Therapeutic analysis of 632 cases treated by transcatheter arterial chemoembolization combined with ablation in hepatocellular carcinoma: A retrospective study.

OBJECTIVES: This study aims to analyze the efficacy of transcatheter arterial chemoembolization (TACE) combined with radiofrequency ablation (RFA), microwave ablation (MWA), and cryoablation (CA) in hepatocellular carcinoma (HCC). METHODS: A retrospective analysis was conducted on 632 patients with HCC at Barcelona Clinic Liver Cancer Staging (BCLC) System stages 0, A, and B from Beijing You'an Hospital affiliated with Capital Medical University. The primary outcomes analyzed were overall survival (OS) and progression-free survival (PFS), while the secondary outcomes included one-, three-, and five-year OS rates among different groups. RESULTS: The median follow-up period for 632 cases identified with HCC was 52.1 months (range: 3-162 months), while 127 patients died during follow-up. The one-, three-, and five-year OS rates were 97.1 %, 89.5 %, and 80.4 %, respectively. Moreover, the one-, three-, and five-year PFS rates were 58.1 %, 29.3 %, and 19.8 %, respectively. Multivariate analysis revealed that the BCLC stages and complete ablation were independent predictors of OS and PFS (all p < 0.05). Subgroup analysis showed no difference in OS rate among TACE-RFA, TACE-MWA, and TACE-CA groups, but TACE-CA showed better efficacy in improving the PFS rate (all p < 0.05). CONCLUSIONS: The combination of TACE and ablation is effective in early-stage HCC and BCLC stage B. Complete ablation and BCLC stages are significant prognostic factors for PFS and OS. Further research, including randomized controlled trials, is needed to validate these findings.

Immune checkpoint inhibitors and anti-vascular endothelial growth factor antibody/tyrosine kinase inhibitors with or without transarterial chemoembolization as first-line treatment for advanced hepatocellular carcinoma (CHANCE2201): a target trial emulation study.

Background: The role of transarterial chemoembolization (TACE) in the treatment of advanced hepatocellular carcinoma (HCC) is unconfirmed. This study aimed to assess the efficacy and safety of immune checkpoint inhibitors (ICIs) plus anti-vascular endothelial growth factor (anti-VEGF) antibody/tyrosine kinase inhibitors (TKIs) with or without TACE as first-line treatment for advanced HCC. Methods: This nationwide, multicenter, retrospective cohort study included advanced HCC patients receiving either TACE with ICIs plus anti-VEGF antibody/TKIs (TACE-ICI-VEGF) or only ICIs plus anti-VEGF antibody/TKIs (ICI-VEGF) from January 2018 to December 2022. The study design followed the target trial emulation framework with stabilized inverse probability of treatment weighting (sIPTW) to minimize biases. The primary outcome was overall survival (OS). Secondary outcomes included progression-free survival (PFS), objective response rate (ORR), and safety. The study is registered with ClinicalTrials.gov, NCT05332821. Findings: Among 1244 patients included in the analysis, 802 (64.5%) patients received TACE-ICI-VEGF treatment, and 442 (35.5%) patients received ICI-VEGF treatment. The median follow-up time was 21.1 months and 20.6 months, respectively. Post-application of sIPTW, baseline characteristics were well-balanced between the two groups. TACE-ICI-VEGF group exhibited a significantly improved median OS (22.6 months [95% CI: 21.2-23.9] vs 15.9 months [14.9-17.8]; P < 0.0001; adjusted hazard ratio [aHR] 0.63 [95% CI: 0.53-0.75]). Median PFS was also longer in TACE-ICI-VEGF group (9.9 months [9.1-10.6] vs 7.4 months [6.7-8.5]; P < 0.0001; aHR 0.74 [0.65-0.85]) per Response Evaluation Criteria in Solid Tumours (RECIST) version 1.1. A higher ORR was observed in TACE-ICI-VEGF group, by either RECIST v1.1 or modified RECIST (41.2% vs 22.9%, P < 0.0001; 47.3% vs 29.7%, P < 0.0001). Grade ≥3 adverse events occurred in 178 patients (22.2%) in TACE-ICI-VEGF group and 80 patients (18.1%) in ICI-VEGF group. Interpretation: This multicenter study supports the use of TACE combined with ICIs and anti-VEGF antibody/TKIs as first-line treatment for advanced HCC, demonstrating an acceptable safety profile. Funding: National Natural Science Foundation of China, National Key Research and Development Program of China, Jiangsu Provincial Medical Innovation Center, Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, and Nanjing Life Health Science and Technology Project.

