ArticleScientific reports2025
Application of CT in predicting lymph node metastasis in cervical cancer and construction of a preoperative nomogram.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Nomogram for Preoperative Prediction of Adjuvant Therapy Requirement Following Radical Surgery in Stage IB Cervical Squamous Cell Carcinoma With Tumor Size ≤ 4 cm: A Retrospective Study.Cancer medicine · 2026Article
- Preoperative non-invasive prediction of lymph node metastasis in cervical cancer using a multiparametric radiomics model based on transvaginal ultrasound.Abdominal radiology (New York) · 2026Article
- The differences of pelvic lymph node metastasis between squamous cell carcinoma and adenocarcinoma in early-stage cervical cancer patients undergoing radical surgery and adjuvant radiotherapy: a large cohort study.Therapeutic advances in medical oncology · 2026Article
- Predicting preoperative lymph node status in patients with cervical cancer: development of interpretable machine learning model and support for the biological plausibility.Frontiers in immunology · 2025Article
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7 authors.
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Abstract
Cervical cancer significantly affects women's health, while current preoperative imaging methods for predicting lymph node status are suboptimal. This study aims to evaluate the predictive value of CT attenuation (Hounsfield units) for lymph node metastasis (LNM) in cervical cancer patients and to develop a nomogram integrates clinical and imaging features to improve the accuracy of preoperative assessment. A retrospective analysis was conducted on 132 cervical cancer patients treated at the Second Affiliated Hospital of Dalian Medical University from January 2021 to August 2024. The cohort was divided into a training set (70%) and a validation set (30%) for constructing and evaluating the nomogram. CT attenuation was identified as robust predictors of LNM. Multivariate logistic regression showed that preoperative SCC levels, tumor histology, uterine corpus involvement, and lymphovascular space invasion were independent risk factors for LNM. The nomogram incorporating CT attenuation demonstrated excellent discrimination and calibration. This study presents a simple but robust nomogram that integrates clinical and imaging data to predict lymph node status in cervical cancer patients. The model exhibits high accuracy and reliability, highlighting the utility of CT imaging as a non-invasive preoperative tool for assessing LNM.
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