Shear wave elastography-based ultrasomics: differentiating malignant from benign focal liver lesions.
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 tota...
| Publicado en: | Abdominal Radiology Vol. 46; no. 1; pp. 237 - 249 |
|---|---|
| Autores principales: | , , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
2021
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=148520007&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 148520007 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 2366004X JT14 jtl: Abdominal Radiology issn: 2366004X maglogo: N pubinfo: dt: 2021 vid: 46 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 148520007 144442522 10.1007/s00261-020-02614-3 148520007 ppf: 237 ppct: 12 formats: fmt: @attributes: type: P tig: atl: Shear wave elastography-based ultrasomics: differentiating malignant from benign focal liver lesions. aug: au: Wang, Wei Zhang, Jian-Chao Tian, Wen-Shuo Chen, Li-Da Zheng, Qiao Hu, Hang-Tong Wu, Shan-Shan Guo, Yu Xie, Xiao-Yan Lu, Ming-De Kuang, Ming Liu, Long-Zhong Ruan, Si-Min affil: Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhongshan Road 2, 510080, Guangzhou, People's Republic of China sug: ab: 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 (Emax, Emin, Emean, and ESD). 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, Emax, Emean, Emin and ESD 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|