Individual surveillance by competing risk model for patients with hepatocellular carcinoma occurrence in all-cause cirrhosis.

PURPOSE: It was of great significance to identify someone with a high risk of hepatocellular carcinoma (HCC) occurrence and make a diagnosis as early as possible. Therefore, we aimed to develop and validate a new, objective, and accurate prediction model, and convert it into a nomogram to make a personalized prediction of cancer occurrence in cirrhotic patients with different etiologies. METHODS: The present study included 938 patients with cirrhosis from January 1, 2011, to December 31, 2012. Patients were prospectively followed-up until January 1, 2018. We used a competing risk model and the Fine-Gray test to develop and validate the prediction model and to plot a nomogram based on the model established. RESULTS: At the end of follow-up, 202 (21.5%) patients developed HCC, with a 5-year incidence of 19.0% (corrected for competing risk model). Based on the competing risk regression method, we built a prediction model including age, gender, etiology, lymphocyte, and A/G ratio. Three groups with different risks were generated on account of tertiles of the 5-year risk predicted by the model. The cumulative 1-, 3-, and 5-year incidences of HCC were 2.0%, 20.8%, and 42.3% in high-risk group, 0.9%, 10.1%, and 17.7% in medium-risk group, and 0%, 2.0%, 8.5% in low-risk group (P < 0.001). The model showed excellent discrimination and calibration in predicting the risk of HCC occurrence in patients with all-cause cirrhosis. CONCLUSION: The model could make an individual prediction of cancer occurrence and stratify patients based on predicted risk, regardless of the causes of cirrhosis.

Effect of HBsAg expression in liver tissue on prognosis of hepatocellular carcinoma after minimally invasive interventional therapy.

Background: The aim of this study was to investigate the association between pathologic markers and prognosis in patients with hepatocellular carcinoma who received transcatheter chemoembolization combined with locoregional ablation therapy. Methods: This retrospective study included 111 hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC). All patients underwent transcatheter arterial chemoembolization (TACE) combined with locoregional ablation therapy, and received core needle biopsy before therapy in Beijing You 'an Hospital affiliated to Capital Medical University from January 1, 2013 to December 31, 2016. Demographic, pathological indicators and clinical laboratory data were collected. The cumulative recurrence-free survival (RFS) and overall survival (OS) were calculated and compared by Kaplan-Meier method and Log-rank test, and Cox proportional risk model was used to screen for independent predictors of recurrence and long-term prognosis in HCC patients. Results: There was a correlation between HBsAg expression in liver tissue and prognosis of HCC patients. Patients with negative HBsAg expression had longer 1-,3- and 5-year RFS rates than positive HBsAg expression (78.3%, 43.5%, 30.4% and 58.5%, 24.5%, 17.0%, P=0.018). Meanwhile,the postoperative 1-,3-and 5-year OS rates of HCC patients in the negative HBsAg expression group were significantly higher than those of HCC patients in the positive HBsAg expression group (100%, 89.1%, 80.4% and 100%, 75.5%, 58.5%, P=0.008). Conclusions: The prognosis of patients with hepatocellular carcinoma with negative HBsAg expression was better than that with positive HBsAg expression. Accordingly, the expression of the liver HBsAg before combined therapy was a prognostic indicator for OS and RFS. For patients with liver HBsAg positive, follow-up should be strengthened and corresponding intervention measures should be taken to improve prognosis.

Transarterial chemoembolization with PD-(L)1 inhibitors plus molecular targeted therapies for hepatocellular carcinoma (CHANCE001).

