2017 Version of LI-RADS for CT and MR Imaging: An Update

High-resolution free-breathing hepatobiliary phase MRI of the liver using XD-GRASP

PURPOSE

To evaluate the performance of high-resolution free-breathing (FB) hepatobiliary phase imaging of the liver using the eXtra-Dimension Golden-angle RAdial Sparse Parallel (XD-GRASP) MRI technique.

METHODS

Fifty-eight clinical patients (41 males, mean age = 52.9 ± 12.9) with liver lesions who underwent dynamic contrast-enhanced MRI with a liver-specific contrast agent were prospectively recruited for this study. Both breath-hold volumetric interpolated examination (BH-VIBE) imaging and FB imaging were performed during the hepatobiliary phase. FB images were acquired using a stack-of-stars golden-angle radial sequence and were reconstructed using the XD-GRASP method. Two experienced radiologists blinded to acquisition schemes independently scored the overall image quality, liver edge sharpness, hepatic vessel clarity, conspicuity of lesion, and overall artifact level of each image. The non-parametric paired two-tailed Wilcoxon signed-rank test was used for statistical analysis.

RESULTS

Compared to BH-VIBE images, XD-GRASP images received significantly higher scores (P < 0.05) for the liver edge sharpness (4.83 ± 0.45 vs 4.29 ± 0.46), the hepatic vessel clarity (4.64 ± 0.67 vs 4.15 ± 0.56) and the conspicuity of lesion (4.75 ± 0.53 vs 4.31 ± 0.50). There were no significant differences (P > 0.05) between BH-VIBE and XD-GRASP images for the overall image quality (4.61 ± 0.50 vs 4.74 ± 0.47) and the overall artifact level (4.13 ± 0.44 vs 4.05 ± 0.61).

CONCLUSION

Compared to conventional BH-VIBE MRI, FB radial acquisition combined with XD-GRASP reconstruction facilitates higher spatial resolution imaging of the liver during the hepatobiliary phase. This enhancement can significantly improve the visualization and evaluation of the liver.

Efficacy and safety of robotic versus laparoscopic liver resection for hepatocellular carcinoma: a propensity score-matched retrospective cohort study

BACKGROUND

Evidence concerning long-term outcome of robotic liver resection (RLR) and laparoscopic liver resection (LLR) for hepatocellular carcinoma (HCC) patients is scarce.

METHODS

This study enrolled all patients who underwent RLR and LLR for resectable HCC between July 2016 and July 2021. Propensity score matching (PSM) was employed to create a 1:3 match between the RLR and LLR groups. A comprehensive collection and analysis of patient data regarding efficacy and safety have been conducted, along with the evaluation of the learning curve for RLR.

RESULTS

Following PSM, a total of 341 patients were included, with 97 in the RLR group and 244 in the LLR group. RLR group demonstrated a significantly longer operative time (median [IQR], 210 [152.0-298.0] min vs. 183.5 [132.3-263.5] min; p = 0.04), with no significant differences in other perioperative and short-term postoperative outcomes. Overall survival (OS) was similar between the two groups (p = 0.43), but RLR group exhibited improved recurrence-free survival (RFS) (median of 65 months vs. 56 months, p = 0.006). The estimated 5-year OS for RLR and LLR were 74.8% (95% CI: 65.4-85.6%) and 80.7% (95% CI: 74.0-88.1%), respectively. The estimated 5-year RFS for RLR and LLR were 58.6% (95% CI: 48.6-70.6%) and 38.3% (95% CI: 26.4-55.9%), respectively. In the multivariate Cox regression analysis, RLR (HR: 0.586, 95% CI (0.393-0.874), p = 0.008) emerged as an independent predictor of reducing recurrence rates and enhanced RFS. The operative learning curve indicates that approximately after the 11th case, the learning curve of RLR stabilized and entered a proficient phase.

CONCLUSIONS

OS was comparable between RLR and LLR, and while RFS was improved in the RLR group. RLR demonstrates oncological effectiveness and safety for resectable HCC.

Evidence Supporting Diagnostic Value of Liver Imaging Reporting and Data System for CT- and MR Imaging-based Diagnosis of Hepatocellular Carcinoma: A Systematic Review and Meta-analysis

Background

Based on the Liver Imaging Data and Reporting System (LI-RADS) guidelines, Hepatocellular Carcinoma (HCC) can be diagnosed using imaging criteria in patients at risk of HCC.

Objective

This study aimed to assess the diagnostic value of LI-RADS in high-risk patients with HCC.

Material and Methods

This systematic review is conducted on international databases, including Google Scholar, Web of Science, PubMed, Embase, PROQUEST, and Cochrane Library, with appropriate keywords. Using the binomial distribution formula, the variance of each study was calculated, and all the data were analyzed using STATA version 16. The pooled sensitivity and specificity were determined using a random-effects meta-analysis approach. Also, we used the chi-squared test and I2 index to calculate heterogeneity among studies, and Funnel plots and Egger tests were used for evaluating publication bias.

Results

The pooled sensitivity was estimated at 0.80 (95% CI 0.76-0.84). According to different types of Liver Imaging Reporting and Data Systems (LI-RADS), the highest pooled sensitivity was in version 2018 (0.83 (95% CI 0.79-0.87) (I2: 80.6%, P of chi 2 test for heterogeneity <0.001 and T2: 0.001). The pooled specificity was estimated as 0.89 (95% CI 0.87-0.92). According to different types of LI-RADS, the highest pooled specificity was in version 2014 (93.0 (95% CI 89.0-96.0) (I2: 81.7%, P of chi 2 test for heterogeneity <0.001 and T2: 0.001).

Conclusion

LI-RADS can assist radiologists in achieving the required sensitivity and specificity in high-risk patients suspected to have HCC. Therefore, this strategy can serve as an appropriate tool for identifying HCC.

The Value of LI-RADS and Radiomic Features From MRI for Predicting Microvascular Invasion in Hepatocellular Carcinoma within 5 cm

RATIONALE AND OBJECTIVES

To explore and compare the performance of LI-RADS® and radiomics from multiparametric MRI in predicting microvascular invasion (MVI) preoperatively in patients with solitary hepatocellular carcinoma (HCC)< 5 cm.

METHODS

We enrolled 143 patients with pathologically proven HCC and randomly stratified them into training (n = 100) and internal validation (n = 43) cohorts. Besides, 53 patients were enrolled to constitute an independent test cohort. Clinical factors and imaging features, including LI-RADS and three other features (non-smooth margin, incomplete capsule, and two-trait predictor of venous invasion), were reviewed and analyzed. Radiomic features from four MRI sequences were extracted. The independent clinic-imaging (clinical) and radiomics model for MVI-prediction were constructed by logistic regression and AdaBoost respectively. And the clinic-radiomics combined model was further constructed by logistic regression. We assessed the model discrimination, calibration, and clinical usefulness by using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision-curve analysis respectively.

RESULTS

Incomplete tumor capsule, corona enhancement, and radiomic features were related to MVI in solitary HCC＜5 cm. The clinical model achieved AUC of 0.694/0.661 (training/internal validation). The single-sequence-based radiomic model's AUCs were 0.753-0.843/0.698-0.767 (training/internal validation). The combination model exhibited superior diagnostic performance to the clinical model (AUC: 0.895/0.848 [training/ internal validation]) and yielded an AUC of 0.858 in an independent test cohort.

CONCLUSION

Incomplete tumor capsule and corona enhancement on preoperative MRI were significantly related to MVI in solitary HCC＜5 cm. Multiple-sequence radiomic features potentially improve MVI-prediction-model performance, which could potentially help determining HCC's appropriate therapy.

Budd-Chiari syndrome in children: Radiological intervention and role of shear wave elastography in monitoring response

OBJECTIVES

Radiological intervention (RI) is the preferred treatment in children with Budd-Chiari syndrome (BCS). We studied the comparative long-term outcome of BCS children, with and without RI and utility of liver and splenic stiffness measurement (LSM, SSM) by 2-dimensional shear wave elastography (2D-SWE) in assessing response.

METHODS

Sixty children (40 boys, median age 10.5 [6.5-15.25] years) with BCS (29 newly diagnosed, 31 follow-up) were evaluated. LSM and SSM by 2D-SWE and vascular patency were monitored pre- and postprocedure (≥ 6 months postprocedure) in those undergoing RI. Medical therapy without anticoagulation and monitoring was done in subjects without RI. The RI and no-RI groups were compared.

RESULTS

Ascites (54,90%), hepatomegaly (56,93%) and prominent abdominal-veins (42,70%), were the commonest features. The majority (46,78%) had isolated hepatic vein block. 44 (73%) cases underwent RI, while 16 (27%) were managed conservatively. Both groups were similar at baseline. Post-RI subjects showed significant improvement in clinical findings, liver functions and portal hypertension. LSM [33 (32-34.5) to 19.2 (18-20.67) kPa] and SSM [54.5 (52.3-57.6) to 28.9 (27.6-30.25) kPa] showed a significant decline from baseline value over a follow-up of 12 (6-13) months. Gradual reduction occurred in the LSM and SSM over 1-5 years, with near-normal LSM [10.2 (9.2-11.5) kPa] and SSM [22.3 (20.5-24.3) kPa] values in patients (n-16) with > 5 years follow-up. Patients without RI showed worsening in LSM and SSM. Hepatopulmonary syndrome and hepatocellular carcinoma developed in 4 (8%) and 1 (1.7%) cases respectively.

CONCLUSION

RI leads to clinical recovery and reduction with near normalization of LSM and SSM over long-term follow-up in children with BCS. 2D-SWE is a promising tool to monitor outcomes.

Consensus report from the 10th Global Forum for Liver Magnetic Resonance Imaging: developments in HCC management

The 10th Global Forum for Liver Magnetic Resonance Imaging (MRI) was held as a virtual 2-day meeting in October 2021, attended by delegates from North and South America, Asia, Australia, and Europe. Most delegates were radiologists with experience in liver MRI, with representation also from specialists in liver surgery, oncology, and hepatology. Presentations, discussions, and working groups at the Forum focused on the following themes: • Gadoxetic acid in clinical practice: Eastern and Western perspectives on current uses and challenges in hepatocellular carcinoma (HCC) screening/surveillance, diagnosis, and management • Economics and outcomes of HCC imaging • Radiomics, artificial intelligence (AI) and deep learning (DL) applications of MRI in HCC. These themes are the subject of the current manuscript. A second manuscript discusses multidisciplinary tumor board perspectives: how to approach early-, mid-, and late-stage HCC management from the perspectives of a liver surgeon, interventional radiologist, and oncologist (Taouli et al, 2023). Delegates voted on consensus statements that were developed by working groups on these meeting themes. A consensus was considered to be reached if at least 80% of the voting delegates agreed on the statements. CLINICAL RELEVANCE STATEMENT: This review highlights the clinical applications of gadoxetic acid-enhanced MRI for liver cancer screening and diagnosis, as well as its cost-effectiveness and the applications of radiomics and AI in patients with liver cancer. KEY POINTS: • Interpretation of gadoxetic acid-enhanced MRI differs slightly between Eastern and Western guidelines, reflecting different regional requirements for sensitivity vs specificity. • Emerging data are encouraging for the cost-effectiveness of gadoxetic acid-enhanced MRI in HCC screening and diagnosis, but more studies are required. • Radiomics and artificial intelligence are likely, in the future, to contribute to the detection, staging, assessment of treatment response and prediction of prognosis of HCC-reducing the burden on radiologists and other specialists and supporting timely and targeted treatment for patients.

