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Updated: Sep 13, 2025

Robot-assisted Total Mesorectal Excision and Lateral Pelvic Lymph Node Dissection for Locally Advanced Middle-low Rectal Cancer
Published on: February 12, 2022
Preoperative MRI Assessment of Mesorectal Lymph Node Metastasis in Patients with Rectal Cancer: A Retrospective Study
Fumi Shigehara1, Hirotoshi Kobayashi1, Ayaka Koizumi1
1Teikyo University Hospital, Mizonokuchi, Japan.
Objectives:
This study aimed to determine the optimal cutoff values for predicting mesorectal lymph node metastasis in rectal cancer using preoperative magnetic resonance imaging (MRI) parameters.
Methods:
We retrospectively analyzed 67 patients with rectal cancer who underwent resection and preoperative pelvic MRI at our institution between April 2015 and December 2023. The MRI-based long- and short-axis diameters of mesorectal lymph nodes were compared with pathological findings to assess their correlation with lymph node metastasis. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff values for metastasis prediction.
Results:
The median age was 70.5 years, and 48 were male. Among the 67 patients, 30 had mesorectal lymph node metastasis. At our institution, lymph nodes with a long-axis diameter of ≥ 8 mm on MRI were considered positive for metastasis. Using this threshold, the sensitivity and specificity for predicting mesorectal lymph node metastasis were 0.63 and 0.54, respectively. ROC curve analysis identified cutoff values of 6.9 mm for the long-axis diameter, 4.8 mm for the short-axis diameter, and 0.83 for the short-to-long axis ratio. The areas under the ROC curve for the long-axis, short-axis, and short-to-long axis ratio were 0.81, 0.86, and 0.60, respectively.
Conclusions:
A preoperative long-axis diameter of ≥ 7 mm and a short-axis diameter of ≥ 5 mm were found to be reliable predictors of mesorectal lymph node metastasis in rectal cancer. Using a 5-mm short-axis cutoff improved diagnostic specificity. These findings require further validation in clinical settings to optimize treatment strategies.
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