWI was more sensitive (90.3% vs. 74.9%) and accurate (91.9% vs. 76.9%) in diagnosing HCC compared with conventional MRI sequencing. With the aid of contrast media, DWI-MRI had 90.0% specificity for detecting small HCCs (smaller than 1 cm). Furthermore, DWI-MRI not only provided physicians with valuable diagnostic information but also delivered histological grading information, with 78% accuracy for all benign lesions and 71% for solid lesions. DECT had relatively high sensitivity and required a lower contrast medium dose. With standardized quantitative parameters, it can be an extremely useful tool for HCC surveillance. DWI-MRI is the preferred imaging process as it produces high-contrast images for supporting an early diagnosis (high sensitivity and specificity) and provides histological information using non-ionizing radiation.

A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI

Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is a histopathological marker and risk factor for HCC recurrence. We integrated diffusion-weighted imaging (DWI) and magnetic resonance (MR) image findings of tumors into a scoring system for predicting MVI. In total, 228 HCC patients with pathologically confirmed MVI who underwent surgical resection or liver transplant between November 2012 and March 2021 were enrolled retrospectively. Patients were divided into a right liver lobe group (n = 173, 75.9%) as the model dataset and a left liver lobe group (n = 55, 24.1%) as the model validation dataset. Multivariate logistic regression identified two-segment involved tumor (Score: 1; OR: 3.14; 95% CI: 1.22 to 8.06; p = 0.017); ADC_min ≤ 0.95 × 10⁻³ mm²/s (Score: 2; OR: 10.88; 95% CI: 4.61 to 25.68; p = 0.000); and largest single tumor diameter ≥ 3 cm (Score: 1; OR: 5.05; 95% CI: 2.25 to 11.30; p = 0.000), as predictive factors for the scoring model. Among all patients, sensitivity was 89.66%, specificity 58.04%, positive predictive value 68.87%, and negative predictive value 84.41%. For validation of left lobe group, sensitivity was 80.64%, specificity 70.83%, positive predictive value 78.12%, and negative predictive value 73.91%. The scoring model using ADC_min, largest tumor diameter, and two-segment involved tumor provides high sensitivity and negative predictive value in MVI prediction for use in routine functional MR.

The Roles of Diffusion Kurtosis Imaging and Intravoxel Incoherent Motion Diffusion-Weighted Imaging Parameters in Preoperative Evaluation of Pathological Grades and Microvascular Invasion in Hepatocellular Carcinoma

Background

Currently, there are disputes about the parameters of diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), and diffusion-weighted imaging (DWI) in predicting pathological grades and microvascular invasion (MVI) in hepatocellular carcinoma (HCC). The aim of our study was to investigate and compare the predictive power of DKI and IVIM-DWI parameters for preoperative evaluation of pathological grades and MVI in HCC.

Methods

PubMed, Web of Science, and Embase databases were searched for relevant studies published from inception to October 2021. Review Manager 5.3 was used to summarize standardized mean differences (SMDs) of mean kurtosis (MK), mean diffusivity (MD), tissue diffusivity (D), pseudo diffusivity (D*), perfusion fraction (f), mean apparent diffusion coefficient (ADCmean), and minimum apparent diffusion coefficient (ADCmin). Stata12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC). Overall, 42 up-to-standard studies with 3,807 cases of HCC were included in the meta-analysis.

Results

The SMDs of ADCmean, ADCmin, and D values, but not those of D* and f values, significantly differed between well, moderately, and poorly differentiated HCC (P < 0.01). The sensitivity, specificity, and AUC of the MK, D, ADCmean, and ADCmin for preoperative prediction of poorly differentiated HCC were 69%/94%/0.89, 87%/80%/0.89, 82%/75%/0.86, and 83%/64%/0.81, respectively. In addition, the sensitivity, specificity, and AUC of the D and ADCmean for preoperative prediction of well-differentiated HCC were 87%/83%/0.92 and 82%/88%/0.90, respectively. The SMDs of ADCmean, ADCmin, D, MD, and MK values, but not f values, showed significant differences (P < 0.01) between MVI-positive (MVI+) and MVI-negative (MVI-) HCC. The sensitivity and specificity of D and ADCmean for preoperative prediction of MVI+ were 80%/80% and 74%/71%, respectively; the AUC of the D (0.87) was significantly higher than that of ADCmean (0.78) (Z = −2.208, P = 0.027). Sensitivity analysis showed that the results of the above parameters were stable and reliable, and subgroup analysis confirmed a good prediction effect.

