本文關(guān)鍵詞： 肝硬化 聲脈沖輻射力成像技術(shù) 肝靜脈壓力梯度 無(wú)創(chuàng)診斷　出處：《東南大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：目的：探討通過ARFI測(cè)定的肝脾硬度與HVPG的相關(guān)性及其診斷門靜脈高壓的效能。方法：對(duì)2014年4月至2016年3月在南京鼓樓醫(yī)院消化內(nèi)科接受HVPG測(cè)定的20例肝硬化門脈高壓的患者術(shù)前運(yùn)用ARFI測(cè)量肝臟硬度(Liver Stiffness,LS)及脾臟硬度(Spleen Stiffness,SS).患者術(shù)前同時(shí)行肝功能、血常規(guī)及凝血功能等檢查。分析患者的年齡、ALT、AST、總膽紅素、白蛋白、血小板計(jì)數(shù)、PT、APRI (AST/Plt)、Child評(píng)分、MELD評(píng)分、LS、SS與反映門脈壓力的HVPG之間的相關(guān)性。結(jié)果：20例患者均成功測(cè)得了HVPG數(shù)值及肝、脾硬度。年齡、ALT、AST、血小板計(jì)數(shù)、PT、APRI、 Child評(píng)分、MELD評(píng)分與HVPG無(wú)顯著相關(guān)性。LS及SS與HVPG顯著相關(guān)(P0.05)。將LS及SS設(shè)為自變量,構(gòu)建預(yù)測(cè)HVPG的多元線性回歸模型為：HVPG=-20.871+10.66*LS+5.32*SS。在預(yù)測(cè)HVPG≥12mmHg時(shí),LS及SS的ROC曲線下面積分別為0.875和0.711。LS最佳界值點(diǎn)為1.77m/s(敏感性為68.8%、特異性為100%)。SS最佳界值點(diǎn)為3.18m/s(敏感性為68.8%、特異性75%)。在預(yù)測(cè)HVPG≥20mmHg時(shí),LS及SS的ROC曲線下面積分別為0.798和0.820。LS最佳界值點(diǎn)為1.85m/s(敏感性為100%、特異性為68.7%)。SS最佳界值點(diǎn)為3.23m/s(敏感性為100%、特異性為56.2%)。結(jié)論：肝硬化患者中,ARFI測(cè)得的肝臟及脾臟硬度與HVPG相關(guān),在門靜脈高壓的無(wú)創(chuàng)診斷中具有一定應(yīng)用價(jià)值。
[Abstract]:Objective: to investigate the correlation between liver and spleen hardness determined by ARFI and HVPG and its effectiveness in the diagnosis of portal hypertension. From April 2014 to March 2016, 20 patients with hepatic cirrhosis and portal hypertension who were examined by HVPG in the Department of Gastroenterology, Nanjing Gulou Hospital, were examined for liver hardness by ARFI before operation. Liver Stiffness. LS) and Spleen Stiffnessen SSS. Liver function, blood routine examination and coagulation function were performed simultaneously before operation. The age of the patients was analyzed. Total bilirubin, albumin, platelet count, PTT APRI / AST / Pltn Child score, meld score and LS. Results the values of HVPG, liver and spleen hardness, alt AST, platelet count and PT were measured successfully in 20 patients. There was no significant correlation between meld score and HVPG. LS and SS were significantly correlated with HVPG (P 0.05). LS and SS were regarded as independent variables. The multivariate linear regression model for predicting HVPG was established as: HVPG 鈮，

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