Rapid and efficient transmission of electric signals among neurons of vertebrates is ensured by myelin‐insulating sheaths surrounding axons. Human cognition, sensation, and motor functions rely on the integrity of these layers, and demyelinating diseases often entail serious cognitive and physical impairments. Magnetic resonance imaging radically transformed the way these disorders are monitored, offering an irreplaceable tool to noninvasively examine the brain structure. Several advanced techniques based on MRI have been developed to provide myelin‐specific contrasts and a quantitative estimation of myelin density in vivo. Here, the vast offer of acquisition strategies developed to date for this task is reviewed. Advantages and pitfalls of the different approaches are compared and discussed.

Purpose To exploit the improved comparability and hardware independency of quantitative MRI, databases of MR physical parameters in healthy tissue are required, to which tissue properties of patients can be compared. In this work, normative values for longitudinal and transverse relaxation times in the brain were established and tested in single‐subject comparisons for detection of abnormal relaxation times. Methods Relaxometry maps of the brain were acquired from 52 healthy volunteers. After spatially normalizing the volumes into a common space, T1 and T2 inter‐subject variability within the healthy cohort was modeled voxel‐wise. A method for a single‐subject comparison against the atlases was developed by computing z‐scores with respect to the established healthy norms. The comparison was applied to two multiple sclerosis and one clinically isolated syndrome cases for a proof of concept. Results The established atlases exhibit a low variation in white matter structures (median RMSE of models equal to 32 ms for T1 and 4 ms for T2), indicating that relaxation times are in a narrow range for normal tissues. The proposed method for single‐subject comparison detected relaxation time deviations from healthy norms in the example patient data sets. Relaxation times were found to be increased in brain lesions (mean z‐scores >5). Moreover, subtle and confluent differences (z‐scores ~2–4) were observed in clinically plausible regions (between lesions, corpus callosum). Conclusions Brain T1 and T2 quantitative norms were derived voxel‐wise with low variability in healthy tissue. Example patient deviation maps demonstrated good sensitivity of the atlases for detecting relaxation time alterations.

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Although several MRI methods have been explored to achieve in vivo myelin quantification, imaging the whole brain in clinically acceptable times and sufficiently high resolution remains challenging. To address this problem, this work investigates the acceleration of multi-echo T 2 acquisitions based on the multi-echo gradient and spin echo (GRASE) sequence using CAIPIRINHA undersampling and adapted k-space reordering patterns. Methods: A prototype multi-echo GRASE sequence supporting CAIPIRINHA parallel imaging was implemented. Multi-echo T 2 data were acquired from 12 volunteers using the implemented sequence (1.6 × 1.6 × 1.6 mm 3 , 84 slices, acquisition time [TA] = 10:30 min) and a multi-echo spin echo (MESE) sequence as reference (1.6 × 1.6 × 3.2 mm 3 , single-slice, TA = 5:41 min). Myelin water fraction (MWF) maps derived from both acquisitions were compared via correlation and Bland-Altman analyses. In addition, scan-rescan datasets were acquired to evaluate the repeatability of the derived maps. Results: Resulting maps from the MESE and multi-echo GRASE sequences were found to be correlated (r = 0.83). The Bland-Altman analysis revealed a mean bias of −0.2% (P = .24) with the limits of agreement ranging from −3.7% to 3.3%. The Pearson's correlation coefficient among MWF values obtained from the scan-rescan datasets was found to be 0.95 and the mean bias equal to 0.11% (P = .32), indicating good repeatability of the retrieved maps. 210 | PIREDDA Et Al. F I G U R E 8 Comparison of MWF maps derived from the multi-echo GRASE in a scan-rescan scenario. A, MWF maps acquired from the same subject after repositioning. Correlation (B) and Bland-Altman (C) analysis considering average values from extracted brain ROIs 220 | PIREDDA Et Al. Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement no. 754462 (EuroTech-Postdoc). CONFLICT OF INTEREST This research is a part G.F. Piredda's Ph.D. thesis funded by Siemens Healthcare AG, Switzerland; T. Hilbert, C. von Deuster and T. Kober are employees of the same company.

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Purpose: High-resolution isotropic T 2 mapping of the human brain with multi-echo spin-echo (MESE) acquisitions is challenging. When using a 2D sequence, the resolution is limited by the slice thickness. If used as a 3D acquisition, specific absorption rate limits are easily exceeded due to the high power deposition of nonselective refocusing pulses. A method to reconstruct 1-mm 3 isotropic T 2 maps is proposed based on multiple 2D MESE acquisitions. Data were undersampled (10-fold) to compensate for the prolonged scan time stemming from the super-resolution acquisition. Theory and Methods: The proposed method integrates a classical super-resolution with an iterative model-based approach to reconstruct quantitative maps from a set of undersampled low-resolution data. The method was tested on numerical and multipurpose phantoms, and in vivo data. T 2 values were assessed with a region-of-interest analysis using a single-slice spin-echo and a fully sampled MESE acquisition in a phantom, and a MESE acquisition in healthy volunteers. Results: Numerical simulations showed that the best trade-off between acceleration and number of low-resolution datasets is 10-fold acceleration with 4 acquisitions (acquisition time = 18 min). The proposed approach showed improved resolution over low-resolution images for both phantom and brain. Region-of-interest analysis of the phantom compartments revealed that at shorter T 2 , the proposed method was comparable with the fully sampled MESE. For the volunteer data, the T 2 values found in the brain structures were consistent across subjects (8.5-13.1 ms standard deviation). Conclusion: The proposed method addresses the inherent limitations associated with high-resolution T 2 mapping and enables the reconstruction of 1 mm 3 isotropic relaxation maps with a 10 times faster acquisition. K E Y W O R D Smodel-based reconstruction, parallel Imaging, super-resolution, T 2 mapping

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