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Related Experiment Video

Updated: May 28, 2025

Gene Regulation and Targeted Therapy in Gastric Cancer Peritoneal Metastasis: Radiological Findings from Dual Energy CT and PET/CT
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Gene Regulation and Targeted Therapy in Gastric Cancer Peritoneal Metastasis: Radiological Findings from Dual Energy CT and PET/CT

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Value of Post-NAC CT-based Node-RADS score for Predicting residual lymph node metastasis and survival outcome of

Yan Sun1,2, Hua Xiao3,4, Lu Wen2

  • 1Graduate Collaborative Training Base of Hunan Cancer Hospital, Hengyang Medical School, University of South China, Hengyang, China.

Abdominal Radiology (New York)
|February 13, 2025
PubMed
Summary
This summary is machine-generated.

The Node Reporting and Data System (Node-RADS) accurately predicts lymph node metastasis in locally advanced gastric cancer after neoadjuvant chemotherapy. This system also shows promise in determining patient survival outcomes.

Keywords:
CTGastric cancerLymph nodeNode-RADSPrognosis

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Area of Science:

  • Oncology
  • Radiology
  • Medical Imaging

Background:

  • Locally advanced gastric cancer (LAGC) requires effective lymph node evaluation.
  • Neoadjuvant chemotherapy (NAC) followed by gastrectomy is a standard treatment.
  • Accurate prediction of residual lymph node metastasis (LNM) and survival is crucial for patient management.

Purpose of the Study:

  • To evaluate the Node Reporting and Data System (Node-RADS) for predicting LNM after NAC in LAGC.
  • To assess the prognostic value of Node-RADS for overall survival (OS) in LAGC patients.
  • To develop and validate predictive and prognostic models based on Node-RADS.

Main Methods:

  • Retrospective analysis of 118 LAGC patients who underwent NAC and gastrectomy.
  • Assessed diagnostic performance of post-NAC CT-based Node-RADS score for LNM using AUC and Youden's index.
  • Developed predictive (logistic regression) and prognostic (Cox regression) models using Node-RADS.

Main Results:

  • Node-RADS demonstrated high accuracy in predicting LNM (AUC 0.843 at patient level), outperforming short-axis criteria.
  • The NR predictive model achieved an AUC of 0.870 with 88.7% sensitivity and 78.9% specificity.
  • Node-RADS was an independent predictor of OS, and the NR prognostic model showed comparable performance to pathological models.

Conclusions:

  • Post-NAC Node-RADS score accurately predicts regional LNM in LAGC.
  • Node-RADS offers valuable prognostic information for LAGC patients.
  • Node-RADS-based models can aid in early identification of high-risk patients.