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Radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity
OBJECTIVE: To determine whether the radiomic features of lung lesions on computed tomography correlate with overall survival in lung cancer patients. MATERIALS AND METHODS: This was a retrospective study involving 101 consecutive patients with malignant neoplasms confirmed by biopsy or surgery. On c...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8029936/ https://www.ncbi.nlm.nih.gov/pubmed/33854262 http://dx.doi.org/10.1590/0100-3984.2019.0135 |
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author | Ferreira Junior, José Raniery Koenigkam-Santos, Marcel Machado, Camila Vilas Boas Faleiros, Matheus Calil Correia, Natália Santana Chiari Cipriano, Federico Enrique Garcia Fabro, Alexandre Todorovic de Azevedo-Marques, Paulo Mazzoncini |
author_facet | Ferreira Junior, José Raniery Koenigkam-Santos, Marcel Machado, Camila Vilas Boas Faleiros, Matheus Calil Correia, Natália Santana Chiari Cipriano, Federico Enrique Garcia Fabro, Alexandre Todorovic de Azevedo-Marques, Paulo Mazzoncini |
author_sort | Ferreira Junior, José Raniery |
collection | PubMed |
description | OBJECTIVE: To determine whether the radiomic features of lung lesions on computed tomography correlate with overall survival in lung cancer patients. MATERIALS AND METHODS: This was a retrospective study involving 101 consecutive patients with malignant neoplasms confirmed by biopsy or surgery. On computed tomography images, the lesions were submitted to semi-automated segmentation and were characterized on the basis of 2,465 radiomic variables. The prognostic assessment was based on Kaplan-Meier analysis and log-rank tests, according to the median value of the radiomic variables. RESULTS: Of the 101 patients evaluated, 28 died (16 dying from lung cancer), and 73 were censored, with a mean overall survival time of 1,819.4 days (95% confidence interval [95% CI]: 1,481.2-2,157.5). One radiomic feature (the mean of the Fourier transform) presented a difference on Kaplan-Meier curves (p < 0.05). A high-risk group of patients was identified on the basis of high values for the mean of the Fourier transform. In that group, the mean survival time was 1,465.4 days (95% CI: 985.2-1,945.6), with a hazard ratio of 2.12 (95% CI: 1.01-4.48). We also identified a low-risk group, in which the mean of the Fourier transform was low (mean survival time of 2,164.8 days; 95% CI: 1,745.4-2,584.1). CONCLUSION: A radiomic signature based on the Fourier transform correlates with overall survival, representing a prognostic biomarker for risk stratification in patients with lung cancer. |
format | Online Article Text |
id | pubmed-8029936 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem |
record_format | MEDLINE/PubMed |
spelling | pubmed-80299362021-04-13 Radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity Ferreira Junior, José Raniery Koenigkam-Santos, Marcel Machado, Camila Vilas Boas Faleiros, Matheus Calil Correia, Natália Santana Chiari Cipriano, Federico Enrique Garcia Fabro, Alexandre Todorovic de Azevedo-Marques, Paulo Mazzoncini Radiol Bras Original Article OBJECTIVE: To determine whether the radiomic features of lung lesions on computed tomography correlate with overall survival in lung cancer patients. MATERIALS AND METHODS: This was a retrospective study involving 101 consecutive patients with malignant neoplasms confirmed by biopsy or surgery. On computed tomography images, the lesions were submitted to semi-automated segmentation and were characterized on the basis of 2,465 radiomic variables. The prognostic assessment was based on Kaplan-Meier analysis and log-rank tests, according to the median value of the radiomic variables. RESULTS: Of the 101 patients evaluated, 28 died (16 dying from lung cancer), and 73 were censored, with a mean overall survival time of 1,819.4 days (95% confidence interval [95% CI]: 1,481.2-2,157.5). One radiomic feature (the mean of the Fourier transform) presented a difference on Kaplan-Meier curves (p < 0.05). A high-risk group of patients was identified on the basis of high values for the mean of the Fourier transform. In that group, the mean survival time was 1,465.4 days (95% CI: 985.2-1,945.6), with a hazard ratio of 2.12 (95% CI: 1.01-4.48). We also identified a low-risk group, in which the mean of the Fourier transform was low (mean survival time of 2,164.8 days; 95% CI: 1,745.4-2,584.1). CONCLUSION: A radiomic signature based on the Fourier transform correlates with overall survival, representing a prognostic biomarker for risk stratification in patients with lung cancer. Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem 2021 /pmc/articles/PMC8029936/ /pubmed/33854262 http://dx.doi.org/10.1590/0100-3984.2019.0135 Text en https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Ferreira Junior, José Raniery Koenigkam-Santos, Marcel Machado, Camila Vilas Boas Faleiros, Matheus Calil Correia, Natália Santana Chiari Cipriano, Federico Enrique Garcia Fabro, Alexandre Todorovic de Azevedo-Marques, Paulo Mazzoncini Radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity |
title | Radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity |
title_full | Radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity |
title_fullStr | Radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity |
title_full_unstemmed | Radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity |
title_short | Radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity |
title_sort | radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8029936/ https://www.ncbi.nlm.nih.gov/pubmed/33854262 http://dx.doi.org/10.1590/0100-3984.2019.0135 |
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