Diffusion-weighted imaging of surgically resected hepatocellular carcinoma: imaging characteristics and relationship among signal intensity, apparent diffusion coefficient, and histopathologic grade. AJR Am J Roentgenol. 2009;193:438-444. [PMID: 19620441 DOI: 10.2214/ajr.08.1424]

Beyond cholangiocarcinoma: imaging features of mimicking pathologies in the biliary tract

Cholangiocarcinoma (CCA) is the second most common primary malignancy of the hepatobiliary system and presents as a heterogeneous disease with three distinct morphological subtypes: mass-forming, periductal-infiltrating, and intraductal-growing, each characterized by distinguishing imaging features. Accurate diagnosis of CCA is challenging due to the overlap of imaging findings with a broad range of benign and malignant conditions. Therefore, it is essential for radiologists to recognize these mimickers and offer a reasonable differential diagnosis, as this has a significant impact on patient management. Although histopathological confirmation is often required for a definitive diagnosis, understanding specific imaging characteristics that differentiate CCA from its mimickers is crucial. This article highlights a variety of benign and malignant conditions that resemble CCA on imaging, emphasizing features that enhance diagnostic accuracy in clinical practice.

MRI for hepatocellular carcinoma and the role of abbreviated MRI for surveillance of hepatocellular carcinoma

INTRODUCTION

Hepatocellular carcinoma (HCC) constitutes the majority of liver cancers and significantly impacts global cancer mortality. While ultrasound (US) with or without alpha-fetoprotein is the mainstay for HCC surveillance, its limitations highlight the necessity for more effective surveillance tools. Therefore, this review explores evolving imaging modalities and abbreviated magnetic resonance imaging (MRI) (AMRI) protocols as promising alternatives, addressing challenges in HCC surveillance.

AREAS COVERED

This comprehensive review delves into the evaluation and challenges of HCC surveillance tools, focusing on non-contrast abbreviated MRI (NC-AMRI) and contrast-enhanced abbreviated MRI protocols. It covers the implementation of AMRI for HCC surveillance, patient preferences, adherence, and strategies for optimizing cost-effectiveness. Additionally, the article provides insights into prospects for HCC surveillance by summarizing meta-analyses, prospective studies, and ongoing clinical trials evaluating AMRI protocols.

EXPERT OPINION

The opinions underscore the transformative impact of AMRI on HCC surveillance, especially in overcoming US limitations. Promising results from NC-AMRI protocols indicate its potential for high-risk patient surveillance, though prospective studies in true surveillance settings are essential for validation. Future research should prioritize risk-stratified AMRI protocols and address cost-effectiveness for broader clinical implementation, alongside comparative analyses with US for optimal surveillance strategies.

Comparison of CT and gadoxetic acid-enhanced MRI with liver imaging reporting and data system to assess liver tumors before resection

BACKGROUND/PURPOSE

Hepatocellular carcinoma (HCC) can be noninvasively diagnosed through dynamic computed tomography (CT) and magnetic resonance imaging (MRI). We compared the diagnostic performance of CT and gadoxetic acid-enhanced MRI (EOB-MRI) in categorizing tumors by using the 2018 version of the Liver Imaging Reporting And Data System (LI-RADS v2018) and assessing liver tumors before resection.

METHODS

Data from a prospective cohort from October 2011 to March 2019 on 106 hepatic tumors in 96 patients with suspected malignancy were included in this study. We performed preoperative CT and EOB-MRI, and reviewed these images retrospectively. Ninety-seven tumors from 87 patients were pathologically diagnosed as HCC, and nine tumors were non-HCC. The clinical data, imaging characteristics, diagnostic performance, and outcomes of CT and EOB-MRI were analyzed and compared.

RESULTS

EOB-MRI had more favorable diagnostic performance (area under curve: 0.920 vs. 0.868) and significantly higher sensitivity (86.87% vs. 69.70%, p = 0.005) than did CT. However, the specificity of EOB-MRI did not differ from that of CT (88.89% vs. 88.89%, p > 0.999). Fourteen (14.5%) patients with pathologically verified HCC had lesions categorized as LI-RADS 4 through CT and as LI-RADS 5 through EOB-MRI. Patients with EOB-MRI-categorized but not CT-categorized LI-RADS 5 lesions had significantly longer overall survival than did those with LI-RADS 4 lesions (p < 0.001).

CONCLUSION

EOB-MRI had higher sensitivity than did CT in diagnosing HCC. Patients with EOB-MRI-categorized LI-RADS 5 lesions had more favorable outcomes than did those with LI-RADS 4 lesions after liver resection.

Non-invasive preoperative prediction of Edmondson-Steiner grade of hepatocellular carcinoma based on contrast-enhanced ultrasound using ensemble learning

Purpose

This study aimed to explore the clinical value of non-invasive preoperative Edmondson-Steiner grade of hepatocellular carcinoma (HCC) using contrast-enhanced ultrasound (CEUS).

Methods

212 cases of HCCs were retrospectively included, including 83 cases of high-grade HCCs and 129 cases of low-grade HCCs. Three representative CEUS images were selected from the arterial phase, portal vein phase, and delayed phase and stored in a 3-dimensional array. ITK-SNAP was used to segment the tumor lesions manually. The Radiomics method was conducted to extract high-dimensional features on these contrast-enhanced ultrasound images. Then the independent sample T-test and the Least Absolute Shrinkage and Selection Operator (LASSO) were employed to reduce the feature dimensions. The optimized features were modeled by a classifier based on ensemble learning, and the Edmondson Steiner grading was predicted in an independent testing set using this model.

Results

A total of 1338 features were extracted from the 3D images. After the dimension reduction, 10 features were finally selected to establish the model. In the independent testing set, the integrated model performed best, with an AUC of 0.931.

Conclusion

This study proposed an Edmondson-Steiner grading method for HCC with CEUS. The method has good classification performance on independent testing sets, which can provide quantitative analysis support for clinical decision-making.

A comparative study between deep learning and radiomics models in grading liver tumors using hepatobiliary phase contrast-enhanced MR images

Purpose

To compare a deep learning model with a radiomics model in differentiating high-grade (LR-3, LR-4, LR-5) liver imaging reporting and data system (LI-RADS) liver tumors from low-grade (LR-1, LR-2) LI-RADS tumors based on the contrast-enhanced magnetic resonance images.

Methods

Magnetic resonance imaging scans of 361 suspected hepatocellular carcinoma patients were retrospectively reviewed. Lesion volume segmentation was manually performed by two radiologists, resulting in 426 lesions from the training set and 83 lesions from the test set. The radiomics model was constructed using a support vector machine (SVM) with pre-defined features, which was first selected using Chi-square test, followed by refining using binary least absolute shrinkage and selection operator (LASSO) regression. The deep learning model was established based on the DenseNet. Performance of the models was quantified by area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity and F1-score.

Results

A set of 8 most informative features was selected from 1049 features to train the SVM classifier. The AUCs of the radiomics model were 0.857 (95% confidence interval [CI] 0.816–0.888) for the training set and 0.879 (95% CI 0.779–0.935) for the test set. The deep learning method achieved AUCs of 0.838 (95% CI 0.799–0.871) for the training set and 0.717 (95% CI 0.601–0.814) for the test set. The performance difference between these two models was assessed by t-test, which showed the results in both training and test sets were statistically significant.

Conclusion

The deep learning based model can be trained end-to-end with little extra domain knowledge, while the radiomics model requires complex feature selection. However, this process makes the radiomics model achieve better performance in this study with smaller computational cost and more potential on model interpretability.

Clinical and imaging features preoperative evaluation of histological grade and microvascular infiltration of hepatocellular carcinoma

Background

To predict the histological grade and microvascular invasion (MVI) in patients with HCC.

Methods

A retrospective analysis was conducted on 175 patients who underwent MRI enhancement scanning (from September 2016.9 to October 2020). They were divided into MVI positive, MVI negative, Grade-high and Grade-low groups.

