The diagnostic value of high-frequency power-based diffusion-weighted imaging in prediction of neuroepithelial tumour grading
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To retrospectively evaluate the diagnostic value of high-frequency power (HFP) compared with the minimum apparent diffusion coefficient (MinADC) in the prediction of neuroepithelial tumour grading.
Diffusion-weighted imaging (DWI) data were acquired on 115 patients by a 3.0-T MRI system, which included b0 images and b1000 images over the whole brain in each patient. The HFP values and MinADC values were calculated by an in-house script written on the MATLAB platform.
There was a significant difference among each group excluding grade I (G1) vs. grade II (G2) (P = 0.309) for HFP and among each group for MinADC. ROC analysis showed a higher discriminative accuracy between low-grade glioma (LGG) and high-grade glioma (HGG) for HFP with area under the curve (AUC) value 1 compared with that for MinADC with AUC 0.83 ± 0.04 and also demonstrated a higher discriminative ability among the G1-grade IV (G4) group for HFP compared with that for MinADC except G1 vs. G2.
HFP could provide a simple and effective optimal tool for the prediction of neuroepithelial tumour grading based on diffusion-weighted images in routine clinical practice.
• HFP shows positive correlation with neuroepithelial tumour grading.
• HFP presents a good diagnostic efficacy for LGG and HGG.
• HFP is helpful in the selection of brain tumour boundary.
KeywordsDiffusion-weighted imaging High-frequency power Minimum apparent diffusion coefficient Neuroepithelial tumour grading Magnetic resonance imaging
Area under the curve
Minimum apparent diffusion coefficient
Receiver-operating characteristics curve
Compliance with ethical standards
The scientific guarantor of this publication is Lin Ma.
Conflict of interest
The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.
This study has received funding from a Special Financial Grant from the China Postdoctoral Science Foundation (2014 T70960), the Foundation for Medical and Health Science and Technology Innovation Project of Sanya (2016YW37), National Natural Science Foundation of China (91520202) and Youth Innovation Promotion Association CAS.
Statistics and biometry
One of the authors has significant statistical expertise.
Written informed consent was not required for this study because this is a retrospective study, and MRI sequences and diffusion-weighted imaging are routinely performed in clinical practice at our hospital.
Institutional Review Board approval was obtained.
• diagnostic or prognostic study
• performed at one institution
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