High-entropy oxides: an emerging anode material for lithium-ion batteries.

High entropy oxides (HEOs) have gained significant attention in multiple research fields, particularly in reversible energy storage. HEOs with rock-salt and spinel structures have shown excellent reversible capacity and longer cycle spans compared to traditional conversion-type anodes. However, research on HEOs and their electrochemical performance remains at an early stage. In this highlight, we review recent progress on HEO materials in the field of lithium-ion batteries (LIBs). Firstly, we introduce the synthesis methods of HEOs and some factors that affect the morphology and electrochemical properties of the synthesized materials. We then elaborate on the structural evolution of HEOs with rock-salt and spinel structures in lithium energy storage and summarize the relationship between morphology, pseudocapacitance effect, oxygen vacancy, and electrochemical performance. In the end, we give the challenges of HEO anodes for LIBs and present our opinions on how to guide the further development of HEOs for advanced anodes.

Two-dimensional shear wave elastography utilized in patients with ascites: a more reliable method than transient elastography for noninvasively detecting the liver stiffness-an original study with 170 patients.

Background: Two dimensional shear wave elastography (2D-SWE) is an ultrasound elastography technique based on shear waves implemented on a diagnostic ultrasound system. Transient elastography (TE) uses an ultrasound displacement M-mode and A-mode image produced by the system. So, TE mechanically induced impulse at tissue surface and difficultly across water. This paper compared the reliability and reproducibility of 2D-SWE with that of TE in patients with chronic hepatic disease. Comparisons were made in terms of the success rate, reliability, reproducibility, operation time, and influence of operator experience. Methods: A total of 170 patients were included in this study. Participants underwent 2D-SWE and TE performed by 2 different operators (a novice and veteran) on the same day. Nonparametric statistical tests were used to compare the technical success rate and reliable measurement rate, and inter-operator reproducibility was evaluated using intra-class correlation coefficients (ICCs). Results: The 2D-SWE technique showed a higher technical success rate than TE. Either 2D-SWE or TE can be utilized in patients with ascites lamella of less than 10 mm or ascites lamella plus skin-capsular distance of less than 25 mm. However, although the reliability rate of liver stiffness measurement with 2D-SWE did not significantly differ between the novice and veteran operators, for TE, there was a significant difference when body mass index (BMI) ≤25 kg/m2. When performed by the novice and veteran operators, 2D-SWE and TE both showed excellent inter-operator agreement, with ICCs of 0.968 and 0.973, respectively. Both 2D-SWE and TE displayed reliable measurement and excellent reproducibility in patients with chronic liver disease, were minimally influenced by operator experience. Conclusions: 2D-SWE may be a more reliable method for clinical application in noninvasive detecting the liver stiffness.

An immune, stroma, and epithelial-mesenchymal transition-related signature for predicting recurrence and chemotherapy benefit in stage II-III colorectal cancer.

BACKGROUND: Debates exist on the treatment decision of the stage II/III colorectal cancer (CRC) due to the insufficiency of the current TNM stage-based risk stratification system. Epithelial-mesenchymal transition (EMT) and tumor microenvironment (TME) have both been linked to CRC progression in recent studies. We propose to improve the prognosis prediction of CRC by integrating TME and EMT. METHODS: In total, 2382 CRC patients from seven datasets and one in-house cohort were collected, and 1640 stage II/III CRC patients with complete survival information and gene expression profiles were retained and divided into a training cohort and three independent validation cohorts. Integrated analysis of 398 immune, stroma, and epithelial-mesenchymal transition (ISE)-related genes identified an ISE signature independently associated with the recurrence of CRC. The underlying biological mechanism of the ISE signature and its influence on adjuvant chemotherapy was further explored. RESULTS: We constructed a 26-gene signature which was significantly associated with poor outcome in Training cohort (p < 0.001, HR [95%CI] = 4.42 [3.25-6.01]) and three independent validation cohorts (Validation cohort-1: p < 0.01, HR [95%CI] = 1.70 [1.15-2.51]; Validation cohort-2: p < 0.001, HR [95% CI] = 2.30 [1.67-3.16]; Validation cohort-3: p < 0.01, HR [95% CI] = 2.42 [1.25-4.70]). After adjusting for known clinicopathological factors, multivariate cox analysis confirmed the ISE signature's independent prognostic value. Subgroup analysis found that stage III patients with low ISE score might benefit from adjuvant chemotherapy (p < 0.001, HR [95%CI] = 0.15 [0.04-0.55]). Hypergeometric test and enrichment analysis revealed that low-risk group was enriched in thr immune pathway while high-risk group was associated with the EMT pathway and CMS4 subtype. CONCLUSION: We proposed an ISE signature for robustly predicting the recurrence of stage II/III CRC and help treatment decision by identifying patients who will not benefit from current standard treatment.