Results

The AFP of 175 HCC patients distributed in MVI positive and negative groups, Grade-low and Grade-high groups were statistically significant (P = 0.002 and 0.03, respectively). Multiple HCC lesions were more common in MVI positive and Grade-high groups. Correspondingly, more single lesions were found in MVI negative and Grade-low groups (P = 0.005 and 0.019, respectively). Capsule on MRI was more common in MVI negative and Grade-high groups, and the difference was statistically significant (P = 0.02 and 0.011, respectively). There were statistical differences in the distribution of three MRI signs: artistic rim enhancement, artistic peripheral enhancement, and tumor margin between MVI positive and MVI negative groups (P = 0.001, < 0.001, and < 0.001, respectively). Tumor hypointensity on HBP was significantly different between MVI positive and negative groups (P < 0.001).

Conclusions

Our research shows that preoperative enhanced imaging can be used to predict MVI and tumor differentiation grade of HCC. The prognosis of MVI-negative group was better than that of MVI-positive group.

Prediction of outcomes by diffusion kurtosis imaging in patients with large (≥5 cm) hepatocellular carcinoma after liver resection: A retrospective study

Purpose

To evaluate preoperative diffusion kurtosis imaging (DKI) in predicting the outcomes of large hepatocellular carcinoma (HCC) after liver resection (LR).

Materials and methods

From January 2015 to December 2017, patients with a large (≥5cm) HCC who underwent preoperative DKI were retrospectively reviewed. The correlations of the mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) with microvascular invasion (MVI) or histological grade were analyzed. Cox regression analyses were performed to identify the predictors of recurrence-free survival (RFS) and overall survival (OS). A nomogram to predict RFS was established. P&lt;0.05 was considered as statistically significant.

Results

A total of 97 patients (59 males and 38 females, 56.0 ± 10.9 years) were included in this study. The MK, MD, and ADC values were correlated with MVI or histological grade (P&lt;0.01). With a median follow-up time of 41.2 months (range 12-69 months), 67 patients (69.1%) experienced recurrence and 41 patients (42.3%) were still alive. The median RFS and OS periods after LR were 29 and 45 months, respectively. The 1-, 3-, and 5-year RFS and OS rates were 88.7%, 41.2%, and 21.7% and 99.0%, 68.3%, and 25.6%, respectively. MK (P&lt;0.001), PVT (P&lt;0.001), and ADC (P=0.033) were identified as independent predictor factors for RFS. A nomogram including the MK value for RFS showed the best performance, and the C-index was 0.895.

Conclusion

The MK value obtained from DKI is a potential predictive factor for recurrence and poor survival, which could provide valuable information for guiding the efficacy of LR in patients with large HCC.

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); ADCmin ≤ 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 ADCmin, largest tumor diameter, and two-segment involved tumor provides high sensitivity and negative predictive value in MVI prediction for use in routine functional MR.

A study of the correlations between IVIM-DWI parameters and the histologic differentiation of hepatocellular carcinoma

The present study aimed to investigate the value of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) in the preoperative prediction of the histologic differentiation of hepatocellular carcinoma (HCC). Seventy HCC patients were scanned with a 3.0 T magnetic resonance scanner. The values of apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D*), and the fraction of the fast apparent diffusion coefficient (f) were measured. Analysis of variance was used to compare the differences in parameters between groups with different degrees of histologic differentiation. p < 0.05 was considered statistically significant. Receiver operating characteristic (ROC) curves were used to analyse the efficacy of IVIM-DWI parameters for predicting the histologic differentiation of HCC. The ADC and D values for well, moderately and poorly differentiated HCC were 1.35 ± 0.17 × 10-3 mm2/s, 1.16 ± 0.17 × 10-3 mm2/s, 0.98 ± 0.21 × 10-3 mm2/s, and 1.06 ± 0.15 × 10-3 mm2/s, 0.88 ± 0.16 × 10-3 mm2/s, 0.76 ± 0.18 × 10-3 mm2/s, respectively, and all differences were significant. The D* and f values of the three groups were 32.87 ± 14.70 × 10-3 mm2/s, 41.68 ± 17.90 × 10-3 mm2/s, 34.54 ± 18.60 × 10-3 mm2/s and 0.22 ± 0.07, 0.23 ± 0.08, 0.18 ± 0.07, respectively, with no significant difference. When the cut-off values of ADC and D were 1.25 × 10-3 mm2/s and 0.97 × 10-3 mm2/s, respectively, their diagnostic sensitivities and specificities for distinguishing well differentiated HCC from moderately differentiated and poorly differentiated HCC were 73.3%, 85.5%, 86.7%, and 78.2%, and their areas under the ROC curve were 0.821 and 0.841, respectively. ADC and D values can be used preoperatively to predict the degree of histologic differentiation in HCC, and the D value has better diagnostic value.

Ex Vivo MR Histology and Cytometric Feature Mapping Connect Three-dimensional in Vivo MR Images to Two-dimensional Histopathologic Images of Murine Sarcomas

Purpose To establish a platform for quantitative tissue-based interpretation of cytoarchitecture features from tumor MRI measurements. Materials and Methods In a pilot preclinical study, multicontrast in vivo MRI of murine soft-tissue sarcomas in 10 mice, followed by ex vivo MRI of fixed tissues (termed MR histology), was performed. Paraffin-embedded limb cross-sections were stained with hematoxylin-eosin, digitized, and registered with MRI. Registration was assessed by using binarized tumor maps and Dice similarity coefficients (DSCs). Quantitative cytometric feature maps from histologic slides were derived by using nuclear segmentation and compared with registered MRI, including apparent diffusion coefficients and transverse relaxation times as affected by magnetic field heterogeneity (T2* maps). Cytometric features were compared with each MR image individually by using simple linear regression analysis to identify the features of interest, and the goodness of fit was assessed on the basis of R² values. Results Registration of MR images to histopathologic slide images resulted in mean DSCs of 0.912 for ex vivo MR histology and 0.881 for in vivo MRI. Triplicate repeats showed high registration repeatability (mean DSC, >0.9). Whole-slide nuclear segmentations were automated to detect nuclei on histopathologic slides (DSC = 0.8), and feature maps were generated for correlative analysis with MR images. Notable trends were observed between cell density and in vivo apparent diffusion coefficients (best line fit: R² = 0.96, P < .001). Multiple cytoarchitectural features exhibited linear relationships with in vivo T2* maps, including nuclear circularity (best line fit: R² = 0.99, P < .001) and variance in nuclear circularity (best line fit: R² = 0.98, P < .001). Conclusion An infrastructure for registering and quantitatively comparing in vivo tumor MRI with traditional histologic analysis was successfully implemented in a preclinical pilot study of soft-tissue sarcomas. Keywords: MRI, Pathology, Animal Studies, Tissue Characterization Supplemental material is available for this article. © RSNA, 2021.

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.

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.

An overview of hepatocellular carcinoma with atypical enhancement pattern: spectrum of magnetic resonance imaging findings with pathologic correlation

BACKGROUND

In the setting of cirrhotic liver, the diagnosis of hepatocellular carcinoma (HCC) is straightforward when typical imaging findings consisting of arterial hypervascularity followed by portal-venous washout are present in nodules larger than 1 cm. However, due to the complexity of hepatocarcinogenesis, not all HCCs present with typical vascular behaviour. Atypical forms such as hypervascular HCC without washout, isovascular or even hypovascular HCC can pose diagnostic dilemmas. In such cases, it is important to consider also the appearance of the nodules on diffusion-weighted imaging and hepatobiliary phase. In this regard, diffusion restriction and hypointensity on hepatobiliary phase are suggestive of malignancy. If both findings are present in hypervascular lesion without washout, or even in iso- or hypovascular lesion in cirrhotic liver, HCC should be considered. Moreover, other ancillary imaging findings such as the presence of the capsule, fat content, signal intensity on T2-weighted image favour the diagnosis of HCC. Another form of atypical HCCs are lesions which show hyperintensity on hepatobiliary phase. Therefore, the aim of the present study was to provide an overview of HCCs with atypical enhancement pattern, and focus on their magnetic resonance imaging (MRI) features.

