Diagnostic value of preoperative chest computed tomography examination in clinical tumor-node-metastasis staging of non-small cell lung cancer

Background: This research aimed to investigate diagnostic value of preoperative chest computed tomography (CT) in the staging of clinical tumor-node-metastasis (TNM) in non-small cell lung cancer (NSCLC).Materials and Methods: Hundred and ninety eight patients with NSCLC accepted by the Affiliated Hospital of Shaoxing University (Shaoxing Municipal Hospital) from June 2021 to October 2022 were retrospectively selected as the study subjects.Preoperative multislice spiral computed tomography (MSCT) examination was performed, and the results of pathological examination were the gold standard to evaluate accuracy of CT diagnosis of TNM staging.Results: The staging accuracy of CT diagnosis was 86% for T1, 85.34% for T2, 76.92% for T3, and 66.7% for T4, with an overall accuracy of 83.83%.The Kappa value was 0.744.For nodal staging, the accuracy of CT diagnosis was 85.34% for stage N0, 67.86% for stage N1, and 72.22% for stage N2, yielding an overall accuracy of 79.29%.The Kappa value for nodal staging was 0.702.In terms of specific stages, the accuracy of CT diagnosis was 80.39% for stage IA, 81.40% for IB, 59.38% for IIA, 76.47% for IIB, and 73.21% for IIIA, with an overall accuracy of 75.25%.The Kappa value for these stages was 0.701. Conclusion:The clinical T stage, N stage, and TNM stage diagnosed by CT before surgery were consistent with the pathological T stage after surgery, especially in the early stage of LC.

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Journal
International Journal of Radiation Research
Published
2025-05-01
DOI
https://doi.org/10.61186/ijrr.23.2.29
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
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article

Diagnostic value of preoperative chest computed tomography examination in clinical tumor-node-metastasis staging of non-small cell lung cancer

Xiaoli Xu, Bin He, Lina Wang, Bing Li et al.
International Journal of Radiation Research
Lung Cancer Diagnosis and Treatment
article

Diagnostic value of preoperative chest computed tomography examination in clinical tumor-node-metastasis staging of non-small cell lung cancer

Xiaoli Xu, Bin He, Lina Wang, Bing Li, Jinming Xu
article en

Abstract

Background: This research aimed to investigate diagnostic value of preoperative chest computed tomography (CT) in the staging of clinical tumor-node-metastasis (TNM) in non-small cell lung cancer (NSCLC).Materials and Methods: Hundred and ninety eight patients with NSCLC accepted by the Affiliated Hospital of Shaoxing University (Shaoxing Municipal Hospital) from June 2021 to October 2022 were retrospectively selected as the study subjects.Preoperative multislice spiral computed tomography (MSCT) examination was performed, and the results of pathological examination were the gold standard to evaluate accuracy of CT diagnosis of TNM staging.Results: The staging accuracy of CT diagnosis was 86% for T1, 85.34% for T2, 76.92% for T3, and 66.7% for T4, with an overall accuracy of 83.83%.The Kappa value was 0.744.For nodal staging, the accuracy of CT diagnosis was 85.34% for stage N0, 67.86% for stage N1, and 72.22% for stage N2, yielding an overall accuracy of 79.29%.The Kappa value for nodal staging was 0.702.In terms of specific stages, the accuracy of CT diagnosis was 80.39% for stage IA, 81.40% for IB, 59.38% for IIA, 76.47% for IIB, and 73.21% for IIIA, with an overall accuracy of 75.25%.The Kappa value for these stages was 0.701. Conclusion:The clinical T stage, N stage, and TNM stage diagnosed by CT before surgery were consistent with the pathological T stage after surgery, especially in the early stage of LC.

International Journal of Radiation ResearchVol. 23(2)
Shaoxing University (CN), Shaoxing People's Hospital (CN)
Good health and well-being
Openalex Percentile: Top 72%
Lung Cancer Diagnosis and Treatment
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Diagnostic value of preoperative chest computed tomography examination in clinical tumor-node-metastasis staging of non-small cell lung cancer — Xiaoli Xu, Bin He, et al. · International Journal of Radiation Research (2025) | TGRS Research Map | TGRS