Noninvasive imaging of hepatocellular carcinoma: From diagnosis to prognosis

Epidemiology, pathophysiology and clinical aspects of Hepatocellular Carcinoma in MAFLD patients

Hepatocellular carcinoma (HCC) is undergoing a transformative shift, with metabolic-associated fatty liver disease (MAFLD) emerging as a dominant etiology. Diagnostic criteria for MAFLD involve hepatic steatosis and metabolic dysregulation. Globally, MAFLD prevalence stands at 38.77%, significantly linked to the escalating rates of obesity. Epidemiological data indicate a dynamic shift in the major etiologies of hepatocellular carcinoma (HCC), transitioning from viral to metabolic liver diseases. Besides the degree of liver fibrosis, several modifiable lifestyle risk factors, such as type 2 diabetes, obesity, alcohol use, smoking, and HBV, HCV infection contribute to the pathogenesis of HCC. Moreover  gut microbiota and genetic variants may contribute to HCC development.The pathophysiological link between MAFLD and HCC involves metabolic dysregulation, impairing glucose and lipid metabolism, inflammation and oxidative stress. Silent presentation poses challenges in early MAFLD-HCC diagnosis. Imaging, biopsy, and AI-assisted techniques aid diagnosis, while HCC surveillance in non-cirrhotic MAFLD patients remains debated.ITA.LI.CA. group proposes a survival-based algorithm for treatment based on Barcelona clinic liver cancer (BCLC) algorithm. Liver resection, transplantation, ablation, and locoregional therapies are applied based on the disease stage. Systemic treatments is promising, with initial immunotherapy results indicating a less favorable response in MAFLD-related HCC.Adopting lifestyle interventions and chemopreventive measures with medications, including aspirin, metformin, and statins, constitute promising approaches for the primary prevention of HCC.Prognosis is influenced by multiple factors, with MAFLD-HCC associated with prolonged survival. Emerging diagnostic biomarkers and epigenomic markers, show promising results for early HCC detection in the MAFLD population.

Liquid Chromatography/Tandem Mass Spectrometry-Based Simultaneous Analysis of 32 Bile Acids in Plasma and Conventional Biomarker-Integrated Diagnostic Screening Model Development for Hepatocellular Carcinoma

Imaging tests, tumor marker (TM) screening, and biochemical tests provide a definitive diagnosis of hepatocellular carcinoma (HCC). However, some patients with HCC may present TM-negative results, warranting a need for developing more sensitive and accurate screening biomarkers. Various diseases exhibit increased blood levels of bile acids, biosynthesized from cholesterol in the liver, and they have been associated with HCC. Herein, we analyzed plasma bile acids using liquid chromatography/tandem mass spectrometry and integrated them with conventional biomarkers to develop a diagnostic screening model for HCC. Plasma samples were obtained from patients diagnosed with chronic hepatitis, hepatic cirrhosis (HC), and HCC. A QTRAP 6500 mass spectrometer and a Nexera liquid chromatograph with a YMC-Triart C18 analytical column were used. The mobile phase A was a 20 mmol/L ammonium formate solution, and mobile phase B was a methanol/acetonitrile mixture (1:1, v/v) with 20 mmol/L ammonium formate. After determining the concentrations of 32 bile acids, statistical analysis and diagnostic screening model development were performed. Plasma concentrations of bile acids differed between sample groups, with significant differences observed between patients with HC and HCC. By integrating bile acid results with conventional biochemical tests, a potential diagnostic screening model for HCC was successfully developed. Future studies should increase the sample size and analyze the data in detail to verify the diagnostic efficacy of the model.

Biomarkers for diagnosis and therapeutic options in hepatocellular carcinoma

Liver cancer is a global health challenge, causing a significant social-economic burden. Hepatocellular carcinoma (HCC) is the predominant type of primary liver cancer, which is highly heterogeneous in terms of molecular and cellular signatures. Early-stage or small tumors are typically treated with surgery or ablation. Currently, chemotherapies and immunotherapies are the best treatments for unresectable tumors or advanced HCC. However, drug response and acquired resistance are not predictable with the existing systematic guidelines regarding mutation patterns and molecular biomarkers, resulting in sub-optimal treatment outcomes for many patients with atypical molecular profiles. With advanced technological platforms, valuable information such as tumor genetic alterations, epigenetic data, and tumor microenvironments can be obtained from liquid biopsy. The inter- and intra-tumoral heterogeneity of HCC are illustrated, and these collective data provide solid evidence in the decision-making process of treatment regimens. This article reviews the current understanding of HCC detection methods and aims to update the development of HCC surveillance using liquid biopsy. Recent critical findings on the molecular basis, epigenetic profiles, circulating tumor cells, circulating DNAs, and omics studies are elaborated for HCC diagnosis. Besides, biomarkers related to the choice of therapeutic options are discussed. Some notable recent clinical trials working on targeted therapies are also highlighted. Insights are provided to translate the knowledge into potential biomarkers for detection and diagnosis, prognosis, treatment response, and drug resistance indicators in clinical practice.

Shear-wave elastographic imaging in choroidal melanomas: clinical and hemodynamic correlations

PURPOSE

This study evaluated the role of shear wave elastography imaging (SWEΙ) in uveal melanomas and the associations between SWEI and clinical and hemodynamic findings.

STUDY DESIGN

Prospective, clinical study METHODS: Twelve patients with uveal melanomas, scheduled to undergo Ru-106 brachytherapy, were prospectively recruited from the Department of Ophthalmology of the University Hospital of Heraklion (September-December 2022). B-mode, hemodynamic and SWEI ultrasonography examinations were performed with the HiScan (OPTIKON 2000) and the LOGIQ E9 (GE Healthcare) sonographic systems, respectively. Differences in SWEI scores (kPa) between tumor (TS) and adjacent non-affected choroid (CS), as well as between TS and orbital fat (FS) were examined. Correlations between SWEI and intra-tumoral hemodynamic parameters, including peak systolic and end diastolic velocities and resistivity index (RI) were also examined.

RESULTS

TS was significantly correlated with intra-tumoral RI (Pearson's bivariate correlation coefficient 0.681, p=0.015) and with maximal tumor height (Pearson's bivariate correlation coefficient 0.620, p=0.031). TS was significantly higher than both FS and CS scores (paired-samples t-test, p=0.003 and p=0.006, respectively).

CONCLUSIONS

SWEI score is applicable as a quantitative biomechanical marker in the assessment of choroidal melanoma. Choroidal melanomas are stiffer than both adjacent choroid and orbital fat. Moreover, choroidal melanomas with higher RI as well as those with higher apical elevations display higher SWEI scores.

Nomogram predicting the prognosis of primary liver cancer after radiofrequency ablation combined with transcatheter arterial chemoembolization

BACKGROUND

The incidence and mortality rates of primary hepatocellular carcinoma (HCC) are high, and the conventional treatment is radiofrequency ablation (RFA) with transcatheter arterial chemoembolization (TACE); however, the 3-year survival rate is still low. Further, there are no visual methods to effectively predict their prognosis.

AIM

To explore the factors influencing the prognosis of HCC after RFA and TACE and develop a nomogram prediction model.

METHODS

Clinical and follow-up information of 150 patients with HCC treated using RFA and TACE in the Hangzhou Linping Hospital of Traditional Chinese Medicine from May 2020 to December 2022 was retrospectively collected and recorded. We examined their prognostic factors using multivariate logistic regression and created a nomogram prognosis prediction model using the R software (version 4.1.2). Internal verification was performed using the bootstrapping technique. The prognostic efficacy of the nomogram prediction model was evaluated using the concordance index (CI), calibration curve, and receiver operating characteristic curve.

RESULTS

Of the 150 patients treated with RFA and TACE, 92 (61.33%) developed recurrence and metastasis. Logistic regression analysis identified six variables, and a predictive model was created. The internal validation results of the model showed a CI of 0.882. The correction curve trend of the prognosis prediction model was always near the diagonal, and the mean absolute error before and after internal validation was 0.021. The area under the curve of the prediction model after internal verification was 0.882 [95% confidence interval (95%CI): 0.820-0.945], with a specificity of 0.828 and sensitivity of 0.656. According to the Hosmer-Lemeshow test, χ 2 = 3.552 and P = 0.895. The predictive model demonstrated a satisfactory calibration, and the decision curve analysis demonstrated its clinical applicability.

CONCLUSION

The prognosis of patients with HCC after RFA and TACE is affected by several factors. The developed prediction model based on the influencing parameters shows a good prognosis predictive efficacy.

