Microvascular Invasion in HCC: The Molecular Imaging Perspective

Magnetic resonance imaging-based rim enhancement could effectually predict poor prognosis in hepatocellular carcinoma: a meta-analysis

Recent studies have initially shown that MRI-based rim enhancement associates with poor prognosis in hepatocellular carcinoma (HCC) patients, but their sample sizes are small, leading to a necessary of comprehensive analyses to make a relatively solid statement. Thus, this meta-analysis aimed to summarize the correlation between MRI-based rim enhancement and prognosis in HCC patients. Until March 2023, a literature search was conducted on Web of Science, PubMed, EMBASE, Cochrane, CNKI, Wangfang, and CQVIP databases in order to identify studies that report the correlation between MRI-based rim enhancement and the prognosis of HCC patients. MRI-based rim enhancement and prognostic data were extracted and analyzed. In our study, eight studies containing 1816 HCC patients were analyzed. Generally, the presence of MRI-based rim enhancement was related to shortened disease-free survival (DFS) [hazard ratio (HR): 2.77, 95% confidence interval (CI): 2.11-3.62, P < 0.001], and worse overall survival (OS) (HR: 5.43, 95% CI: 2.14-13.79, P < 0.001). While no other prognostic data could be retrieved. Funnel plots, Begg's test, and Egger's test all indicated that no publication bias existed; and the risk score by Newcastle-Ottawa Scale criteria ranged from 7-9 points, suggesting a generally low risk of bias. Meanwhile, the sensitivity analysis showed that the significant findings did not change by omitting each study. Then, subgroup analyses revealed that no matter stratified by tumor size, treatment option, or sample size, rim enhancement was linked with unsatisfied DFS (all P < 0.05). Conclusively, MRI-based rim enhancement could effectually estimate poor survival in HCC patients, indicating its good prognostic value.

Nanoparticles for Thrombus Diagnosis and Therapy: Emerging Trends in Thrombus-theranostics

Cardiovascular disease is one of the chief factors that cause ischemic stroke, myocardial infarction, and venous thromboembolism. The elements that speed up thrombosis include nutritional consumption, physical activity, and oxidative stress. Even though the precise etiology and pathophysiology remain difficult topics that primarily rely on traditional medicine. The diagnosis and management of thrombosis are being developed using discrete non-invasive and non-surgical approaches. One of the emerging promising approach is ultrasound and photoacoustic imaging. The advancement of nanomedicines offers concentrated therapy and diagnosis, imparting efficacy and fewer side effects which is more significant than conventional medicine. This study addresses the potential of nanomedicines as theranostic agents for the treatment of thrombosis. In this article, we describe the factors that lead to thrombosis and its consequences, as well as summarize the findings of studies on thrombus formation in preclinical and clinical models and also provide insights on nanoparticles for thrombus imaging and therapy.

Preoperatively Identify the Microvascular Invasion of Hepatocellular Carcinoma with the Restricted Spectrum Imaging

RATIONALE AND OBJECTIVES

To noninvasively and preoperatively identify the microvascular invasion (MVI) of hepatocellular carcinoma (HCC) with the restricted spectrum imaging (RSI).

MATERIALS AND METHODS

62 patients were included into this prospective study and underwent the RSI examination with a 3.0-T scanner. Mono-exponential diffusion-weighted imaging-derived apparent diffusion coefficient (ADC) and RSI-derived metrics including f1 (fraction of restricted diffusion), f2 (fraction of hindered diffusion), f3 (fraction of free diffusion), and f1f2 (the multiply of f1 and f2) were calculated. Univariate and multivariate logistic regression were used to select the independent risk factors. Nomogram-based model was constructed with the selected indexes. Receiver operative characteristics analysis and calibration curve were used to evaluate the diagnostic accuracy.

