A jugular venous compression adjunct for surgical excision of distensible orbital venous malformations.

PURPOSE: Orbital venous malformations (VM) pose challenges in complete resection due to indistinct borders and bleeding proclivity. Current methods for aiding surgical excision of distensible orbital venous malformations are inadequate. We investigated whether external neck compression could facilitate intraoperative distension of venous orbital lesions during surgical excision in patients diagnosed with VM. METHODS: Eighteen patients (8 males and 10 females) diagnosed with distensible venous anomalies were enrolled. Neck compression technology, was employed to distend the lesions before puncture embolization using n-butyl-2-cyanoacrylate glue under general anesthesia. The surgical process, along with preoperative to postoperative changes in ocular symptoms, were recorded. RESULTS: The average surgical duration was 95 min. A mean of 3.41 ml surgical glue was used for embolization. The compression belt maintained pressure at 35-40 mmHg. Total lesion resection was achieved in 12 patients, with 6 patients undergoing subtotal removal not requiring supplementary surgery. Symptoms were entirely alleviated in 17 patients, and signs of distensible lesions during the Valsalva maneuver were absent. One patient underwent secondary surgery for residual eyelid lesions. Minor complications included mild ocular movement restriction, residual subcutaneous induration, transiently increased orbital pressure, and lower lid ectropion in four, three, four, and one patient, respectively. Three patients experienced a mild post-operative visual acuity decrease, although none experienced vision loss. CONCLUSIONS: Direct orbital embolization aided by a jugular vein compression device is safe and demonstrates satisfactory outcomes in orbital varicose vein treatment.

TS-GCN: A novel tumor segmentation method integrating transformer and GCN.

As one of the critical branches of medical image processing, the task of segmentation of breast cancer tumors is of great importance for planning surgical interventions, radiotherapy and chemotherapy. Breast cancer tumor segmentation faces several challenges, including the inherent complexity and heterogeneity of breast tissue, the presence of various imaging artifacts and noise in medical images, low contrast between the tumor region and healthy tissue, and inconsistent size of the tumor region. Furthermore, the existing segmentation methods may not fully capture the rich spatial and contextual information in small-sized regions in breast images, leading to suboptimal performance. In this paper, we propose a novel breast tumor segmentation method, called the transformer and graph convolutional neural (TS-GCN) network, for medical imaging analysis. Specifically, we designed a feature aggregation network to fuse the features extracted from the transformer, GCN and convolutional neural network (CNN) networks. The CNN extract network is designed for the image's local deep feature, and the transformer and GCN networks can better capture the spatial and context dependencies among pixels in images. By leveraging the strengths of three feature extraction networks, our method achieved superior segmentation performance on the BUSI dataset and dataset B. The TS-GCN showed the best performance on several indexes, with Acc of 0.9373, Dice of 0.9058, IoU of 0.7634, F1 score of 0.9338, and AUC of 0.9692, which outperforms other state-of-the-art methods. The research of this segmentation method provides a promising future for medical image analysis and diagnosis of other diseases.

A K-nearest Neighbor Model to Predict Early Recurrence of Hepatocellular Carcinoma After Resection.

Background and Aims: Patients with hepatocellular carcinoma (HCC) surgically resected are at risk of recurrence; however, the risk factors of recurrence remain poorly understood. This study intended to establish a novel machine learning model based on clinical data for predicting early recurrence of HCC after resection. Methods: A total of 220 HCC patients who underwent resection were enrolled. Classification machine learning models were developed to predict HCC recurrence. The standard deviation, recall, and precision of the model were used to assess the model's accuracy and identify efficiency of the model. Results: Recurrent HCC developed in 89 (40.45%) patients at a median time of 14 months from primary resection. In principal component analysis, tumor size, tumor grade differentiation, portal vein tumor thrombus, alpha-fetoprotein, protein induced by vitamin K absence or antagonist-II (PIVKA-II), aspartate aminotransferase, platelet count, white blood cell count, and HBsAg were positive prognostic factors of HCC recurrence and were included in the preoperative model. After comparing different machine learning methods, including logistic regression, decision tree, naïve Bayes, deep neural networks, and k-nearest neighbor (K-NN), we choose the K-NN model as the optimal prediction model. The accuracy, recall, precision of the K-NN model were 70.6%, 51.9%, 70.1%, respectively. The standard deviation was 0.020. Conclusions: The K-NN classification algorithm model performed better than the other classification models. Estimation of the recurrence rate of early HCC can help to allocate treatment, eventually achieving safe oncological outcomes.