Conclusion

DKI parameters (MD and MK) and IVIM-DWI parameters (D value, ADCmean, and ADCmin) can be used as a noninvasive and simple preoperative examination method to predict the grade and MVI in HCC. Compared with ADCmean and ADCmin, MD and D values have higher diagnostic efficacy in predicting the grades of HCC, and D value has superior diagnostic efficacy to ADCmean in predicting MVI+ in HCC. However, f value cannot predict the grade or MVI in HCC.

The Benefit of Apparent Diffusion Coefficient in Evaluating the Invasiveness of Hepatocellular Carcinoma

Background

This study aimed to evaluate hepatocellular carcinoma (HCC) invasiveness using the apparent diffusion coefficient (ADC).

Methods

Eighty-one patients with HCC confirmed by pathology and examined by preoperative magnetic resonance imaging diffusion-weighted imaging from January 2015 to September 2020 were retrospectively analyzed. Clinical and pathological data were recorded. The minimum ADC (ADCmin), average ADC (ADCmean), and the ratio of ADCmean to normal-appearing hepatic parenchyma ADC (ADCnahp) were assessed. The associations between clinical information, ADC value, and HCC invasiveness (microvascular invasion [MVI], tumor differentiation, and Ki-67 expression) were evaluated statistically. Independent risk factors related to HCC invasiveness were screened using binary logistic regression, and the diagnostic efficiency was evaluated by the receiver operating characteristic curve and its area under the curve (AUC) value.

Results

Tumor size was related to HCC MVI and tumor differentiation (P < 0.05). HCC MVI was associated with ADCmin, ADCmean, and the ADCmean-to-ADCnahp ratio (all P < 0.05) with AUC values of 0.860, 0.860, and 0.909, respectively. If these were combined with tumor size, the AUC value increased to 0.912. The degree of tumor differentiation was associated with ADCmin, ADCmean, and the ADCmean-to-ADCnahp ratio (all P < 0.05) with AUC values of 0.719, 0.708, and 0.797, respectively. If these were combined with tumor size, the AUC value increased to 0.868. Ki-67 expression was associated with ADCmin, ADCmean, and the ADCmean-to-ADCnahp ratio (all P < 0.05) with AUC values of 0.731, 0.747, and 0.746, respectively. Combined them, the AUC value increased to 0.763.

Conclusions

The findings indicated that the ADC value has significant potential for the non-invasive preoperative evaluation of HCC invasiveness.

Quantitative magnetic resonance imaging for focal liver lesions: bridging the gap between research and clinical practice

Magnetic resonance imaging (MRI) is highly important for the detection, characterization, and follow-up of focal liver lesions. Several quantitative MRI-based methods have been proposed in addition to qualitative imaging interpretation to improve the diagnostic work-up and prognostics in patients with focal liver lesions. This includes DWI with apparent diffusion coefficient measurements, intravoxel incoherent motion, perfusion imaging, MR elastography, and radiomics. Multiple research studies have reported promising results with quantitative MRI methods in various clinical settings. Nevertheless, applications in everyday clinical practice are limited. This review describes the basic principles of quantitative MRI-based techniques and discusses the main current applications and limitations for the assessment of focal liver lesions.

Magnetic resonance imaging and diffusion-weighted imaging-based histogram analyses in predicting glypican 3-positive hepatocellular carcinoma

PURPOSE

We aimed to investigate the potential MR imaging findings in predicting glypican-3 (GPC3)-positive hepatocellular carcinomas (HCCs), with special emphasis on diffusion-weighted imaging (DWI)-based histogram analyses.

METHODS

Forty-three patients with pathologically-confirmed GPC3-negative HCCs and 100 patients with GPC3-positive HCCs were retrospectively evaluated using contrast-enhanced MRI and DWI. Clinical characteristics and MRI features including DWI-based histogram features were assessed and compared between the two groups. Univariate and multivariate analyses were used to identify the significant clinico-radiologic variables associated with GPC3 expressions that were then incorporated into a predictive nomogram. Nomogram performance was evaluated based on calibration, discrimination, and decision curve analyses.

