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Background: To provide patients the chance of accepting curative transjugular intrahepatic portosystemic shunt (TIPS) rather than palliative treatments for portal hypertension-related variceal bleeding and ascites, we aimed to assess hepatic-associated vascular morphological change to improve the predictive accuracy of overt hepatic encephalopathy (HE) risks., Methods: In this multicenter study, 621 patients undergoing TIPS were subdivided into training (413 cases from 3 hospitals) and external validation datasets (208 cases from another 3 hospitals). In addition to traditional clinical factors, we assessed hepatic-associated vascular morphological changes using maximum diameter (including absolute and ratio values). Three predictive models (clinical, hepatic-associated vascular, and combined) were constructed using logistic regression. Their discrimination and calibration were compared to test the necessity of hepatic-associated vascular assessment and identify the optimal model. Furthermore, to verify the improved performance of Model C-V , we compared it with four previous models, both in discrimination and calibration., Results: The combined model outperformed the clinical and hepatic-associated vascular models (training: 0.814, 0.754, 0.727; validation: 0.781, 0.679, 0.776; p < 0.050) and had the best calibration. Compared to previous models, Model C-V showed superior performance in discrimination. The high-, middle-, and low-risk populations displayed significantly different overt HE incidence (p < 0.001). Despite the limited ability of pre-TIPS ammonia to predict overt HE risks, the combined model displayed a satisfactory ability to predict overt HE risks, both in the low- and high-ammonia subgroups., Conclusion: Hepatic-associated vascular assessment improved the predictive accuracy of overt HE, ensuring curative chances by TIPS for suitable patients and providing insights for cirrhosis-related studies., (© 2024. The Author(s).)

Objective: The relationship between skeletal muscle and adipose tissue compositions and risk of overt hepatic encephalopathy (OHE) following transjugular intrahepatic portosystemic shunt (TIPS) treatment needs to be investigated., Methods: A total of 282 patients were collected from two medical centres. The median time of follow-up was 48.23 + 1.36 months and the first-year results of all patients after TIPS therapy were collected. The muscle and adipose tissue indices were quantified at the third lumbar vertebra level. Sarcopenia and myosteatosis were defined according to previous researches. Receiver operating characteristic curves, chi-square test, univariate and multivariate logistic regression analyses were employed to investigate the potential association between muscle and adipose indices, sarcopenia, myosteatosis and the risk of developing post-TIPS OHE., Results: All skeletal muscle indices, adipose tissue indices and sarcopenia had limited associations with post-TIPS OHE. Myosteatosis (148 cases, 52.5%, 55 with OHE, 37.2%) was identified as an independent risk factor for post-TIPS OHE. with P  < 0.001 in Chi-square test, P  < 0.001, odds ratio (OR): 2.854, 95% confidence interval (CI): 1.632-4.993 in univariate logistic regression analyses, and P  = 0.007, OR: 2.372, 95% CI: 1.268-4.438 in multivariate logistic regression analyses, respectively., Conclusion: Our results showed that myosteatosis was proven as an independent risk factor for the development of post-TIPS OHE., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background and Aims: The transjugular intrahepatic portosystemic shunt has controversial survival benefits; thus, patient screening should be performed preoperatively. In this study, we aimed to develop a model to predict post-transjugular intrahepatic portosystemic shunt mortality to aid clinical decision making., Methods: A total of 811 patients undergoing transjugular intrahepatic portosystemic shunt from five hospitals were divided into the training and external validation data sets. A modified prediction model of post-transjugular intrahepatic portosystemic shunt mortality (Model MT ) was built after performing logistic regression. To verify the improved performance of Model MT , we compared it with seven previous models, both in discrimination and calibration. Furthermore, patients were stratified into low-, medium-, high- and extremely high-risk subgroups., Results: Model MT demonstrated a satisfying predictive efficiency in both discrimination and calibration, with an area under the curve of .875 in the training set and .852 in the validation set. Compared to previous models (ALBI, BILI-PLT, MELD-Na, MOTS, FIPS, MELD, CLIF-C AD), Model MT showed superior performance in discrimination by statistical difference in the Delong test, net reclassification improvement and integrated discrimination improvement (all p < .050). Similar results were observed in calibration. Low-, medium-, high- and extremely high-risk groups were defined by scores of ≤160, 160-180, 180-200 and >200, respectively. To facilitate future clinical application, we also built an applet for Model MT ., Conclusions: We successfully developed a predictive model with improved performance to assist in decision making for transjugular intrahepatic portosystemic shunt according to survival benefits., (© 2023 The Authors. Liver International published by John Wiley & Sons Ltd.)

