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

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

JOURNAL=Frontiers in Imaging

VOLUME=Volume 4 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/imaging/articles/10.3389/fimag.2025.1436275

DOI=10.3389/fimag.2025.1436275

ISSN=2813-3315

ABSTRACT=BackgroundPresurgical 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.MethodsPatients with STS were retrospectively enrolled. The radiomic features were extracted from the US images of the STS lesions. The lesions were graded according to the Fédération Nationale des Centers de Lutte Contre le Cancer (FNCLCC) histopathological grading system. The correlation of the radiomic features and the FNCLCC grades was evaluated. We used the features correlated with the histopathological grades to build a model for predicting high-grade STS (Grade II and III).ResultsA 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.ConclusionThe 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.