Faculty Bibliography

Diffusion tractography is routinely used to study white matter architecture and brain connectivity in vivo. A key step for successful tractography of neuronal tracts is the correct identification of tract directions in each voxel. Here we propose a fingerprinting-based methodology to identify these fiber directions in Orientation Distribution Functions, dubbed ODF-Fingerprinting (ODF-FP). In ODF-FP, fiber configurations are selected based on the similarity between measured ODFs and elements in a pre-computed library. In noisy ODFs, the library matching algorithm penalizes the more complex fiber configurations. ODF simulations and analysis of bootstrapped partial and whole-brain in vivo datasets show that the ODF-FP approach improves the detection of fiber pairs with small crossing angles while maintaining fiber direction precision, which leads to better tractography results. Rather than focusing on the ODF maxima, the ODF-FP approach uses the whole ODF shape to infer fiber directions to improve the detection of fiber bundles with small crossing angle. The resulting fiber directions aid tractography algorithms in accurately displaying neuronal tracts and calculating brain connectivity.

A mechanistic understanding of the pathology of psychiatric disorders has been hampered by extensive heterogeneity in biology, symptoms, and behavior within diagnostic categories that are defined subjectively. We investigated whether leveraging individual differences in information-processing impairments in patients with post-traumatic stress disorder (PTSD) could reveal phenotypes within the disorder. We found that a subgroup of patients with PTSD from two independent cohorts displayed both aberrant functional connectivity within the ventral attention network (VAN) as revealed by functional magnetic resonance imaging (fMRI) neuroimaging and impaired verbal memory on a word list learning task. This combined phenotype was not associated with differences in symptoms or comorbidities, but nonetheless could be used to predict a poor response to psychotherapy, the best-validated treatment for PTSD. Using concurrent focal noninvasive transcranial magnetic stimulation and electroencephalography, we then identified alterations in neural signal flow in the VAN that were evoked by direct stimulation of that network. These alterations were associated with individual differences in functional fMRI connectivity within the VAN. Our findings define specific neurobiological mechanisms in a subgroup of patients with PTSD that could contribute to the poor response to psychotherapy.

The original version of this article, published on 04 June 2018, unfortunately contained a mistake.

INTRODUCTION/BACKGROUND:Dermatomyositis (DM) is an idiopathic inflammatory myopathy involving severe debilitation in need of diagnostics. We evaluated the proximal lower extremity musculature with diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM) and dynamic DTI in DM patients and controls and compared with standard clinical workup.  METHODS: In this IRB-approved, HIPAA-compliant study with written informed consent, anatomical, Dixon fat/water and diffusion imaging were collected in bilateral thigh MRI of 22 controls and 27 DM patients in a 3T scanner. Compartments were scored on T1/T2 scales. Single voxel dynamic DTI metrics in quadriceps before and after 3-min leg exercise were measured. Spearman rank correlation and mixed model analysis of variance/covariance (ANOVA/ANCOVA) were used to correlate with T1 and T2 scores and to compare patients with controls. RESULTS:DM patients showed significantly lower pseudo-diffusion and volume in quadriceps than controls. All subjects showed significant correlation between T1 score and signal-weighted fat fraction; tissue diffusion and pseudo-diffusion varied significantly with T1 and T2 score in patients. Radial and mean diffusion exercise response in patients was significantly higher than controls. CONCLUSION/CONCLUSIONS:Static and dynamic diffusion imaging metrics show correlation with conventional imaging scores, reveal spatial heterogeneity, and provide means to differentiate dermatomyositis patients from controls. KEY POINTS/CONCLUSIONS:• Diffusion imaging shows regional differences between thigh muscles of dermatomyositis patients and controls. • Signal-weighted fat fraction and diffusion metrics correlate with T1/T2 scores of disease severity. • Dermatomyositis patients show significantly higher radial diffusion exercise response than controls.

OBJECTIVES/OBJECTIVE:We describe measurement of skeletal muscle kinetics with multiple echo diffusion tensor imaging (MEDITI). This approach allows characterization of the microstructural dynamics in healthy and pathologic muscle. MATERIALS AND METHODS/METHODS:In a Siemens 3-T Skyra scanner, MEDITI was used to collect dynamic DTI with a combination of rapid diffusion encoding, radial imaging, and compressed sensing reconstruction in a multi-compartment agarose gel rotation phantom and within in vivo calf muscle. An MR-compatible ergometer (Ergospect Trispect) was employed to enable in-scanner plantar flexion exercise. In a HIPAA-compliant study with written informed consent, post-exercise recovery of DTI metrics was quantified in eight volunteers. Exercise response of DTI metrics was compared with that of T2-weighted imaging and characterized by a gamma variate model. RESULTS: = 0.303 ± 0.185). Diffusion and T2-weighted response magnitudes were correlated (e.g., r = 0.792, p = 0.019 for nMD vs. nT2w). CONCLUSION/CONCLUSIONS:We have demonstrated the feasibility of MEDITI for capturing spatially resolved diffusion tensor data in dynamic systems including post-exercise skeletal muscle recovery following in-scanner plantar flexion.