Aptamer-functionalized nanomaterials (AFNs) for therapeutic management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents one of the deadliest cancers globally, making the search for more effective diagnostic and therapeutic approaches particularly crucial. Aptamer-functionalized nanomaterials (AFNs), an innovative nanotechnology, have paved new pathways for the targeted diagnosis and treatment of HCC. Initially, we outline the epidemiological background of HCC and the current therapeutic challenges. Subsequently, we explore in detail how AFNs enhance diagnostic and therapeutic efficiency and reduce side effects through the specific targeting of HCC cells and the optimization of drug delivery. Furthermore, we address the challenges faced by AFNs in clinical applications and future research directions, with a particular focus on enhancing their biocompatibility and assessing long-term effects. In summary, AFNs represent an avant-garde therapeutic approach, opening new avenues and possibilities for the diagnosis and treatment of HCC.

Diagnostic efficacy of contrast-enhanced ultrasound, dynamic contrast-enhanced MRI combined with tumor markers AFP and DCP for primary hepatocellular carcinoma

The purpose of this study was to investigate the diagnostic efficacy of contrast-enhanced ultrasound (CEUS) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) combined with tumor markers alpha-fetoprotein (AFP) and des-γ-carboxyl prothrombin (DCP) for primary hepatic carcinoma (PHC). A total of 70 patients with PHC (PHC group), 42 patients with liver cyst (benign liver disease group (BLDG)) and 30 healthy people (healthy group (HG)) were selected as the research objects. CEUS and DCE-MRI were performed by American GE Vivid E9 color Doppler ultrasound system and Siemens 1.5T magnetic resonance imager, respectively. The levels of AFP and DCP were detected by ABBOTT i2000SR chemiluminescence instrument and enzyme-linked immunoassay (ELISA), respectively. In DCE-MRI examination, the portal phase and prolonged phase were mostly low signal in T1-weighted imaging (T1WI) sequence, and arterial phase was mostly high signal in T2WI sequence. In CEUS, most lesions showed hyper-enhancement in arterial phase, and hypo-enhancement in portal phase and delayed phase. AFP and DCP levels in PHC group were significantly higher than that in BLDG group and HG group. There were statistically significant differences among the three groups. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of combined diagnosis were statistically significant when compared with CEUS, AFP and DCP alone and either AFP or DCP positive. CEUS, DCE-MRI combined with tumor markers AFP and DCP have high sensitivity, specificity and accuracy in the diagnosis of PHC, which can more accurately diagnose the lesion type, provide basis for further treatment, and is worthy of clinical application.

Optimizing LI-RADS: ancillary features screened from LR-3/4 categories can improve the diagnosis of HCC on MRI

OBJECTIVE

To determine the high-efficiency ancillary features (AFs) screened from LR-3/4 lesions and the HCC/non-HCC group and the diagnostic performance of LR3/4 observations.

MATERIALS AND METHODS

We retrospectively analyzed a total of 460 patients (with 473 nodules) classified into LR-3-LR-5 categories, including 311 cases of hepatocellular carcinoma (HCC), 6 cases of non-HCC malignant tumors, and 156 cases of benign lesions. Two faculty abdominal radiologists with experience in hepatic imaging reviewed and recorded the major features (MFs) and AFs of the Liver Imaging Reporting and Data System (LI-RADS). The frequency of the features and diagnostic performance were calculated with a logistic regression model. After applying the above AFs to LR-3/LR-4 observations, the sensitivity and specificity for HCC were compared.

RESULTS

The average age of all patients was 54.24 ± 11.32 years, and the biochemical indicators ALT (P = 0.044), TBIL (P = 0.000), PLT (P = 0.004), AFP (P = 0.000) and Child‒Pugh class were significantly higher in the HCC group. MFs, mild-moderate T2 hyperintensity, restricted diffusion and AFs favoring HCC in addition to nodule-in-nodule appearance were common in the HCC group and LR-5 category. AFs screened from the HCC/non-HCC group (AF-HCC) were mild-moderate T2 hyperintensity, restricted diffusion, TP hypointensity, marked T2 hyperintensity and HBP isointensity (P = 0.005, < 0.001, = 0. 032, p < 0.001, = 0.013), and the AFs screened from LR-3/4 lesions (AF-LR) were restricted diffusion, mosaic architecture, fat in mass, marked T2 hyperintensity and HBP isointensity (P < 0.001, = 0.020, = 0.036, < 0.001, = 0.016), which were not exactly the same. After applying AF-HCC and AF-LR to LR-3 and LR-4 observations in HCC group and Non-HCC group, After the above grades changed, the diagnostic sensitivity for HCC were 84.96% using AF-HCC and 85.71% using AF-LR, the specificity were 89.26% using AF-HCC and 90.60% using AF-LR, which made a significant difference (P = 0.000). And the kappa value for the two methods of AF-HCC and AF-LR were 0.695, reaching a substantial agreement.

CONCLUSION

When adjusting for LR-3/LR-4 lesions, the screened AFs with high diagnostic ability can be used to optimize LI-RADS v2018; among them, AF-LR is recommended for better diagnostic capabilities.

The chemokine CCL20 can assist AFP in serological diagnosis of hepatocellular carcinoma

The chemokine 20 (CCL20) is a member of the CC chemokine family and plays a role in tumor immunity and autoimmune disease. This work investigated the value of CCL20 as a serum diagnostic marker for primary hepatocellular carcinoma (HCC). Based on the data of hepatocellular carcinoma patients in the TCGA database, the up-regulated genes encoding secretory proteins were analyzed in each pathological stage, and the candidate marker CCL20 gene was selected. Serum concentrations of CCL20 in patients with primary HCC, benign liver disease, and healthy subjects were analyzed by enzyme-linked immunosorbent assay (ELISA). The ROC curve evaluated the efficacy of CCL20 alone or in combination with AFP in the diagnosis of HCC. It was found the expression of CCL20 in HCC patients was significantly higher than that in the benign liver disease group and healthy controls (P < 0.05); The AUC of ROC curve to distinguish HCC patients from healthy controls was 0.859, the sensitivity was 73.42%, and the specificity was 86.84%. After combination with AFP, the AUC increased to 0.968, the sensitivity was 88.16%, and the specificity was 97.37%. Although CCL20 was increased in the serum of patients with benign liver diseases, combined with AFP, the AUC to distinguish HCC patients from non-HCC cohorts (benign liver disease group and healthy control group) was 0.902, with a sensitivity of 91.67% and a specificity of 75.26%. Collectively, serum CCL20 is closely related to the occurrence of HCC, and detection of serum CCL20 can assist AFP in improving the diagnostic sensitivity of HCC.

Quantitative peritumoral magnetic resonance imaging fingerprinting improves machine learning-based prediction of overall survival in colorectal cancer

Aim

To investigate magnetic resonance imaging (MRI)-based peritumoral texture features as prognostic indicators of survival in patients with colorectal liver metastasis (CRLM).

Methods

From 2007-2015, forty-eight patients who underwent MRI within 3 months prior to initiating treatment for CRLM were identified. Clinicobiological prognostic variables were obtained from electronic medical records. Ninety-four metastatic hepatic lesions were identified on T1-weighted post-contrast images and volumetrically segmented. A total of 112 radiomic features (shape, first-order, texture) were derived from a 10 mm region surrounding each segmented tumor. A random forest model was applied, and performance was tested by receiver operating characteristic (ROC). Kaplan-Meier analysis was utilized to generate the survival curves.

Results

Forty-eight patients (male:female = 23:25, age 55.3 years ± 18 years) were included in the study. The median lesion size was 25.73 mm (range 8.5-103.8 mm). Microsatellite instability was low in 40.4% (38/94) of tumors, with Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation detected in 68 out of 94 (72%) tumors. The mean survival was 35 months ± 21 months, and local disease progression was observed in 35.5% of patients. Univariate regression analysis identified 42 texture features [8 first order, 5 gray level dependence matrix (GLDM), 5 gray level run time length matrix (GLRLM), 5 gray level size zone matrix (GLSZM), 2 neighboring gray tone difference matrix (NGTDM), and 17 gray level co-occurrence matrix (GLCM)] independently associated with metastatic disease progression (P < 0.03). The random forest model achieved an area under the curve (AUC) of 0.88.

Conclusions

MRI-based peritumoral heterogeneity features may serve as predictive biomarkers for metastatic disease progression and patient survival in CRLM.