There is considerable potential for integrating transarterial chemoembolization (TACE), programmed death-(ligand)1 (PD-[L]1) inhibitors, and molecular targeted treatments (MTT) in hepatocellular carcinoma (HCC). It is necessary to investigate the therapeutic efficacy and safety of TACE combined with PD-(L)1 inhibitors and MTT in real-world situations. In this nationwide, retrospective, cohort study, 826 HCC patients receiving either TACE plus PD-(L)1 blockades and MTT (combination group, n = 376) or TACE monotherapy (monotherapy group, n = 450) were included from January 2018 to May 2021. The primary endpoint was progression-free survival (PFS) according to modified RECIST. The secondary outcomes included overall survival (OS), objective response rate (ORR), and safety. We performed propensity score matching approaches to reduce bias between two groups. After matching, 228 pairs were included with a predominantly advanced disease population. Median PFS in combination group was 9.5 months (95% confidence interval [CI], 8.4-11.0) versus 8.0 months (95% CI, 6.6-9.5) (adjusted hazard ratio [HR], 0.70, P = 0.002). OS and ORR were also significantly higher in combination group (median OS, 19.2 [16.1-27.3] vs. 15.7 months [13.0-20.2]; adjusted HR, 0.63, P = 0.001; ORR, 60.1% vs. 32.0%; P < 0.001). Grade 3/4 adverse events were observed at a rate of 15.8% and 7.5% in combination and monotherapy groups, respectively. Our results suggest that TACE plus PD-(L)1 blockades and MTT could significantly improve PFS, OS, and ORR versus TACE monotherapy for Chinese patients with predominantly advanced HCC in real-world practice, with an acceptable safety profile.

A multi-scale, multi-region and attention mechanism-based deep learning framework for prediction of grading in hepatocellular carcinoma.

BACKGROUND: Histopathological grading is a significant risk factor for postsurgical recurrence in hepatocellular carcinoma (HCC). Preoperative knowledge of histopathological grading could provide instructive guidance for individualized treatment decision-making in HCC management. PURPOSE: This study aims to develop and validate a newly proposed deep learning model to predict histopathological grading in HCC with improved accuracy. METHODS: In this dual-centre study, we retrospectively enrolled 384 HCC patients with complete clinical, pathological and radiological data. Aiming to synthesize radiological information derived from both tumour parenchyma and peritumoral microenvironment regions, a modelling strategy based on a multi-scale and multi-region dense connected convolutional neural network (MSMR-DenseCNNs) was proposed to predict histopathological grading using preoperative contrast enhanced computed tomography (CT) images. Multi-scale inputs were defined as three-scale enlargement of an original minimum bounding box in width and height by given pixels, which correspondingly contained more peritumoral analysis areas with the enlargement. Multi-region inputs were defined as three regions of interest (ROIs) including a squared ROI, a precisely delineated tumour ROI, and a peritumoral tissue ROI. The DenseCNN structure was designed to consist of a shallow feature extraction layer, dense block module, and transition and attention module. The proposed MSMR-DenseCNN was pretrained by the ImageNet dataset to capture basic graphic characteristics from the images and was retrained by the collected retrospective CT images. The predictive ability of the MSMR-DenseCNN models on triphasic images was compared with a conventional radiomics model, radiological model and clinical model. RESULTS: MSMR-DenseCNN applied to the delayed phase (DP) achieved the highest area under the curve (AUC) of 0.867 in the validation cohort for grading prediction, outperforming those on the arterial phase (AP) and portal venous phase (PVP). Fusion of the results on triphasic images did not increase the predictive ability, which underscored the role of DP for grading prediction. Compared with a single-scale and single-region network, the DP-phase based MSMR-DenseCNN model remarkably raised sensitivity from 67.4% to 75.5% with comparable specificity of 78.6%. MSMR-DenseCNN on DP defeated conventional radiomics, radiological and clinical models, where the AUCs were correspondingly 0.765, 0.695 and 0.612 in the validation cohort. CONCLUSIONS: The MSMR-DenseCNN modelling strategy increased the accuracy for preoperative prediction of grading in HCC, and enlightens similar radiological analysis pipelines in a variety of clinical scenarios in HCC management.

Interim efficacy and safety of PD-1 inhibitors in preventing recurrence of hepatocellular carcinoma after interventional therapy.

