Journal of Hepatocellular Carcinoma最新文献

{"title":"In Situ Vaccination with Poly-ICLC Combined with Systemic Nivolumab for the Treatment of Unresectable Hepatocellular Carcinoma.","authors":"Ja-Der Liang, Po-Chin Liang, Chia-Tung Shun, Chien-Hung Chen, Yao-Ming Wu, Yu-Chen Hsu, Ying-Te Lee, Pei-Ming Yang, Guan-Tarn Huang, Andres M Salazar, Hsuan-Shu Lee, Jin-Chuan Sheu, Meng-Tzu Weng","doi":"10.2147/JHC.S520710","DOIUrl":"10.2147/JHC.S520710","url":null,"abstract":"<p><strong>Purpose: </strong>Unresectable hepatocellular carcinoma (HCC) presents significant therapeutic challenges. While immune checkpoint inhibitors (ICIs) are part of the current standard of care, combining poly-ICLC as an in situ vaccination with an ICI may enhance treatment efficacy. The study investigated the safety and therapeutic effects of combining poly-ICLC with nivolumab, an ICI, in patients with unresectable HCC.</p><p><strong>Patients and methods: </strong>Patients with unresectable HCC were enrolled to receive intratumoral and intramuscular poly-ICLC injections along in combination with nivolumab infusions. The primary endpoint was safety, and secondary endpoints included objective response as measured by mRECIST and changes in serum alpha-fetoprotein (AFP) levels. Gene expression profiling, pathway analysis, and immune cell type deconvolution were conducted using NanoString GeoMx Digital Spatial Profiling.</p><p><strong>Results: </strong>Four patients were enrolled. The combination therapy was safe and well-tolerated. Among them, one patient achieved a complete response (CR), and another achieved a partial response (PR). Both responders showed significant declines in serum AFP levels. Notably, the patient with CR showed eradication of cancerous component of the portal vein thrombus, and an abscopal effect was observed in the patient with PR. Gene analysis indicated that interferon-gamma signaling was the most enriched pathway in tumors of the responders.</p><p><strong>Conclusion: </strong>This combination therapy was safe and effective, with two out of four patients demonstrating objective responses. These preliminary findings warrant further investigation into larger clinical cohorts.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"1191-1204"},"PeriodicalIF":4.2,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12176139/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144325949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intravoxel Incoherent Motion Improves the Accuracy of Preoperative Prediction of Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma.","authors":"Min Li, Ge Zhang, Jing Li, Yufan Ren, Xuan Jin, Qiying Ke, Congyue Guo, Jiaqi Lv, Haojun Lu, Yongzhou Xu, Wen Liang, Xianyue Quan, Xinming Li","doi":"10.2147/JHC.S519223","DOIUrl":"10.2147/JHC.S519223","url":null,"abstract":"<p><strong>Purpose: </strong>Hepatocellular carcinoma (HCC) with vessels encapsulating tumor clusters (VETC) pattern presents a higher risk of recurrence and metastasis, and the unique vascular structure of the VETC pattern may affect the perfusion and diffusion, and the effect that can be captured by intravoxel incoherent motion (IVIM). Therefore, this study used preoperative IVIM to predict VETC pattern in HCC and performed preoperative noninvasive recurrence risk stratification.</p><p><strong>Patients and methods: </strong>Patients with suspicious HCC were included prospectively. Two radiologists independently evaluated radiologic features and measured apparent diffusion coefficient (ADC), true diffusion coefficient (<i>D</i>), pseudo-diffusion coefficient (<i>D</i>*), and pseudo-diffusion fraction (<i>f</i>). Logistic regression analyses were used to identify the predictors associated with the VETC pattern. Receiver operating characteristic (ROC) curve analyses were conducted to assess the predictive performance. Recurrence-free survival was evaluated using the Kaplan-Meier analysis and the Log rank test.