MRI evidence for altered venous drainage and intracranial compliance in mild traumatic brain injury.

To compare venous drainage patterns and associated intracranial hydrodynamics between subjects who experienced mild traumatic brain injury (mTBI) and age- and gender-matched controls. Thirty adult subjects (15 with mTBI and 15 age- and gender-matched controls) were investigated using a 3T MR scanner. Time since trauma was 0.5 to 29 years (mean 11.4 years). A 2D-time-of-flight MR-venography of the upper neck was performed to visualize the cervical venous vasculature. Cerebral venous drainage through primary and secondary channels, and intracranial compliance index and pressure were derived using cine-phase contrast imaging of the cerebral arterial inflow, venous outflow, and the craniospinal CSF flow. The intracranial compliance index is the defined as the ratio of maximal intracranial volume and pressure changes during the cardiac cycle. MR estimated ICP was then obtained through the inverse relationship between compliance and ICP. Compared to the controls, subjects with mTBI demonstrated a significantly smaller percentage of venous outflow through internal jugular veins (60.9±21% vs. controls: 76.8±10%; p = 0.01) compensated by an increased drainage through secondary veins (12.3±10.9% vs. 5.5±3.3%; p<0.03). Mean intracranial compliance index was significantly lower in the mTBI cohort (5.8±1.4 vs. controls 8.4±1.9; p<0.0007). Consequently, MR estimate of intracranial pressure was significantly higher in the mTBI cohort (12.5±2.9 mmHg vs. 8.8±2.0 mmHg; p<0.0007). mTBI is associated with increased venous drainage through secondary pathways. This reflects higher outflow impedance, which may explain the finding of reduced intracranial compliance. These results suggest that hemodynamic and hydrodynamic changes following mTBI persist even in the absence of clinical symptoms and abnormal findings in conventional MR imaging

On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke

Recent tract-based analyses provided evidence for the exploitability of 3D-SHORE microstructural descriptors derived from diffusion MRI (dMRI) in revealing white matter (WM) plasticity. In this work, we focused on the main open issues left: (1) the comparative analysis with respect to classical tensor-derived indices, i.e., Fractional Anisotropy (FA) and Mean Diffusivity (MD); and (2) the ability to detect plasticity processes in gray matter (GM). Although signal modeling in GM is still largely unexplored, we investigated their sensibility to stroke-induced microstructural modifications occurring in the contralateral hemisphere. A more complete picture could provide hints for investigating the interplay of GM and WM modulations. Ten stroke patients and ten age/gender-matched healthy controls were enrolled in the study and underwent diffusion spectrum imaging (DSI). Acquisitions at three and two time points (tp) were performed on patients and controls, respectively. For all subjects and acquisitions, FA and MD were computed along with 3D-SHORE-based indices [Generalized Fractional Anisotropy (GFA), Propagator Anisotropy (PA), Return To the Axis Probability (RTAP), Return To the Plane Probability (RTPP), and Mean Square Displacement (MSD)]. Tract-based analysis involving the cortical, subcortical and transcallosal motor networks and region-based analysis in GM were successively performed, focusing on the contralateral hemisphere to the stroke. Reproducibility of all the indices on both WM and GM was quantitatively proved on controls. For tract-based, longitudinal group analyses revealed the highest significant differences across the subcortical and transcallosal networks for all the indices. The optimal regression model for predicting the clinical motor outcome at tp3 included GFA, PA, RTPP, and MSD in the subcortical network in combination with the main clinical information at baseline. Region-based analysis in the contralateral GM highlighted the ability of anisotropy indices in discriminating between groups mainly at tp1, while diffusivity indices appeared to be altered at tp2. 3D-SHORE indices proved to be suitable in probing plasticity in both WM and GM, further confirming their viability as a novel family of biomarkers in ischemic stroke in WM and revealing their potential exploitability in GM. Their combination with tensor-derived indices can provide more detailed insights of the different tissue modulations related to stroke pathology

