Intrahepatic cholangiocarcinoma in the setting of HBV-related cirrhosis: Differentiation with hepatocellular carcinoma by using Intravoxel incoherent motion diffusion-weighted MR imaging

A Pilot Study on Deep Learning With Simplified Intravoxel Incoherent Motion Diffusion-Weighted MRI Parameters for Differentiating Hepatocellular Carcinoma From Other Common Liver Masses

OBJECTIVES

To develop and evaluate a deep learning technique for the differentiation of hepatocellular carcinoma (HCC) using "simplified intravoxel incoherent motion (IVIM) parameters" derived from only 3 b-value images.

MATERIALS AND METHODS

Ninety-eight retrospective magnetic resonance imaging data were collected (68 men, 30 women; mean age 59 ± 14 years), including T2-weighted imaging with fat suppression, in-phase, out-of-phase, and diffusion-weighted imaging (b = 0, 100, 800 s/mm2). Ninety percent of data were used for stratified 10-fold cross-validation. After data preprocessing, diffusion-weighted imaging images were used to compute simplified IVIM and apparent diffusion coefficient (ADC) maps. A 17-layer 3D convolutional neural network (3D-CNN) was implemented, and the input channels were modified for different strategies of input images.

RESULTS

The 3D-CNN with IVIM maps (ADC, f, and D*) demonstrated superior performance compared with other strategies, achieving an accuracy of 83.25 ± 6.24% and area under the receiver-operating characteristic curve of 92.70 ± 8.24%, significantly surpassing the baseline of 50% (P < 0.05) and outperforming other strategies in all evaluation metrics. This success underscores the effectiveness of simplified IVIM parameters in combination with a 3D-CNN architecture for enhancing HCC differentiation accuracy.

CONCLUSIONS

Simplified IVIM parameters derived from 3 b-values, when integrated with a 3D-CNN architecture, offer a robust framework for HCC differentiation.

Diagnostic performance of magnetic resonance imaging and contrast-enhanced ultrasound in differentiating intrahepatic cholangiocarcinoma from hepatocellular carcinoma: a meta-analysis

PURPOSE

To compare the diagnostic ability between magnetic resonance imaging (MRI) and contrast-enhanced ultrasound (CEUS) in distinguishing intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC).

METHODS

Original studies reporting the diagnostic accuracy of MRI and CEUS in differentiating ICC from HCC were identified in PubMed and EMBASE databases. Histopathological examination was used as the reference standard for tumor diagnosis. Study quality was assessed using QUADAS-2 scale. Data were extracted to calculate the pooled diagnostic sensitivity, specificity, and diagnostic odds ratio (DOR) using a bivariate random-effects model, as well as the area under the curve (AUC). Sensitivity analysis, subgroup analysis, meta-regression, and investigation of publication bias were also performed.

RESULTS

A total of 26 studies with 28 data subsets (18 on MRI, 10 on CEUS) were included, consisting of 4169 patients with 1422 ICC lesions and 2747 HCC lesions. Most MRI studies were performed at 3T with hepatobiliary agents, and most CEUS studies used SonoVue as the contrast agent. In MRI, the pooled sensitivity, specificity, DOR, and AUC in distinguishing ICC from HCC were 0.81 (0.79, 0.84), 0.90 (0.88, 0.91), 41.47 (24.07, 71.44), and 0.93 (0.90, 0.96), respectively. The pooled sensitivity, specificity, DOR, and AUC of CEUS were 0.88 (0.84, 0.90), 0.80 (0.78, 0.83), 42.06 (12.38, 133.23), and 0.93 (0.87, 0.99), respectively. Subgroup analysis and meta-regression analysis demonstrated significant heterogeneity among the studies associated with the type of contrast agent in MRI studies. No publication bias was found.

CONCLUSION

Both MRI and CEUS showed excellent diagnostic performance in differentiating ICC from HCC. CEUS showed higher pooled sensitivity and MRI showed higher pooled specificity.