</p><p><strong>Results: </strong>The consecutive cohort included 116 patients (mean age, 55 years ± 11, 94 men). Twenty-nine of the 116 HCC (25.0%) were VETC HCC. The <i>f</i> value (odds ratio [OR], 0.791; p < 0.001), serum α-fetoprotein level (>400 ng/mL) (OR, 2.962; p = 0.042), and intratumor necrosis (OR, 6.022; p = 0.015) were independent predictors of the VETC pattern. These characteristics were used to construct the combined model with area under the ROC curve of 0.854. Additionally, adding the <i>f</i> value to the conventional imaging-clinical model substantially improved its predictive performance (p < 0.001). Moreover, patients with the combined model classified as VETC HCC also had a higher risk of early recurrence than those with non-VETC HCC (p < 0.001).</p><p><strong>Conclusion: </strong>IVIM enhances the accuracy of preoperative prediction of the VETC pattern and provides preoperative noninvasive risk stratification for HCC recurrence.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"1177-1190"},"PeriodicalIF":4.2,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12168965/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144309994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early Recurrence of Hepatocellular Carcinoma in Patients without Microscopic Vascular Invasion: Clinicopathological Characteristics and Risk Factors.","authors":"Hanh Thi Tuyet Ngo, Duy Duc Nguyen, Minh-Xuan Dang, Thao Thi Phuong Doan, Truc Thanh Thai","doi":"10.2147/JHC.S524683","DOIUrl":"10.2147/JHC.S524683","url":null,"abstract":"<p><strong>Purpose: </strong>Early recurrence of hepatocellular carcinoma (HCC) is not uniformly associated with microscopic vascular invasion (MVI). This study aims to identify the clinical and pathological factors associated with early recurrence in HCC patients without MVI.</p><p><strong>Methods: </strong>A retrospective cohort study was conducted on 69 patients who underwent hepatectomy for HCC at the University Medical Center Ho Chi Minh city. All patients were microscopically confirmed as MVI-negative. Clinical and subclinical data, along with tumor recurrence within 24 months post-surgery were collected. Microscopic features of both tumor and non-tumor liver tissue were assessed using Hematoxylin-Eosin-stained slides.</p><p><strong>Results: </strong>The majority of patients were male (78.3%) and had cirrhosis (72.5%). The early recurrence rate was 31.9%, with most recurrences occurring between 6- and 18-month post-surgery. Independent factors for early tumor recurrence included preoperative treatment with Transarterial Chemoembolization (TACE) or Radiofrequency Ablation (RFA) (HR = 8.63, 95% CI = 1.45-51.38), tumor size > 5 cm (HR = 3.82, 95% CI = 1.17-12.42), and HCV infection (HR = 4.61, 95% CI = 1.41-15.1).</p><p><strong>Conclusion: </strong>The pathogenesis and pattern of early tumor recurrence in MVI-negative HCC differ from that in MVI-positive cases. Identifying risk factors, such as HCV infection, tumor size, and preoperative locoregional therapy, may aid in optimizing treatment strategies and postoperative surveillance.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"1167-1175"},"PeriodicalIF":4.2,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12168972/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144309993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic Variants of <i>UGP2</i> and <i>FBP2</i> in the Glycolysis Pathway Independently Predict Survival of Patients with HBV-Related Hepatocellular Carcinoma.","authors":"Rongbin Gong, Moqin Qiu, Yingchun Liu, Ji Cao, Zihan Zhou, Qiuling Lin, Yanji Jiang, Xiumei Liang, Yuying Wei, Qiuping Wen, Peiqin Chen, Xiaoxia Wei, Junjie Wei, Shicheng Zhan, Ruoxin Zhang, Dong Ye, Hongping Yu","doi":"10.2147/JHC.S492516","DOIUrl":"10.2147/JHC.S492516","url":null,"abstract":"<p><strong>Purpose: </strong>Glycolysis is a group of metabolic processes that may alter tumor microenvironment to have effects on the growth and proliferation of tumor cells, including liver cancer. However, the effect of genetic variants in glycolysis pathway genes in survival of patients with hepatitis B virus-related hepatocellular carcinoma (HBV-HCC) remains unclear.</p><p><strong>Methods: </strong>We employed multivariable Cox proportional hazards regression analyses to estimate associations between genetic variants in 240 glycolysis pathway genes and overall survival (OS) of 866 patients with HBV-HCC, and we also used false positive report probability for multiple testing corrections.