A Comprehensive Overview of the Efficacy and Safety of Gadopiclenol: A New Contrast Agent for MRI of the CNS and Body

ABSTRACT

This review describes the pharmacokinetics, efficacy, and safety of gadopiclenol, a new macrocyclic gadolinium-based contrast agent (GBCA) recently approved by the Food and Drug Administration at the dose of 0.05 mmol/kg. Gadopiclenol is a high relaxivity contrast agent that shares similar pharmacokinetic characteristics with other macrocyclic GBCAs, including a predominant renal excretion. In pediatric patients aged 2-17 years, the pharmacokinetic parameters (assessed through a population pharmacokinetics model) were comparable to those observed in adults, indicating no need for age-based dose adjustment. For contrast-enhanced magnetic resonance imaging (MRI) of the central nervous system (CNS) and body indications, gadopiclenol at 0.05 mmol/kg was shown to be noninferior to gadobutrol at 0.1 mmol/kg in terms of 3 lesion visualization parameters (ie, lesion border delineation, internal morphology, and contrast enhancement). Moreover, for contrast-enhanced MRI of the CNS, compared with gadobenate dimeglumine at 0.1 mmol/kg, gadopiclenol exhibited superior contrast-to-noise ratio at 0.1 mmol/kg and comparable contrast-to-noise ratio at 0.05 mmol/kg. A pooled safety analysis of 1047 participants showed a favorable safety profile for gadopiclenol. Comparative studies showed that the incidence and nature of adverse drug reactions with gadopiclenol were comparable to those observed with other GBCAs. Importantly, no significant safety concerns were identified in pediatric and elderly patients, as well as in patients with renal impairment. Overall, these findings support the clinical utility and safety of gadopiclenol for MRI in adult and pediatric patients aged 2 years and older in CNS and body indications.

Ultrasound Patterns of Hepatocellular Carcinoma and Their Prognostic Impact: A Retrospective Study

BACKGROUND

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death. Abdominal ultrasound (US) is by far the most widely used first-level exam for the diagnosis of HCC. We aimed to assess whether different ultrasound patterns were related to tumor prognosis.

METHODS

We retrospectively reviewed all patients with a new diagnosis of HCC (single nodule) and undergoing radiofrequency thermal ablation (RFTA) at our clinic between January 2009 and December 2021. Patients were classified according to four HCC ultrasound patterns: 1A, single capsulated nodule; 1B, well capsulated intra-node nodule; 1C, cluster consisting of capsulated nodules; and 2, non-capsulated nodule.

RESULTS

149 patients were analysed; median follow-up time was 43 months. US patterns 1A (32.9%) and 1B (61.1%) were the most commonly seen. Median overall survival (OS) and recurrence-free survival (RFS) from RFTA were 54 months (95% CI, 42-66) and 22 months (95% CI, 12-32), respectively. Pattern 1A showed the best OS. Compared to pattern 1A, 1B was independently associated with worse OS (51 months (95% CI, 34-68) vs. 46 months (95% CI, 18-62)) and RFS (34 months (95% CI, 27-41) vs. 18 months (95% CI, 12-24)). Patterns 1C and 2 were associated with worse RFS compared to 1A, while no difference was seen for OS. Among baseline clinical variables, pattern 1B exhibited higher histological grade (p = 0.048) and tumor dimension (p = 0.034) compared to pattern 1A.

CONCLUSIONS

Our findings demonstrate that different US patterns correlate with different survival outcomes and tumor behavior in patients with HCC. Prospective studies are needed to confirm these results.

Prediction of survival and analysis of prognostic factors for hepatocellular carcinoma: a 20-year of imaging diagnosis in Upper Northern Thailand

BACKGROUND

To evaluate survival rates of hepatocellular carcinoma (HCC), the Chiang Mai Cancer Registry provided characteristics data of 6276 HCC patients diagnosed between 1998-2020 based on evolution of imaging diagnosis. Evolution can be separated into four cohorts, namely, cohort 1 (1990-2005) when we had ultrasound (US) and single-phase computed tomography (CT), cohort 2 (2006-2009) when one multi-phase CT and one magnetic resonance imaging (MRI) were added, cohort 3 (2010-2015) when MRI with LI-RADS was added, and finally, cohort 4 (2016-2020) when two upgraded MRIs with LI-RADS were added.

METHODS

Cox proportional hazard models were used to determine the relation between death and risk factors including methods of imagining diagnosis, gender, age of diagnosis, tumor stages, history of smoking and alcohol-use, while Kaplan-Meier curves were used to calculate survival rates.

RESULTS

The median age of diagnosis was 57.0 years (IQR: 50.0-65.0) and the median survival time was 5.8 months (IQR: 1.9-26.8) during the follow-up period. In the univariable analysis, all factors were all associated with a higher risk of death in HCC patients except age of diagnosis. In a multivariable analysis, elderly age at diagnosis, regional and metastatic stages and advanced methods of imagining diagnosis during cohorts 2 and 3 were independently associated with the risk of death in HCC patients. The survival rate of patients diagnosed during cohort 4 was significantly higher than the other cohorts.

CONCLUSION

As a significantly increasing survival rate of HCC patients in cohort 4, advanced methods of diagnostic imaging can be a part of the recommendation to diagnose HCC.

Hepatocellular Carcinoma: Surveillance, Diagnosis, Evaluation and Management

Hepatocellular carcinoma (HCC) ranks fourth in cancer-related deaths worldwide. Semiannual surveillance of the disease for patients with cirrhosis or hepatitis B virus allows for early detection with more favorable outcomes. The current underuse of surveillance programs demonstrates the need for intervention at both the patient and provider level. Mail outreach along with navigation provision has proven to increase surveillance follow-up in patients, while provider-targeted electronic medical record reminders and compliance reports have increased provider awareness of HCC surveillance. Imaging is the primary mode of diagnosis in HCC with The Liver Imaging Reporting and Data System (LI-RADS) being a widely accepted comprehensive system that standardizes the reporting and data collection for HCC. The management of HCC is complex and requires multidisciplinary team evaluation of each patient based on their preference, the state of the disease, and the available medical and surgical interventions. Staging systems are useful in determining the appropriate intervention for HCC. Early-stage HCC is best managed by curative treatment modalities, such as liver resection, transplant, or ablation. For intermediate stages of the disease, transarterial local regional therapies can be applied. Advanced stages of the disease are treated with systemic therapies, for which there have been recent advances with new drug combinations. Previously sorafenib was the mainstay systemic treatment, but the recent introduction of atezolizumab plus bevacizumab proves to have a greater impact on overall survival. Although there is a current lack of improved outcomes in Phase III trials, neoadjuvant therapies are a potential avenue for HCC management in the future.

Factors associated with heterochronic gastric cancer development post-endoscopic mucosal dissection in early gastric cancer patients

BACKGROUND

Endoscopic mucosal resection is an innovative method for treating early gastric cancer and has been widely used in clinical practice.

AIM

To analyze the factors associated with the development of heterochronic gastric cancer in patients with early gastric cancer who had undergone endoscopic mucosal dissection (EMD).

METHODS

A cohort of patients with early gastric cancer treated using EMD was retrospectively analyzed, and patients who developed heterochronic gastric cancer after the surgery were compared with those who did not. The effects of patient age, sex, tumor size, pathological type, and surgical technique on the development of heterochronic gastric cancer were assessed using statistical analysis.

RESULTS

Of the 300 patients with early gastric cancer, 150 patients developed heterochronic gastric cancer after EMD. Statistical analysis revealed that patient age (P value = XX), sex (P value = XX), tumor size (P value = XX), pathological type (P value = XX), and surgical technique (P value = XX) were significantly associated with the occurrence of heterochronic gastric cancer.

CONCLUSION

Age, sex, tumor size, pathological type, and surgical technique are key factors influencing the occurrence of heterochronic gastric cancer after EMD in patients with early gastric cancer. To address these factors, postoperative follow-up and management should be strengthened to improve the prognosis and survival rate of patients.

Towards refining the utility of dual (18F-FDG / 18F-Choline) PET/CT for the management of hepatocellular carcinoma: a tertiary center study

BACKGROUND

The role of positron emission tomography/computed tomography (PET/CT) in hepatocellular carcinoma (HCC) management is not clearly defined. Our objective was to analyze the utility of dual-PET/CT (18F-FDG + 18F-Choline) imaging findings on the BCLC staging and treatment decision for HCC patients.

METHODS

Between January 2011 and April 2019, 168 consecutive HCC patients with available baseline dual-PET/CT imaging data were retrospectively analyzed. To identify potential refinement criteria for surgically-treated patients, survival Kaplan-Meier curves of various standard-of-care and dual-PET/CT baseline parameters were estimated. Finally, multivariate cox proportional hazard ratios of the most relevant clinico-biological and/or PET parameters were estimated.

RESULTS

Dual-PET/CT findings increased the score of BCLC staging in 21 (12.5%) cases. In 24.4% (N.=41) of patients, the treatment strategy was modified by the PET findings. Combining AFP levels at a threshold of 10 ng/mL with 18F-FDG or 18F-Choline N status significantly impacted DFS (P<0.05). In particular, the combined criteria of the N+ status assessed by 18F-Choline with AFP threshold of 10 ng/mL provided a highly predictive composite parameter for estimation of DFS according to multivariate analysis (HR=10.6, P<0.05).

