Preoperative prediction of microvascular invasion of hepatocellular carcinoma using 18F-FDG PET/CT: a multicenter retrospective cohort study

Prognostic and diagnostic value of [18F]FDG, 11C-acetate, and [68Ga]Ga-FAPI-04 PET/CT for hepatocellular carcinoma

OBJECTIVES

To assess the prognostic value of Fluorine 18-labeled fluorodeoxyglucose [18F]FDG, gallium 68-labeled fibroblast-activation protein inhibitor-04 [68Ga]Ga-FAPI-04, 11C-acetate in hepatocellular carcinoma (HCC) and evaluate the potential usefulness and advantages of different combinations for accurate diagnosis.

MATERIALS AND METHODS

Thirty-six patients with suspected hepatic masses were prospectively enrolled from May 2021 to September 2022 and underwent [18F]FDG, [68Ga]Ga-FAPI-04, and 11C-acetate PET/CT scans before surgery. PET/CT results and histopathologic examinations were independently interpreted by two radiologists and pathologists, respectively. Kaplan-Meier overall survival curves were calculated and the sensitivity among [18F]FDG, 11C-acetate, [68Ga]Ga-FAPI-04, and different combinations were compared.

RESULTS

Of the 36 included patients (mean age, 59 years ± 10 (standard deviation)), 29 were diagnosed with HCC, four with non-HCC malignant tumors, and three with benign tumors. Patients with HCC lesions negative for 11C-acetate or [68Ga]Ga-FAPI-04 exhibited poorer overall survival. Out of 36 patients, 44 HCC lesions were detected. The dual-tracer [68Ga]Ga-FAPI-04/11C-acetate exhibited the highest sensitivity (39 of 44 lesions (88.6%)) among all schemes. HCC lesions with higher histological grade and microvascular invasion (MVI) showed higher maximum standardized uptake value (SUVmax) and tumor-to-background ratio (TBR) of [18F]FDG, but no evidence of significant differences was found in [68Ga]Ga-FAPI-04 and 11C-acetate PET/CT. Higher expression of fibroblast activation protein (FAP) showed higher uptake of [68Ga]Ga-FAPI-04 and [18F]FDG.

CONCLUSION

[68Ga]Ga-FAPI-04 and 11C-acetate PET/CT exhibited good predictive value for HCC patients, with their combination showing the highest sensitivity for HCC detection, suggesting potential for improved diagnostic protocols.

KEY POINTS

Question What are the prognostic and diagnostic values of PET/CT tracers, including [18F]FDG, [68Ga]FAPI-04, and 11C-acetate? Findings Hepatocellular carcinoma, with differing findings across [18F]FDG, [68Ga]GaFAPI-04, and 11C-acetate PET/CT, showed varied prognoses; [68Ga]GaFAPI-04 and 11C-acetate combined offered the highest detection sensitivity. Clinical relevance Evaluating the prognostic value and diagnostic efficacy of different tracer combinations in patients with hepatocellular carcinoma helps to guide the optimal selection of tracers in clinical practice.

A Machine Learning-Based Clustering Using Radiomics of F-18 Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography for the Prediction of Prognosis in Patients with Intrahepatic Cholangiocarcinoma

BACKGROUND

Intrahepatic cholangiocarcinoma (IHCC) is highly aggressive primary hepatic malignancy with an increasing incidence.

OBJECTIVE

This study aimed to develop machine learning-based radiomic clustering using F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for predicting recurrence-free survival (RFS) and overall survival (OS) in IHCC.

METHODS

We retrospectively reviewed pretreatment F-18 FDG PET/CT scans of 60 IHCC patients who underwent surgery without neoadjuvant treatment between January 2008 and July 2020. Radiomic features such as first order, shape, and gray level were extracted from the scans of 52 patients and analyzed using unsupervised hierarchical clustering.

RESULTS

Of the 60 patients, 36 experienced recurrence and 31 died during follow-up. Eight patients with a negative FDG uptake were classified as Group 0. The unsupervised hierarchical clustering analysis divided the total cohort into three clusters (Group 1: n = 27; Group 2: n = 23; Group 3: n = 2). The Kaplan-Meier curves showed significant differences in RFS and OS among the clusters (p < 0.0001). Multivariate analyses showed that the PET radiomics grouping was an independent prognostic factor for RFS (hazard ratio (HR) = 3.03, p = 0.001) and OS (HR = 2.39, p = 0.030). Oxidative phosphorylation was significantly activated in Group 1, and the KRAS, P53, and WNT β-catenin pathways were enriched in Group 2.

CONCLUSIONS

This study demonstrated that machine learning-based PET radiomics clustering can preoperatively predict prognosis and provide valuable information complementing the genomic profiling of IHCC.

[68Ga]Ga-RAYZ-8009: A Glypican-3-Targeted Diagnostic Radiopharmaceutical for Hepatocellular Carcinoma Molecular Imaging-A First-in-Human Case Series

To date, the imaging and diagnosis of hepatocellular carcinoma (HCC) rely on CT/MRI, which have well-known limitations. Glypican-3 (GPC3) is a cell surface receptor highly expressed by HCC but not by normal or cirrhotic liver tissue. Here we report initial clinical results of GPC3-targeted PET imaging with [68Ga]Ga-DOTA-RYZ-GPC3 (RAYZ-8009), a peptide-based GPC3 ligand in patients with known or suspected HCC. Methods: [68Ga]Ga-RAYZ-8009 was obtained after labeling the peptide precursor with 68Ga from a 68Ge/68Ga generator and heating at 90°C for 10 min followed by sterile filtration. After administration of [68Ga]Ga-RAYZ-8009, a dynamic or static PET/CT scan was acquired between 45 min and 4 h after administration. Radiotracer uptake was measured by SUVs for the following tissues: suspected or actual HCC or hepatoblastoma lesions, non-tumor-bearing liver, renal cortex, blood pool in the left ventricle, and gastric fundus. Additionally, tumor-to-healthy-liver ratios (TLRs) were calculated. Results: Twenty-four patients (5 patients in the dynamic protocol; 19 patients in the static protocol) were scanned. No adverse events occurred. Two patients had no lesion detected and did not have HCC during follow-up. In total, 50 lesions were detected and analyzed. The mean SUVmax of these lesions was 19.6 (range, 2.7-95.3), and the mean SUVmean was 10.1 (range, 1.0-49.2) at approximately 60 min after administration. Uptake in non-tumor-bearing liver and blood pool rapidly decreased over time and became negligible 45 min after administration (mean SUVmean, <1.6), with a continuous decline to 4 h after administration (mean SUVmean, 1.0). The opposite was observed for HCC lesions, for which SUVs and TLRs continuously increased for up to 4 h after administration. In individual lesion analysis, TLR was the highest between 60 and 120 min after administration. Uptake in the gastric fundus gradually increased for up to 45 min (to an SUVmax of 31.3) and decreased gradually afterward. Conclusion: [68Ga]Ga-RAYZ-8009 is safe and allows for high-contrast imaging of GPC3-positive HCC, with rapid clearance from most normal organs. Thereby, [68Ga]Ga-RAYZ-8009 is promising for HCC diagnosis and staging. Further research is warranted.

Multi-transcriptomics analysis of microvascular invasion-related malignant cells and development of a machine learning-based prognostic model in hepatocellular carcinoma

Background

Microvascular invasion (MVI) stands as a pivotal pathological hallmark of hepatocellular carcinoma (HCC), closely linked to unfavorable prognosis, early recurrence, and metastatic progression. However, the precise mechanistic underpinnings governing its onset and advancement remain elusive.

Methods

In this research, we downloaded bulk RNA-seq data from the TCGA and HCCDB repositories, single-cell RNA-seq data from the GEO database, and spatial transcriptomics data from the CNCB database. Leveraging the Scissor algorithm, we delineated prognosis-related cell subpopulations and discerned a distinct MVI-related malignant cell subtype. A comprehensive exploration of these malignant cell subpopulations was undertaken through pseudotime analysis and cell-cell communication scrutiny. Furthermore, we engineered a prognostic model grounded in MVI-related genes, employing 101 algorithm combinations integrated by 10 machine-learning algorithms on the TCGA training set. Rigorous evaluation ensued on internal testing sets and external validation sets, employing C-index, calibration curves, and decision curve analysis (DCA).

Results

Pseudotime analysis indicated that malignant cells, showing a positive correlation with MVI, were primarily concentrated in the early to middle stages of differentiation, correlating with an unfavorable prognosis. Importantly, these cells showed significant enrichment in the MYC pathway and were involved in extensive interactions with diverse cell types via the MIF signaling pathway. The association of malignant cells with the MVI phenotype was corroborated through validation in spatial transcriptomics data. The prognostic model we devised demonstrated exceptional sensitivity and specificity, surpassing the performance of most previously published models. Calibration curves and DCA underscored the clinical utility of this model.

Conclusions

Through integrated multi-transcriptomics analysis, we delineated MVI-related malignant cells and elucidated their biological functions. This study provided novel insights for managing HCC, with the constructed prognostic model offering valuable support for clinical decision-making.

Preoperative prediction of microsatellite instability status: development and validation of a pan-cancer PET/CT-based radiomics model

OBJECTIVE

The purpose of this study is to verify the feasibility of preoperative prediction of patients' microsatellite instability status by applying a PET/CT-based radiation model.

METHODS

This retrospective study ultimately included 142 patients. Three prediction models have been developed. The predictive performance of all models was evaluated by the receiver operating characteristic curve and area under the curve values. The PET/CT radiological histology score (Radscore) was calculated to evaluate the microsatellite instability status, and the corresponding nomogram was established. The correlation between clinical factors and radiological characteristics was analyzed to verify the value of radiological characteristics in predicting microsatellite instability status.

