Preoperative Gadoxetic Acid-Enhanced MRI Features for Evaluation of Vessels Encapsulating Tumor Clusters and Microvascular Invasion in Hepatocellular Carcinoma: Creating Nomograms for Risk Assessment.

BACKGROUND: Vessels encapsulating tumor cluster (VETC) and microvascular invasion (MVI) have a synergistic effect on prognosis assessment and treatment selection of hepatocellular carcinoma (HCC). Preoperative noninvasive evaluation of VETC and MVI is important. PURPOSE: To explore the diagnosis value of preoperative gadoxetic acid (GA)-enhanced magnetic resonance imaging (MRI) features for MVI, VETC, and recurrence-free survival (RFS) in HCC. STUDY TYPE: Retrospective. POPULATION: 240 post-surgery patients with 274 pathologically confirmed HCC (allocated to training and validation cohorts with a 7:3 ratio) and available tumor marker data from August 2014 to December 2021. FIELD STRENGTH/SEQUENCE: 3-T, T1-, T2-, diffusion-weighted imaging, in/out-phase imaging, and dynamic contrast-enhanced imaging. ASSESSMENT: Three radiologists subjectively reviewed preoperative MRI, evaluated clinical and conventional imaging features associated with MVI+, VETC+, and MVI+/VETC+ HCC. Regression-based nomograms were developed for HCC in the training cohort. Based on the nomograms, the RFS prognostic stratification system was further. Follow-up occurred every 3-6 months. STATISTICAL TESTS: Chi-squared test or Fisher's exact test, Mann-Whitney U-test or t-test, least absolute shrinkage and selection operator-penalized, multivariable logistic regression analyses, receiver operating characteristic analysis, Harrell's concordance index (C-index), Kaplan-Meier plots. Significance level: P < 0.05. RESULTS: In the training group, 44 patients with MVI+ and 74 patients with VETC+ were histologically confirmed. Three nomograms showed good performance in the training (C-indices: MVI+ vs. VETC+ vs. MVI+/VETC+, 0.892 vs. 0.848 vs. 0.910) and validation (C-indices: MVI+ vs. VETC+ vs. MVI+/VETC+, 0.839 vs. 0.810 vs. 0.855) cohorts. The median follow-up duration for the training cohort was 43.6 (95% CI, 35.0-52.2) months and 25.8 (95% CI, 16.1-35.6) months for the validation cohort. Patients with either pathologically confirmed or nomogram-estimated MVI, VETC, and MVI+/VETC+ suffered higher risk of recurrence. DATA CONCLUSION: GA-enhanced MRI and clinical variables might assist in preoperative estimation of MVI, VETC, and MVI+/VETC+ in HCC. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Diagnostic Model for Proliferative HCC Using LI-RADS: Assessing Therapeutic Outcomes in Hepatectomy and TKI-ICI Combination.

BACKGROUND: Proliferative hepatocellular carcinoma (HCC), aggressive with poor prognosis, and lacks reliable MRI diagnosis. PURPOSE: To develop a diagnostic model for proliferative HCC using liver imaging reporting and data system (LI-RADS) and assess its prognostic value. STUDY TYPE: Retrospective. POPULATION: 241 HCC patients underwent hepatectomy (90 proliferative HCCs: 151 nonproliferative HCCs), divided into the training (N = 167) and validation (N = 74) sets. 57 HCC patients received combination therapy with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs). FIELD STRENGTH/SEQUENCE: 3.0 T, T1- and T2-weighted, diffusion-weighted, in- and out-phase, T1 high resolution isotropic volume excitation and dynamic gadoxetic acid-enhanced imaging. ASSESSMENT: LI-RADS v2018 and other MRI features (intratumoral artery, substantial hypoenhancing component, hepatobiliary phase peritumoral hypointensity, and irregular tumor margin) were assessed. A diagnostic model for proliferative HCC was established, stratifying patients into high- and low-risk groups. Follow-up occurred every 3-6 months, and recurrence-free survival (RFS), progression-free survival (PFS) and overall survival (OS) in different groups were compared. STATISTICAL TESTS: Fisher's test or chi-square test, t-test or Mann-Whitney test, logistic regression, Harrell's concordance index (C-index), Kaplan-Meier curves, and Cox proportional hazards. Significance level: P < 0.05. RESULTS: The diagnostic model, incorporating corona enhancement, rim arterial phase hyperenhancement, infiltrative appearance, intratumoral artery, and substantial hypoenhancing component, achieved a C-index of 0.823 (training set) and 0.804 (validation set). Median follow-up was 32.5 months (interquartile range [IQR], 25.1 months) for postsurgery patients, and 16.8 months (IQR: 13.2 months) for combination-treated patients. 99 patients experienced recurrence, and 30 demonstrated tumor nonresponse. Differences were significant in RFS and OS rates between high-risk and low-risk groups post-surgery (40.3% vs. 65.8%, 62.3% vs. 90.1%, at 5 years). In combination-treated patients, PFS rates differed significantly (80.6% vs. 7.7% at 2 years). DATA CONCLUSION: The MR-based model could pre-treatment identify proliferative HCC and assist in prognosis evaluation. TECHNICAL EFFICACY: Stage 2.

