基于瞬时弹性成像技术检测参数的非酒精性脂肪性肝病进展评估模型的建立

姚明解; 文夏杰; 王雷婕; 何琼; 罗建文; 范建高; 谢青; 陈成伟; 傅青春; 施军平; 杨永峰; 徐芸; 陆伦根; 鲁凤民

doi:10.3969/j.issn.1001-5256.2021.07.027

基于瞬时弹性成像技术检测参数的非酒精性脂肪性肝病进展评估模型的建立

DOI: 10.3969/j.issn.1001-5256.2021.07.027

姚明解^1a,
文夏杰^1b,
王雷婕^1b,
何琼²,
罗建文²,
范建高³,
谢青⁴,
陈成伟⁵,
傅青春⁵,
施军平⁶,
杨永峰⁷,
徐芸⁸,
陆伦根^9, ,,
鲁凤民^1b, ,

1a.
北京大学基础医学院人体解剖学与组织胚胎学系，北京 100191
1b.
北京大学基础医学院病原生物学系暨感染病研究中心，北京 100191
2.
清华大学医学院生物医学工程系，北京 100084
3.
上海交通大学医学院附属新华医院消化内科，上海 200092
4.
上海交通大学医学院附属瑞金医院感染科，上海 200025
5.
中国人民解放军第九〇五医院肝病中心，上海 200052
6.
杭州师范大学附属医院肝病科，杭州 310014
7.
南京市第二医院肝病科，南京 210003
8.
郑州大学第一附属医院消化内科，郑州 450052
9.
上海交通大学附属第一人民医院消化科，上海 200080

基金项目:

国家自然科学基金青年项目 (81902115);

国家重点研发计划项目 (SQ2020YFF0426358);

国家十三五“艾滋病和病毒性肝炎等重大传染病防治”科技重大专项基金 (2017ZX10302201);

国家十三五“艾滋病和病毒性肝炎等重大传染病防治”科技重大专项基金 (2017ZX10202203);

中国博士后科学基金 (2017M620802);

北京市科学技术委员会资助项目 (Z161100000116047)

利益冲突声明：本研究不存在研究者、伦理委员会成员、受试者监护人以及与公开研究成果有关的利益冲突。

作者贡献声明：鲁凤民、陆伦根、姚明解负责课题设计，拟定写作思路，指导撰写文章；姚明解、文夏杰、王雷婕负责收集数据，资料分析与撰写论文；何琼、罗建文负责超声参数解析及技术指导；范建高、谢青、陈成伟、傅青春、施军平、杨永峰、徐芸负责提供临床数据并指导分析；鲁凤民、姚明解负责修改论文并最后定稿。

详细信息

通信作者:
陆伦根，lungenlu1965@163.com

鲁凤民，lu.fengmin@bjmu.edu.cn

中图分类号: R575.5
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出版历程
- 收稿日期: 2020-11-20
- 录用日期: 2021-01-11
- 出版日期: 2021-07-20

Establishment of a model for evaluating the severity of nonalcoholic fatty liver disease based on transient elastography parameters

1a.
Department of Anatomy and Embryology, School of Basic Medical Sciences, Peking University, Beijing 100191, China
1b.
Department of Microbiology and Infectious Disease Center, School of Basic Medical Sciences, Peking University, Beijing 100191, China
2.
Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
3.
Department of Gastroenterology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China
4.
Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
5.
Liver Center, The 905th Hospital of the Chinese People's Liberation Army Nary, Shanghai 200052, China
6.
Department of Hepatology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 310014, China
7.
Department of Hepatology, The Second Hospital of Nanjing, Nanjing 210003, China
8.
Department of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
9.
Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China

Research funding:

National Natural Science Foundation of China Grant (81902115);

National Key Research and Development Program of China (SQ2020YFF0426358);

National Science and Technology Major Project for Infectious Diseases (2017ZX10302201);

National Science and Technology Major Project for Infectious Diseases (2017ZX10202203);

China Postdoctoral Science Foundation (2017M620802);

Beijing Municipal Science & Technology Commission (Z161100000116047)