RESULTS

Twelve features were retained to establish a comprehensive prediction model of radiological and clinical features. M phase of the tumor has been proven to be an independent predictor of microsatellite instability status. The receiver operating characteristic results showed that the area under the curve values of the training set and the validation set of the radiomics model were 0.82 and 0.75, respectively. The sensitivity, specificity, positive predictive value and negative predictive value of the training set were 0.72, 0.78, 0.83 and 0.66, respectively. The sensitivity, specificity, positive predictive value and negative predictive value of the validation set were 1.00, 0.50, 0.76 and 1.00, respectively. The risk of patients with microsatellite instability was calculated by Radscore and nomograph, and the cutoff value was -0.4385. The validity of the results was confirmed by the decision and calibration curves.

CONCLUSION

Radiological models based on PET/CT can provide clinical and practical noninvasive prediction of microsatellite instability status of several different cancer types, reducing or avoiding unnecessary biopsy to a certain extent.

The potential of 18F-FDG PET/CT metabolic parameter-based nomogram in predicting the microvascular invasion of hepatocellular carcinoma before liver transplantation

PURPOSE

Microvascular invasion (MVI) is a critical factor in predicting the recurrence and prognosis of hepatocellular carcinoma (HCC) after liver transplantation (LT). However, there is a lack of reliable preoperative predictors for MVI. The purpose of this study is to evaluate the potential of an 18F-FDG PET/CT-based nomogram in predicting MVI before LT for HCC.

METHODS

83 HCC patients who obtained 18F-FDG PET/CT before LT were included in this retrospective research. To determine the parameters connected to MVI and to create a nomogram for MVI prediction, respectively, Logistic and Cox regression models were applied. Analyses of the calibration curve and receiver operating characteristic (ROC) curves were used to assess the model's capability to differentiate between clinical factors and metabolic data from PET/CT images.

RESULTS

Among the 83 patients analyzed, 41% were diagnosed with histologic MVI. Multivariate logistic regression analysis revealed that Child-Pugh stage, alpha-fetoprotein, number of tumors, CT Dmax, and Tumor-to-normal liver uptake ratio (TLR) were significant predictors of MVI. A nomogram was constructed using these predictors, which demonstrated strong calibration with a close agreement between predicted and actual MVI probabilities. The nomogram also showed excellent differentiation with an AUC of 0.965 (95% CI 0.925-1.000).

CONCLUSION

The nomogram based on 18F-FDG PET/CT metabolic characteristics is a reliable preoperative imaging biomarker for predicting MVI in HCC patients before undergoing LT. It has demonstrated excellent efficacy and high clinical applicability.

Research progresses of imaging studies on preoperative prediction of microvascular invasion of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the predominant form of primary liver cancer, accounting for approximately 90% of liver cancer cases. It currently ranks as the fifth most prevalent cancer worldwide and represents the third leading cause of cancer-related mortality. As a malignant disease with surgical resection and ablative therapy being the sole curative options available, it is disheartening that most HCC patients who undergo liver resection experience relapse within five years. Microvascular invasion (MVI), defined as the presence of micrometastatic HCC emboli within liver vessels, serves as an important histopathological feature and indicative factor for both disease-free survival and overall survival in HCC patients. Therefore, achieving accurate preoperative noninvasive prediction of MVI holds vital significance in selecting appropriate clinical treatments and improving patient prognosis. Currently, there are no universally recognized criteria for preoperative diagnosis of MVI in clinical practice. Consequently, extensive research efforts have been directed towards preoperative imaging prediction of MVI to address this problem and the relative research progresses were reviewed in this article to summarize its current limitations and future research prospects.

Head-to-head comparison of 18F-FAPI and 18F-FDG PET/CT in staging and therapeutic management of hepatocellular carcinoma

BACKGROUND

Fluorine 18 (18F) fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) has limitations in staging hepatocellular carcinoma (HCC). The recently introduced 18F-labeled fibroblast-activation protein inhibitor (FAPI) has shown promising prospects in detection of HCC lesions. This study aimed to investigate the initial staging and restaging performance of 18F-FAPI PET/CT compared to 18F-FDG PET/CT in HCC.

METHODS

This prospective study enrolled histologically confirmed HCC patients from March 2021 to September 2022. All patients were examined with 18F-FDG PET/CT and 18F-FAPI PET/CT within 1 week. The maximum standard uptake value (SUVmax), tumor-to-background ratio (TBR), and diagnostic accuracy were compared between the two modalities.

RESULTS

A total of 67 patients (57 men; median age, 57 [range, 32-83] years old) were included. 18F-FAPI PET showed higher SUVmax and TBR values than 18F-FDG PET in the intrahepatic lesions (SUVmax: 6.7 vs. 4.3, P < 0.0001; TBR: 3.9 vs. 1.7, P < 0.0001). In diagnostic performance, 18F-FAPI PET/CT had higher detection rate than 18F-FDG PET/CT in intrahepatic lesions [92.2% (238/258) vs 41.1% (106/258), P < 0.0001] and lymph node metastases [97.9% (126/129) vs 89.1% (115/129), P = 0.01], comparable in distant metastases [63.6% (42/66) vs 69.7% (46/66), P > 0.05]. 18F-FAPI PET/CT detected primary tumors in 16 patients with negative 18F-FDG, upgraded T-stages in 12 patients and identified 4 true positive findings for local recurrence than 18F-FDG PET, leading to planning therapy changes in 47.8% (32/67) of patients.

CONCLUSIONS

18F-FAPI PET/CT identified more primary lesions, lymph node metastases than 18F-FDG PET/CT in HCC, which is helpful to improve the clinical management of HCC patients.

TRIAL REGISTRATION

Clinical Trials, NCT05485792 . Registered 1 August 2022, Retrospectively registered.

Combined early dynamic 18F-FDG PET/CT and conventional whole-body 18F-FDG PET/CT in hepatocellular carcinoma

OBJECTIVE

To investigate the diagnostic value of early dynamic 18F-FDG PET/CT(ED 18F-FDG PET/CT) combined with conventional whole-body 18F-FDG PET/CT(WB 18F-FDG PET/CT) in hepatocellular carcinoma (HCC), as well as the difference of early dynamic blood flow parameters and maximum standardized uptake value (SUVmax) in HCC patients with/without liver cirrhosis or microvascular invasion (MVI).

METHODS

Twenty-two consecutive patients (mean age 57.8 years) with 28 established HCC lesions (mean size 4.5 cm) underwent a blood flow study with an 18F-FDG dynamic scan divided into 24 sequences of 5 s each and a standard PET/CT scan. On the ED PET/CT study, an experienced PET/CT physician obtained volumes of interest (VOIs) where three blood flow estimates (time to peak [TTP], blood flow [BF], and hepatic perfusion index [HPI]) were calculated. On the WB PET/CT study, a VOI was placed on the fused scan for each HCC and maximum standardized uptake value (SUVmax) was obtained. Comparison of blood flow estimates, SUVmax, and tumor/background ratio (TNR) was performed among HCCs with and without angioinvasion, as well as HCCs in cirrhotic and non-cirrhotic liver.

RESULTS

Compared with WB 18F-FDG PET/CT alone, ED combined with WB 18F-FDG PET/CT can significantly increase the detection rate of moderately differentiated and poorly differentiated HCCs (both P < 0.05). HPI was higher in HCCs in patients with liver cirrhosis than those without liver cirrhosis (P = 0.044). There was no significant difference in TTP, BF, SUVmax, or TNR between HCCs in patients with liver cirrhosis and those without liver cirrhosis. There was no significant difference in blood flow estimates or SUVmax in background liver parenchyma between patients with and those without cirrhosis. TTP was shorter in HCCs with MVI than without MVI (P = 0.046). There was no significant difference in BF, HPI, SUVmax, or TNR between HCCs with MVI and without MVI. There was no significant difference in blood flow estimates or SUVmax in background liver parenchyma between patients with and those without MVI.

CONCLUSION

ED combined with WB 18F-FDG PET/CT can significantly increase the detection rate of moderately differentiated and poorly differentiated HCCs. HPI was significantly higher in HCCs in patients with liver cirrhosis than those without liver cirrhosis. TTP was significantly shorter in HCCs with MVI than without MVI.

Analysis of Sonazoid contrast-enhanced ultrasound for predicting the risk of microvascular invasion in hepatocellular carcinoma: a prospective multicenter study

OBJECTIVES

The aim of this study was to evaluate the potential of Sonazoid contrast-enhanced ultrasound (SNZ-CEUS) as an imaging biomarker for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

METHODS

From August 2020 to March 2021, we conducted a prospective multicenter study on the clinical application of Sonazoid in liver tumor; a MVI prediction model was developed and validated by integrating clinical and imaging variables. Multivariate logistic regression analysis was used to establish the MVI prediction model; three models were developed: a clinical model, a SNZ-CEUS model, and a combined model and conduct external validation. We conducted subgroup analysis to investigate the performance of the SNZ-CEUS model in non-invasive prediction of MVI.

RESULTS

Overall, 211 patients were evaluated. All patients were split into derivation (n = 170) and external validation (n = 41) cohorts. Patients who had MVI accounted for 89 of 211 (42.2%) patients. Multivariate analysis revealed that tumor size (> 49.2 mm), pathology differentiation, arterial phase heterogeneous enhancement pattern, non-single nodular gross morphology, washout time (< 90 s), and gray value ratio (≤ 0.50) were significantly associated with MVI. Combining these factors, the area under the receiver operating characteristic (AUROC) of the combined model in the derivation and external validation cohorts was 0.859 (95% confidence interval (CI): 0.803-0.914) and 0.812 (95% CI: 0.691-0.915), respectively. In subgroup analysis, the AUROC of the SNZ-CEUS model in diameter  ≤ 30 mm and ˃ 30 mm cohorts were 0.819 (95% CI: 0.698-0.941) and 0.747 (95% CI: 0.670-0.824).

CONCLUSIONS

Our model predicted the risk of MVI in HCC patients with high accuracy preoperatively.

CLINICAL RELEVANCE STATEMENT

Sonazoid, a novel second-generation ultrasound contrast agent, can accumulate in the endothelial network and form a unique Kupffer phase in liver imaging. The preoperative non-invasive prediction model based on Sonazoid for MVI is helpful for clinicians to make individualized treatment decisions.