Introduction: Locoregional interventional therapy including transcatheter arterial chemoembolization (TACE) and ablation are the current standard of treatment for early-to-mid-stage hepatocellular carcinoma (HCC). However, questions remain unanswered regarding the management of recurrence after locoregional treatment. PD-1 inhibitors can block inhibitory signals of T-cell activation and proliferation to reduce the recurrence. We conducted a single-arm phase 2 trial to evaluate the efficacy and safety of PD-1 inhibitors following locoregional interventional therapy in HCC patients with high recurrence risk guided by our novel scoring system. Methods: Patients enrolled initially treated by TACE combined with ablation, then willingly joined the experimental group. One month later, they received the anti-PD-1 adjuvant therapy (intravenous injection of 200 mg), which was repeated every 3 weeks for a total of 4 or 8 cycles. Within this same period, other patients were screened into the control group to match the experimental group by 1:1 based on the propensity score matching method (PSM). The primary endpoint was relapse-free survival (RFS). Secondary endpoints included overall survival (OS) recurrence modality, safety, and quality of life. Result: At the time of data cutoff, the median RFS of the control group was 7.0 months while the experimental group had not reached it. Moreover, the 1-year RFS rate was 73.3% in the experimental group and 46.7% in the control group, showing a significant difference (P =0.02). The rate of local tumor progression in the experimental group was clearly lower than that in the control group (P = 0.027). Benefits associated with anti-PD-1 adjuvant therapy were observed in patients with multiple tumors and tumor size ≤2cm. Univariate and multivariate analyses demonstrated that anti-PD-1 adjuvant therapy was an independent favorable prognostic factor for RFS in HCC patients. The most frequent AE observed in this study was RCCEP, and other AEs included diarrhea, hepatotoxicity, rash, pruritus, and fatigue. The incidence of GRADE ≥3 AE and withdrawal in this study was low with no deaths recorded. Conclusions: Interim analysis from the study suggest the addition of anti-PD-1 adjuvant therapy after TACE combined with ablation could significantly prolong RFS with controllable safety for early-to-mid-stage HCC patients with high recurrence risk.

Percutaneous thermal ablation combined with transcatheter arterial chemoembolization for hepatitis C virus-related hepatocellular carcinoma: Efficacy and survival.

Objective: The aim of this study was to investigate the efficacy and survival of Hepatitis C virus (HCV) -related hepatocellular carcinoma (HCC) undergoing percutaneous thermal ablation combined with transcatheter arterial chemoembolization (TACE). Methods: A total of 83 HCV-related HCC patients who were treated with percutaneous thermal ablation combined with TACE were retrospectively analyzed. The demographic and clinical data were collected. The overall survival (OS) and recurrence free survival (RFS) rates were assessed by the Kaplan-Meier method. Univariate and multivariate Cox regression analysis was used to assess independent risk factors of OS and RFS. Results: 92.8% patients (77/83) and 96.6% (170/176) tumor lesions achieved complete response (CR) 1 month after all treatment, and 10.8% (9/83) patients had minor complications. The median OS was 60 months (95% confidence interval (CI)= 48.0-72.0), and the 1-, 2-, 3-, 5- and 10-year cumulative OS rates were 94%, 78.3%, 72.3%, 43.4% and 27.5%, respectively. The cumulative RFS rates at 1-, 2-, 3- and 5-year were 74.7%, 49.3%, 30.7% and 25.3%, respectively. Sex (HR =0.529, P=0.048), ablation result (HR=5.824, P=0.000) and Albumin-bilirubin (ALBI) score (HR=2.725, P=0.011) were independent prognostic factors for OS. Alpha-fetoprotein (AFP) (HR =2.360, P = 0.005) and tumor number(HR=2.786, P=0.000) were independent prognostic factors for RFS. Conclusions: Percutaneous thermal ablation combined with TACE is a safe and effective treatment for HCV-related HCC. Sex, ablation result and ALBI are significant prognostic factors for OS. AFP and tumor number are significant prognostic factors for RFS.

Preoperatively predicting early response of HCC to TACE using clinical indicators and MRI features.

BACKGROUND: We aimed to evaluate the value of using preoperative magnetic resonance imaging (MRI) features and clinical indicators to predict the early response of hepatocellular carcinoma (HCC) to transcatheter arterial chemoembolization (TACE). We also aimed to establish a preoperative prediction model. METHODS: We retrospectively reviewed data of 111 patients with HCC who underwent magnetic resonance imaging (MRI) before the first TACE and underwent MRI or computed tomography between 30 and 60 days after TACE. We used the modified response evaluation criteria in solid tumors for evaluating the TACE response. We used univariate and multivariate logistic regression analyses to identify independent predictors based on MRI features and clinical indicators. Moreover, receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of the prediction model and each independent predictor. RESULTS: Among the 111 included patients, 85 were men (76.6%). Patient age was 31-86 years (average age, 61.08 ± 11.50 years). After the first treatment session, 56/111 (50.5%) patients showed an objective response (complete response + partial response), whereas the remaining showed non-response (stable disease + local progressive disease). In the univariate analysis, we identified irregular margins, number of nodules, and satellite nodules as predictors of early objective response. However, in the multivariate logistic regression analysis, irregular margins, number of nodules and pretreatment platelet were identified as the independent predictors of early objective response. A combined prediction model was then established, which factored in irregular margins, the number of nodules, and the pretreatment platelet count. This model showed good diagnostic performance (area under the ROC curve = 0.755), with the sensitivity, specificity, positive predictive value, and negative predictive value being 78.6%, 69.1%, 72.1%, and 76.0%, respectively. CONCLUSIONS: Irregular margins, the number of nodules and the pretreatment platelet count are independent predictors of the early response of HCC to TACE. Our clinical combined model can provide a superior predictive power to a single indicator.

