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Development and validation of a [(18)F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients

OBJECTIVE: In this study, based on PET/CT radiomics features, we developed and validated a nomogram to predict progression-free survival (PFS) for cases with diffuse large B cell lymphoma (DLBCL) treated with immunochemotherapy. METHODS: This study retrospectively recruited 129 cases with DLBCL. Amo...

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Autores principales: Li, Mingshan, Yao, Hongyang, Zhang, Peng, Zhang, Lingbo, Liu, Wei, Jiang, Zhiyun, Li, Wei, Zhao, Shu, Wang, Kezheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10121518/
https://www.ncbi.nlm.nih.gov/pubmed/36547676
http://dx.doi.org/10.1007/s00330-022-09301-5
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author Li, Mingshan
Yao, Hongyang
Zhang, Peng
Zhang, Lingbo
Liu, Wei
Jiang, Zhiyun
Li, Wei
Zhao, Shu
Wang, Kezheng
author_facet Li, Mingshan
Yao, Hongyang
Zhang, Peng
Zhang, Lingbo
Liu, Wei
Jiang, Zhiyun
Li, Wei
Zhao, Shu
Wang, Kezheng
author_sort Li, Mingshan
collection PubMed
description OBJECTIVE: In this study, based on PET/CT radiomics features, we developed and validated a nomogram to predict progression-free survival (PFS) for cases with diffuse large B cell lymphoma (DLBCL) treated with immunochemotherapy. METHODS: This study retrospectively recruited 129 cases with DLBCL. Among them, PET/CT scans were conducted and baseline images were collected for radiomics features along with their clinicopathological features. Radiomics features related to recurrence were screened for survival analysis using univariate Cox regression analysis with p < 0.05. Next, a weighted Radiomics-score (Rad-score) was generated and independent risk factors were obtained from univariate and multivariate Cox regressions to build the nomogram. Furthermore, the nomogram was tested for their ability to predict PFS using time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: Blood platelet, Rad-score, and gender were included in the nomogram as independent DLBCL risk factors for PFS. We found that the training cohort areas under the curve (AUCs) were 0.79, 0.84, and 0.88, and validation cohort AUCs were 0.67, 0.83, and 0.72, respectively. Further, the DCA and calibration curves confirmed the predictive nomogram’s clinical relevance. CONCLUSION: Using Rad-score, blood platelet, and gender of the DLBCL patients, a PET/CT radiomics-based nomogram was developed to guide cases’ recurrence risk assessment prior to treatment. The developed nomogram can help provide more appropriate treatment plans to the cases. KEY POINTS: • DLBCL cases can be classified into low- and high-risk groups using PET/CT radiomics based Rad-score. • When combined with other clinical characteristics (gender and blood platelet count), Rad-score can be used to predict the outcome of the pretreatment of DLBCL cases with a certain degree of accuracy. • A prognostic nomogram was established in this study in order to aid in assessing prognostic risk and providing more accurate treatment plans for DLBCL cases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-022-09301-5.
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spelling pubmed-101215182023-04-23 Development and validation of a [(18)F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients Li, Mingshan Yao, Hongyang Zhang, Peng Zhang, Lingbo Liu, Wei Jiang, Zhiyun Li, Wei Zhao, Shu Wang, Kezheng Eur Radiol Nuclear Medicine OBJECTIVE: In this study, based on PET/CT radiomics features, we developed and validated a nomogram to predict progression-free survival (PFS) for cases with diffuse large B cell lymphoma (DLBCL) treated with immunochemotherapy. METHODS: This study retrospectively recruited 129 cases with DLBCL. Among them, PET/CT scans were conducted and baseline images were collected for radiomics features along with their clinicopathological features. Radiomics features related to recurrence were screened for survival analysis using univariate Cox regression analysis with p < 0.05. Next, a weighted Radiomics-score (Rad-score) was generated and independent risk factors were obtained from univariate and multivariate Cox regressions to build the nomogram. Furthermore, the nomogram was tested for their ability to predict PFS using time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: Blood platelet, Rad-score, and gender were included in the nomogram as independent DLBCL risk factors for PFS. We found that the training cohort areas under the curve (AUCs) were 0.79, 0.84, and 0.88, and validation cohort AUCs were 0.67, 0.83, and 0.72, respectively. Further, the DCA and calibration curves confirmed the predictive nomogram’s clinical relevance. CONCLUSION: Using Rad-score, blood platelet, and gender of the DLBCL patients, a PET/CT radiomics-based nomogram was developed to guide cases’ recurrence risk assessment prior to treatment. The developed nomogram can help provide more appropriate treatment plans to the cases. KEY POINTS: • DLBCL cases can be classified into low- and high-risk groups using PET/CT radiomics based Rad-score. • When combined with other clinical characteristics (gender and blood platelet count), Rad-score can be used to predict the outcome of the pretreatment of DLBCL cases with a certain degree of accuracy. • A prognostic nomogram was established in this study in order to aid in assessing prognostic risk and providing more accurate treatment plans for DLBCL cases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-022-09301-5. Springer Berlin Heidelberg 2022-12-22 2023 /pmc/articles/PMC10121518/ /pubmed/36547676 http://dx.doi.org/10.1007/s00330-022-09301-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Nuclear Medicine
Li, Mingshan
Yao, Hongyang
Zhang, Peng
Zhang, Lingbo
Liu, Wei
Jiang, Zhiyun
Li, Wei
Zhao, Shu
Wang, Kezheng
Development and validation of a [(18)F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients
title Development and validation of a [(18)F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients
title_full Development and validation of a [(18)F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients
title_fullStr Development and validation of a [(18)F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients
title_full_unstemmed Development and validation of a [(18)F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients
title_short Development and validation of a [(18)F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients
title_sort development and validation of a [(18)f]fdg pet/ct-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large b cell lymphoma patients
topic Nuclear Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10121518/
https://www.ncbi.nlm.nih.gov/pubmed/36547676
http://dx.doi.org/10.1007/s00330-022-09301-5
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