Predicting prognosis and immunotherapy response among colorectal cancer patients based on a tumor immune microenvironment-related lncRNA signature.

Long non-coding RNAs (lncRNAs) remodel the tumor immune microenvironment (TIME) by regulating the functions of tumor-infiltrating immune cells. It remains uncertain the way that TIME-related lncRNAs (TRLs) influence the prognosis and immunotherapy response of colorectal cancer (CRC). Aiming at providing survival and immunotherapy response predictions, a CRC TIME-related lncRNA signature (TRLs signature) was developed and the related potential regulatory mechanisms were explored with a comprehensive analysis on gene expression profiles from 97 immune cell lines, 61 CRC cell lines and 1807 CRC patients. Stratifying CRC patients with the TRLs signature, prolonged survival was observed in the low-risk group, while the patients in the high-risk group had significantly higher pro-tumor immune cells infiltration and higher immunotherapy response rate. Through the complex TRLs-mRNA regulation network, immunoregulation pathways and immunotherapy response pathways were found to be differently activated between the groups. In conclusion, the CRC TRLs signature is capable of making prognosis and immunotherapy response predictions, which may find application in stratifying patients for immunotherapy in the bedside.

A Transcription Factor Signature Can Identify the CMS4 Subtype and Stratify the Prognostic Risk of Colorectal Cancer.

Background: Colorectal cancer (CRC) is a heterogeneous disease, and current classification systems are insufficient for stratifying patients with different risks. This study aims to develop a generalized, individualized prognostic consensus molecular subtype (CMS)-transcription factors (TFs)-based signature that can predict the prognosis of CRC. Methods: We obtained differentially expressed TF signature and target genes between the CMS4 and other CMS subtypes of CRC from The Cancer Genome Atlas (TCGA) database. A multi-dimensional network inference integrative analysis was conducted to identify the master genes and establish a CMS4-TFs-based signature. For validation, an in-house clinical cohort (n = 351) and another independent public CRC cohort (n = 565) were applied. Gene set enrichment analysis (GSEA) and prediction of immune cell infiltration were performed to interpret the biological significance of the model. Results: A CMS4-TFs-based signature termed TF-9 that includes nine TF master genes was developed. Patients in the TF-9 high-risk group have significantly worse survival, regardless of clinical characteristics. The TF-9 achieved the highest mean C-index (0.65) compared to all other signatures reported (0.51 to 0.57). Immune infiltration revealed that the microenvironment in the high-risk group was highly immune suppressed, as evidenced by the overexpression of TIM3, CD39, and CD40, suggesting that high-risk patients may not directly benefit from the immune checkpoint inhibitors. Conclusions: The TF-9 signature allows a more precise categorization of patients with relevant clinical and biological implications, which may be a valuable tool for improving the tailoring of therapeutic interventions in CRC patients.

Multi-Size Deep Learning Based Preoperative Computed Tomography Signature for Prognosis Prediction of Colorectal Cancer.

Background: Preoperative and postoperative evaluation of colorectal cancer (CRC) patients is crucial for subsequent treatment guidance. Our study aims to provide a timely and rapid assessment of the prognosis of CRC patients with deep learning according to non-invasive preoperative computed tomography (CT) and explore the underlying biological explanations. Methods: A total of 808 CRC patients with preoperative CT (development cohort: n = 426, validation cohort: n = 382) were enrolled in our study. We proposed a novel end-to-end Multi-Size Convolutional Neural Network (MSCNN) to predict the risk of CRC recurrence with CT images (CT signature). The prognostic performance of CT signature was evaluated by Kaplan-Meier curve. An integrated nomogram was constructed to improve the clinical utility of CT signature by combining with other clinicopathologic factors. Further visualization and correlation analysis for CT deep features with paired gene expression profiles were performed to reveal the molecular characteristics of CRC tumors learned by MSCNN in radiographic imaging. Results: The Kaplan-Meier analysis showed that CT signature was a significant prognostic factor for CRC disease-free survival (DFS) prediction [development cohort: hazard ratio (HR): 50.7, 95% CI: 28.4-90.6, p < 0.001; validation cohort: HR: 2.04, 95% CI: 1.44-2.89, p < 0.001]. Multivariable analysis confirmed the independence prognostic value of CT signature (development cohort: HR: 30.7, 95% CI: 19.8-69.3, p < 0.001; validation cohort: HR: 1.83, 95% CI: 1.19-2.83, p = 0.006). Dimension reduction and visualization of CT deep features demonstrated a high correlation with the prognosis of CRC patients. Functional pathway analysis further indicated that CRC patients with high CT signature presented down-regulation of several immunology pathways. Correlation analysis found that CT deep features were mainly associated with activation of metabolic and proliferative pathways. Conclusions: Our deep learning based preoperative CT signature can effectively predict prognosis of CRC patients. Integration analysis of multi-omic data revealed that some molecular characteristics of CRC tumor can be captured by deep learning in CT images.

