Fast fluid-attenuated T2 mapping via multiple overlapping-echo detachment acquisition enhances preoperative histological classification of meningiomas - Qizhi Yang; Yijie Yang; Lu Wang; Xiao Wang; Linyu Fan; Weijian Wang; Qinqin Yang; Jianhui Zhong; Jingliang Cheng; Yong Zhang; Jianfeng Bao; Congbo Cai; et al. (NeuroImage)
Fluid-attenuated inversion recovery (FLAIR) is indispensable in MRI-based head-and-neck assessments, but its quantitative counterpart remains clinically absent due to the influence of cerebrospinal fluid (CSF) dynamics and the lengthy acquisition time spent on a series of weighting-increasing images. This work implements and validates fast fluid-attenuated T2 (FLA-T2) mapping via inversion-recovery-prepared multiple overlapping-echo detachment imaging (IR-MOLED). The clinical value is prospectively investigated with a cohort of 54 meningioma patients (mean age: 56 years ± 11 [standard deviation]; 19 men). Fluid-attenuated proton density mapping was simultaneously fulfilled and therefore intrinsically co-registered, revealing notable benefits in identifying CSF inflow. In quantifying parenchymal T2, IR-MOLED yielded a mean absolute error of 1.22 ms referring to spin-echo, and in fluid suppression, IR-MOLED exhibited a high radiographic consistence with orthodox FLAIR imaging. Using first-level histogram analysis, results of meningioma investigation first discovered: (1) in grading meningiomas, FLA-T2 mapping (AUC = 0.814) outshined FLAIR imaging (AUC = 0.685), contrast-enhanced T1-weighted imaging (insignificant), and T2 mapping (insignificant); and (2) in typing meningiomas, FLA-T2 classified transitional meningiomas from meningothelial or/and fibrous meningiomas, complementing the predictive ability of T2 mapping. In conclusion, with excluded parametric contribution from free water and standardized voxel value scales, FLA-T2 mapping permits a more precise description of brain parenchyma in both structural morphology and relaxation variables than T2 mapping and is fully superior to FLAIR imaging in preoperatively predicting the histopathologic heterogeneity of meningiomas.