The role of enhancing capsule and modified capsule appearances in LI-RADS for diagnosing HCC ≤ 3.0 cm on gadoxetate disodium-enhanced MRI

OBJECTIVES

To evaluate the value of using enhancing capsule (EC) or modified capsule appearance as a major feature in LI-RADS for diagnosing HCC ≤ 3.0 cm on gadoxetate disodium-enhanced MRI (Gd-EOB-MRI), and to explore the relationship between the imaging features and the histological fibrous capsule.

METHODS

This retrospective study enrolled 342 hepatic lesions ≤ 3.0 cm in 319 patients that underwent Gd-EOB-MRIs from January 2018 to March 2021. During dynamic phases and hepatobiliary phase, the modified capsule appearance added the nonenhancing capsule (NEC) (modified LI-RADS + NEC) or corona enhancement (CoE) (modified LI-RADS + CoE) to EC as an alternative capsule appearance. Inter-reader agreement of imaging features was assessed. The diagnostic performances of LI-RADS, LI-RADS with EC ignored, and two modified LI-RADS were compared, followed by Bonferroni correction. Multivariable regression analysis was performed to identify the independent features associated with the histological fibrous capsule.

RESULTS

The inter-reader agreement on EC (0.64) was lower than that on the NEC alternative (0.71) but better than that on CoE alternative (0.58). For HCC diagnosis, compared to LI-RADS, LI-RADS with EC ignored showed significantly lower sensitivity (72.7% vs. 67.4%, p < 0.001) with comparable specificity (89.3% vs. 90.7%, p = 1.000). Two modified LI-RADS showed slightly higher sensitivity and lower specificity than LI-RADS, without statistical significance (all p ≥ 0.006). The AUC was highest with modified LI-RADS + NEC (0.82). Both EC and NEC were significantly associated with the fibrous capsule (p < 0.05).

CONCLUSION

EC appearance improved the diagnostic sensitivity of LI-RADS for HCC ≤ 3.0 cm on Gd-EOB-MRI. Considering NEC as an alternative capsule appearance allowed for better inter-reader reliability and comparable diagnostic ability.

KEY POINTS

• Using the enhancing capsule as a major feature in LI-RADS significantly improved the sensitivity of diagnosing HCC ≤ 3.0 cm without reducing specificity on gadoxetate disodium-enhanced MRI. • Compared to the corona enhancement, the nonenhancing capsule might be a preferable alternative capsule appearance for diagnosing HCC ≤ 3.0 cm. • Capsule appearance should be considered a major feature in LI-RADS for diagnosing HCC ≤ 3.0 cm, regardless whether the capsule appears to be enhancing or nonenhancing.

Machine learning-based radiomics analysis of preoperative functional liver reserve with MRI and CT image

OBJECTIVE

The indocyanine green retention rate at 15 min (ICG-R15) is a useful tool to evaluate the functional liver reserve before hepatectomy for liver cancer. Taking ICG-R15 as criteria, we investigated the ability of a machine learning (ML)-based radiomics model produced by Gd-EOB-DTPA-enhanced hepatic magnetic resonance imaging (MRI) or contrast-enhanced computed tomography (CT) image in evaluating functional liver reserve of hepatocellular carcinoma (HCC) patients.

METHODS

A total of 190 HCC patients with CT, among whom 112 also with MR, were retrospectively enrolled and randomly classified into a training dataset (CT: n = 133, MR: n = 78) and a test dataset (CT: n = 57, MR: n = 34). Then, radiomics features from Gd-EOB-DTPA MRI and CT images were extracted. The features associated with the ICG-R15 classification were selected. Five ML classifiers were used for the ML-model investigation. The accuracy (ACC) and the area under curve (AUC) of receiver operating characteristic (ROC) with 95% confidence intervals (CI) were utilized for ML-model performance evaluation.

RESULTS

A total of 107 different radiomics features were extracted from MRI and CT, respectively. The features related to ICG-R15 which was classified into 10%, 20% and 30% were selected. In MRI groups, classifier XGBoost performed best with its AUC = 0.917 and ACC = 0.882 when the threshold was set as ICG-R15 = 10%. When ICG-R15 = 20%, classifier Random Forest performed best with AUC = 0.979 and ACC = 0.882. When ICG-R15 = 30%, classifier XGBoost performed best with AUC = 0.961 and ACC = 0.941. For CT groups, the classifier XGBoost performed best when ICG-R15 = 10% with AUC = 0.822 and ACC = 0.842. When ICG-R15 = 20%, classifier SVM performed best with AUC = 0.860 and ACC = 0.842. When ICG-R15 = 30%, classifier XGBoost performed best with AUC = 0.938 and ACC = 0.965.

CONCLUSIONS

Both the MRI- and CT-based machine learning models are proved to be valuable noninvasive methods for functional liver reserve evaluation.

Adherence to LI-RADS and EASL high-risk population criteria: A systematic review

BACKGROUND AND AIMS

The Liver Imaging Reporting and Data System (LI-RADS) and European Association for the Study of the Liver (EASL) diagnostic criteria for noninvasive diagnosis of HCC can only be applied to patients at a high risk of HCC. This systematic review assesses adherence to the LI-RADS and EASL high-risk population criteria in published studies.

APPROACH AND RESULTS

PubMed was searched for original research, published between January 2012 and December 2021, reporting LI-RADS and EASL diagnostic criteria on contrast-enhanced ultrasound, CT, or MRI. The algorithm version, publication year, risk status, and etiologies of chronic liver disease were recorded for each study. Adherence to high-risk population criteria was evaluated as optimal (unequivocal adherence), suboptimal (equivocal), or inadequate (clear violation). A total of 219 original studies were included, with 215 that used the LI-RADS criteria, 4 EASL only, and 15 that evaluated both LI-RADS and EASL criteria. Optimal, suboptimal, or inadequate adherence to high-risk population criteria was observed in 111/215 (51.6%), 86/215 (40.0%), and 18/215 (8.4%) LI-RADS and 6/19 (31.6%), 5/19 (26.3%), and 8/19 (42.1%) EASL studies ( p < 0.001) regardless of the imaging modality. Adherence to high-risk population criteria significantly improved according to the CT/MRI LI-RADS versions (optimal in v2018 in 64.5% of studies; v2017, 45.8%; v2014, 24.4%; v2013.1, 33.3%; p < 0.001) and the publication year (2020-2021, 62.5%; 2018-2019, 33.9%; 2014-2017, 39.3% of all LI-RADS studies; p = 0.002). No significant differences in adherence to high-risk population criteria were observed in the versions of contrast-enhanced ultrasound LI-RADS ( p = 0.388) or EASL ( p = 0.293).

CONCLUSION

Adherence to high-risk population criteria was optimal or suboptimal in about 90% and 60% of LI-RADS and EASL studies, respectively.

The feasibility of early response evaluation using superb microvascular imaging one day after transcatheter arterial chemoembolization for hepatocellular carcinoma

PURPOSE

The purpose of this study was to determine the feasibility of early Superb microvascular imaging (SMI) for prediction of the effect of HCC treatment after transcatheter arterial chemoembolization (TACE).

MATERIALS AND METHODS

A total of 96 HCCs (70 patients) treated with TACE between September 2021 and May 2022 were included in this study. SMI, Color Doppler imaging (CDI), and Power Doppler imaging (PDI) were performed the day after TACE for evaluation of intratumoral vascularity of the lesion using an Aplio500 ultrasound scanner (Toshiba Medical Systems, Corporation, Tochigi, Japan). Grading of the vascular presence was performed using a five-point scale. A dynamic CT image taken after 29-42 days was used for comparison of sensitivity, specificity, and accuracy for detection of tumor vascularity between SMI, CDI, and PDI. Univariate and multivariate analysis were performed for assessment of factors affecting intratumoral vascularity.

RESULTS

Fifty-eight lesions (60%) showed complete remission (CR) and 38 lesions (40%) showed partial response (PR) or no response at 29-42 days on Multi-detector Computed Tomography (MDCT) after TACE. SMI showed sensitivity of 86.84% for detection of intratumoral flow, which was significantly higher compared with that of CDI (10.53%, p < 0.001) and PDI (36.84%, p < 0.001). The results of multivariate analysis indicated that tumor size was a significant factor in detection of blood flow using the SMI technique.

CONCLUSION

Early SMI may be utilized as an adjunctive diagnostic test for evaluation of treated lesions after TACE, particularly when the location of the tumor is in an area of the liver where a suitable sonic window can be identified.

Pedunculated hepatocellular carcinoma masquerading as a giant GIST: A case report

INTRODUCTION AND IMPORTANCE

Hepatocellular carcinoma (HCC) is one of the most prevalent malignancies in Indonesia and is well-known as a silent killer disease due to its mortality rate among males. Furthermore, a pedunculated HCC (P-HCC) is a rare subtype challenging to diagnose when presented as an extrahepatic mass.

CASE PRESENTATION

A 61-year-old man was admitted to our hospital due to abdominal pain with a palpable mass in the left upper abdomen after being referred from secondary health care. The laboratory results revealed values within normal ranges, except for reactive anti-HCV and anemia, with no evidence of liver abnormalities. CT scan detected a solid mass with a necrotic center and calcified component in the upper left hemiabdomen originating from the submucosa of the greater curvature of the stomach, which were suggestive of gastrointestinal stromal tumor (GIST). It was approximately 12.9 × 10.9 × 18.6 cm sized, multilobulated, well-defined, and infiltrating the splenic vein.

CLINICAL DISCUSSION

We did a laparotomy and resections consist of distal gastrectomy, liver metastasectomy (segment 2-3), distal pancreatectomy, and splenectomy. Our operative findings were still suggestive of neoplasm of the stomach, most likely a GIST. However, our histological examination revealed a moderate-poorly differentiated liver cell carcinoma, confirmed with immunohistochemical analysis. He was discharged on the seventh day after the operation without any complications.

CONCLUSION

This case illustrates challenges in diagnosing and treating a rare pedunculated hepatocellular carcinoma.

Radiomics, a Promising New Discipline: Example of Hepatocellular Carcinoma

Radiomics is a discipline that involves studying medical images through their digital data. Using “artificial intelligence” algorithms, radiomics utilizes quantitative and high-throughput analysis of an image’s textural richness to obtain relevant information for clinicians, from diagnosis assistance to therapeutic guidance. Exploitation of these data could allow for a more detailed characterization of each phenotype, for each patient, making radiomics a new biomarker of interest, highly promising in the era of precision medicine. Moreover, radiomics is non-invasive, cost-effective, and easily reproducible in time. In the field of oncology, it performs an analysis of the entire tumor, which is impossible with a single biopsy but is essential for understanding the tumor’s heterogeneity and is known to be closely related to prognosis. However, current results are sometimes less accurate than expected and often require the addition of non-radiomics data to create a performing model. To highlight the strengths and weaknesses of this new technology, we take the example of hepatocellular carcinoma and show how radiomics could facilitate its diagnosis in difficult cases, predict certain histological features, and estimate treatment response, whether medical or surgical.