SQLE, A Key Enzyme in Cholesterol Metabolism, Correlates With Tumor Immune Infiltration and Immunotherapy Outcome of Pancreatic Adenocarcinoma.

Background: Pancreatic adenocarcinoma (PAAD) is a treatment-refractory cancer with poor prognosis. Accumulating evidence suggests that squalene epoxidase (SQLE) plays a pivotal role in the development and progression of several cancer types in humans. However, the function and underlying mechanism of SQLE in PAAD remain unclear. Methods: SQLE expression data were downloaded from The Cancer Genome Atlas and the Genotype-Tissue Expression database. SQLE alterations were demonstrated based on the cBioPortal database. The upstream miRNAs regulating SQLE expression were predicted using starBase. The function of miRNA was validated by Western blotting and cell proliferation assay. The relationship between SQLE expression and biomarkers of the tumor immune microenvironment (TME) was analyzed using the TIMER and TISIDB databases. The correlation between SQLE and immunotherapy outcomes was assessed using Tumor Immune Dysfunction and Exclusion. The log-rank test was performed to compare prognosis between the high and low SQLE groups. Results: We demonstrated a potential oncogenic role of SQLE. SQLE expression was upregulated in PAAD, and it predicted poor disease-free survival (DFS) and overall survival (OS) in patients with PAAD. "Amplification" was the dominant type of SQLE alteration. In addition, this alteration was closely associated with the OS, disease-specific survival, DFS, and progression-free survival of patients with PAAD. Subsequently, hsa-miR-363-3p was recognized as a critical microRNA regulating SQLE expression and thereby influencing PAAD patient outcome. In vitro experiments suggested that miR-363-3p could knock down the expression of SQLE and inhibit the proliferation of PANC-1. SQLE was significantly associated with tumor immune cell infiltration, immune checkpoints (including PD-1 and CTLA-4), and biomarkers of the TME. KEGG and GO analyses indicated that cholesterol metabolism-associated RNA functions are implicated in the mechanisms of SQLE. SQLE was inversely associated with cytotoxic lymphocytes and predicted immunotherapy outcomes. Conclusions: Collectively, our results indicate that cholesterol metabolism-related overexpression of SQLE is strongly correlated with tumor immune infiltration and immunotherapy outcomes in patients with PAAD.

DNA Repair-Related Gene Signature in Predicting Prognosis of Colorectal Cancer Patients.

Background: Increasing evidence have depicted that DNA repair-related genes (DRGs) are associated with the prognosis of colorectal cancer (CRC) patients. Thus, the aim of this study was to evaluate the impact of DNA repair-related gene signature (DRGS) in predicting the prognosis of CRC patients. Method: In this study, we retrospectively analyzed the gene expression profiles from six CRC cohorts. A total of 1,768 CRC patients with complete prognostic information were divided into the training cohort (n = 566) and two validation cohorts (n = 624 and 578, respectively). The LASSO Cox model was applied to construct a prediction model. To further validate the clinical significance of the model, we also validated the model with Genomics of Drug Sensitivity in Cancer (GDSC) and an advanced clear cell renal cell carcinoma (ccRCC) immunotherapy data set. Results: We constructed a prognostic DRGS consisting of 11 different genes to stratify patients into high- and low-risk groups. Patients in the high-risk groups had significantly worse disease-free survival (DFS) than those in the low-risk groups in all cohorts [training cohort: hazard ratio (HR) = 2.40, p < 0.001, 95% confidence interval (CI) = 1.67-3.44; validation-1: HR = 2.20, p < 0.001, 95% CI = 1.38-3.49 and validation-2 cohort: HR = 2.12, p < 0.001, 95% CI = 1.40-3.21). By validating the model with GDSC, we could see that among the chemotherapeutic drugs such as oxaliplatin, 5-fluorouracil, and irinotecan, the IC50 of the cell line in the low-risk group was lower. By validating the model with the ccRCC immunotherapy data set, we can clearly see that the overall survival (OS) of the objective response rate (ORR) with complete response (CR) and partial response (PR) in the low-risk group was the best. Conclusions: DRGS is a favorable prediction model for patients with CRC, and our model can predict the response of cell lines to chemotherapeutic agents and potentially predict the response of patients to immunotherapy.