KEY POINTS

• This is the first prospective multicenter study to analyze the possibility of SNZ-CEUS preoperatively predicting MVI. • The model established by combining SNZ-CEUS image features and clinical features has high predictive performance in both derivation cohort and external validation cohort. • The findings can help clinicians predict MVI in HCC patients before surgery and provide a basis for optimizing surgical management and monitoring strategies for HCC patients.

Predicting Outcome after Percutaneous Ablation for Early-Stage Hepatocellular Carcinoma Using Various Imaging Modalities

Percutaneous ablation is a low-invasive, repeatable, and curative local treatment that is now recommended for early-stage hepatocellular carcinoma (HCC) that is not suitable for surgical resection. Poorly differentiated HCC has high-grade malignancy potential. Microvascular invasion is frequently seen, even in tumors smaller than 3 cm in diameter, and prognosis is poor after percutaneous ablation. Biopsy has a high risk of complications such as bleeding and dissemination; therefore, it has limitations in determining HCC tumor malignancy prior to treatment. Advances in diagnostic imaging have enabled non-invasive diagnosis of tumor malignancy. We describe the usefulness of ultrasonography, computed tomography, magnetic resonance imaging, and 18F-fluorodeoxyglucose positron emission tomography for predicting outcome after percutaneous ablation for HCC.

Achievement of Complete Response and Drug-Free Status by Atezolizumab plus Bevacizumab Combined with or without Curative Conversion in Patients with Transarterial Chemoembolization-Unsuitable, Intermediate-Stage Hepatocellular Carcinoma: A Multicenter Proof-Of-Concept Study

Introduction

Atezolizumab plus bevacizumab therapy is extremely effective in the treatment of intermediate-stage hepatocellular carcinoma (HCC), with a response rate of 44%, as reported in the IMbrave150 trial. When tumor shrinkage is obtained, achieving complete response (CR) is possible in many cases using curative conversion with resection, ablation, or superselective transarterial chemoembolization (TACE) with curative intent. This concept, i.e., curative conversion by combining systemic therapy and locoregional therapy, has not been reported before. This multicenter proof-of-concept study was conducted to show the value of curative conversion in immunotherapy-treated intermediate-stage HCC meeting TACE-unsuitable criteria.

Methods

This study included 110 consecutive Child-Pugh A patients who received atezolizumab plus bevacizumab as first-line treatment for unresectable and TACE-unsuitable intermediate-stage HCC at seven centers in Japan. CR rate, drug-free rate, time to CR, change in liver function, efficacy in positron emission tomography (PET)-positive HCC, progression-free survival (PFS), and overall survival (OS) were assessed in patients who achieved CR using resection, ablation, superselective TACE with curative intent following atezolizumab plus bevacizumab or atezolizumab plus bevacizumab alone.

Results

Clinical or pathological CR was achieved in 38 patients (35%) (median observation period: 21.2 months). The modalities of curative conversion in 35 patients were as follows: resection, 7; ablation, 13; and superselective TACE, 15. Three patients achieved clinical CR with atezolizumab plus bevacizumab therapy alone. Among the 38 CR patients, 25 achieved drug-free status. PFS was not reached, and 3 patients experienced recurrence after reaching CR. Regarding OS, there were no deaths in any of the CR patients. The albumin-bilirubin score did not deteriorate after locoregional therapy or resection. Of seven PET-positive patients who achieved CR with atezolizumab plus bevacizumab followed by curative conversion, five achieved drug-free status.

Conclusion

The achievement of CR rate by curative conversion in patients treated with atezolizumab plus bevacizumab as the preceding therapy for unresectable and TACE-unsuitable intermediate-stage HCC was 35%. Overall, 23% of patients achieved drug-free status and no recurrence was observed from this patient subgroup with CR and drug-free status. Thus, achieving CR and/or drug-free status should be a therapeutic goal for patients with intermediate-stage HCC without vascular invasion or extrahepatic spread.

Preoperative prediction of lymphovascular invasion of colorectal cancer by radiomics based on 18F-FDG PET-CT and clinical factors

Purpose

The purpose of this study was to investigate the value of a clinical radiomics model based on Positron emission tomography-computed tomography (PET-CT) radiomics features combined with clinical predictors of Lymphovascular invasion (LVI) in predicting preoperative LVI in patients with colorectal cancer (CRC).

Methods

A total of 95 CRC patients who underwent preoperative 18F-fluorodeoxyglucose (FDG) PET-CT examination were retrospectively enrolled. Univariate and multivariate logistic regression analyses were used to analyse clinical factors and PET metabolic data in the LVI-positive and LVI-negative groups to identify independent predictors of LVI. We constructed four prediction models based on radiomics features and clinical data to predict LVI status. The predictive efficacy of different models was evaluated according to the receiver operating characteristic curve. Then, the nomogram of the best model was constructed, and its performance was evaluated using calibration and clinical decision curves.

Results

Mean standardized uptake value (SUVmean), maximum tumour diameter and lymph node metastasis were independent predictors of LVI in CRC patients (P < 0.05). The clinical radiomics model obtained the best prediction performance, with an Area Under Curve (AUC) of 0.922 (95%CI 0.820-0.977) and 0.918 (95%CI 0.782-0.982) in the training and validation cohorts, respectively. A nomogram based on the clinical radiomics model was constructed, and the calibration curve fitted well (P > 0.05).

Conclusion

The clinical radiomics prediction model constructed in this study has high value in the preoperative individualized prediction of LVI in CRC patients.

A Nomogram Based on Contrast-Enhanced Ultrasound to Predict the Microvascular Invasion in Hepatocellular Carcinoma

OBJECTIVE

The aim of this study was to establish and validate a contrast-enhanced ultrasound (CEUS) nomogram for pre-operative microvascular invasion (MVI) prediction in hepatocellular carcinoma (HCC), and compare it with the nomogram based on gadopentetate dimeglumine-enhanced magnetic resonance imaging (Gd-MRI).

METHODS

A total of 251 patients with a single HCC were enrolled in this prospective study, including 176 patients in the training cohort and 75 patients in the validation cohort. Contrast-enhanced ultrasound (CEUS) with Sonazoid and Gd-MRI was performed pre-operatively. Post-operative histopathology was the gold standard for MVI. Univariate and multivariate logistic regression was performed to determine independent risk factors for MVI. Nomograms based on CEUS and Gd-MRI were established, and their discrimination, calibration and decision curve analysis were evaluated and compared.

RESULTS

Multivariate logistic regression revealed that arterial circular enhancement, non-enhancing area and thick ring-like enhancement in the post-vascular phase were independent risk factors for MVI. The areas under the receiver operating characteristic curve of the nomogram were 0.841 (0.779-0.892) and 0.914 (0.827-0.966) in the training and validation cohorts, with no significant difference compared with the Gd-MRI nomogram (p = 0.294, 0.321). The C-indexes were 0.821 and 0.870 in the training and validation cohorts. Decision curve analysis revealed that the CEUS nomogram had better clinical applicability than the Gd-MRI nomogram when the threshold probability was between 0.35 and 0.95.

CONCLUSION

The CEUS-based nomogram was available for predicting MVI in HCC, and its predictive performance was not inferior to that of Gd-MRI.

Raman Scattering-Based Optical Sensing Of Chronic Liver Diseases

Chronic liver diseases (CLDs) are a major public health problem. Despite the progress achieved in fighting against viral hepatitis, the emergence of non-alcoholic fatty liver disease might pose a serious challenge to the public's health in the coming decades. Medical management of CLDs represents a substantial burden on the public health infrastructures. The health care cost of these diseases is an additional burden that weighs heavily on the economies of developing countries. Effective management of CLDs requires the adoption of reliable and cost-effective screening and diagnosing methods to ensure early detection and accurate clinical assessment of these diseases. Vibrational spectroscopies have emerged as universal analytical methods with promising applications in various industrial and biomedical fields. These revolutionary analytical techniques rely on analyzing the interaction between a light beam and the test sample to generate a spectral fingerprint. This latter is defined by the analyte's chemical structure and the molecular vibrations of its functional groups. Raman spectroscopy and surface-enhanced Raman spectroscopy have been used in combination with various chemometric tests to diagnose a wide range of malignant, metabolic and infectious diseases. The aim of the current review is to cast light on the use of these optical sensing methods in the diagnosis of CLDs. The vast majority of research works that investigated the potential application of these spectroscopic techniques in screening and detecting CLDs were discussed here. The advantages and limitations of these modern analytical methods, as compared with the routine and gold standard diagnostic approaches, were also reviewed in details.

Combined serum CXCL8, CXCL9 and CXCL13 tests for the prediction of microvascular invasion in hepatocellular carcinoma

Aim: This work is to explore the predictive and diagnostic value of chemokine C-X-C motif ligand 8 (CXCL8), CXCL9 and CXCL13 combined detections for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. Materials & methods: A total of 82 HCC patients with MVI were recruited as the MVI group and 154 patients with non MVI were recruited as the non MVI group. Results: In HCC patients with MVI, CXCL8, CXCL9, CXCL13 levels were significantly elevated. Child-Pugh scores and serum α-fetoprotein level had positive correlation with CXCL8, CXCL9 and CXCL13 levels. The serum levels of CXCL8, 9 and 13 were effective in predicting MVI in HCC patients. Conclusion: CXCL8, CXCL9 and CXCL13 levels in HCC patients are valuable parameters in the prediction of MVI.

PET-guided attention for prediction of microvascular invasion in preoperative hepatocellular carcinoma on PET/CT

PURPOSE

To achieve PET/CT-based preoperative prediction of microvascular invasion in hepatocellular carcinoma by combining the advantages of PET and CT.

METHODS

This retrospective study included a total of 100 patients from two institutions who underwent PET/CT imaging. The above patients were divided into a training cohort (n = 70) and a validation cohort (n = 30). This study was based on PET/CT images to evaluate the possibility of microvascular invasion (MVI) of patients. In this study, we proposed a two-branch PET-guided attention network to predict MVI. The model used a two-branch network to extract image features from PET and CT, respectively. The PET-guided attention module aimed to enable the model to focus on the lesion region and reduce the disturbance of irrelevant and redundant information. Model performance was evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve.