</p><p><strong>Results: </strong>We found that <i>UGP2</i> rs4293553 G allele was significantly associated with a better OS of HBV-HCC patients [hazards ratio (HR) = 0.73, 95% confidence interval (CI) = 0.62-0.86, <i>P</i> < 0.001], and that <i>FBP2</i> rs635087 G allele was significantly associated with a worse OS in these patients (HR = 1.38, 95% CI = 1.18-1.61, <i>P</i> < 0.001). The expression quantitative trait loci analysis using the GTEx database showed that the rs635087 G allele was significantly correlated with reduced <i>FBP2</i> mRNA expression levels in normal liver tissues (<i>P</i> < 0.001), but such a correlation was not significant for the rs4293553 G allele. Functional annotation results indicate that these two single nucleotide polymorphisms have potential biological functions, providing biological plausibility for the observed associations. In addition, the mRNA expression levels of both <i>UGP2</i> and <i>FBP2</i> were significantly lower in HCC tissues than in normal liver tissues (both <i>P</i> < 0.001), and high expression levels of both <i>UGP2</i> and <i>FBP2</i> were significantly associated with favorable survival in HCC patients (both <i>P</i> < 0.001).</p><p><strong>Discussion: </strong>Our findings suggested that genetic variants in glycolysis pathway genes may serve as novel prognostic markers for survival of patients with HBV-HCC, especially <i>FBP2</i> rs635087, if validated in additional larger studies and functional investigations.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"1155-1166"},"PeriodicalIF":4.2,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12155380/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144275086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factor Analysis of the Effect of Hepatitis B-Related Liver Cancer Treatment Efficacy.","authors":"Shuai-Wei Liu, Yan Zhou, Xue Yan Feng, Long Hai, Wan-Long Ma, Li Na Ma, Xiang-Chun Ding, Xia Luo","doi":"10.2147/JHC.S519397","DOIUrl":"10.2147/JHC.S519397","url":null,"abstract":"<p><strong>Background and aim: </strong>Drug-eluting bead transcatheter arterial chemoembolization (DEB-TACE) is commonly used to treat unresectable hepatitis B-related primary liver cancer, but its therapeutic effect is influenced by various factors. This study analyzes the clinical factors related to the overall survival (OS) and progression-free survival (PFS) of patients with hepatitis B-related hepatocellular carcinoma (HCC) treated with DEB-TACE to provide reference data for individualized treatment.</p><p><strong>Methods: </strong>In this retrospective study, 128 patients with hepatitis B-related primary liver cancer who received DEB-TACE treatment and being followed up (range of follow-up: 4-39 months) were included. The relationships between clinical characteristics, tumor markers, inflammatory factors, blood biochemical parameters, and OS and PFS were analyzed. Statistical methods, including Kaplan-Meier analysis, the Log rank test, and Cox regression analysis, were used to evaluate independent factors affecting patient prognosis.</p><p><strong>Results: </strong>Factors such as tumor size, tumor number, vascular invasion, extrahepatic metastasis, stage (CNLC and BCLC), and alpha-fetoprotein (AFP) level significantly affected OS and PFS (P < 0.05). In particular, patients with a tumor diameter >5 cm, multiple tumors, portal vein invasion, and extrahepatic metastasis had significantly shorter OS and PFS. Preoperative inflammatory factors (eg, white blood cell count, absolute neutrophil count, procalcitonin, and C-reactive protein) and blood biochemical parameters (eg, aspartate aminotransferase (AST), total bilirubin (TBIL), albumin (ALB)) were closely related to patient prognosis. Multivariate Cox regression analysis revealed that age, Child-Pugh score, BCLC stage, TBIL, ALB, CRP, and AFP were independent prognostic factors for OS.</p><p><strong>Conclusion: </strong>This study highlights the significance of tumor clinical characteristics and preoperative inflammatory factors in predicting the prognosis of patients with hepatitis B-related HCC treated with DEB-TACE. By comprehensively evaluating these clinical and biological markers, more personalized treatment plans can be developed for liver cancer patients, thereby improving treatment outcomes and survival rates.