Endometrial carcinoma (EC) risk stratification is important to guide individualized treatment and prognostic assessment. Accurate preoperative risk stratification can help optimize surgical plans and adjuvant treatment strategies. Conventional imaging plays an important role in risk assessment, including tumor size, myometrial infiltration depth, cervical stromal invasion, lymph node metastatic status, dynamic enhancement pattern, and signal characteristics of diffusion-weighted imaging. By extracting high-throughput features from medical images and combining them with artificial intelligence algorithms, radiomics is able to assess tumor heterogeneity in a more comprehensive way, providing a new method for noninvasive risk stratification. This article describes the research results of traditional imaging and imaging histology in EC risk stratification, discussing the technical advantages, challenges, and future development directions.
Ouyang et al. (Wed,) studied this question.
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