Differentiation of Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma through MRI Radiomics

The purpose of this study was to investigate the efficacy of magnetic resonance imaging (MRI) radiomics in differentiating hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC). The clinical and MRI data of 129 pathologically confirmed HCC patients and 48 ICC patients treated at the Affiliated Hospital of North Sichuan Medical College between April 2016 and December 2021 were retrospectively analyzed. The patients were randomly divided at a ratio of 7:3 into a training group of 124 patients (90 with HCC and 34 with ICC) and a validation group of 53 patients (39 with HCC and 14 with ICC). Radiomic features were extracted from axial fat suppression T2-weighted imaging (FS-T2WI) and axial arterial-phase (AP) and portal-venous-phase (PVP) dynamic-contrast-enhanced MRI (DCE-MRI) sequences, and the corresponding datasets were generated. The least absolute shrinkage and selection operator (LASSO) method was used to select the best radiomic features. Logistic regression was used to establish radiomic models for each sequence (FS-T2WI, AP and PVP models), a clinical model for optimal clinical variables (C model) and a joint radiomics model (JR model) integrating the radiomics features of all the sequences as well as a radiomics-clinical model combining optimal radiomic features and clinical risk factors (RC model). The performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC). The AUCs of the FS-T2WI, AP, PVP, JR, C and RC models for distinguishing HCC from ICC were 0.693, 0.863, 0.818, 0.914, 0.936 and 0.977 in the training group and 0.690, 0.784, 0.727, 0.802, 0.860 and 0.877 in the validation group, respectively. The results of this study suggest that MRI-based radiomics may help noninvasively differentiate HCC from ICC. The model integrating the radiomics features and clinical risk factors showed a further improvement in performance.

Multiparametric MR imaging with diffusion-weighted, intravoxel incoherent motion, diffusion tensor, and dynamic contrast-enhanced perfusion sequences to assess gallbladder wall thickening: a prospective study based on surgical histopathology

OBJECTIVE

To investigate the diagnostic performance of a multiparametric magnetic resonance imaging (MRI) protocol comprising quantitative MRI (diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), and dynamic contrast-enhanced (DCE) perfusion MRI) and conventional MRI in the characterization of gallbladder wall thickening (GWT).

METHODS

This prospective study comprised consecutive adults with GWT who underwent multiparametric MRI between July 2020 and April 2022. Two radiologists evaluated the MRI independently. The final diagnosis was based on surgical histopathology. The association of MRI parameters with malignant GWT was evaluated. The area under the curve (AUC) for the quantitative MRI parameters and diagnostic performance of conventional, and multiparametric MRI were compared. The interobserver agreement between two radiologists was calculated.

RESULTS

Thirty-five patients (mean age, 56 years, 23 females) with GWT (25 benign and ten malignant) were evaluated. The quantitative MRI parameters significantly associated with malignant GWT were apparent diffusion coefficient on DWI (p = 0.007) and mean diffusivity (MD) on DTI (p = 0.013), perfusion fraction (f) on IVIM (p = 0.033), time to peak enhancement (TTP, p = 0.008), and wash in rate (p = 0.049) on DCE-MRI. TTP had the highest AUC of 0.790, followed by MD (0.782) and f (0.742) (p = 0.213) for predicting malignant GWT. Multiparametric MRI had significantly higher sensitivity (90% vs. 80%, p = 0.045) than conventional MRI for diagnosing malignant GWT. The two radiologists' reading had substantial to near-perfect agreement (kappa = 0.639-1) and moderate to strong correlation (interclass correlation coefficient = 0.5-0.88).

CONCLUSION

Multiparametric protocol incorporating advanced sequences improved the diagnostic performance of MRI for differentiating benign and malignant GWT.

KEY POINTS

• Multiparametric MRI had 90% sensitivity and 88% specificity for diagnosing malignant GWT, compared to 80% sensitivity and 88% specificity for conventional CE-MRI. • Among the quantitative MRI parameters, TTP (perfusion-MRI) had the highest AUC of 0.790, followed by MD (0.782) and IVIM-f (0.742). • For most quantitative MRI parameters, there was moderate to strong agreement (ICC = 0.5-0.88).