RESULTS

The method outperformed the single-modality prediction model for preoperative hepatocyte microvascular invasion, achieving an AUC of 0.907. On the validation set, accuracy reached 0.846, precision reached 0.881, recall 0.793, and F1-score 0.835.

CONCLUSION

The model exploits the particularities of the molecular metabolic function of PET and the anatomical structure of CT and can strongly improve the accuracy of clinical diagnosis of MVI.

18F-FDG PET/CT-based radiomics nomogram for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma: a two-center study

PURPOSE

To explore the potential of β-2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in the evaluation of macrotrabecular-massive (MTM) hepatocellular carcinoma (HCC) and to apply radiomics approach to build a radiomics nomogram for predicting MTM-HCC.

METHODS

This study included 140 (training cohort:101; validation cohort:39) HCC patients who underwent preoperative ¹⁸F-FDG PET/CT at two institutions. The clinical features and tumor FDG metabolism measured by the tumor-to-liver ratio (TLR) via ¹⁸F-FDG PET/CT were retrospectively collected. Radiomics features were extracted from ¹⁸F-FDG PET/CT images and a radiomics score (Rad-score) was calculated. A radiomics nomogram was then constructed by combining Rad-score and independent clinical features and was assessed with a calibration curve. The performance of the radiomics nomogram, Rad-score and TLR was evaluated by receiver operating characteristic (ROC) curves and decision curve analysis (DCA).

RESULTS

A total of six top weighted radiomics features were selected from PET/CT images by the least absolute shrinkage and selection operator (LASSO) regression algorithm and were used to construct a Rad-score. Multivariate analysis identified Rad-score (OR = 2.183, P = 0.004), age ≤ 50 years (OR = 3.136, P = 0.036), AST > 40U/L (OR = 0.270, P = 0.017) and TLR (OR = 1.641, P = 0.049) as independent predictors of MTM-HCC. The radiomics nomogram had a higher area under the curves (AUCs) than the Rad-score and TLR for predicting MTM-HCC in both training (0.849 [95% CI 0.774-0.924] vs. 0.764 [95% CI 0.669-0.843], 0.763 [95% CI 0.668-0.842]) and validation (0.749 [95% CI 0.584-0.873] vs. 0.690 [95% CI 0.522-0.828], 0.541 [95% CI 0.374-0.701]) cohorts. DCA showed the radiomics nomogram to be more clinically useful than Rad-score and TLR.

CONCLUSIONS

Tumor FDG metabolism is significantly associated with MTM-HCC. A ¹⁸F-FDG PET/CT-based radiomics nomogram may be useful for preoperatively predicting the MTM subtype in primary HCC patients, contributing to pretreatment decision-making.

New insights into a microvascular invasion prediction model in hepatocellular carcinoma: A retrospective study from the SEER database and China

Background and Aims

The prognosis of liver cancer is strongly influenced by microvascular infiltration (MVI). Accurate preoperative MVI prediction can aid clinicians in the selection of suitable treatment options. In this study, we constructed a novel, reliable, and adaptable nomogram for predicting MVI.

Methods

Using the Surveillance, Epidemiology, and End Results (SEER) database, we extracted the clinical data of 1,063 patients diagnosed with hepatocellular carcinoma (HCC) and divided it into either a training (n = 739) or an internal validation cohort (n = 326). Based on multivariate analysis, the training cohort data were analyzed and a nomogram was generated for MVI prediction. This was further verified using an internal validation cohort and an external validation cohort involving 293 Chinese patients. Furthermore, to evaluate the efficacy, accuracy, and clinical use of the nomogram, we used concordance index (C-index), calibration curve, and decision curve analysis (DCA) techniques.

Results

In accordance with the multivariate analysis, tumor size, tumor number, alpha-fetoprotein (AFP), and histological grade were independently associated with MVI. The established model exhibited satisfactory performance in predicting MVI. The C-indices were 0.719, 0.704, and 0.718 in the training, internal validation, and external validation cohorts, respectively. The calibration curves showed an excellent consistency between the predictions and actual observations. Finally, DCA demonstrated that the newly developed nomogram had favorable clinical utility.

Conclusions

We established and verified a novel preoperative MVI prediction model in HCC patients. This model can be a beneficial tool for clinicians in selecting an optimal treatment plan for HCC patients.

Preoperative prediction model of microvascular invasion in patients with hepatocellular carcinoma

BACKGROUND

Microvascular invasion (MVI) is an adverse factor for the prognosis of patients with hepatocellular carcinoma (HCC). We aimed to construct a preoperative prediction model for MVI, thereby providing a reference for clinicians in formulating treatment options for HCC.

METHODS

A total of 360 patients with non-metastatic HCC were retrospectively enrolled. We used logistic regression analysis to screen out independent risk factors for MVI and further constructed a predictive model for MVI. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

RESULTS

Logistic regression analysis revealed that fibrinogen (>4 g/L) (OR: 6.529), alpha-fetoprotein (≥ 400 ng/mL) (OR: 2.676), cirrhosis (OR: 2.25), tumor size (OR: 1.239), and poor tumor border (OR: 3.126) were independent risk factors of MVI. The prediction model of MVI had C-index of 0.746 and 0.772 in the training and validation cohorts, respectively. The calibration curves showed good agreement between actual and predicted MVI risk. Finally, DCA reveals that this model has good clinical utility.

CONCLUSION

The nomogram-based model we established can predict the preoperative MVI well and provides reference for surgeons to make clinical treatment decisions.

Role of preoperative prediction of microvascular invasion in hepatocellular carcinoma based on the texture of FDG PET image: A comparison of quantitative metabolic parameters and MRI

Objective: To investigate the role of prediction microvascular invasion (mVI) in hepatocellular carcinoma (HCC) by ¹⁸F-FDG PET image texture analysis and hybrid criteria combining PET/CT and multi-parameter MRI.

Materials and methods: Ninety-seven patients with HCC who received the examinations of MRI and ¹⁸F-FDG PET/CT were retrospectively included in this study and were randomized into training and testing cohorts. The lesion image texture features of ¹⁸F-FDG PET were extracted using MaZda software. The optimal predictive texture features of mVI were selected, and the classification procedure was conducted. The predictive performance of mVI by radiomics classier in training and testing cohorts was respectively recorded. Next, the hybrid model was developed by integrating the ¹⁸F-FDG PET image texture, metabolic parameters, and MRI parameters to predict mVI through logistic regression. Furthermore, the diagnostic performance of each time was recorded.

Results: The ¹⁸F-FDG PET image radiomics classier showed good predicted performance in both training and testing cohorts to discriminate HCC with/without mVI, with an AUC of 0.917 (95% CI: 0.824–0.970) and 0.771 (95% CI: 0.578, 0.905). The hybrid model, which combines radiomics classier, SUVmax, ADC, hypovascular arterial phase enhancement pattern on contrast-enhanced MRI, and non-smooth tumor margin, also yielded better predictive performance with an AUC of 0.996 (95% CI: 0.939, 1.000) and 0.953 (95% CI: 0.883, 1.000). The differences in AUCs between radiomics classier and hybrid classier were significant in both training and testing cohorts (DeLong test, both p < 0.05).

Conclusion: The radiomics classier based on ¹⁸F-FDG PET image texture and the hybrid classier incorporating ¹⁸F-FDG PET/CT and MRI yielded good predictive performance, which might provide a precise prediction of HCC mVI preoperatively.

Radiomics in Gastric Cancer: First Clinical Investigation to Predict Lymph Vascular Invasion and Survival Outcome Using 18F-FDG PET/CT Images

Background

Lymph vascular invasion (LVI) is an unfavorable prognostic indicator in gastric cancer (GC). However, there are no reliable clinical techniques for preoperative predictions of LVI. The aim of this study was to develop and validate PET/CT-based radiomics signatures for predicting LVI of GC preoperatively. Radiomics nomograms were also established to predict patient survival outcomes.

Methods

This retrospective study registered 148 GC patients with histopathological confirmation for LVI status, who underwent pre-operative PET/CT scans (Discovery VCT 64 PET/CT system) from December 2014 to June 2019. Clinic-pathological factors (age, gender, and tumor grade, etc.) and metabolic PET data (maximum and mean standardized uptake value, total lesion glycolysis and metabolic tumor volume) were analyzed to identify independent LVI predictors. The dataset was randomly assigned to either the training set or test set in a 7:3 ratios. Three-dimensional (3D) radiomics features were extracted from each PET- and CT-volume of interests (VOI) singularly, and then a radiomics signature (RS) associated with LVI status is built by feature selection. Four models with different modalities (PET-RS: only PET radiomics features; CT-RS: only CT radiomics features; PET/CT-RS: both PET and CT radiomics features; PET/CT-RS plus clinical data) were developed to predict LVI. Patients were postoperatively followed up with PET/CT every 6-12 months for the first two years and then annually up to five years after surgery. The PET/CT radiomics score (Rad-scores) was calculated to assess survival outcome, and corresponding nomograms with radiomics (NWR) or without radiomics (NWOR) were established.

Results

Tumor grade and maximum standardized uptake value (SUVmax) were the independent LVI predictor. 1037 CT and PET 3D radiomics features were extracted separately and reduced to 4 and 5 features to build CT-RS and PET-RS, respectively. PET/CT-RS and PET/CT-RS plus clinical data (tumor grade and SUVmax) were also developed. The ROC analysis demonstrated clinical usefulness of PET/CT-RS plus clinical data (AUC values for training and validation, respectively 0.936 and 0.914) and PET/CT-RS (AUC values for training and validation, respectively 0.881 and 0.854), which both are superior to CT-RS (0.838 and 0.824) and PET-RS (0.821 and 0.812). SUVmax and LVI were independent prognostic indicators of both OS and PFS. Decision curve analysis (DCA) demonstrated NWR outperformed NWOR and was established to assess survival outcomes. For estimation of OS and PFS, the C-indexes of the NWR were 0. 88 and 0.88 in the training set, respectively, while the C-indexes of the NWOR were 0. 82 and 0.85 in the training set, respectively.