The monocyte to lymphocyte ratio not only at baseline but also at relapse predicts poor outcomes in patients with hepatocellular carcinoma receiving locoregional therapy.

BACKGROUND: Monocyte to lymphocyte ratio (MLR) represents a pro-inflammatory immune microenvironment. The aim of this study was to elucidate the effect of MLR and subsequent MLR when relapse occurred (R-MLR) on prognosis for hepatocellular carcinoma (HCC) after transcatheter arterial chemoembolization (TACE) combined with ablation. METHODS: A prospective analysis was conducted on 606 patients with HCC who were treated with TACE combined with local ablation in Beijing You'an Hospital affiliated to Capital Medical University from January 1, 2012 to December 31, 2016. MLR or R-MLR were stratified according to the optimal cut-off values. The cumulative recurrence-free survival (RFS), overall survival (OS) , and recurrence-death survival (RDS) rates were calculated by Kaplan-Meier method. The Cox proportion hazard model and logistic regression analysis was conducted to screen for independent predictive factors for indicating early relapse and long-term prognosis. RESULTS: High MLR was significantly associated with relapse, early recurrence, and overall survival. After a median follow-up of 59.4 months, The cumulative 1-, 3-, 5-year RFS rates of low MLR were 74.6%, 43.8%, and 34.0%; while 66.1%, 32.2%, and 22.6% for high group (P < 0.001). There were also significant differences in corresponding OS rates of the two groups (P = 0.003). The cumulative 1-, 3-, 5-year OS rates of low R-MLR were 99.5%, 87.2%, 75.5%; while 98.3%, 78.3%, 61.7% for high group (P < 0.001). There were also significant differences in corresponding RDS rates in the two groups (P = 0.008). 436 patients were divided into four groups on the base of cut-off values of MLR and R-MLR (low-low, low-high, high-low, and high-high). The low-low group has shown better outcomes including the cumulative 1-, 3-, 5-year OS, and RDS rates(P < 0.001). CONCLUSIONS: High MLR was related to unfavorable outcome. Subsequent change of MLR between baseline and HCC relapse could indicate poor long-term survival after relapse.

Predicting hepatocellular carcinoma early recurrence after ablation based on magnetic resonance imaging radiomics nomogram.

BACKGROUND: The aim of this study is to investigate a model for predicting the early recurrence of hepatocellular carcinoma (HCC) after ablation. METHODS: A total of 181 patients with HCC after ablation (train group was 119 cases; validation group was 62 cases) were enrolled. The cases of early recurrence in the set of train and validation were 63 and 31, respectively. Radiomics features were extracted from the enhanced magnetic resonance imaging scanning, including pre-contrast injection, arterial phase, late arterial phase, portal venous phase, and delayed phase. The least absolute shrinkage and selection operator cox proportional hazards regression after univariate and multivariate analysis was used to screen radiomics features and build integrated models. The nomograms predicting recurrence and survival of patients of HCC after ablation were established based on the clinical, imaging, and radiomics features. The area under the curve (AUC) of the receiver operating characteristic curve and C-index for the train and validation group was used to evaluate model efficacy. RESULTS: Four radiomics features were selected out of 34 texture features to formulate the rad-score. Multivariate analyses suggested that the rad-score, number of lesions, integrity of the capsule, pathological type, and alpha-fetoprotein were independent influencing factors. The AUC of predicting early recurrence at 1, 2, and 3 years in the train group was 0.79 (95% CI: 0.72-0.88), 0.72 (95% CI: 0.63-0.82), and 0.71 (95% CI: 0.61-0.83), respectively. The AUC of predicting early recurrence at 1, 2, and 3 years in the validation group was 0.72 (95% CI: 0.58-0.84), 0.61 (95% CI: 0.45-0.78) and 0.64 (95% CI: 0.40-0.87). CONCLUSION: The model for early recurrence of HCC after ablation based on the clinical, imaging, and radiomics features presented good predictive performance. This may facilitate the early treatment of patients.

