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Related Experiment Video

Updated: Jul 16, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

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

MRI Dark-Light-Dark Sign and Node Reporting Score: An Integrated Model for Predicting Lymph Node Metastasis in Rectal

Cenk Parlatan1, Şeyda Gökçe Turunç2, Okan Dilek2

  • 1Department of Radiology, Adana Dr. Turgut Noyan Application and Research Center, Baskent University, Adana 01250, Turkey.

Journal of Clinical Medicine
|July 15, 2026
PubMed
Summary

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Combining the dark-light-dark (DLD) sign with Node Reporting and Data System (Node-RADS) improves preoperative rectal cancer lymph node metastasis prediction. This integrated imaging approach offers enhanced risk stratification for patients.

Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Accurate preoperative assessment of lymph node metastasis is crucial for rectal cancer staging and treatment planning.
  • Current imaging modalities have limitations in definitively identifying nodal involvement.

Purpose of the Study:

  • To evaluate the diagnostic performance and incremental value of the dark-light-dark (DLD) sign combined with the Node Reporting and Data System (Node-RADS) for preoperative prediction of lymph node metastasis in rectal cancer.

Main Methods:

  • Retrospective analysis of 166 rectal adenocarcinoma patients undergoing preoperative pelvic MRI.
  • Independent assessment of Node-RADS and DLD status by blinded radiologists.
  • Development and validation of a combined DLD + Node-RADS predictive model using logistic regression, ROC analysis, and decision curve analysis.
Keywords:
dark–light–dark signlymph node metastasismagnetic resonance imagingnode reporting and data systemrectal cancer

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Main Results:

  • The combined DLD + Node-RADS model demonstrated superior discriminatory performance (AUC, 0.795) compared to Node-RADS (0.740) and DLD status (0.713) alone.
  • Both Node-RADS and DLD-negative status were independent predictors of lymph node metastasis.
  • The integrated model showed good calibration, stable internal validation, and potential clinical utility.

Conclusions:

  • Integration of DLD status with Node-RADS offers incremental value for preoperative prediction of lymph node metastasis in rectal cancer.
  • The combined imaging-based strategy provides complementary risk stratification, particularly for indeterminate nodal categories.
  • External validation is recommended prior to routine clinical implementation.