Faculty Bibliography

Vitamin H (biotin) is delivered to the fetus transplacentally by an active biotin-transport mechanism and is critical for fetal development. Our objective was to develop a comprehensive MRI technique for mapping biotin transporter activity in the murine placenta. Visualization of transporter activity can employ MRI's unique T₂*-dependent signal 'off-switch', which is triggered by transporter mediated aggregation of biotinylated contrast agent (b-BSA-Gd-DTPA). MRI data were collected from pregnant mice after administration of b-BSA-Gd-DTPA and analyzed using a new sub-voxel biophysical signal model. Validation experiments included competition with native biotin, comparative tests using PET, histology, and ICPMS. MRI signal was governed by binding, aggregation, and clearance of biotin (confirmed by histology). Signal dynamics reflected the placenta's perfusion pattern modulated by biotin transporter activity and trophoblast mediated retention, and were in congruence with a three-compartment sub-voxel model. Pre-saturation of the transporters with free biotin suppressed b-BSA-Gd-DTPA uptake. The results were confirmed by PET, histology and ICPMS. The presented MRI-based platform allows to track activity of essential molecular transporters in the placenta, reflecting a transporter-mediated uptake, followed by retention and aggregation, and recycling associated with the large b-BSA-Gd-DTPA conjugate. The presented DCE-MRI technique can furthermore be used to map and characterize microstructural compartmentation and transporter activity without exposing the fetus to contrast media.

OBJECTIVE:The outcome of arthroscopic treatment for femoroacetabular impingement (FAI) depends on the preoperative status of the hip cartilage. Quantitative T2 can detect early biochemical cartilage changes, but its routine implementation is challenging. Furthermore, intrinsic T2 variability between patients makes it difficult to define a threshold to identify cartilage lesions. To address this, we propose a normalized T2-index as a new method to evaluate cartilage in FAI. DESIGN/METHODS:We retrospectively analyzed magnetic resonance imaging (MRI) data of 18 FAI patients with arthroscopically confirmed cartilage defects. Cartilage T2 maps were reconstructed from multi-spin-echo 3-T data using the echo-modulation-curve (EMC) model-based technique. The central femoral cartilage, assumed healthy in early-stage FAI, was used as the normalization reference to define a T2-index. We investigated the ability of the T2-index to detect surgically confirmed cartilage lesions. RESULTS:The average T2-index was 1.14 ± 0.1 and 1.13 ± 0.1 for 2 separated segmentations. Using T2-index >1 as the threshold for damaged cartilage, accuracy was 88% and 100% for the 2 segmentations. We found moderate intraobserver repeatability, although separate segmentations yielded comparable accuracy. Damaged cartilage could not be identified using nonnormalized average T2 values. CONCLUSIONS:This preliminary study confirms the importance of normalizing T2 values to account for interpatient variability and suggests that the T2-index is a promising biomarker for the detection of cartilage lesions in FAI. Future work is needed to confirm that combining T2-index with morphologic MRI and other quantitative biomarkers could improve cartilage assessment in FAI.

PURPOSE/OBJECTIVE:measurements. METHODS:values were extracted for each model and protocol. RESULTS:recovery, whereas smaller contribution was caused by MMP interactions. Inter-slice gap had a similar effect on in vivo MTR (21.2%), in comparison to increasing the number of slices (18.9%). CONCLUSIONS:.

