Preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma based on kupffer phase radiomics features of sonazoid contrast-enhanced ultrasound (SCEUS): A prospective study

Non-radiomics imaging (US-CEUS) features and clinical text features: correlation with microvascular invasion and tumor grading in hepatocellular carcinoma

OBJECTIVES

To predict microvascular invasion (MVI) status and tumor grading of hepatocellular carcinoma (HCC) by evaluating preoperative non-radiomics ultrasound and contrast-enhanced ultrasound (US-CEUS) features and determine the influences of MVI/tumor grading on the category of CEUS LI-RADS for HCC.

METHODS

A total of 506 HCC patients who underwent preoperative US-CEUS examinations from 8 hospitals between July 2020 and June 2023 were enrolled. According to the MVI status, all the patients were classified, and HCC differentiation was assessed by using Edmondson-Steiner (ES) grading: MVI-negative (M0) and low-grade ES (GI/II) (MN-L, n = 297) and MVI-positive (M1/M2) and/or high-grade ES (GIII/IV) (MP-H, n = 209). Stratified analysis was performed based on fibrosis stage and tumor size.

RESULTS

The results proved that MN-L HCC was more frequently classified into the LR-5 category (p = 0.034), while MP-H HCC was more frequently classified into the LR-TIV (p = 0.010). The heterogeneously arterial phase hyperenhancement (APHE) is significantly correlated with MVI(+)/high grade-ES (p = 0.003). Compared with MN-L HCC, the onset of washout was earlier, washout rate was higher, and tumor-invasion border was larger (all p < 0.01) in MP-H HCC. In addition, fibrosis stage and tumor size significantly influenced the onset of washout and washout rate of HCC (all p < 0.01). The tumor-invasion border was only positively correlated with tumor size (p < 0.001) rather than fibrosis stage (p > 0.05).

CONCLUSIONS

MVI status and tumor grading influence the classification of LR-5 and LR-TIV. Heterogeneous APHE, higher washout rate, earlier onset of washout (≤65 s), larger tumor-invasion border (≥3 mm) and higher alpha fetoprotein level indicate the presence of MVI and/or high-grade ES.

Review of Clinical Applications of Sonazoid Ultrasound Contrast for Liver Evaluation

ABSTRACT

Sonazoid is a new ultrasound contrast agent with unique Kupffer phase imaging advantages and high mechanical index stability. This paper introduces the basic theories and advantages of Sonazoid ultrasound. Then, the application and latest advances of Sonazoid in the diagnosis and treatment of liver diseases are reviewed in detail. In addition, the advantages and disadvantages of Sonazoid ultrasound and its future directions are discussed. Sonazoid is expected to become an important tool for clinical ultrasound diagnosis and treatment.

Advancing Hepatocellular Carcinoma Management Through Peritumoral Radiomics: Enhancing Diagnosis, Treatment, and Prognosis

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and is associated with high mortality rates due to late detection and aggressive progression. Peritumoral radiomics, an emerging technique that quantitatively analyzes the tissue surrounding the tumor, has shown significant potential in enhancing the management of HCC. This paper examines the role of peritumoral radiomics in improving diagnostic accuracy, guiding personalized treatment strategies, and refining prognostic assessments. By offering unique insights into the tumor microenvironment, peritumoral radiomics enables more precise patient stratification and informs clinical decision-making. However, the integration of peritumoral radiomics into routine clinical practice faces several challenges. Addressing these challenges through continued research and innovation is crucial for the successful implementation of peritumoral radiomics in HCC management, ultimately leading to improved patient outcomes.

Prediction of microvascular invasion in hepatocellular carcinoma with conventional ultrasound, Sonazoid-enhanced ultrasound, and biochemical indicator: a multicenter study

PURPOSE

To develop and validate a preoperative prediction model based on multimodal ultrasound and biochemical indicator for identifying microvascular invasion (MVI) in patients with a single hepatocellular carcinoma (HCC) ≤ 5 cm.