Computed tomography texture analysis combined with preoperative clinical factors serve as a predictor of early efficacy of transcatheter arterial chemoembolization in hepatocellular carcinoma

AIM

To investigate a pre-therapeutic radiomics nomogram to accurately predict hepatocellular carcinoma (HCC) lesion responses to transcatheter arterial chemoembolization (TACE).

METHODS

This retrospective study from January 2012 to 2022 included 92 TACE-treated patients who underwent liver contrast-enhanced CT scan 7 days before treatment, having complete clinical information. We extracted quantitative texture parameters and clinical factors for the largest tumors on the baseline arterial and portal venous phase CT images. An adaptive least absolute shrinkage and selection operator (LASSO)-penalized logistic regression identified independent predictors of tumor activity after TACE.

RESULTS

We fitted an adaptive LASSO regression model to narrow down the texture features and clinical risk factors of the tumor activity status. The selected texture features were used to construct radiomic scores (RadScore), which demonstrated superior performance in predicting tumor activity on both the training (area under the curve (AUC): 0.881, 95% CI: 0.799-0.963) and testing sets (AUC: 0.88, 95% CI: 0.726-1). A logistic regression-based nomogram was developed using RadScore and four selected clinical features. In the testing set, nomogram total points were significant predictors (P = 0.034), and the training set showed no departure from perfect fit (P = 0.833). Internal validation of the nomogram was obtained for the training (AUC: 0.91, 95% CI: 0.837-0.984) and testing (AUC: 0.889, 95% CI: 0.746-1) sets.

CONCLUSION

We propose a nomogram to predict the early response of HCC lesions to TACE treatment with high accuracy, which may serve as an additional criterion in multidisciplinary decision-making treatment.

Three-Dimensional Voxel-Wise Quantitative Assessment of Imaging Features in Hepatocellular Carcinoma

Voxel-wise quantitative assessment of typical characteristics in three-dimensional (3D) multiphase computed tomography (CT) imaging, especially arterial phase hyperenhancement (APHE) and subsequent washout (WO), is crucial for the diagnosis and therapy of hepatocellular carcinoma (HCC). However, this process is still missing in practice. Radiologists often visually estimate these features, which limit the diagnostic accuracy due to subjective interpretation and qualitative assessment. Quantitative assessment is one of the solutions to this problem. However, performing voxel-wise assessment in 3D is difficult due to the misalignments between images caused by respiratory and other physiological motions. In this paper, based on the Liver Imaging Reporting and Data System (v2018), we propose a registration-based quantitative model for the 3D voxel-wise assessment of image characteristics through multiple CT imaging phases. Specifically, we selected three phases from sequential CT imaging phases, i.e., pre-contrast phase (Pre), arterial phase (AP), delayed phase (DP), and then registered Pre and DP images to the AP image to extract and assess the major imaging characteristics. An iterative reweighted local cross-correlation was applied in the proposed registration model to construct the fidelity term for comparison of intensity features across different imaging phases, which is challenging due to their distinct intensity appearance. Experiments on clinical dataset showed that the means of dice similarity coefficient of liver were 98.6% and 98.1%, those of surface distance were 0.38 and 0.54 mm, and those of Hausdorff distance were 4.34 and 6.16 mm, indicating that quantitative estimation can be accomplished with high accuracy. For the classification of APHE, the result obtained by our method was consistent with those acquired by experts. For the WO, the effectiveness of the model was verified in terms of WO volume ratio.

Optimizing CT and MRI criteria for differentiating intrahepatic mass-forming cholangiocarcinoma and hepatocellular carcinoma

BACKGROUND

Accurate diagnosis of intrahepatic mass-forming cholangiocarcinoma (IMCC) is crucial with regard to the choice of patient management and treatment options.

PURPOSE

To evaluate the feasibility and diagnostic performance of the LI-RADS M (LR-M) targetoid criteria on computed tomography (CT) and gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI) in differentiating IMCC from hepatocellular carcinoma (HCC).

MATERIAL AND METHODS

A total of 118 patients with IMCC and HCC were included who underwent CT and EOB-MRI examinations. Multivariate analysis was used to determine the strongest predictors differentiating IMCC from HCC. Using these predictors, a predictive model for differentiating IMCC from HCC was constructed and the performance of the model was confirmed using the receiver operating characteristic curve.

RESULTS

Multivariate analyses revealed rim-like arterial phase hyperenhancement (rim APHE) on CT and rim APHE, delayed central enhancement (DCE), and targetoid hepatobiliary phase (HBP) on MRI as independent variables significantly differentiating IMCC from HCC. The multivariate logistic regression model incorporating the three variables on EOB-MRI was constructed with an area under the curve (AUC) of 0.946, sensitivity of 87.80%, specificity of 92.21%, and accuracy of 94.60%. Per the DeLong test, the multivariate logistic regression model showed significantly higher AUC than rim APHE on CT (0.946 vs. 0.871; P = 0.008) and MRI (0.946 vs. 0.876; P = 0.003), whereas rim APHE on CT and MRI did not differ significantly (P = 0.809).

CONCLUSION

The multivariate logistic regression model based on rim APHE, DCE, and targetoid HBP on EOB-MRI can effectively distinguish IMCC from HCC and is superior to any other targetoid appearance criterion of LI-RADS on CT and EOB-MRI.

Hydralazine-augmented contrast ultrasound imaging improves the detection of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) detection with B-mode and contrast-enhanced ultrasound (CUS) imaging often varies between subjects, especially in patients with background cirrhosis. Various factors contribute to this variability, including the tumor blood flow, tumor size, internal echoes, and its location in livers with diffuse fibro-cirrhotic changes.

OBJECTIVE

Towards improving lesion detection, this study evaluates a vasodilator, hydralazine, to enhance the visibility of HCC by reducing its blood flow relative to the surrounding liver tissue.

METHODS

HCC were analyzed for tumor visibility measured for B-mode, CUS, and hydralazine-augmented-contrast ultrasound (HyCUS) in an autochthonous HCC rat model. 21 tumors from 12 rats were studied. B-mode and CUS images were acquired before hydralazine injection. Rats received an intravenous hydralazine injection of 5 mg/kg, then images were acquired 20 min later. Four rats were used as controls. The difference in echo intensity of the lesion and the surrounding tissue was used to determine the visibility index (VI).

RESULTS

The visibility index for HCC was found to be significantly improved with the use of HyCUS imaging compared to traditional B-mode and CUS imaging. The visibility index for HCC was 16.5 ± 2.8 for HyCUS, compared to 5.3 ± 4.8 for B-mode and 4.1 ± 3.8 for CUS. The differences between HyCUS and the other imaging modalities were statistically significant, with p-values of 0.001 and 0.02, respectively. Additionally, when compared to control cases, HyCUS showed higher discrimination of HCC (VI = 6.4 ± 1.2) with a p-value of 0.003, while B-mode (VI = 6.7 ± 1.4, p = 0.5) and CUS (VI = 6.4 ± 1.2, p = 0.3) showed lower discrimination.

CONCLUSION

Vascular blood flow modulation by hydralazine enhances the visibility of HCC. HyCUS offers a potential problem-solving method for detecting HCC when B-mode and CUS are unsuccessful, especially with background fibro-cirrhotic liver disease. Future evaluation of the approach in humans will determine its translatability for clinical applications.

Gadoxetate disodium-enhanced MRI for diagnosis of hepatocellular carcinoma in patients with chronic liver disease: late portal venous phase may improve identification of enhancing capsule

PURPOSE

To investigate added value of late portal venous phase (LPVP) for identification of enhancing capsule (EC) on gadoxetate disodium-enhanced MRI (GD-MRI) for diagnosing hepatocellular carcinoma (HCC) in patients with chronic liver disease (CLD).

METHODS

This retrospective study comprised 116 high-risk patients with 128 pathologically proven HCCs who underwent GD-MRI including arterial phase, conventional portal venous phase (CPVP, 60 s), LPVP (mean, 104.4 ± 6.7 s; range, 90-119 s), and transitional phase (TP, 3 min). Two independent radiologists assessed the presence of major HCC features, including EC on CPVP and/or TP (CPVP/TP) and EC on LPVP. The frequency of EC was compared on GD-MRI between with and without inclusion of LPVP. The radiologists assigned Liver Imaging Reporting and Data System (LI-RADS) v2018 categories before and after identifying EC on LPVP.

RESULTS

Of the total 128 HCCs, 74 and 73 revealed EC on CPVP/TP for reviewer 1 and 2, respectively. After inclusion of LPVP, each reviewer identified seven more EC [Reviewer 1, 57.8% (74/128) vs. 63.3% (81/128); Reviewer 2, 57.0% (73/128) vs. 62.5% (80/128); P = 0.016, respectively]. Sensitivities of LR-5 assignment for diagnosing HCCs were not significantly different in GD-MRI with or without LPVP for EC identification [Reviewer 1, 71.9% (92/128) vs. 72.7% (93/128); Reviewer 2, 75.0% (96/128) vs. 75.8% (97/128); P = 1.000, respectively].

CONCLUSION

Including the LPVP in GD-MRI may improve identification of EC of HCC in patients with CLD. However, LI-RADS v2018 using GD-MRI showed comparable sensitivity for diagnosing HCC regardless of applying LPVP for EC.

Prognosis of Primary Liver Cancer Based on LI-RADS Classification with Extracellular Agent-Enhanced MRI

Objective

The prognostic value of the Liver Imaging Reporting and Data System (LI-RADS) 2018 in differentiating hepatocellular carcinoma (HCC) from other primary liver cancers (PLC) with cirrhosis is unclear. We aim to evaluate the value of LI-RADS 2018 with agent-enhanced MRI in the postoperative prognosis of PLC patients with cirrhosis.

Methods

Between 2016 and 2021, 432 patients with cirrhosis and surgically proven single primary liver cancer were retrospectively evaluated. Two radiologists evaluated the preoperative MRI features independently and assigned each lesion a LI-RADS category. Overall survival (OS), recurrence-free survival (RFS), and their associated factors were evaluated by using the Kaplan-Meier method, Log rank test, and Cox proportional hazards model.

Results

The mean age of 432 patients (239 HCCs, 93 ICCs, and 100 cHCC-CCAs) was 57.27±10.92 years. The LR-M category showed poorer OS and RFS than the LR-4 or LR-5 category did for all primary liver cancers (P <0.001 for both), and so did HCCs with tumor size less than 30mm (P =0.003 and P =0.04, respectively). In the multivariable analysis, the LI-RADS category and tumor size > 30 mm had independent correlations with OS and RFS (all P < 0.05). Multivariable Cox analysis identified rim arterial phase hyperenhancement (APHE) as independent determinants of poor OS and RFS in primary liver cancers (all P < 0.05).

