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Prediction of microvascular invasion in solitary hepatocellular carcinoma≤5 cm based on computed tomography radiomics 被引量:6
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作者 Peng Liu Xian-Zhen Tan +4 位作者 Ting Zhang Qian-Biao Gu xian-hai mao Yan-Chun Li Ya-Qiong He 《World Journal of Gastroenterology》 SCIE CAS 2021年第17期2015-2024,共10页
BACKGROUND Liver cancer is one of the most common malignant tumors,and ranks as the fourth leading cause of cancer death worldwide.Microvascular invasion(MVI)is considered one of the most important factors for recurre... BACKGROUND Liver cancer is one of the most common malignant tumors,and ranks as the fourth leading cause of cancer death worldwide.Microvascular invasion(MVI)is considered one of the most important factors for recurrence and poor prognosis of liver cancer.Thus,accurately identifying MVI before surgery is of great importance in making treatment strategies and predicting the prognosis of patients with hepatocellular carcinoma(HCC).Radiomics as an emerging field,aims to utilize artificial intelligence software to develop methods that may contribute to cancer diagnosis,treatment improvement and evaluation,and better prediction.AIM To investigate the predictive value of computed tomography radiomics for MVI in solitary HCC≤5 cm.METHODS A total of 185 HCC patients,including 122 MVI negative and 63 MVI positive patients,were retrospectively analyzed.All patients were randomly assigned to the training group(n=124)and validation group(n=61).A total of 1351 radiomic features were extracted based on three-dimensional images.The diagnostic performance of the radiomics model was verified in the validation group,and the Delong test was applied to compare the radiomics and MVIrelated imaging features(two-trait predictor of venous invasion and radiogenomic invasion).RESULTS A total of ten radiomics features were finally obtained after screening 1531 features.According to the weighting coefficient that corresponded to the features,the radiomics score(RS)calculation formula was obtained,and the RS score of each patient was calculated.The radiomics model exhibited a better correction and identification ability in the training and validation groups[area under the curve:0.72(95%confidence interval:0.58-0.86)and 0.74(95%confidence interval:0.66-0.83),respectively].Its prediction performance was significantly higher than that of the image features(P<0.05).CONCLUSION Computed tomography radiomics has certain predictive value for MVI in solitary HCC≤5 cm,and the predictive ability is higher than that of image features. 展开更多
关键词 Hepatocellular carcinoma Microvascular invasion Radiomics Image features Computed tomography
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Primary human hepatocyte transplantation in the therapy of hepatic failure:2 cases report 被引量:3
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作者 Zhuo-Ri Li xian-hai mao +5 位作者 Xiao-Xuan Hu Sheng-Dan Nie Yong-Zhong Shi Hua Xiang Jian-Hui Yang Ou-De Cao 《Asian Pacific Journal of Tropical Medicine》 SCIE CAS 2012年第2期165-168,共4页
Liver failure is the end stage of hepatopathy with unfavorable prognosis.In two patients with liver failure,viable primary human hepatocytes,obtained from resected liver tissue of patients with hepatolithiasis.were tr... Liver failure is the end stage of hepatopathy with unfavorable prognosis.In two patients with liver failure,viable primary human hepatocytes,obtained from resected liver tissue of patients with hepatolithiasis.were transplanted into the spleen by interventional therapy through femoral arterial cannula.After transplantation,the patients’ clinical symptoms and liver function were significantly improved.However,their bilirubin increased within six days following transplantation.One suffered from hepatic coma and give up treatment and the other patient died forteen days after transplantation.It is technically safe to treat liver failure by intrasplenic transplantation of adult hepatocytes and the clinical efficacy has been confirmed.How to make transplanted hepatic cells proliferate and functionally survive is the key point to maintain continuous improvement of the recipient’s hepatic function. 展开更多
关键词 Cell TRANSPLANTATION HEPATOCYTE LIVER FAILURE
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