Evaluation of the Therapeutic Effect of Adjuvant Transcatheter Arterial Chemoembolization Based on Ki67 After Hepatocellular Carcinoma Surgery

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.

Diagnostic value of radiomics in predicting Ki-67 and cytokeratin 19 expression in hepatocellular carcinoma: a systematic review and meta-analysis

Background

Radiomics have been increasingly used in the clinical management of hepatocellular carcinoma (HCC), such as markers prediction. Ki-67 and cytokeratin 19 (CK-19) are important prognostic markers of HCC. Radiomics has been introduced by many researchers in the prediction of these markers expression, but its diagnostic value remains controversial. Therefore, this review aims to assess the diagnostic value of radiomics in predicting Ki-67 and CK-19 expression in HCC.

Methods

Original studies were systematically searched in PubMed, EMBASE, Cochrane Library, and Web of Science from inception to May 2023. All included studies were evaluated by the radiomics quality score. The C-index was used as the effect size of the performance of radiomics in predicting Ki-67and CK-19 expression, and the positive cutoff values of Ki-67 label index (LI) were determined by subgroup analysis and meta-regression.

Results

We identified 34 eligible studies for Ki-67 (18 studies) and CK-19 (16 studies). The most common radiomics source was magnetic resonance imaging (MRI; 25/34). The pooled C-index of MRI-based models in predicting Ki-67 was 0.89 (95% CI:0.86-0.92) in the training set, and 0.87 (95% CI: 0.82-0.92) in the validation set. The pooled C-index of MRI-based models in predicting CK-19 was 0.86 (95% CI:0.81-0.90) in the training set, and 0.79 (95% CI: 0.73-0.84) in the validation set. Subgroup analysis suggested Ki-67 LI cutoff was a significant source of heterogeneity (I 2 = 0.0% P>0.05), and meta-regression showed that the C-index increased as Ki-67 LI increased.

Conclusion

Radiomics shows promising diagnostic value in predicting positive Ki-67 or CK-19 expression. But lacks standardized guidelines, which makes the model and variables selection dependent on researcher experience, leading to study heterogeneity. Therefore, standardized guidelines are warranted for future research.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023427953.

Added value of CE-CT radiomics to predict high Ki-67 expression in hepatocellular carcinoma

BACKGROUND

This study aimed to develop a computed tomography (CT) model to predict Ki-67 expression in hepatocellular carcinoma (HCC) and to examine the added value of radiomics to clinico-radiological features.

METHODS

A total of 208 patients (training set, n = 120; internal test set, n = 51; external validation set, n = 37) with pathologically confirmed HCC who underwent contrast-enhanced CT (CE-CT) within 1 month before surgery were retrospectively included from January 2014 to September 2021. Radiomics features were extracted and selected from three phases of CE-CT images, least absolute shrinkage and selection operator regression (LASSO) was used to select features, and the rad-score was calculated. CE-CT imaging and clinical features were selected using univariate and multivariate analyses, respectively. Three prediction models, including clinic-radiologic (CR) model, rad-score (R) model, and clinic-radiologic-radiomic (CRR) model, were developed and validated using logistic regression analysis. The performance of different models for predicting Ki-67 expression was evaluated using the area under the receiver operating characteristic curve (AUROC) and decision curve analysis (DCA).

RESULTS

HCCs with high Ki-67 expression were more likely to have high serum α-fetoprotein levels (P = 0.041, odds ratio [OR] 2.54, 95% confidence interval [CI]: 1.04-6.21), non-rim arterial phase hyperenhancement (P = 0.001, OR 15.13, 95% CI 2.87-79.76), portal vein tumor thrombus (P = 0.035, OR 3.19, 95% CI: 1.08-9.37), and two-trait predictor of venous invasion (P = 0.026, OR 14.04, 95% CI: 1.39-144.32). The CR model achieved relatively good and stable performance compared with the R model (AUC, 0.805 [95% CI: 0.683-0.926] vs. 0.678 [95% CI: 0.536-0.839], P = 0.211; and 0.805 [95% CI: 0.657-0.953] vs. 0.667 [95% CI: 0.495-0.839], P = 0.135) in the internal and external validation sets. After combining the CR model with the R model, the AUC of the CRR model increased to 0.903 (95% CI: 0.849-0.956) in the training set, which was significantly higher than that of the CR model (P = 0.0148). However, no significant differences were found between the CRR and CR models in the internal and external validation sets (P = 0.264 and P = 0.084, respectively).

