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Related Experiment Video

Updated: Oct 18, 2025

Gene Regulation and Targeted Therapy in Gastric Cancer Peritoneal Metastasis: Radiological Findings from Dual Energy CT and PET/CT
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Predicting Response to Systemic Chemotherapy for Advanced Gastric Cancer Using Pre-Treatment Dual-Energy CT

Yi-Yang Liu1,2, Huan Zhang3, Lan Wang3

  • 1Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Frontiers in Oncology
|October 4, 2021
PubMed
Summary

A new dual-energy CT-based clinical-radiomics nomogram accurately predicts chemotherapy response in advanced gastric cancer (AGC). This tool aids clinical decision-making for improved patient outcomes and survival.

Keywords:
dual-energy CTgastric cancerradiomicsresponse predictionsystemic chemotherapy

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Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Advanced gastric cancer (AGC) poses a significant challenge in treatment selection.
  • Predicting response to systemic chemotherapy is crucial for optimizing patient management.
  • Current prediction methods may lack the precision needed for individualized therapy.

Purpose of the Study:

  • To develop and validate a pre-treatment dual-energy CT (DECT)-based clinical-radiomics nomogram.
  • To individualize the prediction of clinical response to systemic chemotherapy in AGC patients.
  • To assess the nomogram's performance in discrimination, calibration, and clinical usefulness.

Main Methods:

  • Retrospective study of 69 AGC patients undergoing DECT before chemotherapy.
  • Extraction of radiomics features from monochromatic images (40, 70, 100 keV) at venous phase.
  • Development of clinical, monochromatic radiomics, multi-energy radiomics, and combined clinical-radiomics models using logistic regression and LASSO.
  • Evaluation of model performance using ROC analysis and DeLong tests.

Main Results:

  • Clinical stage and tumor iodine concentration (IC) were significant predictors of chemotherapy response.
  • The multi-energy radiomics model achieved an AUC of 0.914, outperforming monochromatic models and the clinical model (AUC 0.775).
  • The integrated clinical-radiomics nomogram demonstrated excellent performance with an AUC of 0.934, showing good calibration and clinical utility.

Conclusions:

  • The pre-treatment DECT-based clinical-radiomics nomogram is a valuable tool for predicting chemotherapy response in AGC.
  • This nomogram can aid in clinical decision-making for personalized treatment strategies.
  • Improved prediction may lead to enhanced patient survival in advanced gastric cancer.