RESULTS

MVI-positive HCC showed significantly higher f1 and lower ADC values (ADC: 1.549 ± 0.228 ×10-3 vs 1.365 ± 0.239 ×10-3 mm2/s, P = .003; f1: 0.1633 ± 0.0341 vs 0.2221 ± 0.0491, P < .001). Tumor size and f1 were selected as independent risk factors for MVI. The nomogram-based model was then constructed with tumor size and f1. Nomogram-based model (area under ROC curve [AUC]= 0.856) yielded the best diagnostic accuracy followed by f1 (AUC=0.842) and ADC (AUC=0.708). The AUC of both the f1 and nomogram model were significantly higher than that of ADC.

CONCLUSION

RSI-derived metrics can be utilized to noninvasively and efficiently identify the MVI of HCC. Considering the importance of MVI as a significant prognostic factor for HCC, the utilization of RSI has the potential to assist in prognostic prediction and clinical management.

Can MRI features predict clinically relevant hepatocellular carcinoma genetic subtypes?

PURPOSE

Recent studies in cancer genomics have revealed core drivers for hepatocellular carcinoma (HCC) pathogenesis. We aim to study whether MRI features can serve as non-invasive markers for the prediction of common genetic subtypes of HCC.

METHODS

Sequencing of 447 cancer-implicated genes was performed on 43 pathology proven HCC from 42 patients, who underwent contrast-enhanced MRI followed by biopsy or resection. MRI features were retrospectively evaluated including tumor size, infiltrative tumor margin, diffusion restriction, arterial phase hyperenhancement, non-peripheral washout, enhancing capsule, peritumoral enhancement, tumor in vein, fat in mass, blood products in mass, cirrhosis and tumor heterogeneity. Fisher's exact test was used to correlate genetic subtypes with imaging features. Prediction performance using correlated MRI features for genetic subtype and inter-reader agreement were assessed.

RESULTS

The two most prevalent genetic mutations were TP53 (13/43, 30%) and CTNNB1 (17/43, 40%). Tumors with TP53 mutation more often demonstrated an infiltrative tumor margin on MRI (p = 0.01); inter-reader agreement was almost perfect (kappa = 0.95). The CTNNB1 mutation was associated with peritumoral enhancement on MRI (p = 0.04), inter-reader agreement was substantial (kappa = 0.74). The MRI feature of an infiltrative tumor margin correlated with the TP53 mutation with accuracy, sensitivity, and specificity of 74.4%, 61.5% and 80.0%, respectively. Peritumoral enhancement correlated with the CTNNB1 mutation with accuracy, sensitivity, and specificity of 69.8%, 47.0% and 84.6%, respectively.

CONCLUSION

An infiltrative tumor margin on MRI correlated with TP53 mutation and peritumoral enhancement correlated with CTNNB1 mutation in HCC. Absence of these MRI features are potential negative predictors of the respective HCC genetic subtypes that have implications for prognosis and treatment response.

18F-FDG /18F-Choline Dual-Tracer PET Behavior and Tumor Differentiation in HepatoCellular Carcinoma. A Systematic Review

Background

Post-operative recurrence remains the strongest prognostic factor of resected hepatocellular carcinoma (HCC), making the accurate selection of patients with curable HCC a crucial issue. PET imaging combining both 18F-FDG and fatty acid synthase (FAS) radiotracers—such as Choline—has shown its interest for the initial staging and therapeutic management of patients with HCC, but its use is still not consensual. Importantly, the very first dual-tracer PET studies suggested 18F-FDG/FAS PET behavior be linked to the degree of differentiation of HCC, a major predictive factor of post-operative recurrence. Although this key molecular imaging concept may impact how dual-tracer PET will be used in early-stage HCC, its level of evidence remains largely unexplored. In this study, we conducted a systematic review of the available evidence-based data to clarify the relevance of dual 18F-FDG/18F-Choline PET in characterizing the degree of differentiation of HCC tumors.

Methods

A systematic search of the PubMed/Medline and Embase databases was performed up to November 2021. A systematic review of the dual-tracer 18F-FDG/18F-Choline PET behavior of histology-proven HCC according to their degree of differentiation was conducted. The overall quality of the included studies was critically assessed based on the STROBE guidelines. Information on study date, design, patient cohort characteristics, grade of differentiation of HCC tumors, and the dual-tracer PET behavior per HCC was independently extracted and summarized.