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"1141-1154"},"PeriodicalIF":4.2,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12149274/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144266418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiomics and Deep Learning as Important Techniques of Artificial Intelligence - Diagnosing Perspectives in Cytokeratin 19 Positive Hepatocellular Carcinoma.","authors":"Fei Wang, Chunyue Yan, Xinlan Huang, Jiqiang He, Ming Yang, Deqiang Xian","doi":"10.2147/JHC.S526887","DOIUrl":"10.2147/JHC.S526887","url":null,"abstract":"<p><strong>Background: </strong>Currently, there are inconsistencies among different studies on preoperative prediction of Cytokeratin 19 (CK19) expression in HCC using traditional imaging, radiomics, and deep learning. We aimed to systematically analyze and compare the performance of non-invasive methods for predicting CK19-positive HCC, thereby providing insights for the stratified management of HCC patients.</p><p><strong>Methods: </strong>A comprehensive literature search was conducted in PubMed, EMBASE, Web of Science, and the Cochrane Library from inception to February 2025. Two investigators independently screened and extracted data based on inclusion and exclusion criteria. Eligible studies were included, and key findings were summarized in tables to provide a clear overview.</p><p><strong>Results: </strong>Ultimately, 22 studies involving 3395 HCC patients were included. 72.7% (16/22) focused on traditional imaging, 36.4% (8/22) on radiomics, 9.1% (2/22) on deep learning, and 54.5% (12/22) on combined models. The magnetic resonance imaging was the most commonly used imaging modality (19/22), and over half of the studies (12/22) were published between 2022 and 2025. Moreover, 27.3% (6/22) were multicenter studies, 36.4% (8/22) included a validation set, and only 13.6% (3/22) were prospective. The area under the curve (AUC) range of using clinical and traditional imaging was 0.560 to 0.917. The AUC ranges of radiomics were 0.648 to 0.951, and the AUC ranges of deep learning were 0.718 to 0.820. Notably, the AUC ranges of combined models of clinical, imaging, radiomics and deep learning were 0.614 to 0.995. Nevertheless, the multicenter external data were limited, with only 13.6% (3/22) incorporating validation.</p><p><strong>Conclusion: </strong>The combined model integrating traditional imaging, radiomics and deep learning achieves excellent potential and performance for predicting CK19 in HCC. Based on current limitations, future research should focus on building an easy-to-use dynamic online tool, combining multicenter-multimodal imaging and advanced deep learning approaches to enhance the accuracy and robustness of model predictions.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"1129-1140"},"PeriodicalIF":4.2,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12149279/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144266419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness and Safety of Systemic Therapy and Stereotactic Body Radiotherapy in Oligoprogressive and Oligometastatic Hepatocellular Carcinoma.","authors":"Zhuo Song, Xuan Zheng, Hongzhi Wang, Dezuo Dong, Xianggao Zhu, Jianhao Geng, Shuai Li, Maxiaowei Song, Rongxu Du, Yangzi Zhang, Zhiyan Liu, Yong Cai, Yongheng Li, Weihu Wang","doi":"10.2147/JHC.S519770","DOIUrl":"10.2147/JHC.S519770","url":null,"abstract":"<p><strong>Purpose: </strong>This study explored the efficacy and safety of combining systemic therapy with stereotactic body radiotherapy (SBRT) for oligoprogressive (OP) and oligometastatic (OM) hepatocellular carcinoma (HCC).</p><p><strong>Patients and methods: </strong>From January 2017 to June 2023, 37 HCC patients (28 OP, 9 OM) receiving systemic therapy and SBRT were identified. OP is defined as up to 5 progressive lesions with others stable after systemic therapy and OM as newly identified metastatic disease with up to 5 metastatic lesions. SBRT was delivered in fractions of 5 Gy or more to all lesions. Clinical outcomes and toxicity were evaluated.