A multivariate model based on gadoxetic acid-enhanced MRI using Li-RADS v2018 and other imaging features for preoperative prediction of dual­phenotype hepatocellular carcinoma.

OBJECTIVE: To investigate the diagnostic value of liver imaging reporting and data system (LI-RADS) v2018 and other imaging features in dual-phenotype hepatocellular carcinoma (DPHCC), establish a prediagnostic model based on gadoxetic acid-enhanced MRI, and explore the prognostic significance after surgery of the DPHCC. MATERIALS AND METHODS: Preoperative enhanced MRI findings and the clinical and pathological data of patients with surgically confirmed HCC were analysed retrospectively. Image analysis was based on LI-RADS v2018 and other image features. Univariate analysis was used to screen for predictive factors of DPHCC, and multivariate logistic regression analysis was used to determine the predictive factors. A regression diagnostic model was established. Receiver operating characteristic (ROC) curve analysis was used to determine the critical value, area under curve (AUC), and the corresponding 95% confidence interval (95% CI). The diagnostic performance was verified by fivefold cross-validation. Cox regression analysis was used to determine the prognostic factors associated with early recurrence after surgical resection. RESULTS: In total, 158 patients were included, of whom 79 had DPHCC and 79 had non-DPHCC. Multivariate analysis showed that rim arterial phase hyperenhancement (Rim APHE) and targetoid restriction were independent risk factors for DPHCC (P < 0.05). The AUC (95% CI) of the model was 0.862 (0.807-0.918), sensitivity was 81.01%, and specificity was 89.874%. Cox regression analysis showed that DPHCC, microvascular invasion, tumour diameter, and an increase of alpha-fetoprotein were independent factors for recurrence. CONCLUSION: Rim APHE and targetoid restriction were sensitive imaging features of DPHCC before surgery, and the identification of DPHCC has important prognostic significance for early recurrence.

Gut microbiota dysbiosis induced by polychlorinated biphenyl 126 contributes to increased brain proinflammatory cytokines: Landscapes from the gut-brain axis and fecal microbiota transplantation.

The pathogenesis of brain inflammation induced by polychlorinated biphenyl 126 (PCB126) has not yet been fully illustrated. Growing evidence highlights the relevance of the microbiota-gut-brain axis in central nervous system (CNS) dysfunction. Therefore, we aimed to study the role of the gut microbiota in PCB126-induced proinflammatory cytokine increases in the mouse brain. The results showed that PCB126 exposure significantly disordered gut bacterial communities, resulting in the enrichment of gram-negative bacteria (e.g., Bacteroidetes and Proteobacteria), further leading to elevated levels of the gram-negative bacterial lipopolysaccharide (LPS). Subsequently, colonic toll-like receptor 4 (TLR-4) was activated by bacterial LPS, which promoted proinflammatory cytokine generation and inhibited tight junction (TJ) protein expression. Then, bacterial LPS translocated from the gut lumen into the blood circulation and reached the brain, triggering LPS/TLR-4-mediated increases in brain proinflammatory cytokines. Further analysis after fecal microbiota transplantation (FMT) suggested that the gut microbiota disturbance caused by PCB126 could induce elevated bacterial LPS and trigger TLR-4-mediated increases in proinflammatory cytokines in the brain. This study highlights the possibility that PCB126-induced gut microbiota disorder contributes to increased brain proinflammatory cytokines. These results provide a new perspective for identifying the toxicity mechanisms of PCB126 and open up the possibility of modulating the gut microbiota as a therapeutic target for CNS disease caused by environmental pollution.

Acute and subchronic toxicity of Ag+-laden liposomes on Daphnia magna: the effect of encapsulation.

