A Prospective Validation Study of Radiomics in the Differential Diagnosis of Uterine Leiomyoma and Uterine Sarcoma

In our previous study, based on the multi-center clinical big data collected from January 2012 to January 2025, we have completed the construction of a multimodal early warning model for the malignant transformation of uterine fibroids. The model was mainly based on T2WI and DWI sequences, and was trained and optimized by support vector machine (SVM) algorithm. In the retrospective study and internal validation, the model shows high sensitivity and specificity, which preliminarily proves that it has good application potential in identifying high-risk groups and predicting the risk of malignant transformation of uterine fibroids. However, there are still some limitations in retrospective studies and internal validation results, and its application value, universality and stability in real clinical environment have not been fully verified. Therefore, we plan to conduct a prospective validation study in consecutive patients enrolled after January 2025 to evaluate the clinical performance and generalization of the model in predicting the malignant tendency or risk of malignant transformation of uterine fibroids through practical application in the real population, and further analyze the operability in the actual diagnosis and treatment process and the potential value for patient management. This study will provide reliable evidence for early screening, follow-up management and individualized treatment of high-risk population, and has important clinical and public health significance for improving the early diagnosis rate, reducing the risk of malignant transformation and improving the prognosis of patients with uterine fibroids.