[Home ] [Archive]    
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
IJRR Information::
For Authors::
For Reviewers::
Subscription::
News & Events::
Web Mail::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
ISSN
Hard Copy 2322-3243
Online 2345-4229
..
Online Submission
Now you can send your articles to IJRR office using the article submission system.
..

AWT IMAGE

AWT IMAGE

:: Volume 23, Issue 2 (5-2025) ::
Int J Radiat Res 2025, 23(2): 467-472 Back to browse issues page
Diagnostic value of preoperative chest computed tomography examination in clinical tumor-node-metastasis staging of non-small cell lung cancer
X. Xu , J. Xu , L. Wang , B. Li , B. He
Department of Radiology, The Affiliated Hospital of Shaoxing University, Shaoxing, Zhejiang Province, China , 277528573@qq.com
Abstract:   (223 Views)
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.
Keywords: TNM staging, CT examination, preoperative diagnosis, NSCLC.
Full-Text [PDF 632 kb]   (79 Downloads)    
Type of Study: Original Research | Subject: Radiation Biology
References
1. Jones GS and Baldwin DR (2018) Recent advances in the management of lung cancer. Clin Med (Lond), 18(Suppl 2): s41-s46. DOI: 10.7861/clinmedicine.18-2-s41 [DOI:10.7861/clinmedicine.18-2-s41]
2. Zhang K, Lai Y, Axelrod R, et al. (2015) Modeling the overall survival of patients with advanced-stage non-small cell lung cancer using data of routine laboratory tests. Int J Cancer, 136(2): 382-91. DOI: 10.1002/ijc.28995 [DOI:10.1002/ijc.28995]
3. Li C, Lu H, Jiang X, et al. (2022) Network pharmacology study of Citrus reticulata and Pinellia ternata in the treatment of non-small cell lung cancer. Cell Mol Biol, 67(4): 10-17. DOI: 10.14715/cmb/2021.67.4.2 [DOI:10.14715/cmb/2021.67.4.2]
4. Novello S, Kowalski DM, Luft A, et al. (2023) Pembrolizumab plus chemotherapy in squamous non-small-cell lung cancer: 5-year update of the phase III KEYNOTE-407 study. J Clin Oncol, 41(11): 1999-2006. DOI: 10.1200/JCO.22.01990 [DOI:10.1200/JCO.22.01990]
5. Ikeuchi N, Igata F, Kinoshita E, et al. (2023) Real-world efficacy and safety of atezolizumab plus bevacizumab, paclitaxel and carboplatin for first-line treatment of japanese patients with metastatic non-squamous non-small cell lung cancer. Anticancer Res, 43(2): 713-724. DOI: 10.21873/anticanres.16210 [DOI:10.21873/anticanres.16210]
6. Ren J, Ren J, Wang K, et al. (2023) The location of visceral pleural invasion in stage IB patients with non-small cell lung cancer: Comparison and prognosis. Eur J Surg Oncol, 49(5): 950-957. DOI: 10.1016/j.ejso.2023.01.022 [DOI:10.1016/j.ejso.2023.01.022]
7. Chen D, Han W, Wang P, et al. (2023) Correlation between the mRNA levels of BCRP and LUNX genes and pathological types and stages of patients with non-small cell lung cancer. Zhonghua Yi Xue Yi Chuan Xue Za Zhi, 40(2): 202-207. DOI: 10.3760/cma.j.cn511386-20210624-00538
8. Wan Y, Qian Y, Wang Y, et al. (2022) Prognostic value of Beclin 1, EGFR and ALK in non-squamous non-small cell lung cancer. Discov Oncol, 13(1): 127. DOI: 10.1007/s12672-022-00586-y [DOI:10.1007/s12672-022-00586-y]
9. Mohammed ASS and Faraj KA (2023) Estimation of oesophageal surface dose in breast cancer patients undergoing supraclavicular irradiation by thermoluminescent dosimeter (TLD) and treatment planning system (TPS). International Journal of Radiation Research, 21(4): 647-652. DOI: 10.61186/ijrr.21.4.647 [DOI:10.61186/ijrr.21.4.647]
10. Luo Y, Hu S, Wang F, et al. (2022) miR-137 represses migration and cell motility by targeting COX-2 in non-small cell lung cancer. Transl Cancer Res, 11(10): 3803-3813. DOI: 10.21037/tcr-22-2177 [DOI:10.21037/tcr-22-2177]
11. Wang R, Wang S, Li Z, et al. (2022) PLEKHH2 binds β-arrestin1 through its FERM domain, activates FAK/PI3K/AKT phosphorylation, and promotes the malignant phenotype of non-small cell lung cancer. Cell Death Dis, 13(10): 858. DOI: 10.1038/s41419-022-05307-5 [DOI:10.1038/s41419-022-05307-5]
12. Ammann Y, Beutner U, Vital DG, et al. (2021) Impact of the new TNM Staging System (8th edition) on oral tongue cancers. Swiss Med Wkly, 151: w20493. DOI: 10.4414/smw.2021.20493 [DOI:10.4414/smw.2021.20493]
13. Baum P, Taber S, Erdmann S, et al. (2021) Validation of the T Descriptor (TNM-8) in T3N0 non-small-cell lung cancer patients
14. a bicentric cohort analysis with arguments for redefinition. Cancers, 13(8): 1812. DOI: 10.3390/cancers13081812 [DOI:10.3390/cancers13081812]
15. Li Y, Wu X, Yang P, et al. (2022) Machine learning for lung cancer diagnosis, treatment, and prognosis. Genomics Proteomics Bioinformatics, 20(5): 850-866. DOI: 10.1016/j.gpb.2022.11.003 [DOI:10.1016/j.gpb.2022.11.003]