METHODS

From May 2022 to November 2023, a total of 318 patients with pathologically confirmed single HCC ≤ 5 cm from three institutions were enrolled. All of them underwent preoperative biochemical, conventional ultrasound (US), and contrast-enhanced ultrasound (CEUS) (Sonazoid, 0.6 mL, bolus injection) examinations. Univariate and multivariate logistic regression analyses on clinical information, biochemical indicator, and US imaging features were performed in the training set to seek independent predictors for MVI-positive. The models were constructed and evaluated using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis in both validation and test sets. Subgroup analyses in patients with different liver background and tumor sizes were conducted to further investigate the model's performance.

RESULTS

Logistic regression analyses showed that obscure tumor boundary in B-mode US, intra-tumoral artery in pulsed-wave Doppler US, complete Kupffer-phase agent clearance in Sonazoid-CEUS, and biomedical indicator PIVKA-II were independently correlated with MVI-positive. The combined model comprising all predictors showed the highest AUC, which were 0.937 and 0.893 in the validation and test sets. Good calibration and prominent net benefit were achieved in both sets. No significant difference was found in subgroup analyses.

CONCLUSIONS

The combination of biochemical indicator, conventional US, and Sonazoid-CEUS features could help preoperative MVI prediction in patients with a single HCC ≤ 5 cm.

CRITICAL RELEVANCE STATEMENT

Investigation of imaging features in conventional US, Sonazoid-CEUS, and biochemical indicators showed a significant relation with MVI-positivity in patients with a single HCC ≤ 5 cm, allowing the construction of a model for preoperative prediction of MVI status to help treatment decision making.

KEY POINTS

MVI status is important for patients with a single HCC ≤ 5 cm. The model based on conventional US, Sonazoid-CEUS and PIVKA-II performs best for MVI prediction. The combined model has potential for preoperative prediction of MVI status.

Artificial intelligence-aided ultrasound imaging in hepatopancreatobiliary surgery: where are we now?

BACKGROUND

Artificial intelligence (AI) models have been applied in various medical imaging modalities and surgical disciplines, however the current status and progress of ultrasound-based AI models within hepatopancreatobiliary surgery have not been evaluated in literature. Therefore, this review aimed to provide an overview of ultrasound-based AI models used for hepatopancreatobiliary surgery, evaluating current advancements, validation, and predictive accuracies.

METHOD

Databases PubMed, EMBASE, Cochrane, and Web of Science were searched for studies using AI models on ultrasound for patients undergoing hepatopancreatobiliary surgery. To be eligible for inclusion, studies needed to apply AI methods on ultrasound imaging for patients undergoing hepatopancreatobiliary surgery. The Probast risk of bias tool was used to evaluate the methodological quality of AI methods.

RESULTS

AI models have been primarily used within hepatopancreatobiliary surgery, to predict tumor recurrence, differentiate between tumoral tissues, and identify lesions during ultrasound imaging. Most studies have combined radiomics with convolutional neural networks, with AUCs up to 0.98.

CONCLUSION

Ultrasound-based AI models have demonstrated promising accuracies in predicting early tumoral recurrence and even differentiating between tumoral tissue types during and after hepatopancreatobiliary surgery. However, prospective studies are required to evaluate if these results will remain consistent and externally valid.

Strategies to enhance the therapeutic efficacy of anti-PD-1 antibody, anti-PD-L1 antibody and anti-CTLA-4 antibody in cancer therapy

Although immune checkpoint inhibitors (anti-PD-1 antibody, anti-PD-L1 antibody, and anti-CTLA-4 antibody) have displayed considerable success in the treatment of malignant tumors, the therapeutic effect is still unsatisfactory for a portion of patients. Therefore, it is imperative to develop strategies to enhance the effect of these ICIs. Increasing evidence strongly suggests that the key to this issue is to transform the tumor immune microenvironment from a state of no or low immune infiltration to a state of high immune infiltration and enhance the tumor cell-killing effect of T cells. Therefore, some combination strategies have been proposed and this review appraise a summary of 39 strategies aiming at enhancing the effectiveness of ICIs, which comprise combining 10 clinical approaches and 29 foundational research strategies. Moreover, this review improves the comprehensive understanding of combination therapy with ICIs and inspires novel ideas for tumor immunotherapy.

Predicting Ki-67 expression in hepatocellular carcinoma: nomogram based on clinical factors and contrast-enhanced ultrasound radiomics signatures

PURPOSE

To develop a contrast-enhanced ultrasound (CEUS) clinic-radiomics nomogram for individualized assessment of Ki-67 expression in hepatocellular carcinoma (HCC).