Conclusions

The PET/CT-based radiomics analysis might serve as a non-invasive approach to predict LVI status in GC patients and provide effective predictors of patient survival outcomes.

Preoperative clinical-radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using 18 F-FDG PET/CT

PURPOSE

To develop a clinical-radiomics nomogram by incorporating radiomics score and clinical predictors for preoperative prediction of microvascular invasion in hepatocellular carcinoma.

METHODS

A total of 97 HCC patients were retrospectively enrolled from Shanghai Universal Medical Imaging Diagnostic Center and Changhai Hospital Affiliated to the Second Military Medical University. 909 CT and 909 PET slicers from 97 HCC patients were divided into a training cohort (N = 637) and a validation cohort (N = 272). Radiomics features were extracted from each CT or PET slicer, and features selection was performed with least absolute shrinkage and selection operator regression and radiomics score was also generated. The clinical-radiomics nomogram was established by integrating radiomics score and clinical predictors, and the performance of the models were evaluated from its discrimination ability, calibration ability, and clinical usefulness.

RESULTS

The radiomics score consisted of 45 selected features, and age, the ratio of maximum to minimum tumor diameter, and18 F-FDG uptake status were independent predictors of microvascular invasion. The clinical-radiomics nomogram showed better performance for MVI detection (0.890 [0.854, 0.927]) than the clinical nomogram (0.849 [0.804, 0.893]) (p < 0.05 ). Both nomograms showed good calibration and the clinical-radiomics nomogram's clinical practicability outperformed the clinical nomogram.

CONCLUSIONS

With the combination of radiomics score and clinical predictors, the clinical-radiomics nomogram can significantly improve the predictive efficacy of microvascular invasion in hepatocellular carcinoma (p < 0.05 ) compared with clinical nomogram.

Analysis of Related Risk Factors of Microvascular Invasion in Hepatocellular Carcinoma

Objective

To forecast the onset of microvascular invasion (MVI) in patients with hepatoma by evaluating the preoperative aspartate aminotransferase-to-platelet ratio index (APRI), alpha-fetoprotein (AFP), neutrophil-to-lymphocyte ratio (NLR), and other clinicopathological data.

Methods

In this study, we retrospectively analysed the clinical data of 62 patients who received radical surgery for hepa toma from 2019 to 2021. Patients were separated into the MVI-negative group and the MVI-positive group according to the postoperative pathological diagnosis. The relationships between MVI and NLR, APRI, AFP, tumor size, and other clinical data were assessed using the univariate analysis, receiver operating characteristic (ROC) curve, least absolute shrinkage and selection operator (LASSO) analysis, and logistic analysis.

Results

The ROC curve determined that the cutoff values of NLR, platelet-to-lymphocyte ratio (PLR), and APRI were 1.520, 98, and 0.275, respectively. The univariate analysis showed that the MVI-positive result was associated with five factors: tumor size (χ² = 10.620, p = 0.001), AFP (χ² = 10.524, p = 0.001), Edmondson grade (χ² = 20.736, p < 0.001), NLR (χ² = 8.744, p = 0.003), and APRI (χ² = 4.849, p = 0.028). The LASSO analysis indicated that the risk factors were the number of tumors, PLR, APRI, NLR, AFP, Edmondson grade, and tumor size. The multivariate logistic regression analysis showed that NLR ≥ 1.520 (OR 11.119, p = 0.006), APRI ≥ 0.275 (OR 12.515, p = 0.009), AFP ≥ 200 μg/mL (OR 7.823, p = 0.016), and tumor size > 3 cm (OR 7.689, p = 0.022) were independent risk factors for MVI in patients with hepatoma.

Conclusion

Preoperative NLR, APRI, AFP, and tumor size are reliable indicators for predicting the appearance of MVI in patients with hepatoma and are of great value in making detailed and reliable treatment protocols for these patients before surgery.

Identification and Validation of a Prognostic Model Based on Three MVI-Related Genes in Hepatocellular Carcinoma

MVI has significant clinical value for treatment selection and prognosis evaluation in hepatocellular carcinoma (HCC). We aimed to construct a model based on MVI-Related Genes (MVIRGs) for risk assessment and prognosis prediction in patients with HCC. This study utilized various statistical analysis methods for prognostic model construction and validation in the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts, respectively. In addition, immunohistochemistry and qRT-PCR were used to analyze and identify the value of the model in our cohort. After the analyses, 153 differentially expressed MVIRGs were identified, and three key genes were selected to construct a prognostic model. The high-risk group showed significantly lower overall survival (OS), and this trend was observed in all subgroups: different age groups, genders, stages, and grades. Risk score was a risk factor independent of age, gender, stage, and grade. Moreover, the ICGC cohort validated the prognostic value of the model corresponding to the TCGA. In our cohort, qRT-PCR and immunohistochemistry showed that all three genes had higher expression levels in HCC samples than in normal controls. High expression levels of genes and high-risk scores showed significantly lower recurrence-free survival (RFS) and OS, especially in MVI-positive HCC samples. Therefore, the prognostic model constructed by three MVIRGs can reliably predict the RFS and OS of patients with HCC and is valuable for guiding clinical treatment selection and prognostic assessment of HCC.

Metabolic tumour volume on 18F-FDG PET/CT predicts extended pathological T stages in patients with renal cell carcinoma at staging

We evaluated the predictive value of ¹⁸F-fluorodeoxyglucose (FDG) uptake on positron emission tomography/CT (PET/CT) for extended pathological T (pT) stages (≥ pT3a) in Renal cell carcinoma (RCC) patients at staging. Thirty-eight RCC patients who underwent ¹⁸F-FDG PET/CT at staging, followed by radical nephrectomy between September 2016 and September 2018, were included in this prospective study. Patients were classified into two groups (limited pT stage: stage T1/2, n = 17; extended pT stage: T3/4, n = 21). Univariate and multivariate logistic regression analyses were performed to identify clinicopathological and metabolic variables to predict extended pT stages. ¹⁸F-FDG metabolic parameters were compared in relation to International Society of Urological Pathology (ISUP) grade and lymphovascular invasion (LVI). In univariate analysis, maximum standardised uptake value, metabolic tumour volume (MTV), and ISUP grade were significant. In multivariate analysis, MTV was the only significant factor of extended pT stages. With a cut-off MTV of 21.2, an area under the curve was 0.944, which was higher than 0.824 for clinical T stages (p = 0.037). In addition, high MTV, but not tumour size, was significantly correlated with aggressive pathologic features (ISUP grade and LVI). High glycolytic tumour volume on ¹⁸F-FDG PET/CT in RCC patients at staging is predictive of extended pT stages which could aid decision-making regarding the best type of surgery.

Microvascular invasion may be the determining factor in selecting TACE as the initial treatment in patients with hepatocellular carcinoma

ABSTRACT

The aim of this study was to investigate factors affecting tumor necrosis with transcatheter arterial chemoembolization (TACE). Factors associated with early hepatocellular carcinoma recurrence after curative hepatectomy were also evaluated.Data of 51 patients who underwent surgery after a single session of TACE at a single university hospital were retrospectively analyzed. Factors that might affect tumor necrosis were determined by evaluating the TACE approach and by analyzing computed tomography and TACE findings, pathologic reports, and laboratory findings.In univariate analysis, microvascular invasion (MVI), radiological capsule appearance on the computed tomography, chronic hepatitis B, diabetes mellitus and serum albumin, MVI were significantly associated with tumor necrosis by TACE (P < .02). In multivariate analysis, MVI was the only statistically significant factor in TACE-induced tumor necrosis (P = .001). In univariate and multivariate analysis, MVI was the strongest factor for recurrence-free survival rate within 2 years (P = .008, P = .002).MVI could be a crucial factor in determining TACE as an initial treatment for hepatocellular carcinoma. MVI is also a strong indicator of recurrence within 2 years after curative hepatic resection.

Diagnostic test accuracies of F-18 FDG PET/CT for prediction of microvascular invasion of hepatocellular carcinoma: A meta-analysis

PURPOSE

The aim of the current meta-analysis was to evaluate diagnostic accuracies of preoperative F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) or positron emission tomography/computed tomography (PET/CT) for prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients.

METHODS

The scientific database such as PubMed, Cochrane, and Embase database were searched for studies evaluating diagnostic accuracies of preoperative F-18 FDG PET or PET/CT for prediction of MVI in HCC patients up to November 30, 2020.

RESULTS

Fourteen eligible studies (1276 patients) were enrolled. The pooled sensitivity for F-18 FDG PET or PET/CT was 0.67 (95% CI; 0.57-0.76) with heterogeneity and a pooled specificity of 0.80 (95% CI; 0.74-0.85) with heterogeneity. Likelihood ratio (LR) syntheses gave an overall positive likelihood ratio (LR+) of 3.3 (95% CI; 2.5-4.5) and negative likelihood ratio (LR-) of 0.41 (95% CI; 0.31-0.55). The pooled diagnostic odds ratio (DOR) was 8 (95% CI; 5-14). Summary receiver operating characteristic (ROC) curve indicates that the area under the curve was 0.81 (95% CI; 0.78-0.84).

CONCLUSION

The current meta-analysis showed a low sensitivity and moderate specificity of F-18 FDG PET or PET/CT for the prediction of MVI in HCC patients. F-18 FDG PET or PET/CT might not be useful for the preoperative prediction of MVI in HCC patients and should not be used to exclude MVI. Therefore, cautious application and interpretation should be paid to the F-18 FDG PET or PET/CT for the prediction of MVI in HCC patients preoperatively.

