Realistic boundary conditions in SimVascular through inlet catheter modeling

Objective This study aims at developing a pipeline that provides the capability to include the catheter effect in the computational fluid dynamics (CFD) simulations of the cardiovascular system and other human vascular flows carried out with the open-source software SimVascular. This tool is particularly useful for CFD simulation of interventional radiology procedures such as tumor embolization where estimation of a therapeutic agent distribution is of interest. Results A pipeline is developed that generates boundary condition files which can be used in SimVascular CFD simulations. The boundary condition files are modified such that they simulate the effect of catheter presence on the flow field downstream of the inlet. Using this pipeline, the catheter flow, velocity profile, radius, wall thickness, and deviation from the vessel center can be defined. Since our method relies on the manipulation of the boundary condition that is imposed on the inlet, it is sensitive to the mesh density. The finer the mesh is (especially around the catheter wall), the more accurate the velocity estimations are. In this study, we also utilized this pipeline to qualitatively investigate the effect of catheter presence on the flow field in a truncated right hepatic arterial tree of a liver cancer patient.

Liver Cancer Patient Classification on a Multiple-Stage using Hybrid Classification Methods

This paper proposes a model to detect liver cancer patients and estimate the abnormality level of livers using a classification method based on an Indian liver patient dataset. The dataset is prepared by 3 processes: preliminary study, data cleansing, and handling imbalanced class to build the model based on multiple-stages using hybrid classification methods. The 1st stage is liver cancer patient detection. The 2nd stage is abnormality level of liver estimation, as divided using the DeRitis Ratio. The abnormality level of livers is divided into 3 levels: low, medium, and high, called ALL framework. Machine learning method is used to build multiple classification stages, which consist of Multilayer Perceptron, Logistic Regression, and Random Forest. The experimental results demonstrate that the 1st model (stage I) can detect liver cancer patient with 78.88 % accuracy. The 2nd model (stage II) achieves accuracy of 99.83 % for abnormality level of liver estimation. In addition, we compare our proposed model with another dataset. Our proposed model also outperforms detection with 76.73 and 98.26 % accuracy in stage I and stage II, respectively. Our proposed model is a benefit for physicians to support diagnosis and treatment, especially in the case of physicians desiring an intelligent decision support system.

ROS new function for ECT imaging observation of sustained 99mTC-labeled cytarabine in liver cancer patient with hydrogen peroxide.

e15568 Background: To investigate the sustaining time of 99mTc labeled cytarabine in the tumor of liver cancer patients by ROS under ECT imaging instrument. Methods: A liver cancer patient with 2 lesions in the liver was enrolled in this study. After obtaining informed consent and excluding relevant contraindications, two tumors in the liver of the patient were guided by single photon emission computed tomography (ECT). Injecting the drug, the tumor was injected with 99m TC-labeled cytarabine solution as control, the tumor was injected with 99m TC-labeled cytarabine + hydrogen peroxide solution (ROS) as experimental, and the two tumor masses were detected by ECT imaging, with an intensity of 1h as background. The drug retention rate was calculated by caculated of deduction of the baseline (minus background) at 1h, 3h, and 23h. Results: The patient was detected by ECT on the right laid down position. The area of the region of interest was 679 account by Gama detector, and the background level of the liver was 494 account. The acquisition time was about 400 seconds as a standard acquisition. The ECT imaging showed that the labeling rate of 99mTC-labeled cytarabine was about 100%. The drug of 99mTC-labeled cytarabineretentionrates in tumor lesions with ROS at 1 hours, 3 hours, and 23 hours were 97.83%, 81.63%, and 60.72%, respectively; the drug retention rates in tumor lesions without ROS at 1 hours, 3 hours, and 23 hours were 44.74%, 15.87%, and 0, respectively. Conclusions: The ROS can hold drug in the tumor long time after the intratumoral injection of drugs with ROS whichoxidant with the extracellular matrix and interstitial of the tumor to cause degeneration and deformation so that drug of Ara-C sustaining in tumor for a long time, and the tumor cells are also degenerated and necrotic and died, so that high concentrations of cytarabine are embedded between the denatured tumor tissues and cells. The drug slowly released from the inside to the outside to kill tumor cells. IT is further confirmed that the ROS is a sustained release agent intratumorally injection and it can significantly increase the residence time of 99mTc-labeled cytarabine in the tumor, prolong the drug action time of cytarabine, and improve the effect of killing tumor cells.