TRIM32 Deficiency Impairs the Generation of Pyramidal Neurons in Developing Cerebral Cortex.

Excitatory-inhibitory imbalance (E/I) is a fundamental mechanism underlying autism spectrum disorders (ASD). TRIM32 is a risk gene genetically associated with ASD. The absence of TRIM32 causes impaired generation of inhibitory GABAergic interneurons, neural network hyperexcitability, and autism-like behavior in mice, emphasizing the role of TRIM32 in maintaining E/I balance, but despite the description of TRIM32 in regulating proliferation and differentiation of cultured mouse neural progenitor cells (NPCs), the role of TRIM32 in cerebral cortical development, particularly in the production of excitatory pyramidal neurons, remains unknown. The present study observed that TRIM32 deficiency resulted in decreased numbers of distinct layer-specific cortical neurons and decreased radial glial cell (RGC) and intermediate progenitor cell (IPC) pool size. We further demonstrated that TRIM32 deficiency impairs self-renewal of RGCs and IPCs as indicated by decreased proliferation and mitosis. A TRIM32 deficiency also affects or influences the formation of cortical neurons. As a result, TRIM32-deficient mice showed smaller brain size. At the molecular level, RNAseq analysis indicated reduced Notch signalling in TRIM32-deficient mice. Therefore, the present study indicates a role for TRIM32 in pyramidal neuron generation. Impaired generation of excitatory pyramidal neurons may explain the hyperexcitability observed in TRIM32-deficient mice.

Clinical significance of long noncoding RNA MNX1-AS1 in human cancers: a meta-analysis of cohort studies and bioinformatics analysis based on TCGA datasets.

MNX1-AS1 expression has been proposed to be abnormally upregulated in multiple human malignancies and be linked with the survival outcome of patients. However, relevant conclusions were yielded based on the limited samples. Therefore, we herein implemented a meta-analysis of the published cohort studies to further decipher the relationship of MNX1-AS1 level to prognosis and clinicopathological features in various cancers. Additionally, using The Cancer Genome Atlas (TCGA) datasets we carried out a bioinformatics analysis to make a further evaluation on the prognostic value of MNX1-AS1 expression. The results of meta-analysis indicated elevated MNX1-AS1 level closely correlated with poorer overall survival (OS) (HR = 1.97, 95% CI, 1.73-2.24; P < 0.00001), and disease-free survival (DFS) (HR = 2.24, 95% CI, 1.48-3.38; P = 0.0001) in cancers, which was confirmed by the bioinformatics analysis. Besides, it was observed the upregulated MNX1-AS1 level was significantly related to invasion depth, disease stage, tumor metastasis, and differentiation. Collectively, high MNX1-AS1 level correlated with poor survival outcome and aggressive clinicopathological characteristics in various cancers, suggesting that MNX1-AS1 may be applied as a prognostic marker and even a therapeutic target. Nevertheless, more high-quality studies designed with a large sample size should be conducted to further determine the clinical role of MNX1-AS1 in specific cancer types.

Transplantation of GABAergic Interneuron Progenitor Attenuates Cognitive Deficits of Alzheimer's Disease Model Mice.