2-[18F]FDG PET/CT as a Predictor of Microvascular Invasion and High Histological Grade in Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) generally presents a low avidity for 2-deoxy-2-[18F]fluoro-d-glucose (FDG) in PET/CT although an increased FDG uptake seems to relate to more aggressive biological factors. To define the prognostic value of PET/CT with FDG in patients with an HCC scheduled for a tumor resection, forty-one patients were prospectively studied. The histological factors of a poor prognosis were determined and FDG uptake in the HCC lesions was analyzed semi-quantitatively (lean body mass-corrected standardized uptake value (SUL) and tumor-to-liver ratio (TLR) at different time points). The PET metabolic parameters were related to the histological characteristics of the resected tumors and to the evolution of patients. Microvascular invasion (MVI) and a poor grade of differentiation were significantly related to a worse prognosis. The SULpeak of the lesion 60 min post-FDG injection was the best parameter to predict MVI while the SULpeak of the TLR at 60 min was better for a poor differentiation. Moreover, the latter parameter was also the best preoperative variable available to predict any of these two histological factors. Patients with an increased TLRpeak60 presented a significantly higher incidence of poor prognostic factors than the rest (75% vs. 28.6%, p = 0.005) and a significantly higher incidence of recurrence at 12 months (38% vs. 0%, p = 0.014). Therefore, a semi-quantitative analysis of certain metabolic parameters on PET/CT can help identify, preoperatively, patients with histological factors of a poor prognosis, allowing an adjustment of the therapeutic strategy for those patients with a higher risk of an early recurrence.

A Nomogram Estimation for the Risk of Microvascular Invasion in Hepatocellular Carcinoma Patients Meeting the Milan Criteria

OBJECTIVE

We aimed to develop and validate a nomogram for preoperatively estimating the risk of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) within the Milan criteria.

METHODS

The clinical data of 312 HCC patients who underwent liver surgery at the xxx from Jan 2017 to Dec 2019 were retrospectively collected. Then, the study population was categorized into the training and validation group based on the date of surgery. To identify risk factors related to MVI, we conducted a series of logistic regression analyses. By combining these risk factors, a nomogram was then established. We further clarified the usability of our model through the area under the ROC curve (AUC), decision curve analysis (DCA), and calibration curve.

RESULTS

Pathological examination revealed MVI in 108 patients with HCC (34.6%). Three independent predictors were identified: level of alpha-fetoprotein (AFP) exceeds 194 ng/mL (OR = 2.20, 95% CI: 1.13-4.31, p = 0.021), size of tumor (OR = 1.59; 95% CI: 1.18-2.12; P < 0.001) and number of tumors (OR = 3.37, 95% CI: 1.64-7.28, p < 0.001). A nomogram was subsequently built with an AUC of 0.73 and 0.74 respectively in the training cohort and validation cohort. The calibration curve showed a relatively high consistency between predicted probability and observed outcomes. Besides, the DCA revealed that the model was clinically beneficial for preoperatively predicting MVI in HCC.

CONCLUSIONS

A model for evaluating the risk of MVI HCC patients was developed and validated. The model could provide clinicians with a relatively reliable basis for optimizing treatment decisions.

Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning

PURPOSE

Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI preoperatively.

METHODS

In total, 405 patients were included. A total of 7302 radiomic features and 17 radiological features were extracted by a radiomics feature extraction package and radiologists, respectively. We developed a XGBoost model based on radiomics features, radiological features and clinical variables and a three-dimensional convolutional neural network (3D-CNN) to predict MVI status. Next, we compared the efficacy of the two models.

RESULTS

Of the 405 patients, 220 (54.3%) were MVI positive, and 185 (45.7%) were MVI negative. The areas under the receiver operating characteristic curves (AUROCs) of the Radiomics-Radiological-Clinical (RRC) Model and 3D-CNN Model in the training set were 0.952 (95% confidence interval (CI) 0.923-0.973) and 0.980 (95% CI 0.959-0.993), respectively (p = 0.14). The AUROCs of the RRC Model and 3D-CNN Model in the validation set were 0.887 (95% CI 0.797-0.947) and 0.906 (95% CI 0.821-0.960), respectively (p = 0.83). Based on the MVI status predicted by the RRC and 3D-CNN Models, the mean recurrence-free survival (RFS) was significantly better in the predicted MVI-negative group than that in the predicted MVI-positive group (RRC Model: 69.95 vs. 24.80 months, p < 0.001; 3D-CNN Model: 64.06 vs. 31.05 months, p = 0.027).

CONCLUSION

The RRC Model and 3D-CNN models showed considerable efficacy in identifying MVI preoperatively. These machine learning models may facilitate decision-making in HCC treatment but requires further validation.

Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients

Background

Microvascular invasion (MVI) is a significant hazard factor that influences the recurrence and survival of hepatocellular carcinoma (HCC) patients after undergoing hepatectomy. This study aimed to develop and validate a nomogram that combines hematological and imaging features of HCC patients to preoperatively predict MVI, and investigate the effect of wide resection margin (≥1 cm) on the prognosis of MVI-positive HCC patients.

Methods

A total of 709 HCC patients who underwent hepatectomy at the Liver Cancer Institute of Zhongshan Hospital, Fudan University between June 1, 2015 and December 30, 2016 were included in this study and divided into training (496 patients) and validation cohort (213 patients). Least absolute shrinkage and selection operator (Lasso) regression and multivariable logistic regression were used for variables’ selection and development of the predictive model. The model was presented as a nomogram, and its performance was assessed in terms of discrimination, calibration and clinical usefulness.

Results

Independent prognostic factors such as alkaline phosphatase (ALP, >125 U/L), alpha-fetoprotein (AFP, within 20–400 or >400 ng/mL), protein induced by vitamin K absence-II (PVIKA-II, within 40–400 or >400 mAU/mL), tumor number, diameter, pseudo-capsule, tumor growth pattern and intratumor hemorrhage were incorporated in the nomogram. The model showed good discrimination and calibration, with a concordance index (0.82, 95% CI, 0.782–0.857) in the training cohort and C-index (0.80, 95% CI, 0.772–0.837) in the validation cohort. Decision curve analysis (DCA) also showed that this model is clinically useful. Moreover, HCC patients with wide resection margin had a significantly lower 3-year recurrence rate than those with narrower resection margin (0.5–1 cm).

Conclusions

This study presents an optimal model for preoperative prediction of MVI and shows that wide resection margin for MVI-positive HCC patients has a better prognosis. This model can help surgeons choose the best treatment options for HCC patients before and after the operation.

Experience With LDLT in Patients With Hepatocellular Carcinoma and Portal Vein Tumor Thrombosis Postdownstaging

BACKGROUND

Median survival in patients with hepatocellular carcinoma (HCC) and portal vein tumor thrombosis (PVTT) is 2-6 months; conventionally liver transplantation is contraindicated.

METHODS

We studied outcomes following living donor liver transplantation (LDLT) post-PVTT downstaging (DS) with stereotactic body radiotherapy (SBRT), and tumor ablation (with transarterial chemo- or radio-embolization).

RESULTS

Of 2348 consecutive LDLTs, 451 were for HCC, including 25 with PVTT (mainly Vp1-3) after successful DS and 20 with Vp1/2 PVTT without previous treatment. DS was attempted in 43, was successful in 27 (63%), and 25 underwent LDLT. Median alpha fetoprotein (AFP) at diagnosis and pre-LDLT were 78.1 ng/mL (3-58 200) and 55 ng/mL (2-7320), respectively. Mean DS to LDLT time was 10.2 weeks (5-16). Excluding 2 postoperative deaths, 1- and 5-year overall survival (OS) and recurrence-free survival (RFS) were 82%, 57%, and 77%, 51%, respectively, comparable to survival in 382 HCC patients without PVTT undergoing upfront LDLT (5-y OS 65%, P = 0.06; RFS 66%, P = 0.33, respectively). There was a trend toward better OS in DS+LDLT versus non-DS LDLT group (5-y OS/RFS-48%/40%). OS was significantly better than in HCC-PVTT patients receiving no intervention or palliative Sorafenib alone (1-y OS of 0%) or Sorafenib with TARE/SBRT (2-y OS of 17%) at our center during the study period. Initial AFP <400 ng/mL and AFP fall (initial minus pre-LDLT) >2000 ng/mL predicted better RFS; Grade III/IV predicted worse OS in DS patients.

CONCLUSIONS

HCC patients with PVTT can achieve acceptable survival with LDLT after successful DS. Low initial AFP level, a significant drop in AFP with DS and low tumor grade, favorably influence survival in these patients.

Radiomics analysis of [18F]FDG PET/CT for microvascular invasion and prognosis prediction in very-early- and early-stage hepatocellular carcinoma

As a reliable preoperative predictor for microvascular invasion (MVI) and disease-free survival (DFS) is lacking, we developed a radiomics nomogram of [¹⁸F]FDG PET/CT to predict MVI status and DFS in patients with very-early- and early-stage (BCLC 0, BCLC A) hepatocellular carcinoma (HCC).

METHODS

Patients (N = 80) with BCLC0-A HCC who underwent [¹⁸F]FDG PET/CT before surgery were enrolled in this retrospective study and were randomized to a training cohort and a validation cohort. Texture features from patients obtained using Lifex software in the training cohort were subjected to LASSO regression to select the most useful predictive features of MVI and DFS. Then, the radiomics nomogram was constructed using the radiomics signature and clinical features and further validated.

RESULTS

To predict MVI, the [¹⁸F]FDG PET/CT radiomics signature consisted of five texture features from the PET and six texture features from CT. The signature was significantly associated with MVI status in the training cohort (P = 0.001). None of the clinical features was independent predictors for MVI status (P > 0.05). The area under the curve value of the M-PET/CT model was 0.891 (95% CI: 0.799-0.984) in the training cohort and showed good discrimination and calibration. To predict DFS, the [¹⁸F]FDG PET/CT radiomics nomogram (D-PET/CT model) and a clinicopathologic nomogram were built in the training cohort. The D-PET/CT model, which integrated the D-PET/CT radiomics signature with INR and TB, provided better predictive performance (C-index: 0.831, 95% CI: 0.761-0.900) and larger net benefits than the simple clinical model, as determined by decision curve analyses.

