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imaging biomarkers for predicting poor prognosis of hepatocellular carcinoma: a review

Hepatoma Research 2020年第6期6卷 17-32页

作者： Yun Zhang Zi-Xing Huang Jie Chen Yu-Jun Shi Han-Yu Jiang Li-Kun Cao Bin Song Department of Radiology West China HospitalSichuan UniversityChengdu 610041SichuanChina Laboratory of Pathology Key Laboratory of Transplant Engineering and ImmunologyNHCWest China HospitalSichuan UniversityChengdu 610041SichuanChina Department of Radiology Peking Union Medical College Hospital(Dongdan campus)Beijing 100730China

Hepatocellular carcinoma(HCC)is a primary malignancy of the liver with a high mortality *** is the main biological characteristic of HCC,which manifests through the different biological behaviors of each phenotype and ultimately,affects patient prognosis and treatment *** aggressive biological behaviors are considered to be associated with the poor prognosis of HCC patients including poor differentiation,microvascular invasion,intracellular fat accumulation,invasive growth,bile duct invasion or tumor thrombosis,and tumor spread and metastasis,and have been reported as prognostic *** addition,HCC results from multifactor synergistic damage,and various factors related to genetics,molecular pathology and immunohistochemistry such asβ-catenin,Ki67,cytokeratin-19,and epithelial cell adhesion molecule have an impact on HCC differentiation and *** article is an overview of the biological behaviors that lead to poor prognosis of HCC,and the roles of morphological and quantitative noninvasive imaging biomarkers in the evaluation and prediction of these *** common biomarkers related to genetics,molecular pathology and immunohistochemistry are also briefly *** is hoped that this review will provide clinicians and radiologists with an update on the development of liver imaging,and provide directions for the combination of radiology,genetics,molecular pathology and histopathology to better predict the prognosis of HCC patients.

关键词： Hepatocellular carcinoma poor prognosis biological behaviors imaging biomarkers genetics molecular pathology immunohistochemistry

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Exploring non-invasive diagnostics for metabolic dysfunctionassociated fatty liver disease

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World Journal of Gastroenterology 2024年第28期30卷 3447-3451页

作者： Biao Qu Zheng Li Department of Clinical Pharmacology The Second Hospital of Anhui Medical UniversityHefei 230601Anhui ProvinceChina Jiangsu Engineering Research Center of Cardiovascular Drugs Targeting Endothelial Cells College of Health SciencesSchool of Life SciencesJiangsu Normal UniversityXuzhou 221000Jiangsu ProvinceChina

The population with metabolic dysfunction-associated fatty liver disease(MAFLD)is increasingly common *** of people at risk of progression to advanced stages is necessary to timely offer interventions and appropriate *** biopsy is currently considered the gold standard for the diagnosis and staging of MAFLD,but it has associated risks and *** has spurred the exploration of non-invasive diagnostics for MAFLD,especially for steatohepatitis and *** non-invasive approaches mostly include biomarkers and algorithms derived from anthropometric measurements,serum tests,imaging or stool metagenome ***,they still need rigorous and widespread clinical validation for the diagnostic performance.

关键词： Metabolic dysfunction-associated fatty liver disease Non-invasive diagnostics Circulating biomarkers imaging biomarkers Stool microbial biomarkers

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Brain network markers of abnormal cerebral glucose metabolism and blood flow in Parkinson's disease

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Neuroscience Bulletin 2014年第5期30卷 823-837页

作者： Shichun Peng David Eidelberg Yilong Ma Center for Neurosciences The Feinstein Institute for Medical ResearchNorth Shore-Long Island Jewish Health System

Neuroimaging of cerebral glucose metabolism and blood flow is ideally suited to assay widely-distributed brain circuits as a result of local molecular events and behavioral modulation in the central nervous system. With the progress in novel analytical methodology, this endeavor has succeeded in unraveling the mechanisms underlying a wide spectrum of neurodegenerative diseases. In particular, statistical brain mapping studies have made significant strides in describing the pathophysiology of Parkinson＇s disease （PD） and related disorders by providing signature biomarkers to determine the systemic abnormalities in brain function and evaluate disease progression, therapeutic responses, and clinical correlates in patients. In this article, we review the relevant clinical applications in patients in relation to healthy volunteers with a focus on the generation of unique spatial covariance patterns associated with the motor and cognitive symptoms underlying PD. These characteristic biomarkers can be potentially used not only to improve patient recruitment but also to predict outcomes in clinical trials.

关键词： Parkinson's disease metabolism blood flow PET SPECT movement disorder network analysis imaging biomarkers

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Radiomic analysis based on multi-phase magnetic resonance imaging to predict preoperatively microvascular invasion in hepatocellular carcinoma

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World Journal of Gastroenterology 2022年第24期28卷 2733-2747页

作者： Yue-Ming Li Yue-Min Zhu Lan-Mei Gao Ze-Wen Han Xiao-Jie Chen Chuan Yan Rong-Ping Ye Dai-Rong Cao Department of Radiology The First Affiliated Hospital of Fujian Medical UniversityFuzhou 350005Fujian ProvinceChina Key Laboratory of Radiation Biology(Fujian Medical University) Fujian Province UniversityFuzhou 350005Fujian ProvinceChina

BACKGROUND The prognosis of hepatocellular carcinoma(HCC)remains poor and relapse occurs in more than half of patients within 2 years after *** terms of recent studies,microvascular invasion(MVI)is one of the potential predictors of *** preoperative prediction of MVI is potentially beneficial to the optimization of treatment *** To develop a radiomic analysis model based on pre-operative magnetic resonance imaging(MRI)data to predict MVI in *** A total of 113 patients recruited to this study have been diagnosed as having HCC with histological confirmation,among whom 73 were found to have MVI and 40 were *** the patients received preoperative examination by Gd-enhanced MRI and then curative *** manually delineated the tumor lesion on the largest cross-sectional area of the tumor and the adjacent two images on MRI,namely,the regions of *** analyses included most discriminant factors(MDFs)developed using linear discriminant analysis algorithm and histogram analysis with MaZda *** significant variables of clinical and radiological features and MDFs for the prediction of MVI were estimated and a discriminant model was established by univariate and multivariate logistic regression *** ability of the above-mentioned parameters or model was then evaluated by receiver operating characteristic(ROC)curve ***-fold cross-validation was also applied via R *** The area under the ROC curve(AUC)of the MDF(0.77-0.85)outperformed that of histogram parameters(0.51-0.74).After multivariate analysis,MDF values of the arterial and portal venous phase,and peritumoral hypointensity in the hepatobiliary phase were identified to be independent predictors of MVI(P<0.05).The AUC value of the model was 0.939[95%confidence interval(CI):0.893-0.984,standard error:0.023].The result of internal five-fold cross-validation(AUC:0.912,95%CI:0.841-0.959,standard error:0.029

关键词： Hepatocellular carcinoma Microvascular invasion Magnetic resonance imaging Radiomic analysis imaging biomarkers

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