摘要

摘要: 目的通过对基于瞬时弹性成像技术检测参数联合分析，建立对非酒精性脂肪性肝病(NAFLD)病情严重程度的评估模型。方法回顾性收集2014年7月—2017年7月在我国7家医院就诊的具有肝穿刺病理学诊断的184例NAFLD患者的临床信息及肝弹性相关参数。将iLivTouch肝弹性检测参数得到的和弹性、超声信号的幅度、频率、散射及衰减程度相关的多参数分别命名为P1~P18。通过Spearman相关性检验、线性回归分析分别建立用于NAFLD患者脂肪变程度、炎症活动度、肝纤维化程度判断模型，使用受试者工作特征曲线(ROC曲线)对模型诊断价值进行评价。结果基于瞬时弹性成像技术的相关超声参数与NAFLD患者肝脂肪变、炎症活动度与肝纤维化程度有良好的相关性。多因素分析结果显示，P1、P12是肝脂肪变程度的独立相关指标(P值均＜0.05)，P1、P3、P6、P11是肝脏炎症活动度的独立相关指标(P值均＜0.05)，P2、P3与肝纤维化程度显著相关(P值均＜0.05)。通过线性回归建立的肝脂肪变程度判断模型：Y=0.013×P1+0.055×P12-0.318 5，对轻度及中重度脂肪变诊断的ROC曲线下面积(AUC)分别为0.895(95%CI：0.842~0.936)、0.939(95%CI：0.894~0.969)，敏感度分别为82.35%、86.26%，特异度分别为89.23%、93.27%，P值均＜0.001；肝脏炎症活动度诊断模型：Y=0.008×P1+0.030×P3+0.029×P6-1.875×10^-4×P11+0.416，对早期炎症及显著炎症活动诊断的AUC分别为0.828(95%CI：0.793~0.865)、0.874(95%CI：0.817~0.918)，敏感度分别为70.6%、73.96%，特异度分别为85.7%、93.33%，P值均＜0.001；肝纤维化程度诊断模型：Y=-0.003×P1+0.601×(lnP2)+0.285×(lnP3)+0.036×P15+0.078，对显著纤维化、严重纤维化及早期肝硬化诊断的AUC分别为0.805(95%CI：0.740~0.869)、0.767(95%CI：0.699~0.827)、0.803(95%CI：0.701~0.906)，敏感度分别为72.27%、77.63%和90.00%，特异度分别为79.69%、66.42%和66.47%，P值均＜0.001。结论瞬时弹性成像技术检测不同参数能够分别有效反映NAFLD患者脂肪变程度、炎症活动度及纤维化程度，通过联合模型能够提高对NAFLD患者疾病严重程度判断的准确性。
- 非酒精性脂肪性肝病 /
- 弹性成像技术 /
- 模型，统计学
Abstract: Objective To establish a model for evaluating the severity of nonalcoholic fatty liver disease (NAFLD) based on a combined analysis of transient elastography parameters. Methods A retrospective analysis was performed for the clinical information and liver elasticity parameters of 184 NAFLD patients who attended 7 hospitals in China from July 2014 to July 2017 and underwent liver biopsy for pathological diagnosis. Liver elasticity parameters were named as P1-P18 according to the amplitude, frequency, dispersion, and attenuation of ultrasound signals. The Spearman rank correlation test and the linear regression analysis were used to establish the models for evaluating steatosis degree, inflammatory activity, and fibrosis degree, and the receiver operating characteristic (ROC) curve was used to evaluate the value of each diagnostic model. Results The ultrasound parameters based on transient elastography were well correlated with steatosis degree, inflammatory activity, and liver fibrosis degree in NAFLD patients. The multivariate analysis showed that P1 and P12 were independent indicators for predicting steatosis degree; P1, P3, P6, and P11 were independent indicators for predicting inflammatory activity; P2 and P3 were significantly correlated with liver fibrosis degree. The model Y=0.013×P1+0.055×P12-0.318 5 for predicting steatosis degree established based on linear regression had an area under the ROC curve (AUC) of 0.895 (95% confidence interval [CI]: 0.842-0.936) and 0.939 (95%CI: 0.894-0.969), respectively, in the diagnosis of mild steatosis and moderate-to-severe steatosis, with a sensitivity of 82.35% and 86.26%, respectively, and a specificity of 89.23% and 93.27%, respectively (P < 0.001). The model Y=0.008×P1+0.030×P3+0.029×P6-1.875×10^-4×P11+0.416 for predicting inflammatory activity had an AUC of 0.828 (95%CI: 0.793-0.865) and 0.874 (95%CI: 0.817-0.918), respectively, in the diagnosis of early-stage inflammation and significant inflammation, with a sensitivity of 70.6% and 73.96%, respectively, and a specificity of 85.7% and 93.33%, respectively (P < 0.001). The model Y=-0.003×P1 + 0.601×(lnP2)+0.285×(lnP3)+0.036×P15 + 0.078 for predicting liver fibrosis degree had an AUC of 0.805 (95%CI: 0.740-0.869), 0.767 (95%CI: 0.699-0.827), and 0.803 (95%CI: 0.701-0.906), respectively, in the diagnosis of significant fibrosis, severe fibrosis, and early liver cirrhosis, with a sensitivity of 72.27%, 77.63%, and 90.00%, respectively, and a specificity of 79.69%, 66.42%, and 66.47%, respectively (P < 0.001). Conclusion Different parameters of transient elastography can effectively reflect steatosis degree, inflammatory activity, and fibrosis degree in NAFLD patients, and a combined model can improve the accuracy of disease severity prediction in NAFLD patients.
- Non-alcoholic Fatty Liver Disease /
- Elasticity Imaging Techniques /
- Models, Statistical

