4.2 Article

Diagnostic value of apparent diffusion coefficient in differentiating between high-grade gliomas and brain metastases

Journal

ACTA RADIOLOGICA
Volume 59, Issue 5, Pages 599-605

Publisher

SAGE PUBLICATIONS LTD
DOI: 10.1177/0284185117727787

Keywords

Diffusion-weighted imaging (DWI); apparent diffusion coefficient (ADC); high-grade glioma; brain metastasis; peritumoral edema

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Background: High-grade gliomas (HGGs) and brain metastases (BMs) can display similar imaging characteristics on conventional MRI. In HGGs, the peritumoral edema may be infiltrated by the malignant cells, which was not observed in BMs. Purpose: To determine whether the apparent diffusion coefficient values could differentiate HGGs from BMs. Material and Methods: Fifty-seven patients underwent conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) before treatment. The minimum and mean ADC in the enhancing tumor (ADC(min), ADC(mean)) and the minimum ADC in the peritumoral region (ADC(edema)) were measured from ADC maps. To determine whether there was a statistical difference between groups, ADC values were compared. A receiver operating characteristic (ROC) curve analysis was used to determine the cutoff ADC value for distinguishing between HGGs and BMs. Results: The mean ADC(min) values in the intratumoral regions of HGGs were significantly higher than those in BMs. No differences were observed between groups regarding ADC(mean) values. The mean ADC(min) values in the peritumoral edema of HGGs were significantly lower than those in BMs. According to ROC curve analysis, a cutoff value of 1.332x10(-3) mm(2)/s for the ADC(edema) generated the best combination of sensitivity (95%) and specificity (84%) for distinguishing between HGGs and BMs. The same value showed a sensitivity of 95.6% and a specificity of 100% for distinguishing between GBMs and BMs. Conclusion: ADC values from DWI were found to distinguish between HGGs and solitary BMs. The peritumoral ADC values are better than the intratumoral ADC values in predicting the tumor type.

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