RESULTS

Features significantly related to GPC3-positive HCCs at univariate analyses were serum alpha-fetoprotein (AFP) levels >20 ng/mL (P < 0.0001), absence of enhancing capsule (P = 0.040), peritumoral enhancement appearance on the arterial phase (P = 0.049), as well as lower mean (P = 0.0278), median (P = 0.0372) and 75th percentile (P = 0.0085) apparent diffusion coefficient (ADC) values. At multivariate analysis, the AFP levels (odds ratio, 11.236; P < 0.0001) and 75th percentile ADC values (odds ratio, 1.009; P = 0.033) were independent risk factors associated with GPC3-positive HCCs. When both criteria were combined, both sensitivity (79.0 %) and specificity (79.1 %) greater than 75 % were achieved, and satisfactory predictive nomogram performance was obtained with a C-index of 0.804 (95 % confidence interval, 0.729-0.866). Decision curve analysis further confirmed the clinical usefulness of the nomogram.

CONCLUSIONS

Elevated serum AFP levels and lower 75th percentile ADC values were helpful in differentiating GPC3-positive and GPC3-negative HCCs. The combined nomogram achieved satisfactory preoperative risk prediction of GPC3 expression in HCC patients.

MRI Features for Predicting Microvascular Invasion of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

PURPOSE

Microvascular invasion (MVI) is an important prognostic factor in patients with hepatocellular carcinoma (HCC). However, the reported results of magnetic resonance imaging (MRI) features for predicting MVI of HCC are variable and conflicting. Therefore, this meta-analysis aimed to identify the significant MRI features for MVI of HCC and to determine their diagnostic value.

METHODS

Original studies reporting the diagnostic performance of MRI for predicting MVI of HCC were identified in MEDLINE and EMBASE up until January 15, 2020. Study quality was assessed using QUADAS-2. A bivariate random-effects model was used to calculate the meta-analytic pooled diagnostic odds ratio (DOR) and 95% confidence interval (CI) for each MRI feature for diagnosing MVI in HCC. The meta-analytic pooled sensitivity and specificity were calculated for the significant MRI features.

RESULTS

Among 235 screened articles, we found 36 studies including 4,274 HCCs. Of the 15 available MRI features, 7 were significantly associated with MVI: larger tumor size (>5 cm) (DOR = 5.2, 95% CI [3.0-9.0]), rim arterial enhancement (4.2, 95% CI [1.7-10.6]), arterial peritumoral enhancement (4.4, 95% CI [2.8-6.9]), peritumoral hypointensity on hepatobiliary phase imaging (HBP) (8.2, 95% CI [4.4-15.2]), nonsmooth tumor margin (3.2, 95% CI [2.2-4.4]), multifocality (7.1, 95% CI [2.6-19.5]), and hypointensity on T1-weighted imaging (T1WI) (4.9, 95% CI [2.5-9.6]). Both peritumoral hypointensity on HBP and multifocality showed very high meta-analytic pooled specificities for diagnosing MVI (91.1% [85.4-94.8%] and 93.3% [74.5-98.5%], respectively).

CONCLUSIONS

Seven MRI features including larger tumor size, rim arterial enhancement, arterial peritumoral enhancement, peritumoral hypointensity on HBP, nonsmooth margin, multifocality, and hypointensity on T1WI were significant predictors for MVI of HCC. These MRI features predictive of MVI can be useful in the management of HCC.

Microvascular Invasion Status and Its Survival Impact in Hepatocellular Carcinoma Depend on Tissue Sampling Protocol

BACKGROUND

The aim of this work is to explore the impact of the number of sampling sites (NuSS) and sampling location on microvascular invasion (MVI) detection rate and long-term survival of hepatocellular carcinoma (HCC), and determine the minimum NuSS for sufficient MVI detection.

PATIENTS AND METHODS

From January 2008 to March 2017, 1144 HCC patients who underwent hepatectomy were retrospectively enrolled. Associations between NuSS and MVI positive rates and overall survival were investigated. NuSS thresholds were determined by Chow test and confirmed prospectively in 305 patients from April 2017 to February 2019. In the prospective cohort, the distribution of MVI in different sampling locations and its prognostic effect was evaluated.