CONCLUSION

The newly developed [¹⁸F]FDG PET/CT radiomics signature was an independent biomarker for the estimation of MVI and DFS in patients with very-early- and early-stage HCC. Moreover, PET/CT nomogram, which incorporated the radiomics signature of [¹⁸F]FDG PET/CT and clinical risk factors in patients with very-early- and early-stage HCC, performed better for individualized DFS estimation, which might enable a step forward in precise medicine.

Efficacy of Raman spectroscopy in the diagnosis of hepatocellular carcinoma: A protocol for systematic review and meta-analysis

BACKGROUND

To comprehensively analyze the relative effectiveness of Raman spectroscopy (RS) in the diagnosis of suspected hepatocellular carcinoma (HCC).

METHODS

We will perform a complete systematic review based on studies from PubMed/Medline, EMBASE, Web of Science, Ovid, Web of Knowledge, Cochrane Library and CNKI. We plan to identify over 2000 spectra with strict criteria in several individual studies published between January 2008 and November 2020 in accordance to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We are going to summarize the test performance using random effects models.

RESULTS

This study will provide solid evidence and data on the sensitivity, specificity and accuracy of RS in the diagnosis of HCC.

CONCLUSION

Through this meta-analysis, we intend to provide the pooled sensitivity, specificity and diagnostic accuracy of RS in the diagnosis of suspected HCC. Other parameters like positive LR, negative LR, DOR and AUC of the SROC curve will also be calculated and drawn to help illustrate the efficacy of RS in the diagnosis of HCC.

Preoperative Prediction Power of Imaging Methods for Microvascular Invasion in Hepatocellular Carcinoma: A Systemic Review and Meta-Analysis

Background: To compare the predictive power between radiomics and non-radiomics (conventional imaging and functional imaging methods) for preoperative evaluation of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Methods: Comprehensive publications were screened in PubMed, Embase, and Cochrane Library. Studies focusing on the discrimination values of imaging methods, including radiomics and non-radiomics methods, for MVI evaluation were included in our meta-analysis.

Results: Thirty-three imaging studies with 5,462 cases, focusing on preoperative evaluation of MVI status in HCC, were included. The sensitivity and specificity of MVI prediction in HCC were 0.78 [95% confidence interval (CI): 0.75–0.80; I² = 70.7%] and 0.78 (95% CI: 0.76–0.81; I² = 0.0%) for radiomics, respectively, and were 0.73 (95% CI: 0.71–0.75; I² = 83.7%) and 0.82 (95% CI: 0.80–0.83; I² = 86.5%) for non-radiomics, respectively. The areas under the receiver operation curves for radiomics and non-radiomics to predict MVI status in HCC were 0.8550 and 0.8601, respectively, showing no significant difference.

Conclusion: The imaging method is feasible to predict the MVI state of HCC. Radiomics method based on medical image data is a promising application in clinical practice and can provide quantifiable image features. With the help of these features, highly consistent prediction performance will be achieved in anticipation.

Contrast-enhanced CT radiomics for preoperative evaluation of microvascular invasion in hepatocellular carcinoma: A two-center study

Background

The present study constructed and validated the use of contrast‐enhanced computed tomography (CT)‐based radiomics to preoperatively predict microvascular invasion (MVI) status (positive vs negative) and risk (low vs high) in patients with hepatocellular carcinoma (HCC).

Methods

We enrolled 637 patients from two independent institutions. Patients from Institution I were randomly divided into a training cohort of 451 patients and a test cohort of 111 patients. Patients from Institution II served as an independent validation set. The LASSO algorithm was used for the selection of 798 radiomics features. Two classifiers for predicting MVI status and MVI risk were developed using multivariable logistic regression. We also performed a survival analysis to investigate the potentially prognostic value of the proposed MVI classifiers.

Results

The developed radiomics signature predicted MVI status with an area under the receiver operating characteristic curve (AUC) of .780, .776, and .743 in the training, test, and independent validation cohorts, respectively. The final MVI status classifier that integrated two clinical factors (age and α‐fetoprotein level) achieved AUC of .806, .803, and .796 in the training, test, and independent validation cohorts, respectively. For MVI risk stratification, the AUCs of the radiomics signature were .746, .664, and .700 in the training, test, and independent validation cohorts, respectively, and the AUCs of the final MVI risk classifier‐integrated clinical stage were .783, .778, and .740, respectively. Survival analysis showed that our MVI status classifier significantly stratified patients for short overall survival or early tumor recurrence.

Conclusions

Our CT radiomics‐based models were able to predict MVI status and MVI risk of HCC and might serve as a reliable preoperative evaluation tool.

The Value of TTPVI in Prediction of Microvascular Invasion in Hepatocellular Carcinoma

Purpose

The objective of our study was to evaluate the value of two-trait predictor of venous invasion (TTPVI) in the prediction of pathological microvascular invasion (pMVI) in patients with hepatocellular carcinoma (HCC) from preoperative computed tomography (CT) and magnetic resonance (MR).

Methods

A total of 128 preoperative patients with findings of HCC were enrolled. Tumor size, tumor margins, tumor capsule, peritumoral enhancement, and TTPVI was assessed on preoperative CT and MRI images. Histopathological features were reviewed: pathological tumor size, tumor differentiation, pMVI along with alpha-fetoprotein level (AFP). Significant imaging findings and histopathological features were determined with univariate and multivariate logistic regression analysis.

Results

Univariate analysis revealed that tumor size (p<0.01), AFP level (p=0.043), tumor differentiation (p<0.01), peritumoral enhancement (p=0.003), pathological tumor size (p<0.01), tumor margins (p<0.01) on CT and MRI, and TTPVI (p<0.01) showed statistically significant associations with pMVI. In multivariate logistic regression analysis, tumor size (odds ratio [OR] = 1.294; 95% confidence interval [CI]: 1.155, 1.451; p < 0.001), tumor differentiation (odds ratio [OR] =1.384; 95% confidence interval [CI]: 1.224, 1.564; p < 0.001), and TTPVI (odds ratio [OR] = 4.802; 95% confidence interval [CI]: 1.037, 22.233; p=0.045) were significant independent predictors of pMVI. Using 5.8 as the threshold for size, one could obtain an area-under-curve (AUC) of 0.793, 95% confidence interval [CI]: 0.715 to 0.857.

Conclusion

Tumor size, tumor differentiation, and TTPVI depicted in preoperative CT and MRI had a statistically significant correlation with pMVI. Hence, TTPVI detected on CT and MRI may be predictive of pMVI in HCC cases.

Addition of [18 F]Fluorodeoxyglucose Positron Emission Tomography With Computed Tomography to Cross-Sectional Imaging Improves Staging and Alters Management in Hepatocellular Carcinoma

In this work, we characterize the value of positron emission tomography (PET) with computed tomography (CT) in combination with cross-sectional imaging for staging and prognostication of hepatocellular carcinoma (HCC) patients. In this retrospective cohort study, HCC patients underwent PET-CT after initial staging with contrast-enhanced CT or magnetic resonance imaging (MRI). The benefit of PET-CT was measured by the identification of new HCC lesions, and potential harm was quantified by the number of false positives and subsequent diagnostic evaluation. We used multivariate Cox regression analysis to evaluate the association between the highest grade on PET-CT with the risk of extrahepatic metastasis, progression-free, and overall survival. Among 148 patients, PET-CT detected additional extrahepatic metastasis in 11.9% of treatment-naïve and 13.8% of treatment-experienced patients. PET-CT changed the Barcelona Clinic Liver Cancer (BCLC) staging in 5.9% of treatment-naïve and 18.8% of treatment-experienced patients compared with CT/MRI alone, changing HCC management in 9.9% and 21.3% of patients, respectively. Of the patients, 5% (n = 8) experienced severe physical harm requiring additional procedures to evaluate extrahepatic findings. High tumor grade on PET-CT was independently associated with a higher likelihood of extrahepatic metastasis (hazard ratio [HR], 17.1; 95% confidence interval [CI], 3.6-81.5) and worse overall survival (HR, 2.4; 95% CI, 1.4-4.3). Treatment-experienced patients (versus treatment-naïve patients; HR, 9.7; 95% CI, 1.9-49.4) and BCLC stage A (HR, 8.2; 95% CI, 1.5-45.9; P < 0.01) and BCLC stage B (HR, 20.6; 95% CI, 1.5-282.2; P < 0.05) were more likely to have an upstaging with PET-CT compared with BCLC stage C (reference). PET-CT provides prognostic information and improves tumor staging beyond CT/MRI alone, with subsequent changes in management for patients with HCC.

Additional value of metabolic parameters to PET/CT-based radiomics nomogram in predicting lymphovascular invasion and outcome in lung adenocarcinoma

PURPOSE

Lymphovascular invasion (LVI) impairs surgical outcomes in lung adenocarcinoma (LAC) patients. Preoperative prediction of LVI is challenging by using traditional clinical and imaging parameters. The purpose of this study was to investigate the value of the radiomics nomogram integrating clinical factors, CT features, and maximum standardized uptake value (SUVmax) to predict LVI and outcome in LAC and to evaluate the additional value of the SUVmax to the PET/CT-based radiomics nomogram.

METHODS

A total of 272 LAC patients (87 LVI-present LACs and 185 LVI-absent LACs) with PET/CT scans were retrospectively enrolled, and 160 patients with SUVmax ≥ 2.5 of them were used for PET radiomics analysis. Clinical data and CT features were analyzed to select independent LVI predictors. The performance of the independent LVI predictors and SUVmax was evaluated. Two-dimensional (2D) and three-dimensional (3D) CT radiomics signatures (RSs) and PET-RS were constructed with the least absolute shrinkage and selection operator algorithm and radiomics scores (Rad-scores) were calculated. The radiomics nomograms, incorporating Rad-score and independent clinical and CT factors, with SUVmax (RNWS) or without SUVmax (RNWOS) were built. The performance of the models was assessed with respect to calibration, discrimination, and clinical usefulness. All the clinical, PET/CT, pathologic, therapeutic, and radiomics parameters were assessed to identify independent predictors of progression-free survival (PFS).

