Wei Wang1, Jian-Chao Zhang1, Wen-Shuo Tian1, Li-Da Chen1, Qiao Zheng2, Hang-Tong Hu1, Shan-Shan Wu1, Yu Guo3, Xiao-Yan Xie1, Ming-De Lu1,4, Ming Kuang1,4, Long-Zhong Liu5, Si-Min Ruan6. 1. 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, Guangzhou, 510080, People's Republic of China. 2. Department of Medical Ultrasonics, Fetal Medical Center, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People's Republic of China. 3. Department of General Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People's Republic of China. 4. Department of Hepatobiliary Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People's Republic of China. 5. Department of Ultrasound, State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, No. 651 Dongfeng Dong Road, Guangzhou, 510060, People's Republic of China. liulzh@sysucc.org.cn. 6. 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, Guangzhou, 510080, People's Republic of China. ruansm@mail2.sysu.edu.cn.
Abstract
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.
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.