CONCLUSIONS

In order to correctly characterize atypical HCC lesions in cirrhotic liver it is important to consider not only vascular behaviour of the nodule, but also ancillary MRI features, such as diffusion restriction, hepatobiliary phase hypointensity, and T2-weighted hyperintensity. Fat content, corona enhancement, mosaic architecture are other MRI feautures which favour the diagnosis of HCC even in the absence of typical vascular profile.

Quantitative analysis of multiphase magnetic resonance images may assist prediction of histopathological grade of small hepatocellular carcinoma

Background

The aim of the study was to investigate whether preoperative quantitative analysis of multiphase magnetic resonance images may assist in predicting the pathological grade of small hepatocellular carcinoma (HCC).

Methods

A total of 49 patients with small HCCs (≤3 cm) underwent multiphase magnetic resonance imaging (MRI) and were retrospectively reviewed. Routine unenhanced and post gadobenate dimeglumine (Gd-BOPTA)-enhanced MRI were preoperatively performed. Signal intensity (SI) was measured within the designated region of interest (ROI) including those of the lesion and paraspinous muscles. The lesion-to-paraspinous muscle relative contrast ratio (RCR) on T2-weighted (T2W) imaging, diffusion-weighted (DW) imaging, and dynamic phase Gd-BOPTA-enhanced T1W (T1-weighted) imaging were calculated, and statistical analysis was performed to determine the predictive power for the histological grade.

Results

In all, 49 cases were included comprising 3 well-differentiated (WD) HCCs, 36 moderately differentiated (MD) HCCs, and 10 poorly differentiated (PD) HCCs. There was a negative correlation between the RCR and pathological grade of small HCC in the arterial phase [correlation coefficient (ρ)=-0.305, P<0.05]. However, there was no correlation between RCR in other phases and pathological grade (P>0.05 for all). There was also no correlation between tumor margin, tumor location, cystic/necrotic change, intratumoral fat, enhancement pattern, tumor capsule, tumor boundary or tumor size, and any of the differentiation categories (P>0.05 for all).

Conclusions

The lesion-to-paraspinous muscle RCR on arterial phase Gd-BOPTA-enhanced T1W imaging may be useful for the prediction of the histological characteristics of small HCC.

Pearls and pitfalls in magnetic resonance imaging of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy, which usually arises in cirrhotic liver. When the typical enhancement pattern, consisting of late arterial hyperenhancement followed by washout, is present in nodules larger than 1 cm, HCC can be confidently diagnosed without the need for tissue biopsy. Nevertheless, HCC can display an atypical enhancement pattern, either as iso or hypovascular lesion, or hypervascular lesion without washout. Not only the enhancement pattern of HCC could be atypical, but also a variety of histological types of HCC, such as steatotic, scirrhous, fibrolamellar, or combined hepatocellular-cholangiocellular carcinoma could raise diagnostic dilemmas. In addition, distinct morphological types of HCC or different growth pattern can occur. Awareness of these atypical and rare HCC presentations on magnetic resonance imaging is important for accurate differentiation from other focal liver lesions and timely diagnosis, which allows optimal treatment of patients.

Associations Between Apparent Diffusion Coefficient Value With Pathological Type, Histologic Grade, and Presence of Lymph Node Metastases of Esophageal Carcinoma

Objective:

To investigate the application value of apparent diffusion coefficient value in the pathological type, histologic grade, and presence of lymph node metastases of esophageal carcinoma.

Materials and Methods:

Eighty-six patients with pathologically confirmed esophageal carcinoma were divided into different groups according to pathological type, histological grade, and lymph node status. All patients underwent conventional magnetic resonance imaging and diffusion-weighted imaging scan, and apparent diffusion coefficient values of tumors were measured. Independent sample t test and 1-way variance were used to compare the difference of apparent diffusion coefficient value in different pathological types, histologic grades, and lymph node status. Correlation between the apparent diffusion coefficient value and the histologic grade was evaluated using Spearman rank correlation test. Receiver operating characteristic curve of apparent diffusion coefficient value was generated to evaluate the differential diagnostic efficiency of poorly and well/moderately differentiated esophageal carcinoma.

Results:

No significant difference was observed in apparent diffusion coefficient value between esophageal squamous cell carcinoma and adenocarcinoma and in patients between those with and without lymph node metastases (P > .05). The differences of apparent diffusion coefficient value were statistically significant between different histologic grades of esophageal carcinoma (P < .05). The apparent diffusion coefficient value was positively correlated with histologic grade (rs = 0.802). The apparent diffusion coefficient value ≤1.25 × 10⁻³ mm²/s as the cutoff value for diagnosis of poorly differentiated esophageal carcinoma with the sensitivity of 84.3%, and the specificity was 94.3%.

Conclusions:

The performance of apparent diffusion coefficient value was contributing to predict the histologic grade of esophageal carcinoma, which might increase lesions characterization before choosing the best therapeutic alternative. However, they do not correlate with pathological type and the presence of lymph node metastases of esophageal carcinoma.

Differentiation of Small Hepatocellular Carcinoma From Dysplastic Nodules in Cirrhotic Liver: Texture Analysis Based on MRI Improved Performance in Comparison Over Gadoxetic Acid-Enhanced MR and Diffusion-Weighted Imaging

Background: Accurate characterization of small (3 cm) hepatocellular carcinoma (sHCC) and dysplastic nodules (DNs) in cirrhotic liver is challenging. We aimed to investigate whether texture analysis (TA) based on T2-weighted images (T2WI) is superior to qualitative diagnosis using gadoxetic acid-enhanced MR imaging (Gd-EOB-MRI) and diffusion-weighted imaging (DWI) for distinguishing sHCC from DNs in cirrhosis.

Materials and methods: Sixty-eight patients with 73 liver nodules (46 HCCs, 27 DNs) pathologically confirmed by operation were included. For imaging diagnosis, three sets of images were reviewed by two experienced radiologists in consensus: a Gd-EOB-MRI set, a DWI set, and a combined set (combination of Gd-EOB-MRI and DWI). For TA, 279 texture features resulting from T2WI were extracted for each lesion. The performance of each approach was evaluated by a receiver operating characteristic analysis. The area under the receiver operating characteristic curve (A_z), sensitivity, specificity, and accuracy were determined.

Results: The performance of TA (A_z = 0.96) was significantly higher than that of imaging diagnosis using Gd-EOB-MRI set (A_z = 0.86) or DWI set (A_z = 0.80) alone in differentiation of sHCC from DNs (P = 0.008 and 0.025, respectively). The combination of Gd-EOB-MRI and DWI showed a greater sensitivity (95.6%) but reduced specificity (66.7%). The specificity of TA (92.6%) was significantly higher than that of the combined set (P < 0.001), but no significant difference was observed in sensitivity (97.8 vs. 95.6%, P = 0.559).

Conclusion: TA-based T2WI showed a better classification performance than that of qualitative diagnosis using Gd-EOB-MRI and DW imaging in differentiation of sHCCs from DNs in cirrhotic liver. TA-based MRI may become a potential imaging biomarker for the early differentiation HCCs from DNs in cirrhosis.

A comparative study of monoexponential versus biexponential models of diffusion-weighted imaging in differentiating histologic grades of hepatitis B virus-related hepatocellular carcinoma

PURPOSE

To compare the diagnostic value of apparent diffusion coefficient (ADC) and intravoxel incoherent motion metrics in discriminating histologic grades of hepatocellular carcinoma (HCC) in patients with hepatitis B virus (HBV) infection.

METHODS

117 chronic HBV patients with 120 pathologically confirmed HCCs after surgical resection or liver transplantation were enrolled in this retrospective study. Diffusion-weighted imaging was performed using eleven b values (0-1500 s/mm²) and two b values (0, 800 s/mm²) successively on a 3.0 T system. ADC_{0, 800}, ADC_total, diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were calculated. The parameters of three histologically differentiated subtypes were investigated using Kruskal-Wallis test, Spearman rank correlation, and receiver-operating characteristic analysis. Interobserver agreement was assessed using the intraclass correlation coefficient.