Development of Advanced, Clinically Feasible Neuroimaging Methodology with Diffusional Kurtosis Imaging

Diffusion MRI (dMRI) is a powerful, non-invasive tool for probing the structural organization of the human brain. Quantitative dMRI analyses provide unique capabilities for the characterization of tissue microstructure as well as imaging contrast that is not available to other modalities. White matter tractography relies on dMRI and is currently the only non-invasive technique for mapping structural connections in the human brain. In this chapter, we will describe diffusional kurtosis imaging, an effective and versatile dMRI technique, and discuss a clinical problem in temporal lobe epilepsy (TLE) which is insurmountable with current diagnostic approaches. Subsequent chapters will further develop the capabilities of DKI and demonstrate how it may be particularly well suited to overcome current barriers to care in the clinical management of TLE

In vivo diffusion tensor imaging of chronic spinal cord compression in rat model

Conference Theme: Engineering the Future of BiomedicineChronic spinal cord compression induced cervical myelopathy is a comon cause of spinal cord dysfunction. The exact mechanisms of underlying progressive cell death remain to be elucidated. In this study, in vivo diffusion tensor imaging (DTI) has been applied to investigate the microstructural changes of white matter (WM) in this neurodegenerative disease. Compared with conventional MRI techniques, DTI is believed to be more specific to pathological changes. Radial diffusivity (λ⊥) is higher in the ipilesional region, suggesting demyelination or axonal degradation may occur after prolonged compression. Near the epicenter of lesion, axial diffusivity (λ∥) is lower. Also, caudal-rostral asymmetry has been observed in λ∥. Feasibility of using DTI to detect microstructural changes in chronic disease has been demonstrated. ©2009 IEEE.published_or_final_versionThe 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2009), Minneapolis, MN., 3-6 September 2009. In Proceedings of the 31st EMBC, 2009, p. 2715-271

Pathological and Biomedical Characteristics of Spinal Cord Injury Determined Using Diffusion Tensor Imaging

Traumatic spinal cord injury: SCI) is the most devastating injury that often causes the victim permanent paralysis and undergo a lifetime of therapy and care. It is caused by a mechanical impact that ultimately causes pathophysiological consequences which at this moment in time are an unresolved scientific challenge of great social impact. Scientists have long used animal contusion models to study the pathophysiology of SCI in the discovery of progressive secondary tissue degeneration, demyelination, and apoptosis. More importantly, most therapies that have gone to human clinical trial were first validated in spinal cord contusion models. Magnetic resonance imaging: MRI) is the modality of choice to noninvasively detect the soft tissue injury, particularly suitable for assessing the tissue integrity in SCI. However, the convention MRI lacks capability of detecting and evaluating the injury severity acutely, probably resulting in lost opportunities of effective prognostication or treatment stratification for SCI patients. Diffusion Tensor Magnetic Resonance Imaging: DTMRI, DTI) is an emerging technique known to provide dynamic contrast reflecting the progression of the underlying pathology in CNS tissues. In this study, we hypothesized that axial: ||) and radial: λ^) diffusivity derived from DTI is sensitive to the pathological alteration in spinal cord white matter: WM) tract and could be used as potential biomarkers detecting and characterizing the axonal and myelin damage in SCI. A mouse model of contusion SCI was examined using DTI, behavioral assessment, and histology to test our hypothesis. Techniques employed including the simplification of diffusion weighting scheme, the implementation of diffusion weighted multiple spin-echo sequence, and verified for setting up the experimental protocol and data processing procedures. Secondly, the hypothesis was test on the projects comparing the change of these biomarkers on both the myelinated and dysmyelinated shiverer mice cooperating with histological analysis, and behavioral assessment. Finally, a finite element analysis: FEA) of contusion SCI was deployed to provide evidences of injury mechanics correlated with the injury patterns detected by diffusion MRI for a better characterized animal model of contusion SCI