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Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features
BACKGROUND: Texture features reflecting tumour heterogeneity enable us to investigate prognostic factors. The R package ComBat can harmonize the quantitative texture features among several positron emission tomography (PET) scanners. We aimed to identify prognostic factors among harmonized PET radio...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9986192/ https://www.ncbi.nlm.nih.gov/pubmed/36872413 http://dx.doi.org/10.1186/s41824-023-00163-8 |
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author | Watanabe, Masao Ashida, Ryo Miyakoshi, Chisato Arizono, Shigeki Suga, Tsuyoshi Kanao, Shotaro Kitamura, Koji Ogawa, Takahisa Ishikura, Reiichi |
author_facet | Watanabe, Masao Ashida, Ryo Miyakoshi, Chisato Arizono, Shigeki Suga, Tsuyoshi Kanao, Shotaro Kitamura, Koji Ogawa, Takahisa Ishikura, Reiichi |
author_sort | Watanabe, Masao |
collection | PubMed |
description | BACKGROUND: Texture features reflecting tumour heterogeneity enable us to investigate prognostic factors. The R package ComBat can harmonize the quantitative texture features among several positron emission tomography (PET) scanners. We aimed to identify prognostic factors among harmonized PET radiomic features and clinical information from pancreatic cancer patients who underwent curative surgery. METHODS: Fifty-eight patients underwent preoperative enhanced dynamic computed tomography (CT) scanning and fluorodeoxyglucose PET/CT using four PET scanners. Using LIFEx software, we measured PET radiomic parameters including texture features with higher order and harmonized these PET parameters. For progression-free survival (PFS) and overall survival (OS), we evaluated clinical information, including age, TNM stage, and neural invasion, and the harmonized PET radiomic features based on univariate Cox proportional hazard regression. Next, we analysed the prognostic indices by multivariate Cox proportional hazard regression (1) by using either significant (p < 0.05) or borderline significant (p = 0.05–0.10) indices in the univariate analysis (first multivariate analysis) or (2) by using the selected features with random forest algorithms (second multivariate analysis). Finally, we checked these multivariate results by log-rank test. RESULTS: Regarding the first multivariate analysis for PFS after univariate analysis, age was the significant prognostic factor (p = 0.020), and MTV and GLCM contrast were borderline significant (p = 0.051 and 0.075, respectively). Regarding the first multivariate analysis of OS, neural invasion, Shape sphericity and GLZLM LZLGE were significant (p = 0.019, 0.042 and 0.0076). In the second multivariate analysis, only MTV was significant (p = 0.046) for PFS, whereas GLZLM LZLGE was significant (p = 0.047), and Shape sphericity was borderline significant (p = 0.088) for OS. In the log-rank test, age, MTV and GLCM contrast were borderline significant for PFS (p = 0.08, 0.06 and 0.07, respectively), whereas neural invasion and Shape sphericity were significant (p = 0.03 and 0.04, respectively), and GLZLM LZLGE was borderline significant for OS (p = 0.08). CONCLUSIONS: Other than the clinical factors, MTV and GLCM contrast for PFS and Shape sphericity and GLZLM LZLGE for OS may be prognostic PET parameters. A prospective multicentre study with a larger sample size may be warranted. |
format | Online Article Text |
id | pubmed-9986192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-99861922023-03-07 Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features Watanabe, Masao Ashida, Ryo Miyakoshi, Chisato Arizono, Shigeki Suga, Tsuyoshi Kanao, Shotaro Kitamura, Koji Ogawa, Takahisa Ishikura, Reiichi Eur J Hybrid Imaging Original Article BACKGROUND: Texture features reflecting tumour heterogeneity enable us to investigate prognostic factors. The R package ComBat can harmonize the quantitative texture features among several positron emission tomography (PET) scanners. We aimed to identify prognostic factors among harmonized PET radiomic features and clinical information from pancreatic cancer patients who underwent curative surgery. METHODS: Fifty-eight patients underwent preoperative enhanced dynamic computed tomography (CT) scanning and fluorodeoxyglucose PET/CT using four PET scanners. Using LIFEx software, we measured PET radiomic parameters including texture features with higher order and harmonized these PET parameters. For progression-free survival (PFS) and overall survival (OS), we evaluated clinical information, including age, TNM stage, and neural invasion, and the harmonized PET radiomic features based on univariate Cox proportional hazard regression. Next, we analysed the prognostic indices by multivariate Cox proportional hazard regression (1) by using either significant (p < 0.05) or borderline significant (p = 0.05–0.10) indices in the univariate analysis (first multivariate analysis) or (2) by using the selected features with random forest algorithms (second multivariate analysis). Finally, we checked these multivariate results by log-rank test. RESULTS: Regarding the first multivariate analysis for PFS after univariate analysis, age was the significant prognostic factor (p = 0.020), and MTV and GLCM contrast were borderline significant (p = 0.051 and 0.075, respectively). Regarding the first multivariate analysis of OS, neural invasion, Shape sphericity and GLZLM LZLGE were significant (p = 0.019, 0.042 and 0.0076). In the second multivariate analysis, only MTV was significant (p = 0.046) for PFS, whereas GLZLM LZLGE was significant (p = 0.047), and Shape sphericity was borderline significant (p = 0.088) for OS. In the log-rank test, age, MTV and GLCM contrast were borderline significant for PFS (p = 0.08, 0.06 and 0.07, respectively), whereas neural invasion and Shape sphericity were significant (p = 0.03 and 0.04, respectively), and GLZLM LZLGE was borderline significant for OS (p = 0.08). CONCLUSIONS: Other than the clinical factors, MTV and GLCM contrast for PFS and Shape sphericity and GLZLM LZLGE for OS may be prognostic PET parameters. A prospective multicentre study with a larger sample size may be warranted. Springer International Publishing 2023-03-06 /pmc/articles/PMC9986192/ /pubmed/36872413 http://dx.doi.org/10.1186/s41824-023-00163-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Watanabe, Masao Ashida, Ryo Miyakoshi, Chisato Arizono, Shigeki Suga, Tsuyoshi Kanao, Shotaro Kitamura, Koji Ogawa, Takahisa Ishikura, Reiichi Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features |
title | Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features |
title_full | Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features |
title_fullStr | Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features |
title_full_unstemmed | Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features |
title_short | Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features |
title_sort | prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9986192/ https://www.ncbi.nlm.nih.gov/pubmed/36872413 http://dx.doi.org/10.1186/s41824-023-00163-8 |
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