Results

From 440 records initially available, 6 full-text articles (99 histology-proven HCC) provided dual-tracer 18F-FDG/18F-Choline PET behavior per HCC tumor grade were included in the systematic review. Based on our analysis, 43/99 HCCs were reported to be well-differentiated, and 56/99 HCCs were reported to be less-differentiated tumors. In the well-differentiated subgroup, more than half were exclusively positive for 18F-Choline (51%), whereas 39% were positive for both 18F-FDG and 18F-Choline. In the less-differentiated subgroup, 37% of HCC patients were positive exclusively for FDG, 36% were positive for both 18F-FDG and 18F-Choline, and 25% were positive exclusively for 18F-Choline.

Conclusion

The 18F-FDG/18F-Choline dual-tracer PET behavior of uptake shows high overlap between well- and less differentiated HCC, making the characterization of tumors challenging based on such PET combination alone. Given our growing knowledge of the molecular complexity of HCC, further studies are necessary to refine our understanding of radiotracers’ behavior in this field and improve the usefulness of PET imaging in the clinical decision process of HCC.

Efficacy of Lipid Nanoparticle-Loaded Sorafenib Combined with Hepatic Artery Chemoembolization in the Treatment of Primary Hepatocellular Carcinoma Complicated with Microvascular Invasion

This work was to evaluate the therapeutic effect of lipid nanoparticle-loaded sorafenib combined with transcatheter artery chemoembolization (TACE) in patients with primary hepatocellular carcinoma (HC) complicated with microvascular invasion (MVI). In this work, 102 patients with primary HC combined with MVI after radical resection were divided into 4 groups according to different treatment methods. Experimental group 1 was treated with lipid nanoparticle-loaded sorafenib combined with TACE treatment group; experimental group 2 was treated with lipid nanoparticle-loaded sorafenib treatment group; experimental group 3 was TACE treatment group; control group was postoperative routine nursing group. Sorafenib lipid nanoparticles were prepared. The basic information, operation, MVI degree, tumor recurrence, and survival time of patients in each group were recorded and compared to evaluate the therapeutic effect of combined way. No great difference was found in MVI grade, average age, sex ratio, preoperative tumor markers, tumor size, number of patients with liver cirrhosis, operation time, and intraoperative bleeding among the four groups (P > 0.05). In addition, the tumor free survival time (TFST), overall survival time (OST), and postoperative 1-year and 2-year survival rates of patients in test group 1 were greatly higher than those in single mode treatment group and control group (P < 0.05). In summary, sorafenib nanoparticles combined with TACE can improve the survival status of patients after resection and delay the time of postoperative tumor recurrence.

Tumor in vein (LR-TIV) and liver imaging reporting and data system (LI-RADS) v2018: diagnostic features, pitfalls, prognostic and management implications

Vascular invasion by hepatocellular carcinoma (HCC), also known as tumor in vein (TIV), indicates highly invasive tumor behavior and is also associated with poor outcome. Because a diagnosis of TIV precludes liver transplantation, knowledge of the imaging findings to differentiate between TIV and bland thrombus is key for proper patient management. Prior versions of liver imaging reporting and data system (LI-RADS) included presence of TIV as part of LR-5 criteria. However, even if HCC is the most common liver malignancy associated with TIV, other tumors can have vascular invasion and may occur in cirrhotic patients. For these reasons, in LI-RADS v2017 LR-TIV has been introduced as a new different diagnostic category. The aim of this article is to discuss the diagnostic criteria of LR-TIV according to LI-RADS v2018 and analyze potential pitfalls encountered on daily clinical practice. Indeterminate cases and how to manage them will also be discussed.

Radiomic Features of Multi-ROI and Multi-Phase MRI for the Prediction of Microvascular Invasion in Solitary Hepatocellular Carcinoma

Objectives

To develop and validate an MR radiomics-based nomogram to predict the presence of MVI in patients with solitary HCC and further evaluate the performance of predictors for MVI in subgroups (HCC ≤ 3 cm and > 3 cm).