RESULTS

CT morphology was the independent LVI predictor. SUVmax provided better discrimination capability compared with CT morphology in the training set (P < 0.001) and test set (P = 0.042). A total of 1409 CT and PET radiomics features were extracted and reduced to 8, 8, and 10 features to build the 2D CT-RS, 3D CT-RS, and the PET-RS, respectively. There was no significant difference in AUC between the 2D-RS and 3D-RS (P > 0.05), and 2D CT-RS showed a relatively higher AUC than 3D CT-RS. The CT-RS, the CT-RNWOS, and the CT-RNWS showed good discrimination in the training set (AUC [area under the curve], 0.799, 0.796, and 0.851, respectively) and the test set (AUC, 0.818, 0.822, and 0.838, respectively). There was significant difference in AUC between the CT-RNWS and CT-RNWOS (P = 0.044) in the training set. Decision curve analysis (DCA) demonstrated the CT-RNWS outperformed the CT-RS and the CT-RNWOS in terms of clinical usefulness. Furthermore, DCA showed the PETCT-RNWS provided the highest net benefit compared with the PET-RNWS and CT-RNWS. PFS was significantly different between the pathologic and RNWS-predicted LVI-present and LVI-absent patients (P < 0.001). Carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), pathologic LVI, histologic subtype, and SUVmax were independent predictors of PFS in the 244 CT-RNWS-predicted cohort; and CA125, NSE, pathologic LVI, and SUVmax were the independent predictors of PFS in the 141 PETCT-RNWS-predicted cohort.

CONCLUSIONS

The radiomics nomogram, incorporating Rad-score, clinical and PET/CT parameters, shows favorable predictive efficacy for LVI status in LAC. Pathologic LVI and SUVmax are associated with LAC prognosis.

Serum STIP1, a Novel Indicator for Microvascular Invasion, Predicts Outcomes and Treatment Response in Hepatocellular Carcinoma

Background: Previous studies reported that stress-induced phosphoprotein 1 (STIP1) can be secreted by hepatocellular carcinoma (HCC) cells and is increased in the serum of HCC patients. However, the therapy-monitoring and prognostic value of serum STIP1 in HCC remains unclear. Here, we aimed to systemically explore the prognostic significance of serum STIP1 in HCC.

Methods: A total of 340 HCC patients were recruited to this study; 161 underwent curative resection and 179 underwent transcatheter arterial chemoembolization (TACE). Serum STIP1 was detected by enzyme-linked immunosorbent assay (ELISA). Optimal cutoff values for serum STIP1 in resection and TACE groups were determined by receiver operating characteristic (ROC) analysis. Prognostic value was assessed by Kaplan-Meier, log-rank, and Cox regression analyses. Predictive values of STIP1 for objective response (OR) to TACE and MVI were evaluated by ROC curves and logistic regression.

Results: Serum STIP1 was significantly increased in HCC patients when compared with chronic hepatitis B patients or health donors (both P < 0.05). Optimal cutoff values for STIP1 in resection and TACE groups were 83.43 and 112.06 ng/ml, respectively. High pretreatment STIP1 was identified as an independent prognosticator. Dynamic changes in high STIP1 status were significantly associated with long-term prognosis, regardless of treatment approaches. Moreover, post-TACE STIP1 was identified as an independent predictor for OR, with a higher area under ROC curve (AUC-ROC) than other clinicopathological features. Specifically, pretreatment STIP1 was significantly increased in patients with microvascular invasion (MVI), and was confirmed as a novel, powerful predictor for MVI.

Conclusions: Serum STIP1 is a promising biomarker for outcome evaluation, therapeutic response assessment, and MVI prediction in HCC. Integration serum STIP1 detection into HCC management might facilitate early clinical decision making to improve the prognosis of HCC.

Pan-Asian adapted ESMO Clinical Practice Guidelines for the management of patients with intermediate and advanced/relapsed hepatocellular carcinoma: a TOS-ESMO initiative endorsed by CSCO, ISMPO, JSMO, KSMO, MOS and SSO

The most recent version of the European Society for Medical Oncology (ESMO) Clinical Practice Guidelines for the diagnosis, treatment and follow-up of hepatocellular carcinoma (HCC) was published in 2018, and covered the diagnosis, management, treatment and follow-up of early, intermediate and advanced disease. At the ESMO Asia Meeting in November 2018 it was decided by both the ESMO and the Taiwan Oncology Society (TOS) to convene a special guidelines meeting immediately after the Taiwan Joint Cancer Conference (TJCC) in May 2019 in Taipei. The aim was to adapt the ESMO 2018 guidelines to take into account both the ethnic and the geographic differences in practice associated with the treatment of HCC in Asian patients. These guidelines represent the consensus opinions reached by experts in the treatment of patients with intermediate and advanced/relapsed HCC representing the oncology societies of Taiwan (TOS), China (CSCO), India (ISMPO) Japan (JSMO), Korea (KSMO), Malaysia (MOS) and Singapore (SSO). The voting was based on scientific evidence, and was independent of the current treatment practices, the drug availability and reimbursement situations in the individual participating Asian countries.

Nomogram For Preoperative Prediction Of Microvascular Invasion Risk In Hepatocellular Carcinoma

Objective

To preoperatively predict the microvascular invasion (MVI) risk in hepatocellular carcinoma (HCC) using nomogram.

Methods

A retrospective cohort of 513 patients with HCC hospitalized at Xiangya Hospital between January 2014 and December 2018 was included in the study. Univariate and multivariate analysis was performed to identify the independent risk factors for MVI. Based on the independent risk factors, nomogram was established to preoperatively predict the MVI risk in HCC. The accuracy of nomogram was evaluated by using receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA).

Results

Tumor size (OR=1.17, 95% CI: 1.11–1.23, p<0.001), preoperative AFP level greater than 155 ng/mL (OR=1.65, 95% CI: 1.13–2.39, p=0.008) and NLR (OR=1.14, 95% CI: 1.00–1.29, p=0.042) were the independent risk factors for MVI. Incorporating these 3 factors, nomogram was established with the concordance index of 0.71 (95% CI, 0.66–0.75) and well-fitted calibration curves. DCA confirmed that using this nomogram added more benefit compared with the measures that treat all patients or treat none patients. At the cutoff value of predicted probability ≥0.44, the model demonstrated sensitivity of 61.64%, specificity of 71.53%, positive predictive value (PPV) of 64.13%, and negative predictive value (NPV) of 69.31%.

Conclusion

Nomogram was established for preoperative prediction of the MVI risk in HCC patients, and better therapeutic choice will be made if it was applied in clinical practice.

18F-FDG PET/CT predicts microvascular invasion and early recurrence after liver resection for hepatocellular carcinoma: A prospective observational study

BACKGROUND

This study assessed the prognostic value of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) in the prediction of MVI and early recurrence following resection.

METHOD

This prospective study (ClinicalTrials.gov ID: NCT02145013) included 78 consecutive HCC patients who underwent 18F-FDG PET/CT before curative-intent resection from 2014 to 2017. Prognostic factors available before surgery for predicting MVI and early recurrence (≤2 years) were identified by univariate and multivariate analyses.

RESULTS

The 18F-FDG PET/CT result was positive in 30 (38%) patients. MVI was present in 33% (26/78) of specimens. Early recurrence occurred in 19% (14/74) of surviving patients. PET/CT positivity was the sole independent predictor of MVI (odds ratio [OR] = 3.6, 95% confidence interval [CI] = 1.1-11.2; p = 0.03), with a specificity and sensitivity for predicting MVI of 73% and 62%, respectively. Analysis of variables available before surgery showed that PET/CT positivity (hazard ratio [HR] = 5.8, 95% CI = 1.6-20.4; p = 0.006) and the male sex (HR = 6.6; 95% CI = 1.8-24.2; p = 0.005) were independent predictors of early recurrence.

CONCLUSION

18F-FDG PET/CT predicts MVI and early recurrence after surgery for HCC and could be used to select patients for neoadjuvant treatment.

Emerging role of 18F-fluorodeoxyglucose positron emission tomography for guiding management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of major causes of cancer mortality worldwide. For decades, ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) has been widely used for staging, predicting prognosis, and detecting cancer recurrence in various types of malignant diseases. Due to low sensitivity of FDG PET for detecting intrahepatic HCC lesions, the clinical value of FDG PET in HCC patients has been limited. However, recent studies with diverse analytic methods have shown that FDG PET has promising role in aiding management of HCC patients. In this review, we will discuss the clinical role of FDG PET for staging, predicting prognosis, and evaluating treatment response in HCC. Further, we will focus on recent clinical studies regarding implication of volumetric FDG PET parameters, the significance of FDG uptake in HCC for selecting treatment and predicting treatment response, and the use of radiomics of FDG PET in HCC.

18F-fludeoxyglucose positron emission tomography for diagnosis of HCC: implications for therapeutic strategy in curative and non-curative approaches

Hepatocellular carcinoma (HCC) is a global health issue with increasing incidence and high mortality rate. Depending on the tumor load and extent of underlying liver cirrhosis, aggressive surgical treatment by hepatectomy or liver transplantation (LT) may lead to cure, whereas different modalities of liver-directed locoregional or systemic tumor treatments are currently available for a noncurative approach. Apart from tumor burden and grade of liver dysfunction, assessment of prognostic relevant biological tumor aggressiveness is vitally important for establishing a promising multimodal therapeutic strategy and improving the individual treatment-related risk/benefit ratio. In recent years, an increasing body of clinical evidence has been presented that ¹⁸F-fludeoxyglucose (¹⁸F-FDG) positron emission tomography (PET), which is a standard nuclear imaging device in oncology, may serve as a powerful surrogate for tumor invasiveness and prognosis in HCC patients and, thereby, impact individual decision making on most appropriate therapy concept. This review describes the currently available data on the prognostic value of ¹⁸F-FDG PET in patients with early and advanced HCC stages and the resulting implications for treatment strategy.