Dysfunctional Mechanism of Liver Cancer Mediated by Transcription Factor and Non-coding RNA

Background:There have been numerous experiments and studies on liver cancer by biomedical scientists, while no comprehensive and systematic exploration has yet been conducted. Therefore, this study aimed to systematically dissect the transcriptional and non-coding RNAmediated mechanisms of liver cancer dysfunction.Method:At first, we collected 974 liver cancer associated genes from the Online Mendelian Inheritance in Man (OMIM). Afterwards, their interactors were recruited from STRING database so as to identify 18 co-expression modules in liver cancer patient expression profile. Crosstalk analysis showed the interactive relationship between these modules. In addition, core drivers for modules were identified, including 111 transcription factors (STAT3, JUN and NFKB1, etc.) and 1492 ncRNAs (FENDRR and miR-340-5p, etc.).Results:In view of the results of enrichment, we found that these core drivers were significantly involved in Notch signaling, Wnt / β-catenin pathways, cell proliferation, apoptosis-related functions and pathways, suggesting they can affect the development of liver cancer. Furthermore, a global effect on bio-network associated with liver cancer has been integrated from the ncRNA and TF pivot network, module crosstalk network, module-function/pathways network. It involves various development and progression of cancer.Conclusion:Overall, our analysis further suggests that comprehensive network analysis will help us to not only understand in depth the molecular mechanisms, but also reveal the influence of related gene dysfunctional modules on the occurrence and progression of liver cancer. It provides a valuable reference for the design of liver cancer diagnosis and treatment.

DAPK1 as an independent prognostic marker in liver cancer

The death-associated protein kinase 1 (DAPK1) can act as an oncogene or a tumor suppressor gene depending on the cellular context as well as external stimuli. Our study aims to investigate the prognostic significance of DAPK1 in liver cancer in both mRNA and protein levels. The mRNA expression of DAPK1 was extracted from the Gene Expression Omnibus database in three independent liver cancer datasets while protein expression of DAPK1 was detected by immunohistochemistry in our Chinese liver cancer patient cohort. The associations between DAPK1 expression and clinical characteristics were tested. DAPK1 mRNA expression was down-regulated in liver cancer. Low levels of DAPK1 mRNA were associated with shorter survival in a liver cancer patient cohort (n = 115; p = 0.041), while negative staining of DAPK1 protein was significantly correlated with shorter time to progression (p = 0.002) and overall survival (p = 0.02). DAPK1 was an independent prognostic marker for both time to progression and overall survival by multivariate analysis. Liver cancer with the b-catenin mutation has a lower DAPK1 expression, suggesting that DAPK1 may be regulated under the b-catenin pathway. In addition, we also identified genes that are co-regulated with DAPK1. DAPK1 expression was positively correlated with IRF2, IL7R, PCOLCE and ZBTB16, and negatively correlated with SLC16A3 in both liver cancer datasets. Among these genes, PCOLCE and ZBTB16 were significantly down-regulated, while SLC16A3 was significantly upregulated in liver cancer. By using connectivity mapping of these co-regulated genes, we have identified amcinonide and sulpiride as potential small molecules that could potentially reverse DAPK1/PCOLCE/ZBTB16/SLC16A3 expression. Our study demonstrated for the first time that both DAPK1 mRNA and protein expression levels are important prognostic markers in liver cancer, and have identified genes that may contribute to DAPK1-mediated liver carcinogenesis.

Prevalence and Characteristics of Liver Cancer Patients in Immanuel Hospital Bandung within January 2013 until December 2014 Period

Liver cancer is the fifth most common cancer in Indonesia. This research is to find out the prevalence and characteristics of liver cancer patients in Immanuel Hospital Bandung within the January 2013 until December 2014 period based on age, gender, clinical symptoms and predilections. This study was a descriptive verificative research with data retrieval of patients medical records that have been diagnosed with liver cancer that were hospitalized in Immanuel Hospital Bandung within January 2013 until December 2014 period. The study showed that the liver cancer patient prevalence in Immanuel Hospital Bandung within the period of January 2013 until December 2014 was 46 people. Characteristics of liver cancer patients in Immanuel Hospital Bandung within January 2013 until December 2014 period showed that the most liver cancer patients were male, compare with female with ratio 4:1, the most common age group of 56-65 years old, the most common clinical symptoms were abdominal pain with or without reffered pain to the right scapular bone and the most common predilection was right lobe of the liver. Key words: liver cancer, patients' characteristics, prevalence