Conclusion

The LI-RADS categories can predict the postsurgical prognosis of primary liver cancers independently.

Safety and Efficacy of Robotic vs Open Liver Resection for Hepatocellular Carcinoma

Importance

Long-term oncologic outcomes of robotic surgery remain a hotly debated topic in surgical oncology, but sparse data have been published thus far.

Objective

To analyze short- and long-term outcomes of robotic liver resection (RLR) for hepatocellular carcinoma (HCC) from Western high-volume centers to assess the safety, reproducibility, and oncologic efficacy of this technique.

Design, Setting, and Participants

This cohort study evaluated the outcomes of patients receiving RLR vs open liver resection (OLR) for HCC between 2010 and 2020 in 5 high-volume centers. After 1:1 propensity score matching, a group of patients who underwent RLR was compared with a validation cohort of OLR patients from a high-volume center that did not perform RLR.

Main Outcomes and Measures

A retrospective analysis was performed of prospectively maintained databases at 2 European and 2 US institutions of patients who underwent RLR for HCC between January 1, 2010, and September 30, 2020. The main outcomes were safety and feasibility of RLR for HCC and its oncologic outcomes compared with a European OLR validation cohort. A 2-sided P < .05 was considered significant.

Results

The study included 398 patients (RLR group: 125 men, 33 women, median [IQR] age, 66 [58-71] years; OLR group: 315 men, 83 women; median [IQR] age, 70 [64-74] years), and 106 RLR patients were compared with 106 OLR patients after propensity score matching. The RLR patients had a significantly longer operative time (median [IQR], 295 [190-370] minutes vs 200 [165-255] minutes, including docking; P < .001) but a significantly shorter hospital length of stay (median [IQR], 4 [3-6] days vs 10 [7-13] days; P < .001) and a lower number of admissions to the intensive care unit (7 [6.6%] vs 21 [19.8%]; P = .002). Incidence of posthepatectomy liver failure was significantly lower in the RLR group (8 [7.5%] vs 30 [28.3%]; P = .001), with no cases of grade C failure. The 90-day overall survival rate was comparable between the 2 groups (RLR, 99.1% [95% CI, 93.5%-99.9%]; OLR, 97.1% [95% CI, 91.3%-99.1%]), as was the cumulative incidence of death related to tumor recurrence (RLR, 8.8% [95% CI, 3.1%-18.3%]; OLR, 10.2% [95% CI, 4.9%-17.7%]).

Conclusions and Relevance

This study represents the largest Western experience to date of full RLR for HCC. Compared with OLR, RLR performed in tertiary centers represents a safe treatment strategy for patients with HCC and those with compromised liver function while achieving oncologic efficacy.

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.

Contrast-enhanced ultrasound for assessing blood flow modulation of hepatocellular carcinoma by hydralazine

Modulating aberrant tumor microvasculature provides unique opportunities for enhancing ultrasound imaging of hepatocellular carcinoma (HCC). This study aims to use contrast-enhanced ultrasound to evaluate the potential of a potent vasodilator, hydralazine, to attenuate blood flow in HCC while enhancing it in the surrounding liver tissue. The "steel effect," where blood flow is diverted from the lesion to the surrounding tissue aims to enhance lesion-tissue contrast. Methods: HCC was induced in six rats by oral ingestion of diethylnitrosamine for 12 weeks. 10 tumors were studied to assess the enhancement in HCC tumors and surrounding tissue. Contrast-enhanced ultrasound images (CEUS) of each tumor were acquired before and after hydralazine injection. The enhancement of images was analyzed for the qualitative and quantitative assessment of HCC enhancement. Peak enhancement (PE) was calculated, representing the maximum signal intensity reached during the transit of the contrast bolus for both the tumor and the surrounding tissue. Intravenous administration of hydralazine significantly reduced CEUS signals in HCC tumors. The visual examination of images showed that the enhancement of tumors dramatically decreased after hydralazine injection. On the other hand, the surrounding tissue showed an increased enhancement. PE for the HCC changed from (71.8 ± 5) pre hydralazine to (28.7± 4.9), a 61.7% reduction after hydralazine injection, p=0.01. Future studies validating the technique in clinical settings for enhancing lesion-tissue contrast may allow physicians greater precision and accuracy in HCC surveillance for early detection of small tumors.

Clinicopathological assessment of steatohepatitic hepatocellular carcinoma

AIM

To compare the clinicopathological features of typical steatohepatitic HCC (SH-HCC) with other HCCs.

METHODS

Subjects were 486 patients with untreated HCC who underwent hepatectomy at our hospital from January 2015 to December 2020. We compared patient backgrounds, preoperative laboratory data, imaging findings (ultrasonography, computed tomography [CT], and magnetic resonance imaging [MRI]), and postoperative pathological findings (tumor and background of liver). The Liver Imaging Reporting And Data System (LI-RADS) was used to examine CT and MRI findings.

RESULTS

Typical SH-HCCs were significantly different from other HCCs with respect to age, hepatitis B virus (HBV) infection, and nonalcoholic steatohepatitis (NASH). Diabetes and hyperlipidemia were also significantly more common. Regarding histopathology, tumor size and background steatosis were significantly different between groups. Although ultrasonography, CT, and MRI could each alone diagnose SH-HCCs with a diameter < 20 mm in ≥ 50% of patients, the combined use of these tests improved diagnostic accuracy. By LI-RADS, 87% of SH-HCC cases were classified as LR-5, which are considered to be malignant tumors.

CONCLUSIONS

It seems possible to diagnose SH-HCC by combining ultrasonography, CT, and MRI.

Interrater reliability and agreement of the liver imaging reporting and data system (LI-RADS) v2018 for the evaluation of hepatic lesions

Purpose

The liver imaging reporting and data system (LI-RADS) is a structured reporting system that categorizes hepatic observations according to major imaging features and lesion size, with an optional ancillary features contribution. This study aimed to evaluate inter-reader agreement of dynamic magnetic resonance imaging (MRI) using LI-RADS v2018 lexicon.

Material and methods

Forty-nine patients with 69 hepatic observations were included in our study. The major and ancillary features of each hepatic observation were evaluated by 2 radiologists using LI-RADS v2018, and the interreader agreement was allocated.

Results

The inter-reader agreement of major LI-RADS features was substantial; κ of non-rim arterial hyperenhancement, non-peripheral washout appearance, and enhancing capsule was 0.796, 0.799, and 0.772 (p < 0.001), respectively. The agreement of the final LI-RADS category was substantial with κ = 0.651 (p < 0.001), and weighted κ = 0.786 (p < 0.001). The inter-reader agreement of the ancillary features was substantial to almost perfect (k range from 0.718 to 1; p < 0.001). An almost perfect correlation was noted for the hepatic lesion size measurement with ICC = 0.977 (p < 0.001).

Conclusions

The major and ancillary features of the LI-RADS v2018, as well as the final category and lesions size, have substantial to almost perfect inter-reader agreement.

Phase 1 trial of apatinib combined with intensity-modulated radiotherapy in unresectable hepatocellular carcinoma

Background

To investigate the maximum tolerated dose (MTD) of apatinib delivered during and after intensity-modulated radiotherapy (IMRT) for unresectable hepatocellular carcinoma (HCC).

Methods

Patients with unresectable HCC who were not eligible for radiofrequency ablation (RFA), transcatheter arterial chemoembolization (TACE), or residual/ recurrent after the prior local treatment were enrolled. Patients were scheduled to be treated with IMRT at 50–60 Gy/25–30 fractions. Oral apatinib tablets were administered concurrently with IMRT and continued thereafter. We used a 3 + 3 dose-escalation design, with three dose levels of apatinib (250, 500, and 750 mg). Grade 3 or more severe adverse events (AEs) were defined as dose-limiting toxicities (DLTs). The treatment response was calculated using the Modified Response Evaluation Criteria in Solid Tumours.

Results

Nine patients with Barcelona Clinic Liver Cancer Stage C were included. One patient withdrew from the apatinib 250 mg group and another patient was added. No DLTs occurred in the apatinib 250 mg group. Five patients were included in the apatinib 500 mg group, and 2 cases of DLT (grade 3 leukopenia) were found among them. Dose escalation was terminated and the MTD was determined to be 250 mg. Common grade 1–2 AEs included fatigue, hypertension, dizziness, bone marrow suppression, and hyperbilirubinemia. The median follow-up time for all patients was 16.0 months. Three patients achieved complete response and another three achieved partial response. The objective response rate was 6/9 (66.7%), and the disease control rate was 9/9 (100%). Three patients relapsed out of the radiation field. The median progression-free survival was 17.0 months, and the median overall survival was 16.7 months.

Conclusions

When combined with IMRT, apatinib 250 mg daily was recommended for a phase 2 study of unresectable HCC. The antitumor activity of the combination treatment was encouraging. The safety and efficacy of apatinib combined with IMRT for unresectable HCC should be further investigated in future studies.

Trial registration

Registration No. ChiCTR1800018309. Registered 11 September 2018. Retrospectively registered, https://www.chictr.org.cn/showproj.aspx?proj=30461.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09819-3.

Diagnostic Performance of LI-RADS Version 2018 for Primary Liver Cancer in Patients With Liver Cirrhosis on Enhanced MRI

Purpose

The study evaluated the diagnostic performance of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 for differentiating hepatocellular carcinoma (HCC) from primary liver cancer in patients with liver cirrhosis based on the updated 2019 WHO classification.

Materials and Methods

From 2016 to 2021, 300 patients with surgically confirmed primary liver cancer (PLC) and liver cirrhosis based on the updated 2019 WHO classification were eligible for this retrospective study (100 cases in each of three groups including HCC, ICC, and cHCC-CCA). Two radiologists were blinded to the final diagnosis and independently assigned an LI-RADS category to each liver nodule. The diagnostic performances of the LR-5 category (definitely HCC), and the LR-M category (probably or definitely malignant, but not specific for HCC) were calculated in overall and small observations (<20 mm). Comparisons between groups of categorical variables were performed by one-way analysis of variance and the Chi-squared or Fisher’s exact test.

Results

The mean age of 300 patients (226 men and 74 women) was 57.40 ± 11.05 years. The sensitivity and specificity of the LR-5 category for differentiating HCCs from other primary liver cancers were 81% (81 of 100) and 82% (164 of 200), respectively. The LR-M category had a sensitivity of 63% (126 of 200) for diagnosing non-HCCs (ICCs and cHCC-CCAs), with a specificity of 90% (90 of 100). The LR-5 category had a sensitivity of 82.5% (33 of 40) for diagnosing HCCs in small observations (<20 mm) with a specificity of 76.6% (59 of 77). On the contrary, LR-M demonstrated slightly higher specificity (93.8%) and sensitivity (73.8%) for diagnosing non-HCCs with tumor size <20 mm.

Conclusion

The LR-5 category as well as the LR-M category of Liver Imaging Reporting and Data System (LI-RADS) version 2018 can effectively distinguish hepatocellular carcinoma from other primary hepatic malignancies in patients with liver cirrhosis, especially for small observations (<20 mm).

