Error analysis of cine phase contrast MRI velocity measurements used for strain calculation

© 2014 Elsevier Ltd. Cine Phase Contrast (CPC) MRI offers unique insight into localized skeletal muscle behavior by providing the ability to quantify muscle strain distribution during cyclic motion. Muscle strain is obtained by temporally integrating and spatially differentiating CPC-encoded velocity. The aim of this study was to quantify CPC measurement accuracy and precision and to describe error propagation into displacement and strain. Using an MRI-compatible jig to move a B-gel phantom within a 1.5T MRI bore, CPC-encoded velocities were collected. The three orthogonal encoding gradients (through plane, frequency, and phase) were evaluated independently in post-processing. Two systematic error types were corrected: eddy current-induced bias and calibration-type error. Measurement accuracy and precision were quantified before and after removal of systematic error. Through plane- and frequency-encoded data accuracy were within 0.4. mm/s after removal of systematic error - a 70% improvement over the raw data. Corrected phase-encoded data accuracy was within 1.3. mm/s. Measured random error was between 1 to 1.4. mm/s, which followed the theoretical prediction. Propagation of random measurement error into displacement and strain was found to depend on the number of tracked time segments, time segment duration, mesh size, and dimensional order. To verify this, theoretical predictions were compared to experimentally calculated displacement and strain error. For the parameters tested, experimental and theoretical results aligned well. Random strain error approximately halved with a two-fold mesh size increase, as predicted. Displacement and strain accuracy were within 2.6. mm and 3.3%, respectively. These results can be used to predict the accuracy and precision of displacement and strain in user-specific applications

Global network modulation during thalamic stimulation for Tourette syndrome

Background and objectives: Deep brain stimulation (DBS) of the thalamus is a promising therapeutic alternative for treating medically refractory Tourette syndrome (TS). However, few human studies have examined its mechanism of action. Therefore, the networks that mediate the therapeutic effects of thalamic DBS remain poorly understood.Methods: Five participants diagnosed with severe medically refractory TS underwent bilateral thalamic DBS stereotactic surgery. Intraoperative fMRI characterized the blood oxygen level-dependent (BOLD) response evoked by thalamic DBS and determined whether the therapeutic effectiveness of thalamic DBS, as assessed using the Modified Rush Video Rating Scale test, would correlate with evoked BOLD responses in motor and limbic cortical and subcortical regions.Results: Our results reveal that thalamic stimulation in TS participants has wide-ranging effects that impact the frontostriatal, limbic, and motor networks. Thalamic stimulation induced suppression of motor and insula networks correlated with motor tic reduction, while suppression of frontal and parietal networks correlated with vocal tic reduction. These regions mapped closely to major regions of interest (ROI) identified in a nonhuman primate model of TS.Conclusions: Overall, these findings suggest that a critical factor in TS treatment should involve modulation of both frontostriatal and motor networks, rather than be treated as a focal disorder of the brain. Using the novel combination of DBS-evoked tic reduction and fMRI in human subjects, we provide new insights into the basal ganglia-cerebellar-thalamo-cortical network-level mechanisms that influence the effects of thalamic DBS. Future translational research should identify whether these network changes are cause or effect of TS symptoms

Measuring the characteristic topography of brain stiffness with magnetic resonance elastography.

To develop a reliable magnetic resonance elastography (MRE)-based method for measuring regional brain stiffness.First, simulation studies were used to demonstrate how stiffness measurements can be biased by changes in brain morphometry, such as those due to atrophy. Adaptive postprocessing methods were created that significantly reduce the spatial extent of edge artifacts and eliminate atrophy-related bias. Second, a pipeline for regional brain stiffness measurement was developed and evaluated for test-retest reliability in 10 healthy control subjects.This technique indicates high test-retest repeatability with a typical coefficient of variation of less than 1% for global brain stiffness and less than 2% for the lobes of the brain and the cerebellum. Furthermore, this study reveals that the brain possesses a characteristic topography of mechanical properties, and also that lobar stiffness measurements tend to correlate with one another within an individual.The methods presented in this work are resistant to noise- and edge-related biases that are common in the field of brain MRE, demonstrate high test-retest reliability, and provide independent regional stiffness measurements. This pipeline will allow future investigations to measure changes to the brain's mechanical properties and how they relate to the characteristic topographies that are typical of many neurologic diseases