METHODS

A retrospective cohort comprising 310 HCC individuals who underwent preoperative CEUS (using SonoVue) at three different centers was partitioned into a training set, a validation set, and an external test set. Radiomics signatures indicating the phenotypes of the Ki-67 were extracted from multiphase CEUS images. The radiomics score (Rad-score) was calculated accordingly after feature selection and the radiomics model was constructed. A clinic-radiomics nomogram was established utilizing multiphase CEUS Rad-score and clinical risk factors. A clinical model only incorporated clinical factors was also developed for comparison. Regarding clinical utility, calibration, and discrimination, the predictive efficiency of the clinic-radiomics nomogram was evaluated.

RESULTS

Seven radiomics signatures from multiphase CEUS images were selected to calculate the Rad-score. The clinic-radiomics nomogram, comprising the Rad-score and clinical risk factors, indicated a good calibration and demonstrated a better discriminatory capacity compared to the clinical model (AUCs: 0.870 vs 0.797, 0.872 vs 0.755, 0.856 vs 0.749 in the training, validation, and external test set, respectively) and the radiomics model (AUCs: 0.870 vs 0.752, 0.872 vs 0.733, 0.856 vs 0.729 in the training, validation, and external test set, respectively). Furthermore, both the clinical impact curve and the decision curve analysis displayed good clinical application of the nomogram.

CONCLUSION

The clinic-radiomics nomogram constructed from multiphase CEUS images and clinical risk parameters can distinguish Ki-67 expression in HCC patients and offer useful insights to guide subsequent personalized treatment.

Contrast-enhanced ultrasound features of hepatic sarcomatoid carcinoma different from hepatocellular carcinoma

BACKGROUND

Hepatic sarcomatoid carcinoma (HSC) is a rare malignancy of the liver. The ultrasound and clinical features of HSC have not been determined.

OBJECTIVE

To investigate and compare the ultrasound and clinical features of HSC and hepatocellular carcinoma (HCC), and to reveal the valuable features of HSC.

METHODS

The ultrasound features and clinical data of pathologically proven HSC (n = 37) were compared with HCC (n = 92) in a matching ratio of 1:4 using the propensity score (age, gender and tumor size).

RESULTS

The HSC patients were more likely to accompany with clinical symptoms and vascular invasion than HCC patients (40.5% vs 17.4%, 24.3% vs 6.5%, P < 0.05). The size of HSCs was significantly larger than that of HCCs (P < 0.05). The proportion of patients with elevated alpha-fetoprotein was significantly lower in HSC (35.1% vs 54.3%, P < 0.05). On gray-scale ultrasound images, the HSCs were more likely to demonstrate as indistinct margin and irregular shape lesions compared to HCCs (78.4% vs 48.8%; 70.3% vs 23.9%, P < 0.05). Under color Doppler flow imaging (CDFI), the blood flow signals were more frequently detected in HSC lesions (75.7% vs 56.5%, P < 0.05). Resistance index (RI) was higher in HSCs than in HCCs [0.78 (0.70,0.82) vs 0.70 (0.62,0.76), P < 0.05]. On contrast-enhanced ultrasound (CEUS), HSCs mainly showed entirety heterogeneous hyper-enhancement (48.6%), entirety homogeneous enhancement (18.9%), peripheral and internal septal enhancement (18.9%). The incidence of non-enhanced areas inside HSC lesions was higher than that inside HCC lesions (56.8% vs 31.5%, P < 0.05). During the portal venous and late phases, most of the lesions revealed hypo-enhancement in both groups, whereas earlier washout was observed in HSCs [43.0 s (30.5,58.0) vs 60.0 s (46.3,100.0), P < 0.05].

CONCLUSIONS

CEUS features are useful in preoperative and non-invasive differentiation of hepatic sarcomatoid carcinoma and hepatocellular carcinoma.

Clinical application of dual-layer spectral CT multi-parameter feature to predict microvascular invasion in hepatocellular carcinoma

OBJECTIVE

This study aimed to investigate the feasibility of using dual-layer spectral CT multi-parameter feature to predict microvascular invasion of hepatocellular carcinoma.