A correlative study between IVIM-DWI parameters and VEGF and MMPs expression in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer-related death worldwide. Angiogenic factors may be valuable indices of tumor recurrence and treatment and potentially useful markers for predicting the response to antiangiogenesis therapy. Vascular endothelial growth factor (VEGF) and matrix metalloproteinases (MMPs) are major drivers of tumor angiogenesis. Preoperatively predicting the expression of VEGF and MMPs is crucial for treating HCC. Intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) has been successfully used in the differential diagnosis of HCC, pathological grading, and treatment response evaluation. However, the correlations between IVIM-DWI parameters and VEGF and MMP expression have not been reported. This study provides a preliminary analysis of the correlation between IVIM-DWI parameters and the expression of VEGF, MMP-2, and MMP-9 to investigate the value of IVIM-DWI in the noninvasive evaluation of angiogenesis in HCC.

METHODS

IVIM-DWI was performed in 61 patients with HCC 1 week before they underwent surgical resection. VEGF, MMP-2, and MMP-9 expression was detected using immunohistochemistry staining. Spearman correlation analysis was used to analyze the correlations between the IVIM-DWI parameters and VEGF, MMP-2, and MMP-9 expression in HCC.

RESULTS

The fast apparent diffusion coefficient fraction (f) value was positively correlated with the expression of VEGF (P<0.001), MMP-2 (P=0.002), and MMP-9 (P<0.001). The fast apparent diffusion coefficient (D*) was positively correlated with VEGF (P<0.001) and MMP-9 (P<0.001) expression but was not correlated with MMP-2 (P=0.659) expression. The apparent diffusion coefficient (ADC) and slow apparent diffusion coefficient (D) values were not significantly correlated with the expression of VEGF (P=0.103 and P=0.543, respectively), MMP-2 (P=0.596 and P=0.338, respectively), or MMP-9 (P=0.102 and P=0.660, respectively).

CONCLUSIONS

IVIM-DWI can be used to noninvasively evaluate angiogenesis in HCC.

The influence of resection margin width in patients with intrahepatic cholangiocarcinoma: a meta-analysis

BACKGROUND

Some studies have pointed out that a wide resection margin can improve the prognosis of intrahepatic cholangiocarcinoma, but some researchers disagree and believe that a wide margin may increase complications. The optimal margin length of intrahepatic cholangiocarcinoma is controversial.

METHOD

The literature was searched in PubMed, MedLine, Embase, the Cochrane Library, and Web of Science until December 31, 2021, to evaluate the postoperative outcomes of patients with different margin width after resection. Odds ratios (ORs) with 95% confidence intervals were used to determine the effect size.

RESULT

A total of 11 articles were included in this meta-analysis, including 3007 patients. The narrow group had significantly lower 1-, 3-, and 5-year overall survival rates and recurrence-free survival rates than the wide group. Postoperative morbidity and prognostic factors were also evaluated.

CONCLUSION

A resection margin width of over 10 mm is recommended in intrahepatic cholangiocarcinoma patients, especially in patients with negative lymph node and early tumor stage. When the resection margin width cannot be greater than 10 mm, we should ensure that the resection margin width is greater than 5 mm.

Application of intravoxel incoherent motion diffusion-weighted imaging in hepatocellular carcinoma

The morbidity and mortality of hepatocellular carcinoma (HCC) rank 6th and 4th, respectively, among malignant tumors worldwide. Traditional diffusion-weighted imaging (DWI) uses the apparent diffusion coefficient (ADC) obtained by applying the monoexponential model to reflect water molecule diffusion in active tissue; however, the value of ADC is affected by microcirculation perfusion. Using a biexponential model, intravoxel incoherent motion (IVIM)-DWI quantitatively measures information related to pure water molecule diffusion and microcirculation perfusion, thus compensating for the shortcomings of DWI. The number of studies examining the application of IVIM-DWI in patients with HCC has gradually increased over the last few years, and many results show that IVIM-DWI has vital value for HCC differentiation, pathological grading, and predicting and evaluating the treatment response. The present study principally reviews the principle of IVIM-DWI and its research progress in HCC differentiation, pathological grading, predicting and evaluating the treatment response, predicting postoperative recurrence and predicting gene expression prediction.

