Objective：To investigate the correlation between MRI phenotypes and various clinical and histopathological characteristics in patients with early - stage cervical cancer（CC）. Methods：The MRI radiomics features，along with clinical and histopathological characteristics of 164 patients with CC were collected retrospectively from July 2019 to December 2023. Tumors and pelvic lymph nodes of all patients were divided into two clusters using raidomics-based consensus clustering. Differences in clinical and histopathological characteristics between the two groups were compared. Results：Tumor - based clustering analysis showed no significant differences between the two groups in terms of average age，histological type，tumor differentiation，lymphovascular space invasion，or parametrial invasion. Clustering analysis based on tumors showed that compared with the cluster 1，patients in the cluster 2 had a more advanced postoperative International Federation of Gynecology and Obstetrics（FIGO）stage[ⅡA and above：22/72（30.6%） vs. 56/92（60.9%），P=0.001]，a higher probability of lymph node metastasis[9/72（12.5%）vs. 30/92（32.6%），P=0.002]，larger tumor size[short diameter：（16.67 ± 6.32）mm vs.（28.38 ± 9.73）mm，long diameter：（21.02 ± 7.39）mm vs.（34.34 ± 9.72）mm，height：（18.93 ± 8.01）mm vs.（29.92 ± 10.61）mm，all P ＜ 0.001]，and deeper stromal invasion[＞2/3：26/72（36.1%）vs. 62/92（67.4%），P ＜ 0.001]. Clustering analysis based on lymph nodes showed that no significant differences between the two clusters in short axis，long axis，short - to - long axis ratio，signal，border，or lymph node metastasis. Conclusion：Associations between radiomics features and clinical and histopathological characteristics of patients with CC could be identified by consensus clustering based on multiparametric MRI-based radiomics，suggesting possibilities for preoperative risk stratification.