{Reference Type}: Journal Article
{Title}: Quantifying H&E staining results, grading and predicting IDH mutation status of gliomas using hybrid multi-dimensional MRI.
{Author}: Sun W;Xu D;Li H;Li S;Bao Q;Song X;Topgaard D;Xu H;
{Journal}: MAGMA
{Volume}: 0
{Issue}: 0
{Year}: 2024 Apr 5
{Factor}: 2.533
{DOI}: 10.1007/s10334-024-01154-x
{Abstract}: <B>OBJECTIVE: </B>To assess the performance of hybrid multi-dimensional magnetic resonance imaging (HM-MRI) in quantifying hematoxylin and eosin (H&E) staining results, grading and predicting isocitrate dehydrogenase (IDH) mutation status of gliomas.<BR><B>METHODS: </B>Included were 71 glioma patients (mean age, 50.17 ± 13.38 years; 35 men). HM-MRI images were collected at five different echo times (80-200 ms) with seven b-values (0-3000 s/mm2). A modified three-compartment model with very-slow, slow and fast diffusion components was applied to calculate HM-MRI metrics, including fractions, diffusion coefficients and T2 values of each component. Pearson correlation analysis was performed between HM-MRI derived fractions and H&E staining derived percentages. HM-MRI metrics were compared between high-grade and low-grade gliomas, and between IDH-wild and IDH-mutant gliomas. Using receiver operational characteristic (ROC) analysis, the diagnostic performance of HM-MRI in grading and genotyping was compared with mono-exponential models.<BR><B>RESULTS: </B>HM-MRI metrics FDvery-slow and FDslow demonstrated a significant correlation with the H&E staining results (p < .05). Besides, FDvery-slow showed the highest area under ROC curve (AUC = 0.854) for grading, while Dslow showed the highest AUC (0.845) for genotyping. Furthermore, a combination of HM-MRI metrics FDvery-slow and T2Dslow improved the diagnostic performance for grading (AUC = 0.876).<BR><B>CONCLUSIONS: </B>HM-MRI can aid in non-invasive diagnosis of gliomas.