RESULTS

MVI positive rates increased as NuSS increased, steadily reaching a plateau when NuSS reached a threshold. A threshold of four, six, eight, and eight sampling sites within paracancerous parenchyma ≤ 1 cm from tumor was required for detecting MVI in solitary tumors measuring 1.0-3.0, 3.1-4.9, and ≥ 5.0 cm and multiple tumors. Patients with adequate NuSS achieved longer survival than those with inadequate NuSS [hazard ratio (HR) = 0.75, P = 0.043]. For all MVI-positive patients, MVI could be detected positive in paracancerous parenchyma ≤ 1 cm from tumor. Patients with MVI positive in paracancerous parenchyma > 1 cm had higher recurrence risk than those with MVI positive only in parenchyma ≤ 1 cm (HR = 6.05, P < 0.001).

CONCLUSIONS

Adequate NuSS is associated with higher MVI detection rate and better survival of HCC patients. We recommend four, six, eight, and eight as the cut-points for evaluating MVI sampling quality and patients' prognostic stratification in the subgroups of solitary tumors measuring 1.0-3.0 cm, 3.1-4.9 cm and ≥ 5.0 cm and multiple tumors, respectively.

Morphophenotypic Classification of Hepatocellular Carcinoma: the Biliary/Stem Cell Subgroup and Worst Outcome-Implications on Patient Selection

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and the third cause of cancer-related death. Current clinical/pathological criteria contribute to risk stratification, but are far from the desired on individualized medicine. Recently, HCC classifications have been published based on immunohistochemical and morphological features.

METHODS

A retrospective review of patients submitted to surgical treatment-partial hepatectomy (PH) or liver transplantation (LT), with pathological diagnosis of HCC, in a 9-year period (2007-2015) was performed.

RESULTS

Applying the classification of Srivastava et al. (#1), based on the expression of CD31, p53, AFP and CD44, tumour size and presence of vascular invasion, HCC were categorized as low- and high-risk HCC. With the classification of Tsujikawa et al. (#2), HCC were classified into biliary/stem cell marker positive, Wnt signalling positive and the "all negative" HCC, according to the expression of CK19, SALL4, β-catenin glutamine synthetase, EpCAM and p53. There were sixty-six patients (53 males; 13 females), with median age of 64.5 ± 9.46 years (range 38-86), with solitary HCC, comprehending 37 PH (56.1%) and 29 LT (43.9%). The mean overall survival (OS) was 75.4 ± 6.9 months. Biliary/stem cell type of HCC was a predictive factor of worse OS on the overall population (24.4 versus 78.3 months, p = 0.032) and in PH cohort (11.5 versus 64.01 months, p = 0.016), on uni- and multivariate analyses.

CONCLUSION

These results support the relevance of a risk stratification classification of HCC. Classification #2 seems adequate to our reality demonstrating OS impact, allowing its application in future biopsies, prompting individualized medicine.

Diffusion-Weighted Imaging Reflects Tumor Grading and Microvascular Invasion in Hepatocellular Carcinoma

BACKGROUND

To date, there are inconsistent data about relationships between diffusion-weighted imaging (DWI) and tumor grading/microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Our purpose was to systematize the reported results regarding the role of DWI in prediction of tumor grading/MVI in HCC.

METHOD

MEDLINE library, Scopus, and Embase data bases were screened up to December 2019. Overall, 29 studies with 2,715 tumors were included into the analysis. There were 20 studies regarding DWI and tumor grading, 8 studies about DWI and MVI, and 1 study investigated DWI, tumor grading, and MVI in HCC.

RESULTS

In 21 studies (1,799 tumors), mean apparent diffusion coefficient (ADC) values (ADC_mean) were used for distinguishing HCCs. ADC_mean of G1-3 lesions overlapped significantly. In 4 studies (461 lesions), minimum ADC (ADC_min) was used. ADC_min values in G1/2 lesions were over 0.80 × 10^-3 mm²/s and in G3 tumors below 0.80 × 10^-3 mm²/s. In 4 studies (241 tumors), true diffusion (D) was reported. A significant overlapping of D values between G1, G2, and G3 groups was found. ADC_mean and MVI were analyzed in 9 studies (1,059 HCCs). ADC_mean values of MIV+/MVI- lesions overlapped significantly. ADC_min was used in 4 studies (672 lesions). ADC_min values of MVI+ tumors were in the area under 1.00 × 10^-3 mm²/s. In 3 studies (227 tumors), D was used. Also, D values of MVI+ lesions were predominantly in the area under 1.00 × 10^-3 mm²/s.