Variations in dynamic tumor-associated antigen-specific T cell responses correlate with HCC recurrence after thermal ablation.

Background: Ablative therapy is a recommended treatment for hepatocellular carcinoma (HCC) not only for its effective eradication of tumors, but also for its induction of host immunity. However, the high 5-year recurrence rate after ablation underlines the poor understanding of the antitumor immunity response. Here, we investigated the effects of thermal ablation on antitumor immunity. Methods: We analyzed the dynamics of tumor-associated antigen (TAA)-specific immune responses and changes in peripheral blood mononuclear cell phenotype in patients with HCC before and after tumor ablation. We used the IFN-γ ELISPOT assay and immunophenotyping by flow cytometry to evaluate the effects of ablation on host immunity. The correlation between the T cell response and disease outcome was explored to uncover the efficacy of the immune response in inhibiting HCC recurrence. Results: Different TAA-specific T cell responses were identified among patients before and after ablation. One week after ablation, there was an improved immune state, with a switch from the dominance of an AFP-specific T cell response to that of a SMNMS-specific T cell response, which was correlated with better survival. Furthermore, an improvement in immune status was accompanied by a lower level of PD1+ and Tim3+ T cells in CD8+ T cells. Although this functional state was not durable, there was a higher degree of AFP-specific T cell responses at 4-weeks post-ablation. Furthermore, T cells presented a more exhausted phenotype at 4-weeks post-ablation than at the 1-week timepoint. Conclusions: Ablation elicits a transient antitumor immune response in patients with HCC by changing the profile of the T cell response and the expression of immune checkpoint molecules, which correlated with longer recurrence-free survival of patients with HCC.

Multi-scale patches convolutional neural network predicting the histological grade of hepatocellular carcinoma.

Preoperative predicting histological grade of hepatocellular carcinoma (HCC) is a crucial issue for the evaluation of patient prognosis and determining clinical treatment strategies. Previous studies have shown the potential of preoperative medical imaging in HCC grading diagnosis, however, there still remain challenges. In this work, we proposed a multi-scale 2D dense connected convolutional neural network (MS-DenseNet) for the classification of grade. This architecture consisted of three CNN branches to extract features of CT image patches in different scale. Then the outputs for each CNN branch were concatenated to the final fully connected layer. Our network was developed and evaluated on 455 HCC patients from two different centers. For data augmentation, more than 2000 patches for each scale were cropped from transverse section 2D region of interest on these patients. Besides, three-channel inputs including original CT image, tumor region and peritumoral component provided complementary knowledge. Experimental results demonstrated that the proposed method achieved encouraging prediction performance with AUC of 0.798 in testing dataset.Clinical Relevance-The proposed MS-DenseNet yielded an encouraging prediction performance for HCC histological grade and might assist the clinical diagnosis and decision making of HCC patients.

Saliency-based 3D convolutional neural network for categorising common focal liver lesions on multisequence MRI.

BACKGROUND: The imaging features of focal liver lesions (FLLs) are diverse and complex. Diagnosing FLLs with imaging alone remains challenging. We developed and validated an interpretable deep learning model for the classification of seven categories of FLLs on multisequence MRI and compared the differential diagnosis between the proposed model and radiologists. METHODS: In all, 557 lesions examined by multisequence MRI were utilised in this retrospective study and divided into training-validation (n = 444) and test (n = 113) datasets. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the performance of the model. The accuracy and confusion matrix of the model and individual radiologists were compared. Saliency maps were generated to highlight the activation region based on the model perspective. RESULTS: The AUC of the two- and seven-way classifications of the model were 0.969 (95% CI 0.944-0.994) and from 0.919 (95% CI 0.857-0.980) to 0.999 (95% CI 0.996-1.000), respectively. The model accuracy (79.6%) of the seven-way classification was higher than that of the radiology residents (66.4%, p = 0.035) and general radiologists (73.5%, p = 0.346) but lower than that of the academic radiologists (85.4%, p = 0.291). Confusion matrices showed the sources of diagnostic errors for the model and individual radiologists for each disease. Saliency maps detected the activation regions associated with each predicted class. CONCLUSION: This interpretable deep learning model showed high diagnostic performance in the differentiation of FLLs on multisequence MRI. The analysis principle contributing to the predictions can be explained via saliency maps.