CONCLUSIONS

The 18F-Choline / AFP composite parameter appears promising, and further prospective studies are mandatory to validate its oncological impact.

Hepatic epithelioid hemangioendothelioma-a single-institution experience with 51 cases

Objectives

The aim of the present study was to describe the experience at a single institution in the management of hepatic epithelioid hemangioendothelioma (HEHE).

Methods

We included 51 patients with histologically confirmed HEHE. We performed log-rank (Cox-Mantel) survival analyses using Kaplan-Meier methods to test differences in survival between patients in different groups. Univariate Cox regression analyses and multivariate proportional hazards regression model were carried out to identify independent prognostic factors.

Results

Different imaging modalities were used to diagnose HEHE with various presentations. Liver resection (LR), liver transplantation (LT), systemic treatment (ST), and surveillance had been used in our study. A significant difference was noted between the LR group and the surveillance group with respect to mean survival (p = 0.006), as was in the LR group and the ST group (p = 0.036), and in surgical approach (LR and LT) and nonsurgical approach (ST and surveillance) (p = 0.008). The mean survival between the ST group and the surveillance group was not significantly different (p = 0.851). LR (p = 0.010) and surgical approach (p = 0.014) were favorable predictors of outcome, while macrovascular invasion (MaVI) (p = 0.037), lung metastasis (p = 0.040), and surveillance (p = 0.033) were poor prognostic factors in univariate analysis. Multivariate analysis showed that LR (p = 0.010) and surgical approach (p = 0.014) were independently associated with good OS, while surveillance (p = 0.033) was independently associated with poor OS. After adjusting for confounding factors, patients in the LR group have much better OS than those in the surveillance group (p = 0.013). However, there was no significant difference in OS between the LR group and ST group (p = 0.254), as was in the ST group and the surveillance group (p = 0.857).

Conclusions

The definitive diagnosis of HEHE was dependent on histopathology, and it was not possible to make a specific diagnosis without biopsy because the radiological findings were similar to those in some hepatic malignancies. ST was not recommended for patients who were not candidates for surgical approaches, and surgical approaches should be warranted regardless of disease stage. The retrospective nature and the small size of the data limited the generalizability of the study, designing a worldwide database that contains all data about patients with HEHE independent of their therapy, which was highly recommended.

Natural History and Outcomes of Cavernous Transformation of the Portal Vein in Cirrhosis

BACKGROUND AND AIMS

Cavernous transformation of the portal vein can occur after portal vein thrombosis (PVT). In this study, we investigated clinical complications associated with cavernous transformation in the context of cirrhosis and PVT.

METHODS

In this retrospective cohort analysis, 204 patients with cirrhosis and PVT with or without cavernous transformation were identified using MUSC's Clinical Data Warehouse between January 1, 2013, through December 31, 2019. Complete demographic data, clinical history, and laboratory tests were abstracted from the electronic medical record.

RESULTS

Of 204 patients, 41 (20%) had cavernous transformation. MELD, Child-Pugh, and Charlson Comorbidity Index scores were similar among groups. There were no significant differences in the prevalence of esophageal varices (with or without bleeding), splenomegaly, or hepatic encephalopathy in patients with and without cavernous transformation, although ascites tended to be lower in patients with cavernous transformation (31/41 (76%) vs 142/163 (87%), p = 0.06). Patients with cavernous transformation were significantly less likely to have hepatocellular carcinoma (HCC) (13/41 (32%) vs 81/163 (50%), p < 0.05) and had significantly lower APRI (1.4 vs 2.0, p < 0.05) and Fib-4 (4.7 vs 6.5, p < 0.05). Patients with cavernous transformation had lower 5-year mortality (12/41 (29%) vs 81/163 (49%) died, p = 0.06). The 10-year mortality of patients with cavernous transformation without HCC was significantly lower than in those without cavernous transformation (8/28 (29%) vs 46/82 (56%), respectively, p < 0.05).

CONCLUSIONS

Patients with cavernous transformation appeared to have better outcomes than those without cavernous transformation.

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

Purpose

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

Methods

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

Results

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

Conclusion

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

Hepatocellular Carcinoma: a Narrative Review on Current Knowledge and Future Prospects

OPINION STATEMENT

Hepatocellular carcinoma is the fourth leading cause of cancer-related deaths worldwide and its associated mortality rate is expected to rise within the next decade. The incidence rate of hepatocellular carcinoma varies significantly across countries and the latter can be attributed to the differences in risk factors that are prevalent across different countries. Some of the risk factors associated with hepatocellular carcinoma include hepatitis B and C infections, non-alcoholic fatty liver disease, and alcoholic liver disease. Regardless of the underlying aetiology, the end result is liver fibrosis and cirrhosis that ultimately progress into carcinoma. The treatment and management of hepatocellular carcinoma is complicated by treatment resistance and high tumor recurrence rates. Early stages of hepatocellular carcinoma are treated with liver resection and other forms of surgical therapy. Advanced stages of hepatocellular carcinoma can be treated with chemotherapy, immunotherapy, and the use of oncolytic viruses and these treatment options can be combined with nanotechnology to improve efficacy and reduce side effects. Moreover, chemotherapy and immunotherapy can be combined to further improve treatment efficacy and overcome resistance. Despite the treatment options available, the high mortality rates provide evidence that current treatment options for advanced-stage hepatocellular carcinoma are not achieving the desired therapeutic goals. Various clinical trials are ongoing to improve treatment efficacy, reduce recurrence rates, and ultimately prolong survival. This narrative review aims to provide an update on our current knowledge and future direction of research on hepatocellular carcinoma.

Delivery of Lipid Nanoparticles with ROS Probes for Improved Visualization of Hepatocellular Carcinoma

Reactive oxygen species (ROS) are highly reactive products of the cell metabolism derived from oxygen molecules, and their abundant level is observed in many diseases, particularly tumors, such as hepatocellular carcinoma (HCC). In vivo imaging of ROS is a necessary tool in preclinical research to evaluate the efficacy of drugs with antioxidant activity and for diagnosis and monitoring of diseases. However, most known sensors cannot be used for in vivo experiments due to low stability in the blood and rapid elimination from the body. In this work, we focused on the development of an effective delivery system of fluorescent probes for intravital ROS visualization using the HCC model. We have synthesized various lipid nanoparticles (LNPs) loaded with ROS-inducible hydrocyanine pro-fluorescent dye or plasmid DNA (pDNA) with genetically encoded protein sensors of hydrogen peroxide (HyPer7). LNP with an average diameter of 110 ± 12 nm, characterized by increased stability and pDNA loading efficiency (64 ± 7%), demonstrated preferable accumulation in the liver compared to 170 nm LNPs. We evaluated cytotoxicity and demonstrated the efficacy of hydrocyanine-5 and HyPer7 formulated in LNP for ROS visualization in mouse hepatocytes (AML12 cells) and in the mouse xenograft model of HCC. Our results demonstrate that obtained LNP could be a valuable tool in preclinical research for visualization ROS in liver diseases.

Deep Learning Algorithm for Differentiating Patients with a Healthy Liver from Patients with Liver Lesions Based on MR Images

The problems in diagnosing the state of a vital organ such as the liver are complex and remain unresolved. These problems are underscored by frequently published studies on this issue. At the same time, demand for imaging diagnostics, preferably using a method that can detect the disease at the earliest possible stage, is constantly increasing. In this paper, we present liver diseases in the context of diagnosis, diagnostic problems, and possible elimination. We discuss the dataset and methods and present the stages of the pipeline we developed, leading to multiclass segmentation of the liver in multiparametric MR image into lesions and normal tissue. Finally, based on the processing results, each case is classified as either a healthy liver or a liver with lesions. For the training set, the AUC ROC is 0.925 (standard error 0.013 and a p-value less than 0.001), and for the test set, the AUC ROC is 0.852 (standard error 0.039 and a p-value less than 0.001). Further refinements to the proposed pipeline are also discussed. The proposed approach could be used in the detection of focal lesions in the liver and the description of liver tumors. Practical application of the developed multi-class segmentation method represents a key step toward standardizing the medical evaluation of focal lesions in the liver.

Imaging of Hepatobiliary Cancer

The liver and biliary tree are common sites of primary and secondary malignancies. MRI followed by CT is the mainstay for the imaging characterization of these malignancies with the dynamically acquired contrast enhanced phases being the most important for diagnosis. The liver imaging reporting and data system classification provides a useful framework for reporting lesions in patents with underlying cirrhosis or who are at high risk for developing hepatocellular carcinoma. Detection of metastases is improved with the use of liver specific MRI contrast agents and diffusion weighted sequences. Aside from hepatocellular carcinoma, which is often diagnosed noninvasively, other primary hepatobiliary tumors may require biopsy for definite diagnosis, especially when presenting with nonclassic imaging findings. In this review, we examine the imaging findings of common and less common hepatobiliary tumors.