Materials and Methods

Between May 2015 and October 2020, 201 patients with solitary HCC were analysed. Radiomic features were extracted from precontrast T₁WI, arterial phase, portal venous phase, delayed phase and hepatobiliary phase images in regions of the intratumoral, peritumoral and their combining areas. The mRMR and LASSO algorithms were used to select radiomic features related to MVI. Clinicoradiological factors were selected by using backward stepwise regression with AIC. A nomogram was developed by incorporating the clinicoradiological factors and radiomics signature. In addition, the radiomic features and clinicoradiological factors related to MVI were separately evaluated in the subgroups (HCC ≤ 3 cm and > 3 cm).

Results

Histopathological examinations confirmed MVI in 111 of the 201 patients (55.22%). The radiomics signature showed a favourable discriminatory ability for MVI in the training set (AUC, 0.896) and validation set (AUC, 0.788). The nomogram incorporating peritumoral enhancement, tumour growth type and radiomics signature showed good discrimination in the training (AUC, 0.932) and validation sets (AUC, 0.917) and achieved well-fitted calibration curves. Subgroup analysis showed that tumour growth type was a predictor for MVI in the HCC ≤ 3 cm cohort and peritumoral enhancement in the HCC > 3 cm cohort; radiomic features related to MVI varied between the HCC ≤ 3 cm and HCC > 3 cm cohort. The performance of the radiomics signature improved noticeably in both the HCC ≤ 3 cm (AUC, 0.953) and HCC > 3 cm cohorts (AUC, 0.993) compared to the original training set.

Conclusions

The preoperative nomogram integrating clinicoradiological risk factors and the MR radiomics signature showed favourable predictive efficiency for predicting MVI in patients with solitary HCC. The clinicoradiological factors and radiomic features related to MVI varied between subgroups (HCC ≤ 3 cm and > 3 cm). The performance of radiomics signature for MVI prediction was improved in both the subgroups.

Risk Score Model for Microvascular Invasion in Hepatocellular Carcinoma: The Role of Tumor Burden and Alpha-Fetoprotein

Simple Summary

Microvascular invasion (MVI) is the most consistently reported risk factor for recurrence after curative treatment in hepatocellular carcinoma (HCC), but the preoperative prediction of MVI is still challenging. We retrospectively collected 1153 patients who underwent liver resection for HCC, and our multivariate analysis revealed preoperative total tumor volume (TTV) and alpha-fetoprotein (AFP) to be independent risk factors for MVI. We used both factors to build a risk score model that is easy to calculate and objective, with minimal user bias. The preoperative prediction of MVI can guide the treatment plan of HCC, including surgical planning, criteria for transplantation, and adjuvant or neoadjuvant therapy. Our risk score model is easily and widely applicable with moderate performance, which optimizes clinical practice and helps study design in the future.

Abstract

Microvascular invasion (MVI) is a significant risk factor for the recurrence of hepatocellular carcinoma, but it is a histological feature that needs to be confirmed after hepatectomy or liver transplantation. The preoperative prediction of MVI can optimize the treatment plan of HCC, but an easy and widely applicable model is still lacking. The aim of our study was to predict the risk of MVI using objective preoperative factors. We retrospectively collected 1153 patients who underwent liver resection for HCC, and MVI was found to be associated with significantly poor disease-free survival. The patients were randomly split in a 3:1 ratio into training (n = 864) and validation (n = 289) datasets. The multivariate analysis of the training dataset found preoperative total tumor volume (TTV) and alpha-fetoprotein (AFP) to be independent risk factors for MVI. We built a risk score model with cutoff points of TTV at 30, 60, and 300 cm³ and AFP at 160 and 2000 ng/mL, and the model stratified the risk of MVI into low risk (14.1%), intermediate risk (36.4%), and high risk (60.5%). The validation of the risk score model with the validation dataset showed moderate performance (the concordance statistic: 0.731). The model comprised simple and objective preoperative factors with good applicability, which can help to guide treatment plans for HCC and future study design.