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表 1 研究对象的一般情况

指标	数值
男/女(例)	114/70
年龄(岁)	40 (26~51)
ALT(U/L)	53(29~97)
AST(U/L)	41(26~60)
GGT(U/L)	54(31~98)
脂肪变评分(0/1/2/3，例)	65/39/48/32
气球样变评分(0/1/2，例)	22/47/115
小叶炎症评分(0/1/2，例)	16/70/98
纤维化评分(0/1/2/3/4，例)¹⁾	25/38/43/65/10
注：1)纤维化评分有3例研究对象缺失，在后期有关纤维化模型构建中未纳入研究。

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表 2 超声参数与NAFLD人群脂肪变程度、炎症活动度及肝纤维化程度相关性分析

变量	脂肪变程度		炎症活动度		肝纤维化程度
变量	r值	P值	r值	P值	r值	P值
P1	0.748	＜0.001	0.154	0.037	-0.068	0.358
P2	-0.014	0.849	0.161	0.029	0.510	＜0.001
P3	0.003	0.969	0.241	0.001	0.476	＜0.001
P4	0.578	＜0.001	0.078	0.293	-0.008	0.918
P5	0.334	＜0.001	0.186	0.011	0.100	0.177
P6	0.469	＜0.001	0.271	＜0.001	0.123	0.097
P7	0.653	＜0.001	0.065	0.382	-0.047	0.527
P8=P10	0.680	＜0.001	0.111	0.133	0.101	0.174
P9	0.649	＜0.001	0.091	0.221	-0.032	0.665
P11	0.714	＜0.001	0.1331	0.071	0.075	0.312
P12	0.677	＜0.001	0.116	0.118	0.107	0.105
P14	0.513	＜0.001	0.094	0.203	-0.012	0.871
P15=P17	0.521	＜0.001	0.117	0.115	0.113	0.128
P16	0.669	＜0.001	0.103	0.162	-0.029	0.700
P18	0.694	＜0.001	0.085	0.250	-0.012	0.868

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表 3 线性回归判定对于NAFLD人群脂肪变程度具有预测价值的参数

参数	B值	SE	t值	P值
常量	-3.185	0.293	-11.455	＜0.001
P1	0.013	0.001	8.670	＜0.001
P12	0.055	0.013	0.277	＜0.001

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表 4 线性回归判定对于NAFLD人群肝脏炎症活动度具有预测价值的参数

参数	B值	SE	t值	P值
常量	0.416	0.590	0.705	0.482
P1	0.008	0.003	3.036	0.003
P3	0.030	0.009	3.442	0.001
P6	0.029	0.015	1.930	0.055
P11	-1.875×10^-4	＜0.001	-2.455	0.015

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表 5 线性回归判定对于NAFLD人群纤维化程度具有预测价值的参数

参数	B值	SE	t值	P值
常量	0.078	0.477	0.164	0.870
P1	-0.003	0.002	-1.962	0.051
lnP2	0.601	0.237	2.534	0.012
lnP3	0.285	0.189	1.506	0.134
P15	0.036	0.015	2.438	0.016

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参考文献(14)

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