Predicting Infiltrative Hepatocellular Carcinoma Patient Outcome Post-TACE: MR Bias Field Correction Effect on 3D-quantitative Image Analysis.

Background and Aims: To investigate the impact of MR bias field correction on response determination and survival prediction using volumetric tumor enhancement analysis in patients with infiltrative hepatocellular carcinoma, after transcatheter arterial chemoembolization (TACE). Methods: This study included 101 patients treated with conventional or drug-eluting beads TACE between the years of 2001 and 2013. Semi-automated 3D quantification software was used to segment and calculate the enhancing tumor volume (ETV) of the liver with and without bias-field correction on multi-phasic contrast-enhanced MRI before and 1-month after initial TACE. ETV (expressed as cm3) at baseline imaging and the relative change in ETV (as % change, ETV%) before and after TACE were used to predict response and survival, respectively. Statistical survival analyses included Kaplan-Meier curve generation and Cox proportional hazards modeling. Q statistics were calculated and used to identify the best cut-off value for ETV to separate responders and non-responders (ETV cm3). The difference in survival was evaluated between responders and non-responders using Kaplan-Meier and Cox models. Results: MR bias field correction correlated with improved response calculation from baseline MR as well as survival after TACE; using a 415 cm3 cut-off for ETV at baseline (hazard ratio: 2.00, 95% confidence interval: 1.23-3.26, p=0.01) resulted in significantly improved response prediction (median survival in patients with baseline ETV <415 cm3: 19.66 months vs. ≥415 cm3: 9.21 months, p<0.001, log-rank test). A ≥41% relative decrease in ETV (hazard ratio: 0.58, 95%confidence interval: 0.37-0.93, p=0.02) was significant in predicting survival (ETV ≥41%: 19.20 months vs. ETV <41%: 8.71 months, p=0.008, log-rank test). Without MR bias field correction, response from baseline ETV could be predicted but survival after TACE could not. Conclusions: MR bias field correction improves both response assessment and accuracy of survival prediction using whole liver tumor enhancement analysis from baseline MR after initial TACE in patients with infiltrative hepatocellular carcinoma.

Intra-arterial therapy of neuroendocrine tumour liver metastases: comparing conventional TACE, drug-eluting beads TACE and yttrium-90 radioembolisation as treatment options using a propensity score analysis model.

OBJECTIVES: To compare efficacy, survival outcome and prognostic factors of conventional transarterial chemoembolisation (cTACE), drug-eluting beads TACE (DEB-TACE) and yttrium-90 radioembolisation (Y90) for the treatment of liver metastases from gastroenteropancreatic (GEP) neuroendocrine tumours (NELM). METHODS: This retrospective analysis included 192 patients (58.6 years mean age, 56% men) with NELM treated with cTACE (N = 122), DEB-TACE (N = 26) or Y90 (N = 44) between 2000 and 2014. Radiologic response to therapy was assessed according to Response Evaluation Criteria in Solid Tumours (RECIST) and World Health Organization (WHO) criteria using periprocedural MR imaging. Survival analysis included propensity score analysis (PSA), median overall survival (MOS), hepatic progression-free survival, Kaplan-Meier using log-rank test and the uni- and multivariate Cox proportional hazards model (MVA). RESULTS: MOS of the entire study population was 28.8 months. As for cTACE, DEB-TACE and Y90, MOS was 33.8 months, 21.7 months and 23.6 months, respectively. According to the MVA, cTACE demonstrated a significantly longer MOS as compared to DEB-TACE (p <.01) or Y90 (p = .02). The 5-year survival rate after initial cTACE, DEB-TACE and Y90 was 28.2%, 10.3% and 18.5%, respectively. CONCLUSIONS: Upon PSA, our study suggests significant survival benefits for patients treated with cTACE as compared to DEB-TACE and Y90. This data supports the therapeutic decision for cTACE as the primary intra-arterial therapy option in patients with unresectable NELM until proven otherwise. KEY POINTS: • cTACE achieved a significantly longer overall survival in patients with unresectable NELM. • Patients treated with cTACE showed a prolonged hepatic progression-free survival. • cTACE, DEB-TACE and Y90 radioembolisation demonstrated comparable safety and toxicity profiles. • Age >70 years, extrahepatic metastases and tumour burden >50% were identified as negative predictors. • Propensity score analysis suggests the superiority of cTACE over DEB-TACE and Y90.