16. Belfiore MP, Sansone M, Monti R, et al. (2022) Robustness of radiomics in pre-surgical computer tomography of non-small-cell lung cancer. J Pers Med, 13(1): 83. DOI: 10.3390/jpm13010083 [DOI:10.3390/jpm13010083]
17. Alhomoud M, Chokr N, Gomez-Arteaga A, et al. (2023) Screening chest CT prior to allogenic hematopoietic stem cell transplantation. Transplant Cell Ther, 29(5): 326.e1-326.e10. DOI: 10.1016/j.jtct.2023.01.029 [DOI:10.1016/j.jtct.2023.01.029]
18. Kandathil A, Kay FU, Butt YM, et al. (2018) Role of FDG PET/CT in the Eighth Edition of TNM staging of non-small cell lung cancer. Radiographics, 38(7): 2134-2149. DOI: 10.1148/rg.2018180060 [DOI:10.1148/rg.2018180060]
19. Hou X, Zhou C, Wu G, et al. (2023) Efficacy, safety, and health-related quality of life with camrelizumab plus pemetrexed and carboplatin as first-line treatment for advanced nonsquamous NSCLC with brain metastases (CAP-BRAIN): A multicenter, open-label, single-arm, phase 2 study. J Thorac Oncol, 18(6): 769-779. DOI: 10.1016/j.jtho.2023.01.083 [DOI:10.1016/j.jtho.2023.01.083]
20. Volpe S, Isaksson LJ, Zaffaroni M, et al. (2022) Impact of image filtering and assessment of volume-confounding effects on CT radiomic features and derived survival models in non-small cell lung cancer. Transl Lung Cancer Res, 11(12): 2452-2463. DOI: 10.21037/tlcr-22-248 [DOI:10.21037/tlcr-22-248]
21. Liu H, Dilger JP, Lin J (2020) Effects of local anesthetics on cancer cells. Pharmacol Ther, 212: 107558. DOI: 10.1016/j.pharmthera.2020 [DOI:10.1016/j.pharmthera.2020.107558]
22. Jin Z, Zhang W, Liu H, et al. (2022) Potential therapeutic application of local anesthetics in cancer treatment. Recent Pat Anticancer Drug Discov, 17(4): 326-342. DOI: 10.2174/1574892817666220119121204 [DOI:10.2174/1574892817666220119121204]
23. Erdoğu V, Çıtak N, Sezen CB, et al. (2022) Comparison of 6th, 7th, and 8th editions of the TNM staging in non-small cell lung cancer patients: Validation of the 8th edition of TNM staging. Turk Gogus Kalp Damar Cerrahisi Derg, 30(3): 395-403. DOI: 10.5606/tgkdc.dergisi.2022.20089 [DOI:10.5606/tgkdc.dergisi.2022.20089]
24. Colombi D, Petrini M, Rapacioli F, et al. (2022) Role of visceral pleural invasion and tumor sizing at CT of resected NSCLC in clinical-radiological and pathological T agreement. Tumori, 109(2): 215-223. DOI: 10.1177/03008916221083702 [DOI:10.1177/03008916221083702]
25. Chen Y, Zhang J, Chen J, et al. (2022) Prognostic relevance of rib invasion and modification of T description for resected NSCLC patients: A propensity score matching analysis of the SEER database. Front Oncol, 12: 1082850. DOI: 10.3389/fonc.2022.1082850 [DOI:10.3389/fonc.2022.1082850]
26. Lazar V, Girard N, Raymond E, et al. (2022) Transcriptomics in tumor and normal lung tissues identify patients with early-stage non-small-cell lung cancer with high risk of postsurgery recurrence who may benefit from adjuvant therapies. JCO Precis Oncol, 6: e2200072. DOI: 10.1200/PO.22.00072 [DOI:10.1200/PO.22.00072]
27. Kucuker M, Kucuker KA, Guney IB, et al. (2021) The importance of anatomical localization of non-small cell lung carcinoma in predicting mediastinal lymph node metastasis. Clin Anat, 35(2): 136-142. DOI: 10.1002/ca.23786 [DOI:10.1002/ca.23786]
28. Can C, Kepenek F, Kömek H, et al. (2022) Comparison of 18 F-FDG PET/CT and 68 Ga-FAPI-04 PET/CT in patients with non-small cell lung cancer. Nucl Med Commun, 43(10): 1084-1091. DOI: 10.1097/MNM.0000000000001607 [DOI:10.1097/MNM.0000000000001607]
29. Daylan AEC, Miao E, Tang K, et al. (2023) Lung cancer in never smokers: delving into epidemiology, genomic and immune landscape, prognosis, treatment, and screening. Lung, 201(6): 521-529. DOI: 10.1007/s00408-023-00661-3 [DOI:10.1007/s00408-023-00661-3]
30. Wang C, Tan S, Li J, et al. (2020) CircRNAs in lung cancer - Biogenesis, function and clinical implication. Cancer Lett, 492:106-115. DOI: 10.1016/j.canlet.2020.08.013. [DOI:10.1016/j.canlet.2020.08.013]
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA



XML     Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Xu X, Xu J, Wang L, Li B, He B. Diagnostic value of preoperative chest computed tomography examination in clinical tumor-node-metastasis staging of non-small cell lung cancer. Int J Radiat Res 2025; 23 (2) :467-472
URL: http://ijrr.com/article-1-6424-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 23, Issue 2 (5-2025) Back to browse issues page
International Journal of Radiation Research
Persian site map - English site map - Created in 0.05 seconds with 50 queries by YEKTAWEB 4714