CONCLUSIONS

Preoperative models based on clinical and CE-CT imaging features can be used to predict HCC with high Ki-67 expression accurately. However, radiomics cannot provide added value.

Noninvasive Prediction of Ki-67 Expression in Hepatocellular Carcinoma Using Machine Learning-Based Ultrasomics: A Multicenter Study

OBJECTIVES

To investigate the ability of ultrasomics to predict Ki-67 expression in hepatocellular carcinoma (HCC).

METHODS

A total of 244 patients from three hospitals were retrospectively recruited (training dataset, n = 168; test dataset, n = 43; and validation dataset, n = 33). Lesion segmentation of the ultrasound images was performed manually by two radiologists. In total, 1409 ultrasomics features were extracted. Feature selection was conducted using the intra-class correlation coefficient, variance threshold, mutual information, and recursive feature elimination plus eXtreme Gradient Boosting. The support vector machine was combined with the learning curve and grid search parameter tuning to construct the clinical, ultrasomics, and combined models. The predictive performance of the models was assessed using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity and accuracy.

RESULTS

The ultrasomics model performed well on the training, test, and validation datasets. The AUC (95% confidence interval [CI]) for these datasets were 0.955 (0.912-0.981), 0.861 (0.721-0.947), and 0.665 (0.480-0.819), respectively. The combination of ultrasomics and clinical features significantly improved model performance on all three datasets. The AUC (95% CI), sensitivity, specificity, and accuracy were 0.986 (0.955-0.998), 0.973, 0.840, and 0.869 on the training dataset; 0.871 (0.734-0.954), 0.750, 0.829, and 0.814 on the test dataset; and 0.742 (0.560-0.878), 0.714, 0.808, and 0.788 on the validation dataset, respectively.

CONCLUSIONS

Ultrasomics was proved to be a potential noninvasive method to predict Ki-67 expression in HCC.

Diffusion-Weighted Imaging as a Quantitative Imaging Biomarker for Predicting Proliferation Rate in Hepatocellular Carcinoma: Developing a Radiomics Nomogram

PURPOSE

This study aimed to explore the predictive performance of diffusion-weighted imaging with apparent diffusion coefficient map in predicting the proliferation rate of hepatocellular carcinoma and to develop a radiomics-based nomogram.

METHODS

This was a single-center retrospective study. A total of 110 patients were enrolled. The sample included 38 patients with low Ki67 expression (Ki67 ≤10%) and 72 with high Ki67 expression (Ki67 >10%) as demonstrated by surgical pathology. Patients were randomly divided into either a training (n = 77) or validation (n = 33) cohort. Diffusion-weighted imaging with apparent diffusion coefficient maps was used to extract radiomic features and the signal intensity values of tumor (SItumor), normal liver (SIliver), and background noise (SIbackground) from all samples. Subsequently, the clinical model, radiomic model, and fusion model (with clinical data and radiomic signature) were developed and validated.

RESULTS

The area under the curve (AUC) of the clinical model for predicting the Ki67 expression including serum α-fetoprotein level (P = 0.010), age (P = 0.015), and signal noise ratio (P = 0.026) was 0.799 and 0.715 in training and validation cohorts, respectively. The AUC of the radiomic model constructed by 9 selected radiomic features was 0.833 and 0.772 in training and validation cohorts, respectively. The AUC of the fusion model containing serum α-fetoprotein level (P = 0.011), age (P = 0.019), and rad score (P < 0.001) was 0.901 and 0.781 in training and validation cohorts, respectively.

CONCLUSIONS

Diffusion-weighted imaging as a quantitative imaging biomarker can predict Ki67 expression level in hepatocellular carcinoma across various models.

Therapeutic effect of postoperative adjuvant transcatheter arterial chemoembolization based on the neutrophil-to-lymphocyte ratio

Aim

To evaluate the feasibility of the preoperative neutrophil-to-lymphocyte ratio (NLR) as an index to guide postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE) in patients with liver cancer.

Methods

We recruited a total of 166 patients with liver cancer who underwent surgery alone or surgery plus PA-TACE between January 2013 and June 2017 and compared the 1, 2, and 3-year recurrence-free survival (RFS) and overall survival (OS) between patients with high and low NLRs, surgery and surgery plus PA-TACE groups, and relevant subgroups using the Kaplan-Meier method. We also evaluated the independent factors affecting the prognosis of liver cancer after surgery using a Cox risk ratio model and correlation between NLR levels and high-risk recurrence factors of liver cancer with logistic regression analysis.

