Application of Distributed Parameter Model to Assessment of Glioma IDH Mutation Status by Dynamic Contrast-Enhanced Magnetic Resonance Imaging
Previous studies using contrast-enhanced imaging for glioma isocitrate dehydrogenase (IDH) mutation assessment showed promising yet inconsistent results, and this study attempts to explore this problem by using an advanced tracer kinetic model, the distributed parameter model (DP). Fifty-five patien...
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doaj-4cd66e238b7b466fbda4d56bd36840992020-12-07T09:08:24ZengHindawi-WileyContrast Media & Molecular Imaging1555-43091555-43172020-01-01202010.1155/2020/88430848843084Application of Distributed Parameter Model to Assessment of Glioma IDH Mutation Status by Dynamic Contrast-Enhanced Magnetic Resonance ImagingZongfang Li0Wei Zhao1Bo He2Tong San Koh3Yanxi Li4Yizhen Zeng5Zhuo Zhang6Jingzhong Zhang7Zujun Hou8Department of Radiology, The First Affiliated Hospital, Kunming Medical University, Kunming 650032, ChinaDepartment of Radiology, The First Affiliated Hospital, Kunming Medical University, Kunming 650032, ChinaDepartment of Radiology, The First Affiliated Hospital, Kunming Medical University, Kunming 650032, ChinaDepartment of Oncologic Imaging, National Cancer Center, 169610, SingaporeDepartment of Anatomical & Cellular Pathology, The First Affiliated Hospital, Kunming Medical University, Kunming 650032, ChinaDepartment of Radiology, The First Affiliated Hospital, Kunming Medical University, Kunming 650032, ChinaInstitute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis, 138632, SingaporeSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaPrevious studies using contrast-enhanced imaging for glioma isocitrate dehydrogenase (IDH) mutation assessment showed promising yet inconsistent results, and this study attempts to explore this problem by using an advanced tracer kinetic model, the distributed parameter model (DP). Fifty-five patients with glioma examined using dynamic contrast-enhanced imaging sequence at a 3.0 T scanner were retrospectively reviewed. The imaging data were processed using DP, yielding the following parameters: blood flow F, permeability-surface area product PS, fractional volume of interstitial space Ve, fractional volume of intravascular space Vp, and extraction ratio E. The results were compared with the Tofts model. The Wilcoxon test and boxplot were utilized for assessment of differences of model parameters between IDH-mutant and IDH-wildtype gliomas. Spearman correlation r was employed to investigate the relationship between DP and Tofts parameters. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis and quantified using the area under the ROC curve (AUC). Results showed that IDH-mutant gliomas were significantly lower in F (P = 0.018), PS (P<0.001), Vp (P<0.001), E (P<0.001), and Ve (P = 0.002) than IDH-wildtype gliomas. In differentiating IDH-mutant and IDH-wildtype gliomas, Vp had the best performance (AUC = 0.92), and the AUCs of PS and E were 0.82 and 0.80, respectively. In comparison, Tofts parameters were lower in Ktrans (P = 0.013) and Ve (P<0.001) for IDH-mutant gliomas. No significant difference was observed in Kep (P = 0.525). The AUCs of Ktrans, Ve, and Kep were 0.69, 0.79, and 0.55, respectively. Tofts-derived Ve showed a strong correlation with DP-derived Ve (r > 0.9, P<0.001). Ktrans showed a weak correlation with F (r < 0.3, P > 0.16) and a very weak correlation with PS (r < 0.06, P > 0.8), both of which were not statistically significant. The findings by DP revealed a tissue environment with lower vascularity, lower vessel permeability, and lower blood flow in IDH-mutant than in IDH-wildtype gliomas, being hostile to cellular differentiation of oncogenic effects in IDH-mutated gliomas, which might help to explain the better outcomes in IDH-mutated glioma patients than in glioma patients of IDH-wildtype. The advantage of DP over Tofts in glioma DCE data analysis was demonstrated in terms of clearer elucidation of tissue microenvironment and better performance in IDH mutation assessment.http://dx.doi.org/10.1155/2020/8843084 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zongfang Li Wei Zhao Bo He Tong San Koh Yanxi Li Yizhen Zeng Zhuo Zhang Jingzhong Zhang Zujun Hou |