A novel approach is presented for group statistical analysis of diffusion weighted MRI datasets through voxelwise Orientation Distribution Functions (ODF). Recent advances in MRI acquisition make it possible to use high quality diffusion weighted protocols (multi-shell, large number of gradient directions) for routine in vivo study of white matter architecture. The dimensionality of these data sets is however often reduced to simplify statistical analysis. While these approaches may detect large group differences, they do not fully capitalize on all acquired image volumes. Incorporation of all available diffusion information in the analysis however risks biasing the outcome by outliers. Here we propose a statistical analysis method operating on the ODF, either the diffusion ODF or fiber ODF. To avoid outlier bias and reliably detect voxelwise group differences and correlations with demographic or behavioral variables, we apply the Low-Rank plus Sparse (L+S) matrix decomposition on the voxelwise ODFs which separates the sparse individual variability in the sparse matrix S whilst recovering the essential ODF features in the low-rank matrix L. We demonstrate the performance of this ODF L+S approach by replicating the established negative association between global white matter integrity and physical obesity in the Human Connectome dataset. The volume of positive findings (p<0.01, 227 cm³) agrees with and expands on the volume found by TBSS (17 cm³), Connectivity based fixel enhancement (15 cm³) and Connectometry (212 cm³). In the same dataset we further localize the correlations of brain structure with neurocognitive measures such as fluid intelligence and episodic memory. The presented ODF L+S approach will aid in the full utilization of all acquired diffusion weightings leading to the detection of smaller group differences in clinically relevant settings as well as in neuroscience applications.

PURPOSE: Diffusion spectrum imaging (DSI) provides us non-invasively and robustly with anatomical details of brain microstructure. To achieve sufficient angular resolution, DSI requires a large number of q-space samples, leading to long acquisition times. This need is mitigated here by combining the beneficial properties of Radial q-space sampling for DSI with a Multi-Echo Stimulated Echo Sequence (MESTIM). METHODS: Full 2D k-spaces for each of several q-space samples, along the same radially outward line in q-space, are acquired in one readout train with one spin and three stimulated echoes. RF flip angles are carefully chosen to distribute spin magnetization over the echoes and the DSI reconstruction is adapted to account for differences in diffusion time among echoes. RESULTS: Individual datasets and bootstrapped reproducibility analysis demonstrate image quality and SNR of the more-than-twofold-accelerated RDSI MESTIM sequence. Orientation distribution functions (ODF) and tractography results benefit from the longer diffusion times of the latter echoes in the echo train. CONCLUSION: A MESTIM sequence can be used to shorten RDSI acquisition times significantly without loss of image or ODF quality. Further acceleration is possible by combination with simultaneous multi-slice techniques. Magn Reson Med, 2017. (c) 2017 International Society for Magnetic Resonance in Medicine.

A diffusion measurement in the short-time surface-to-volume ratio (S/V) limit (Mitra et al., Phys Rev Lett. 1992;68:3555) can disentangle the free diffusion coefficient from geometric restrictions to diffusion. Biophysical parameters, such as the S/V of tissue membranes, can be used to estimate microscopic length scales non-invasively. However, due to gradient strength limitations on clinical MRI scanners, pulsed gradient spin echo (PGSE) measurements are impractical for probing the S/V limit. To achieve this limit on clinical systems, an oscillating gradient spin echo (OGSE) sequence was developed. Two phantoms containing 10 fiber bundles, each consisting of impermeable aligned fibers with different packing densities, were constructed to achieve a range of S/V values. The frequency-dependent diffusion coefficient, D(omega), was measured in each fiber bundle using OGSE with different gradient waveforms (cosine, stretched cosine, and trapezoidal), while D(t) was measured from PGSE and stimulated-echo measurements. The S/V values derived from the universal high-frequency behavior of D(omega) were compared against those derived from quantitative proton density measurements using single spin echo (SE) with varying echo times, and from magnetic resonance fingerprinting (MRF). S/V estimates derived from different OGSE waveforms were similar and demonstrated excellent correlation with both SE- and MRF-derived S/V measures (rho >/= 0.99). Furthermore, there was a smoother transition between OGSE frequency f and PGSE diffusion time when using teffS/V=9/64f, rather than the commonly used teff = 1/(4f), validating the specific frequency/diffusion time conversion for this regime. Our well-characterized fiber phantom can be used for the calibration of OGSE and diffusion modeling techniques, as the S/V ratio can be measured independently using other MR modalities. Moreover, our calibration experiment offers an exciting perspective of mapping tissue S/V on clinical systems.

PURPOSE: Diffusion spectrum imaging (DSI) has been shown to be an effective tool for noninvasively depicting the anatomical details of brain microstructure. Existing implementations of DSI sample the diffusion encoding space using a rectangular grid. Here we present a different implementation of DSI whereby a radially symmetric q-space sampling scheme for DSI is used to improve the angular resolution and accuracy of the reconstructed orientation distribution functions. METHODS: Q-space is sampled by acquiring several q-space samples along a number of radial lines. Each of these radial lines in q-space is analytically connected to a value of the orientation distribution functions at the same angular location by the Fourier slice theorem. RESULTS: Computer simulations and in vivo brain results demonstrate that radial diffusion spectrum imaging correctly estimates the orientation distribution functions when moderately high b-values (4000 s/mm2) and number of q-space samples (236) are used. CONCLUSION: The nominal angular resolution of radial diffusion spectrum imaging depends on the number of radial lines used in the sampling scheme, and only weakly on the maximum b-value. In addition, the radial analytical reconstruction reduces truncation artifacts which affect Cartesian reconstructions. Hence, a radial acquisition of q-space can be favorable for DSI. Magn Reson Med, 2015. (c) 2015 Wiley Periodicals, Inc.