RESULTS

There was excellent agreement for ADC_total/D/f, good agreement for ADC_0,800, and moderate agreement for D*. ADC_total, ADC_{0, 800,}D, and f were significantly different for well, moderately, and poorly differentiated HCCs (P < 0.001), and they were all inversely correlated with histologic grades: r = - 0.633, - 0.394, - 0.435, and - 0.358, respectively (P < 0.001). ADC_total demonstrated higher performance than ADC_0,800 in diagnosing both well and poorly differentiated HCCs (P < 0.001 and P = 0.04, respectively). ADC_total showed higher performance than D and f in diagnosing well differentiated HCCs (P < 0.001) and similar performance in diagnosing poorly differentiated HCCs (P = 0.06 and 0.13, respectively).

CONCLUSIONS

ADC_total showed better diagnostic performance than ADC_0,800, D, and f to discriminate histologic grades of HCC.

Value of Intravoxel Incoherent Motion for Hepatocellular Carcinoma Grading

BACKGROUND

To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) parameters in estimation of hepatocellular carcinoma (HCC) grading.

MATERIALS AND METHODS

Twenty-nine patients with histopathologically diagnosed as 42 HCC at explant were included in this retrospective study. All patients were examined by 1.5T magnetic resonance imaging with the use of 4-channel phased array body coil. In addition to routine pre- and postcontrast sequences, IVIM (16 different b factors varying from 0 to 1300 s/mm²) and conventional diffusion-weighted imaging (3 different b factors of 50, 400, 800 s/mm²) were obtained with single-shot echo planar spin echo sequence. Apparent diffusion coefficient (ADC) and IVIM parameters including mean D (true diffusion coefficient), D* (pseudo-diffusion coefficient associated with blood flow), and f (perfusion fraction) values were calculated. Histopathologically, HCC was classified as low (grade 1, 2) and high (grade 3, 4) grade in accordance with the Edmondson-Steiner score. Quantitatively, ADC, D, D*, and f values were compared between the low- and high-grade groups by Student t test. The relationship between the parameters and histologic grade was analyzed using the Spearman's correlation test. To evaluate the diagnostic performance of the parameters, receiver operating characteristic analysis was performed.

RESULTS

High-grade HCCs had significantly lower ADC and D values than low grade groups (P = .005 and P = .026, retrospectively); ADC and D values were inversely correlated with tumor grade (r = -0.519, P = .011, r = -0.510, P = .026, respectively). High-grade HCCs had significantly higher f values when compared with the low-grade group (P = .005). The f values were positively correlated with tumor grade (r = 0.548, P = .007). The best discriminative parameter was f value. Cut-off value of 32% of f values showed sensitivity of 75.6% and a specificity of 73.5%.

CONCLUSION

ADC values and IVIM parameters such as f values appear to reflect the grade of HCCs.

Whole-lesion histogram analysis metrics of the apparent diffusion coefficient: a correlation study with histological grade of hepatocellular carcinoma

PURPOSE

The study evaluated the relationship between the histological grade of hepatocellular carcinoma (HCC) and the histogram-derived parameters of apparent diffusion coefficient (ADC) obtained from the whole-lesion assessment of diffusion-weighted magnetic resonance (MR) imaging in the liver.

METHODS

A total of 51 patients were included. The parameters were correlated with the Edmondson-Steiner grades by using the Spearman correlation coefficient (ρ). The differences of ADC parameters between different tumor histological grades were compared using the Mann-Whitney U test. The extent to which each parameter aided in differentiating tumors with poor performance (III, IV) and fair performance (I, II) was assessed by using the area under the receiver operating characteristic curve (Az).

RESULTS

The 25th percentile ADC exhibits the most negative correlation with histological grade (ρ = - 0.397), followed by the 30th percentile ADC (ρ = - 0.395), the minimum ADC value (ρ = - 0.390) and the 20th percentile ADC (ρ = - 0.385), whereas the minimum ADC value yielded the highest Az (0.763) in the discrimination of tumor foci with poor differentiation from fairly differentiated HCCs. The minimum ADC of 4.15 × 10^-3 mm²/s or lower was considered to indicate poorly differentiated performance, and the corresponding sensitivity and specificity were 66.7 and 90.9%, respectively.

CONCLUSION

The 25th percentile ADC showed a stronger correlation with the histological grade of HCC than other ADC parameters, and the minimum ADC value might be an optimal metric for determining poor and fair differentiations of HCC in DWI.

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.

Grading of hepatocellular carcinoma based on diffusion weighted images with multiple b-values using convolutional neural networks

PURPOSE

To effectively grade hepatocellular carcinoma (HCC) based on deep features derived from diffusion weighted images (DWI) with multiple b-values using convolutional neural networks (CNN).

MATERIALS AND METHODS

Ninety-eight subjects with 100 pathologically confirmed HCC lesions from July 2012 to October 2018 were included in this retrospective study, including 47 low-grade and 53 high-grade HCCs. DWI was performed for each subject with a 3.0T MR scanner in a breath-hold routine with three b-values (0,100, and 600 s/mm² ). First, logarithmic transformation was performed on original DWI images to generate log maps (logb0, logb100, and logb600). Then, a resampling method was performed to extract multiple 2D axial planes of HCCs from the log map to increase the dataset for training. Subsequently, 2D CNN was used to extract deep features of the log map for HCCs. Finally, fusion of deep features derived from three b-value log maps was conducted for HCC malignancy classification. Specifically, a deeply supervised loss function was devised to further improve the performance of lesion characterization. The data set was split into two parts: the training and validation set (60 HCCs) and the fixed test set (40 HCCs). Four-fold cross validation with 10 repetitions was performed to assess the performance of deep features extracted from single b-value images for HCC grading using the training and validation set. Receiver operating characteristic curve (ROC) and area under the curve (AUC) values were used to assess the characterization performance of the proposed deep feature fusion method to differentiate low-grade and high-grade in the fixed test set.

RESULTS

The proposed fusion of deep features derived from logb0, logb100, and logb600 with deeply supervised loss function generated the highest accuracy for HCC grading (80%), thus outperforming the method of deep feature derived from the ADC map directly (72.5%), the original b0 (65%), b100 (68%), and b600 (70%) images. Furthermore, AUC values of the deep features of the ADC map, the deep feature fusion with concatenation, and the proposed deep feature fusion with deeply supervised loss function were 0.73, 0.78, and 0.83, respectively.

CONCLUSION

The proposed fusion of deep features derived from the logarithm of the three b-value images yields high performance for HCC grading, thus providing a promising approach for the assessment of DWI in lesion characterization.

The utility of diffusion-weighted imaging in improving the sensitivity of LI-RADS classification of small hepatic observations suspected of malignancy

PURPOSE

We investigated the added value of diffusion-weighted imaging (DWI)/apparent diffusion coefficient (ADC) in the categorization of small hepatic observation (≤ 20 mm) detected in patients with chronic liver disease in reference to LI-RADS (liver imaging reporting and data system) classification system.

METHODS

We prospectively evaluated 165 patients with chronic liver disease with small hepatic observations (≤ 20 mm) which were previously categorized as LI-RADS grade 3-5 on dynamic contrast-enhanced CT (DCE-CT). All patients were submitted to a functional MRI including DCE and DWI. Using LI-RADS v2017, two radiologists independently evaluated the observations and assigned a LI-RADS category to each observation using DCE-MRI alone and combined DCE-MRI and DWI/ADC. In the combined technique, the radiologists assigned a LI-RADS category based on a modified LI-RADS criteria in which restricted diffusion on DWI was considered a major feature of HCC. We evaluated the inter-reader agreement with Kappa statistics and compared the diagnostic performance of the LI-RADS with two imaging techniques by Fisher's exact test using histopathology as the reference standard.

RESULTS

Combined technique in LI-RADS yielded better sensitivities (reader 1, 97% [65/67]; reader 2, 95.5% [64/67]) for HCC diagnosis than DCE-MRI alone (reader 1, 80.6% [54/67], p = 0.005; reader 2, 83.6% [56/67], p = 0.04). The specificities were insignificantly lower in combined technique (reader 1, 88.4% [107/121]; reader 2, 77.7% [94/121]) than in DCE-MRI alone (reader 1, 90.9% [110/121], p = 0.67; reader 2, 79.3% [96/121], p = 0.88). The inter-reader agreement of the LI-RADS scores between combined technique and DCE-MRI was good (κ = 0.765).

