Faculty Bibliography

PURPOSE: Strict regulations are imposed on the amount of radiofrequency (RF) energy that devices can emit to prevent excessive deposition of RF energy into the body. In this study, we investigated the application of MR temperature mapping and 10-g average specific absorption rate (SAR) computation for safety evaluation of RF-emitting devices. METHODS: Quantification of the RF power deposition was shown for an MRI-compatible dipole antenna and a non-MRI-compatible mobile phone via phantom temperature change measurements. Validation of the MR temperature mapping method was demonstrated by comparison with physical temperature measurements and electromagnetic field simulations. MR temperature measurements alongside physical property measurements were used to reconstruct 10-g average SAR. RESULTS: The maximum temperature change for a dipole antenna and the maximum 10-g average SAR were 1.83 degrees C and 12.4 W/kg, respectively, for simulations and 1.73 degrees C and 11.9 W/kg, respectively, for experiments. The difference between MR and probe thermometry was <0.15 degrees C. The maximum temperature change and the maximum 10-g average SAR for a cell phone radiating at maximum output for 15 min was 1.7 degrees C and 0.54 W/kg, respectively. CONCLUSION: Information acquired using MR temperature mapping and thermal property measurements can assess RF/microwave safety with high resolution and fidelity. Magn Reson Med, 2014. (c) 2014 Wiley Periodicals, Inc.

Despite the increasing development and applications of iron imaging, the pathophysiology of iron accumulation in multiple sclerosis (MS), and its role in disease progression and development of clinical disability, is poorly understood. The aims of our study were to determine the presence and extent of iron in T2 visible lesions and gray and white matter using magnetic field correlation (MFC) MRI and correlate with microscopic white matter (WM) injury as measured by diffusion tensor imaging (DTI). This is a case-control study including a series of 31 patients with clinically definite MS. The mean age was 39 years [standard deviation (SD) = 9.55], they were 11 males and 20 females, with a disease duration average of 3 years (range 0-13) and a median EDSS of 2 (0-4.5). Seventeen healthy volunteers (6 males and 11 females) with a mean age of 36 years (SD = 11.4) were recruited. All subjects underwent MR imaging on a 3T scanner using T2-weighted sequence, 3D T1 MPRAGE, MFC, single-shot DTI and post-contrast T1. T2-lesion volumes, brain volumetry, DTI parameters and iron quantification were calculated and multiple correlations were exploited. Increased MFC was found in the putamen (p = 0.061), the thalamus (p = 0.123), the centrum semiovale (p = 0.053), globus pallidus (p = 0.008) and gray matter (GM) (p = 0.004) of MS patients compared to controls. The mean lesional MFC was 121 s-2 (SD = 67), significantly lower compared to the GM MFC (<0.0001). The GM mean diffusivity (MD) was inversely correlated with the MFC in the centrum semiovale (p < 0.001), and in the splenium of the corpus callosum (p < 0.001). Patients with MS have increased iron in the globus pallidus, putamen and centrum with a trend toward increased iron in all the brain structures. Quantitative iron evaluation of WM and GM may improve the understanding of MS pathophysiology, and might serve as a surrogate marker of disease progression.

The production and isolation of forebrain interneuron progenitors is essential for both understanding cortical development and developing cell-based therapies for developmental and neurodegenerative disorders. Here we demonstrate production of a population of putative calretinin-positive (CalR+)-bipolar interneurons that express markers consistent with caudal ganglionic eminence identities Using serum-free embryoid bodies (SFEBs) generated from human inducible pluripotent stem cells (iPSCs) we demonstrate that these interneuron progenitors exhibit morphological, immunocytochemical, and electrophysiological hallmarks of developing cortical interneurons. Finally, we develop a fluorescence-activated cell sorting (FACS) strategy to isolate interneuron progenitors from SFEBs to allow the development of a purified population of these cells. The identification of this critical neuronal cell type within iPSC-derived SFEBs is an important and novel step in describing cortical development in within this iPSC preparation.