Role of noninvasive imaging in the evaluation of intrahepatic cholangiocarcinoma: from diagnosis and prognosis to treatment response

INTRODUCTION

Intrahepatic cholangiocarcinoma is the second most common liver cancer. Desmoplastic stroma may be revealed as distinctive histopathologic findings favoring intrahepatic cholangiocarcinoma. Meanwhile, a range of imaging manifestations is often accompanied with rich desmoplastic stroma in intrahepatic cholangiocarcinoma, which can indicate large bile duct ICC, and a higher level of cancer-associated fibroblasts with poor prognosis and weak treatment response.

AREAS COVERED

We provide a comprehensive review of current state-of-the-art and recent advances in the imaging evaluation for diagnosis, staging, prognosis and treatment response of intrahepatic cholangiocarcinoma. In addition, we discuss precursor lesions, cells of origin, molecular mutation, which would cause the different histological classification. Moreover, histological classification and tumor microenvironment, which are related to the proportion of desmoplastic stroma with many imaging manifestations, would be also discussed.

EXPERT OPINION

The diagnosis, prognosis, treatment response of intrahepatic cholangiocarcinoma may be revealed as the presence and the proportion of desmoplastic stroma with a range of imaging manifestations. With the utility of radiomics and artificial intelligence, imaging is helpful for ICC evaluation. Multicentre, large-scale, prospective studies with external validation are in need to develop comprehensive prediction models based on clinical data, imaging findings, genetic parameters, molecular, metabolic, and immune biomarkers.

Diagnosis of hilar cholangiocarcinoma using intravoxel incoherent motion diffusion-weighted magnetic resonance imaging

OBJECTIVE

To investigate the value of intravoxel incoherent motion diffusion-weighed magnetic resonance imaging (IVIM-DWI) in discriminating the pathological grades of hilar cholangiocarcinoma (HC).

PATIENTS AND METHODS

Thirty-seven HC patients were enrolled and received routine and advanced DWI scanning with multiple b-values. IVIM-DWI images were obtained using echo-planar imaging sequence.

RESULTS

The consistency of the maximum cross-sectional area ROI measuring method was higher than that of the repeated sampling ROI measuring method. ADC_slow values were closely correlated with the pathological grades of HC. The degrees of biliary dilatation and MELD scores had no influence on the negative correlation between ADC_slow values and the pathological degrees of HC patients.

CONCLUSIONS

ADC_slow values could be applied in indicating the pathological grades of HC, which was independent on the extent of biliary dilatation.

The Role of Non-Gaussian Models of Diffusion Weighted MRI in Hepatocellular Carcinoma: A Systematic Review

The importance of Diffusion Weighted Imaging (DWI) in hepatocellular carcinoma (HCC) has been widely handled in the literature. Due to the mono-exponential model limitations, several studies recently investigated the role of non-Gaussian DWI models in HCC. However, their results are variable and inconsistent. Therefore, the aim of this systematic review is to summarize current knowledge on non-Gaussian DWI techniques in HCC. A systematic search of the literature, including PubMed, Google Scholar, MEDLINE, and ScienceDirect databases, was performed to identify original articles since 2010 that evaluated the role of non-Gaussian DWI models for HCC diagnosis, grading, response to treatment, and prognosis. Studies were grouped and summarized according to the non-Gaussian DWI models investigated. We focused on the most used non-Gaussian DWI models (Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Stretched Exponential—SE). The quality of included studies was evaluated by using QUADAS-2 and QUIPS tools. Forty-three articles were included, with IVIM and DKI being the most investigated models. Although the role of non-Gaussian DWI models in clinical settings has not fully been established, our findings showed that their parameters may potentially play a role in HCC. Further studies are required to identify a standardized DWI acquisition protocol for HCC diagnosis, grading, response to treatment, and prognosis.

Synergistic impact of resection margin and microscopic vascular invasion for patients with HBV-related intrahepatic cholangiocarcinoma

OBJECTIVES

The resection margin (RM) status and microscopic vascular invasion (MVI) are known prognostic factors for intrahepatic cholangiocarcinoma (ICC). An enhanced understanding of their impact on long-term prognosis is required to improve oncological outcomes.