CONCLUSION

The use of DWI/ADC as an additional major criterion, improved the sensitivity of LI-RADS in the diagnosis of HCC while keeping high specificity.

Collagen networks determine viscoelastic properties of connective tissues yet do not hinder diffusion of the aqueous solvent

Collagen accounts for the major extracellular matrix (ECM) component in many tissues and provides mechanical support for cells. Magnetic Resonance (MR) Imaging, MR based diffusion measurements and MR Elastography (MRE) are considered sensitive to the microstructure of tissues including collagen networks of the ECM. However, little is known whether water diffusion interacts with viscoelastic properties of tissues. This study combines highfield MR based diffusion measurements, novel compact tabletop MRE and confocal microscopy in collagen networks of different cross-linking states (untreated collagen gels versus additional treatment with glutaraldehyde). The consistency of bulk rheology and MRE within a wide dynamic range is demonstrated in heparin gels, a viscoelastic standard for MRE. Additional crosslinking of collagen led to an 8-fold increased storage modulus, a 4-fold increased loss modulus and a significantly decreased power law exponent, describing multi-relaxational behavior, corresponding to a pronounced transition from viscous-soft to elastic-rigid properties. Collagen network changes were not detectable by MR based diffusion measurements and microscopy which are sensitive to the micrometer scale. The MRE-measured shear modulus is sensitive to collagen fiber interactions which take place on the intrafiber level such as fiber stiffness. The insensitivity of MR based diffusion measurements to collagen hydrogels of different cross-linking states alludes that congeneric collagen structures in connective tissues do not hinder extracellular diffusive water transport. Furthermore, the glutaraldehyde induced rigorous changes in viscoelastic properties indicate that intrafibrillar dissipation is the dominant mode of viscous dissipation in collagen-dominated connective tissue.

The quest for high spatial resolution diffusion-weighted imaging of the human brain in vivo

Diffusion-weighted imaging, a contrast unique to MRI, is used for assessment of tissue microstructure in vivo. However, this exquisite sensitivity to finer scales far above imaging resolution comes at the cost of vulnerability to errors caused by sources of motion other than diffusion motion. Addressing the issue of motion has traditionally limited diffusion-weighted imaging to a few acquisition techniques and, as a consequence, to poorer spatial resolution than other MRI applications. Advances in MRI imaging methodology have allowed diffusion-weighted MRI to push to ever higher spatial resolution. In this review we focus on the pulse sequences and associated techniques under development that have pushed the limits of image quality and spatial resolution in diffusion-weighted MRI.

Hepatocellular Carcinoma: State of the Art Imaging and Recent Advances

The incidence of hepatocellular carcinoma (HCC) is increasing, with this trend expected to continue to the year 2030. Hepatocarcinogenesis follows a predictable course, which makes adequate identification and surveillance of at-risk individuals central to a successful outcome. Moreover, imaging is central to this surveillance, and ultimately to diagnosis and management. Many liver study groups throughout Asia, North America and Europe advocate a surveillance program for at-risk individuals to allow early identification of HCC. Ultrasound is the most commonly utilized imaging modality. Many societies offer guidelines on how to diagnose HCC. The Liver Image Reporting and Data System (LIRADS) was introduced to standardize the acquisition, interpretation, reporting and data collection of HCC cases. The LIRADS advocates diagnosis using multiphase computed tomography or magnetic resonance imaging (MRI) imaging. The 2017 version also introduces contrast-enhanced ultrasound as a novel approach to diagnosis. Indeed, imaging techniques have evolved to improve diagnostic accuracy and characterization of HCC lesions. Newer techniques, such as T1 mapping, intravoxel incoherent motion analysis and textural analysis, assess specific characteristics that may help grade the tumor and guide management, allowing for a more personalized approach to patient care. This review aims to analyze the utility of imaging in the surveillance and diagnosis of HCC and to assess novel techniques which may increase the accuracy of imaging and determine optimal treatment strategies.

Questionable correlation of the apparent diffusion coefficient with the histological grade and microvascular invasion in small hepatocellular carcinoma

AIM

To evaluate the correlation between the apparent diffusion coefficient (ADC) and various histopathological parameters in small hepatocellular carcinomas (HCCs).

MATERIALS AND METHODS

In 143 surgically resected small HCCs, the mean and minimum ADC values, tumour-to-liver ADC ratio, and normalised ADC (ADC of the HCC/ADC of the spleen) were correlated to the tumour grade, microvascular invasion (MVI), cellularity, fatty change, degree of fibrosis, and lymphocytic infiltration using linear regression analysis, the Wilcoxon rank sum test, or Spearman's rank correlation.

RESULTS

No significant correlation was found between the ADC parameters and tumour grade. In the univariate analysis, the ADC ratio of the tumour was significantly correlated with MVI as well as the degree of fibrosis and lymphocyte infiltration of the HCC (p=0.017, 0.042, and 0.002, respectively). The ADC of the tumour was significantly correlated with the degree of lymphocyte infiltration of the HCC (p=0.049). In the multivariate analysis, the ADC ratio of the tumour was an independent parameter for MVI and the degree of lymphocyte infiltration of the HCC (p=0.034 and <0.001, respectively), and the ADC of the tumour was an independent parameter for the degree of lymphocyte infiltration of the HCC (p=0.009). There was no significant correlation between the other ADCs and pathological tumour parameters.

CONCLUSION

The tumour grade of small HCCs was not correlated with ADC parameters. The tumour-to-liver ADC ratio was a significant independent parameter for the degree of lymphocyte infiltration and MVI of small HCCs.

Intravoxel incoherent motion diffusion-weighted imaging for assessment of histologic grade of hepatocellular carcinoma: comparison of three methods for positioning region of interest

OBJECTIVES

To prospectively compare the diagnostic performances of three methods of region of interest (ROI) placement for the measurements of intravoxel incoherent motion (IVIM) diffusion-weighted MR imaging in differentiating the histologic grade of hepatocellular carcinoma (HCC).

METHODS

Eighty-seven patients with 91 newly diagnosed HCCs were studied using IVIM imaging. Two attending radiologists separately identified the selection of tumour tissue for ROI positioning. Three different ROI positioning methods, namely the whole tumour volume (WTV) method, three-ROI method and one-section method, were used for the measurement. Kruskal-Wallis rank test or one-way ANOVA was used to compare the difference in IVIM parameters and ADC across the three different ROI positioning methods. Spearman correlation analysis was used to determine the correlation between each parameter and Edmondson-Steiner (E-S) grade. Receiver operating characteristics (ROC) curve analyses were performed to evaluate the diagnostic performance.

RESULTS

For the ADC and ADCslow, the mean value measured by using the WTV method was significant higher than the one-section and three-ROI methods (all p < 0.01). For the ADCslow, the highest area under curve (AUC) with a value of 0.969 was obtained by using the WTV method, followed by the one-section method (AUC = 0.938) and three-ROI method (AUC = 0.873). Additionally, for the ADC, AUC values were 0.861 for WTV method, 0.840 for one-section method and 0.806 for three-ROI method.

CONCLUSIONS

Different ROI positioning methods used significantly affect the IVIM parameters and ADC measurements. Measurements of ADCslow value derived from WTV method entailed the highest diagnostic performance in grading HCC.

KEY POINTS

• Diffusion MRI is useful for non-invasively differentiating the histologic grade of hepatocellular carcinoma. • Different ROI positioning methods used significantly affect the IVIM parameters and ADC measurements. • IVIM model is advantageous over mono-exponential model for assessing the histologic grade of hepatocellular carcinoma.

Predicting the grade of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature

PURPOSE

This study was conducted in order to investigate the value of magnetic resonance imaging (MRI)-based radiomics signatures for the preoperative prediction of hepatocellular carcinoma (HCC) grade.

METHODS

Data from 170 patients confirmed to have HCC by surgical pathology were divided into a training group (n = 125) and a test group (n = 45). The radiomics features of tumours based on both T1-weighted imaging (WI) and T2WI were extracted by using Matrix Laboratory (MATLAB), and radiomics signatures were generated using the least absolute shrinkage and selection operator (LASSO) logistic regression model. The predicted values of pathological HCC grades using radiomics signatures, clinical factors (including age, sex, tumour size, alpha fetoprotein (AFP) level, history of hepatitis B, hepatocirrhosis, portal vein tumour thrombosis, portal hypertension and pseudocapsule) and the combined models were assessed.