Caregiver-associated cues, including those learned in abusive attachment, provide a sense of safety and security to the child. Here, we explore how cues associated with abusive attachment, such as maternal odor, can modify the enduring neurobehavioral effects of early-life abuse. Two early-life abuse models were used: a naturalistic paradigm, where rat pups were reared by an abusive mother; and a more controlled paradigm, where pups underwent peppermint odor-shock conditioning that produces an artificial maternal odor through engagement of the attachment circuit. Animals were tested for maternal odor preference in infancy, forced swim test (FST), social behavior, and sexual motivation in adulthood-in the presence or absence of maternal odors (natural or peppermint). Amygdala odor-evoked local field potentials (LFPs) via wireless electrodes were also examined in response to the maternal odors in adulthood. Both early-life abuse models induced preference for the maternal odors in infancy. In adulthood, these early-life abuse models produced FST deficits and decreased social behavior, but did not change sexual motivation. Presentation of the maternal odors rescued FST and social behavior deficits induced by early-life abuse and enhanced sexual motivation in all animals. In addition, amygdala LFPs from both abuse animal models showed unique activation within the gamma frequency (70-90 Hz) bands in response to the specific maternal odor present during early-life abuse. These results suggest that attachment-related cues learned during infancy have a profound ability to rescue neurobehavioral dysregulation caused by early-life abuse. Paradoxically, abuse-associated cues seem to acquire powerful and enduring antidepressive properties and alter amygdala modulation.Neuropsychopharmacology advance online publication, 29 October 2014; doi:10.1038/npp.2014.266.

Structural brain connections develop atypically in very preterm children, and altered functional connectivity is also evident in fMRI studies. Such alterations in brain network connectivity are associated with cognitive difficulties in this population. Little is known, however, about electrophysiological interactions among specific brain networks in children born very preterm. In the present study, we recorded magnetoencephalography while very preterm children and full-term controls performed a visual short-term memory task. Regions expressing task-dependent activity changes were identified using beamformer analysis, and inter-regional phase synchrony was calculated. Very preterm children expressed altered regional recruitment in distributed networks of brain areas, across standard physiological frequency ranges including the theta, alpha, beta and gamma bands. Reduced oscillatory synchrony was observed among task-activated brain regions in very preterm children, particularly for connections involving areas critical for executive abilities, including middle frontal gyrus. These findings suggest that inability to recruit neurophysiological activity and interactions in distributed networks including frontal regions may contribute to difficulties in cognitive development in children born very preterm.

PURPOSE: To compare fitting methods and sampling strategies, including the implementation of an optimized b-value selection for improved estimation of intravoxel incoherent motion (IVIM) parameters in breast cancer. METHODS: Fourteen patients (age, 48.4 +/- 14.27 years) with cancerous lesions underwent 3 Tesla breast MRI examination for a HIPAA-compliant, institutional review board approved diffusion MR study. IVIM biomarkers were calculated using "free" versus "segmented" fitting for conventional or optimized (repetitions of key b-values) b-value selection. Monte Carlo simulations were performed over a range of IVIM parameters to evaluate methods of analysis. Relative bias values, relative error, and coefficients of variation (CV) were obtained for assessment of methods. Statistical paired t-tests were used for comparison of experimental mean values and errors from each fitting and sampling method. RESULTS: Comparison of the different analysis/sampling methods in simulations and experiments showed that the "segmented" analysis and the optimized method have higher precision and accuracy, in general, compared with "free" fitting of conventional sampling when considering all parameters. Regarding relative bias, IVIM parameters fp and Dt differed significantly between "segmented" and "free" fitting methods. CONCLUSION: IVIM analysis may improve using optimized selection and "segmented" analysis, potentially enabling better differentiation of breast cancer subtypes and monitoring of treatment. Magn Reson Med, 2014. (c) 2014 Wiley Periodicals, Inc.