Ultrasound radiomics in the prediction of microvascular invasion in hepatocellular carcinoma: A systematic review and meta-analysis

Purpose

To systematically assess the clinical value of ultrasound radiomics in the prediction of microvascular invasion in hepatocellular carcinoma (HCC).

Methods

Relevant articles were searched in PubMed, Web of Science, Cochrane Library, Embase and Medline and screened according to the eligibility criteria. The quality of the included articles was assessed based on the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. After article assessment and data extraction, the diagnostic performance of ultrasound radiomics was evaluated based on pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR), and the area under the curve (AUC) was calculated by generating the ROC curve. Meta-analysis was performed using Stata 15.1, and subgroup analysis was conducted to identify the sources of heterogeneity. A Fagan nomogram was generated to assess the clinical utility of ultrasound radiomics.

Results

Five studies involving 1260 patients were included. Meta-analysis showed that ultrasound radiomics had a pooled sensitivity of 79% (95% CI: 75-83%), specificity of 70% (95% CI: 59-79%), PLR of 2.6 (95% CI: 1.9-3.7), NLR of 0.30 (95% CI: 0.23-0.39), DOR of 9 (95% CI: 5-16), and AUC of 0.81 (95% CI: 0.78-0.85). Sensitivity analysis indicated that the results were statistically reliable and stable, and no significant difference was identified during subgroup analysis.

Conclusion

Ultrasound radiomics has favorable predictive performance in the microvascular invasion of HCC and may serve as an auxiliary tool for guiding clinical decision-making.

Diagnostic value of imaging modalities in primary squamous cell carcinoma of the liver

Primary squamous cell carcinoma of the liver (PSCCL) is rare. PSCCL's lack of specific clinical manifestations and laboratory tests necessitate preoperative diagnosis via imaging examination. Conventional ultrasound (US) demonstrates a mass with mixed echogenicity, and contrast-enhanced US shows a circular pattern of "fast forward, fast backward or slow backward, high enhancement." Enhanced computed tomography (CT) showed enhancement in the center or edge of the lesion, and the density of the enhanced lesion was lower than that of the liver tissue in the same layer. Positron emission tomography-CT demonstrates an inhomogeneous low-density mass with increased 18F-FDG metabolism. Magnetic resonance imaging shows low signal intensity on T1-weighed images (T1WI) and high signal on T2-weighed images (T2WI). By summarizing the imaging characteristics of PSCCL, this review aims to improve clinicians' understanding of PSCCL and its diagnosis.

Short-term PET-derived kinetic estimation for the diagnosis of hepatocellular carcinoma: a combination of the maximum-slope method and dual-input three-compartment model

BACKGROUND

Kinetic estimation provides fitted parameters related to blood flow perfusion and fluorine-18-fluorodeoxyglucose (¹⁸F-FDG) transport and intracellular metabolism to characterize hepatocellular carcinoma (HCC) but usually requires 60 min or more for dynamic PET, which is time-consuming and impractical in a busy clinical setting and has poor patient tolerance.

METHODS

This study preliminarily evaluated the equivalence of liver kinetic estimation between short-term (5-min dynamic data supplemented with 1-min static data at 60 min postinjection) and fully 60-min dynamic protocols and whether short-term ¹⁸F-FDG PET-derived kinetic parameters using a three-compartment model can be used to discriminate HCC from the background liver tissue. Then, we proposed a combined model, a combination of the maximum-slope method and a three-compartment model, to improve kinetic estimation.

RESULTS

There is a strong correlation between the kinetic parameters K₁ ~ k₃, HPI and [Formula: see text] in the short-term and fully dynamic protocols. With the three-compartment model, HCCs were found to have higher k₂, HPI and k₃ values than background liver tissues, while K₁, k₄ and [Formula: see text] values were not significantly different between HCCs and background liver tissues. With the combined model, HCCs were found to have higher HPI, K₁ and k₂, k₃ and [Formula: see text] values than background liver tissues; however, the k₄ value was not significantly different between HCCs and the background liver tissues.

CONCLUSIONS

Short-term PET is closely equivalent to fully dynamic PET for liver kinetic estimation. Short-term PET-derived kinetic parameters can be used to distinguish HCC from background liver tissue, and the combined model improves the kinetic estimation.

CLINICAL RELEVANCE STATEMENT

Short-term PET could be used for hepatic kinetic parameter estimation. The combined model could improve the estimation of liver kinetic parameters.

Mucins as Potential Biomarkers for Early Detection of Cancer

Early detection significantly correlates with improved survival in cancer patients. So far, a limited number of biomarkers have been validated to diagnose cancers at an early stage. Considering the leading cancer types that contribute to more than 50% of deaths in the USA, we discuss the ongoing endeavors toward early detection of lung, breast, ovarian, colon, prostate, liver, and pancreatic cancers to highlight the significance of mucin glycoproteins in cancer diagnosis. As mucin deregulation is one of the earliest events in most epithelial malignancies following oncogenic transformation, these high-molecular-weight glycoproteins are considered potential candidates for biomarker development. The diagnostic potential of mucins is mainly attributed to their deregulated expression, altered glycosylation, splicing, and ability to induce autoantibodies. Secretory and shed mucins are commonly detected in patients' sera, body fluids, and tumor biopsies. For instance, CA125, also called MUC16, is one of the biomarkers implemented for the diagnosis of ovarian cancer and is currently being investigated for other malignancies. Similarly, MUC5AC, a secretory mucin, is a potential biomarker for pancreatic cancer. Moreover, anti-mucin autoantibodies and mucin-packaged exosomes have opened new avenues of biomarker development for early cancer diagnosis. In this review, we discuss the diagnostic potential of mucins in epithelial cancers and provide evidence and a rationale for developing a mucin-based biomarker panel for early cancer detection.

Pre-operative MRI features predict early post-operative recurrence of hepatocellular carcinoma with different degrees of pathological differentiation

PURPOSE

To investigate the value of pre-operative gadoxetate disodium (Gd-EOB-DTPA) enhanced MRI predicting early post-operative recurrence (< 2 years) of hepatocellular carcinoma (HCC) with different degrees of pathological differentiation.

METHODS

Retrospective analysis of pre-operative MR imaging features of 177 patients diagnosed as suffering from HCC and that underwent radical resection. Multivariate logistic regression assessment was adopted to assess predictors for HCC recurrence with different degrees of pathological differentiation. The area under the curve (AUC) of receiver operating characteristics (ROC) was utilized to assess the diagnostic efficacy of the predictors.

RESULTS

Among the 177 patients, 155 (87.5%) were males, 22 (12.5%) were females; the mean age was 49.97 ± 10.71 years. Among the predictors of early post-operative recurrence of highly-differentiated HCC were an unsmooth tumor margin and an incomplete/without tumor capsule (p = 0.037 and 0.033, respectively) whereas those of early post-operative recurrence of moderately-differentiated HCC were incomplete/without tumor capsule, peritumoral enhancement along with peritumoral hypointensity (p = 0.006, 0.046 and 0.004, respectively). The predictors of early post-operative recurrence of poorly-differentiated HCC were peritumoral enhancement, peritumoral hypointensity, and tumor thrombosis (p = 0.033, 0.006 and 0.021, respectively). The AUCs of the multi-predictor diagnosis of early post-operative recurrence of highly-, moderately-, and poorly-differentiated HCC were 0.841, 0.873, and 0.875, respectively. The AUCs of the multi-predictor diagnosis were each higher than for those predicted separately.

CONCLUSIONS

The imaging parameters for predicting early post-operative recurrence of HCC with different degrees of pathological differentiation were different and combining these predictors can improve the diagnostic efficacy of early post-operative HCC recurrence.

Management of Hepatocellular Carcinoma: A Review

Importance

Hepatocellular carcinoma (HCC) is the sixth most common malignancy and fourth leading cause of cancer-related death worldwide. Recent advances in systemic and locoregional therapies have led to changes in many guidelines regarding systemic therapy, as well as the possibility to downstage patients to undergo resection. This review examines the advances in surgical and medical therapies relative to multidisciplinary treatment strategies for HCC.