</p><p><strong>Results: </strong>The median follow-up was 32.8 months. The objective response rates (ORRs) were 47.2%, 44.4%, and 55.5% for overall, OP, and OM cohorts. SBRT treated 48 OP and 17 OM lesions, achieving an ORR of 64.7%. For overall, OP, and OM cohorts, the 2-year local failure rates were 3.0%, 4.0%, and 0%, with median progression-free survival (PFS) of 11.2, 11.2, and 10.2 months, and median overall survival (OS) of 34.9 months, 32.6 months, and not reached (NR), respectively. In the OP cohort, 12 patients switched to next-line systemic therapy (OP-N) and 16 remained on current therapy (OP-C). Median PFS and OS were 11.6 months and NR for OP-N versus 16.5 months and 32.6 months for OP-C (P=0.89 and 0.47). Grade 3 acute and late treatment-related adverse events occurred in 40.5% and 5.4% of patients.</p><p><strong>Conclusion: </strong>Systemic therapy combined with SBRT was effective and safe for OP and OM HCC. SBRT may delay next-line systemic therapy by blocking OP.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"1097-1110"},"PeriodicalIF":4.2,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136078/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144225688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Resistance and Survival of HCC Patients Post-HAIC: Based on Shapley Additive exPlanations and Machine Learning.","authors":"Fan Yao, Jianliang Miao, Bing Quan, Jinghuan Li, Bei Tang, Shenxin Lu, Xin Yin","doi":"10.2147/JHC.S523806","DOIUrl":"10.2147/JHC.S523806","url":null,"abstract":"<p><strong>Purpose: </strong>To establish prediction models using Shapley Additive exPlanations (SHAP) and multiple machine learning (ML) algorithms to identify clinical features influencing hepatic arterial infusion chemotherapy (HAIC) resistance and survival in patients with hepatocellular carcinoma (HCC).</p><p><strong>Patients and methods: </strong>We recruited 286 patients with unresectable HCC who underwent HAIC. Patients were divided into training and validation datasets (7:3 ratio). eXtreme Gradient Boosting (XGBoost) was used to build the preliminary resistance prediction model. The SHAP values explained the importance of the clinical features. Recursive Feature Elimination with Cross-Validation (RFECV) was used to select the optimum number of features. Seven ML methods were used to construct further resistance prediction models, and ten ML algorithms were employed to establish the survival prognosis models.</p><p><strong>Results: </strong>The areas under the curve (AUC) of the XGBoost model were 1.000 and 0.812 for the training and validation groups, respectively. SHAP identified 27 of the 38 clinical features affecting resistance, with pre-HAIC treatment being the main factor. RFECV showed the best model performance with six features (pre-HAIC treatment, tumor size, HBV DNA, alkaline phosphatase (AKP), prothrombin time (PT), and portal vein tumor thrombosis (PVTT)). Random Forest had the best performance among the seven ML algorithms (AUC=0.935 for training, AUC=0.876 for validation). The combination of Stepcox [forward] and Gradient Boosting Machine was the best for predicting survival (AUC=0.98 in training, AUC=0.83 in validation). Based on the above clinical characteristics, patients were categorized into high-risk and low-risk groups based on the median risk score, and it was found that these characteristics also performed well in the prognostic model for predicting the survival of patients with HCC.</p><p><strong>Conclusion: </strong>Pre-HAIC treatment, tumor size, HBV DNA, AKP, PT, and PVTT are effective predictors of post-HAIC resistance and survival in patients with unresectable advanced HCC.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"1111-1128"},"PeriodicalIF":4.2,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12140075/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144234330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intratumoral and Peritumoral Radiomics Based on DCE-MRI for Prediction of Microvascular Invasion Grading in Solitary Hepatocellular Carcinoma (≤3 cm).","authors":"Yinqiao Li, Helin Li, Yayuan Feng, Lun Lu, Juan Zhang, Ningyang Jia","doi":"10.2147/JHC.S519578","DOIUrl":"10.2147/JHC.S519578","url":null,"abstract":"<p><strong>Purpose: </strong>To explore the application value of clinical indicators, radiological features, and magnetic resonance imaging (MRI) radiomics to predict the grading of MVI in nodular hepatocellular carcinoma (≤3cm).