Liver Transplantation in Patients with Hepatocellular Carcinoma beyond the Milan Criteria: A Comprehensive Review

The Milan criteria (MC) were developed more than 20 years ago and are still considered the benchmark for liver transplantation (LT) in patients with hepatocellular carcinoma (HCC). However, the strict application of MC might exclude some patients who may receive a clinical benefit of LT. Several expanded criteria have been proposed. Some of these consider pretransplant morphological and biological variables of the tumor, others consider post-LT variables such as the histology of the tumor, and others combine pre- and post-LT variables. More recently, the HCC response to locoregional treatments before transplantation emerged as a surrogate marker of the biological aggressiveness of the tumor to be used as a better selection criterion for LT in patients beyond the MC at presentation. This essential review aims to present the current data on the pretransplant selection criteria for LT in patients with HCC exceeding the MC at presentation based on morphological and histological characteristics of the tumor and to critically discuss those that have been validated in clinical practice. Moreover, the role of HCC biological markers and the tumor response to downstaging procedures as new tools for selecting patients with a tumor burden outside of the MC for LT is evaluated.

Quantitative assessment of microvascular invasion in hepatocellular carcinoma using preoperative serological and imaging markers

BACKGROUND

The aim of this study was to establish a quantitative equation to predict microvascular invasion (MVI) for patients with resectable hepatocellular carcinoma (HCC).

METHODS

This retrospective study included 219 patients with resected HCC from 2004 to 2015. All had available three pre-operative serological markers (alfa-feto protein (AFP), fucosylated AFP (AFP-L3), and des-gamma-carboxy prothrombin (DCP)), and one imaging marker (tumor to liver ratio of SUVmax (TLR) by ¹⁸F-FDG-PET). A multiple linear regression model for predicting MVI was developed (2004-2009, n = 111) and then validated (2010-2015, n = 108). Further, impact on the obtained model on survival outcomes was assessed.

RESULTS

Using the derivation cohort, following equation was developed; MVI probability (%) = 14.2 × log₁₀DCP + 9.9 × TLR - 22.0. This model resulted in an area under receiver operating characteristic curve (ROC) of 0.806 and 0.751, in the derivation and validation cohort, respectively. Furthermore, MVI probability ≥40% determined by ROC analysis was associated with worse overall survival and recurrence-free survival in the derivation and the validation cohort (all p < 0.05).

CONCLUSION

A quantitative model, using DCP and TLR, was able to preoperatively predict with good performance MVI and long-term outcomes in patients with HCC after liver resection.

Arterial Spin Labeling MRI for Predicting Microvascular Invasion of T1 Staging Renal Clear Cell Carcinoma Preoperatively

BACKGROUND

Microvascular invasion (MVI) is a valuable factor for T1 staging renal clear cell carcinoma (ccRCC) operation strategy decision, which is confirmed histopathologically post-operation. This study aimed to prospectively evaluate the performance of arterial spin labeling (ASL) MRI for predicting MVI of T1 staging ccRCC preoperatively.

METHODS

16 volunteers and 39 consecutive patients were enrolled. MRI examinations consisted of ASL (three post label delays separately) of the kidney, followed by T1 and T2-weighted imaging. Two sessions of ASL were used to evaluate the reproducibility on volunteers. Renal blood flow of renal cortex, medulla, the entire and solid part of the tumor were measured on ASL images. Conventional imaging features were extracted. MVI and WHO/ISUP classification were evaluated histopathologically. A paired t-test was used to compare the renal cortex and medulla between ASL 1 and ASL 2. The reproducibility was assessed using the intraclass correlation. Differences in mean perfusion between the entire and the solid parts of tumors with or without MVI were assessed separately using Student's t test. The diagnostic performance was assessed. Logistic regression analysis was used to indicate the independent prediction index for MVI.