Liver imaging reporting and data system (LI-RADS) v2018: Reliability and agreement for assessing hepatocellular carcinoma locoregional treatment response

PURPOSE

The purpose of this study was to determine the reliability and interobserver agreement of the liver imaging reporting and data system (LI-RADS) treatment response algorithm (LR-TR) v2018 using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and the added value of diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

A total of 54 patients who underwent DCE-MRI and DWI after locoregional treatment of 81 hepatocellular carcinoma (HCC) lesions from September 2020 to July 2021 were included. There were 47 men and 7 women, with a mean age of 63.9 ± 9.2 (SD) years (age range: 23-77 years). Locoregional treatments included transarterial chemoembolization (TACE) (53/81; 65.4%), radiofrequency ablation (RFA) (25/81; 30.9%) and microwave ablation (MWA) (3/81; 3.7%). Two independent radiologists retrospectively evaluated DCE-MRI examinations obtained after locoregional treatment using LR-TR, and then three months later both radiologists reevaluated DCE-MRI examinations with DWI. Interobserver agreement was assessed using intraclass correlation coefficient (ICC) and Kappa test. Diagnostic performances were evaluated in term of sensitivity, specificity, and area under ROC curve (AUC) using a composite standard of reference that included results of histopathological examinations and follow-up findings.

RESULTS

Using DCE-MRI alone, observer 1 had 83.9% sensitivity (26/31; 95% confidence interval [CI]: 66-95%), 88% specificity (44/50; 95% CI: 76-95%) and 86.4% accuracy (70/81; 95%CI: 77-93%), and observer 2 had 71% sensitivity (22/31; 95% CI: 52-86%), 92% specificity (46/50; 95% CI: 81-98%) and 83.9% accuracy (68/81; 95% CI: 74-91%). For the diagnosis of viable tumors using DCE-MRI with DWI, observer 1 and observer 2 had 87.1% (27/31; 95% CI: 70-96%) and 74.2% (23/31; 95% CI: 55-88%) sensitivity, respectively. The diagnostic performance of DCE-MRI with DWI yielded an AUC (0.875; 95% CI: 0.789-0.962) not different from that of DCE-MRI without DWI (0.859; 95% CI: 0.768-0.951) (P = 0.317). Interobserver agreement for arterial phase hyperenhancement, washout, enhancement similar to pretreatment and DWI findings in all treated HCCs was almost perfect (kappa = 0.815, 0.837, 0.826 and 0.81 respectively). Agreement between observers for LR-TR category was substantial (kappa = 0.795; 95% CI: 0.665-0.924). Interobserver agreement for size of viable HCC was excellent (ICC = 0.938; 95% CI: 0.904-0.960).

CONCLUSION

LR-TR using DCE-MRI alone or DCE-MRI with DWI are both accurate for detecting viable HCC lesions after locoregional treatment, with no differences in diagnostic performance and excellent interobserver agreement.

Research on the Construction of Bispecific-Targeted Sustained-Release Drug-Delivery Microspheres and Their Function in Treatment of Hepatocellular Carcinoma

Lenvatinib (LEN) is approved as one of the commonly used drugs in the treatment of hepatocellular carcinoma (HCC). It is recognized to be a novel therapeutic choice for the direct and targeted delivery of effective drugs to HCC tumor sites. The key to the proposed method lies in the requirement for efficient targeted drug delivery carriers with targeting performance to deliver effective drugs directly and safely to tumor lesions. Methods: Here, magnetic liposomes (MLs) were modified by phosphatidylinositol proteoglycan 3 (GPC3) and epithelial cell adhesion molecules (EpCAMs). Subsequently, bispecific-targeted sustained-release drug-loaded microspheres containing LEN (GPC3/EpCAM-LEN-MLs) were constructed. In addition, both cytotoxicity and magnetic resonance imaging (MRI) analyses were performed to establish a mouse model and further perform corresponding performance assessments. Results: The corresponding results showed that GPC3/EpCAM-LEN-MLs were spherical-shaped and evenly dispersed. The encapsulation and drug-loading efficiencies were 91.08% ± 1.83% and 8.22% ± 1.24%, respectively. Meanwhile, GPC3/EpCAM-LEN-MLs showed a high inhibition rate on the proliferation of HCC cells and significantly increased their apoptosis. Furthermore, MRI revealed that the system possessed the function of tracking and localizing tumor cells, and animal experiments verified that it could exert the function of disease diagnosis. Conclusions: Our experiments successfully constructed a safe and efficient bispecific-targeted sustained-release drug delivery system for HCC tumor cells. It provides a useful diagnostic and therapeutic scheme for the clinical diagnosis and targeted therapy of HCC. Moreover, it can be used as a potential tumor-specific MRI contrast agent for the localization and diagnosis of malignant tumors.

Contrast Agents for Hepatocellular Carcinoma Imaging: Value and Progression

Hepatocellular carcinoma (HCC) has the third-highest incidence in cancers and has become one of the leading threats to cancer death. With the research on the etiological reasons for cirrhosis and HCC, early diagnosis has been placed great hope to form a favorable prognosis. Non-invasive medical imaging, including the associated contrast media (CM)-based enhancement scan, is taking charge of early diagnosis as mainstream. Meanwhile, it is notable that various CM with different advantages are playing an important role in the different imaging modalities, or even combined modalities. For both physicians and radiologists, it is necessary to know more about the proper imaging approach, along with the characteristic CM, for HCC diagnosis and treatment. Therefore, a summarized navigating map of CM commonly used in the clinic, along with ongoing work of agent research and potential seeded agents in the future, could be a needed practicable aid for HCC diagnosis and prognosis.

Bi-specific T1 positive-contrast-enhanced magnetic resonance imaging molecular probe for hepatocellular carcinoma in an orthotopic mouse model

BACKGROUND

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality. HCC-targeted magnetic resonance imaging (MRI) is an effective noninvasive diagnostic method that involves targeting clinically-related HCC biomarkers, such as alpha-fetoprotein (AFP) or glypican-3 (GPC3), with iron oxide nanoparticles. However, in vivo studies of HCC-targeted MRI utilize single-target iron oxide nanoprobes as negative (T2) contrast agents, which might weaken their future clinical applications due to tumor heterogeneity and negative MRI contrast. Ultra-small superparamagnetic iron oxide (USPIO) nanoparticles (approximately 5 nm) are potential optimal positive (T1) contrast agents. We previously verified the efficiency of AFP/GPC3-double-antibody-labeled iron oxide MR molecular probe in vitro.

AIM

To validate the effectiveness of a bi-specific probe in vivo for enhancing T1-weighted positive contrast to diagnose the early-stage HCC.

METHODS

The single- and double-antibody-conjugated 5-nm USPIO probes, including anti-AFP-USPIO (UA), anti-GPC3-USPIO (UG), and anti-AFP-USPIO-anti-GPC3 (UAG), were synthesized. T1- and T2-weighted MRI were performed on day 10 after establishment of the orthotopic HCC mouse model. Following intravenous injection of U, UA, UG, and UAG probes, T1- and T2-weighted images were obtained at 12, 12, and 32 h post-injection. At the end of scanning, mice were euthanized, and a histologic analysis was performed on tumor samples.

RESULTS

T1- and T2-weighted MRI showed that absolute tumor-to-background ratios in UAG-treated HCC mice peaked at 24 h post-injection, with the T1- and T2-weighted signals increasing by 46.7% and decreasing by 11.1%, respectively, relative to pre-injection levels. Additionally, T1-weighted contrast in the UAG-treated group at 24 h post-injection was enhanced 1.52-, 2.64-, and 4.38-fold compared to those observed for single-targeted anti-GPC3-USPIO, anti-AFP-USPIO, and non-targeted USPIO probes, respectively. Comparison of U-, UA-, UG-, and UAG-treated tumor sections revealed that UAG-treated mice exhibited increased stained regions compared to those observed in UG- or UA-treated mice.

CONCLUSION

The bi-specific T1-positive contrast-enhanced MRI probe (UAG) for HCC demonstrated increased specificity and sensitivity to diagnose early-stage HCC irrespective of tumor size and/or heterogeneity.

Added value of enhanced CT on LR-3 and LR-4 observation of Gd-EOB-DTPA MRI for the diagnosis of HCC: are CT and MR washout features interchangeable?

OBJECTIVE

To characterize the use of portal venous or delayed phase CT as an alternative to estimate washout for the non-invasive diagnosis of hepatocellular carcinoma (HCC) on gadoxetic acid-enhanced MRI in combination with other features.

METHODS

This retrospective study included 226 observations (n = 162 patients) at high risk for HCC imaged with gadoxetic acid-enhanced MRI and enhanced liver CT between March 2015 and March 2018. Two radiologists independently evaluated two sets of images and assigned the final Liver Imaging Reporting and Data System (LI-RADS) categories by consensus using gadoxetic acid-enhanced MRI. LR-1, LR-2, LR-5, and LR-M were excluded from the study.The observations were divided using different criteria for washout: hypointensity on the portal venous phase (PVP) at MRI (criteria 1), hypointensity on PVP at MRI and/or hypoattenuation on the PVP/delayed phase at dynamic CT (criteria 2), and hypointensity on the PVP and/or hepatobiliary phase at MRI (criteria 3). The sensitivity, specificity, and accuracy for the diagnosis of HCC were analyzed for each criterion.

RESULTS

Using gadoxetic acid-enhanced, 226 lesions were diagnosed as LR-3 or LR-4 by LI-RADS. Among them, 98 and 152 had "washout" at criteria 1 and 2, respectively. For the diagnosis of HCC, criteria 2 and 3 showed significantly higher sensitivities (67.3 and 92.5%, respectively) compared with criteria 1 (35.5%) (p < 0.001). The specificity of criteria 3 (13%) was significantly lower than those of criteria 1 and 2 (40.7% and 38.4%, respectively, p < 0.001). The specificities between criteria 1 and 2 were not statistically different (p = 0.427).

CONCLUSION

Although the LI-RADS lexicon does not permit the interchange of image features among various image modalities, the sensitivity of HCC diagnosis could be improved without any decrease in specificity by adding CT image washout features.

ADVANCES IN KNOWLEDGE

Although the LI-RADS lexicon does not permit the interchange of image features among various image modalities, complementary use of dynamic CT in LR-3 or LR-4 categories on the basis of gadoxetic acid-enhanced MRI may contribute to major imaging feature.

Surveillance for hepatocellular carcinoma: current status and future perspectives for improvement

INTRODUCTION

Hepatocellular carcinoma (HCC) is a globally relevant medical problem. Fortunately, risk factors for this tumor have been identified, and surveillance protocols developed. Patients with liver cirrhosis have the highest risk of developing HCC and have historically been included in surveillance programs. Special categories have also emerged in recent years, especially patients with eradicated HCV infection or nonalcoholic fatty liver disease. Novel serum biomarkers and magnetic resonance imaging protocols are currently being proposed to refine existing surveillance protocols.