METHODS

This retrospective study enrolled 50 HCC patients who underwent multiphase contrast-enhanced spectral CT studies preoperatively. Combined clinical data, radiological features with spectral CT quantitative parameter were constructed to predict MVI. ROC was applied to identify potential predictors of MVI. The CT values obtained by simulating the conventional CT scans with 70 keV images were compared with those obtained with 40 keV images.

RESULTS

50 hepatocellular carcinomas were detected with 30 lesions (Group A) with microvascular invasion and 20 (Group B) without. There were significant differences in AFP,tumer size, IC, NIC,slope and effective atomic number in AP and ICrr in VP between Group A ((1000(10.875,1000),4.360±0.3105, 1.7750 (1.5350,1.8825) mg/ml, 0.1785 (0.1621,0.2124), 2.0362±0.2108,8.0960±0.1043,0.2830±0.0777) and Group B (4.750(3.325,20.425),3.190±0.2979,1.4700 (1.4500,1.5775) mg/ml, 0.1441 (0.1373,0.1490),1.8601±0.1595, 7.8105±0.7830 and 0.2228±0.0612) (all p < 0.05). Using 0.1586 as the threshold for NIC, one could obtain an area-under-curve (AUC) of 0.875 in ROC to differentiate between tumours with and without microvascular invasion. AUC was 0.625 with CT value at 70 keV and improved to 0.843 at 40 keV.

CONCLUSION

Dual-layer spectral CT provides additional quantitative parameters than conventional CT to enhance the differentiation between hepatocellular carcinoma with and without microvascular invasion. Especially, the normalized iodine concentration (NIC) in arterial phase has the greatest potential application value in determining whether microvascular invasion exists, and can offer an important reference for clinical treatment plan and prognosis assessment.

Pitfalls and strategies of Sonazoid enhanced ultrasonography in differentiating metastatic and benign hepatic lesions

OBJECTIVE

This article aims to clarify pitfalls and find strategies for the detecting and diagnosing hyperechoic liver metastases (LMs) using Sonazoid-contrast enhanced ultrasonography (Sonazoid-CEUS).

METHODS

This study was a prospective self-controlled study. Patients with hepatic lesions suspected as LMs or benign lesions were included in the study. Baseline ultrasonography (BUS) and Sonazoid-CEUS were performed on every patient. Characteristics of LMs and benign nodules were compared by chi-square test and fisher test. Factors influenced the CEUS were demonstrated by univariate analysis and multivariate logistic regression analysis.

RESULTS

54 patients were included in this study. CEUS found additional 75 LMs from 19 patients in Kupffer phase. We found hyperechoic focal liver lesions and deep seated in liver are main confounding factors in CEUS diagnosis. Sensitivity would be improved from 16.67% to 78.57%, negative predictive value (NPV) would be improved from 28.57% to 76.92% and accuracy would be improved from 37.5% to 87.50% when using rapid "wash-in" and "wash-out" as main diagnostic criteria.

CONCLUSIONS

Hyperechoic LMs especially deeply seated ones are usually not shown typical "black hole" sign in Kupffer phase. Quickly "wash-in and wash out" shows high accuracy in diagnosing malignant nodules. We highly recommend CEUS as a routing exam to detect and diagnose LMs.

Perfluorobutane application value in microwave ablation of small hepatocellular carcinoma (<3 cm)

BACKGROUND

No studies have been retrieved comparing perfluorobutane with sulfur hexafluoride for microwave ablation (MWA) in small hepatocellular carcinoma(sHCC).

OBJECTIVE

To retrospective investigate the value of perfluorobutane ultrasonography contrast agent in ultrasonography (US)-guided MWA of sHCC.

METHODS

We conducted a retrospective clinical controlled study about US-guided percutaneous MWA in patients with sHCC, and in patients undergoing intra-operative treatment with perfluorobutane or sulfur hexafluoride. In both groups, a contrast agent was injected to clear the tumor and then a needle was inserted. A 5-point needle prick difficulty score was developed to compare needle prick difficulty in the two groups of cases.

