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Quantifying H&E staining results, grading and predicting IDH mutation status of gliomas using hybrid multi-dimensional MRI

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Abstract

Objective

To assess the performance of hybrid multi-dimensional magnetic resonance imaging (HM-MRI) in quantifying hematoxylin and eosin (H&E) staining results, grading and predicting isocitrate dehydrogenase (IDH) mutation status of gliomas.

Materials and methods

Included were 71 glioma patients (mean age, 50.17 ± 13.38 years; 35 men). HM-MRI images were collected at five different echo times (80–200 ms) with seven b-values (0–3000 s/mm2). A modified three-compartment model with very-slow, slow and fast diffusion components was applied to calculate HM-MRI metrics, including fractions, diffusion coefficients and T2 values of each component. Pearson correlation analysis was performed between HM-MRI derived fractions and H&E staining derived percentages. HM-MRI metrics were compared between high-grade and low-grade gliomas, and between IDH-wild and IDH-mutant gliomas. Using receiver operational characteristic (ROC) analysis, the diagnostic performance of HM-MRI in grading and genotyping was compared with mono-exponential models.

Results

HM-MRI metrics FDvery-slow and FDslow demonstrated a significant correlation with the H&E staining results (p < .05). Besides, FDvery-slow showed the highest area under ROC curve (AUC = 0.854) for grading, while Dslow showed the highest AUC (0.845) for genotyping. Furthermore, a combination of HM-MRI metrics FDvery-slow and T2Dslow improved the diagnostic performance for grading (AUC = 0.876).

Discussion

HM-MRI can aid in non-invasive diagnosis of gliomas.

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Data availability

For ethical considerations, the data supporting the study's conclusions are not publicly available; however, they are available from the corresponding author upon appropriate request. 

Abbreviations

CNS:

Central nervous system

DWI:

Diffusion weighted imaging

IDH:

Isocitrate dehydrogenase

ADC:

Apparent diffusion coefficient

LGG:

Low-grade glioma

HGG:

High-grade glioma

IDH-MUT:

IDH-mutant glioma

IDH-WILD:

IDH-wild glioma

HM-MRI:

Hybrid multi-dimensional MRI

GRE:

Gradient echo

TR:

Repetition time

TE:

Echo time

FOV:

Field of view

FSE:

Fast spin echo

FLAIR:

Fluid-attenuated inversion recovery

EES:

Extravascular extracellular space

BBB:

Brain-blood barrier

ROI:

Regions of interest

IHC:

Immune-histochemical

ROC:

Receiver operating characteristic

AUC:

Area under the receiver operating characteristic curve

LR:

Logistic regression

WHO:

World Health Organization

H&E:

Hematoxylin and eosin 

AQP4:

aquaporin-4

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Acknowledgements

This work was partly supported by the National NSFC International (regional) Cooperation and Exchange Project (Grant No. 82111530204), partly supported by Swedish Foundation for International Cooperation in Research and Higher Education (Grant No. CH2020-8775), and partly supported by Hubei Provincial Natural Science Foundation of China (Grant No. 2021CFB099).

Author information

Author notes

  1. Wenbo Sun and Dan Xu share the first authorship.

Authors and Affiliations

  1. Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, People’s Republic of China

    Wenbo Sun, Huan Li, Sirui Li & Haibo Xu

  2. Department of Nuclear Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, People’s Republic of China

    Dan Xu

  3. State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, Hubei, People’s Republic of China

    Qingjia Bao

  4. Central Research Institute, United-Imaging Healthcare, Shanghai, China

    Xiaopeng Song

  5. Department of Chemistry, Lund University, P.O.B. 124, 221 00, Lund, Sweden

    Daniel Topgaard

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Contributions

Wenbo Sun: investigation; data curation; validation; writing—original draft; visualization; formal analysis. Dan Xu: investigation; data curation; validation; writing—original draft; visualization; formal analysis. Huan Li: data curation; project administration. Sirui Li: investigation; methodology. QingJia Bao: writing—review & editing; resources. Xiaopeng Song: software; resources. Daniel Topgaard: supervision; conceptualization; funding acquisition; writing-review & editing. Haibo Xu: supervision; conceptualization; funding acquisition; writing—review & editing.

Corresponding authors

Correspondence to Daniel Topgaard or Haibo Xu.

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The authors declare no conflict of interest.

Ethical statement

All enrolled subjects provided informed consent, and the ethics committee of our hospital approved this prospective study (Ethics number 2020109). 

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Sun, W., Xu, D., Li, H. et al. Quantifying H&E staining results, grading and predicting IDH mutation status of gliomas using hybrid multi-dimensional MRI. Magn Reson Mater Phy (2024). https://doi.org/10.1007/s10334-024-01154-x

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  • DOI: https://doi.org/10.1007/s10334-024-01154-x

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