AREAS COVERED

We discuss the rationale of surveillance programs for HCC and report the most recent recommendations from international guidelines about this topic. Gray areas, such as nonalcoholic fatty liver disease and the role of intrahepatic cholangiocellular carcinoma, are also discussed.

EXPERT OPINION

Surveillance is recognized as a tool to favor early diagnosis of HCC, access to curative treatment, and increase survival, even if the supporting evidence is mainly based on observational studies. As new randomized clinical trials are difficult to propose, future challenges will include optimizing implementation in the primary care setting and a more personalized approach, balancing the opportunities and risks of overdiagnosis of novel techniques and biomarkers.

Transfer language space with similar domain adaptation: a case study with hepatocellular carcinoma

Background

Transfer learning is a common practice in image classification with deep learning where the available data is often limited for training a complex model with millions of parameters. However, transferring language models requires special attention since cross-domain vocabularies (e.g. between two different modalities MR and US) do not always overlap as the pixel intensity range overlaps mostly for images.

Method

We present a concept of similar domain adaptation where we transfer inter-institutional language models (context-dependent and context-independent) between two different modalities (ultrasound and MRI) to capture liver abnormalities.

Results

We use MR and US screening exam reports for hepatocellular carcinoma as the use-case and apply the transfer language space strategy to automatically label imaging exams with and without structured template with > 0.9 average f1-score.

Conclusion

We conclude that transfer learning along with fine-tuning the discriminative model is often more effective for performing shared targeted tasks than the training for a language space from scratch.

[Small hepatocellular carcinoma : Diagnostics according to guidelines and established in the clinical setting]

CLINICAL/METHODICAL ISSUE

The diagnosis of hepatocellular carcinoma (HCC)-especially the characterization of small lesions <2 cm-continues to be a radiological challenge.

STANDARD RADIOLOGICAL METHODS

In the current S3 guideline on diagnosis and therapy of HCC, contrast-enhanced imaging examinations, such as contrast-enhanced ultrasonography (CEUS), computed tomography (CT), and magnetic resonance imaging (MRI), are still the diagnostic standard.

METHODOLOGICAL INNOVATIONS

HCC in the cirrhotic liver should be diagnosed by its typical contrast-enhanced pattern in the MRI. In addition, the use of quality assurance instruments such as LI-RADS (Liver Imaging Reporting and Data System) contributes to the desired consistency of findings, even with small ambiguous findings.

PERFORMANCE

Many studies have shown that the LI-RADS classification reflects the likelihood of HCC and other malignant liver lesions.

ACHIEVEMENTS

Guidelines and quality assurance instruments contribute to a more precise diagnosis in patients with suspected HCC.

PRACTICAL RECOMMENDATIONS

A guideline-compliant diagnostic algorithm and the LI-RADS should be used across the board for accurate HCC diagnostics.

Profile of patients with hepatocellular carcinoma: An experience from a tertiary care center in India

BACKGROUND

The prevalence of hepatocellular carcinoma (HCC) is increasing worldwide and it is now the third most common cause of cancer-related death. HCC is becoming a major health burden with steadily increasing incidence globally.

METHODS

This is an observational study over a 3-year period in a tertiary care center in India. Three hundred and thirty-nine patients diagnosed to have HCC were included in this study. Patients' clinical, etiological, radiological and cytohistological data and therapy offered were recorded and analyzed.

RESULTS

Cirrhosis of the liver was seen in 73.2% of the patients. 16.8% of patients were asymptomatic at the time of presentation. Ascites (57.2%) and jaundice (22.4%) were the most common signs of hepatic decompensation. The most common etiology of HCC was cryptogenic/non-alcoholic fatty liver disease (NAFLD) in 51% of the patients, while hepatitis B and C were seen in 17.4% and 5.8% of the patients, respectively. Advanced and end-stage disease with Barcelona Clinic Liver Cancer (BCLC) stages C and D were seen in 62.4% of patients. 56.6% had Albumin-bilirubin (ALBI) score of 2, while 62.8% had Okuda stage II disease. High alpha-fetoprotein (AFP) levels (>400 ng/mL) were seen in 48.9% of patients. Macrovascular invasion and metastases were seen in 45.9% and 22.2% of the patients, respectively. 17.6% of patients had evidence of tumor thrombus. 14.5% of biopsy specimens showed associated steatosis/steatohepatitis along with confirmation of HCC. Only 26.6% of the cirrhotic HCC patients were diagnosed during surveillance.

CONCLUSIONS

HCC due to unknown cause/NAFLD appears to be overtaking hepatitis B as the commonest cause for HCC. Despite the advances in diagnostic methods and surveillance, most cases of HCC tend to be diagnosed at advanced stages.

Impact of the Liver Imaging Reporting and Data System on Research Studies of Diagnosing Hepatocellular Carcinoma Using MRI

Objective

Since its introduction in 2011, the CT/MRI diagnostic Liver Imaging Reporting and Data System (LI-RADS) has been updated in 2014, 2017, and 2018. We evaluated the impact of CT/MRI diagnostic LI-RADS on liver MRI research methodology for the diagnosis of hepatocellular carcinoma (HCC).

Materials and Methods

The MEDLINE, EMBASE, and Cochrane databases were searched for original articles reporting the diagnostic performance of liver MRI for HCC between 2011 and 2019. The MRI techniques, image analysis methods, and diagnostic criteria for HCC used in each study were investigated. The studies were classified into three groups according to the year of publication (2011–2013, 2014–2016, and 2017–2019). We compared the percentage of studies adopting MRI techniques recommended by LI-RADS, image analysis methods in accordance with the lexicon defined in LI-RADS, and diagnostic criteria endorsed by LI-RADS. We compared the pooled sensitivity and specificity between studies that used the LI-RADS and those that did not.

Results

This systematic review included 179 studies. The percentages of studies using imaging techniques recommended by LI-RADS were 77.8% for 2011–2013, 85.7% for 2014–2016, and 84.2% for 2017–2019, with no significant difference (p = 0.951). After the introduction of LI-RADS, the percentages of studies following the LI-RADS lexicon were 0.0%, 18.4%, and 56.6% in the respective periods (p < 0.001), while the percentages of studies using the LI-RADS diagnostic imaging criteria were 0.0%, 22.9%, and 60.7%, respectively (p < 0.001). Studies that did not use the LI-RADS and those that used the LI-RADS version 2018 showed no significant difference in sensitivity and specificity (86.3% vs. 77.7%, p = 0.102 and 91.4% vs. 89.9%, p = 0.770, respectively), with some difference in heterogeneity (I² = 94.3% vs. 86.7% in sensitivity and I² = 86.6% vs. 53.2% in specificity).

Conclusion

LI-RADS imparted significant changes in the image analysis methods and diagnostic criteria used in liver MRI research for the diagnosis of HCC.

The Course of LIRADS 3 and 4 Hepatic Abnormalities as Correlated With Explant Pathology: A Single Center Experience

BACKGROUND AND AIMS

The Liver Reporting and Data System (LI-RADS) is the standard classification of imaging findings of hepatic abnormalities for hepatocellular carcinoma (HCC) surveillance. We aimed to study the course of LI-RADS 3 and 4 (LR-3 and LR-4) abnormalities through correlations with explant pathology.

METHODS

A single center retrospective study of liver transplant recipients between January 2016 and September 2019 with HCC on explant pathology was conducted. Eligible patients were divided into three subgroups based on their LI-RADS classification: LR-3/4, LR-5 only, and combination of LR-3/4/5.

RESULTS

There were 116 eligible patients with 99 LR-3/4 observations (60 LR-3 and 39 LR-4); the rest had LR-5 lesions. LR-4 more often than LR-3 observations progressed to LR-5 (36% vs 12%) and with shorter duration during follow-up (median 175 days and 196 days). Mean size growth of LR-3 and LR-4 abnormalities were 2.6 and 3.8 mm; median growth rates were 0.2 and 0.4 mm/month, respectively. Numbers of HCC lesions per explant, largest HCC lesion size, and cumulative size were higher in LR-3/4/5 subgroup than LR-5 subgroup (P = 0.007, 0.007 and 0.006, respectively); 68% of LR-3 and 82% of LR-4 abnormalities were confirmed HCC on explant (P = 0.09).

CONCLUSION

Compared to LR-3, more LR-4 abnormalities progressed to LR-5 (12% and 36%, respectively) in a shorter time and with faster growth rate. A high proportion of LR-3 and LR-4 lesions (68% and 82%, respectively) were confirmed HCC on explant, raising the question of whether excluding HCC based on radiologic criteria alone is adequate in those with LR-3/4 abnormalities.

Optimizing diagnostic imaging data using LI-RADS and the Likert scale in patients with hepatocellular carcinoma

Purpose

The study aimed to compare the diagnostic performance of the Liver Imaging Reporting and Data System (LI-RADS), which incorporates fixed criteria, and the Likert scale (LS), which mainly depends on an overall impression in liver lesion diagnosis.

Material and methods

Diagnostic data of 110 hepatic nodules in 103 high-risk patients for hepatocellular carcinoma (HCC) were included. Data including diameter, arterial hyperenhancement, washout, and capsule were reviewed by 2 readers using LI-RADS and LS (range, score 1-5). Inter-reader agreement (IRA), intraclass agreement (ICA), and diagnostic performance were determined by Fleiss, Cohen’s k, and logistic regression, respectively.

Results

There were 53 triphasic enhanced computed tomography (CT) and 50 dynamic magnetic resonance (MR) examinations. Overall, IRA was excellent (k = 0.898). IRA was good for arterial hyperenhancement (k = 0.705), washout (k = 0.763), and capsule (k = 0.771) and excellent for diameter (k = 0.981) and tumour embolus (k = 0.927). Overall, ICA between LI-RADS and LS was fair 0.32; ICA was good for scores of 1 (k = 0.682), fair for scores of 2 (k = 0.36), moderate for scores of 5 (k = 0.52), but no agreement was found for scores of 3 (k = –0.059) and 4 (k = –0.022). LIRADS produced relatively high accuracy (87.3% vs. 80%), relatively low sensitivity (84.3% vs. 98%), and significantly higher specificity (89.83% vs. 64.4%) and positive likelihood ratio (+LR: 8.29 vs. 2.75) compared to LS approach.

Conclusions

LI-RADS revealed higher diagnostic accuracy as compared to LS with statistical proof higher specificity and +LR showing its ability to foretell malignancy in high-risk patients. We recommend the practical application of the LI-RADS system in the detection and treatment response monitoring of patients with HCC.

Saliency-based 3D convolutional neural network for categorising common focal liver lesions on multisequence MRI

Background

The imaging features of focal liver lesions (FLLs) are diverse and complex. Diagnosing FLLs with imaging alone remains challenging. We developed and validated an interpretable deep learning model for the classification of seven categories of FLLs on multisequence MRI and compared the differential diagnosis between the proposed model and radiologists.

Methods

In all, 557 lesions examined by multisequence MRI were utilised in this retrospective study and divided into training–validation (n = 444) and test (n = 113) datasets. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the performance of the model. The accuracy and confusion matrix of the model and individual radiologists were compared. Saliency maps were generated to highlight the activation region based on the model perspective.

