Related Experiment Video
Updated: May 26, 2026
Clinical Imaging of Microwave Mammography
Published on: November 14, 2025
MRI-Based Habitat Radiomics for Differentiating Early-Stage Endometrial Carcinoma from Submucous Leiomyoma: A
Hao Tian1, Anqi Yan2, Lei Cao3
1Department of Radiology, Affiliated Hospital of Nantong University, Nantong, China.
Objective:
This study aimed to investigate the utility of magnetic resonance imaging (MRI)-based habitat radiomics for preoperatively distinguishing early-stage endometrial carcinoma (EC) from submucous leiomyoma (SML).
Materials And Methods:
A retrospective study was conducted on uterine lesions patients who underwent MRI from three hospitals. The k-means clustering algorithm was applied to segment the MRI into distinct habitats based on T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and apparent diffusion coefficient (ADC) maps. Radiomic features were extracted from whole-tumor and these habitats and selected by the Pearson correlation coefficient and least absolute shrinkage and selection operator (LASSO) regression. A logistic regression (LR) model was constructed by these radiomics in the training set.
Results:
A total of 231 eligible patients were incorporated, 97 EC and 134 SML confirmed by histopathology. In the training cohort, the AUCs of the models based on features from the whole-tumor, habitat_1, habitat_2, and habitat_3 were 0.826, 0.787, 0.770, and 0.907, respectively, while in the test and external validation cohorts, the corresponding AUCs were 0.774/0.751, 0.486/0.608, 0.663/0.514, and 0.858/0.881. Compared with whole-tumor model, habitat_3 model demonstrated incrementally improved predictive performance in the external validation cohort (0.881 [95% CI: 0.799-0.934]).
Conclusion:
MRI-based habitat radiomics offers incremental improvement for preoperative differentiation between early-stage EC and SML.