Background: Overt hepatic encephalopathy (HE) should be predicted preoperatively to identify suitable candidates for transjugular intrahepatic portosystemic shunt (TIPS) instead of first-line treatment. This study aimed to construct a 3D assessment-based model to predict post-TIPS overt HE., Methods: In this multi-center cohort study, 487 patients who underwent TIPS were subdivided into a training dataset (390 cases from three hospitals) and an external validation dataset (97 cases from another two hospitals). Candidate factors included clinical, vascular, and 2D and 3D data. Combining the least absolute shrinkage and operator method, support vector machine, and probability calibration by isotonic regression, we constructed four predictive models: clinical, 2D, 3D, and combined models. Their discrimination and calibration were compared to identify the optimal model, with subgroup analysis performed., Results: The 3D model showed better discrimination than did the 2D model (training: 0.719 vs. 0.691; validation: 0.730 vs. 0.622). The model combining clinical and 3D factors outperformed the clinical and 3D models (training: 0.802 vs. 0.735 vs. 0.719; validation: 0.816 vs. 0.723 vs. 0.730; all p < 0.050). Moreover, the combined model had the best calibration. The performance of the best model was not affected by the total bilirubin level, Child-Pugh score, ammonia level, or the indication for TIPS., Conclusion: 3D assessment of the liver and the spleen provided additional information to predict overt HE, improving the chance of TIPS for suitable patients. 3D assessment could also be used in similar studies related to cirrhosis., (© 2023. The Author(s).)

Aim: This study aimed to explore whether the addition of sarcopenia and visceral adiposity could improve the accuracy of model predicting progression-free survival (PFS) in hepatocellular carcinoma (HCC)., Methods: In total, 394 patients with HCC from five hospitals were divided into the training and external validation datasets. Patients were initially treated by liver resection or transarterial chemoembolization. We evaluated adipose and skeletal muscle using preoperative computed tomography imaging and then constructed three predictive models, including metabolic (Model MA ), clinical-imaging (Model CI ), and combined (Model MA-CI ) models. Their discrimination, calibration, and decision curves were compared, to identify the best model. Nomogram and subgroup analysis was performed for the best model., Results: Model MA-CI containing sarcopenia and visceral adiposity had good discrimination and calibrations (integrate area under the curve for PFS was 0.708 in the training dataset and 0.706 in the validation dataset). Model MA-CI had better accuracy than Model CI and Model MA . The performance of Model MA-CI was not affected by treatments or disease stages. The high-risk subgroup (scored > 198) had a significantly shorter PFS (p < 0.001) and poorer OS (p < 0.001)., Conclusions: The addition of sarcopenia and visceral adiposity improved accuracy in predicting PFS in HCC, which may provide additional insights in prognosis for HCC in subsequent studies., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Macrovascular invasion (MaVI) is a major threat to survival in hepatocellular carcinoma (HCC), which should be treated as early as possible to ensure safety and efficacy. In this aspect, MaVI prediction can be helpful. However, MaVI prediction is difficult because of the inter-class similarity and intra-class variation of HCC in computed tomography (CT) images. Moreover, existing methods fail to include clinical priori knowledge associated with HCC, leading to incomprehensive information extraction. In this paper, we proposed a prior knowledge-aware fusion network (PKAFnet) to accurately achieve MaVI prediction in CT images. First, a perception module was presented to extract features related to tumor marginal heterogeneity in the graph domain, which contributed to rotation invariance and captured intensity variations of tumor margin. Second, a tumor segmentation network was built to obtain global information of a 3D tumor image and information associated with tumor internal heterogeneity in the image domain. Finally, multi-domain features associated with the tumor margin and tumor region were combined by using a multi-domain attentional feature fusion module. Thus, by incorporating MaVI-related prior knowledge, our PKAFnet can alleviate overfitting, which can improve the discriminative ability. The proposed PKAFnet was validated on a multi-center dataset, and remarkable performance was achieved in an independent testing set. Moreover, the interpretability of perception module and segmentation network were presented in our paper, which illustrated the effectiveness and credibility of PKAFnet. Therefore, the proposed method showed great application potential for MaVI prediction.