MiR-155 Promotes Uveal Melanoma Cell Proliferation and Invasion by Regulating NDFIP1 Expression.

MicroRNAs refer to small RNA molecules that destroy the messenger RNA by binding on them inhibiting the production of protein. However, the role of miR-155 in uveal melanoma metastasis remains largely unknown. In this study, we found that miR-155 was upregulated in both uveal melanoma cells and tissues. Transfection of miR-155 mimic into uveal melanoma cells led to an increase in cell growth and invasion; in contrast, inhibition of miR-155 resulted in opposite effects. Also, we identified Nedd4-family interacting protein 1 as a direct target of miR-155, and the expression of Nedd4-family interacting protein 1 was inhibited by miR-155. Furthermore, ectopic expression of Nedd4-family interacting protein 1 restored the effects of miR-155 on cell proliferation and invasion of uveal melanoma cells. In conclusion, miR-155 acts as a tumor promotor in uveal melanoma through increasing cell proliferation and invasion. Thus, miR-155 might serve as a potential therapeutic target in patients with uveal melanoma.

An osmotic micro-pump integrated on a microfluidic chip for perfusion cell culture.

A novel microfluidic chip integrating an osmosis-based micro-pump was developed and used for perfusion cell culture. The micro-pump includes two sealed chambers, i.e., the inner osmotic reagent chamber and the outer water chamber, sandwiching a semi-permeable membrane. The water in the outer chamber was forced to flow through the membrane into the inner chamber via osmosis, facilitating continuous flow of fluidic zone in the channel. An average flow rate of 0.33microLmin(-1) was obtained within 50h along with a precision of 4.3% RSD (n=51) by using a 100mgmL(-1) polyvinylpyrrolidone (PVP) solution as the osmotic driving reagent and a flow passage area of 0.98cm(2) of the semi-permeable membrane. The power-free micro-pump has been demonstrated to be pulse-free offering stable flow rates during long-term operation. The present microfluidic chip has been successfully applied for the perfusion culture of human colorectal carcinoma cell by continuously refreshing the culture medium with the osmotic micro-pump. In addition, in situ cell immunostaining was also performed on the microchip by driving all the reagent zones with the integrated micro-pump.

Immunolabeling and NIR-excited fluorescent imaging of HeLa cells by using NaYF(4):Yb,Er upconversion nanoparticles.

Upconversion fluorescent nanoparticles can convert a longer wavelength radiation (e.g., near-infrared light) into a shorter wavelength fluorescence (e.g., visible light) and thus have emerged as a new class of fluorescent probes for biomedical imaging. Rare-earth doped beta-NaYF(4):Yb,Er upconversion nanoparticles (UCNPs) with strong UC fluorescence were synthesized in this work by using a solvothermal approach. The UCNPs were coated with a thin layer of SiO(2) to form core-shell nanoparticles via a typical Stober method, which were further modified with amino groups. After surface functionalization, the rabbit anti-CEA8 antibodies were covalently linked to the UCNPs to form the antibody-UCNP conjugates. The antibody-UCNP conjugates were used as fluorescent biolabels for the detection of carcinoembryonic antigen (CEA), a cancer biomarker expressed on the surface of HeLa cells. The successful conjugation of antibody to the UCNPs was found to lead to the specific attachment of the UCNPs onto the surface of the HeLa cells, which further resulted in the bright green UC fluorescence from the UCNP-labeled cells under 980 nm near-infrared (NIR) excitation and enabled the fluorescent imaging and detection of the HeLa cells. These results indicate that the amino-functionalized UCNPs can be used as fluorescent probes in cell immunolabeling and imaging. Because the UCNPs can be excited with a NIR light to exhibit strong visible fluorescence and the NIR light is safe to the body and can penetrate tissue as deep as several inches, our work suggests that, with proper cell-targeting or tumor-homing peptides or proteins conjugated, the NaYF(4):Yb,Er UCNPs can find potential applications in the in vivo imaging, detection, and diagnosis of cancers.