Chinese expert consensus of image-guided irreversible electroporation for pancreatic cancer.

Pancreatic cancer (PC) is a lethal disease with extremely high mortality. Although surgical resection is the optimal therapeutic approach for PC, about 30%-40% of those patients are not candidates for surgical resection when diagnosed. Chemotherapy and radiotherapy also could not claim a desirable effect on PC. The application of interventional radiology approaches is limited by unavoidable damage to the surrounding vessels or organs. By the superiority of mechanism and technology, IRE could ablate the tumor by creating irreversible pores on the membrane of PC cells with other tissues like vessels and pancreatic ducts untouched. This consensus gathers the theoretical basis and clinical experience from multiple Chinese medical centers, to provide the application principles and experience from Chinese experts in the IRE field.

Engineering Peptide-Functionalized Biomimetic Nanointerfaces for Synergetic Capture of Circulating Tumor Cells in an EpCAM-Independent Manner.

Broad-spectrum detection and long-term monitoring of circulating tumor cells (CTCs) remain challenging due to the extreme rarity, heterogeneity, and dynamic nature of CTCs. Herein, a dual-affinity nanostructured platform was developed for capturing different subpopulations of CTCs and monitoring CTCs during treatment. Stepwise assembly of fibrous scaffolds, a ligand-exchangeable spacer, and a lysosomal protein transmembrane 4 ß (LAPTM4B)-targeting peptide creates biomimetic, stimuli-responsive, and multivalent-binding nanointerfaces, which enable harvest of CTCs directly from whole blood with high yield, purity, and viability. The stable overexpression of the target LAPTM4B protein in CTCs and the enhanced peptide-protein binding facilitate the capture of rare CTCs in patients at an early stage, detection of both epithelial-positive and nonepithelial CTCs, and tracking of therapeutic responses. The reversible release of CTCs allows downstream molecular analysis and identification of specific liver cancer genes. The consistency of the information with clinical diagnosis presents the prospect of this platform for early diagnosis, metastasis prediction, and prognosis assessment.

Magnetic resonance radiomics signatures for predicting poorly differentiated hepatocellular carcinoma: A SQUIRE-compliant study.

ABSTRACT: Radiomics contributes to the extraction of undetectable features with the naked eye from high-throughput quantitative images. In this study, 2 predictive models were constructed, which allowed recognition of poorly differentiated hepatocellular carcinoma (HCC). In addition, the effectiveness of the as-constructed signature was investigated in HCC patients.A retrospective study involving 188 patients (age, 29-85 years) enrolled from November 2010 to April 2018 was carried out. All patients were divided randomly into 2 cohorts, namely, the training cohort (n = 141) and the validation cohort (n = 47). The MRI images (DICOM) were collected from PACS before ablation; in addition, the radiomics features were extracted from the 3D tumor area on T1-weighted imaging (T1WI) scans, T2-weighted imaging (T2WI) scans, arterial images, portal images and delayed phase images. In total, 200 radiomics features were extracted. t test and Mann-Whitney U test were performed to exclude some radiomics signatures. Afterwards, a radiomics signature model was built through LASSO regression by RStudio Software. We constructed 2 support vector machine (SVM)-based models: 1 with a radiomics signature only (model 1) and 1 that integrated clinical and radiomics signatures (model 2). Then, the diagnostic performance of the radiomics signature was evaluated through receiver operating characteristic (ROC) analysis.The classification accuracy in the training and validation cohorts was 80.9% and 72.3%, respectively, for model 1. In the training cohort, the area under the ROC curve (AUC) was 0.623, while it was 0.576 in the validation cohort. The classification accuracy in the training and validation cohorts were 79.4% and 74.5%, respectively, for model 2. In the training cohort, the AUC was 0.721, while it was 0.681 in the validation cohort.The MRI-based radiomics signature and clinical model can distinguish HCC patients that belong in a low differentiation group from other patients, which helps in the performance of personal medical protocols.

Automatic discrimination of different sequences and phases of liver MRI using a dense feature fusion neural network: a preliminary study.