Purpose: Preoperative prediction of overt hepatic encephalopathy (OHE) should be performed in patients with variceal bleeding treated using the transjugular intrahepatic portosystemic shunt (TIPS) procedure. A reliable prediction tool is therefore required., Method: Patients with cirrhosis-related variceal bleeding treated using the TIPS procedure were screened at two hospitals. Patients classified as Child-Pugh Class B were identified. The least absolute shrinkage and selection operator method and the backward stepwise selection method were used to screen the clinical and radiological characteristics of participants. Then, models were constructed accordingly to predict OHE. Area under the receiver operating characteristic curves, calibration curves, and decision curves were performed to discover the optimal model. Finally, whether clinical factors influenced the performance of our optimal model was tested., Results: A total of 191 patients were included (training cohort: 127 cases; validation cohort: 64 cases). Three novel radiological independent risk factors were found. The combined model outperformed the models containing clinical factors or radiological characteristics alone. The areas under the curve for the training and validation cohorts were 0.901 and 0.903, respectively, with satisfactory calibration and decision curves. The Model for End-Stage Liver Disease score, serum sodium, albumin, total bilirubin, and age exhibited limited influence on the performance of the combined model., Conclusions: These radiological characteristics are also independent risk factors for post-TIPS OHE. Combining clinical factors and radiological characteristics was an effective means of predicting OHE. This study's model could be used for preoperative selection of appropriate patients before the TIPS procedure is performed., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Models predicting future macrovascular invasion in hepatocellular carcinoma are constructed to assist timely interventions., Methods: A total of 366 HCC cases were retrospectively collected from five Chinese hospitals between April 2007 and November 2016: the training dataset comprised 281 patients from four hospitals; the external validation dataset comprised 85 patients from another hospital. Multi-task deep learning network-based models were constructed to predict future macrovascular invasion. The discrimination, calibration, and decision curves were compared to identify the best model. We compared the time to macrovascular invasion and overall survival using the best model and related image heterogeneity scores (H-score). Then, we determined the need for a segmentation subnet or the replacement deep learning algorithm by logistic regression in screening clinical/radiological factors. Finally, an applet was constructed for future application., Findings: The best model combined clinical/radiological factors and radiomic features. It achieved best discrimination (areas under the curve: 0·877 in the training dataset and 0·836 in the validation dataset), calibration, and decision curve. Its performance was not affected by the treatments and disease stages. The subgroups had statistical significance for time to macrovascular invasion (training: hazard ratio [HR] = 0·073, 95% confidence interval [CI]: 0·032-0·167, p < 0·001 and validation: HR = 0·090, 95%CI: 0·022-0·366, p < 0·001) and overall survival (training: HR = 0·344, 95%CI: 0·246-0·547, p < 0·001 and validation: HR = 0·489, 95%CI: 0·279 - 0·859, p  = 0·003) . Similar results were achieved when the patients were subdivided by the H-score. The subnet for segmentation and end-to-end deep learning algorithms improved the performance of the model., Interpretation: Our multi-task deep learning network-based model successfully predicted future macrovascular invasion. In high-risk populations, besides the current first-line treatments, more therapies may be explored for macrovascular invasion., Competing Interests: The authors have no conflicts of interest to declare., (© 2021 The Authors. Published by Elsevier Ltd.)