METHODS

A total of 711 consecutive patients who underwent curative liver resection for hepatitis B virus-related ICC were retrospectively analyzed. The different impact of the RM status (narrow, <1 cm, or wide, ≥1 cm) and MVI (positive, +, or negative, -) on overall survival (OS) and recurrence-free survival (RFS) were analyzed.

RESULTS

The 1-, 3-, and 5-year OS rates were 67.6%, 42.5%, and 33.2% in wide RM & MVI (-), 58.0%, 36.1%, and 26.5% in narrow RM & MVI (-), 51.0%, 27.0%, and 24.3% in wide RM & MVI (+), and 39.0%, 20.4% and 14.3% in narrow RM & MVI (+) (p < 0.001). Multivariate analysis showed that RM & MVI were independent risk factors for the OS and RFS.

CONCLUSION

Combined analysis of RM and MVI can better stratify the risks of postoperative death and recurrence in patients with HBV-related ICC, which may help subsequent adjuvant therapy and closer follow-up.

The Role of 18F-FDG PET/MRI in the Assessment of Primary Intrahepatic Neoplasms

RATIONALE AND OBJECTIVES

To evaluate the results of 18F-FDG PET/MRI in relation to the histopathologic subtypes and histologic grades of mass-forming primary intrahepatic neoplasms.

MATERIALS AND METHODS

We retrospectively evaluated 18F-FDG positron emission tomography/magnetic resonance imaging (PET/MRI) results for 39 patients with histopathologically confirmed primary hepatic neoplasms, 15 with mass-forming intrahepatic cholangiocarcinoma (ICC) and 24 with hepatocellular carcinoma (HCC). The apparent diffusion coefficient (ADC) and standardized uptake value (SUV) were analyzed in relation to the histopathologic diagnosis and histologic grade, including calculating the sensitivity and specificity of the imaging findings.

RESULTS

The median SUV of ICC (6.0 [interquartile range, 5-10]) was significantly higher than that of HCC (4.0 [2.62-6.50]) (p = 0.002). An area under the curve (AUC) of 0.79 (95% confidence interval 0.649-0.932) had a sensitivity of 86.7% and a specificity of 67% at the best cut-off SUV of 4.41 to differentiate between ICC and HCC. ADC values did not differ significantly between HCCs and ICCs (p = 0.283). Both SUV and ADC values differed significantly between low-grade (well- and moderately differentiated) and high-grade (poorly differentiated) HCCs. Combining ADC and SUV further improved differentiation of low- from high-grade HCCs to a significant level (0.929). The SUV did not differ significantly between ICC histologic grades (p = 0.280), while the ADC differed significantly only between well and poorly differentiated ICCs (p = 0.004).

CONCLUSION

Assessing primary hepatic neoplasms with 18F-Fluorodeoxyglucose PET/MRI may help to predict tumor grade and differentiate between types of intrahepatic neoplasms.

Preoperatively Grading Rectal Cancer with the Combination of Intravoxel Incoherent Motions Imaging and Diffusion Kurtosis Imaging

Purpose

To combine Intravoxel Incoherent Motions (IVIM) imaging and diffusion kurtosis imaging (DKI) which can aid in the quantification of different biological inspirations including cellularity, vascularity, and microstructural heterogeneity to preoperatively grade rectal cancer.

Methods

A total of 58 rectal patients were included into this prospective study. MRI was performed with a 3T scanner. Different combinations of IVIM-derived and DKI-derived parameters were performed to grade rectal cancer. Pearson correlation coefficients were applied to evaluate the correlations. Binary logistic regression models were established via integrating different DWI parameters for screening the most sensitive parameter. Receiver operating characteristic analysis was performed for evaluating the diagnostic performance.

Results

For individual DWI-derived parameters, all parameters except the pseudodiffusion coefficient displayed the capability of grading rectal cancer (p < 0.05). The better discrimination between high- and low-grade rectal cancer was achieved with the combination of different DWI-derived parameters. Similarly, ROC analysis suggested the combination of D (true diffusion coefficient), f (perfusion fraction), and K_app (apparent kurtosis coefficient) yielded the best diagnostic performance (AUC = 0.953, p < 0.001). According to the result of binary logistic analysis, cellularity-related D was the most sensitive predictor (odds ratio: 9.350 ± 2.239) for grading rectal cancer.