The toxic effects of various substances on Daphnia magna (D. magna) observed through traditional waterborne uptake may involve alterations to the nutritional quality of the contaminated algae and culture media. It is essential to find an alternative delivery method that will not affect the nutritional quality of D. magna's diet in order to elucidate the mechanisms of dietary metal toxicity. Therefore, this study examined the application of liposome encapsulation on the dietary toxicity of D. magna. Ag+-laden liposomes were prepared and the Ag encapsulation efficiency and inhibition effect on algae growth were examined. Then, acute and 14-day subchronic studies were performed to examine the effect of Ag+-laden liposomes on D. magna. The EC50 for the 24 h immobilization test was 10.59 µg/L for Ag+-laden liposomes and 3.07 µg/L for Ag+. In terms of subchronic effects, the estimated ECx values under the Ag+-laden liposome condition were always higher than the direct exposure condition. Furthermore, the bioaccumulation of Ag+-laden liposomes was about 1.68 times lower than direct exposure. Generally, Ag+-laden liposomes produced less efficient toxicity than direct exposure, e.g., lower D. magna mortality, production of more neonates, higher intrinsic rate of natural increase (rm), earlier time to first brood, and higher enzyme activities.

Application of deep learning and radiomics in the prediction of hematoma expansion in intracerebral hemorrhage: a fully automated hybrid approach

PURPOSE: Spontaneous intracerebral hemorrhage (ICH) is the most severe form of stroke. The timely assessment of early hematoma enlargement and its proper treatment are of great significance in curbing the deterioration and improving the prognosis of patients with ICH. This study aimed to develop an automated hybrid approach to predict hematoma expansion in ICH. METHODS: The transfer learning method was applied to build a hybrid model based on a convolutional neural network (CNN) to predict the expansion of hematoma. The model integrated (1) a CNN for automated hematoma segmentation and (2) a CNN-based classifier for hematoma expansion prediction that incorporated both 2-dimensional images and the radiomics features of the 3-dimensional hematoma shape. RESULTS: The radiomics feature module had the highest area under the receiver operating characteristic curve (AUC) of 0.58, a precision of 0, a recall of 0, and an average precision (AP) of 0.26. The ResNet50 and Inception_v3 modules had AUCs of 0.79 and 0.93, a precision of 0.56 and 0.86, a recall of 0.42 and 0.75, and an AP of 0.51 and 0.85, respectively. Radiomic with Inception_v3 and Radiomic with ResNet50 had AUCs of 0.95 and 0.81, a precision of 0.90 and 0.57, a recall of 0.79 and 0.17, and an AP of 0.87 and 0.69, respectively. CONCLUSION: A model using deep learning and radiomics was successfully developed. This model can reliably predict the hematoma expansion of ICH with a fully automated process based on non-contrast computed tomography imaging. Furthermore, the radiomics fusion with the Inception_v3 model had the highest accuracy.

Gadoxetic Acid-Enhanced MRI-Based Radiomic Models for Preoperative Risk Prediction and Prognostic Assessment of Proliferative HCC.

RATIONALE AND OBJECTIVES: Proliferative hepatocellular carcinoma (HCC) is associated with high invasiveness and poor prognosis. This study aimed to investigate the preoperative risk prediction and prognostic value of different radiomics models and a nomogram for proliferative HCC. MATERIALS AND METHODS: Patients were randomly divided into a training cohort (n = 156) and a validation cohort (n = 66) in a 7:3 ratio. Original and delta (the different value between imaging features extracted from two different phases) radiomics features were extracted from T1-weighted imaging (T1WI), arterial, and hepatobiliary phases to construct models using different machine learning algorithms. Logistic regression was used to select clinical independent risk factors. A nomogram was constructed by integrating the optimal radiomics model score with independent risk factors. The diagnostic efficacy and clinical utility of the models were assessed. Subsequently, patients were stratified into high-risk and low-risk subgroups based on radiomics model scores and nomogram scores, and both recurrence-free survival (RFS) and overall survival (OS) were evaluated. RESULTS: Multivariate logistic regression analysis showed that BCLC stage and combined radscore were independent predictors of proliferative HCC. The area under the curve (AUC) of the nomogram incorporating these factors was 0.838 and 0.801 in the training and validation cohorts, respectively, with good predictive performance. Multivariate Cox regression analysis shows that the delta radiomics model (DR)-predicted proliferative HCC can independently predict RFS and OS, with scores from the delta radiomics model performing best in prognostic risk stratification. CONCLUSION: The nomogram can effectively predict proliferative HCC, while different radiomics models and the nomogram can offer varying prognostic stratification values.

Radiomics analysis of gadoxetic acid-enhanced MRI for evaluating vessels encapsulating tumour clusters in hepatocellular carcinoma.