Excitatory (E) and inhibitory (I) balance of neural network activity is essential for normal brain function and of particular importance to memory. Disturbance of E/I balance contributes to various neurological disorders. The appearance of neural hyperexcitability in Alzheimer's disease (AD) is even suggested as one of predictors of accelerated cognitive decline. In this study, we found that GAD67+, Parvalbumin+, Calretinin+, and Neuropeptide Y+ interneurons were progressively lost in the brain of APP/PS1 mice. Transplanted embryonic medial ganglionic eminence derived interneuron progenitors (IPs) survived, migrated, and differentiated into GABAergic interneuron subtypes successfully at 2 months after transplantation. Transplantation of IPs hippocampally rescued impaired synaptic plasticity and cognitive deficits of APP/PS1 transgenic mice, concomitant with a suppression of neural hyperexcitability, whereas transplantation of IPs failed to attenuate amyloid-ß accumulation, neuroinflammation, and synaptic loss of APP/PS1 transgenic mice. These observations indicate that transplantation of IPs improves learning and memory of APP/PS1 transgenic mice via suppressing neural hyperexcitability. This study highlights a causal contribution of GABAergic dysfunction to AD pathogenesis and the potentiality of IP transplantation in AD therapy.

A Metabolism-Related Radiomics Signature for Predicting the Prognosis of Colorectal Cancer.

Background: Radiomics refers to the extraction of a large amount of image information from medical images, which can provide decision support for clinicians. In this study, we developed and validated a radiomics-based nomogram to predict the prognosis of colorectal cancer (CRC). Methods: A total of 381 patients with colorectal cancer (primary cohort: n = 242; validation cohort: n = 139) were enrolled and radiomic features were extracted from the vein phase of preoperative computed tomography (CT). The radiomics score was generated by using the least absolute shrinkage and selection operator algorithm (LASSO). A nomogram was constructed by combining the radiomics score with clinicopathological risk factors for predicting the prognosis of CRC patients. The performance of the nomogram was evaluated by the calibration curve, receiver operating characteristic (ROC) curve and C-index statistics. Functional analysis and correlation analysis were used to explore the underlying association between radiomic feature and the gene-expression patterns. Results: Five radiomic features were selected to calculate the radiomics score by using the LASSO regression model. The Kaplan-Meier analysis showed that radiomics score was significantly associated with disease-free survival (DFS) [primary cohort: hazard ratio (HR): 5.65, 95% CI: 2.26-14.13, P < 0.001; validation cohort: HR: 8.49, 95% CI: 2.05-35.17, P < 0.001]. Multivariable analysis confirmed the independent prognostic value of radiomics score (primary cohort: HR: 5.35, 95% CI: 2.14-13.39, P < 0.001; validation cohort: HR: 5.19, 95% CI: 1.22-22.00, P = 0.026). We incorporated radiomics signature with the TNM stage to build a nomogram, which performed better than TNM stage alone. The C-index of the nomogram achieved 0.74 (0.69-0.80) in the primary cohort and 0.82 (0.77-0.87) in the validation cohort. Functional analysis and correlation analysis found that the radiomic signatures were mainly associated with metabolism related pathways. Conclusions: The radiomics score derived from the preoperative CT image was an independent prognostic factor and could be a complement to the current staging strategies of colorectal cancer.

The prognostic value of decreased NDRG1 expression in patients with digestive system cancers: A meta-analysis.

BACKGROUND: Digestive system cancers are recognized as associated with high morbidity and mortality. It is generally accepted that N-myc downstream-regulated gene 1 (NDRG1) is aberrantly overexpressed or downregulated in digestive system cancers, and its prognostic value remains controversial. Accordingly, we herein conducted a meta-analysis to explore whether NDRG1 expression is correlated with overall survival (OS) and clinicopathological characteristics of patients with digestive system cancers. METHODS: We systematically searched PubMed, EMBASE, and Web of Science for eligible studies up to June 6, 2017. In all, 19 publications with 21 studies, were included. RESULTS: The pooled results showed that low NDRG1 expression was significantly associated with worse OS in colorectal cancer (pooled HR = 1.67, 95% CI: 1.22-2.28, P < .001) and pancreatic cancer (pooled HR = 1.87, 95% CI: 1-3.5, P < .0001). Moreover, the relationships between low NDRG1 expression and higher OS ratio of patients with liver cancer (pooled HR = 0.44, 95% CI: 0.32-0.62, P = .009) and gallbladder cancer (pooled HR = 0.56, 95% CI: 0.23-1.38, P = .01) were observed. Nevertheless, no significant association was observed between low NDRG1 expression and OS in gastric cancer (pooled HR = 0.81, 95% CI: 0.45-1.43, P = .46) or esophageal cancer (pooled HR = 0.76, 95% CI: 0.26-2.24, P = .62). CONCLUSION: The prognostic significance of NDRG1 expression varies according to cancer type in patients with DSCs. Considering that several limitations existed in this meta-analysis, more studies are required to further assess the prognostic value of NDRG1 expression in patients with DSCs and relevant mechanisms.