RESULTS

The two sessions of ASL showed no significant difference between the mean cortex values of RBF. The cortical RBF measurements demonstrated good agreement. 12 ccRCCs presented with MVI histopathologically. Mean perfusion of the solid part of tumors with MVI were 536.4 ± 154.8 ml/min/100 g (PLD1), 2912.5 ± 939.3 ml/min/100 g (PLD2), 3280.3 ± 901.2 ml/min/100 g (PLD3). Mean perfusion of the solid part of tumors without MVI were 453.5 ± 87.2 ml/min/100 g (PLD1), 1043.6 ± 695.8 ml/min/100 g (PLD2), 1577.6 ± 1085.8 ml/min/100 g (PLD3). These two groups have significant difference at all the PLDs (p < 0.05). The RBF of PLD1 of the solid part of tumor perfusion showed well diagnostic performance for predicting MVI: sensitivity 75%, specificity 100%, positive predictive value 66.7%, and negative predictive value 95.7%. The maximum diameter of the tumor, ill-defined margin, and the solid part of tumor perfusion were the independent prediction index for MVI.

CONCLUSION

ASL MR imaging has good reproducibility for renal cortex, and good diagnostic performance for predicting MVI for ccRCC.

Evolution of the liver biopsy and its future

Liver biopsies are commonly used to evaluate a wide variety of medical disorders, including neoplasms and post-transplant complications. However, its use is being impacted by improved clinical diagnosis of disorders, and non-invasive methods for evaluating liver tissue and as a result the indications of a liver biopsy have undergone major changes in the last decade. The evolution of highly effective treatments for some of the common indications for liver biopsy in the last decade (e.g., viral hepatitis B and C) has led to a decline in the number of liver biopsies in recent years. At the same time, the emergence of better technologies for histologic evaluation, tissue content analysis and genomics are among the many new and exciting developments in the field that hold great promise for the future and are going to shape the indications for a liver biopsy in the future. Recent advances in slide scanners now allow creation of "digital/virtual" slides that have image of the entire tissue section present in a slide [whole slide imaging (WSI)]. WSI can now be done very rapidly and at very high resolution, allowing its use in routine clinical practice. In addition, a variety of technologies have been developed in recent years that use different light sources and/or microscopes allowing visualization of tissues in a completely different way. One such technique that is applicable to liver specimens combines multiphoton microscopy (MPM) with advanced clearing and fluorescent stains known as Clearing Histology with MultiPhoton Microscopy (CHiMP). Although it has not yet been extensively validated, the technique has the potential to decrease inefficiency, reduce artifacts, and increase data while being readily integrable into clinical workflows. Another technology that can provide rapid and in-depth characterization of thousands of molecules in a tissue sample, including liver tissues, is matrix assisted laser desorption/ionization (MALDI) mass spectrometry. MALDI has already been applied in a clinical research setting with promising diagnostic and prognostic capabilities, as well as being able to elucidate mechanisms of liver diseases that may be targeted for the development of new therapies. The logical next step in huge data sets obtained from such advanced analysis of liver tissues is the application of machine learning (ML) algorithms and application of artificial intelligence (AI), for automated generation of diagnoses and prognoses. This review discusses the evolving role of liver biopsies in clinical practice over the decades, and describes newer technologies that are likely to have a significant impact on how they will be used in the future.

Clinical impact of anatomical resection on long-term outcomes after hepatectomy for primary solitary hepatocellular carcinoma with or without preoperative positron emission tomography positivity

Background

There is little evidence indicating that anatomical resection (AR) is associated with improved survival in patients with solitary hepatocellular carcinoma (HCC) who were preoperatively evaluated by positron emission tomography (PET). The aim of our study was to compare the oncologic outcomes of AR in PET-positive versus PET-negative patients with HCC.

Methods

From January 2007 to September 2015, 259 patients with preoperative PET underwent hepatectomy as the primary treatment for solitary HCC. Patients were divided into four groups according to PET uptake and hepatectomy type [AR or non-anatomical resection (NAR)]: Group 1 (PET-negative and AR, n=62); Group 2 (PET-negative and NAR, n= 46); Group 3 (PET-positive and AR, n=100); Group 4 (PET-positive and NAR, n=51).