INTRODUCTION: Quantitative T2 mapping may provide an objective biomarker for occult nervous tissue pathology in relapsing-remitting multiple sclerosis (RRMS). We applied a novel echo modulation curve (EMC) algorithm to identify T2 changes in normal-appearing brain regions of subjects with RRMS (N = 27) compared to age-matched controls (N = 38). METHODS: The EMC algorithm uses Bloch simulations to model T2 decay curves in multi-spin-echo MRI sequences, independent of scanner, and scan-settings. T2 values were extracted from normal-appearing white and gray matter brain regions using both expert manual regions-of-interest and user-independent FreeSurfer segmentation. RESULTS: Compared to conventional exponential T2 modeling, EMC fitting provided more accurate estimations of T2 with less variance across scans, MRI systems, and healthy individuals. Thalamic T2 was increased 8.5% in RRMS subjects (p < 0.001) and could be used to discriminate RRMS from healthy controls well (AUC = 0.913). Manual segmentation detected both statistically significant increases (corpus callosum & temporal stem) and decreases (posterior limb internal capsule) in T2 associated with RRMS diagnosis (all p < 0.05). In healthy controls, we also observed statistically significant T2 differences for different white and gray matter structures. CONCLUSIONS: The EMC algorithm precisely characterizes T2 values, and is able to detect subtle T2 changes in normal-appearing brain regions of RRMS patients. These presumably capture both axon and myelin changes from inflammation and neurodegeneration. Further, T2 variations between different brain regions of healthy controls may correlate with distinct nervous tissue environments that differ from one another at a mesoscopic length-scale.

Two new 3T MR imaging contrast methods, track density imaging and echo modulation curve T2 mapping, were combined with simultaneous multisection acquisition to reveal exquisite anatomic detail at 7 canonical levels of the brain stem. Compared with conventional MR imaging contrasts, many individual brain stem tracts and nuclear groups were directly visualized for the first time at 3T. This new approach is clinically practical and feasible (total scan time = 20 minutes), allowing better brain stem anatomic localization and characterization.

PURPOSE: Development of a quantitative transverse relaxation time (T2 )-mapping platform that operates at clinically feasible timescales by employing advanced image reconstruction of radially undersampled multi spin-echo (MSE) datasets. METHODS: Data was acquired on phantom and in vivo at 3 Tesla using MSE protocols employing radial k-space sampling trajectories. In order to overcome the nontrivial spin evolution associated with MSE protocols, a numerical signal model was precalculated based on Bloch simulations of the actual pulse-sequence scheme used in the acquisition process. This signal model was subsequently incorporated into an iterative model-based image reconstruction process, producing T2 and proton-density maps. RESULTS: T2 maps of phantom and in vivo brain were successfully constructed, closely matching values produced by a single spin-echo reference scan. High-resolution mapping was also performed for the spinal cord in vivo, differentiating the underlying gray/white matter morphology. CONCLUSION: The presented MSE data-processing framework offers reliable mapping of T2 relaxation values in a approximately 5-minute timescale, free of user- and scanner-dependent variations. The use of radial k-space sampling provides further advantages in the form of high immunity to irregular physiological motion, as well as enhanced spatial resolutions, owing to its inherent ability to perform alias-free limited field-of-view imaging. Magn Reson Med, 2015. (c) 2015 Wiley Periodicals, Inc.

The task of imaging is to gather spatiotemporal information which can be organized into a coherent map. Tomographic imaging in particular involves the use of multiple projections, or other interactions of a probe (light, sound, etc.) with a body, in order to determine cross-sectional information. Though the probes and the corresponding imaging modalities may vary, and though the methodology of particular imaging approaches is in constant ferment, the conceptual underpinnings of tomographic imaging have in many ways remained fixed for many decades. Recent advances in applied mathematics, however, have begun to roil this intellectual landscape. The advent of compressed sensing, anticipated in various algorithms dating back many years but unleashed in full theoretical force in the last decade, has changed the way imagers have begun to think about data acquisition and image reconstruction. The power of incoherent sampling and sparsity-enforcing reconstruction has been demonstrated in various contexts and, when combined with other modern fast imaging techniques, has enabled unprecedented increases in imaging efficiency. Perhaps more importantly, however, such approaches have spurred a shift in perspective, prompting us to focus less on nominal data sufficiency than on information content. Beginning with examples from MRI, then proceeding through selected other modalities such as CT and PET, as well as multimodality combinations, this paper explores the potential of newly evolving acquisition and reconstruction paradigms to change the way we do imaging in the lab and in the clinic.