Results

The 1, 2, and 3-year RFS rates were all significantly higher in the low-NLR group compared to the high-NLR group (P < 0.05). However, the 1, 2, and 3-year OS rates were similar in the low- and high-NLR groups (P > 0.05). After propensity score matching, the 1, 2, and 3-year RFS and OS rates were significantly better in patients treated with surgery plus PA-TACE compared with surgery alone (P < 0.05). The 1, 2, and 3-year RFS and OS rates were also significantly better in the surgery plus PA-TACE subgroup compared with the surgery-alone subgroup in the high-NLR group (P < 0.05), but there was no significant difference in RFS or OS between the surgery plus PA-TACE and surgery-alone subgroups at 1, 2, and 3 years in the low-NLR group (P > 0.05). Multivariate analysis in the high-NLR group showed that a poorly differentiated or undifferentiated tumor was an independent risk factor for postoperative RFS. Multiple tumors were an independent risk factor for postoperative OS (P < 0.05), while PA-TACE was an independent protective factor for postoperative RFS and OS (P < 0.05). In the low-NLR group, AFP > 400 µg/L was an independent risk factor for postoperative OS (P < 0.05). Multivariate logistic regression indicated that patients with a maximum tumor diameter of >5 cm were at increased risk of having high NLR levels compared to patients with a maximum tumor diameter of <5 cm (P < 0.05).

Conclusion

PA-TACE can improve the prognosis of patients with a high preoperative NLR (≥2.5), but has no obvious benefit in patients with low preoperative NLR (<2.5). This may provide a reference for clinical selection of PA-TACE.

Prognostic Value of GPNMB, EGFR, p-PI3K, and Ki-67 in Patients with Esophageal Squamous Cell Carcinoma

Background. GPNMB is a newly discovered tumour-promoting factor that may promote tumour cell progression by activating the PI3K/AKT pathway by EGFR. However, there are insufficient studies about GPNMB in ESCC. This study investigated the relationship between GPNMB and EGFR/PI3K pathway genes in ESCC. Methods. The expression levels of GPNMB, EGFR, p-PI3K, and Ki-67 were examined using immunohistochemistry. Statistical analysis was done by SPSS 22.0 and R. Results. GPNMB mRNA expression is higher in ESCC compared with paracancerous tissues. The expression of EGFR, PIK3CA, PIK3CB, and AKT1 was increased in GPNMB upregulated samples. GPNMB expression was positively correlated with EGFR, p-PI3K, and Ki-67 expression. GPNMB was expressed higher in the AJCC III stage, lymph node metastasis, and moderately poorly differentiated patients. EGFR was higher expressed in patients with vascular invasion; p-PI3K expression in Kazak was higher than that in Han; Ki-67 expression was higher in $\text{tumour}\text{size}\ge 3\text{cm}$ . Patients with high expression of GPNMB, p-PI3K, and Ki-67 had worse OS. p-PI3K, Ki-67, nerve invasion, and lymphatic metastasis were independent risk factors, and postoperative adjuvant therapy was a protective factor in ESCC. Conclusion. As a tumour-promoting factor, GPNMB is expected to be a potential target for ESCC.

Added Value of Viscoelasticity for MRI-Based Prediction of Ki-67 Expression of Hepatocellular Carcinoma Using a Deep Learning Combined Radiomics (DLCR) Model

Simple Summary

This study aimed to explore the added value of magnetic resonance elastography (MRE) in the prediction of Ki-67 expression in hepatocellular carcinoma (HCC) using a deep learning combined radiomics (DLCR) model. A total of 108 histopathology-proven HCC patients who underwent preoperative MRI and MR elastography were included. All the patients were divided into training and validation cohorts. An independent cohort including 43 patients was included for testing. A DLCR model was proposed to predict the expression of Ki-67 with conventional MRI (cMRI) as inputs. The images of shear wave speed (c-map) and phase angle (φ-map) derived from MRE were also fed into the DLCR model. Experimental results show that both c and φ values were ranked within the top six features for Ki-67 prediction with random forest selection, which revealed the value of MRE-based viscosity for the assessment of the tumor proliferation status in HCC. The model with all modalities (MRE, AFP, and cMRI) as inputs achieved the highest AUC of 0.90 ± 0.03 (CI: 0.89–0.91) in the validation cohort. The same finding was observed in the independent testing cohort with an AUC of 0.83 ± 0.03 (CI: 0.82–0.84). MRE-based c and φ-maps can serve as important parameters to assess the tumor proliferation status in HCC.