Purpose: The aim of this study was to develop an integrated model that combines clinical-radiologic and radiomics features based on gadoxetic acid-enhanced MRI for preoperative evaluating of vessels encapsulating tumour clusters (VETC) patterns in hepatocellular carcinoma (HCC). Methods: This retrospective study encompassed 234 patients who underwent surgical resection. Among them, 101 patients exhibited VETC-positive HCC, while 133 patients displayed VETC-negative HCC. Volumes of interest were manually delineated for entire tumour regions in the arterial phase (AP), portal phase (PP), and hepatobiliary phase (HBP) images. Independent predictors for VETC were identified through least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression analysis, utilising radiomics-AP, PP, HBP, along with 24 imaging features and 19 clinical characteristics. Subsequently, the clinico-radiologic model, radiomics model, and integrated model were established, with a nomogram visualising the integrated model. The performance for VETC prediction was evaluated using a receiver operating characteristic curve. Results: The integrated model, composed of 3 selected traditional imaging features (necrosis or severe ischemia [OR=2.457], peripheral washout [OR=1.678], LLR_AP (Lesion to liver ratio_AP) [OR=0.433] and radiomics-AP [OR=2.870], radiomics-HBP [OR=2.023], radiomics-PP [OR=1.546]), showcased good accuracy in predicting VETC patterns in both the training (AUC=0.873, 95% confidence interval [CI]: 0.821-0.925)) and validation (AUC=0.869, 95% CI:0.789-0.950) cohorts. Conclusion: This study established an integrated model that combines traditional imaging features and radiomic features from gadoxetic acid-enhanced MRI, demonstrating good performance in predicting VETC patterns.

Prediction for Aggressiveness and Postoperative Recurrence of Hepatocellular Carcinoma Using Gadoxetic Acid-Enhanced Magnetic Resonance Imaging.

RATIONALE AND OBJECTIVES: To investigate the predictive value of gadoxetic acid-enhanced magnetic resonance imaging (MRI) features on the pathologic grade, microvascular invasion (MVI), and cytokeratin-19 (CK19) expression in hepatocellular carcinomas (HCC), and to evaluate their association with postoperative recurrence of HCC. MATERIALS AND METHODS: This retrospective study included 147 patients with surgically confirmed HCCs who underwent gadoxetic-enhanced MRI. The lesions were evaluated quantitatively in terms of the relative enhancement ratio (RER), and qualitatively based on imaging features and clinical parameters. Logistic regression analyses were performed to investigate the value of these parameters in predicting the pathologic grade, MVI, and CK19 in HCC. Predictive factors for postoperative recurrence were determined using a Cox proportional hazards model. RESULTS: Peritumoral enhancement (odds ratio [OR], 3.396; p = 0.025) was an independent predictor of high pathologic grades. Serum protein induced by vitamin K absence or antagonist (PIVKA) level > 40 mAU/mL (OR, 3.763; p = 0.018) and peritumoral hypointensity (OR, 4.343; p = 0.003) were independent predictors of MVI. Predictors of CK19 included serum alpha-fetoprotein (AFP) level > 400 ng/mL (OR, 4.576; p = 0.005), rim enhancement (OR, 5.493; p = 0.024), and lower RER (OR, 0.013; p = 0.011). Peritumoral hypointensity (hazard ratio [HR], 1.957; p = 0.027) and poor pathologic grades (HR, 2.339; p = 0.043) were independent predictors of recurrence. CONCLUSION: We demonstrated the value of preoperative gadoxetic-enhanced MRI in predicting aggressive pathological features of HCC. Poor pathologic grades and peritumoral hypointensity may independently predict the recurrence of HCC.

A model incorporating histopathology and preoperative gadoxetic acid-enhanced MRI to predict early recurrence of hepatocellular carcinoma without microvascular invasion after curative hepatectomy.