Non-invasive assessment of liver fibrosis using two-dimensional shear wave elastography in patients with autoimmune liver diseases.

AIM: To determine the diagnostic accuracy of two-dimensional shear wave elastography (2D-SWE) for the non-invasive assessment of liver fibrosis in patients with autoimmune liver diseases (AILD) using liver biopsy as the reference standard. METHODS: Patients with AILD who underwent liver biopsy and 2D-SWE were consecutively enrolled. Receiver operating characteristic (ROC) curves were constructed to assess the overall accuracy and to identify optimal cut-off values. RESULTS: The characteristics of the diagnostic performance were determined for 114 patients with AILD. The areas under the ROC curves for significant fibrosis, severe fibrosis, and cirrhosis were 0.85, 0.85, and 0.86, respectively, and the optimal cut-off values associated with significant fibrosis (≥ F2), severe fibrosis (≥ F3), and cirrhosis (F4) were 9.7 kPa, 13.2 kPa and 16.3 kPa, respectively. 2D-SWE showed sensitivity values of 81.7% for significant fibrosis, 83.0% for severe fibrosis, and 87.0% for cirrhosis, and the respective specificity values were 81.3%, 74.6%, and 80.2%. The overall concordance rate of the liver stiffness measurements obtained using 2D-SWE vs fibrosis stages was 53.5%. CONCLUSION: 2D-SWE showed promising diagnostic performance for assessing liver fibrosis stages and exhibited high cut-off values in patients with AILD. Low overall concordance rate was observed in the liver stiffness measurements obtained using 2D-SWE vs fibrosis stages.

Equipping the 8th Edition American Joint Committee on Cancer Staging for Gastric Cancer with the 15-Node Minimum: a Population-Based Study Using Recursive Partitioning Analysis.

BAKCGROUND: The recently proposed 8th American Joint Committee on Cancer (AJCC) staging for gastric cancer (GC) did not include the evaluated lymph node (ELN) count as a prognostic indicator. In this study, we performed recursive partitioning analysis (RPA) to objectively combine the 15-ELN threshold and 8th AJCC stage to refine the staging for GC. METHODS: We analyzed 19,018 patients with non-metastatic GC from the Surveillance, Epidemiology, and End Results database. The dataset was randomly divided into training and validation sets. RESULTS: For each 8th AJCC stage, survival was significantly better for patients with ≥15 ELNs versus those with <15 ELNs (P < 0.001 for all). RPA divided non-metastatic GC into seven stages: RPA-IA (8th AJCC IA with ≥15 ELNs), RPA-IB (IA with <15 ELNs and IB/IIA with ≥15 ELNs), RPA-IIA (IB with <15 ELNs and IIB with ≥15 ELNs), RPA-IIB (IIA with <15 ELNs and IIIA with ≥15 ELNs), RPA-IIIA (IIB with <15 ELNs), RPA-IIIB (IIIA with <15 ELNs and IIIB ≥15 ELNs), and RPA-IIIC (IIIB with <15 ELNs and IIIC). The corresponding 5-year survival rates were 84.1, 70.3, 52.8, 41.4, 32.9, 21.7, and 10.2%, respectively (P < 0.001 for all pairwise comparisons). The RPA staging outperformed the 8th AJCC staging in terms of discrimination and homogeneity among the SEER training and validation sets, as well as an independent Chinese cohort. CONCLUSION: By equipping the 8th AJCC stage with the 15-ELN threshold, the proposed RPA staging is superior to the 8th AJCC staging without overcomplicating.

Equipping the American Joint Committee on Cancer staging for resectable pancreatic ductal adenocarcinoma with tumor grade: a recursive partitioning analysis.