Abstract

This study aimed to explore the added value of viscoelasticity measured by magnetic resonance elastography (MRE) in the prediction of Ki-67 expression in hepatocellular carcinoma (HCC) using a deep learning combined radiomics (DLCR) model. This retrospective study included 108 histopathology-proven HCC patients (93 males; age, 59.6 ± 11.0 years) who underwent preoperative MRI and MR elastography. They were divided into training (n = 87; 61.0 ± 9.8 years) and testing (n = 21; 60.6 ± 10.1 years) cohorts. An independent validation cohort including 43 patients (60.1 ± 11.3 years) was included for testing. A DLCR model was proposed to predict the expression of Ki-67 with cMRI, including T2W, DW, and dynamic contrast enhancement (DCE) images as inputs. The images of the shear wave speed (c-map) and phase angle (φ-map) derived from MRE were also fed into the DLCR model. The Ki-67 expression was classified into low and high groups with a threshold of 20%. Both c and φ values were ranked within the top six features for Ki-67 prediction with random forest selection, which revealed the value of MRE-based viscosity for the assessment of tumor proliferation status in HCC. When comparing the six CNN models, Xception showed the best performance for classifying the Ki-67 expression, with an AUC of 0.80 ± 0.03 (CI: 0.79–0.81) and accuracy of 0.77 ± 0.04 (CI: 0.76–0.78) when cMRI were fed into the model. The model with all modalities (MRE, AFP, and cMRI) as inputs achieved the highest AUC of 0.90 ± 0.03 (CI: 0.89–0.91) in the validation cohort. The same finding was observed in the independent testing cohort, with an AUC of 0.83 ± 0.03 (CI: 0.82–0.84). The shear wave speed and phase angle improved the performance of the DLCR model significantly for Ki-67 prediction, suggesting that MRE-based c and φ-maps can serve as important parameters to assess the tumor proliferation status in HCC.

Outcomes of postoperative adjuvant transarterial chemoembolization for hepatocellular carcinoma according to the Ki67 index

Aim: To assess whether Ki67 is related to the efficacy of postoperative adjuvant transarterial chemoembolization (PA-TACE) in hepatocellular carcinoma patients at high risk of postsurgical recurrence. Methods: A total of 716 patients undergoing surgical resection with or without PA-TACE were retrospectively enrolled. Immunohistochemistry was used to analyze Ki67 expression. Results: There was no significant difference in tumor-free survival between patients who underwent resection with or without chemoembolization. However, chemoembolization was associated with significantly higher tumor-free survival rates among patients with 'low' (<30%) or 'moderate' (30-59%) levels of Ki67. Patients highly expressing Ki67 displayed higher rates of overall recurrence, earlier recurrence, multiple intrahepatic recurrence and extrahepatic metastasis. Conclusion: In patients with relatively high Ki67 levels, PA-TACE does not appear to improve outcomes.

Adjuvant Transarterial Chemoembolization Following Curative-Intent Hepatectomy Versus Hepatectomy Alone for Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

The role of adjuvant transarterial chemoembolization (TACE) for patients with resectable hepatocellular carcinoma (HCC) undergoing hepatectomy is currently unclear. We performed a systematic review of the literature using the MEDLINE, Embase, and Cochrane Library databases. Random-effects meta-analysis was carried out to compare the overall survival (OS) and recurrence-free survival (RFS) of patients with resectable HCC undergoing hepatectomy followed by adjuvant TACE vs. hepatectomy alone in randomized controlled trials (RCTs). The risk of bias was assessed using the Risk of Bias 2.0 tool. Meta-regression analyses were performed to explore the effect of hepatitis B viral status, microvascular invasion, type of resection (anatomic vs. parenchymal-sparing), and tumor size on the outcomes. Ten eligible RCTs, reporting on 1216 patients in total, were identified. The combination of hepatectomy and adjuvant TACE was associated with superior OS (hazard ratio (HR): 0.66, 95% confidence interval (CI): 0.52 to 0.85; p < 0.001) and RFS (HR: 0.70, 95% CI: 0.56 to 0.88; p < 0.001) compared to hepatectomy alone. There were significant concerns regarding the risk of bias in most of the included studies. Overall, adjuvant TACE may be associated with an oncologic benefit in select HCC patients. However, the applicability of these findings may be limited to Eastern Asian populations, due to the geographically restricted sample. High-quality multinational RCTs, as well as predictive tools to optimize patient selection, are necessary before adjuvant TACE can be routinely implemented into standard practice. PROSPERO Registration ID: CRD42021245758.