Related Experiment Video For colorectal cancer
Updated: Oct 28, 2025
Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
The additional diagnostic impact of positron emission tomography-computed tomography for lymph node metastasis from
Yukitoshi Todate1,2, Michitaka Honda1,2, Toshihiko Takada3
1Department of Surgery, Southern TOHOKU Research Institute for Neuroscience, Southern TOHOKU General Hospital, Koriyama, Japan.
Background:
We conducted a prospective study to determine the diagnostic performance of positron emission tomography-computed tomography (PET-CT) for lymph node metastasis in colorectal cancer patients.
Methods:
We enrolled patients scheduled to receive curative surgery with lymph node dissection for colorectal adenocarcinoma who underwent contrast-enhanced abdominopelvic CT and PET-CT before surgery and who had primary lesions of cT2 or deeper. A radiologist determined the fluorodeoxyglucose uptake and the standardized uptake value (SUV) and metabolic volume (MV) to diagnose metastasis in cases with enlarged lymph nodes (≥7 mm long in minor diameter) on contrast-enhanced CT. Two gastrointestinal surgeons intraoperatively identified target lymph nodes to assess the association between images and pathological findings. The diagnostic performance (i.e., sensitivity, specificity, and positive and negative predictive values) for lymph node metastasis was determined using multilevel logistic modeling.
Results:
A total of 205 colorectal cancer patients were enrolled from February 2018 to April 2020 and 194 patients were analyzed in this study. The sensitivity, specificity, and positive and negative predictive values of PET-CT were 15.3% (13.4%-17.5%), 100.0% (99.0%-100.0%), 100.0% (51.2%-100.0%), and 98.7% (98.5%-99.0%), respectively.
Conclusion:
PET-CT is a useful modality for determining the presence of metastasis in swollen lymph nodes on contrast-enhanced CT in colorectal cancer patients.
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