基于CT影像组学特征评估肝硬化患者肝脏储备功能

张喆; 李民; 赵丽琴; 刘长春; 黄旭方; 曹邱婷; 王麟; 贾继东

doi:10.15953/j.ctta.2021.019

基于CT影像组学特征评估肝硬化患者肝脏储备功能

张喆^{1a, 2a,},
李民^{1a, 2a},
赵丽琴^{1a, 2a, ,},
刘长春³,
黄旭方^1a,
曹邱婷^2a,
王麟^1b,
贾继东^2b

1.
放射科首都医科大学附属北京天坛医院
2.
消化内科，北京100070 首都医科大学附属北京天坛医院
1.
放射科首都医科大学附属北京友谊医院
2.
肝病研究中心, 北京100050 首都医科大学附属北京友谊医院
3.
解放军总医院第五医学中心放射科, 北京100039

基金项目: 北京市自然科学基金（基于能谱CT的肝硬化食管静脉曲张出血无创性预警的智能诊断系统研究（7192042））。

详细信息

作者简介:
张喆: 男，首都医科大学影像医学与核医学硕士研究生在读，主要从事CT影像组学研究，E-mail：baichengzhangzhe@126.com

赵丽琴: 女，首都医科大学附属北京天坛医院放射科主任医师、教授、博士研究生导师，擅长胸腹部疾病影像诊断，E-mail：zhaolq0129@163.com

中图分类号: R 814
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出版历程
- 收稿日期: 2020-10-30
- 录用日期: 2021-12-03
- 网络出版日期: 2021-12-09
- 刊出日期: 2022-01-31

Evaluation on the Hepatic Functional Reserve of Cirrhotic Patients based on CT Radiomics Characteristics

ZHANG Zhe^{1a, 2a,},
LI Min^{1a, 2a},
ZHAO Liqin^{1a, 2a, ,},
LIU Changchun³,
HUANG Xufang^1a,
CAO Qiuting^2a,
WANG Lin^1b,
JIA Jidong^2b

1.
Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China Department of Radiology
2.
Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China Department of Gastroenterology
1.
Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China Department of Radiology
2.
Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China Liver Research Center
3.
Department of Radiology, 5th Medical Center of PLA General Hospital, Beijing 100039, China

摘要

摘要:
目的：探讨应用CT影像组学特征评估肝硬化患者肝脏储备功能的价值。方法：回顾性收集经临床确诊的肝硬化患者121例。根据Child-Pugh分级标准分为A、B和C三个等级，其中A级51例（A组）；B和C级共70例（B组）。所有患者均采用GE Discovery CT 750 HD行平扫加增强扫描。选择增强扫描门静脉期图像，由两名放射科医生应用Shukun Radiomics V94软件在门静脉左支层面对整个肝脏进行勾画；使用组内相关系数对两名医生勾画的结果进行一致性检验。将所有患者按照7∶3的比例随机分为训练集与验证集后，对整个肝脏进行影像组学特征提取，经过降维后筛选出影像组学特征，使用逻辑回归方法建立肝硬化患者的肝脏储备功能模型。应用ROC曲线下面积（AUC）评价模型的性能。结果：两名医生对图像分割的一致性检验结果良好，ICC均大于0.75。最终用17个影像组学特征建立了评估肝硬化患者肝脏储备功能的模型，训练集的AUC为0.84，准确性为0.78，敏感性为0.79，特异性为0.77；验证集的AUC为0.77，准确性为0.71，敏感性为0.76，特异性为0.65。结论：应用CT影像组学特征，能够评估肝硬化患者的肝脏储备功能。
- 影像组学特征 /
- 计算机断层扫描 /
- 肝硬化
Abstract:
Objective: To explore the value of CT radiomics characteristics in evaluating hepatic functional reserve of patients with liver cirrhosis. Methods: A total of 121 patients with clinically confirmed liver cirrhosis were retrospectively collected, who were graded as A, B and C according to Child-Pugh standard. 51 cases were grade A (group A) and 70 cases were grade B and C (group B). All patients underwent non-contrast and contrast enhanced CT scan using GE Discovery CT 750 HD scanner. Enhanced CT images of portal venous phase were selected, and the whole liver was delineated at the level of the left portal vein by 2 radiologists using Shukun Radiomics V94 software. Intraclass correlation coefficient (ICC) was applied to test the inter-group consistency of the results obtained by the 2 radiologists. All patients were randomly divided into the training set and the validation set at a ratio of 7∶3, and the whole liver was performed extraction process for radiomics characteristics. After dimensionality reduction, radiomics characteristics were acquired and the model was established by Logistic Regression (LR). Area Under ROC Curve (AUC) was used to evaluate the performance of the model. Results: The consistency test results of image delineation by two radiologists turned out well and the ICC were greater than 0.75. Finally, 17 radiomics characteristics were used to establish the evaluation model for hepatic functional reserve of patients with liver cirrhosis. The AUC of the training set was 0.84 while the accuracy, sensitivity and specificity was 0.78, 0.79, and 0.77, respectively. The AUC of the validation set was 0.77 while the accuracy, sensitivity and specificity was 0.71, 0.76, and 0.65, respectively. Conclusion: CT radiomics characteristics could be used to evaluate the hepatic functional reserve of patients with liver cirrhosis.
- radiomics characteristics /
- computed tomography /
- liver cirrhosis

HTML全文

图 1 入组患者肝硬化病因

Figure 1. Pathogeny of patients with liver cirrhosis

下载: 全尺寸图片幻灯片

图 2 图像分割

Figure 2. Image segmentation of liverparenchyma

下载: 全尺寸图片幻灯片

图 3 肝硬化患者CT门静脉期图像影像组学特征的筛选

Figure 3. Radiomics characteristics selection of portal venous phase CT image

下载: 全尺寸图片幻灯片

图 4 训练集与验证集ROC曲线

Figure 4. ROC curve of training and testing set

下载: 全尺寸图片幻灯片

表 1 训练集与验证集ROC-AUC值比较

Table 1 Comparison of ROC-AUC values between training set and validation set

组别	AUC	准确性	敏感性	特异性
训练集	0.839	0.784	0.793	0.773
验证集	0.765	0.712	0.759	0.652

下载: 导出CSV

1 训练集与验证集ROC-AUC值比较

组别	AUC	准确性	敏感性	特异性
训练集	0.839	0.784	0.793	0.773
验证集	0.765	0.712	0.759	0.652

下载: 导出CSV

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