Purpose: For timely treatment of extrahepatic metastasis and macrovascular invasion (aggressive progressive disease [PD]) in hepatocellular carcinoma, models aimed at stratifying the risks of subsequent aggressive PD should be constructed., Patients and Methods: After dividing 332 patients from five hospitals into training (n = 236) and validation (n = 96) datasets, non-invasive models, including clinical/semantic factors (Model CS ), deep learning radiomics (Model D ), and both (Model CSD ), were constructed to stratify patients according to the risk of aggressive PD. We examined the discrimination and calibration; similarly, we plotted a decision curve and devised a nomogram. Furthermore, we performed analyses of subgroups who received different treatments or those in different disease stages and compared time to aggressive PD and overall survival in the high- and low-risk subgroups., Results: Among the constructed models, Model CSD , combining clinical/semantic factors and deep learning radiomics, outperformed Model CS and Model D (areas under the curve [AUCs] for the training dataset: 0.741, 0.815, and 0.856; validation dataset: 0.780, 0.836, and 0.862), with statistical difference per the net reclassification improvement, the integrated discrimination improvement, and/or the DeLong test in both datasets. Besides, Model CSD had the best calibration and decision curves. The performance of Model CSD was not affected by treatment types (AUC: resection = 0.839; transarterial chemoembolization = 0.895; p = 0.183) or disease stages (AUC: BCLC [Barcelona Clinic Liver Cancer] stage 0 and A = 0.827; BCLC stage AB &B = 0.861; p = 0.537). Moreover, the high-risk group had a significantly shorter median time to aggressive PD than the low-risk group (training dataset hazard ratio [HR] = 0.108, p < 0.001; validation dataset HR = 0.058, p < 0.001) and poorer overall survival (training dataset HR = 0.357, p < 0.001; validation dataset HR = 0.204, p < 0.001)., Conclusion: Our deep learning-based model successfully stratified the risks of aggressive PD. In the high-risk population, current guideline indicates that first-line treatments are insufficient to prevent extrahepatic metastasis and macrovascular invasion and ensure survival benefits, so more therapies may be explored for these patients., Competing Interests: The authors have no competing interests to declare in this work., (© 2021 Fu et al.)

Background/purpose: Overt hepatic encephalopathy (HE) risk should be preoperatively predicted to identify patients suitable for curative transjugular intrahepatic portosystemic shunt (TIPS) instead of palliative treatments., Methods: A total of 185 patients who underwent TIPS procedure were randomised (130 in the training dataset and 55 in the validation dataset). Clinical factors and imaging characteristics were assessed. Three different models were established by logistic regression analyses based on clinical factors (Model C ), imaging characteristics (Model I ), and a combination of both (Model CI ). Their discrimination, calibration, and decision curves were compared, to identify the best model. Subgroup analysis was performed for the best model., Results: Model CI , which contained two clinical factors and two imaging characteristics, was identified as the best model. The areas under the curve of Model C , Model I , and Model CI were 0.870, 0.963, and 0.978 for the training dataset and 0.831, 0.971, and 0.969 for the validation dataset. The combined model outperformed the clinical and imaging models in terms of calibration and decision curves. The performance of Model CI was not influenced by total bilirubin, Child-Pugh stages, model of end-stage liver disease score, or ammonia. The subgroup with a risk score ≥ 0.88 exhibited a higher proportion of overt HE (training dataset: 13.3% vs. 97.4%, p < 0.001; validation dataset: 0.0% vs. 87.5%, p < 0.001)., Conclusion: Our combination model can successfully predict the risk of overt HE post-TIPS. For the low-risk subgroup, TIPS can be performed safely; however, for the high-risk subgroup, it should be considered more carefully., (© 2021. The Author(s).)

Increasing evidence indicates that c-mesenchymal-epithelial transition factor (cMET) plays an important role in the malignant progression of colorectal cancer (CRC). However, the underlying mechanism is not fully understood. As a metastasis suppressor, raf kinase inhibitory protein (RKIP) loss has been reported in many cancer types. In this study, the expression levels of cMET and RKIP in CRC tissues and cell lines were determined, and their crosstalk and potential biological effects were explored in vitro and in vivo. Our results showed that cMET was inversely correlated with RKIP. Both cMET upregulation and RKIP downregulation indicated poor clinical outcomes. Moreover, the MAPK/ERK signaling pathway was implicated in the regulation of cMET and RKIP. Overexpression of cMET promoted tumor cell epithelial-mesenchymal transition, invasion, migration, and chemoresistance, whereas the effects could be efficiently inhibited by increased RKIP. Notably, small hairpin RNA-mediated cMET knockdown dramatically suppressed cell proliferation, although no RKIP-induced influence on cell growth was observed in CRC. Altogether, cMET overexpression may contribute to tumor progression by inhibiting the antioncogene RKIP, providing preclinical justification for targeting RKIP to treat cMET-induced metastasis of CRC., (© 2020 Wiley Periodicals LLC.)