PURPOSE: To develop and validate a dense feature fusion neural network (DFuNN) to automatically recognize different sequences and phases of liver magnetic resonance imaging (MRI). MATERIALS AND METHODS: In total, 3869 sequences and phases from 384 liver MRI examinations, divided into training/validation (n = 2886 sequences from 287 patients) and test (n = 983 sequences from 97 patients) sets, were used in this retrospective study. Ten unenhanced sequences and enhanced phases were included. Manual sequence recognition, performed by two radiologists (20 and 10 years of experience) in a consensus reading, was used as the reference standard. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were calculated to evaluate the performance of the DFuNN on an identical unseen test set. Finally, we evaluated the factors impacting the model precision. RESULTS: A fusion block improved the performance of the DFuNN. DFuNN with a fusion block achieved good recognition performance for both complete and incomplete sequences and phases in the test set. The average sensitivity of recognition performance for complete sequence and phase inputs ranged from 88.06 to 100%, the average specificity ranged from 99.12 to 99.94%, and the median accuracy ranged from 98.02 to 99.95%. The DFuNN prediction accuracy for patients without cirrhosis were significantly higher than those for patients with cirrhosis (P = 0.0153). No significant difference was found in the accuracy across other factors. CONCLUSION: DFuNN can automatically and accurately identify specific unenhanced MRI sequences and enhanced MRI phases.

POU2F2-IL-31 Autoregulatory Circuit Converts Hepatocytes into the Origin Cells of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) originates from fully differentiated hepatocytes, but the decisive events for converting hepatocytes to the cells of origin for HCC are still unclear. Liver cancer stem cells (LCSCs) cause HCC but are not bona fide cells of origin. Here, the expressions of POU2F2 and IL-31 are identified in macroscopically normal livers of diethylnitrosamine-challenged mice. An autoregulatory circuit formed by mutual induction between POU2F2 and IL-31 drives hepatocytes to progress to LCSCs by acquiring stemness, as well as stimulates them to in vivo grow and malignantly progress. The development of the autoregulatory circuit is a decisive event for converting hepatocytes into the cells of origin, since hepatocytes expressing the circuit have acquired tumorigenic potential before progressing to LCSCs. Nonetheless, acquiring stemness is still required for the cells of origin to initiate hepatocarcinogenesis. The circuit also occurs in human cirrhotic tissues, partially elucidating how premalignant lesions progress to HCC.

The Dynamic Changes of AFP From Baseline to Recurrence as an Excellent Prognostic Factor of Hepatocellular Carcinoma After Locoregional Therapy: A 5-Year Prospective Cohort Study.

BACKGROUND: Although many studies have confirmed the prognostic value of preoperative alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC), the association between AFP at baseline (b-AFP), subsequent AFP at relapse (r-AFP), and AFP alteration and overall survival in HCC patients receiving locoregional therapy has rarely been systematically elucidated. PATIENTS AND METHODS: A total of 583 subjects with newly diagnosis of virus-related HCC who were admitted to Beijing You 'an Hospital, Capital Medical University from January 1, 2012 to December 31, 2016 were prospectively enrolled. The influence of b-AFP, subsequent r-AFP, and AFP alteration on relapse and post-recurrence survival were analyzed. RESULTS: By the end of follow-up, a total of 431 (73.9%) patients relapsed and 200 (34.3%) died. Patients with positive b-AFP had a 24% increased risk of recurrence compared with those who were negative. Patients with positive r-AFP had a 68% increased risk of death after relapse compared with those who were negative. The cumulative recurrence-death survival (RDS) rates for 1, 3, 5 years in patients with negative r-AFP were 85.6% (184/215), 70.2%(151/215), and 67.4%(145/215), while the corresponding rates were 75.1% (154/205), 51.2% (105/205), and 48.8% (100/205) in those with positive AFP (P<0.001). 35 (21.6%) of the 162 patients with negative b-AFP turned positive at the time of recurrence, and of this subset, only 12 (34.3%) survived. Of the 255 patients with positive b-AFP, 86 (33.7%) turned negative at the time of relapse, and of this subset, only 30 (34.9%) died. The 1-, 3-, and 5-year cumulative RDS rates were also compared among groups stratified by AFP at baseline and relapse. The present study found that patients with positive AFP at baseline and relapse, as well as those who were negative turned positive, had the shortest RDS and OS. CONCLUSIONS: Not only AFP at baseline but also subsequent AFP at relapse can be used to predict a post-recurrence survival, which can help evaluate mortality risk stratification of patients after relapse.