Observations

HCC is a major health problem worldwide. The obesity epidemic has made nonalcoholic fatty liver disease a major risk factor for the development of HCC. Multiple societies, such as the American Association for the Study of Liver Diseases, the European Association for the Study of the Liver, the Asian Pacific Association for the Study of the Liver, and the National Comprehensive Cancer Network, provide guidelines for screening at-risk patients, as well as define staging systems to guide optimal treatment strategies. The Barcelona Clinic Liver Cancer staging system is widely accepted and has recently undergone updates with the introduction of new systemic therapies and stage migration.

Conclusions and Relevance

The treatment of patients with HCC should involve a multidisciplinary approach with collaboration among surgeons, medical oncologists, radiation oncologists, and interventional radiologists to provide optimal care. Treatment paradigms must consider both tumor and patient-related factors such as extent of liver disease, which is a main driver of morbidity and mortality. The advent of more effective systemic and locoregional therapies has prolonged survival among patients with advanced disease and allowed some patients to undergo surgical intervention who would otherwise have disease considered unresectable.

Multiparametric MRI-based radiomics for the prediction of microvascular invasion in hepatocellular carcinoma

BACKGROUND

Preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is essential in obtaining a successful surgical treatment, in decreasing recurrence, and in improving survival.

PURPOSE

To investigate the value of multiparametric magnetic resonance imaging (MRI)-based radiomics in the prediction of peritumoral MVI in HCC.

MATERIAL AND METHODS

A total of 102 patient with pathologically proven HCC after surgical resection from June 2014 to March 2018 were enrolled in this retrospective study. Histological analysis of resected specimens confirmed positive MVI in 48 patients and negative MVI in 54 patients. Radiomics features were extracted from four MRI sequences and selected with the least absolute shrinkage and selection operator (LASSO) regression and used to analyze the tumoral and peritumoral regions for MVI. Univariate logistic regression was employed to identify the most important clinical factors, which were integrated with the radiomics signature to develop a nomogram.

RESULTS

In total, 11 radiomics features were selected and used to build the radiomics signature. The serum level of alpha-fetoprotein was identified as the clinical factor with the highest predictive value. The developed nomogram achieved the highest AUC in predicting MVI status. The decision curve analysis confirmed the potential clinical utility of the proposed nomogram.

CONCLUSION

The multiparametric MRI-based radiomics nomogram is a promising tool for the preoperative diagnosis of peritumoral MVI in HCCs and helps determine the appropriate medical or surgical therapy.

Epidemiological Study of Hepatopancreatobiliary Sarcoma in Iran, 2010 - 2014

Background: Hepatopancreatobiliary (HPB) malignancies are a relatively rare but important type of cancer with usually poor prognosis. Prompt diagnosis and treatment are crucial to improving the patient’s outcome. For this issue, acknowledgment of epidemiological characteristics is helpful. Objectives: In this study, the epidemiological characteristics of cases with HPB sarcoma among Iranian patients were assessed. Methods: In this epidemiological study, 133 consecutive cases with HPB sarcoma in Iran from 2010 to 2014 were evaluated, including gallbladder, pancreas, hepatic, pancreatic body and head, and other biliary tumors. Results: Nine gallbladder sarcoma cases were reported between 2010 and 2014, accounting for 6.7% of all HPB sarcoma cases, and leiomyosarcoma was the most common. A total of 16 patients of pancreatic origin were reported during this period, with the highest rate of 6 cases in 2011; in this sarcoma category, malignant type spindle cell tumor was the most common type accounting for 12.5% of all cases. Ninety-five cases of liver sarcomas were reported generally. Non-specified and desmoplastic small round cell tumors were the most common types. Five cases of pancreatic head sarcomas were reported during 2010 - 2013. There was no predominant tumor type. Five cases of pancreatic head sarcoma were reported during 2010 - 2013. There was no dominant tumor type. About the other biliary tract sites, six patients were reported. Gastrointestinal stromal sarcoma was the most common type. Conclusions: Hepatopancreatobiliary sarcoma in the Iranian population generally has diverse types, and there are different patterns according to the age and sex distribution in patients according to the initial location of the tumor and also their pathological subtypes.

Ensemble Learning of Multiple Models Using Deep Learning for Multiclass Classification of Ultrasound Images of Hepatic Masses

Ultrasound (US) is often used to diagnose liver masses. Ensemble learning has recently been commonly used for image classification, but its detailed methods are not fully optimized. The purpose of this study is to investigate the usefulness and comparison of some ensemble learning and ensemble pruning techniques using multiple convolutional neural network (CNN) trained models for image classification of liver masses in US images. Dataset of the US images were classified into four categories: benign liver tumor (BLT) 6320 images, liver cyst (LCY) 2320 images, metastatic liver cancer (MLC) 9720 images, primary liver cancer (PLC) 7840 images. In this study, 250 test images were randomly selected for each class, for a total of 1000 images, and the remaining images were used as the training. 16 different CNNs were used for training and testing ultrasound images. The ensemble learning used soft voting (SV), weighted average voting (WAV), weighted hard voting (WHV) and stacking (ST). All four types of ensemble learning (SV, ST, WAV, and WHV) showed higher values of accuracy than the single CNN. All four types also showed significantly higher deep learning (DL) performance than ResNeXt101 alone. For image classification of liver masses using US images, ensemble learning improved the performance of DL over a single CNN.

Rapid, label-free histopathological diagnosis of liver cancer based on Raman spectroscopy and deep learning

Biopsy is the recommended standard for pathological diagnosis of liver carcinoma. However, this method usually requires sectioning and staining, and well-trained pathologists to interpret tissue images. Here, we utilize Raman spectroscopy to study human hepatic tissue samples, developing and validating a workflow for in vitro and intraoperative pathological diagnosis of liver cancer. We distinguish carcinoma tissues from adjacent non-tumour tissues in a rapid, non-disruptive, and label-free manner by using Raman spectroscopy combined with deep learning, which is validated by tissue metabolomics. This technique allows for detailed pathological identification of the cancer tissues, including subtype, differentiation grade, and tumour stage. 2D/3D Raman images of unprocessed human tissue slices with submicrometric resolution are also acquired based on visualization of molecular composition, which could assist in tumour boundary recognition and clinicopathologic diagnosis. Lastly, the potential for a portable handheld Raman system is illustrated during surgery for real-time intraoperative human liver cancer diagnosis.

Accelerated T2-weighted MRI of the liver at 3 T using a single-shot technique with deep learning-based image reconstruction: impact on the image quality and lesion detection

PURPOSE

Fat-suppressed T2-weighted imaging (T2-FS) requires a long scan time and can be wrought with motion artifacts, urging the development of a shorter and more motion robust sequence. We compare the image quality of a single-shot T2-weighted MRI prototype with deep-learning-based image reconstruction (DL HASTE-FS) with a standard T2-FS sequence for 3 T liver MRI.

METHODS

41 consecutive patients with 3 T abdominal MRI examinations including standard T2-FS and DL HASTE-FS, between 5/6/2020 and 11/23/2020, comprised the study cohort. Three radiologists independently reviewed images using a 5-point Likert scale for artifact and image quality measures, while also assessing for liver lesions.

RESULTS

DL HASTE-FS acquisition time was 54.93 ± 16.69, significantly (p < .001) shorter than standard T2-FS (114.00 ± 32.98 s). DL HASTE-FS received significantly higher scores for sharpness of liver margin (4.3 vs 3.3; p < .001), hepatic vessel margin (4.2 vs 3.3; p < .001), pancreatic duct margin (4.0 vs 1.9; p < .001); in-plane (4.0 vs 3.2; p < .001) and through-plane (3.9 vs 3.4; p < .001) motion artifacts; other ghosting artifacts (4.3 vs 2.9; p < .001); and overall image quality (4.0 vs 2.9; p < .001), in addition to receiving a higher score for homogeneity of fat suppression (3.7 vs 3.4; p = .04) and liver-fat contrast (p = .03). For liver lesions, DL HASTE-FS received significantly higher scores for sharpness of lesion margin (4.4 vs 3.7; p = .03).

CONCLUSION

Novel single-shot T2-weighted MRI with deep-learning-based image reconstruction demonstrated superior image quality compared with the standard T2-FS sequence for 3 T liver MRI, while being acquired in less than half the time.

Preoperative and Prognostic Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Review Based on Artificial Intelligence

Microvascular invasion of hepatocellular carcinoma is an important factor affecting tumor recurrence after liver resection and liver transplantation. There are many ways to classify microvascular invasion, however, an international consensus is urgently needed. Recently, artificial intelligence has emerged as an important tool for improving the clinical management of hepatocellular carcinoma. Many studies about microvascular invasion currently focus on preoperative and prognosis prediction of microvascular invasion using artificial intelligence. In this paper, we review the definition and staging of microvascular invasion, especially the diagnosis of it by using artificial intelligence. In preoperative prediction, deep learning based on multimodal data modeling of radiomics-screened features, clinical features, and medical images is currently the most effective means. In prognostic prediction, pathology is the gold standard, and the techniques used should more effectively utilize the global features of the pathology images.