Regional brain stiffness changes across the Alzheimer's disease spectrum

Magnetic resonance elastography (MRE) is an MRI-based technique to noninvasively measure tissue stiffness. Currently well established for clinical use in the liver, MRE is increasingly being investigated to measure brain stiffness as a novel biomarker of a variety of neurological diseases. The purpose of this work was to apply a recently developed MRE pipeline to measure regional brain stiffness changes in human subjects across the Alzheimer's disease (AD) spectrum, and to gain insights into the biological processes underlying those stiffness changes by correlating stiffness with existing biomarkers of AD. The results indicate that stiffness changes occur mostly in the frontal, parietal and temporal lobes, in accordance with the known topography of AD pathology. Furthermore, stiffness in those areas correlates with existing imaging biomarkers of AD including hippocampal volumes and amyloid PET. Additional analysis revealed preliminary but significant evidence that the relationship between brain stiffness and AD severity is nonlinear and non-monotonic. Given that similar relationships have been observed in functional MRI experiments, we used task-free fMRI data to test the hypothesis that brain stiffness was sensitive to structural changes associated with altered functional connectivity. The analysis revealed that brain stiffness is significantly and positively correlated with default mode network connectivity. Therefore, brain stiffness as measured by MRE has potential to provide new and essential insights into the temporal dynamics of AD, as well as the relationship between functional and structural plasticity as it relates to AD pathophysiology

Deep brain stimulation induces BOLD activation in motor and non-motor networks: An fMRI comparison study of STN and EN/GPi DBS in large animals

AbstractThe combination of deep brain stimulation (DBS) and functional MRI (fMRI) is a powerful means of tracing brain circuitry and testing the modulatory effects of electrical stimulation on a neuronal network in vivo. The goal of this study was to trace DBS-induced global neuronal network activation in a large animal model by monitoring the blood oxygenation level-dependent (BOLD) response on fMRI. We conducted DBS in normal anesthetized pigs, targeting the subthalamic nucleus (STN) (n=7) and the entopeduncular nucleus (EN), the non-primate analog of the primate globus pallidus interna (n=4). Using a normalized functional activation map for group analysis and the application of general linear modeling across subjects, we found that both STN and EN/GPi DBS significantly increased BOLD activation in the ipsilateral sensorimotor network (FDR<0.001). In addition, we found differential, target-specific, non-motor network effects. In each group the activated brain areas showed a distinctive correlation pattern forming a group of network connections. Results suggest that the scope of DBS extends beyond an ablation-like effect and that it may have modulatory effects not only on circuits that facilitate motor function but also on those involved in higher cognitive and emotional processing. Taken together, our results show that the swine model for DBS fMRI, which conforms to human implanted DBS electrode configurations and human neuroanatomy, may be a useful platform for translational studies investigating the global neuromodulatory effects of DBS

Error analysis of cine phase contrast MRI velocity measurements used for strain calculation

Cine Phase Contrast (CPC) MRI offers unique insight into localized skeletal muscle behavior by providing the ability to quantify muscle strain distribution during cyclic motion. Muscle strain is obtained by temporally integrating and spatially differentiating CPC-encoded velocity. The aim of this study was to quantify measurement accuracy and precision and to describe error propagation into displacement and strain. Using an MRI-compatible jig to move a B-gel phantom within a 1.5T MRI bore, CPC-encoded velocities were collected. The three orthogonal encoding gradients (through plane, frequency, and phase) were evaluated independently in post-processing. Two systematic error types were corrected: eddy current-induced bias and calibration-type error. Measurement accuracy and precision were quantified before and after removal of systematic error. Through plane- and frequency-encoded data accuracy were within 0.4mm/s after removal of systematic error – a 70% improvement over the raw data. Corrected phase-encoded data accuracy was within 1.3mm/s. Measured random error was between 1 to 1.4mm/s, which followed the theoretical prediction. Propagation of random measurement error into displacement and strain was found to depend on the number of tracked time segments, time segment duration, mesh size, and dimensional order. To verify this, theoretical predictions were compared to experimentally calculated displacement and strain error. For the parameters tested, experimental and theoretical results aligned well. Random strain error approximately halved with a two-fold mesh size increase, as predicted. Displacement and strain accuracy were within 2.6mm and 3.3%, respectively. These results can be used to predict the accuracy and precision of displacement and strain in user-specific applications