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Pre-Operative Prediction of Mediastinal Node Metastasis Using Radiomics Model Based on (18)F-FDG PET/CT of the Primary Tumor in Non-Small Cell Lung Cancer Patients
Purpose: We investigated whether a fluorine-18-fluorodeoxy glucose positron emission tomography/computed tomography ((18)F-FDG PET/CT)-based radiomics model (RM) could predict the pathological mediastinal lymph node staging (pN staging) in patients with non-small cell lung cancer (NSCLC) undergoing...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8249728/ https://www.ncbi.nlm.nih.gov/pubmed/34222284 http://dx.doi.org/10.3389/fmed.2021.673876 |
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author | Zheng, Kai Wang, Xinrong Jiang, Chengzhi Tang, Yongxiang Fang, Zhihui Hou, Jiale Zhu, Zehua Hu, Shuo |
author_facet | Zheng, Kai Wang, Xinrong Jiang, Chengzhi Tang, Yongxiang Fang, Zhihui Hou, Jiale Zhu, Zehua Hu, Shuo |
author_sort | Zheng, Kai |
collection | PubMed |
description | Purpose: We investigated whether a fluorine-18-fluorodeoxy glucose positron emission tomography/computed tomography ((18)F-FDG PET/CT)-based radiomics model (RM) could predict the pathological mediastinal lymph node staging (pN staging) in patients with non-small cell lung cancer (NSCLC) undergoing surgery. Methods: A total of 716 patients with a clinicopathological diagnosis of NSCLC were included in this retrospective study. The prediction model was developed in a training cohort that consisted of 501 patients. Radiomics features were extracted from the (18)F-FDG PET/CT of the primary tumor. Support vector machine and extremely randomized trees were used to build the RM. Internal validation was assessed. An independent testing cohort contained the remaining 215 patients. The performances of the RM and clinical node staging (cN staging) in predicting pN staging (pN0 vs. pN1 and N2) were compared for each cohort. The area under the curve (AUC) of the receiver operating characteristic curve was applied to assess the model's performance. Results: The AUC of the RM [0.81 (95% CI, 0.771–0.848); sensitivity: 0.794; specificity: 0.704] for the predictive performance of pN1 and N2 was significantly better than that of cN in the training cohort [0.685 (95% CI, 0.644–0.728); sensitivity: 0.804; specificity: 0.568], (P-value = 8.29e-07, as assessed by the Delong test). In the testing cohort, the AUC of the RM [0.766 (95% CI, 0.702–0.830); sensitivity: 0.688; specificity: 0.704] was also significantly higher than that of cN [0.685 (95% CI, 0.619–0.747); sensitivity: 0.799; specificity: 0.568], (P = 0.0371, Delong test). Conclusions: The RM based on (18)F-FDG PET/CT has a potential for the pN staging in patients with NSCLC, suggesting that therapeutic planning could be tailored according to the predictions. |
format | Online Article Text |
id | pubmed-8249728 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82497282021-07-03 Pre-Operative Prediction of Mediastinal Node Metastasis Using Radiomics Model Based on (18)F-FDG PET/CT of the Primary Tumor in Non-Small Cell Lung Cancer Patients Zheng, Kai Wang, Xinrong Jiang, Chengzhi Tang, Yongxiang Fang, Zhihui Hou, Jiale Zhu, Zehua Hu, Shuo Front Med (Lausanne) Medicine Purpose: We investigated whether a fluorine-18-fluorodeoxy glucose positron emission tomography/computed tomography ((18)F-FDG PET/CT)-based radiomics model (RM) could predict the pathological mediastinal lymph node staging (pN staging) in patients with non-small cell lung cancer (NSCLC) undergoing surgery. Methods: A total of 716 patients with a clinicopathological diagnosis of NSCLC were included in this retrospective study. The prediction model was developed in a training cohort that consisted of 501 patients. Radiomics features were extracted from the (18)F-FDG PET/CT of the primary tumor. Support vector machine and extremely randomized trees were used to build the RM. Internal validation was assessed. An independent testing cohort contained the remaining 215 patients. The performances of the RM and clinical node staging (cN staging) in predicting pN staging (pN0 vs. pN1 and N2) were compared for each cohort. The area under the curve (AUC) of the receiver operating characteristic curve was applied to assess the model's performance. Results: The AUC of the RM [0.81 (95% CI, 0.771–0.848); sensitivity: 0.794; specificity: 0.704] for the predictive performance of pN1 and N2 was significantly better than that of cN in the training cohort [0.685 (95% CI, 0.644–0.728); sensitivity: 0.804; specificity: 0.568], (P-value = 8.29e-07, as assessed by the Delong test). In the testing cohort, the AUC of the RM [0.766 (95% CI, 0.702–0.830); sensitivity: 0.688; specificity: 0.704] was also significantly higher than that of cN [0.685 (95% CI, 0.619–0.747); sensitivity: 0.799; specificity: 0.568], (P = 0.0371, Delong test). Conclusions: The RM based on (18)F-FDG PET/CT has a potential for the pN staging in patients with NSCLC, suggesting that therapeutic planning could be tailored according to the predictions. Frontiers Media S.A. 2021-06-18 /pmc/articles/PMC8249728/ /pubmed/34222284 http://dx.doi.org/10.3389/fmed.2021.673876 Text en Copyright © 2021 Zheng, Wang, Jiang, Tang, Fang, Hou, Zhu and Hu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Medicine Zheng, Kai Wang, Xinrong Jiang, Chengzhi Tang, Yongxiang Fang, Zhihui Hou, Jiale Zhu, Zehua Hu, Shuo Pre-Operative Prediction of Mediastinal Node Metastasis Using Radiomics Model Based on (18)F-FDG PET/CT of the Primary Tumor in Non-Small Cell Lung Cancer Patients |
title | Pre-Operative Prediction of Mediastinal Node Metastasis Using Radiomics Model Based on (18)F-FDG PET/CT of the Primary Tumor in Non-Small Cell Lung Cancer Patients |
title_full | Pre-Operative Prediction of Mediastinal Node Metastasis Using Radiomics Model Based on (18)F-FDG PET/CT of the Primary Tumor in Non-Small Cell Lung Cancer Patients |
title_fullStr | Pre-Operative Prediction of Mediastinal Node Metastasis Using Radiomics Model Based on (18)F-FDG PET/CT of the Primary Tumor in Non-Small Cell Lung Cancer Patients |
title_full_unstemmed | Pre-Operative Prediction of Mediastinal Node Metastasis Using Radiomics Model Based on (18)F-FDG PET/CT of the Primary Tumor in Non-Small Cell Lung Cancer Patients |
title_short | Pre-Operative Prediction of Mediastinal Node Metastasis Using Radiomics Model Based on (18)F-FDG PET/CT of the Primary Tumor in Non-Small Cell Lung Cancer Patients |
title_sort | pre-operative prediction of mediastinal node metastasis using radiomics model based on (18)f-fdg pet/ct of the primary tumor in non-small cell lung cancer patients |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8249728/ https://www.ncbi.nlm.nih.gov/pubmed/34222284 http://dx.doi.org/10.3389/fmed.2021.673876 |
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