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<p>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.</p>

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Application of CT in predicting lymph node metastasis in cervical cancer and construction of a preoperative nomogram

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月5日

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  • Xiao Meng,
  • Siyu Song,
  • Ke Li,
  • Yajie Duan,
  • Jiayuan Zhong,
  • Jiawei Wang,
  • Shichao Han

摘要

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.