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Study of Diffusion Weighted Imaging Derived Diffusion Parameters as Biomarkers for the Microenvironment in Gliomas

OBJECTIVES: To explore the efficacy of diffusion weighted imaging (DWI)-derived metrics under different models as surrogate indicators for molecular biomarkers and tumor microenvironment in gliomas. METHODS: A retrospective study was performed for 41 patients with gliomas. The standard apparent diff...

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Autores principales: Bai, Yan, Liu, Taiyuan, Chen, Lijuan, Gao, Haiyan, Wei, Wei, Zhang, Ge, Wang, Lifu, Kong, Lingfei, Liu, Siyun, Liu, Huan, Roberts, Neil, Wang, Meiyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8546342/
https://www.ncbi.nlm.nih.gov/pubmed/34712604
http://dx.doi.org/10.3389/fonc.2021.672265
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author Bai, Yan
Liu, Taiyuan
Chen, Lijuan
Gao, Haiyan
Wei, Wei
Zhang, Ge
Wang, Lifu
Kong, Lingfei
Liu, Siyun
Liu, Huan
Roberts, Neil
Wang, Meiyun
author_facet Bai, Yan
Liu, Taiyuan
Chen, Lijuan
Gao, Haiyan
Wei, Wei
Zhang, Ge
Wang, Lifu
Kong, Lingfei
Liu, Siyun
Liu, Huan
Roberts, Neil
Wang, Meiyun
author_sort Bai, Yan
collection PubMed
description OBJECTIVES: To explore the efficacy of diffusion weighted imaging (DWI)-derived metrics under different models as surrogate indicators for molecular biomarkers and tumor microenvironment in gliomas. METHODS: A retrospective study was performed for 41 patients with gliomas. The standard apparent diffusion coefficient (ADC(st)) and ADC under ultra-high b values (ADC(uh)) (b values: 2500 to 5000 s/mm(2)) were calculated based on monoexponential model. The fraction of fast diffusion (f), pseudo ADC (ADC(fast)) and true ADC (ADC(slow)) were calculated by bi-exponential model (b values: 0 to 2000 s/mm(2)). The apparent diffusional kurtosis (K(app)) was derived from the simplified diffusion kurtosis imaging (DKI) model (b values: 200 to 3000 s/mm(2)). Potential correlations between DWI parameters and immunohistological indices (i.e. Aquaporin (AQP)1, AQP4, AQP9 and Ki-67) were investigated and DWI parameters were compared between high- and low-grade gliomas, and between tumor center and peritumor. Receiver operator characteristic (ROC) curve and area under the curve (AUC) were calculated to determine the performance of independent or combined DWI parameters in grading gliomas. RESULTS: The ADC(slow) and ADC(uh) at tumor center showed a stronger correlation with Ki-67 than other DWI metrics. The ADC(st), ADC(slow) and ADC(uh) at tumor center presented correlations with AQP1 and AQP4 while AQP9 did not correlate with any DWI metric. K(app) showed a correlation with Ki-67 while no significant correlation with AQPs. ADC(st) (p < 0.001) and ADC(slow) (p = 0.001) were significantly lower while the ADC(uh) (p = 0.006) and K(app) (p = 0.005) were significantly higher in the high-grade than in the low-grade gliomas. ADC(st), f, ADC(fast), ADC(slow), ADC(uh), K(app) at the tumor center had significant differences with those in peritumor when the gliomas grade became high (p < 0.05). Involving ADC(uh) and K(app) simultaneously into an independent ADC(st) model (AUC = 0.833) could further improve the grading performance (ADC(st)+ADC(uh)+K(app): AUC = 0.923). CONCLUSION: Different DWI metrics fitted within different b-value ranges (low to ultra-high b values) have different efficacies as a surrogate indicator for molecular expression or microstructural complexity in gliomas. Further studies are needed to better explain the biological meanings of these DWI parameters in gliomas.