Role of Machine Learning in Precision Oncology: Applications in Gastrointestinal Cancers

Gastrointestinal (GI) cancers, consisting of a wide spectrum of pathologies, have become a prominent health issue globally. Despite medical imaging playing a crucial role in the clinical workflow of cancers, standard evaluation of different imaging modalities may provide limited information. Accurate tumor detection, characterization, and monitoring remain a challenge. Progress in quantitative imaging analysis techniques resulted in "radiomics", a promising methodical tool that helps to personalize diagnosis and treatment optimization. Radiomics, a sub-field of computer vision analysis, is a bourgeoning area of interest, especially in this era of precision medicine. In the field of oncology, radiomics has been described as a tool to aid in the diagnosis, classification, and categorization of malignancies and to predict outcomes using various endpoints. In addition, machine learning is a technique for analyzing and predicting by learning from sample data, finding patterns in it, and applying it to new data. Machine learning has been increasingly applied in this field, where it is being studied in image diagnosis. This review assesses the current landscape of radiomics and methodological processes in GI cancers (including gastric, colorectal, liver, pancreatic, neuroendocrine, GI stromal, and rectal cancers). We explain in a stepwise fashion the process from data acquisition and curation to segmentation and feature extraction. Furthermore, the applications of radiomics for diagnosis, staging, assessment of tumor prognosis and treatment response according to different GI cancer types are explored. Finally, we discussed the existing challenges and limitations of radiomics in abdominal cancers and investigate future opportunities.

The Value of MRI Combined with AFP, AFP-L3, GP73, and DCP in the Diagnosis of Early Primary Liver Cancer

Objective

To investigate the diagnostic value of magnetic resonance imaging (MRI) combined with serum alpha-fetoprotein (AFP), alpha-fetoprotein (AFP-L3), Golgi protein 73 (GP73), and des-γ-carboxyprothrombin (DCP) on early-stage primary liver cancer (PHC).

Methods

A total of 122 patients who were treated in our hospital from January 2019 to May 2022 were included in this study, including 62 patients with early PHC (referred to as the observation group) and 60 patients with benign liver disease (referred to as the control group). MRI scans were performed on all participants, and MRI image features were compared. Subsequently, the differences in serum AFP, AFP-L3, GP73, and DCP concentrations of the two groups of patients were detected and compared. Receiver operating characteristic (ROC) curve was used to analyze the efficacy of MRI and each of the above tumor markers in diagnosing early PHC.

Results

The proportion of low or slightly low signal on T1WI in the observation group was significantly greater than that in the control group, while the proportions of equisignal and high signal were lower than those in the control group. The proportion of high signal on T2WI and high signal on DWI in the observation group was higher than that in the control group, while the proportion of low or slightly low signal and equisignal was lower than that in the control group. Compared with the control group, the serum concentrations of AFP, AFP-L3, GP73, and DCP in the observation group were significantly increased (all P < 0.05). For the diagnosis of early-stage PHC patients, MRI combined with these four markers showed favorable diagnostic value compared with parameter alone (area under the ROC curve, sensitivity, and specificity were 0.943, 0.919, and 0.833, respectively).

Conclusion

MRI combined with serum AFP, AFP-L3, GP73, and DCP detection has good value in the diagnosis of early PHC patients, and can serve as an effective strategy to improve the early diagnosis rate of PHC.

Circulating Non-Coding RNAs as Potential Diagnostic Biomarkers in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is currently the second leading cause of cancer-related deaths worldwide, with high morbidity and mortality. The clinical diagnosis of HCC mainly depends on imaging technology, such as ultrasound and computed tomography, and serum biomarkers, such as alpha-fetoprotein (AFP). However, HCC is still hard to diagnose at an early stage due to the low sensitivity of the above mentioned traditional methods. Typically, HCC is diagnosed at an advanced stage when limited treatment options are available. It is urgent to identify effective biomarkers for the early diagnosis of HCC. Increasing evidence uncovered ncRNAs, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), could be used in HCC diagnosis. The aim of this review is to summarize our understanding of circulating miRNAs, lncRNAs and circRNAs as fluid-based non-invasive biomarkers, and aiming at providing new insights into the diagnosis of HCC.

Liver Imaging Reporting and Data System criteria for the diagnosis of hepatocellular carcinoma in clinical practice: A pictorial minireview

Hepatocellular carcinoma (HCC) is the sixth most common cancer. The main risk factors associated with HCC development include hepatitis B virus, hepatitis C virus, alcohol consumption, aflatoxin B1, and nonalcoholic fatty liver disease. However, hepatocarcinogenesis is a complex multistep process. Various factors lead to hepatocyte malignant transformation and HCC development. Diagnosis and surveillance of HCC can be made with the use of liver ultrasound (US) every 6 mo. However, the sensitivity of this imaging method to detect HCC in a cirrhotic liver is limited, due to the abnormal liver parenchyma. Computed tomography (CT) and magnetic resonance imaging (MRI) are considered to be most useful tools for at-risk patients or patients with inadequate US. Liver biopsy is still used for diagnosis and prognosis of HCC in specific nodules that cannot be definitely characterized as HCC by imaging. Recently the American College of Radiology designed the Liver Imaging Reporting and Data System (LI-RADS), which is a comprehensive system for standardized interpretation of CT and MRI liver examinations that was first proposed in 2011. In 2018, it was integrated into the American Association for the Study of Liver Diseases guidance statement for HCC. LI-RADS is designed to ensure high sensitivity, precise categorization, and high positive predictive value for the diagnosis of HCC and is applied to “high-risk populations” according to specific criteria. Most importantly LI-RADS criteria achieved international collaboration and consensus among liver experts around the world on the best practices for caring for patients with or at risk for HCC.

Clinical application of deep learning and radiomics in hepatic disease imaging: a systematic scoping review

OBJECTIVE

Artificial intelligence (AI) has begun to play a pivotal role in hepatic imaging. This systematic scoping review summarizes the latest progress of AI in evaluating hepatic diseases based on computed tomography (CT) and magnetic resonance (MR) imaging.

METHODS

We searched PubMed and Web of Science for publications, using terms related to deep learning, radiomics, imaging methods (CT or MR), and the liver. Two reviewers independently selected articles and extracted data from each eligible article. The Quality Assessment of Diagnostic Accuracy Studies-AI (QUADAS-AI) tool was used to assess the risk of bias and concerns regarding applicability.

RESULTS

The screening identified 45 high-quality publications from 235 candidates, including 8 on diffuse liver diseases and 37 on focal liver lesions. Nine studies used deep learning and 36 studies used radiomics. All 45 studies were rated as low risk of bias in patient selection and workflow, but 36 (80%) were rated as high risk of bias in the index test because they lacked external validation. In terms of concerns regarding applicability, all 45 studies were rated as low concerns. These studies demonstrated that deep learning and radiomics can evaluate liver fibrosis, cirrhosis, portal hypertension, and a series of complications caused by cirrhosis, predict the prognosis of malignant hepatic tumors, and differentiate focal hepatic lesions.

CONCLUSIONS

The latest studies have shown that deep learning and radiomics based on hepatic CT and MR imaging have potential application value in the diagnosis, treatment evaluation, and prognosis prediction of common liver diseases. The AI methods may become useful tools to support clinical decision-making in the future.

ADVANCES IN KNOWLEDGE

Deep learning and radiomics have shown their potential in the diagnosis, treatment evaluation, and prognosis prediction of a series of common diffuse liver diseases and focal liver lesions.

Artificial Intelligence Algorithm in Classification and Recognition of Primary Hepatic Carcinoma Images under Magnetic Resonance Imaging

This study aimed to discuss the application value of the bias field correction algorithm in magnetic resonance imaging (MRI) images of patients with primary hepatic carcinoma (PHC). In total, 52 patients with PHC were selected as the experimental group and divided into three subgroups: mild (15 cases), moderate (19 cases), and severe (18 cases) according to pathological grading. Another 52 patients with hepatic nodules in the same period were included in the control group. All the patients underwent dynamic contrast-enhanced (DCE) MRI examination, and the image qualities of MRI before and after bias field correction were compared. The DCE-MRI perfusion parameters were measured, including the transport constant Ktrans, reverse rate constant Kep, extravascular extracellular volume fraction (Ve), plasma volume (Vp), microvascular density (MVD), hepatic artery perfusion index (HPI), mean transit time of contrast agent (MTT), time to peak (TTP), blood volume (BV), hepatic arterial perfusion (HAP), full perfusion (FP), and portal venous perfusion (PVP). It was found that the sensitivity (93.63%), specificity (71.62%), positive predictive value (95.63%), negative predictive value (71.62%), and accuracy (90.01%) of MRI examination processed by the bias field correction algorithm were all significantly greater than those before processing (P < 0.05). The Ktrans, Kep, Ve, Vp, and MVD of patients in the experimental group were significantly larger than those of the control group, and severe group> moderate group> mild group (P < 0.05). HPI, MTT, TTP, BV, and HAP of patients in the experimental group were also significantly greater than those of the control group, which was shown as severe group > moderate group > mild group (P < 0.05). FP and PVP of the experimental group were significantly lower than those of the control group, and severe group < moderate group < mild group (P < 0.05). It was suggested that in MRI images of patients with PHC, the bias field correction algorithm could significantly improve the diagnosis rate. Each perfusion parameter was related to the pathological grading, which could be used to evaluate the prognosis of patients.