Rationale : Hepatocellular carcinoma (HCC) is one of the leading causes of mortality worldwide. Methyltransferase-like 3 (Mettl3), an RNA N6-methyladenosine (m6A) methyltransferase, has been shown to act as an oncogene in several human cancers. However, the regulatory role of posttranslational modifications of Mettl3 in liver cancer remains elusive. Methods : SUMOylation was analyzed using immunoprecipitation and western blot assays. In vitro and in vivo biological functions were examined using MTS, colony formation, wound healing, transwell, apoptosis, and viability assays and the BALB/c nude mouse model, respectively. Immunohistochemistry was conducted to evaluate the prognostic value of Mettl3 expression in HCC. The regulatory mechanism of Mettl3 in HCC was investigated by m6A dot blot, immunofluorescence, dual luciferase reporter, protein stability, and RNA stability assays. Results : Mettl3 was found to be SUMOylated by a small ubiquitin-like modifier SUMO1. Further, SUMOylation of Mettl3 was increased upon mitogen stimulation, which correlated with UBC9 upregulation, and was positively correlated with high metastatic potential of liver cancer. Finally, SUMOylation of Mettl3 was found to regulate HCC progression via controlling Snail mRNA homeostasis in an m6A methyltransferase activity-dependent manner. Conclusions : This study revealed a novel mechanism of SUMOylated Mettl3-mediated Snail mRNA homeostasis, identifying the UBC9/SUMOylated Mettl3/Snail axis as a novel mediator of the SUMO pathway involved in HCC progression., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Objectives: Models should be developed to assist choice between liver resection (LR) and transarterial chemoembolization (TACE) for hepatocellular carcinoma., Methods: After separating 520 cases from 5 hospitals into training (n = 302) and validation (n = 218) data sets, we weighted the cases to control baseline difference and ensured the causal effect between treatments (LR and TACE) and estimated progression-free survival (PFS) difference. A noninvasive PFS model was constructed with clinical factors, radiological characteristics, and radiomic features. We compared our model with other 4 state-of-the-art models. Finally, patients were classified into subgroups with and without significant PFS difference between treatments., Results: Our model included treatments, age, sex, modified Barcelona Clinic Liver Cancer stage, fusion lesions, hepatocellular carcinoma capsule, and 3 radiomic features, with good discrimination and calibrations (area under the curve for 3-year PFS was 0.80 in the training data set and 0.75 in the validation data set; similar results were achieved in 1- and 2-year PFS). The model had better accuracy than the other 4 models. A nomogram was built, with different scores assigned for LR and TACE. Separated by the threshold of score difference between treatments, for some patients, LR provided longer PFS and might be the better option (training: hazard ratio [HR] = 0.50, P = 0.014; validation: HR = 0.52, P = 0.026); in the others, LR provided similar PFS with TACE (training: HR = 0.84, P = 0.388; validation: HR = 1.14, P = 0.614). TACE may be better because it was less invasive., Discussion: We propose an individualized model predicting PFS difference between LR and TACE to assist in the optimal treatment choice.

The applications of Polylactide (PLA) microspheres in biomedical areas are greatly determined by the size, morphology and internal structure. Taking advantage of the formation of stereocomplex (SC) crystallites between poly(L-lactide) (PLLA) and poly(D-lactide) (PDLA), we propose a facile strategy to prepare PLA microspheres with tunable morphology and crystalline structure by compounding PLLA and PDLA. With increasing PDLA content, the crystallinity of SC-PLA rose gradually until the ratio of PLLA and PDLA reached 1:1 and then fell. Correspondingly, the morphology of the microspheres were varied (smooth, porous, golf-ball like, guava like) and higher crystallinity of SC-PLA would lead to a more coarse and porous structure. Finally, three typical kinds of Rifampicin-loaded microspheres with different ratio of PLLA and PDLA (7:3, 3:7, 10:0, sorted by porosity from high to low) were prepared and the release behavior was compared. At 30 h, the cumulative release of 7:3, 3:7 and 10:0 microspheres were 32.6%, 17.8% and 6.0% respectively, indicating that the release profiles were generally determined by the porosity of the microspheres. Our findings not only provide a new strategy to prepare PLA microspheres with controllable morphology but offer additional possibilities for the applications of SC-PLA products in biomedical area., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Hypoxia within solid tumors is often responsible for the failure of radiotherapy. The development of hypoxia-targeting nanomaterials - aimed at enhancing the effect of radiotherapy by electrical or heat effects and at modulating hypoxia in the tumor microenvironment - is a promising strategy to address this issue. We provide an overview of recently developed advanced materials that potentiate radiotherapy. First, we summarize novel materials for oxygen delivery or production to modify the tumor microenvironment, thus improving the effects of ionizing radiation. Second, we present new approaches for the design of high- Z element-based multifunctional nanoplatforms to enhance radiotherapy. Third, novel drug delivery systems for hypoxic regions and hypoxia-inducible factor-1-targeted therapies are discussed. Fourth, we establish the effectiveness of X-ray- or near-infrared-responsive nanoparticles for selectively triggering therapeutic effects under hypoxic conditions. Finally, this review emphasizes the importance of research in the field of nanomedicine focused on tumor hypoxia to improve clinical outcomes., Competing Interests: Disclosure The authors report no conflicts of interest in this work.