CONCLUSION

ADC_min reflects tumor grading, and ADC_min and D predict MVI in HCC. Therefore, these DWI parameters should be estimated for every HCC lesion for pretreatment tumor stratification. ADC_mean cannot predict tumor grading/MVI in HCC.

Preoperative Prediction Power of Imaging Methods for Microvascular Invasion in Hepatocellular Carcinoma: A Systemic Review and Meta-Analysis

Background: To compare the predictive power between radiomics and non-radiomics (conventional imaging and functional imaging methods) for preoperative evaluation of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Methods: Comprehensive publications were screened in PubMed, Embase, and Cochrane Library. Studies focusing on the discrimination values of imaging methods, including radiomics and non-radiomics methods, for MVI evaluation were included in our meta-analysis.

Results: Thirty-three imaging studies with 5,462 cases, focusing on preoperative evaluation of MVI status in HCC, were included. The sensitivity and specificity of MVI prediction in HCC were 0.78 [95% confidence interval (CI): 0.75–0.80; I² = 70.7%] and 0.78 (95% CI: 0.76–0.81; I² = 0.0%) for radiomics, respectively, and were 0.73 (95% CI: 0.71–0.75; I² = 83.7%) and 0.82 (95% CI: 0.80–0.83; I² = 86.5%) for non-radiomics, respectively. The areas under the receiver operation curves for radiomics and non-radiomics to predict MVI status in HCC were 0.8550 and 0.8601, respectively, showing no significant difference.

Conclusion: The imaging method is feasible to predict the MVI state of HCC. Radiomics method based on medical image data is a promising application in clinical practice and can provide quantifiable image features. With the help of these features, highly consistent prediction performance will be achieved in anticipation.

The Value of TTPVI in Prediction of Microvascular Invasion in Hepatocellular Carcinoma

Purpose

The objective of our study was to evaluate the value of two-trait predictor of venous invasion (TTPVI) in the prediction of pathological microvascular invasion (pMVI) in patients with hepatocellular carcinoma (HCC) from preoperative computed tomography (CT) and magnetic resonance (MR).

Methods

A total of 128 preoperative patients with findings of HCC were enrolled. Tumor size, tumor margins, tumor capsule, peritumoral enhancement, and TTPVI was assessed on preoperative CT and MRI images. Histopathological features were reviewed: pathological tumor size, tumor differentiation, pMVI along with alpha-fetoprotein level (AFP). Significant imaging findings and histopathological features were determined with univariate and multivariate logistic regression analysis.

Results

Univariate analysis revealed that tumor size (p<0.01), AFP level (p=0.043), tumor differentiation (p<0.01), peritumoral enhancement (p=0.003), pathological tumor size (p<0.01), tumor margins (p<0.01) on CT and MRI, and TTPVI (p<0.01) showed statistically significant associations with pMVI. In multivariate logistic regression analysis, tumor size (odds ratio [OR] = 1.294; 95% confidence interval [CI]: 1.155, 1.451; p < 0.001), tumor differentiation (odds ratio [OR] =1.384; 95% confidence interval [CI]: 1.224, 1.564; p < 0.001), and TTPVI (odds ratio [OR] = 4.802; 95% confidence interval [CI]: 1.037, 22.233; p=0.045) were significant independent predictors of pMVI. Using 5.8 as the threshold for size, one could obtain an area-under-curve (AUC) of 0.793, 95% confidence interval [CI]: 0.715 to 0.857.

Conclusion

Tumor size, tumor differentiation, and TTPVI depicted in preoperative CT and MRI had a statistically significant correlation with pMVI. Hence, TTPVI detected on CT and MRI may be predictive of pMVI in HCC cases.

Microvascular invasion and grading in hepatocellular carcinoma: correlation with major and ancillary features according to LIRADS

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.