RESULTS

Radiomics signatures could successfully categorise high-grade and low-grade HCC cases (p < 0.05) in both the training and test datasets. Regarding the performances of clinical factors, radiomics signatures and the combined clinical and radiomics signature (from the combined T1WI and T2WI images) models for HCC grading prediction, the areas under the curve (AUCs) were 0.600, 0.742 and 0.800 in the test datasets, respectively. Both the AFP level and radiomics signature were independent predictors of HCC grade (p < 0.05).

CONCLUSIONS

Radiomics signatures may be important for discriminating high-grade and low-grade HCC cases. The combination of the radiomics signatures with clinical factors may be helpful for the preoperative prediction of HCC grade.

KEY POINTS

• The radiomics signature based on non-contrast-enhanced MR images was significantly associated with the pathological grade of HCC. • The radiomics signatures based on T1WI or T2WI images performed similarly at predicting the pathological grade of HCC. • Combining the radiomics signature and clinical factors (including age, sex, tumour size, AFP level, history of hepatitis B, hepatocirrhosis, portal vein tumour thrombosis, portal hypertension and pseudocapsule) may be helpful for the preoperative prediction of HCC grade.

Diagnostic value of imaging examinations in patients with primary hepatocellular carcinoma

Primary hepatocellular carcinoma (PHC) includes hepatocellular carcinoma, intrahepatic cholangiocarcinoma and other pathological types and is characterized by rapid progression. Most of the clinical diagnoses are made at late stage or when distant metastasis occurs, increasing the difficulty of treatment and resulting in a poor prognosis. Therefore, the early diagnosis of PHC plays an important role in timely treatment and the improvement of prognosis. The gold standard for the diagnosis of primary liver cancer is liver biopsy, but it has limitations as an invasive examination. Presently, imaging has become the first choice for the diagnosis of liver cancer. We here summarize the new methods and techniques of imaging in diagnosis and evaluation of primary liver cancer in recent years, including ultrasonography, computed tomography perfusion imaging, diffusion-weighted imaging technology-voxel incoherent motion, diffusion tensor imaging, iterative decomposition of water and fat with echo asymmetry and least squares estimation-iron quantification, dynamic enhanced magnetic resonance imaging and hepatocyte-specific contrast medium imaging. Imaging diagnosis can not only evaluate the degree of differentiation, blood supply and perfusion, and invasiveness of the lesion, but also predict the prognosis, evaluate liver function, and provide references for clinical diagnosis and treatment.

ADC similarity predicts microvascular invasion of bifocal hepatocellular carcinoma

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-(|value_{large lesion}-value_{small lesion}|)/(value_{large lesion} + value_{small 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.

The current role and future prospectives of functional parameters by diffusion weighted imaging in the assessment of histologic grade of HCC

Hepatocellular carcinoma (HCC) is one of the most common human solid malignancies worldwide. Although the MRI is the technique that is best adapted to characterize HCC, there is not an agreement regarding the study protocol and even what the role of Diffusion-weighted imaging (DWI). The possibility that imaging study can correlate to histologic grade to selecting the therapeutic strategy would be valuable in helping to direct the proper management of HCC. Apparent Diffusion Coefficient (ADC) and IVIM-derived perfusion fraction (fp) and tissue diffusivity (Dt) values of HCC showed significantly better diagnostic performance in differentiating high-grade HCC from low-grade HCC, and significant correlation was observed between ADC, fp, Dt and histological grade.

Differentiating malignant from benign hyperintense nodules on unenhanced T1-weighted images in patients with chronic liver disease: using gadoxetic acid-enhanced and diffusion-weighted MR imaging

PURPOSE

To evaluate value of gadoxetic acid-enhanced and diffusion-weighted (DW) MRI for distinguishing malignant from benign hyperintense nodules on unenhanced T1-weighted images (T1WIs) in patients with chronic liver disease.

MATERIALS AND METHODS

Forty-two patients with 37 malignant and 41 benign hyperintense nodules on unenhanced T1WIs who underwent gadoxetic acid-enhanced and DW MRI, followed by histopathological examination, were included. Qualitative and quantitative analyses were conducted. Significant findings on univariate and multivariate analyses were identified and their diagnostic performances were analyzed for predicting hyperintense hepatocellular carcinomas (HCCs).

RESULTS

In univariate analysis, hyperintensity on T2WI, arterial enhancement, washout, hypointensity on hepatobiliary phase, and diffusion restriction were more frequently observed (P < 0.05) in hyperintense HCCs. Tumor-to-liver SI ratio on hepatobiliary phase and minimum apparent diffusion coefficient (ADC_min) were significantly lower in hyperintense HCCs (P < 0.05). In multivariate analysis, hyperintensity on T2WI (OR, 13.58; P = 0.02), arterial enhancement (OR, 8.21; P = 0.002), and ADC_min ≤ 0.83 × 10^-3 mm²/s (OR, 6.88; P = 0.008) were independently significant factors for predicting hyperintense HCCs. When two of three criteria were combined, 75.7% (28/37) of hyperintense HCCs were identified with a specificity of 92.7%, and when all three criteria were satisfied, the specificity was 97.6%.

CONCLUSION

Gadoxetic acid-enhanced and DW MRI may be helpful for differentiating malignant from benign hyperintense nodules on unenhanced T1WI.

Preoperative prediction of microvascular invasion of hepatocellular carcinoma with IVIM diffusion-weighted MR imaging and Gd-EOB-DTPA-enhanced MR imaging

Microvascular invasion (MVI) is regarded as one of the independent risk factors for recurrence and poor prognosis of hepatocellular carcinoma (HCC). The presence of MVI in HCCs was evaluated on the basis of pathological reports of surgical specimens and was defined as tumor within a vascular space lined by endothelium that was visible only on microscopy. The aim of the study was to investigate the usefulness of intravoxel incoherent motion (IVIM) diffusion weighted (DW) magnetic resonance (MR) imaging in predicting MVI of HCC. Preoperative IVIM DW imaging and Gd-EOB-DTPA-enhanced MRI (DCE-MRI) of 51 patients were analyzed. Standard apparent diffusion coefficient (ADC), D (the true diffusion coefficient), D* (the pseudodiffusion coefficient) and f (the perfusion fraction), relative enhancement (RE) and radiological features were evaluated and analyzed. Univariate analysis revealed that HCCs with MVI had a higher portion of an irregular tumor shape than HCCs without MVI (p = 0.009), the Standard ADC, D value were significantly lower in HCCs with MVI (p = 0.022, p = 0.007, respectively). Multivariate analysis revealed that an irregular shape (p = 0.012) and D value ≤ 1.16×10^-3mm²/sec (p = 0.048) were independent predictors for MVI. Combining the two factors of an irregular shape and D value, a sensitivity of 94.4% and specificity of 63.6% for predicting MVI was obtained. In conclusion, we found that an irregular shape and D value ≤ 1.16×10^-3mm²/sec may suggest the presence of MVI in HCCs.

Apparent diffusion coefficient of hepatocellular carcinoma on diffusion-weighted imaging: Histopathologic tumor grade versus arterial vascularity during dynamic magnetic resonance imaging

Objectives

Apparent diffusion coefficient (ADC) has been suggested to reflect the tumor grades of hepatocellular carcinomas (HCCs); i.e., it can be used as a biomarker to predict the patients’ prognosis. To verify its feasibility as a biomarker, the present study sought to determine how the ADC values of HCC are affected by a tumor’s histopathologic grade and arterial vascularity.

Materials and methods

From 131 consecutive patients, 141 surgically resected HCCs (16 well-differentiated [wd-HCCs], 83 moderately-differentiated [md-HCCs], and 42 poorly-differentiated HCCs [pd-HCCs]) were subjected to a comparison of the tumors’ arterial vascularity (non-, slightly-, or markedly-hypervascular) determined on dynamic magnetic resonance imaging (MRI) and the ADC was measured retrospectively.

