Abstract
Purpose
An accurate assessment of the World Health Organization grade is vital for patients with pediatric gliomas to direct treatment planning. We aim to evaluate the diagnostic performance of whole-tumor histogram analysis of diffusion-weighted imaging (DWI) and dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) for differentiating pediatric high-grade gliomas from pediatric low-grade gliomas.
Methods
Sixty-eight pediatric patients (mean age, 10.47 ± 4.37 years; 42 boys) with histologically confirmed gliomas underwent preoperative MR examination. The conventional MRI features and whole-tumor histogram features extracted from apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps were analyzed, respectively. Receiver operating characteristic curves and the binary logistic regression analysis were performed to determine the diagnostic performance of parameters.
Results
For conventional MRI features, location, hemorrhage and tumor margin showed significant difference between pediatric high- and low-grade gliomas (all, P < .05). For advanced MRI parameters, ten histogram features of ADC and CBV showed significant differences between pediatric high- and low-grade gliomas (all, P < .05). The diagnostic performance of the combination of DSC-PWI and DWI (AUC = 0.976, sensitivity = 100%, NPV = 100%) is superior to conventional MRI or DWI model, respectively (AUCcMRI = 0.700, AUCDWI = 0.830; both, P < .05).
Conclusion
The whole-tumor histogram analysis of DWI and DSC-PWI is a promising method for grading pediatric gliomas.
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Data availability
The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Funding
This study was supported by the Leading Project of the Department of Science and Technology of Fujian Province (grant number 2020Y0025), the National Natural Science Foundation of China (grant number 82071869), and the Startup Fund for Scientific Research, Fujian Medical University (grant number 2018QH1048), the Young and Middle-aged Key Personnel Training Project of Fujian Provincial Health Commission (grant number 2021GGA025), and the Young and Middle-aged Key Personnel Training Project of Fujian Provincial Health Commission (grant number 2020GGA049s).
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Su, Y., Kang, J., Lin, X. et al. Whole-tumor histogram analysis of diffusion and perfusion metrics for noninvasive pediatric glioma grading. Neuroradiology 65, 1063–1071 (2023). https://doi.org/10.1007/s00234-023-03145-6
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DOI: https://doi.org/10.1007/s00234-023-03145-6