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spelling pubmed-85463422021-10-27 Study of Diffusion Weighted Imaging Derived Diffusion Parameters as Biomarkers for the Microenvironment in Gliomas Bai, Yan Liu, Taiyuan Chen, Lijuan Gao, Haiyan Wei, Wei Zhang, Ge Wang, Lifu Kong, Lingfei Liu, Siyun Liu, Huan Roberts, Neil Wang, Meiyun Front Oncol Oncology OBJECTIVES: To explore the efficacy of diffusion weighted imaging (DWI)-derived metrics under different models as surrogate indicators for molecular biomarkers and tumor microenvironment in gliomas. METHODS: A retrospective study was performed for 41 patients with gliomas. The standard apparent diffusion coefficient (ADC(st)) and ADC under ultra-high b values (ADC(uh)) (b values: 2500 to 5000 s/mm(2)) were calculated based on monoexponential model. The fraction of fast diffusion (f), pseudo ADC (ADC(fast)) and true ADC (ADC(slow)) were calculated by bi-exponential model (b values: 0 to 2000 s/mm(2)). The apparent diffusional kurtosis (K(app)) was derived from the simplified diffusion kurtosis imaging (DKI) model (b values: 200 to 3000 s/mm(2)). Potential correlations between DWI parameters and immunohistological indices (i.e. Aquaporin (AQP)1, AQP4, AQP9 and Ki-67) were investigated and DWI parameters were compared between high- and low-grade gliomas, and between tumor center and peritumor. Receiver operator characteristic (ROC) curve and area under the curve (AUC) were calculated to determine the performance of independent or combined DWI parameters in grading gliomas. RESULTS: The ADC(slow) and ADC(uh) at tumor center showed a stronger correlation with Ki-67 than other DWI metrics. The ADC(st), ADC(slow) and ADC(uh) at tumor center presented correlations with AQP1 and AQP4 while AQP9 did not correlate with any DWI metric. K(app) showed a correlation with Ki-67 while no significant correlation with AQPs. ADC(st) (p < 0.001) and ADC(slow) (p = 0.001) were significantly lower while the ADC(uh) (p = 0.006) and K(app) (p = 0.005) were significantly higher in the high-grade than in the low-grade gliomas. ADC(st), f, ADC(fast), ADC(slow), ADC(uh), K(app) at the tumor center had significant differences with those in peritumor when the gliomas grade became high (p < 0.05). Involving ADC(uh) and K(app) simultaneously into an independent ADC(st) model (AUC = 0.833) could further improve the grading performance (ADC(st)+ADC(uh)+K(app): AUC = 0.923). CONCLUSION: Different DWI metrics fitted within different b-value ranges (low to ultra-high b values) have different efficacies as a surrogate indicator for molecular expression or microstructural complexity in gliomas. Further studies are needed to better explain the biological meanings of these DWI parameters in gliomas. Frontiers Media S.A. 2021-10-12 /pmc/articles/PMC8546342/ /pubmed/34712604 http://dx.doi.org/10.3389/fonc.2021.672265 Text en Copyright © 2021 Bai, Liu, Chen, Gao, Wei, Zhang, Wang, Kong, Liu, Liu, Roberts and Wang 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 Oncology
Bai, Yan
Liu, Taiyuan
Chen, Lijuan
Gao, Haiyan
Wei, Wei
Zhang, Ge
Wang, Lifu
Kong, Lingfei
Liu, Siyun
Liu, Huan
Roberts, Neil
Wang, Meiyun
Study of Diffusion Weighted Imaging Derived Diffusion Parameters as Biomarkers for the Microenvironment in Gliomas
title Study of Diffusion Weighted Imaging Derived Diffusion Parameters as Biomarkers for the Microenvironment in Gliomas
title_full Study of Diffusion Weighted Imaging Derived Diffusion Parameters as Biomarkers for the Microenvironment in Gliomas
title_fullStr Study of Diffusion Weighted Imaging Derived Diffusion Parameters as Biomarkers for the Microenvironment in Gliomas
title_full_unstemmed Study of Diffusion Weighted Imaging Derived Diffusion Parameters as Biomarkers for the Microenvironment in Gliomas
title_short Study of Diffusion Weighted Imaging Derived Diffusion Parameters as Biomarkers for the Microenvironment in Gliomas
title_sort study of diffusion weighted imaging derived diffusion parameters as biomarkers for the microenvironment in gliomas
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8546342/
https://www.ncbi.nlm.nih.gov/pubmed/34712604
http://dx.doi.org/10.3389/fonc.2021.672265
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