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Evaluating the diagnostic accuracy of dynamic CT transmural sign for T staging of gastric cancer compared to conventional CT criteria

  • The Catholic University of Korea, College of Medicine

Research output: Contribution to journalArticlepeer-review

Abstract

Background: To retrospectively evaluate the diagnostic performance of pre-procedural multidetector computed tomography (MDCT) using dynamic CT transmural (CTTM) criteria for T staging of gastric cancer. Methods: This retrospective study enrolled 116 patients who underwent three-phase dynamic MDCT and subsequently received endoscopic treatment or surgery. The positive CTTM sign was defined as a new diagnostic criterion for this study. Two radiologists independently reviewed the CT images, categorizing patients into five groups: T1b sm1, T1b sm2/3, T2, T3, and T4. The diagnostic performance of the new criterion was assessed against pathological results as the gold standard. Sensitivity, specificity, accuracy, and positive and negative predictive values for each T stage were compared to those of conventional CT. Results: Dynamic CTTM criteria demonstrated higher overall diagnostic accuracy (Reviewer 1: 88.9%, Reviewer 2: 91.4%) for T staging compared to conventional CT criteria (75.9%). Reviewer 1 accurately staged T1b in 85.3% of patients, T2 in 87.7%, T3 in 94.1%, and T4 in 98.3%. Reviewer 2 achieved T1b accuracy of 87.9%, T2 of 89.2%, T3 of 94.9%, and T4 of 98.3%. The dynamic CTTM criteria effectively subdivided T1b into T1b sm1 (87.2% and 88.1%) and T1b sm2/3 (84.6% and 86.2%). Dynamic CTTM criteria exhibited higher under-staging rates, while conventional criteria showed higher over-staging rates. Conclusions: Dynamic CTTM criteria demonstrated superior accuracy in T staging of gastric cancer and reasonable effectiveness in subdividing T1b stages into T1b sm1 and T1b sm2/3.

Original languageEnglish
Article number179
JournalBMC Medical Imaging
Volume25
Issue number1
DOIs
StatePublished - Dec 2025

Bibliographical note

Publisher Copyright:
© The Author(s) 2025.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Computed tomography
  • Gastric cancer
  • Histopathology
  • Staging

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