Magnetic susceptibility gradients caused by tissue/air interfaces lead to very short T 2 * times in the human lung. These susceptibility gradients are dependent on the magnetic susceptibility of the respiratory gas and therefore should influence T 2 * relaxation. In this work, a technique for quantitative T 2 * mapping of the human lung during one breath hold is presented. Using this method, the lung T 2 * relaxation time was measured under normoxic (room air, 21% O 2 ) and hyperoxic (100% O 2 ) conditions to verify this assumption. The mean T 2 * difference between room air and 100% O 2 is about 10% and contains ventilation information, since only ventilated regions contribute to signal change due to different susceptibility gradients.

The recent introduction of advanced magnetic resonance (MR) imaging techniques to characterize focal and global degeneration in multiple sclerosis (MS), like the Composite Hindered and Restricted Model of Diffusion, or CHARMED, diffusional kurtosis imaging (DKI) and Neurite Orientation Dispersion and Density Imaging (NODDI) made available new tools to image axonal pathology non-invasively in vivo. These methods already showed greater sensitivity and specificity compared to conventional diffusion tensor-based metrics (e.g., fractional anisotropy), overcoming some of its limitations. While previous studies uncovered global and focal axonal degeneration in MS patients compared to healthy controls, here our aim is to investigate and compare different diffusion MRI acquisition protocols in their ability to highlight microstructural differences between MS and control tissue over several much used models. For comparison, we contrasted the ability of fractional anisotropy measurements to uncover differences between lesion, normal-appearing white matter (WM), gray matter and healthy tissue under the same imaging protocols. We show that: (1) focal and diffuse differences in several microstructural parameters are observed under clinical settings; (2) advanced models (CHARMED, DKI and NODDI) have increased specificity and sensitivity to neurodegeneration when compared to fractional anisotropy measurements; and (3) both high (3 T) and ultra-high fields (7 T) are viable options for imaging tissue change in MS lesions and normal appearing WM, while higher b-values are less beneficial under the tested short-time (10 min acquisition) conditions.

This paper describes imaging of lung function with oxygen-enhanced MRI using dynamically acquired T1 parameter maps, which allows an accurate, quantitative assessment of time constants of T1-enhancement and therefore lung function. Eight healthy volunteers were examined on a 1.5-T whole-body scanner. Lung T1-maps based on an IR Snapshot FLASH technique (TE = 1.4 ms, TR = 3.5 ms, FA = 7 (composite function )) were dynamically acquired from each subject. Without waiting for full relaxation between subsequent acquisition of T1-maps, one T1-map was acquired every 6.7 s. For comparison, all subjects underwent a standard pulmonary function test (PFT). Oxygen wash-in and wash-out time course curves of T1 relaxation rate (R1)-enhancement were obtained and time constants of oxygen wash-in (w(in)) and wash-out (w(out)) were calculated. Averaged over the whole right lung, the mean w(out) was 43.90 +/- 10.47 s and the mean (w(in)) was 51.20 +/- 15.53 s, thus about 17% higher in magnitude. Wash-in time constants correlated strongly with forced expired volume in one second in percentage of the vital capacity (FEV1 % VC) and with maximum expiratory flow at 25% vital capacity (MEF25), whereas wash-out time constants showed only weak correlation. Using oxygen-enhanced rapid dynamic acquisition of T1-maps, time course curves of R1-enhancement can be obtained. With w(in) and w(out) two new parameters for assessing lung function are available. Therefore, the proposed method has the potential to provide regional information of pulmonary function in various lung diseases.

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While widely in use in automated segmentation approaches for the detection of group differences or of changes associated with continuous predictors in gray matter volume, T1-weighted images are known to represent dura and cortical vessels with signal intensities similar to those of gray matter. By considering multiple signal sources at once, multimodal segmentation approaches may be able to resolve these different tissue classes and address this potential confound. We explored here the simultaneous use of FLAIR and apparent transverse relaxation rates (a signal related to T2* relaxation maps and having similar contrast) with T1-weighted images. Relative to T1-weighted images alone, multimodal segmentation had marked positive effects on 1. the separation of gray matter from dura, 2. the exclusion of vessels from the gray matter compartment, and 3. the contrast with extracerebral connective tissue. While obtainable together with the T1-weighted images without increasing scanning times, apparent transverse relaxation rates were less effective than added FLAIR images in providing the above mentioned advantages. FLAIR images also improved the detection of cortical matter in areas prone to susceptibility artifacts in standard MPRAGE T1-weighted images, while the addition of transverse relaxation maps exacerbated the effect of these artifacts on segmentation. Our results confirm that standard MPRAGE segmentation may overestimate gray matter volume by wrongly assigning vessels and dura to this compartment and show that multimodal approaches may greatly improve the specificity of cortical segmentation. Since multimodal segmentation is easily implemented, these benefits are immediately available to studies focusing on translational applications of structural imaging.