Shear wave elastography-based ultrasomics: differentiating malignant from benign focal liver lesions

被引:11
|
作者
Wang, Wei [1 ]
Zhang, Jian-Chao [1 ]
Tian, Wen-Shuo [1 ]
Chen, Li-Da [1 ]
Zheng, Qiao [2 ]
Hu, Hang-Tong [1 ]
Wu, Shan-Shan [1 ]
Guo, Yu [3 ]
Xie, Xiao-Yan [1 ]
Lu, Ming-De [1 ,4 ]
Kuang, Ming [1 ,4 ]
Liu, Long-Zhong [5 ]
Ruan, Si-Min [1 ]
机构
[1] Sun Yat Sen Univ, Ultras Artificial Intelligence X Lab, Inst Diagnost & Intervent Ultrasound, Dept Med Ultrason,Affiliated Hosp 1, 58 Zhongshan Rd 2, Guangzhou 510080, Peoples R China
[2] Sun Yat Sen Univ, Affiliated Hosp 1, Fetal Med Ctr, Dept Med Ultrason, Guangzhou, Peoples R China
[3] Sun Yat Sen Univ, Affiliated Hosp 1, Dept Gen Surg, Guangzhou, Peoples R China
[4] Sun Yat Sen Univ, Affiliated Hosp 1, Dept Hepatobiliary Surg, Guangzhou, Peoples R China
[5] Sun Yat Sen Univ, Canc Ctr, State Key Lab Oncol South China, Dept Ultrasound, 651 Dongfeng Dong Rd, Guangzhou 510060, Peoples R China
关键词
Ultrasonography; Machine learning; Elasticity imaging techniques; Liver; CONTRAST-ENHANCED ULTRASOUND; HEPATOCELLULAR-CARCINOMA; RADIOMICS; RECOMMENDATIONS; GUIDELINES; ACCURACY; FIBROSIS; MODEL;
D O I
10.1007/s00261-020-02614-3
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose Ultrasomics is a radiomics technique that extracts high-throughput quantitative data from ultrasound imaging. The aim of this study was to differentiate malignant from benign focal liver lesions (FLLs) using two-dimensional shear wave elastography (2D-SWE)-based ultrasomics. Methods A total of 175 FLLs in 169 patients were prospectively analyzed. The study population was divided into a training cohort (n = 122) and a validation cohort (n = 53). The maxima, minima, mean, and standard deviation of 2D-SWE measurements were expressed in kilopascals (E-max,E-min,E-mean, andE(SD)). The ultrasonics technique was used to extract the features from the 2D-SWE images. Support vector machine was used to establish two prediction models: the ultrasomics score (ultrasomics features only) and the combined score (SWE measurements and ultrasomics features). The diagnostic performance of the models in differentiating FLLs was analyzed. Results A total of 1044 features were extracted and 15 features were selected. The AUC for the combined score, ultrasomics score,E-max,E-mean,E(min)andE(SD)were 0.94, 0.91, 0.92, 0.89, 0.67, and 0.89, respectively. The combined score had the best diagnostic performance. The sensitivity, specificity, PPV, NPV, +LR, LR of the combined score were 92.59%, 87.50%, 94.59%, 82.50%, 7.35%, and 0.09%, respectively. The decision curve analysis results showed that when the threshold probability was > 29%, the combined score showed improved benefits for patients compared to using the ultrasomics score and 2D-SWE measurements. Conclusion The results of this study demonstrated that the combined score had good diagnostic accuracy in differentiating malignant from benign FLLs.
引用
收藏
页码:237 / 248
页数:12
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