Conclusion

The combination of IVIM and DKI holds great potential in accurately grading rectal cancer as IVIM and DKI can provide the quantification of different biological inspirations including cellularity, vascularity, and microstructural heterogeneity.

Progress of intravoxel incoherent motion diffusion-weighted imaging in liver diseases

Traditional magnetic resonance (MR) diffusion-weighted imaging (DWI) uses a single exponential model to obtain the apparent diffusion coefficient to quantitatively reflect the diffusion motion of water molecules in living tissues, but it is affected by blood perfusion. Intravoxel incoherent motion (IVIM)-DWI utilizes a double-exponential model to obtain information on pure water molecule diffusion and microcirculatory perfusion-related diffusion, which compensates for the insufficiency of traditional DWI. In recent years, research on the application of IVIM-DWI in the diagnosis and treatment of hepatic diseases has gradually increased and has achieved considerable progress. This study mainly reviews the basic principles of IVIM-DWI and related research progress in the diagnosis and treatment of hepatic diseases.

Intravoxel incoherent motion diffusion-weighted imaging to differentiate hepatocellular carcinoma from intrahepatic cholangiocarcinoma

The present study aimed to explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC). This study included 65 patients with malignant hepatic nodules (55 with HCC, 10 with ICC), and 17 control patients with normal livers. All patients underwent IVIM-DWI scans on a 3.0 T magnetic resonance imaging (MRI) scanner. The standard apparent diffusion coefficient (ADC), pure diffusion coefficient (Dslow), pseudo-diffusion coefficient (Dfast), and perfusion fraction (f) were obtained. Differences in the parameters among the groups were analysed using one-way ANOVA, with p < 0.05 indicating statistical significance. Receiver operating characteristic (ROC) curve analysis was used to compare the efficacy of each parameter in differentiating HCC from ICC. ADC, Dslow, Dfast, f significantly differed among the three groups. ADC and Dslow were significantly lower in the HCC group than in the ICC group, while Dfast was significantly higher in the HCC group than in the ICC group; f did not significantly differ between the HCC and ICC groups. When the cut-off values of ADC, Dslow, and Dfast were 1.27 × 10−3 mm2/s, 0.81 × 10−3 mm2/s, and 26.04 × 10−3 mm2/s, respectively, their diagnostic sensitivities for differentiating HCC from ICC were 98.18%, 58.18%, and 94.55%, their diagnostic specificities were 50.00%, 80.00%, and 80.00%, and their areas under the ROC curve (AUCs) were 0.687, 0.721, and 0.896, respectively. Dfast displayed the largest AUC value. IVIM-DWI can be used to differentiate HCC from ICC.

Intravoxel incoherent motion diffusion-weighted imaging to differentiate hepatocellular carcinoma from intrahepatic cholangiocarcinoma

The present study aimed to explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC). This study included 65 patients with malignant hepatic nodules (55 with HCC, 10 with ICC), and 17 control patients with normal livers. All patients underwent IVIM-DWI scans on a 3.0 T magnetic resonance imaging (MRI) scanner. The standard apparent diffusion coefficient (ADC), pure diffusion coefficient (Dslow), pseudo-diffusion coefficient (Dfast), and perfusion fraction (f) were obtained. Differences in the parameters among the groups were analysed using one-way ANOVA, with p < 0.05 indicating statistical significance. Receiver operating characteristic (ROC) curve analysis was used to compare the efficacy of each parameter in differentiating HCC from ICC. ADC, Dslow, Dfast, f significantly differed among the three groups. ADC and Dslow were significantly lower in the HCC group than in the ICC group, while Dfast was significantly higher in the HCC group than in the ICC group; f did not significantly differ between the HCC and ICC groups. When the cut-off values of ADC, Dslow, and Dfast were 1.27 × 10-3 mm2/s, 0.81 × 10-3 mm2/s, and 26.04 × 10-3 mm2/s, respectively, their diagnostic sensitivities for differentiating HCC from ICC were 98.18%, 58.18%, and 94.55%, their diagnostic specificities were 50.00%, 80.00%, and 80.00%, and their areas under the ROC curve (AUCs) were 0.687, 0.721, and 0.896, respectively. Dfast displayed the largest AUC value. IVIM-DWI can be used to differentiate HCC from ICC.

