Exploring the correlation of radiomic features of ultrasound images and FNCLCC Grading of soft tissue sarcoma

Chenyang Zhao Yusen Zhang Heng Lv Nan Zhuang Guangyin Yu Yuzhou Shen Licong Dong Wangjie Wu Lu Xie Yun Tian Zhaoling Yi Desheng Sun Xingen Wang ^* Haiqin Xie ^*

• Shenzhen Hospital, Peking University, Shenzhen, China

Background Presurgical evaluation of the histopathological grade of soft tissue sarcoma (STS) is important for enacting treatment strategies. In this study, we plan to investigate the correlation of high-output ultrasound (US) radiomic features and the histopathological grade of STS.Methods Patients with STS were retrospectively enrolled. The radiomic features were extracted from the US images of the STS lesions. And tThe lesions were graded according to the Fédération Nationale des Centres de Lutte Contre le Cancer (FNCLCC) histopathological grading system. The correlation of the radiomic features and the FNCLCC grades was evaluated. And wWe used the features correlated with the histopathological grades to build a model for predicting high-grade STS (Grade II and III).Results A total of 79 patients with STS were enrolled. And 15 radiomic features were found correlated with the FNCLCC grades of STSs, with the correlation coefficient ranging from 0.22 to 0.38. And 8 features showed significant difference among the three grades. The model for predicting high-grade STS based on the 8 radiomic features had an AUC value of 0.80, a sensitivity of 0.73, and a specificity of 0.78.The US radiomic features were correlated with the FNCLCC grade of STS. The radiomic analysis of US imaging could be potentially helpful for identifying the FNCLCC grades of STS pre-surgically.