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Diagnostic performance of apparent diffusion coefficient parameters for glioma grading

  • Clinical Study
  • Published:
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Abstract

This study was to evaluate the diagnostic performance of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) parameters derived from diffusion tensor imaging in the differentiation between grade II and III gliomas. The records of 60 patients (30 women, 30 men; mean age, 45.4 years) suspected of having gliomas who underwent an ADC image-guided stereotactic biopsy were retrospectively reviewed. The values of FA and ADC were measured, and the sensitivity, specificity, accuracy and area under the curve (AUC) of those parameters were calculated based on the receiver operating characteristic curve analysis. A predictive diagnostic equation was also constructed and evaluated. Significant differences in minimum ADC values were found in the quantitative analysis between the grade III and II glioma groups. The sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), accuracy and AUC for identifying grade III and II gliomas at the optimum cut-off value of 0.895 × 10−3 mm2/s of minimum ADC were 81.0, 89.1, 77.3, 91.1, 86.6 and 0.87, respectively. The predictive diagnostic equation was superior to the single minimum ADC indicator with a sensitivity of 90.5%, a specificity of 84.8%, a PPV of 73.1%, an NPV of 95.1%, and an accuracy of 86.6%, respectively. The study provides evidence that minimum ADC values have a superior diagnostic performance in differentiating grade III and II gliomas, and the predictive diagnostic equation may be helpful in the differentiation.

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Abbreviations

ADC:

Apparent diffusion coefficient

AU:

Arbitrary unit

AUC:

Area under the curve

CI:

Confidence intervals

DTI:

Diffusion tensor imaging

DWI:

Diffusion-weighted imaging

FA:

Fractional anisotropy

FN:

False negative

FP:

False positive

HGG:

High-grade glioma

LGG:

Low-grade glioma

MRI:

Magnetic resonance imaging

MRS:

Magnetic resonance spectroscopy

NOS:

Not otherwise specified

NPV:

Negative predictive values

PPV:

Positive predictive values

ROC:

Receiver operating characteristic curve

SD:

Standard deviation

SEN:

Sensitivity

SPE:

Specificity

TN:

True negative

TP:

True positive

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Acknowledgements

The scientific guarantor of this publication is Xiaolei Chen, PHD. 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 by Hospital Young Doctor Funding Plan of Chinese PLA General Hospital (Grant Number 15KMM19), Hospital Clinical Sponsor Foundation Plan of Chinese PLA General Hospital (Grant Number 2016FC-TSYS-1023). One of the authors (Xinghua Xu) has significant statistical expertise. Institutional review board approval and written informed consent were obtained.

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Author notes

  1. Qun Wang, JiaShu Zhang and Xinghua Xu are first authors and they have contributed equally to this work.

Authors and Affiliations

  1. Department of Neurosurgery, Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, Beijing, 100853, China

    Qun Wang, JiaShu Zhang, Xinghua Xu, XiaoLei Chen & BaiNan Xu

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  1. Qun Wang
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  2. JiaShu Zhang
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  3. Xinghua Xu
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  4. XiaoLei Chen
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Correspondence to XiaoLei Chen or BaiNan Xu.

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Cite this article

Wang, Q., Zhang, J., Xu, X. et al. Diagnostic performance of apparent diffusion coefficient parameters for glioma grading. J Neurooncol 139, 61–68 (2018). https://doi.org/10.1007/s11060-018-2841-5

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  • DOI: https://doi.org/10.1007/s11060-018-2841-5

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