Results

The pd-HCCs (1.05±0.16 × 10⁻³ mm²/s) had a significantly lower ADC than md-HCCs (1.16±0.21 × 10⁻³ mm²/s; p = 0.010), but there was no significant difference compared to wd-HCCs (1.11±0.18 × 10⁻³ mm²/s; p = 0.968). The mean ADC was significantly higher in markedly hypervascular lesions (1.20±0.20 × 10⁻³ mm²/s) than in nonhypervascular lesions (0.95±0.14 × 10⁻³mm²/s; p<0.001) or slightly hypervascular lesions (1.04±0.15 × 10⁻³mm²/s; p<0.001). The ADC values and arterial vascularity were significantly correlated in wd-HCCs (p = 0.005) and md-HCCs (p<0.001). The mean ADC of pd-HCCs was significantly lower than those of other lesions, even in the markedly hypervascular lesion subgroup (p = 0.020).

Conclusion

Although pd-HCC constantly shows low ADCs regardless of arterial vascularities, ADCs cannot stably stratify histopathologic tumor grades due to the variable features of wd-HCCs; and the ADC should be used with caution as a tumor biomarker of HCC.

Diffusion-weighted imaging in evaluating the efficacy of concurrent chemoradiotherapy in the treatment of non-small cell lung cancer

Objective:

To explore the predictive value of diffusion-weighted imaging (DWI) in evaluating the short-term efficacy of concurrent chemoradiotherapy (CCRT) in the treatment of patients with non-small cell lung cancer (NSCLC).

Methods:

A total of 192 patients with NSCLC were selected and treated with CCRT. Dynamic contrast-enhanced magnetic resonance imaging combined with DWI was performed on all patients before and after CCRT treatment. Correspondingly, apparent diffusion coefficient (ADC) values were recorded before treatment (ADCpre), during treatment (ADCmid), and after treatment (ADCpost). Tumor response was evaluated as complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD). Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic power of quantitative DWI parameters in predicting the short-term efficacy of CCRT for patients with NSCLC.

Results:

There were 21 patients with CR, 82 with PR, 77 with SD, and 12 with PD. The ADCpre was negatively correlated with tumor regression rate, whereas ADCmid, ADCpost, and their respective change rates ∆ADCmid and ∆ADCpost were positively related to tumor regression rate. The ROC curve analysis suggested ADCpre = 1.38 × 10−3 mm2/s, ∆ADCmid = 14.14%, and ∆ADCpost = 20.39% as thresholds to predict the short-term efficacy of CCRT, with corresponding areas under the curve of 0.637, 0.743, and 0.752, respectively.

Conclusions:

These findings indicate that DWI provides promising predictive value in evaluating the short-term efficacy of CCRT in the treatment of patients with NSCLC.

Intravoxel incoherent motion (IVIM) in diffusion-weighted imaging (DWI) for Hepatocellular carcinoma: correlation with histologic grade

Purpose

To assess the correlation between DWI diffusion parameters obtained using Intravoxel Incoherent Motion Method (IVIM) and histological grade of Hepatocellular carcinoma (HCC).

Results

According to Edmondson-Steiner grade lesions were classified with grade 1 (14), grade 2 (30), grade 3 (18), and grade 4 (0). Apparent Diffusion Coefficient (ADC), perfusion fraction (fp), tissue diffusion coefficient (Dt) median values were statistically different in HCC groups with 1, 2, 3 histological grade (p<0.001). A significant correlation was reported between ADC, fp, Dt and histologic grade respectively of 0.687, 0.737 and 0.674. Receiver operating characteristic (ROC) analysis demonstrated that an ADC of 2.11×10-3 mm2/sec, an fp of 47.33% and an Dt of 0.94×10-3 mm²/sec were the optimal cutoff values to differentiate high histological grade (3) versus low histological grade (1-2), with a sensitivity and specificity for ADC of 100% and 100%, for fp of 100% and 89%, for Dt of 100% and 74%, respectively.

Material and Methods

A retrospective approved study was performed including 34 patients with 62 HCCs. IVIM was performed to obtain ADC, fp, pseudo-diffusion coefficient (Dp), Dt coefficients. Kruskal Wallis, Spearman Correlation Coefficient, ROC analysis were performed.

Conclusions

ADC and IVIM-derived fp showed significantly better diagnostic performance in differentiating high-grade from low-grade HCC, and significant correlation was observed between ADC, fp, Dt and histological grade.

Prediction of histological grade of hepatocellular carcinoma using quantitative diffusion-weighted MRI: a retrospective multivendor study

OBJECTIVE

To evaluate the usefulness of quantitative diffusion-weighted (DW) imaging acquired by multivendor magnetic resonance units for predicting grade of hepatocellular carcinoma (HCC).

METHODS

83 patients with 100 histologically diagnosed HCCs who underwent pre-operative liver DW imaging with b = 0 and1000 s mm^-2 or b = 0 and800 s mm^-2 at any of six institutions were included. Two radiologists independently measured the apparent diffusion coefficient (ADC) of the lesion as well as non-ADC parameters, such as the relative contrast ratio and the contrast-to-noise ratio (CNR) between the lesion and the liver parenchyma on high b-value DW images. The diagnostic performance of the DW parameters in discriminating poorly-differentiated HCCs was compared using receiver operating characteristic (ROC) analysis.

RESULTS

The areas under the receiver operating characteristic curves for the CNR (86.4% [95% confidence interval (CI) (77.2-95.6] and 83.9% [95% CI 71.2-96.6] for b = 1000 and 800 s mm^-2, respectively] and the relative contrast ratio (85.3% [95% CI 75.5-94.8] and 83.5% [95% CI 70.5-96.4]) tended to be superior to the ADC [71.1% [95% CI (56.9-85.2)] and 75.7% [95% CI (55.1-96.2)]; p < 0.05 for CNR vs ADC for b = 1000 s mm^-2, but not significant for other parameters) for discrimination of poorly-differentiated HCCs.

CONCLUSION

All DW parameters could discriminate HCC grade. Non-ADC parameters might be more useful than the ADC for predicting poorly-differentiated HCCs. Advances in knowledge: The utility of quantitative DW parameters for predicting HCC grade was demonstrated by using multivendor MR units.

LI-RADS® ancillary features on CT and MRI

The Liver Imaging Reporting and Data System (LI-RADS) uses an algorithm to assign categories that reflect the probability of hepatocellular carcinoma (HCC), non-HCC malignancy, or benignity. Unlike other imaging algorithms, LI-RADS utilizes ancillary features (AFs) to refine the final category. AFs in LI-RADS v2017 are divided into those favoring malignancy in general, those favoring HCC specifically, and those favoring benignity. Additionally, LI-RADS v2017 provides new rules regarding application of AFs. The purpose of this review is to discuss ancillary features included in LI-RADS v2017, the rationale for their use, potential pitfalls encountered in their interpretation, and tips on their application.

Diffusion weighted magnetic resonance imaging of liver: Principles, clinical applications and recent updates

Diffusion-weighted imaging (DWI), a functional imaging technique exploiting the Brownian motion of water molecules, is increasingly shown to have value in various oncological and non-oncological applications. Factors such as the ease of acquisition and ability to obtain functional information in the absence of intravenous contrast, especially in patients with abnormal renal function, have contributed to the growing interest in exploring clinical applications of DWI. In the liver, DWI demonstrates a gamut of clinical applications ranging from detecting focal liver lesions to monitoring response in patients undergoing serial follow-up after loco-regional and systemic therapies. DWI is also being applied in the evaluation of diffuse liver diseases such as non-alcoholic fatty liver disease, hepatic fibrosis and cirrhosis. In this review, we intend to review the basic principles, technique, current clinical applications and future trends of DW-MRI in the liver.

Evaluating histologic differentiation of hepatitis B virus-related hepatocellular carcinoma using intravoxel incoherent motion and AFP levels alone and in combination

PURPOSE

To evaluate histologic differentiation of hepatitis B virus (HBV)-related hepatocellular carcinomas (HCCs) using apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM)-derived metrics and to compare findings with alpha-fetoprotein (AFP) levels alone and in combination.

