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The added value of relative amide proton transfer to advanced multiparametric MR imaging for brain glioma characterization
The added value of relative amide proton transfer to advanced multiparametric MR imaging for brain glioma characterization
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The added value of relative amide proton transfer to advanced multiparametric MR imaging for brain glioma characterization
The added value of relative amide proton transfer to advanced multiparametric MR imaging for brain glioma characterization

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The added value of relative amide proton transfer to advanced multiparametric MR imaging for brain glioma characterization
The added value of relative amide proton transfer to advanced multiparametric MR imaging for brain glioma characterization
Journal Article

The added value of relative amide proton transfer to advanced multiparametric MR imaging for brain glioma characterization

2023
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Overview
Background Differentiation between the grades of brain gliomas is a crucial step in the management of patients. The gold standard technique for grading is biopsy but MR imaging may play a more substantial role as a non-invasive method by using promising molecular sequences. Our purpose was to assess the added value of the relative amide proton transfer signal [rAPT] to advanced multiparametric MRI protocol. Methods We enrolled a pathologically confirmed 102 patients with low-grade glioma [n = 38] and high-grade glioma [n = 64] who underwent advanced multiparametric MRI protocol on the same scanner. The protocol included anatomic, diffusion, MRS, and perfusion sequences. The newly added sequence was Amide proton transfer. The rAPT values of all lesions were investigated by two neuroradiologists to assess the inter-rater agreement of using interclass correlation coefficient [ICC]. HGGs demonstrated significantly higher mean values of relative cerebral blood volume (rCBV), choline to creatine ratio (Cho/cr), and rAPT with lower Apparent diffusion coefficient (ADC) values compared to LGGs. ROC analyses revealed medium to high diagnostic performance with an AUC of 0.941 for rAPT, 0.907 for mean ADC, and 0.906 for rCBV. Discriminant function analysis of two models, the first one included mean ADC, rCBV, and Cho/Cr, while in the second Model, we added rAPT to them. Model two demonstrated higher accuracy and a significant difference in the AUC after adding the rAPT. The inter-rater agreement was reasonable (ICC 0.61). Conclusions rAPT adds significant value to multiparametric MRI for distinguishing LGG from HGG.