RESULTS

A total of 67 patients were included: 25 patients in group perfluorobutane, aged 41-82 (60.64±9.46), tumor size 1.1-2.8 (1.78±0.45) cm. 42 patients in group sulfur hexafluoride, aged 38-78 (62.26±9.27), with tumor size of 1.1-3.0 (1.89±0.49) cm. There was no significant difference in age or tumor size in both groups (P > 0.05). Puncture difficulty score (5-point): 2.0-2.7 (2.28±0.29) in group perfluorobutane, and 2.0-4.7 (2.95±0.85) in group sulfur hexafluoride, and the difference between the two groups was statistically significant (P < 0.05). Enhanced imaging results within 3 months after surgery: complete ablation rate was 100% (25/25) in the group perfluorobutane, 95.2% (40/42 in the group sulfur hexafluoride), with no significant difference between the two groups (P > 0.05).

CONCLUSION

Perfluorobutane kupffer phase can make the operator accurately deploy the ablation needle and reduce the difficulty of operation.

Peri-interventional LiMAx test for liver ablation - A feasibility study

BACKGROUND

Local ablation is an important treatment for liver cancer in cases of cirrhosis. Liver failure may occur after ablation, especially in advanced liver diseases. Currently, there is no standardization for peri-interventional risk assessment. The liver maximum capacity test (LiMAx) is used to assess functional liver capacity, but there is a lack of exploration of its use in this context.

OBJECTIVE

The aim of this study was to retrospectively evaluate the usefulness of peri-interventional LiMAx measurements in patients with primary or secondary liver cancer who underwent ablation treatment.

METHODS

A LiMAx test was performed at 24 hours pre- and postablation in 49 patients. Blood parameters were collected to determine liver function using MELD and ALBI scores. The results of the LiMAx test were related with these scores and to critical postintervention LiMAx values.

RESULTS

LiMAx values correlated strongly with MELD and ALBI scores before the intervention and reflected the change in liver function, as shown by an increase in scores after the intervention. Notably, LiMAx values decreased during the intervention. AUC analysis for patients at risk of reaching a critical liver level after the intervention showed a cutoff value of 186μg/kg/h.

CONCLUSIONS

The LiMAx test may be a valuable tool in liver ablation for both peri-interventional monitoring of liver function and preintervention risk assessment.

Dynamic contrast-enhanced ultrasonography with sonazoid predicts microvascular invasion in early-stage hepatocellular carcinoma

OBJECTIVE

Microvascular invasion (MVI) is an independent risk factor for the early recurrence and poor survival of hepatocellular carcinoma (HCC). This study aims to investigate the potential clinical value of dynamic contrast-enhanced ultrasound (DCE-ultrasound)-Sonazoid in pre-operatively assessing MVI in HCC.

METHODS AND MATERIALS

This single centre prospective study included 140 patients with histopathologically confirmed single HCC lesions. Patients were classified according to the post-operative pathological information presence of MVI: MVI+ group (n = 32) and MVI- group (n = 108). All patients underwent DCE-ultrasound within 1 week before surgery. The quantitative perfusion parameters of HCC lesions, margins of HCC lesions, and distal liver parenchyma were obtained and analyzed.

RESULTS

Clinicopathological (serum alpha-fetoprotein, Des-gamma-carboxyprothrombin, and pathological grade) and grayscale imaging features (tumor size) were significantly different between the MVI+ and MVI- groups (p < 0.05). Further quantitative analysis showed that when comparing the MVI+ and MVI- groups, half-decrease time and wash-out rate of HCC lesions and peak enhancement in the arterial phase of difference between the margin area of HCC and distal liver parenchyma were significantly different (p = 0.045, p = 0.035, and p = 0.023, respectively). Combining the above three quantitative parameters, the accuracy, sensitivity, specificity, positive-predictive value, and negative-predictive value were 69.3% (97/140), 37.8% (17/45), 84.3% (80/95), 53.1% (17/32), 74.1% (80/108), respectively.

CONCLUSION

DCE-ultrasound with quantitative perfusion analysis has the potential to predict MVI in HCC lesions.

ADVANCES IN KNOWLEDGE

DCE-ultrasound with quantitative perfusion analysis has the potential to predict MVI in HCC lesions.