spellingShingle |
Zongfang Li Wei Zhao Bo He Tong San Koh Yanxi Li Yizhen Zeng Zhuo Zhang Jingzhong Zhang Zujun Hou Application of Distributed Parameter Model to Assessment of Glioma IDH Mutation Status by Dynamic Contrast-Enhanced Magnetic Resonance Imaging Contrast Media & Molecular Imaging |
author_facet |
Zongfang Li Wei Zhao Bo He Tong San Koh Yanxi Li Yizhen Zeng Zhuo Zhang Jingzhong Zhang Zujun Hou |
author_sort |
Zongfang Li |
title |
Application of Distributed Parameter Model to Assessment of Glioma IDH Mutation Status by Dynamic Contrast-Enhanced Magnetic Resonance Imaging |
title_short |
Application of Distributed Parameter Model to Assessment of Glioma IDH Mutation Status by Dynamic Contrast-Enhanced Magnetic Resonance Imaging |
title_full |
Application of Distributed Parameter Model to Assessment of Glioma IDH Mutation Status by Dynamic Contrast-Enhanced Magnetic Resonance Imaging |
title_fullStr |
Application of Distributed Parameter Model to Assessment of Glioma IDH Mutation Status by Dynamic Contrast-Enhanced Magnetic Resonance Imaging |
title_full_unstemmed |
Application of Distributed Parameter Model to Assessment of Glioma IDH Mutation Status by Dynamic Contrast-Enhanced Magnetic Resonance Imaging |
title_sort |
application of distributed parameter model to assessment of glioma idh mutation status by dynamic contrast-enhanced magnetic resonance imaging |
publisher |
Hindawi-Wiley |
series |
Contrast Media & Molecular Imaging |
issn |
1555-4309 1555-4317 |
publishDate |
2020-01-01 |
description |
Previous studies using contrast-enhanced imaging for glioma isocitrate dehydrogenase (IDH) mutation assessment showed promising yet inconsistent results, and this study attempts to explore this problem by using an advanced tracer kinetic model, the distributed parameter model (DP). Fifty-five patients with glioma examined using dynamic contrast-enhanced imaging sequence at a 3.0 T scanner were retrospectively reviewed. The imaging data were processed using DP, yielding the following parameters: blood flow F, permeability-surface area product PS, fractional volume of interstitial space Ve, fractional volume of intravascular space Vp, and extraction ratio E. The results were compared with the Tofts model. The Wilcoxon test and boxplot were utilized for assessment of differences of model parameters between IDH-mutant and IDH-wildtype gliomas. Spearman correlation r was employed to investigate the relationship between DP and Tofts parameters. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis and quantified using the area under the ROC curve (AUC). Results showed that IDH-mutant gliomas were significantly lower in F (P = 0.018), PS (P<0.001), Vp (P<0.001), E (P<0.001), and Ve (P = 0.002) than IDH-wildtype gliomas. In differentiating IDH-mutant and IDH-wildtype gliomas, Vp had the best performance (AUC = 0.92), and the AUCs of PS and E were 0.82 and 0.80, respectively. In comparison, Tofts parameters were lower in Ktrans (P = 0.013) and Ve (P<0.001) for IDH-mutant gliomas. No significant difference was observed in Kep (P = 0.525). The AUCs of Ktrans, Ve, and Kep were 0.69, 0.79, and 0.55, respectively. Tofts-derived Ve showed a strong correlation with DP-derived Ve (r > 0.9, P<0.001). Ktrans showed a weak correlation with F (r < 0.3, P > 0.16) and a very weak correlation with PS (r < 0.06, P > 0.8), both of which were not statistically significant. The findings by DP revealed a tissue environment with lower vascularity, lower vessel permeability, and lower blood flow in IDH-mutant than in IDH-wildtype gliomas, being hostile to cellular differentiation of oncogenic effects in IDH-mutated gliomas, which might help to explain the better outcomes in IDH-mutated glioma patients than in glioma patients of IDH-wildtype. The advantage of DP over Tofts in glioma DCE data analysis was demonstrated in terms of clearer elucidation of tissue microenvironment and better performance in IDH mutation assessment. |
url |
http://dx.doi.org/10.1155/2020/8843084 |
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