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Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy

BACKGROUND: To assess the survival predictability of perfusion magnetic resonance imaging (MRI) by the normalized cerebral blood volume (nCBV) prior to particle beam radiotherapy (PBRT) in high-grade glioma (HGG) patients underwent particle therapy. METHODS: The study retrieved dynamic susceptibilit...

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Autores principales: Qiu, Xianxin, Gao, Jing, Yang, Jing, Hu, Jiyi, Hu, Weixu, Zhang, Xiaoyong, Lu, Jiade J., Kong, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9761124/
https://www.ncbi.nlm.nih.gov/pubmed/36544672
http://dx.doi.org/10.21037/atm-20-1646
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author Qiu, Xianxin
Gao, Jing
Yang, Jing
Hu, Jiyi
Hu, Weixu
Zhang, Xiaoyong
Lu, Jiade J.
Kong, Lin
author_facet Qiu, Xianxin
Gao, Jing
Yang, Jing
Hu, Jiyi
Hu, Weixu
Zhang, Xiaoyong
Lu, Jiade J.
Kong, Lin
author_sort Qiu, Xianxin
collection PubMed
description BACKGROUND: To assess the survival predictability of perfusion magnetic resonance imaging (MRI) by the normalized cerebral blood volume (nCBV) prior to particle beam radiotherapy (PBRT) in high-grade glioma (HGG) patients underwent particle therapy. METHODS: The study retrieved dynamic susceptibility contrast MRI acquired prior to PBRT between 6/2015 and 3/2019 in 45 patients with HGG. Maximum nCBV (nCBVmax) within or adjacent to surgical/tumor bed was measured using ‘hot-spot’ method. The predictive values of nCBVmax for progression-free survival (PFS) and overall survival (OS) were assessed in univariate Kaplan-Meier curve and multivariate Cox proportional hazards (CPH) models. Nomograms based on CPH results were constructed to individualize the predicted probability of OS and PFS. RESULTS: The Kaplan-Meier curves and all CPH models based on nCBVmax as continuous variable (nCBVmax-C), group by cut-off derived from median value and Youden-index method showed that nCBVmax prior to radiotherapy was a strong predictor for both PFS and OS in HGG patients who underwent PBRT. Nomograms built on CPH models showed similar excellent performance in both discrimination and calibration. CONCLUSIONS: Perfusion imaging prior to PBRT is a strong predictor of survival in HGG. Novel perfusion MR-based nomogram with prospective validation could potentially be formally used in future clinical practice to individualize survival probability.
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spelling pubmed-97611242022-12-20 Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy Qiu, Xianxin Gao, Jing Yang, Jing Hu, Jiyi Hu, Weixu Zhang, Xiaoyong Lu, Jiade J. Kong, Lin Ann Transl Med Original Article BACKGROUND: To assess the survival predictability of perfusion magnetic resonance imaging (MRI) by the normalized cerebral blood volume (nCBV) prior to particle beam radiotherapy (PBRT) in high-grade glioma (HGG) patients underwent particle therapy. METHODS: The study retrieved dynamic susceptibility contrast MRI acquired prior to PBRT between 6/2015 and 3/2019 in 45 patients with HGG. Maximum nCBV (nCBVmax) within or adjacent to surgical/tumor bed was measured using ‘hot-spot’ method. The predictive values of nCBVmax for progression-free survival (PFS) and overall survival (OS) were assessed in univariate Kaplan-Meier curve and multivariate Cox proportional hazards (CPH) models. Nomograms based on CPH results were constructed to individualize the predicted probability of OS and PFS. RESULTS: The Kaplan-Meier curves and all CPH models based on nCBVmax as continuous variable (nCBVmax-C), group by cut-off derived from median value and Youden-index method showed that nCBVmax prior to radiotherapy was a strong predictor for both PFS and OS in HGG patients who underwent PBRT. Nomograms built on CPH models showed similar excellent performance in both discrimination and calibration. CONCLUSIONS: Perfusion imaging prior to PBRT is a strong predictor of survival in HGG. Novel perfusion MR-based nomogram with prospective validation could potentially be formally used in future clinical practice to individualize survival probability. AME Publishing Company 2022-11 /pmc/articles/PMC9761124/ /pubmed/36544672 http://dx.doi.org/10.21037/atm-20-1646 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Qiu, Xianxin
Gao, Jing
Yang, Jing
Hu, Jiyi
Hu, Weixu
Zhang, Xiaoyong
Lu, Jiade J.
Kong, Lin
Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy
title Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy
title_full Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy
title_fullStr Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy
title_full_unstemmed Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy
title_short Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy
title_sort perfusion mr prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9761124/
https://www.ncbi.nlm.nih.gov/pubmed/36544672
http://dx.doi.org/10.21037/atm-20-1646
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