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Vascular habitat analysis based on dynamic susceptibility contrast perfusion MRI predicts IDH mutation status and prognosis in high-grade gliomas

  • Magnetic Resonance
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

The current study aimed to evaluate the clinical practice for hemodynamic tissue signature (HTS) method in IDH genotype prediction in three groups derived from high-grade gliomas.

Methods

Preoperative MRI examinations of 44 patients with known grade and IDH genotype were assigned into three study groups: glioblastoma multiforme, grade III, and high-grade gliomas. Perfusion parameters were analyzed and were used to automatically draw the four reproducible habitats (high-angiogenic enhancing tumor habitats, low-angiogenic enhancing tumor habitats, infiltrated peripheral edema habitats, vasogenic peripheral edema habitats) related to vascular heterogeneity. These four habitats were then compared between inter-patient with IDH mutation and their wild-type counterparts at these three groups, respectively. The discriminating potential for HTS in assessing IDH mutation status prediction was assessed by ROC curves.

Results

Compared with IDH wild type, IDH mutation had significantly decreased relative cerebral blood volume (rCBV) at the high-angiogenic enhancing tumor habitats and low-angiogenic enhancing tumor habitats. ROC analysis revealed that the rCBVs in habitats had great ability to discriminate IDH mutation from their wild type in all groups. In addition, the Kaplan-Meier survival analysis yielded significant differences for the survival times observed from the populations dichotomized by low (< 4.31) and high (> 4.31) rCBV in the low-angiogenic enhancing tumor habitat.

Conclusions

The HTS method has been proven to have high prediction capabilities for IDH mutation status in high-grade glioma patients, providing a set of quantifiable habitats associated with tumor vascular heterogeneity.

Key Points

• The HTS method has a high accuracy for molecular stratification prediction for all subsets of HGG.

• The HTS method can give IDH mutation–related hemodynamic information of tumor-infiltrated and vasogenic edema.

• IDH-relevant rCBV difference in habitats will be a great prognosis factor in HGG.

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Abbreviations

DSC-PWI:

Dynamic susceptibility contrast perfusion-weighted imaging

FLAIR:

Fluid attenuation inversion recovery

FLASH:

Fast low-angle shot

FOV:

Field of view

GBCA:

Gadolinium-based contrast agent

GBM:

Glioblastoma multiforme

HAT:

High-angiogenic enhancing tumor habitats

HGG:

High-grade glioma

HTS:

Hemodynamic tissue signatures

IDH:

Isocitrate dehydrogenase

IPE:

Infiltrated peripheral edema habitats

LAT:

Low-angiogenic enhancing tumor habitats

LGG:

Low-grade glioma

NPV:

Negative predictive value

PPV:

Positive predictive value

RM-ANOVA:

Repeated measure analysis of variance

rCBF:

Relative cerebral blood flow

rCBV:

Relative cerebral blood volume

ROC:

Receiver operating characteristic

ROI:

Regions of interest

SPM:

Statistical parametric mapping

SPSS:

Statistical Package for the Social Sciences

SVM:

Support vector machine

T1-CE:

T1-weighted contrast-enhanced

VASRI:

Visually AcceSAble Rembrandt Images

VPE:

Vasogenic peripheral edema habitats

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Funding

This work was supported by the National Key R&D Program of China (2018YFC0115004) and grants from the Natural Science Foundation of China (81871421 and 81571660).

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Author notes

  1. Hao Wu and Haipeng Tong contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, Army Medical Center of PLA, Army Medical University, 10# Changjiangzhilu, Chongqing, 400042, People’s Republic of China

    Hao Wu, Haipeng Tong, Xuesong Du, Hong Guo, Yulong Zhang, Heng Liu, Sunan Wang, Jingqin Fang & Weiguo Zhang

  2. Chongqing Clinical Research Centre of Imaging and Nuclear Medicine, Chongqing, 400042, China

    Hao Wu, Haipeng Tong, Xuesong Du, Hong Guo, Yulong Zhang, Heng Liu, Sunan Wang & Weiguo Zhang

  3. Department of Pathology, Army Medical Center of PLA, Army Medical University, 10# Changjiangzhilu, Chongqing, 400042, People’s Republic of China

    Qiang Ma

  4. MR Collaboration, Siemens Healthineers Ltd., Shanghai, China

    Xiaoyue Zhou

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  1. Hao Wu
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Corresponding authors

Correspondence to Jingqin Fang or Weiguo Zhang.

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Guarantor

The scientific guarantor of this publication is W.G. Z., Ph.D, M.D., the Chief Director of Radiology Department of Army Medical Center.

Conflict of interest

One of the authors of this manuscript (Xiaoyue Zhou) is an employee of Siemens Healthineers. The remaining authors declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors (H.W.) has significant statistical expertise.

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Written informed consent was obtained from all subjects (patients) in this study.

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Institutional Review Board approval was obtained.

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• performed at one institution

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Wu, H., Tong, H., Du, X. et al. Vascular habitat analysis based on dynamic susceptibility contrast perfusion MRI predicts IDH mutation status and prognosis in high-grade gliomas. Eur Radiol 30, 3254–3265 (2020). https://doi.org/10.1007/s00330-020-06702-2

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