Results

PET positivity was associated with higher protein induced by vitamin K antagonist-II (P=0.025), lager tumor size (P=0.05), microvascular invasion (MVI) (P=0.012), and portal vein invasion (P=0.031). In Kaplan-Meier analysis for RFS, Group 1 showed remarkable difference from Group 3 and Group 4 (P=0.045, P=0.023, respectively). In the PET-positive subgroup with HCC under 3 cm, AR was associated with better RFS than NAR (P=0.016).

Conclusions

A combination of AR and PET negativity showed good prognosis in long-term outcomes. Finally, AR can decrease the risk of tumor recurrence in patients with a solitary PET-positive HCC less than 3 cm.

CT Image-Based Texture Analysis to Predict Microvascular Invasion in Primary Hepatocellular Carcinoma

The objective of this study was to determine the clinical value of computed tomography (CT) image-based texture analysis in predicting microvascular invasion of primary hepatocellular carcinoma (HCC). CT images of patients with HCC from May 2017 to May 2019 confirmed by surgery and histopathology were retrospectively analyzed. Image features including tumor margin, tumor capsule, peritumoral enhancement, hypoattenuating halo, intratumoral arteries, and tumor-liver differences were assessed. All patients were divided into microvascular invasion (MVI)-negative group (n = 34) and MVI-positive group (n = 68). Preoperative CT images were further imported into MaZda software, where the regions of interest of the lesions were manually delineated. Texture features of lesions based on pre-contrast, arterial, portal, and equilibrium phase CT images were extracted. Thirty optimal texture parameters were selected from each phase by Fisher's coefficient (Fisher), classification error probability combined with average correlation coefficient (POE+ACC), and mutual information (MI). Finally, receiver operating characteristic curve analysis was performed. The results showed that the Edmonson-Steiner grades, tumor size, tumor margin, and intratumoral artery characteristics were significantly different between the two groups (P = 0.012, < 0.001, < 0.001, = 0.003, respectively). There were 58 parameters with significant differences between the MVI-negative and MVI-positive groups (P < 0.001 for all). Among them, 12, 14, 17, and 15 parameters were derived from the pre-contrast phase, arterial phase, portal phase, and equilibrium phase respectively. According to the ROC analysis, optimal texture parameters based on the pre-contrast, arterial, portal, and equilibrium phases were 135dr_GLevNonU (AUC, 0.766; the cutoff value, 1055.00), Vertl_RLNonUni (AUC, 0.764; the cutoff value, 5974.38), 45dgr_GLevNonU (AUC, 0.762; the cutoff value, 924.34), and Vertl_RLNonUni (AUC, 0.754; the cutoff value, 4868.80), respectively. Texture analysis of preoperative CT images may be used as a non-invasive method to predict microvascular invasion in patients with primary hepatocellular carcinomas, and further to guide the treatment and evaluate prognosis. The most valuable parameters were derived from the gray-level run-length matrix.

When to call it off: defining transplant candidacy limits in liver donor liver transplantation for hepatocellular carcinoma

Background

Living donor liver transplantation (LDLT) is an acceptable treatment option for hepatocellular carcinoma (HCC). Traditional transplant criteria aim at best utilization of donor organs with low risk of post transplant recurrence. In LDLT, long term recurrence free survival (RFS) of 50% is considered acceptable. The objective of the current study was to determine preoperative factors associated with high recurrence rates in LDLT.

Methods

Between April 2012 and December 2019, 898 LDLTs were performed at our center. Out of these, 242 were confirmed to have HCC on explant histopathology. We looked at preoperative factors associated with ≤ 50%RFS at 4 years. For survival analysis, Kaplan Meier curves were used and Cox regression analysis was used to identify independent predictors of recurrence.