Previous studies of pancreatic ductal adenocarcinoma (PDAC) have demonstrated that the addition of tumor grade to the 7th American Joint Committee on Cancer (AJCC) staging can provide improved prognostication and that the recently proposed 8th edition AJCC staging exhibited superior reproducibility to the 7th edition in resectable PDAC. Thus, we aimed to combine tumor grade and 8th AJCC stage to develop a refined staging scheme for resectable PDAC. We analyzed 7719 patients with resectable PDAC from the 2004-2012 Surveillance, Epidemiology, and End Results database. We performed recursive partitioning analysis (RPA) to objectively incorporate tumor grade with 8th AJCC stage into a novel staging system. The performance of the proposed RPA staging was assessed against the 8th AJCC staging in terms of discriminatory ability and prognostic homogeneity. For each 8th AJCC stage, survival was significantly worse for high-grade versus low-grade tumors. RPA divided resectable PDAC into five stages: RPA-IA (low-grade T1N0), RPA-IB (high-grade T1N0 or low-grade T2N0), RPA-IIA (high-grade T2N0 or low-grade T3N0/T1-T3N1), RPA-IIB (high-grade T3N0/T1-T3N1 or low-grade T1-T3N2), and RPA-III (high-grade T1-T3N2; median survival: 42, 26, 19, 15, and 12 months, respectively; P < 0.001). The RPA staging outperformed the 8th AJCC classifications in terms of discrimination (concordance index, 0.585 versus 0.565; P < 0.001) and prognostic homogeneity. Tumor grade can provide additional prognostic information to the 8th AJCC staging. The proposed RPA staging is a superior risk-stratified tool to the 8th AJCC staging and is not substantially more complex.

Assessment of radiofrequency ablation margin by MRI-MRI image fusion in hepatocellular carcinoma.

AIM: To investigate the feasibility and clinical value of magnetic resonance imaging (MRI)-MRI image fusion in assessing the ablative margin (AM) for hepatocellular carcinoma (HCC). METHODS: A newly developed ultrasound workstation for MRI-MRI image fusion was used to evaluate the AM of 62 tumors in 52 HCC patients after radiofrequency ablation (RFA). The lesions were divided into two groups: group A, in which the tumor was completely ablated and 5 mm AM was achieved (n = 32); and group B, in which the tumor was completely ablated but 5 mm AM was not achieved (n = 29). To detect local tumor progression (LTP), all patients were followed every two months by contrast-enhanced ultrasound, contrast-enhanced MRI or computed tomography (CT) in the first year after RFA. Then, the follow-up interval was prolonged to every three months after the first year. RESULTS: Of the 62 tumors, MRI-MRI image fusion was successful in 61 (98.4%); the remaining case had significant deformation of the liver and massive ascites after RFA. The time required for creating image fusion and AM evaluation was 15.5 ± 5.5 min (range: 8-22 min) and 9.6 ± 3.2 min (range: 6-14 min), respectively. The follow-up period ranged from 1-23 mo (14.2 ± 5.4 mo). In group A, no LTP was detected in 32 lesions, whereas in group B, LTP was detected in 4 of 29 tumors, which occurred at 2, 7, 9, and 15 mo after RFA. The frequency of LTP in group B (13.8%; 4/29) was significantly higher than that in group A (0/32, P = 0.046). All of the LTPs occurred in the area in which the 5 mm AM was not achieved. CONCLUSION: The MRI-MRI image fusion using an ultrasound workstation is feasible and useful for evaluating the AM after RFA for HCC.

Diagnostic accuracy of two-dimensional shear wave elastography for the non-invasive staging of hepatic fibrosis in chronic hepatitis B: a cohort study with internal validation.

OBJECTIVES: To determine the accuracy of two-dimensional shear wave elastography (2D-SWE) for noninvasive staging of hepatic fibrosis in chronic hepatitis B (CHB). METHODS: Patients with CHB infection who underwent liver biopsy were consecutively included. Receiver-operating characteristic (ROC) curves were constructed to assess the overall accuracy and identify optimal cutoff values. RESULTS: Three hundred three patients were analysed. The diagnostic performance characteristics were determined for the first 202 patients (the index cohort) and were validated on the next 101 patients (validation cohort). The areas under the ROC curves for significant fibrosis, severe fibrosis and cirrhosis were all greater than 0.90 and did not differ significantly between the index and validation cohorts. Using the cutoff values generated from the index cohort, the validation cohort 2D-SWE had negative predictive values of 82.6 % (95 % confidence interval [CI]: 68.4 % - 92.3 %) for significant fibrosis, 95.1 % (95 % CI: 86.3 % - 99.0 %) for severe fibrosis and 97.4 % (95 % CI: 90.8 % - 99.7 %) for cirrhosis. The positive predictive values were 83.6 % (95 % CI: 71.2 % - 92.2 %), 65.0 % (95 % CI: 48.1 - 79.5 %) and 60.0 % (95 % CI: 38.7 % - 78.9 %), respectively. CONCLUSION: The 2D-SWE showed good diagnostic accuracy in staging liver fibrosis in patients with CHB infection and assisted in excluding liver fibrosis and cirrhosis. KEY POINTS: • Two-dimensional shear wave elastography showed good diagnostic accuracy in assessing liver fibrosis. • Diagnostic performance did not differ significantly between the index and validation cohorts. • Two-dimensional shear wave elastography assisted in excluding liver fibrosis and cirrhosis.