Liver cancer stem cells (LCSCs) have important roles in the occurrence, development, recurrence, therapy resistance and metastasis of hepatocellular carcinoma (HCC). Therefore, intensive studies are undergoing to identify the mechanisms by which LCSCs contribute to HCC invasion and metastasis, and to design more efficient treatments for this disease. With continuous efforts in LCSC research over the years, therapies targeting LCSCs are thought to have great potential for the clinical treatment and prognosis of liver cancer. Novel LCSC surface markers are continuously discovered and several have been used in targeted therapies to reduce HCC recurrence, metastasis, and drug resistance following tumor resection. The present review describes the surface markers characterizing LCSCs and the recent progress in therapies targeting these markers, including antibodies and polypeptides.

Transcatheter arterial chemoembolization (TACE) and sorafenib combination treatment for unselected hepatocellular carcinoma (HCC) is controversial. We explored the potential of texture analysis for appropriate patient selection. There were 261 HCCs included (TACE group: n = 197; TACE plus sorafenib (TACE+Sorafenib) group n = 64). We applied a Gabor filter and wavelet transform with 3 band-width responses (filter 0, 1.0, and 1.5) to portal-phase computed tomography (CT) images of the TACE group. Twenty-one textural parameters per filter were extracted from the region of interests delineated around tumor outline. After testing survival correlations, the TACE group was subdivided according to parameter thresholds in receiver operating characteristic curves and compared to TACE+Sorafenib group survival. The Gabor-1-90 (filter 0) was most significantly correlated with TTP. The TACE group was accordingly divided into the TACE-1 (Gabor-1-90 ≤ 3.6190) and TACE-2 (Gabor-1-90 > 3.6190) subgroups; TTP was similar in the TACE-1 subgroup and TACE+Sorafenib group, but shorter in the TACE-2 subgroup. Only wavelet-3-D (filter 1.0) correlated with overall survival (OS), and was used for subgrouping. The TACE-5 (wavelet-3-D ≤ 12.2620) subgroup and the TACE+Sorafenib group showed similar OS, while the TACE-6 (wavelet-3-D > 12.2620) subgroup had shorter OS. Gabor-1-90 and wavelet-3-D were consistent.Independent of tumor number or size, CT textural parameters are correlated with TTP and OS. Patients with lower Gabor-1-90 (filter 0) and wavelet-3-D (filter 1.0) should be treated with TACE and sorafenib. Texture analysis holds promise for appropriate selection of HCCs for this combination therapy.

This study explored the potential of computed tomography (CT) textural feature analysis for the stratification of single large hepatocellular carcinomas (HCCs) > 5 cm, and the subsequent determination of patient suitability for liver resection (LR) or transcatheter arterial chemoembolization (TACE). Wavelet decomposition was performed on portal-phase CT images with three bandwidth responses (filter 0, 1.0, and 1.5). Nine textural features of each filter were extracted from regions of interest. Wavelet-2-H (filter 1.0) in LR and wavelet-2-V (filter 0 and 1.0) in TACE were related to survival. Subsequently, LR and TACE patients were divided based on the wavelet-2-H and wavelet-2-V median at filter 1.0 into two subgroups (+ or -). LR+ patients showed the best survival, followed by LR-, TACE+, and TACE-. We estimated that LR+ patients treated using TACE would exhibit a survival similar to TACE- patients and worse than TACE+ patients, with a severe compromise in overall survival. LR was recommended for TACE- patients, whereas TACE was preferred for LR- and TACE+ patients. Independent of tumor size, CT textural features showed positive and negative correlations with survival after LR and TACE, respectively. Although further validation is needed, texture analysis demonstrated the feasibility of using HCC patient stratification for determining the suitability of LR vs. TACE.