Liver Imaging Reporting and Data System Category 5: MRI Predictors of Microvascular Invasion and Recurrence After Hepatectomy for Hepatocellular Carcinoma

OBJECTIVE. We investigated in Liver Imaging Reporting and Data System category 5 (LR-5) observations whether imaging features, including LI-RADS imaging features, could predict microvascular invasion (MVI) and posthepatectomy recurrence in high-risk adult patients with hepatocellular carcinoma (HCC). MATERIALS AND METHODS. We retrospectively identified 149 high-risk patients who underwent 3-T MRI within 1 month before hepatectomy for HCC; 81 of 149 patients with no HCC recurrence were followed for more than 1 year. Tumors with clear surgical margins were confirmed in each hepatectomy specimen. MVI was evaluated histologically by a histopathologist. Tumor recurrence was determined by clinical and imaging follow-up. Two independent radiologists reviewed the prehepatectomy MR images and assessed LI-RADS v2018 imaging features as well as some non-LI-RADS features in all LR-5 observations in consensus. Alpha-fetoprotein level, tumor number, and imaging features were analyzed as potential predictors for MVI and posthepatectomy recurrence using multivariate logistic regression and Cox proportional hazards models. RESULTS. One hundred forty-nine patients with pathologically confirmed HCC were included; 64 of 149 (43.0%) patients had MVI, whereas 48 of 129 (37.2%) patients had tumor recurrence within 3 years after hepatectomy. Mosaic architecture (odds ratio, 3.420; p < 0.001) and nonsmooth tumor margin (odds ratio, 2.554; p = 0.011) were independent predictors of MVI. Multifocal tumors (hazard ratio, 2.101; p = 0.034), absence of fat in mass (hazard ratio, 2.109; p = 0.015), and nonsmooth tumor margin (hazard ratio, 2.415; p = 0.005) were independent predictors of posthepatectomy recurrence. CONCLUSION. In high-risk patients with LR-5 HCC, mosaic architecture and non-smooth tumor margin independently predicted MVI. Multifocal tumors, absence of fat in mass, and nonsmooth tumor margin independently predicted recurrence.

Diffusion kurtosis imaging (DKI) of hepatocellular carcinoma: correlation with microvascular invasion and histologic grade

BACKGROUND

The aim of this study was to prospectively evaluate the diagnostic efficacy of diffusion kurtosis imaging (DKI) in predicting microvascular invasion (MVI) and histologic grade of hepatocellular carcinoma (HCC) with comparison to the conventional diffusion-weighted imaging (DWI).

METHODS

This prospective study was approved by the Institutional Review Board, and written informed consent was obtained from all patients. From September 2015 to January 2017, 74 consecutive HCC patients were enrolled in this study. Preoperative magnetic resonance imaging including DKI protocol was performed, and patients were followed up for at least one year after surgery. Diffusion parameters including the mean corrected apparent diffusion coefficient (MD), mean apparent kurtosis coefficient (MK), and apparent diffusion coefficient (ADC) were calculated. Differences of diffusion parameters among different histopathological groups were compared. For parameters that were significantly different between pathological groups, receiver operating characteristics (ROC) curve analyses were performed to evaluate the diagnostic efficiency for identifying MVI and predicting high-grade HCC. Univariate and multivariate logistic regression analyses were used to evaluate the relative value of clinical and laboratory variables and diffusion parameters as risk factors for early recurrence (≤1 year).

RESULTS

Among all the studied diffusion parameters, only MK differed significantly between the MVI-positive and MVI-negative group (0.91±0.10 vs. 0.82±0.09, P<0.001), and showed moderate diagnostic efficacy (AUC =0.77) for identifying MVI. High-grade HCCs showed significantly higher MK values (0.93±0.10 vs. 0.82±0.09, P<0.001), along with MD (1.34±0.18 vs. 1.54±0.22, P<0.001) and ADC values (1.17±0.15 vs. 1.30±0.16, P=0.001) than low-grade HCCs. For differentiating high-grade from low-grade HCCs, MK demonstrated a higher area under the ROC curve (AUC) and significantly higher specificity than MD and ADC (AUC =0.81 vs. 0.76 and 0.74; specificity =82.2% vs. 60.0% and 60.0%, P=0.02). In addition, higher MK (OR =5.700, P=0.002) and Barcelona Clinic Liver Cancer (BCLC) stage C (OR =6.329, P=0.005) were independent risk factors for early HCC recurrence.

CONCLUSIONS

DKI-derived MK values outperformed conventional ADC values for predicting MVI and histologic grade of HCC, and are associated with increased risk of early tumor recurrence.