Role of Intravoxel Incoherent Motion in Discriminating Hepatitis B Virus-Related Intrahepatic Mass-Forming Cholangiocarcinoma from Hepatocellular Carcinoma Based on Liver Imaging Reporting and Data System v2018

Backgroud: Intravoxel incoherent motion (IVIM) could be used to characterize benign and malignant hepatic lesions and predict the histological grade of hepatocellular carcinoma (HCC). To evaluate IVIM-derived parameters for differentiating between hepatitis B virus (HBV)-related intrahepatic mass-forming cholangiocarcinoma (IMCC) and HCC based on the Liver Imaging Reporting and Data System (LI-RADS) v2018. Materials and Methods: 20 IMCC patients and one-to-one matched control HCC patients were retrospectively assessed. IVIM scanning with 11 b-values (from 0 to 1500 s/mm²) was obtained using a 3.0-T magnetic resonance scanner. Apparent diffusion coefficient (ADC) and IVIM parameters, including diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f), were compared between IMCC and HCC. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performances of ADC, D, f, and D*. The LI-RADS features and a final category were also compared using LI-RADS v2018. Results: ADC and D were significantly higher in IMCC than in HCC (p = 0.012 and p = 0.007, respectively); f was significantly higher in HCC than in IMCC (p = 0.004). The area under the ROC curve values for ADC, D, and f for differentiating HBV-related IMCC from HCC were 0.724, 0.753, and 0.741, respectively. Conclusion: The majority of HBV-related IMCCs can be categorized as LR-M by using LI-RADS. However, atypical IMCCs may be classified as non-LR-M. ADC, D, and f values may be helpful in differentiating HBV-related IMCC from HCC, and similar diagnostic performances were obtained for these values.

Volumetric quantitative histogram analysis using diffusion-weighted magnetic resonance imaging to differentiate HCC from other primary liver cancers

OBJECTIVE

To evaluate the ability of volumetric quantitative apparent diffusion coefficient (ADC) histogram parameters and LI-RADS categorization to distinguish hepatocellular carcinoma (HCC) from other primary liver cancers [intrahepatic cholangiocarcinoma (ICC) and combined HCC-ICC].

METHODS

Sixty-three consecutive patients (44 M/19F; mean age 62 years) with primary liver cancers and pre-treatment MRI including diffusion-weighted imaging (DWI) were included in this IRB-approved single-center retrospective study. Tumor type was categorized pathologically. Qualitative tumor features and LI-RADS categorization were assessed by 2 independent observers. Lesion volume of interest measurements (VOIs) were placed on ADC maps to extract first-order radiomics (histogram) features. ADC histogram metrics and qualitative findings were compared. Binary logistic regression and AUROC were used to assess performance for distinction of HCC from ICC and combined tumors.

RESULTS

Sixty-five lesions (HCC, n = 36; ICC, n = 17; and combined tumor, n = 12) were assessed. Only enhancement pattern (p < 0.015) and capsule were useful for tumor diagnosis (p < 0.014). ADC 5th/10th/95th percentiles were significant for discrimination between each tumor types (all p values < 0.05). Accuracy of LI-RADS for HCC diagnosis was 76.9% (p < 0.0001) and 69.2% (p = 0.001) for both observers. The combination of male gender, LI-RADS, and ADC 5th percentile yielded an AUROC/sensitivity/specificity/accuracy of 0.90/79.3%/88.9%/81.5% and 0.89/86.2%/77.8%/80.0% (all p values < 0.027) for the diagnosis of HCC compared to ICC and combined tumors for both observers, respectively.

CONCLUSION

The combination of quantitative ADC histogram parameters and LI-RADS categorization yielded the best prediction accuracy for distinction of HCC compared to ICC and combined HCC-ICC.