Corona enhancement and mosaic architecture are 2 radiologic features of hepatocellular carcinoma (HCC). However, neither their prognostic values nor their impacts on the selection of liver resection (LR) versus transcatheter arterial chemoembolization (TACE) as treatment modalities have been established.We retrospectively analyzed 275 patients with a single HCC lesion >5 cm without extrahepatic metastasis treated with LR or TACE. In LR patients, the overall survival (OS) and time to progression (TTP) were compared between corona enhancement negative (corona-) versus positive (corona+) and mosaic architecture negative (mosaic-) versus positive (mosaic+) patients. Furthermore, by the combination of corona and mosaic, LR patients were divided into negative for both corona and mosaic patterns (LR-/-), positive for only 1 feature (LR+/-), and positive for both (LR+/+); their OS and TTP were compared to those of the TACE group. Cox regression was performed to identify independent factors for OS.In the survival plots for LR, corona- had better OS and TTP than corona+, and mosaic- had better OS than mosaic+. There was no significant difference in TTP between the subgroups. On Cox regression analysis, corona enhancement, but not mosaic architecture, was a significant factor for OS, whereas neither were a significant factor for TTP. In TACE patients, neither corona nor mosaic patterns had significant correlations with OS or TTP. In the whole population, LR-/ and LR+/- subgroups had similar OS, which was better than the LR+/+ and TACE groups. Moreover, LR-/- and LR+/- patients had better TTP than TACE patients, but there were no differences between the LR-/- versus LR+/-, LR-/ versus LR+/+, LR+/- versus LR+/+, and LR+/+ versus TACE groups. On Cox regression analysis, the presence of corona/mosaic patterns was an independent prognostic factor for OS.Our results showed that, for patients with a single HCC >5 cm without extrahepatic metastasis, corona and mosaic patterns are indicators of limited LR efficacy. When both of the features are present, TACE can be used instead of LR with no negative influence on survival.

Background: The survival benefit of combining sorafenib and transarterial chemoembolization (TACE) therapy compared with sorafenib monotherapy for patients with advanced hepatocellular carcinoma (HCC) and main portal vein tumor thrombosis (MPVTT) is unclear., Methods: Between January 2009 and June 2013, 183 consecutive patients with advanced HCC (Barcelona Clinic Liver Cancer stage C) and MPVTT were retrospectively reviewed. Of these, 89 patients with advanced HCC and MPVTT were enrolled in this study: 45 were treated with combination therapy (sorafenib-TACE group), and the other 44 treated with sorafenib monotherapy (sorafenib group)., Results: The mean number of TACE sessions per patient was 2.6 (range: 1-5). The median duration of sorafenib in the sorafenib-TACE group and sorafenib group was 5.6 months and 5.4 months, respectively. The disease control rate was similar between the two groups. Median time to progression was 3.0 months (95% confidence interval [CI]: 2.2, 3.7) in the sorafenib-TACE group, and 3.0 months (95% CI: 2.1, 3.8) in the sorafenib group (p = .924). Median overall survival was 7.0 months (95% CI: 6.1, 7.8) and 6.0 months (95% CI: 4.7, 7.3) in the sorafenib-TACE group and the sorafenib group, respectively (p = .544). The adverse events related to sorafenib were comparable between the two groups. Twenty-one adverse events of grade 3-4 related to TACE occurred in 12 patients (26.7%), and 2 of them died (4.4%)., Conclusion: This study demonstrated no advantage of combination therapy over sorafenib monotherapy. Considering the patients' morbidity after TACE, sorafenib monotherapy is appropriate for managing patients with advanced HCC and MPVTT., (©AlphaMed Press.)