OBJECTIVES: To assess the predictive value of preoperative gadoxetic acid (GA)-enhanced magnetic resonance imaging (MRI) features and postoperative histopathological grading for early recurrence of hepatocellular carcinoma (HCC) without microvascular invasion (MVI) after curative hepatectomy. METHODS: A total of 85 MVI-negative HCC cases were retrospectively analyzed. Cox analyses were used to identify the independent predictors of early recurrence (within a 24 months span). The clinical prediction Model-1 or Model-2 was established without or with postoperative pathological factor, respectively. Nomogram models were constructed and receiver operating characteristic (ROC) curve analysis was used to assess the models' predictive ability. Internal validation of the prediction models for early HCC recurrence was performed using a bootstrap re-sampling approach. RESULTS: In the multivariate cox regression analysis, Edmondson-Steiner grade, peritumoral hypointensity on hepatobiliary phase (HBP), and relative intensity ratio (RIR) in HBP were identified as independent variables associated with early recurrence. The C-index of the nomogram models and internal validation were both between 0.7 and 0.8, showing good model fitting and calibration effects. The area under the ROC curve (AUC) was 0.781 for Model-1 based on the two preoperative MRI factors. When a third factor, the Edmondson-Steiner grade, was included (Model-2), the AUC increased to 0.834, and the sensitivity increased from 71.4 to 96.4%. CONCLUSIONS: Edmondson-Steiner grade, peritumoral hypointensity on HBP, and RIR on HBP can help predict early recurrence of MVI-negative HCC. In comparison with Model-1 (only imaging features), Model-2 (imaging features + histopathological grades) increases the sensitivity in predicting early recurrence of HCC without MVI. ADVANCES IN KNOWLEDGE: Preoperative GA-enhanced MRI signs are of great value in predicting early postoperative recurrence of HCC without MVI, and a combined pathological model was established to evaluate the feasibility and effectiveness of this technique.

An Assessment of Temporal and Spatial Dynamics of Regional Water Resources Security in the DPSIR Framework in Jiangxi Province, China.

Water resources are critical for the survival and prosperity of both natural and socioeconomic systems. A good and informational water resources evaluation system is substantial in monitoring and maintaining sustainable use of water. The Driver-Pressure-State-Impact-Response (DPSIR) framework is a widely used general framework that enabled the measurement of water resources security in five different environmental and socioeconomic subsystems: driver, pressure, state, impact, and response. Methodologically, outcomes of water resources evaluation based on such framework and using fuzzy set pair analysis method and confidence interval rating method depend critically on a confidence threshold parameter which was often subjectively chosen in previous studies. In this work, we demonstrated that the subjectivity in the choice of this critical parameter can lead to contradicting conclusions about water resources security, and we addressed this caveat of subjectivity by proposing a simple modification in which we sample a range of thresholds and pool them to make more objective evaluations. We applied our modified method and used DPSIR framework to evaluate the regional water resource security in Jiangxi Province, China. The spatial-temporal analysis of water resources security level was carried out in the study area, despite the improvement in Pressure, Impact, and Response factors, the Driver factor is found to become less safe over the years. Significant variation of water security across cities are found notably in Pressure and Response factors. Furthermore, we assessed both cross-sectionally and longitudinally the inter-correlations among the DPSIR nodes in the DPSIR framework. The region-specific associations among the DPSIR nodes showed important deviances from the general DPSIR framework, and our analysis showed that in our study region, although Responses of regional government work effectively in improving Pressure and State security, more attention should be paid to improving Driver security in future regional water resources planning and management in Jiangxi Province, China.

Multiple perspectives reveal the gut toxicity of polystyrene microplastics on Eisenia fetida: Insights into community signatures of gut bacteria and their translocation.

The gut is the primary pathway by which soil animals are exposed to microplastics (MPs). However, the gut toxicity of MPs has not been elucidated in earthworms. Herein, we aimed to study the gut toxicity (e.g., gut barrier dysfunction, gut bacterial translocation, and pathogen invasion) of polystyrene microplastics (PS-MPs) on Eisenia fetida and its relationship with gut bacteria. We found that PS-MPs exposure caused gut barrier damage to Eisenia fetida. This damage included apparent injury of gut epithelial cells and significantly lower transcription levels of genes coding for gut tight junction (TJ)-related proteins. We then observed significantly increased levels of bacterial lipopolysaccharide (LPS) and gut bacterial load, indicating the occurrence of gut bacterial translocation and related barrier damage. Subsequently, antibacterial immune responses were activated and accompanied by a failure of the antioxidant defense system, indicating that pathogen invasion might occur. Gut barrier damage could weaken host selective pressures (deterministic process) on gut bacteria, such as particular pathogens. Indeed, members of Proteobacteria, e.g., Aeromonas and Escherichia/Shigella, regarded as potential opportunistic pathogens, were remarkable signatures of groups exposed to PS-MPs. These potential opportunistic gut bacteria were pivotal contributors to gut TJ damage and gut bacterial translocation resulting from PS-MPs exposure. In addition, the gut bacterial networks of PS-MPs exposure groups were more uncomplicated than those of the control group, but more negative interactions were easy to observe. In conclusion, our work sheds light on the molecular mechanism of earthworm gut toxicity caused by PS-MPs exposure and provides a prospective risk assessment of MPs in soil ecosystems.