A scientometric analysis on hepatocellular carcinoma magnetic resonance imaging research from 2008 to 2017

Background

With the development of new magnetic resonance imaging (MRI) techniques, an increasing number of articles have been published regarding hepatocellular carcinoma magnetic resonance imaging (HCCMRI) in the past decade. However, few studies have statistically analyzed these published articles. In this study, we aim to systematically evaluate the scientific outcomes of HCCMRI research and explore the research hotspots from 2008 to 2017.

Methods

The included articles regarding HCCMRI research from 2008 to 2017 were downloaded from the Web of Science Core Collection and verified by two experienced radiologists. Excel 2016 was used to analyze the literature data, including the publication years and journals. CiteSpace V was used to perform co-occurrence analyses for authors, countries/regions and institutions and to generate the related collaboration network maps. Reference co-citation analysis (RCA) and burst keyword detection were also performed using CiteSpace V to explore the research hotspots in the past decade.

Results

A total of 835 HCCMRI articles published from 2008 to 2017 were identified. Journal of Magnetic Resonance Imaging published the most articles (79 publications, 9.46%). Extensive cooperating relationship were observed among countries/regions and among authors. South Korea had the most publications (199 publications, 21.82%), followed by the United States of America (USA) (190 publications, 20.83%), Japan (162 publications, 17.76%), and the People's Republic of China (148 publications, 16.23%). Among the top 10 co-cited authors, Bruix J (398 citations) was ranked first, followed by Llovet JM (235 citations), Kim YK (170 citations) and Forner A (152 citations). According to the RCA, ten major clusters were explored over the last decade; "LI-RADS data system" and "microvascular invasion" (MVI) were the two most recent clusters. Forty-seven burst keywords with the highest citation strength were detected over time. Of these keywords, "microvascular invasion" had the highest strength in the last 3 years. The LI-RADS has been constantly updated with the latest edition released in July 2018. However, the LI-RADS still has limitations in identifying certain categories of lesions by conceptual and non-quantitative probabilistic methods. Plenty of questions still need to be further answered such as the difference of diagnostic efficiency of each major/ancillary imaging features. Preoperative prediction of MVI of HCC is very important to therapeutic decision-making. Some parameters of Gd-EOB-DTPA-enhanced MRI were found to be useful in prediction of MVI, however, with a high specificity but a very low sensitivity. Comprehensive predictive model incorporating both imaging and clinical variables may be the more preferable in prediction of MVI of HCC.

Conclusions

HCCMRI-related publications displayed a gradually increasing trend from 2008 to 2017. The USA has a central position in collaboration with other countries/regions, while South Korea contributed the most in the number of publications. Of the ten major clusters identified in the RCA, the two most recent clusters were "LI-RADS data system" and "microvascular invasion", indicative of the current HCCMRI research hotspots.

Efficacy of apparent diffusion coefficient in predicting aggressive histological features of papillary thyroid carcinoma

PURPOSE

We aimed to evaluate preoperative diffusion-weighted magnetic resonance imaging (DWI) for predicting aggressive histological features in papillary thyroid cancer (PTC).

METHODS

This prospective study included 141 PTC patients, who underwent DWI prior to thyroidectomy; 88 patients with 88 PTC lesions were finally analyzed. Multiple comparisons of mean and minimum apparent diffusion coefficient (ADC) values (ADCmean and ADCmin) and ADC of the solid component (ADCsolid) between the lowly aggressive PTC, highly aggressive PTC without hobnail, and hobnail variant PTC groups were performed by one-way ANOVA or the Welch test. The nonparametric Kruskal-Wallis H-test was used to assess lesion size differences. Receiver-operating characteristic (ROC) curve analysis was also performed.

RESULTS

ADC values in the lowly aggressive PTC group were found to be significantly higher than those in the highly aggressive PTC without hobnail group (ADCmean: 1.35±0.20×10-3 mm2/s vs. 1.16±0.17×10-3 mm2/s, P = 0.003; ADCmin: 1.10±0.17×10-3 mm2/s vs. 0.88±0.16×10-3 mm2/s, P < 0.001; ADCsolid: 1.26±0.23×10-3 mm2/s vs. 1.04±0.17×10-3 mm2/s, P < 0.001). No significant differences for the ADCmean, ADCmin, and ADCsolid were observed between the lowly aggressive and hobnail variant PTC groups (all P > 0.05). Lesion sizes in the hobnail variant PTC group was significantly elevated compared with the lowly aggressive PTC group (2.19±1.21 cm vs. 0.93±0.37 cm, P < 0.001). Areas under the curves (AUCs) for ADCmean, ADCmin, and ADCsolid between the lowly aggressive PTC and highly aggressive PTC group without hobnail were 0.758, 0.851, and 0.787, respectively. The AUC for size between the lowly aggressive and hobnail variant PTC group was 0.896.