Aims: To assess the efficacy of continued administration of sorafenib for patients with unresectable hepatocellular carcinoma (HCC) treated with local regional therapy (LRT) after a complete response (CR), also, the adverse events of sorafenib after discontinuation of administration were observed., Methods: Between April 2008 and May 2012, 956 consecutive patients with unresectable HCC treated with LRT (transarterial chemoembolization, radiofrequency ablation) combined with sorafenib were retrospectively investigated. Of these, 157 patients with a CR were enrolled: 102 of them continued to receive sorafenib (test group) and the other 55 stopped receiving sorafenib (control group)., Results: The median recurrence-free survival (RFS), post-complete response overall survival (pOS) and overall survival (OS) in the test and control groups were 11 months (95% CI: 6.1, 15.9), 25 months (95% CI: 20.7, 29.3) and 33 months (95% CI: 29.2, 36.8) and 12 months (95% CI: 10.4, 13.6), 28 months (95% CI 24.2, 31.8) and 34 months (95% CI: 30.8, 37.2) respectively. The differences in RFS, pOS and OS between the groups were not significant (P = 0.768, 0.797 and 0.730, respectively). The adverse events related to sorafenib resolved after discontinuation of administration and the quality of life (QoL) scores improved., Conclusions: Patients with unresectable HCC who achieved a CR did not benefit from continued sorafenib in terms of RFS, pOS or OS. The adverse events of sorafenib were reversible, and discontinuation of sorafenib may improve the QoL of patients who have achieved a CR.

Purpose: To investigate whether serum microRNA-210 (miR-210) level can serve as an indicator of prognosis and a predictor of efficacy of transarterial chemoembolization in patients with hepatocellular carcinoma (HCC)., Materials and Methods: Serum miR-210 level was measured in 113 patients with HCC before transarterial chemoembolization (t1), 3 days after transarterial chemoembolization (t2), and 4 weeks after transarterial chemoembolization (t3) and compared with 39 healthy control subjects. The correlations between miR-210 levels and clinicopathologic factors, tumor responsiveness, and prognosis were analyzed. The modified Response Evaluation Criteria in Solid Tumors assessment was conducted at t3., Results: A higher mean baseline miR-210 level was observed in patients with HCC compared with control subjects (3.69 ± 2.04 vs 1.08 ± 0.45, P < .001). A positive correlation between baseline miR-210 level and tumor size (P < .001), vascular invasion (P = .005), tumor differentiation (P = .037), and Barcelona Clinic Liver Cancer stage (P < .001) was observed. Elevated baseline miR-210 level also served as an independent prognostic factor predicting poor overall survival (risk ratio, 2.082; P = .003). Patients who did not respond to transarterial chemoembolization had higher baseline miR-210 levels than patients who did respond to treatment (4.34 ± 1.67 vs 3.28 ± 2.15, P < .001). In addition, miR-210 levels increased significantly 4 weeks after transarterial chemoembolization in nonresponders (5.79 ± 2.06 at t3 vs 4.34 ± 1.67 at t1, P < .001), whereas no significant change was observed in responders (3.53 ± 2.20 at t3 vs 3.28 ± 2.15 at t1, P = .116). Lastly, an inverse correlation was identified between miR-210 change t1-t3 with the time to radiologic progression (P < .001)., Conclusions: Serum miR-210 may represent a novel biomarker for predicting efficacy of transarterial chemoembolization and overall survival for patients with HCC., (Copyright © 2014 SIR. Published by Elsevier Inc. All rights reserved.)

Stretchable conductors, which can keep their excellent electrical conductivity while highly stretched, have been investigated extensively due to their wide range of applications in flexible and stretchable electronics, wearable displays, etc.; however, their preparation is often complicated and expensive. Herein, an efficient method to prepare high performance stretchable conductors through morphological control of conductive networks formed with carbon nanotubes (CNTs) in an elastomer matrix is reported. It is observed that an interface-mediated method could be used to align randomly oriented filler during stretching and to induce buckling of CNTs during relaxation. Further morphological studies indicate the possible formation of a wavy CNT structure induced by cyclic pre-straining. Subsequent thermal annealing is observed to collapse the oriented network and improve the local contacts between conductive networks. Through such a simple procedure, a conductivity of nearly 1000 S m(-1) and a stretchability of 200% can be achieved for composites containing 20 wt% CNTs. CNTs are observed to buckle over a large area in polymer bulk, and the combination of pre-straining and thermal annealing modifies the conductive network in the elastomer matrix. As a general method, this could be used for easy fabrication of high-performance stretchable conductors for arbitrary-shaped objects on a large scale., (Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)