Study of detection times for liver stiffness evaluation by shear wave elastography.

AIM: To investigate enough valid measurements (VMs) to assess liver fibrosis in chronic hepatitis B patients (CHB). METHODS: One hundred and twelve CHB patients (25 women, 87 men) with a mean age of 38.43 years received liver stiffness evaluations using real-time shear wave elastography for 10 VMs. All patients underwent liver biopsy. Based on the biopsy pathology, the liver stiffness data obtained from different VMs (1, 2, 3, 5 and 10 times) were compared for the evaluation of liver fibrosis. The correlation between the elastic modulus means of the liver obtained from different VMs of detection at each pathological stage was analysed. The receiver operating characteristic (ROC) curve was employed to determine the diagnostic performance of different VMs of detection, and the areas under the ROC curve of different groups were compared. RESULTS: The liver stiffness values obtained from 1 VM, 2 VMs, 3 VMs, 5 VMs and all 10 VMs for stage F0 were 6.95 ± 2.01 kPa, 6.87 ± 1.83 kPa, 6.90 ± 1.88 kPa, 6.95 ± 1.93 kPa and 7.15 ± 1.89 kPa, respectively (F = 0.043, P = 0.996). For stage F1, these values were 7.12 ± 1.72 kPa, 7.24 ± 1.72 kPa, 7.21 ± 1.74 kPa, 7.10 ± 1.78 kPa and 7.04 ± 1.70 kPa, respectively (F = 0.075, P = 0.990). For stage F2, they were 9.37 ± 3.87 kPa, 9.18 ± 3.68 kPa, 9.19 ± 3.81 kPa, 9.18 ± 3.81 kPa and 9.19 ± 3.53 kPa, respectively (F = 0.012, P = 1.000). For stage F3, these were 11.91 ± 3.88 kPa, 11.78 ± 4.04 kPa, 11.83 ± 4.07 kPa, 11.94 ± 4.17 kPa and 12.00 ± 4.02 kPa, respectively (F = 0.010, P = 1.000). For stage F4, the readings were 19.30 ± 7.63 kPa, 19.40 ± 7.36 kPa, 19.54 ± 7.43 kPa, 19.73 ± 7.21 kPa and 20.25 ± 7.22 kPa, respectively (F = 0.054, P = 0.995). There were no significant differences between these groups. Intraclass correlation coefficients among different pathological stages (F0-F4) with different detection VMs were 0.995, 0.993, 0.996, 0.994 and 0.996, respectively. The mean elasticity values from 1 VM, 2 VMs, 3 VMs, 5 VMs and 10 VMs can accurately distinguish fibrosis stages (F0 vs F1234, F01 vs F234, F012 vs F34 and F0123 vs F4) with no significant differences in the five groups (P > 0.05 for all). CONCLUSION: One VM may be sufficient to assess liver fibrosis by using SWE without any significant loss of accuracy in patients with CHB. However, future studies of larger patient samples are necessary for the validation of this method.

Influence of measurement depth on the stiffness assessment of healthy liver with real-time shear wave elastography.

The purpose of this study was to determine the measurement depth range within which liver stiffness can be reliably assessed using real-time shear wave elastography (SWE) technology. Measurements were performed on phantoms and healthy volunteers. In the first group of patients, measurements were performed at depths of 2-8 cm from the probe surface. In the second group of patients, measurements were conducted 0-7 cm below the liver capsule. Success rate of measurements (SRoM), success rate of patients (SRoS) and coefficients of variation (CVs) of repeated measurements were compared. The SRoMs at 3-7 cm and the CVs at 2-5 cm from the probe surface were significantly higher and lower than those at other depths (p < 0.001), respectively. SRoS was zero 0-1 cm below the liver capsule. Furthermore, the features of 2-D stiffness mapping images were also found to change with depth. According to our results, the depth range for the most reliable liver stiffness assessment using SWE should be 3-5 cm from the probe surface and simultaneously 1-2 cm below the liver capsule.