Purpose This investigation aimed to enhance the reliability and spatial resolution of MTR measurements for interrogation of subcortical brain regions with an automated volume of interest (VOI) approach. Materials and Methods A 3D MT sequence was acquired using a scan-rescan imaging protocol in 9 healthy volunteers. VOI definition masks for the MTR measurements were generated using FreeSurfer and compared to a manual region of interest (ROI) approach. (The longitudinal stability of MTR was monitored using agar gel phantom over a 5-month period.) Intra-class correlation coefficients (ICC), coefficients of variation (CV) and instrumental standard deviation (ISD) were determined. Results CVs ranged from1.29–2.64% (automated) vs. 1.30–3.40% (manual). ISDs ranged from 0.62–1.10 pu (automated) vs. 0.68–1.67 pu (manual). The SD of the running difference was 1.70% for the phantom scans. Bland-Altman method indicated interchangeability of the automated VOI and manual ROI measurements. Conclusions The automated VOI approach for MTR measurement yielded higher ICCs, lower CVs and lower ISDs compared to the manual method, supporting the utility of this strategy. These results demonstrate the feasibility of obtaining reliable MTR measurements in hippocampus and other critical subcortical regions.

Magnetization transfer imaging (MT) may have considerable promise for early detection and monitoring of subtle brain changes before they are apparent on conventional magnetic resonance images. At 3 Tesla (T), MT affords higher resolution and increased tissue contrast associated with macromolecules. The reliability and reproducibility of a new high-resolution MT strategy were assessed in brain images acquired from 9 healthy subjects. Repeated measures were taken for 12 brain regions of interest (ROIs): genu, splenium, and the left and right hemispheres of the hippocampus, caudate, putamen, thalamus, and cerebral white matter. Spearman's correlation coefficient, coefficient of variation, and intraclass correlation coefficient (ICC) were computed. Multivariate mixed-effects regression models were used to fit the mean ROI values and to test the significance of the effects due to region, subject, observer, time, and manual repetition. A sensitivity analysis of various model specifications and the corresponding ICCs was conducted. Our statistical methods may be generalized to many similar evaluative studies of the reliability and reproducibility of various imaging modalities.

Purpose: To evaluate a rapid sub-millimeter isotropic spoiled gradient-echo (nonselective SPGR) to facilitate the brain subcortical segmentation and the visualization of brain volume compared with the commonly accepted inversion recovery-prepared SPGR (SPGR-IR) technique. Materials and Methods:The feasibility of the nonselective SPGR was evaluated for two segmentation algorithms. FAST was used to segment the brain into constituent tissue classes (white matter, gray matter, cerebrospinal fluid) and FreeSurfer was used to segment specific subcortical structures (hippocampus, caudate, putamen, and thalamus). Localized apparent signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values for nonselective SPGR and the SPGR-IR were compared for the studied subcortical regions. The three-dimensional volume rendering was generated to evaluate the nonselective SPGR and the SPGR-IR for brain visualization.Results: In basal ganglia regions, nonselective SPGR allows for consistent segmentation results for both FAST and FreeSurfer. This sequence also better differentiated gray/white matter compared with SPGR-IR. An approximate two-fold improvement of image quality in apparent SNR and CNR was indicated for subcortical brain anatomical structures with nonselective SPGR versus SPGR-IR. The nonselective SPGR improved clarity and yielded a more realistic depiction of the brain surface for visualization compared with SPGR-IR. Conclusion:Compared with SPGR-IR, nonselective SPGR allows for consistent segmentation results for basal ganglia regions and improved clarity for visualization of the brain.

Excellent scan-rescan reproducibility (ICC > .9, COV < 10%) was observed for specific MTR histogram metrics and the mean MTR approach. These results are comparable to the volumetric approach. Future studies can examine the possibility that MTR changes precede morphological changes as this study suggests that both MTR and volumetric measurements of the hippocampus can be used as reliable imaging tools.