Cytological Comparison between Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma by Image Analysis Software Using Touch Smear Samples of Surgically Resected Specimens

To investigate useful cytological features for differential diagnosis of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), this study cytologically compared HCC to ICC using image analysis software. Touch smear specimens of surgically resected specimens were obtained from a total of 61 nodules of HCC and 16 of ICC. The results indicated that the major/minor axis ratio of ICC is significantly larger than that of HCC (1.67 ± 0.27 vs. 1.32 ± 0.11, p < 0.0001) in Papanicolaou staining. This result means that the nucleus of HCC is close to round and the nucleus of ICC is close to an oval. This significant difference in the major/minor axis ratio between ICC and HCC was consistently observed by the same analyses using clinical samples of cytology (4 cases of HCC and 13 cases of ICC) such a fine-needle aspiration, brushing and ascites (ICC: 1.45 ± 0.13 vs. HCC: 1.18 ± 0.056, p = 0.004). We also confirmed that nuclear position center-positioned nucleus (p < 0.0001) and granular cytoplasm (p < 0.0001) are typical features of HCC tumor cells compared to ICC tumor cells. The research study found a significant difference in the nuclear morphology of HCC (round shape) and ICC (oval shape) in Papanicolaou-stained cytology specimens. This simple and objective finding will be very useful for the differential cytodiagnosis of HCC and ICC.

The Diagnostic Value of Contrast-Enhanced Ultrasound and Enhanced CT Combined with Tumor Markers AFP and CA199 in Liver Cancer

Background

Early screening and diagnosis are of great significance to the treatment and prognosis of patients with liver cancer. This study aims to explore the application value of contrast-enhanced ultrasound and enhanced CT combined with tumor markers alpha-fetoprotein (AFP) and carbohydrate antigen 199 (CA199) in the diagnosis of liver cancer.

Methods

Liver cancer group (n = 256), benign disease group (n = 110), and control group (n = 50) participated in this study. The liver cancer and benign disease groups were diagnosed pathologically by contrast-enhanced ultrasound and enhanced CT before operation. The electrochemiluminescence method was used to detect the content of AFP and CA199. And the receiver operating characteristic (ROC) curve was drawn.

Results

The detection rate of contrast-enhanced ultrasound is higher than that of enhanced CT. Serum levels of AFP and CA199 in the liver cancer group were significantly higher than those in the benign lesion group and the control group. The ROC curve showed that the sensitivity, accuracy, and negative prediction rate of contrast-enhanced ultrasound and enhanced CT combined with tumor markers AFP and CA199 in the diagnosis of liver cancer were significantly higher than that of a single test.

Conclusion

The combined detection of contrast-enhanced ultrasound and enhanced CT, AFP, and CA199 significantly improved the sensitivity and accuracy of liver cancer diagnosis. It has a significant effect on the early diagnosis of liver cancer and can be used as an important means of early screening.

Gene expression signature as a surrogate marker of microvascular invasion on routine hepatocellular carcinoma biopsies

BACKGROUND & AIMS

Microvascular invasion (MVI), a major risk factor for tumor recurrence after surgery in hepatocellular carcinoma (HCC), is only detectable by microscopic examination of the surgical specimen. We aimed to define a transcriptomic signature associated with MVI in HCC than can be applied to formalin-fixed paraffin-embedded (FFPE) biopsies for use in clinical practice.

METHODS

To identify a gene expression signature related to MVI by using NanoString technology, we selected a set of 200 genes according to the literature and RNA-sequencing data obtained from a cohort of 150 frozen HCC samples previously published. We used 178 FFPE-archived HCC samples, including 109 surgical samples for the training set and 69 paired pre-operative biopsies for the validation set. In 14 cases of the training set, a paired biopsy was available and was also analyzed.

RESULTS

We identified a 6-gene signature (ROS1, UGT2B7, FAS, ANGPTL7, GMNN, MKI67) strongly associated with MVI in the training set of FFPE surgical HCC samples, with 82% accuracy (sensitivity 82%, specificity 81%, AUC 0.82). The NanoString gene expression was highly correlated in 14 paired surgical/biopsy HCC samples (mean R: 0.97). In the validation set of 69 FFPE HCC biopsies, the 6-gene NanoString signature predicted MVI with 74% accuracy (sensitivity 73%, specificity 76%, AUC 0.74). Moreover, on multivariate analysis, the MVI signature was associated with overall survival in both sets (hazard ratio 2.29; 95% CI 1.03-5.07; p = 0.041).

CONCLUSION

We defined a 6-gene signature that can accurately predict MVI in FFPE HCC biopsy samples, which is also associated with overall survival, although its survival impact must be confirmed by extensive study with further clinical data.

LAY SUMMARY

Microvascular invasion, a major risk factor for tumor recurrence after surgery in hepatocellular carcinoma, is only detectable by microscopic examination of a surgical specimen. In this study, we defined a relevant surrogate signature of microvascular invasion in hepatocellular carcinoma that may be applied in clinical practice with routine tumor biopsy and integrated into the therapeutic strategy.

Consensus on the secondary prevention of primary liver cancer

To standardize the effective prevention, surveillance, and diagnosis of primary liver cancer, the Chinese Society of Hepatology, Chinese Medical Association, invited clinical experts and methodologists to develop the Consensus on the Secondary Prevention of Primary Liver Cancer, which was based on the clinical and scientific advances on hepatocellular carcinoma. The purpose is to provide a current basis for the prevention, surveillance, and early diagnosis of primary liver cancer in patients with chronic liver diseases.

Clinical Management of Liver Cancer in India and Other Developing Nations: A Focus on Radiation Based Strategies

Hepatocellular carcinoma (HCC) is a global killer with preponderance in Asian and African countries. It poses a challenge for successful management in less affluent or developing nations like India, with large populations and limited infrastructures. This review aims to assess the available options and future directions for management of HCC applicable to such countries. While summarizing current and emerging clinical strategies for detection, staging and therapy of the disease, it highlights radioisotope- and radioactivity-based strategies as part of an overall program. Using the widely accepted Barcelona Clinic Liver Cancer (BCLC) staging system as a base, it evaluates the applicability of different therapeutic approaches and their synergistic combination(s) in the context of a patient-specific dynamic results-based strategy. It distills the conclusions of multiple HCC management-focused consensus recommendations to provide a picture of clinical strategies, especially radiation-related approaches. Additionally, it discusses the logistical and economic feasibility of these approaches in the context of the limitations of the burdened public health infrastructure in India (and like nations) and highlights possible strategies both at the clinical level and in terms of an administrative health policy on HCC to provide the maximum possible benefit to the widest swathe of the affected population.

SLC41A3 Exhibits as a Carcinoma Biomarker and Promoter in Liver Hepatocellular Carcinoma

Liver Hepatocellular Carcinoma (LIHC) is the fifth widely occurred carcinoma, which is thought to be the second primary contributor of carcinoma-associated death. There are almost 788,000 death tolls worldwide. Solute carrier family 41 member 3 (SLC41A3) is a member of solute carrier family 41, and it is the key point of numerous researches. Our research attempted to explore the links between SLC41A3 and LIHC through public databases. Higher expression of SLC41A3 displayed an intimate association with higher pathological stages and poorer prognosis. GO and KEGG analysis revealed the possible regulatory pathways of SLC41A3. Additionally, we carried out cell functional experiments to determine the expression of SLC41A3 in the cell lines of LIHC, as well as the effects of its silence on cell proliferation, migration, and invasion. Our data showed that SLC41A3 was greatly increased in the cell lines of LIHC. Moreover, silencing SLC41A3 impeded LIHC cell proliferation, migration, and invasion in vitro. Collectively, our study demonstrated that highly expressed SLC41A3 was a probable indication of LIHC occurrence, and SLC41A3 could be regarded as a prospective target in the treatment of LIHC.