Synaptic inhibition, brought about by a rich variety of interneuron types that target different domains of principal cells and other interneurons, counters excitation, modulates the gain, timing, tuning, bursting properties of principal cell firing, and exerts selective filtering of synaptic excitation. At the network level, it allows for coordinating transient interactions among the principal cells to form cooperative assemblies for efficient transmission of information and routing of excitatory activity across networks, typically in the form of brain oscillations. Targeted expression of neuronal activity modulators, such as optogenetics, allow physiological identification and perturbation of specific interneuron subtypes. Combined with large-scale recordings or imaging techniques, these approaches facilitate our understanding of the multiple roles of inhibitory interneurons in shaping circuit functions. This article is part of a Special Issue entitled 'GABAergic signaling'.

The ongoing release of the Human Connectome Project (HCP) data is a watershed event in clinical neuroscience. By attaining a quantum leap in spatial and temporal resolution within the framework of a twin/sibling design, this open science resource provides the basis for delineating brain-behavior relationships across the neuropsychiatric landscape. Here we focus on attention-deficit/hyperactivity disorder (ADHD), which is at least partly continuous across the population, highlighting constructs that have been proposed for ADHD and which are included in the HCP phenotypic battery. We review constructs implicated in ADHD (reward-related processing, inhibition, vigilant attention, reaction time variability, timing and emotional lability) which can be examined in the HCP data and in future 'high definition' clinical datasets.

PURPOSE: Diffusional kurtosis imaging (DKI) is sensitive to the effects of signal noise due to strong diffusion weightings and higher order modeling of the diffusion weighted signal. A simple noise correction scheme is proposed to remove the majority of the noise bias in the estimated diffusional kurtosis. METHODS: Weighted linear least squares (WLLS) fitting together with a voxel-wise, subtraction-based noise correction from multiple, independent acquisitions are employed to reduce noise bias in DKI data. The method is validated in phantom experiments and demonstrated for in vivo human brain for DKI-derived parameter estimates. RESULTS: As long as the signal-to-noise ratio (SNR) for the most heavily diffusion weighted images is greater than 2.1, errors in phantom diffusional kurtosis estimates are found to be less than 5 percent with noise correction, but as high as 44 percent for uncorrected estimates. In human brain, noise correction is also shown to improve diffusional kurtosis estimates derived from measurements made with low SNR. CONCLUSION: The proposed correction technique removes the majority of noise bias from diffusional kurtosis estimates in noisy phantom data and is applicable to DKI of human brain. Features of the method include computational simplicity and ease of integration into standard WLLS DKI post-processing algorithms.

Tagged Meganetic Resonance Image (TMRI) provides a direct and noninvasive way to visualize the in-wall deformation of the myocardium. Due to the through-plane motion, the tracking of 3D trajectories of the material points and the computation of 3D strain field call for the nessicity of building 3D cardiac deformable models. The intersections of three stacks of orthogonal tagging planes are material points in the myocardium. With these intersections as control points, 3D motion can be reconstructed with a novel meshless deformable model. Volumetric meshless deformable models describe an object as point cloud inside the object boundary and the coordinate of each point can be written in parametric functions. A generic heart mesh is registered on the tagged MRI with polar decomposition. A 3D meshless deformable model is generated and deformed with MR image tagging lines. Volumetric meshless deformable models are deformed by calculating the dynamics function and minimizing the local Laplacian coordinates. The similarity transformation of each point is computed by assuming its neighboring points are making the same transformation. The deformation is computed iteratively until the control points match the target positions in the consecutive image frame. The 3D strain field is computed from the 3D displacement field with Moving Least Squares (MLS). We demonstrate that meshless deformable models outperformed the finite element method (FEM) and the spline method with a numerical phantom. Meshless deformable models can track the trajectory of any material point in the myocardium and compute the 3D strain field of any particular area. The experimental results on in vivo healthy and patient heart MRI show that the meshless deformable model can fully recover the myocardium motion in three dimension.