Preoperative prediction and risk assessment of microvascular invasion in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and highly lethal tumors worldwide. Microvascular invasion (MVI) is a significant risk factor for recurrence and poor prognosis after surgical resection for HCC patients. Accurately predicting the status of MVI preoperatively is critical for clinicians to select treatment modalities and improve overall survival. However, MVI can only be diagnosed by pathological analysis of postoperative specimens. Currently, numerous indicators in serology (including liquid biopsies) and imaging have been identified to effective in predicting the occurrence of MVI, and the multi-indicator model based on deep learning greatly improves accuracy of prediction. Moreover, several genes and proteins have been identified as risk factors that are strictly associated with the occurrence of MVI. Therefore, this review evaluates various predictors and risk factors, and provides guidance for subsequent efforts to explore more accurate predictive methods and to facilitate the conversion of risk factors into reliable predictors.

Preoperative prediction of microvascular invasion in hepatocellular carcinoma using ultrasound features including elasticity

BACKGROUND

Microvascular invasion (MVI) is an important predictor of poor prognosis in patients with hepatocellular carcinoma (HCC). Accurate preoperative prediction of MVI in HCC would provide useful information to guide the choice of therapeutic strategy. Shear wave elastography (SWE) plays an important role in hepatic imaging, but its value in the preoperative prediction of MVI in HCC has not yet been proven.

AIM

To explore the value of conventional ultrasound features and SWE in the preoperative prediction of MVI in HCC.

METHODS

Patients with a postoperative pathological diagnosis of HCC and a definite diagnosis of MVI were enrolled in this study. Conventional ultrasound features and SWE features such as maximal elasticity (Emax) of HCCs and Emax of the periphery of HCCs were acquired before surgery. These features were compared between MVI-positive HCCs and MVI-negative HCCs and between mild MVI HCCs and severe MVI HCCs.

RESULTS

This study included 86 MVI-negative HCCs and 102 MVI-positive HCCs, including 54 with mild MVI and 48 with severe MVI. Maximal tumor diameters, surrounding liver tissue, color Doppler flow, Emax of HCCs, and Emax of the periphery of HCCs were significantly different between MVI-positive HCCs and MVI-negative HCCs. In addition, Emax of the periphery of HCCs was significantly different between mild MVI HCCs and severe MVI HCCs. Higher Emax of the periphery of HCCs and larger maximal diameters were independent risk factors for MVI, with odds ratios of 2.820 and 1.021, respectively.

CONCLUSION

HCC size and stiffness of the periphery of HCC are useful ultrasound criteria for predicting positive MVI. Preoperative ultrasound and SWE can provide useful information for the prediction of MVI in HCCs.

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.

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

Purpose

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

Methods

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

Results

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

Conclusion

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

Quality of radiomics for predicting microvascular invasion in hepatocellular carcinoma: a systematic review

OBJECTIVES

To comprehensively evaluate the reporting quality, risk of bias, and radiomics methodology quality of radiomics models for predicting microvascular invasion in hepatocellular carcinoma.

METHODS

A systematic search of available literature was performed in PubMed, Embase, Web of Science, Scopus, and the Cochrane Library up to January 21, 2022. Studies that developed and/or validated machine learning models based on radiomics data to predict microvascular invasion in hepatocellular carcinoma were included. These studies were reviewed by two investigators and the consensus data were used for analyzing. The reporting quality, risk of bias, and radiomics methodological quality were evaluated by Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD), Prediction model Risk of Bias Assessment Tool, and Radiomics Quality Score (RQS), respectively.

RESULTS

A total of 30 studies met eligibility criteria with 24 model developing studies and 6 model developing and external validation studies. The median overall TRIPOD adherence was 75.4% (range 56.7-94.3%). All studies were at high risk of bias with at least 2 of 20 sources of bias. Furthermore, 28 studies showed unclear risks of bias in up to 5 signaling questions because of the lack of specified reports. The median RQS score was 37.5% (range 25-61.1%).

CONCLUSION

Current radiomic models for MVI-status prediction have moderate to good reporting quality, moderate radiomics methodology quality, and high risk of bias in model development and validation.

KEY POINTS

• Current microvascular invasion prediction radiomics studies have moderate to good reporting quality, moderate radiomics methodology quality, and high risk of bias in model development and validation. • Data representativeness, feature robustness, events-per-variable ratio, evaluation metrics, and appropriate validation are five main aspects futures studies should focus more on to improve the quality of radiomics. • Both Radiomics Quality Score and Prediction model Risk of Bias Assessment Tool are needed to comprehensively evaluate a radiomics study.