CONCLUSION

ADCmin from DWI could potentially provide quantitative information to differentiate lowly aggressive PTC from highly aggressive PTC lesions without hobnail variants.

Preoperative histogram analysis of intravoxel incoherent motion (IVIM) for predicting microvascular invasion in patients with single hepatocellular carcinoma

PURPOSE

To evaluate the value of intravoxel incoherent motion (IVIM) histogram analysis based on whole tumor volume in predicting microvascular invasion (MVI) of single hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

The study enrolled 41 patients with pathologically proven HCCs who underwent IVIM diffusion-weighted imaging with nine b values and contrast-enhanced magnetic resonance imaging (MRI). Histogram parameters including mean; skewness; kurtosis; and percentiles (5th, 10th, 25th, 50th, 75th, 90th, 95th) were derived from apparent diffusion coefficient (ADC), perfusion fraction (f), true diffusion coefficient (D), and pseudo diffusion coefficient (D*). Quantitative histogram parameters and clinical data were compared between HCCs with and without MVI. For significant parameters, receiver operating characteristic (ROC) curves were further plotted to compare the diagnosis performance for identifying MVI.

RESULTS

The mean, 5th, 10th, 25th, 50th, and 75th percentiles of D, and the 5th, 10th, and 25th percentiles of ADC between HCCs with and without MVI were statistically significant (all P＜0.05). The histogram parameters of D* and f showed no statistically significant differences between HCCs with and without MVI (all P＞0.05). The areas under the ROC curves (AUCs) were 0.707-0.874 for D and 0.668-0.720 for ADC. The largest AUC of D (5th percentile) showed significantly higher accuracy than that of ADC or tumor size (P = 0.009-0.046). With a cut-off of 0.403 × 10^-3 mm²/s, the 5th percentile of D value provided a sensitivity of 81% and a specificity of 85% in the prediction of MVI.

CONCLUSIONS

Histogram analysis of IVIM based on whole tumor volume can be useful for predicting MVI. The 5th percentile of D was most useful value to predict MVI of HCC.

Preoperative prediction of microvascular invasion of hepatocellular carcinoma using 18F-FDG PET/CT: a multicenter retrospective cohort study

PURPOSE

The aim of this study was to assess the potential of tumor ¹⁸F-fluorodeoxyglucose (FDG) avidity as a preoperative imaging biomarker for the prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

METHODS

One hundred and fifty-eight patients diagnosed with Barcelona Clinic Liver Cancer stages 0 or A HCC (median age, 57 years; interquartile range, 50-64 years) who underwent ¹⁸F-FDG positron emission tomography with computed tomography (PET/CT) before curative surgery at seven university hospitals were included. Tumor FDG avidity was measured by tumor-to-normal liver standardized uptake value ratio (TLR) of the primary tumor on FDG PET/CT imaging. Logistic regression analysis was performed to identify significant parameters associated with MVI. The predictive performance of TLR and other clinical variables was assessed using receiver operating characteristic (ROC) curve analysis.

RESULTS

MVI was present in 76 of 158 patients with HCCs (48.1%). Multivariable logistic regression analysis revealed that TLR, serum alpha-fetoprotein (AFP) level, and tumor size were significantly associated with the presence of MVI (P < 0.001). Multinodularity was not significantly associated with MVI (P = 0.563). The area under the ROC curve (AUC) for predicting the presence of MVI was best with TLR (AUC = 0.704), followed by tumor size (AUC = 0.685) and AFP (AUC = 0.670). We were able to build an improved prediction model combining TLR, tumor size, and AFP by using multivariable logistic regression modeling (AUC = 0.756).

CONCLUSIONS

Tumor FDG avidity measured by TLR on FDG PET/CT is a preoperative imaging biomarker for the prediction of MVI in patients with HCC.