Results

The AUC of the two- and seven-way classifications of the model were 0.969 (95% CI 0.944–0.994) and from 0.919 (95% CI 0.857–0.980) to 0.999 (95% CI 0.996–1.000), respectively. The model accuracy (79.6%) of the seven-way classification was higher than that of the radiology residents (66.4%, p = 0.035) and general radiologists (73.5%, p = 0.346) but lower than that of the academic radiologists (85.4%, p = 0.291). Confusion matrices showed the sources of diagnostic errors for the model and individual radiologists for each disease. Saliency maps detected the activation regions associated with each predicted class.

Conclusion

This interpretable deep learning model showed high diagnostic performance in the differentiation of FLLs on multisequence MRI. The analysis principle contributing to the predictions can be explained via saliency maps.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-021-01117-z.

Measuring HCC Tumor Size in MRI-The Sequence Matters!

BACKGROUND

The aim of this paper was to assess and compare the accuracy of common magnetic resonance imaging (MRI) pulse sequences in measuring the lesion sizes of hepatocellular carcinomas (HCCs) with respect to the Milan criteria and histopathology as a standard of reference.

METHODS

We included 45 patients with known HCC who underwent contrast-enhanced MRI of the liver prior to liver transplantation or tumor resection. Tumor size was assessed pathologically for all patients. The MRI protocol contained axial T2-weighted images as well as T1-weighted imaging sequences before and after application of Gd-EOB-DTPA. Tumor diameters, the sharpness of lesions, and the presence of artifacts were evaluated visually on all available MRI sequences. MRI measurements and pathologically assessed tumor dimensions were correlated using Pearson's correlation coefficient and Bland-Altman plots. The rate of misclassifications following Milan criteria was assessed.

RESULTS

The mean absolute error (in cm) of MRI size measurements in comparison to pathology was the smallest for the hepatobiliary phase T1-weighted acquisition (0.71 ± 0.70 cm, r = 0.96) and largest for the T2w turbo-spin-echo (TSE) sequence (0.85 ± 0.78 cm, r = 0.94). The misclassification rate regarding tumor size under the Milan criteria was lowest for the T2w half-Fourier acquisition single-shot turbo spin-echo sequence and the hepatobiliary phase T1w acquisition (each 8.6%). The highest rate of misclassification occurred in the portal venous phase T1w acquisition and T2w TSE sequence (each 14.3%).

CONCLUSIONS

The hepatobiliary phase T1-weighted acquisition seems to be most accurate among commonly used MRI sequences for measuring HCC tumor size, resulting in low rates of misclassification with respect to the Milan criteria.

The Value of Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System in the Diagnosis of Hepatocellular Carcinoma:: A Meta-Analysis

OBJECTIVES

The aim of this study is to systematically evaluate the diagnostic ability of the contrast-enhanced ultrasound (CEUS) liver imaging reporting and data system (LI-RADS) in hepatocellular carcinoma (HCC).

METHODS

We searched relevant studies from PubMed, Medline, and Embase database. After literature search, duplicate removal, and data extraction, we calculated and analyzed the pooled sensitivity, pooled specificity, pooled odds ratios of diagnostic, pooled likelihood ratio (LR) of positive and negative, and area under the curve (AUC), accuracy, and F1 score to evaluate the diagnostic value of CEUS LI-RADS for HCC.

RESULTS

Thirteen studies and 6491 patients were included in this analysis. The pooled sensitivity and pooled specificity were 0.72 (95% confidence interval [CI], 0.70-0.73) and 0.92 (95% CI, 0.91-0.93), respectively. The positive LR was 8.02 (95% CI, 4.93-13.06) and the negative LR was 0.31 (95% CI, 0.27-0.37). The pooled diagnostic odds ratio was 27.91 (95% CI, 15.39-50.63). The overall AUC was 0.8406 and the accuracy was 0.77.

CONCLUSIONS

CEUS LI-RADS is an effective and promising method to diagnose HCC.

Imaging Features at the Periphery: Hemodynamics, Pathophysiology, and Effect on LI-RADS Categorization

Liver lesions have different enhancement patterns at dynamic contrast-enhanced imaging. The Liver Imaging Reporting and Data System (LI-RADS) applies the enhancement kinetic of liver observations in its algorithms for imaging-based diagnosis of hepatocellular carcinoma (HCC) in at-risk populations. Therefore, careful analysis of the spatial and temporal features of these enhancement patterns is necessary to increase the accuracy of liver mass characterization. The authors focus on enhancement patterns that are found at or around the margins of liver observations-many of which are recognized and defined by LI-RADS, such as targetoid appearance, rim arterial phase hyperenhancement, peripheral washout, peripheral discontinuous nodular enhancement, enhancing capsule appearance, nonenhancing capsule appearance, corona enhancement, and periobservational arterioportal shunts-as well as peripheral and periobservational enhancement in the setting of posttreatment changes. Many of these are considered major or ancillary features of HCC, ancillary features of malignancy in general, features of non-HCC malignancy, features associated with benign entities, or features related to treatment response. Distinction between these different patterns of enhancement can help with achieving a more specific diagnosis of HCC and better assessment of response to local-regional therapy. ^©RSNA, 2021.

A Radiomics Approach to Predict the Emergence of New Hepatocellular Carcinoma in Computed Tomography for High-Risk Patients with Liver Cirrhosis

Liver cirrhosis poses a major risk for the development of hepatocellular carcinoma (HCC). This retrospective study investigated to what extent radiomic features allow the prediction of emerging HCC in patients with cirrhosis in contrast-enhanced computed tomography (CECT). A total of 51 patients with liver cirrhosis and newly detected HCC lesions (n = 82) during follow-up (FU-CT) after local tumor therapy were included. These lesions were not to have been detected by the radiologist in the chronologically prior CECT (PRE-CT). For training purposes, segmentations of 22 patients with liver cirrhosis but without HCC-recurrence were added. A total of 186 areas (82 HCCs and 104 cirrhotic liver areas without HCC) were analyzed. Using univariate analysis, four independent features were identified, and a multivariate logistic regression model was trained to classify the outlined regions as "HCC probable" or "HCC improbable". In total, 60/82 (73%) of segmentations with later detected HCC and 84/104 (81%) segmentations without HCC were classified correctly (AUC of 81%, 95% CI 74-87%), yielding a sensitivity of 72% (95% CI 57-83%) and a specificity of 86% (95% CI 76-96%). In conclusion, the model predicted the occurrence of new HCCs within segmented areas with an acceptable sensitivity and specificity in cirrhotic liver tissue in CECT.

The New Era of TIRADSs to Stratify the Risk of Malignancy of Thyroid Nodules: Strengths, Weaknesses and Pitfalls

Simple Summary

The aim of this review is to provide the reader with a comprehensive overview of thyroid imaging and reporting data systems used for thyroid nodules, so as to understand how nodules are scored with all existing systems. Both ultrasound based risk stratification systems and indications for fine-needle aspirations are described. Systems are compared by analyzing their strengths and weaknesses. Studies show satisfactory sensitivities and specificities for the diagnosis of malignancy for all systems, and none of them have shown a real significant advantage over the others in terms of raw diagnostic value. Interobserver agreement is also very similar for all systems, fairly adequate to robust. Dimensional cut-offs for fine-needle aspiration are quite similar and all RSSs seem to reduce effectively the number of unnecessary FNAs. Merging all existing systems in a common international one is desirable.

Abstract

Since 2009, thyroid imaging reporting and data systems (TI-RADS) have been playing an increasing role in the field of thyroid nodules (TN) imaging. Their common aims are to provide sonologists of varied medical specialties and clinicians with an ultrasound (US) based malignancy risk stratification score and to guide decision making of fine-needle aspiration (FNA). Schematically, all TI-RADSs scores can be classified as either pattern-based or point-based approaches. The main strengths of these systems are their ability (i) to homogenize US TN descriptions among operators, (ii) to facilitate and shorten communication on the malignancy risk of TN between sonologists and clinicians, (iii) to provide quantitative ranges of malignancy risk assessment with high sensitivity and negative predictive values, and (iv) to reduce the number of unnecessary FNAs. Their weaknesses are (i) the remaining inter-observer discrepancies and (ii) their insufficient sensitivity for the diagnosis of follicular cancers and follicular variant of papillary cancers. Most common pitfalls are degenerating shrinking nodules and confusion between individual and coalescent nodules. The benefits of all TI-RADSs far outweigh their shortcomings, explaining their rising use, but the necessity to improve and merge the different existing systems remains.

The Feasibility of a Fast Liver MRI Protocol for Lesion Detection of Adults at 3.0-T

Purpose

To investigate the feasibility of a fast liver magnetic resonance imaging (MRI) protocol for lesion detection in adults using 3.0-T MRI.

Methods

A fast liver MRI exam protocol was proposed. The protocol included motion-resistant coronal T2-w sequence, axial T2-w fast spin echo sequence with fat suppression, axial in-op phase gradient recalled echo (GRE) T1, axial diffusion weighted imaging (DWI), and axial contrast-enhanced T1 sequences. To evaluate the diagnostic capacity of the proposed protocol, 31 consecutive patients (20 males and 11 females; mean age, 53.2 years) underwent a liver MRI exam with conventional sequences, including the proposed protocol as a subset. Images from the conventional protocol and extracted abbreviated protocol were independently read, and the diagnostic concordance rate was assessed for each patient. The concordance analysis is presented as the proportion of concordant cases between the two protocols.

Results

The net measurement time of the fast liver MRI protocol without adjustment and waiting time were 4 min and 28 s. In the 31 patients included in this study, 139 suspicious findings were found from both the conventional liver MR protocol and the fast liver MRI protocol. The diagnostic concordance rate was 96.4%.

Conclusions

The fast liver MRI protocol is feasible at 3.0-T, with a shorter exam time and high diagnostic concordance compared to the conventional liver MRI workflow.

A modified LI-RADS: targetoid tumors with enhancing capsule can be diagnosed as HCC instead of LR-M lesions

OBJECTIVE

To elucidate whether the presence of enhancing capsule can be applied to establish a modified Liver Imaging Reporting and Data System (LI-RADS) to differentiate hepatocellular carcinoma (HCC) from non-HCC malignancies in extracellular contrast agent (ECA)-enhanced and hepatobiliary agent (HBA)-enhanced MRI.

METHODS

We enrolled 198 participants (161 men; mean age, 56.3 years) with chronic liver disease who underwent ECA-MRI and HBA-MRI before surgery for de novo hepatic nodule(s). Two reviewers assigned LI-RADS categories (v2018). We defined a "modified LR-5 category, which emphasizes enhancing capsule (mLR-5C)" over targetoid features and classifies tumors with both targetoid appearance and enhancing capsule as HCC instead of LR-M. We compared the diagnostic performance of conventional LI-RADS and modified LI-RADS criteria for both MRIs.