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

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

Predicting glypican-3 expression in hepatocellular carcinoma: A comprehensive analysis using combined contrast-enhanced ultrasound and clinical factors

OBJECTIVE

Glypican-3 (GPC3) has emerged as a significant marker for the diagnosis and prognosis of hepatocellular carcinoma (HCC) and has garnered considerable attention as an immunotherapeutic target. In this study, we propose a combination of preoperative contrast-enhanced ultrasound (CEUS) imaging features and clinical factors to predict the positive expression of GPC3 in HCC patients.

METHODS

We retrospectively included 30 cases of GPC3-negative HCC and 115 cases of GPC3-positive HCC patients who underwent conventional ultrasound and CEUS evaluation. We assessed and compared the clinical characteristics, conventional ultrasound features, and CEUS features between the two groups of HCC patients. Based on the clinical and ultrasound features between the two groups, we developed a binary logistic regression model for predicting GPC3-positive HCC.

RESULTS

A total of 145 HCC patients were included in this study. Binary logistic regression analysis showed that AFP > 20 ng/mL (OR = 4.047; 95% CI: 1.467-11.16; p = 0.007), arterial phase hyperenhancement (APHE) (OR = 12.557; 95% CI: 3.608-43.706; p < 0.001), and asynchronous perfusion (OR = 4.209; 95% CI: 1.206-14.691; p = 0.024) were predictive factors for GPC3-positive HCC. Receiver operating characteristic (ROC) analysis was conducted to predict GPC3-positive expression. The model combining the three independent predictive factors showed good predictive performance (AUC 0.817, 95% CI: 0.731-0.902, sensitivity: 91.3%, specificity: 60.0%). This combined model demonstrated excellent discriminatory ability to predict GPC3-positive HCC.

CONCLUSION

Preoperative integration of CEUS features and clinical factors can non-invasively and effectively identify GPC3-positive HCC patients, providing valuable assistance in making personalized treatment decisions.

Protocol of Kupffer phase whole liver scan for metastases: A single-center prospective study

Introduction

As the presence of hepatic metastases is very important to cancer patients' clinical stage which would directly affect the selection and application of anti-cancer treatments. Although conventional ultrasound is commonly performed as a screening tool, most of the examinations have relatively poor sensitivity and specificity for detecting liver metastases. Contrast-enhanced ultrasound (CEUS) with Sonazoid has been reported to have the advantage of the diagnosis and therapeutic support of focal hepatic lesions and its specific Kupffer phase whole liver scan (KPWLS) is believed to be sensitive to detect liver metastases. And the purpose of this study is to determine the number, size, location and diagnosis of metastatic lesions, and to compare the results with conventional ultrasound and contrast-enhanced computed tomography (CECT), thus to clarify the application value, indications of Sonazoid-CEUS in screening liver metastasis.

Methods and analysis

Kupffer phase whole liver scan for metastases (KPWLSM) is a self-control, blind map-reading, single-center, prospective superiority trial. Approved by the institutional review committee, the study period is planned to be from 1 January 2022 to 31 December 2025. Our study will include 330 patients with history of malignant tumors that cling to metastasize to liver. All patients will undergo the examinations of conventional ultrasound, Sonazoid-CEUS, and contrast-enhanced magnetic resonance imaging (CEMRI), and 65 of them should have additional CECT scans. The primary endpoint is the comparative analysis of the numbers of detected liver metastatic lesions among Sonazoid-CEUS, conventional ultrasound and CECT in screening liver metastases. Subjective conditions of patient after injection of Sonazoid will be followed up 3 and 30 days after KPWLSM, and any short-term and long-term adverse events are to be recorded with telephone interviews.

Ethics and dissemination

This study has been granted by the Ethics Committee of Shanghai Jiao Tong University Affiliated Sixth People's Hospital (Approval No: 2021-197). When the KPWLSM is completed, we will publish it in an appropriate journal to promote further widespread use.

Registration

Trial Registration Number and Date of Registration: Chinese Clinical Trial Registry, ChiCTR2100054385, December 16, 2021.