Results

Median AFP was 14.4(0.7–11,326.7) ng/ml. Median tumor size was 2.8(range = 0.1–11) cm and tumor number was 2(range = 1–15). On multivariate analysis, AFP > 600 ng/ml [HR:6, CI: 1.9–18.4, P = 0.002] and microvascular invasion (MVI) [HR:5.8, CI: 2.5–13.4, P <  0.001] were independent predictors of 4 year RFS ≤ 50%. When AFP was > 600 ng/ml, MVI was seen in 88.9% tumors with poor grade and 75% of tumors outside University of California San Francisco criteria. Estimated 4 year RFS was 78% for the entire cohort. When AFP was < 600 ng/ml, 4 year RFS for well-moderate and poor grade tumors was 88 and 73%. With AFP > 600 ng/ml, RFS was 53% and 0 with well-moderate and poor grade tumors respectively (P <  0.001).

Conclusion

Patients with AFP < 600 ng/ml have acceptable outcomes after LDLT. In patients with AFP > 600 ng/ml, a preoperative biopsy to rule out poor differentiation should be considered for patient selection.

Individualized Ablation of Hepatocellular Carcinoma: Tailored Approaches across the Phenotype Spectrum

Ablation is now recommended by international guidelines for the definitive treatment of hepatocellular carcinoma (HCC). Extensive clinical studies have demonstrated outcomes comparable to surgical resection with shorter hospital stays, decreased costs, and improved quality of life. Successful ablation requires complete treatment of both tumor and margin while preserving critical adjacent structures. HCC exhibits highly variable presentations in both anatomic involvement and biology which have significant implications on choice of ablative therapy. There are now abundant ablation modalities and adjunctive techniques which can be used to individualize ablation and maximize curative results. This article provides a patient-centered summary of approaches to HCC ablation in the context of patient performance, hepatic reserve, tumor phenotype and biology, intra- and extrahepatic anatomy, and ablation technology.

A Nomogram Predicting Microvascular Invasion Risk in BCLC 0/A Hepatocellular Carcinoma after Curative Resection

Background

Numerous studies have shown that hepatocellular carcinoma (HCC) without microvascular invasion (MVI) may have better outcomes. This study established a preoperative MVI risk nomogram mainly incorporating three related risk factors of MVI in BCLC 0/A HCC after surgery.

Methods

Independent predictors for the risk of MVI were investigated, and an MVI risk nomogram was established based on 60 patients in the training group who underwent curative hepatectomy for BCLC 0/A HCC and validated using a dataset in the validation group.

Results

Univariate analysis in the training group showed that hepatitis viral B (HBV) DNA (P=0.034), tumor size (P<0.001), CT value in the venous phase (P=0.039), CT value in the delayed phase (P=0.017), peritumoral enhancement (P=0.013), visible small blood vessels in the arterial phase (P=0.002), and distance from the tumor to the inferior vena cava (IVC) (DTI, P=0.004) were risk factors significantly associated with the presence of MVI. According to multivariate analysis, the independent predictive factors of MVI, including tumor size (P=0.002), CT value in the delayed phase (P=0.018), and peritumoral enhancement (P=0.057), were incorporated in the corresponding nomogram. The nomogram displayed an unadjusted C-index of 0.851 and a bootstrap-corrected C-index of 0.832. Calibration curves also showed good agreement on the presence of MVI. ROC curve analyses showed that the nomogram had a large AUC (0.851).

Conclusions

The proposed nomogram consisting of tumor size, CT value in the delayed phase, and peritumoral enhancement was associated with MVI risk in BCLC 0/A HCC following curative hepatectomy.

Applications of nanoparticles in biomedical imaging

An urgent need for early detection and diagnosis of diseases continuously pushes the advancements of imaging modalities and contrast agents. Current challenges remain for fast and detailed imaging of tissue microstructures and lesion characterization that could be achieved via development of nontoxic contrast agents with longer circulation time. Nanoparticle technology offers this possibility. Here, we review nanoparticle-based contrast agents employed in most common biomedical imaging modalities, including fluorescence imaging, MRI, CT, US, PET and SPECT, addressing their structure related features, advantages and limitations. Furthermore, their applications in each imaging modality are also reviewed using commonly studied examples. Future research will investigate multifunctional nanoplatforms to address safety, efficacy and theranostic capabilities. Nanoparticles as imaging contrast agents have promise to greatly benefit clinical practice.