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• Clinical Article •
Prediction of lymph node metastasis in cervical cancer using virtual magnetic resonance elastography
ZHANG Yuejie  YANG Zihan  DONG Linxiao  LIU Jinjin  CHEN Jiejie  JIANG Wenliang  FAN Rongke  WU Qingxia  WU Qingxia  WANG Meiyun 

DOI:10.12015/issn.1674-8034.2026.01.011.


[Abstract] Objective To evaluate the predictive efficacy of virtual magnetic resonance elastography (vMRE) based on diffusion-weighted imaging (DWI) for lymph node metastasis (LNM) in cervical cancer patients undergoing direct surgery.Materials and Methods Clinical and imaging data of cervical cancer patients who underwent preoperative pelvic MRI and radical hysterectomy at Henan Provincial People's Hospital between November 2021 and November 2022 were retrospectively collected and analyzed. The pelvic MRI protocol included multi-b-value DWI, and vMRE images were generated from DWI data to extract the (μDiff) parameter. Based on postoperative pathology, patients were divided into LNM-positive and LNM-negative groups. The t-test or Mann-Whitney U test was used to compare differences in DWI-based virtual shear modulus μDiff parameters between groups, and logistic regression analysis was performed to identify variables associated with lymph node status. Predictive models were constructed, and receiver operating characteristic (ROC) curves were plotted. The area under the curve (AUC) was used to evaluate the predictive performance of each model.Results Among clinical variables, squamous cell carcinoma antigen (SCCAG) and maximum lymph node short-axis diameter were significantly associated with LNM. The mean, maximum, and median μDiff values in the LNM-positive group were significantly higher than those in the negative group (P < 0.05). The combined model incorporating the maximum μDiff value and maximum lymph node short-axis diameter demonstrated the best predictive performance for LNM, with an AUC of 0.824 (95% CI: 0.683 to 0.965), superior to the single model constructed solely based on the mean μDiff value and the short-axis diameter of the largest lymph node.Conclusions vMRE image features based on multi-b-value DWI can serve as a noninvasive indicator reflecting tissue stiffness, improving the predictive accuracy of LNM in cervical cancer patients. This approach provides a novel imaging biomarker for the preoperative noninvasive assessment of LNM.
[Keywords] cervical cancer；lymph node metastasis；magnetic resonance imaging；virtual magnetic resonance elastography；diffusion-weighted imaging

ZHANG Yuejie1   YANG Zihan2   DONG Linxiao1   LIU Jinjin2   CHEN Jiejie2   JIANG Wenliang1   FAN Rongke1   WU Qingxia3   WU Qingxia1, 2*   WANG Meiyun1, 2, 4  

1 Department of Medical Imaging, People's Hospital of Henan University (Henan Provincial People's Hospital), Zhengzhou 450003, China

2 Department of Medical Imaging, People's Hospital of Zhengzhou University (Henan Provincial People's Hospital), Zhengzhou 450003, China

3 United Imaging Intelligence Medical Technology (Beijing) Co., Ltd., Beijing 100089, China

4 Henan Academy of Science, Zhengzhou 450008, China

Corresponding author: WU Q X, E-mail: qxwu@zzu.edu.cn

Conflicts of interest   None.

Received  2025-08-26
Accepted  2025-12-29
DOI: 10.12015/issn.1674-8034.2026.01.011
DOI:10.12015/issn.1674-8034.2026.01.011.

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