RESULTS

A total of 258 hepatic nodules (194 HCCs, 43 benign lesions, and 21 non-HCC malignancies; median size, 19 mm) were analyzed. By conventional LI-RADS, 47 (18.2%) nodules (31 HCCs and 16 non-HCC malignancies) were categorized as LR-M. The mLR-5C criterion showed superior sensitivity (ECA-MRI, 76.6% vs. 67.0%; HBA-MRI, 60.4% vs. 56.3%; both p < 0.05) while maintaining high specificity (ECA-MRI, 93.8% vs. 98.4%; HBA-MRI, 95.3% vs. 98.4%; both p > 0.05) compared with the LR-5 criterion. Using the mLR-5C criterion, ECA-MRI exhibited higher sensitivity than HBA-MRI (76.6% vs. 60.4%, p < 0.001) and similar specificity (93.8% vs. 95.3%, p > 0.99).

CONCLUSION

Our modified LI-RADS achieved superior sensitivity for diagnosing HCC, without compromising specificity compared with LR-5. ECA-MRI showed higher sensitivity in diagnosing HCC than HBA-MRI by applying the mLR-5C for LR-M lesions.

KEY POINTS

• By conventional LI-RADS, 31 (16.0%) of 194 HCCs were categorized as LR-M. • Among 31 HCCs categorized as LR-M, 19 HCCs or 8 HCCs were recategorized as HCC on ECA-MRI or HBA-MRI, respectively, after applying the modified LR-5 category, which allocates targetoid lesions with enhancing capsule as mLR-5C instead of LR-M. • The mLR-5C showed superior sensitivity compared with the LR-5 in both MRIs (ECA-MRI, 76.6% vs. 67.0%; HBA-MRI, 60.4% vs. 56.3%, both p < 0.05), while maintaining high specificity (ECA-MRI, 93.8% vs. 98.4%; HBA-MRI, 95.3% vs. 98.4%; both p > 0.05).

Post-treatment CT LI-RADS categories: predictors of overall survival in hepatocellular carcinoma post bland transarterial embolization

PURPOSE

The LI-RADS Treatment Response (LR-TR) algorithm was introduced in 2017 to assist radiologists in assessing hepatocellular carcinoma (HCC) response following locoregional therapy. The objective of this study was to evaluate the associations between pre-treatment LI-RADS diagnostic categories, post-treatment LR-TR categories, and mRECIST response categories with overall survival (OS) of patients with HCC.

METHODS

This retrospective study included untreated patients with one or two lesions who underwent transarterial embolization with or without concomitant ablation from December 2003 to December 2017. Two radiologists (R1 and R2) reviewed pre- and post-treatment CT imaging. Associations between pre- and post-treatment variables, including post-treatment LR-TR categories (Viable, Equivocal, Nonviable), with OS were assessed using the Kaplan-Meier method and Cox proportional hazards regression.

RESULTS

Eighty-five patients were included (median age = 71 years, range 50-87; 17 women). The median OS from first embolization was 43.92 months. Pre- and post-treatment tumor size, pre-treatment LR-TIV (compared with LR-5), and post-treatment LR-TR Viable (compared with LR-TR Nonviable) were associated with OS (p < 0.05 for all). Median OS was shorter for LR-TR Viable patients (R1, 25.64 months, 95% CI 18.58-35.70; R2, 26.43 months 95% CI 20.68-43.92) than for LR-TR Nonviable patients (64.21 months R1 and R2, 95% CI 42.71-92.45 and 36.30-94.09, respectively). mRECIST categories showed similar associations with OS. Inter-reader agreement was moderate for LI-RADS categories (κ = 0.57, 95% CI 0.35-0.78) and substantial for LR-TR categories (κ = 0.68, 95% CI 0.55-0.81).

CONCLUSIONS

LR-TR categories show a strong association with OS in HCC patients treated with transarterial embolization.

Role of the radiologist at HCC multidisciplinary conference and use of the LR-TR algorithm for improving workflow

Multidisciplinary conferences (MDCs) play a major role in management and care of oncology patients. Hepatocellular carcinoma (HCC) is a complex disease benefiting from multidisciplinary discussions to determine optimal patient management. A multitude of liver-directed locoregional therapies have emerged allowing for more options for treatment of HCC. A radiologist dedicated to HCC-MDC is an important member of the team contributing to patient care in multiple ways. The radiologist plays a key role in image interpretation guiding initial therapy discussions as well as interpreting post-treatment imaging following liver-directed therapy. Standardization of image interpretation can lead to more consistent treatment received by the patient as well as accurate assessment of transplant eligibility. The radiologist can facilitate this process using structured reporting that is also supported by stakeholders involved in interdisciplinary management of liver diseases. The Liver Imaging Reporting and Data System (LI-RADS), is a living document which offers a standardized reporting algorithm for consistent communication of radiologic findings for HCC screening and characterization of liver observations in patients at risk for HCC. The LI-RADS post-treatment algorithm (LR-TR algorithm) has been developed to standardize liver observations following liver-directed locoregional therapy. This review article focuses on the role of the radiologist at HCC-MDC and implementation of the LR-TR algorithm for improving workflow.

Combined hepatocellular carcinoma-cholangiocarcinoma: MRI features correlated with tumor biomarkers and prognosis

OBJECTIVES

To determine how MRI features are correlated to biomarkers, and to the prognostic factors for recurrence-free survival (RFS) and overall survival (OS) in combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) patients.

METHODS

The study enrolled 160 cHCC-CCA patients pathologically confirmed according to the 2019 WHO classification. The preoperative MRI features and clinical data were retrospectively evaluated and compared between patients grouped by AFP or CA19-9 level and with pathological findings. The RFS and OS of cHCC-CCA patients were estimated using Kaplan-Meier survival curves and compared using the log-rank test. Moreover, predictors of RFS and OS were investigated using Cox regression analyses.

RESULTS

One hundred and sixty patients (mean age, males vs. females: 55.7 ± 10.2 years vs. 54.9 ± 14.0 years) were evaluated. The incidence of nodule-in-nodule architecture, mosaic architecture, intratumoral hemorrhage, hepatic capsule retraction, arterial phase peritumoral enhancement, and portal vein thrombus was significantly higher in patients with AFP > 20 ng/ml (all p < 0.05). Multivariate Cox regression analysis indicated that age (HR 1.031, p = 0.03), CA19-9 > 37 U/ml (HR 1.880, p = 0.04), arterial phase peritumoral enhancement (HR 2.287, p = 0.01), and delayed enhancement (HR 0.377, p = 0.02) were independent predictors of poor RFS, while arterial phase peripheral enhancement (HR 2.391, p = 0.04) was an independent predictor of poor OS.

CONCLUSIONS

cHCC-CCA imaging features are complex and not correlated with AFP or CA19-9. Age, CA19-9 > 37 U/ml, arterial phase peritumoral enhancement, and delayed enhancement are independent predictors of poor RFS. Arterial phase peripheral enhancement is an independent predictor of poor OS.

KEY POINTS

• The imaging features of combined hepatocellular carcinoma-cholangiocarcinoma are complex and are not correlated with the alpha fetoprotein or CA19-9 levels. • Age, CA19-9 > 37 U/ml, arterial phase peritumoral enhancement, and delayed enhancement are independent predictors of poor recurrence-free survival in combined hepatocellular carcinoma-cholangiocarcinoma patients. • Arterial phase peripheral enhancement is an independent predictor of poor overall survival in patients with combined hepatocellular carcinoma-cholangiocarcinoma.

Comparison of low kVp CT and dual-energy CT for the evaluation of hypervascular hepatocellular carcinoma

PURPOSE

To compare lesion conspicuity and image quality of arterial phase images obtained from low kVp (90-kVp) and dual-energy (DE) scans for the evaluation of hypervascular hepatocellular carcinoma (HCC).

METHODS

This retrospective study included 229 patients with HCC who underwent either 90 kVp (n = 106) or DE scan (80- and 150-kVp with a tin filter) (n = 123) during the arterial phase. DE scans were reconstructed into a linearly blended image with a mixed ratio of 0.6 (60% 80kVp and 40% 150 kVp) and post-processed for 40 keV and 50 keV images. The contrast-to-noise ratio (CNR) of HCC to the liver and image noise was measured. Lesion conspicuity, liver parenchymal image quality, and overall image preference were assessed qualitatively by three independent radiologists.

RESULTS

DE 40 keV images had the highest CNR of HCC, and DE blended images had the lowest image noise among four image sets (p = 0.01 and p < 0.001, respectively). There was no significant difference in mean volume CT dose index and dose-length product between DE and low kVp scan (ps > 0.05). For qualitative analyses, DE blended images had the highest scores for image quality and overall image preference (ps < 0.001).

CONCLUSION

At an equal radiation dose, DE 40 keV showed higher CNR of HCC and DE blended image showed higher image quality and image preference compared with low kVp CT.

A novel computer-aided diagnostic system for accurate detection and grading of liver tumors

Liver cancer is a major cause of morbidity and mortality in the world. The primary goals of this manuscript are the identification of novel imaging markers (morphological, functional, and anatomical/textural), and development of a computer-aided diagnostic (CAD) system to accurately detect and grade liver tumors non-invasively. A total of 95 patients with liver tumors (M = 65, F = 30, age range = 34–82 years) were enrolled in the study after consents were obtained. 38 patients had benign tumors (LR1 = 19 and LR2 = 19), 19 patients had intermediate tumors (LR3), and 38 patients had hepatocellular carcinoma (HCC) malignant tumors (LR4 = 19 and LR5 = 19). A multi-phase contrast-enhanced magnetic resonance imaging (CE-MRI) was collected to extract the imaging markers. A comprehensive CAD system was developed, which includes the following main steps: i) estimation of morphological markers using a new parametric spherical harmonic model, ii) estimation of textural markers using a novel rotation invariant gray-level co-occurrence matrix (GLCM) and gray-level run-length matrix (GLRLM) models, and iii) calculation of the functional markers by estimating the wash-in/wash-out slopes, which enable quantification of the enhancement characteristics across different CE-MR phases. These markers were subsequently processed using a two-stages random forest-based classifier to classify the liver tumor as benign, intermediate, or malignant and determine the corresponding grade (LR1, LR2, LR3, LR4, or LR5). The overall CAD system using all the identified imaging markers achieved a sensitivity of 91.8%±0.9%, specificity of 91.2%±1.9%, and F\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{1}$$\end{document}1 score of 0.91±0.01, using the leave-one-subject-out (LOSO) cross-validation approach. Importantly, the CAD system achieved overall accuracies of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$88\%\pm 5\%$$\end{document}88%±5%, 85%±2%, 78%±3%, 83%±4%, and 79%±3% in grading liver tumors into LR1, LR2, LR3, LR4, and LR5, respectively. In addition to LOSO, the developed CAD system was tested using randomly stratified 10-fold and 5-fold cross-validation approaches. Alternative classification algorithms, including support vector machine, naive Bayes classifier, k-nearest neighbors, and linear discriminant analysis all produced inferior results compared to the proposed two stage random forest classification model. These experiments demonstrate the feasibility of the proposed CAD system as a novel tool to objectively assess liver tumors based on the new comprehensive imaging markers. The identified imaging markers and CAD system can be used as a non-invasive diagnostic tool for early and accurate detection and grading of liver cancer.