</p><p><strong>Methods: </strong>A total of 131 patients with hepatocellular carcinoma (HCC) and confirmed microvascular invasion (MVI) who underwent surgical resection between January 2016 and December 2022 were retrospectively analyzed. A clinical-radiological (CR) model was constructed using independent risk factors identified by logistic regression. Radiomics models based on MRI (arterial phase, portal venous phase, delayed phase) across various regions (AVDP_intra, AVDP_{intra+peri3mm}, AVDP_{intra+peri5mm}, AVDP_{intra+peri10mm}) were developed using the Logistic Regression (LR) classifiers. The optimal radiomics model was subsequently integrated with the CR model to construct a combined clinical-radiological-radiomics (CRR) model. Model performance was assessed using the area under the curve (AUC).</p><p><strong>Results: </strong>Non-smooth margin and intratumoral artery were risk factors for MVI grading. The combined CRR model demonstrated the best predictive performance, with AUCs of 0.907 and 0.917 in the training and testing sets, respectively. Compared with the CR model alone, the CRR model showed a statistically significant improvement (p = 0.008, DeLong test).</p><p><strong>Conclusion: </strong>The AVDP_{intra+peri3mm} model based on MRI radiomics demonstrates good predictive performance in predicting MVI grading in HCC (≤3cm). Combining features from the CR model with those of the AVDP_{intra+peri3mm} model to construct the CRR model further enhances the prediction of MVI grading.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"1083-1095"},"PeriodicalIF":4.2,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12132667/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144216042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spleen Volume Dynamics and Survival Outcomes in HCC Patients Undergoing Immune Checkpoint Inhibitors: A Retrospective Analysis.","authors":"Xiaona Fu, Shanshan Jiang, Yi Li, Yusheng Guo, Bingxin Gong, Jie Lou, Yanlin Li, Sichen Wang, Yuxin Sun, Yi Ren, Quan Chen, Lian Yang","doi":"10.2147/JHC.S524483","DOIUrl":"10.2147/JHC.S524483","url":null,"abstract":"<p><strong>Purpose: </strong>The spleen serves as an important immune organ which influences the anti-tumor immune response by modulating the immune microenvironment. This study investigated the prognostic impact of spleen volume (SV) on the survival in hepatocellular carcinoma (HCC) patients receiving immune checkpoint inhibitors (ICIs).</p><p><strong>Patients and methods: </strong>This retrospective study included 224 HCC patients treated with ICIs, categorized into Higher and Lower SV groups by median SV and further into SV increased and Non-SV increased groups based on changes in SV at 3 months after ICIs. Kaplan-Meier curves and Cox regression models were used to evaluate the influence of SV and clinical indicators on progression-free survival (PFS) and overall survival (OS). Independent prognostic factors identified via multivariate analysis were incorporated into nomograms, with their accuracy assessed using concordance index (C-index), time-dependent receiver operating characteristic (ROC) and calibration curves. Restricted cubic spline (RCS) analysis was conducted to assess the relationship between baseline SV and survival.</p><p><strong>Results: </strong>The Higher SV and SV increased groups demonstrated shorter PFS and OS compared to the Lower SV and Non-SV increased groups, respectively. These results were consistent with different regimens in the Child A. The C-index of nomogram for PFS were 0.700 (0.678-0.721) and OS 0.733(0.709-0.757). The ROC and calibration curves confirmed robust discrimination and predictive accuracy of models. RCS analysis revealed a nonlinear association between baseline SV and survival risk, providing a more comprehensive overview of SV in relation to survival in HCC patients treated with ICIs.</p><p><strong>Conclusion: </strong>The baseline SV and its relative change at three months after treatment are expected to become routine imaging makers for predicting survival in HCC patients receiving ICIs, which consequently contributes to their clinical management.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"1069-1082"},"PeriodicalIF":4.2,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12132512/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144216043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}