Improved Visualization of Focal Cortical Dysplasia With Surface-Based Multiparametric Quantitative MRI

Abstract

Detection of FCD With qMRI Conclusion: Synthetically enhanced FLAIR-anatomies resulting from surface-based multiparametric qMRI-analyses have the potential to improve the visualization of FCD and, accordingly, the treatment of the respective patients.

MRI of focal cortical dysplasia

“…Surface-based (SBM) tools at least theoretically allow for a better analysis of the cortical layers itself; however, the superiority to VBM has not been shown yet [ 20 – 30 , 51 , 65 ]. Multiple stand-alone tools also processing multiple including quantitative sequences are currently being developed [ 25 , 27 , 28 , 30 , 31 , 47 , 52 , 64 , 66 ]. Which postprocessing tool will prevail is at the end also a matter of availability and ease of use [ 64 ].…”

“…Acquired signals from a single ≈ 12 min 3D sequence with variable combinations of hundreds to thousands of TRs and flip angles are compared with those in a dictionary that contains signal evolutions from a wide range of physiologically relevant combinations of T1 and T2 [49). The acquired signal from each voxel is then assigned to the entry in the dictionary that best matches the signal evolution [47]. 3D MRF was reported to show additional information in 4 of 15 patients with FCD but is not in clinical routine yet [48].…”

“…For T1and PD mapping, the variable flip angle method acquiring two spoiled gradient echo data sets at different flip angles is used [ 45 ]. A strategy for voxel-wise measurement of the T2 relaxation time is to acquire four fast spin echo datasets with different echo times (TEs), e.g., TE = 13, 67, 93, and 106 ms. Mapping of both T2* and B0 inhomogeneities (to correct T1 data) is based on the acquisition of eight multiple-echo gradient echo (GE) datasets, e.g., 10, 16, 22, 28, 34, 40, 46, and 52 ms [ 46 , 47 ]. Quantitative MRI sequences can be used to calculate synthetic magnetization-prepared rapid gradient-echo (MPRAGE) sequences which are—due to their high B 1 field homogeneity—particularly suited for postprocessing.…”

Multiparametric Quantitative MRI in Neurological Diseases

“…Nöth et al ( 36 ) developed a method for improved FCD visualization, utilizing quantitative T1 maps, and assessing the cortical extent and the smoothness of the WM-GM-junction. Furthermore, a different method for improved FCD visualization based on multiparametric qMRI data (T1, T2, and PD maps) and surface-based analysis techniques has been proposed, measuring the standard deviations of the respective parameters at the WM-cortex junction ( 37 ). The resulting information on junction smoothness and additional measures of the local cortical thickness are then used in combination to artificially enhance the signal in conventional fluid attenuated inversion recovery (FLAIR) datasets, thus highlighting regions suspicious of FCD.…”

Matching Quantitative MRI Parameters with Histological Features of Treatment-Naïve IDH Wild-Type Glioma

“…Significant deviations of parameters from normal control values reflect tissue alterations, facilitating the identification of brain pathologies [4]. For example, it has been demonstrated that synthetic data sets derived from qMRI maps may improve the visibility of brain structures such as the deep cerebellar nuclei [5] and pathologies such as brain tumors [6] or focal cortical dysplasia [7,8]. In glioblastoma, maps of quantitative T1-relaxation time differences pre-to-post intravenous application of a gadolinium-based contrast agent (GBCA) have been shown to better visualize GBCA leakage than conventional T1-weighted MRI, indicating tumor cell infiltration in and beyond the peritumoral edema [9,10].…”