MATERIALS AND METHOD

One hundred and six chronic HBV-related HCC patients who underwent IVIM diffusion-weighted magnetic resonance imaging with eleven b values were enrolled. Mean ADC, diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) values were determined for all detected lesions. The metrics and AFP levels of different histologically differentiated groups were compared. Spearman's rank correlation was used to assess the statistical dependence among the histologically differentiated HCCs. Receiver operating characteristic (ROC) analysis was performed to evaluate diagnostic performance of these metrics and AFP levels alone and in combination.

RESULTS

ADC, D, and f values and AFP levels were significantly different among well-, moderately, and poorly differentiated HCCs. The four metrics were significantly correlated with histologic differentiation. The area under the ROC curve (AUC-ROC) of ADC, D, f, and AFP for diagnosing well-differentiated HCCs was 0.903, 0.84, 0.782, and 0.806, respectively, and the AUC-ROC of above metrics for diagnosing poorly differentiated HCCs was 0.787, 0.726, 0.624, and 0.633, respectively. The combination of ADC and AFP provided an AUC-ROC of 0.945 for well-differentiated HCC. However, this did not provide better performance for diagnosing poorly differentiated HCC.

CONCLUSION

ADC, IVIM metrics, and AFP levels may be useful for evaluating histologic differentiation of HBV-related HCCs, and the combination of ADC and AFP provides better diagnostic performance for well-differentiated HCC.

Characterization of small (≤3 cm) hepatic lesions with atypical enhancement feature and hypointensity in hepatobiliary phase of gadoxetic acid-enhanced MRI in cirrhosis: A STARD-compliant article

It is difficult to characterize the nodular lesions in cirrhotic liver if typical enhancement pattern is not present on dynamic contrast-enhanced imagings. Although the signal intensity of the hepatobiliary phase in gadoxetic acid-enhanced magnetic resonance imaging (MRI) is helpful for characterization of the lesions, some dysplastic nodules may also exhibit low signal intensity in the hepatobiliary phase. We aimed to assess the usefulness of gadoxetic acid (Gd-EOB-DTPA)-enhanced MRI including diffusion-weighted imaging (DWI) for differentiation between atypical small hepatocellular carcinomas (HCCs) and dysplastic nodules showing low signal intensity (SI) in the hepatobiliary phase, and to evaluate the MRI findings in determining the histological grade of atypical HCCs in patients with cirrhosis.A total of 43 cirrhotic patients with a small (≤3 cm) liver nodule (n = 25, HCC; n = 18, dysplastic nodule) who underwent Gd-EOB-DTPA-enhanced MRI and pathologic confirmation were retrospectively reviewed. Atypical HCC was defined as not showing arterial hyperenhancement and delayed washout on dynamic MRI.High SI on both T2WI and DWI (sensitivity 80.0%, specificity 100%, positive predictive value 100%, negative predictive value 78.3%) was the most specific feature to differentiate atypical HCCs from dysplastic nodules. High SI on both T2WI and DWI (100% vs 61.5%, P = .039) or low SI on pre-enhanced T1WI (83.3% vs 30.8%, P = .021) was more frequent observed in Edmonson grade II-III HCCs compared with those in grade I HCCs.The combination of DWI and T2WI is most useful for the differentiation of atypical small HCCs from dysplastic nodules showing low SI in the hepatobiliary phase. Combination of DWI and T2WI or pre-enhanced T1WI seems to be useful for predicting the histological grade of atypical HCCs.

Major and ancillary magnetic resonance features of LI-RADS to assess HCC: an overview and update

Liver Imaging Reporting and Data System (LI-RADS) is a system for interpreting and reporting of imaging features on multidetector computed tomography (MDCT) and magnetic resonance (MR) studies in patients at risk for hepatocellular carcinoma (HCC). American College of Radiology (ACR) sustained the spread of LI-RADS to homogenizing the interpreting and reporting data of HCC patients. Diagnosis of HCC is due to the presence of major imaging features. Major features are imaging data used to categorize LI-RADS-3, LI-RADS-4, and LI-RADS-5 and include arterial-phase hyperenhancement, tumor diameter, washout appearance, capsule appearance and threshold growth. Ancillary are features that can be used to modify the LI-RADS classification. Ancillary features supporting malignancy (diffusion restriction, moderate T2 hyperintensity, T1 hypointensity on hapatospecifc phase) can be used to upgrade category by one or more categories, but not beyond LI-RADS-4. Our purpose is reporting an overview and update of major and ancillary MR imaging features in assessment of HCC.

Critical analysis of the major and ancillary imaging features of LI-RADS on 127 proven HCCs evaluated with functional and morphological MRI: Lights and shadows

PURPOSE

To report a critical analysis of major and ancillary MR imaging features in assessment of HCC.

METHODS

Retrospectively we evaluated 70 cirrhotic patients with 173 nodules, which were subjected to MR study at 0 time (MR0), after 3 (MR3) and 6 months (MR6) using two different contrast media. EOB-GD-DTPA was injected at MR0 and MR6, while Gd-BT-DO3A at MR3. Three expert hepatic radiologists reviewed all images, recording, according to LI-RADS, the size, the presence and quality of arterial-phase hyperenhancement, washout and capsule appearance, threshold growth. Additionally, we recorded signal intensity (SI) on T2-W images, on DWI, on apparent diffusion coefficient (ADC) maps and SI on T1-W images of EOB-GD-BPTA hepatospecific phase. Median value of ADC and of Intravoxel incoherent motion related parameters were assessed.

RESULTS

127 HCCs and 24 dysplastic nodules were assessed. Hypervascular on arterial phase was found in 84 HCCs, washout appearance in 124, capsule appearance in 111, hypointensity on hepatospecific phase in 127, hyperintensity on T2-W sequences and restricted diffusion in 107. Hyper vascular on arterial phase was found in 17 dysplastic nodules, wash-out appearance in 2, hypointensity on hepatospecific phase in 7 while no dysplastic nodules showed capsule appearance, hyperintensity on T2-W and restricted diffusion. Highest accuracy was obtained by washout appearance and hypointense signal on hepatospecific phase (97% and 95%).

CONCLUSIONS

Hypointensity on hepatospecific phase and washout appearance are the most relevant diagnostic sign for differentiating low-risk from high-risk HCC nodules. The capsule appearance, T2-W hyperintensity and restricted diffusion have high positive predictive value.

Subcentimeter hypervascular nodules with typical imaging findings of hepatocellular carcinoma on gadoxetic acid-enhanced MRI: Outcomes of early treatment and watchful waiting

OBJECTIVES

To compare treatment outcomes of subcentimeter hypervascular nodules at high risk for developing into hepatocellular carcinomas (SHNHR) between early treatment and watchful waiting until progression to overt hepatocellular carcinoma (HCC) groups.

METHODS

SHNHRs were defined as subcentimeter hypervascular nodules with the usual imaging features of HCC on gadoxetic acid-enhanced magnetic resonance imaging (MRI). Among 63 patients with 74 SHNHRs, 27 (37 SHNHRs) received early treatment (treatment of < 1 cm nodules), and 36 (37 SHNHRs) underwent watchful waiting until progression to overt HCC. Risk factor analysis was performed for recurrence-free and local recurrence-free survival.

RESULTS

Among the 36 patients who adopted watchful waiting, 33 eventually underwent treatment because their SHNHRs progressed to overt HCC. For recurrence-free survival, significant risk factors included number of previous treatments (HR, 1.181; p < 0.001), tumour number (HR, 1.943; p = 0.009), and α-feto protein level (HR, 1.005; p = 0.037) in the multivariate analyses. Treatment strategy was not a significant risk factor for recurrence-free survival. For local recurrence-free survival from the date of treatment, only treatment modality (transarterial chemoembolization) (HR, 6.879; p = 0.002) was a significant risk factor.

CONCLUSION

Recurrence-free survival was not significantly different between early treatment and watchful waiting for SHNHRs.

KEY POINTS

• Recurrence-free survival did not vary between the two treatment strategies. • Treatment modality was a significant factor for local recurrence-free survival. • Number of treatments, tumour number, and α-FP were risk factors for recurrence.