Irvin Teh

Tracking cerebral white matter changes across the lifespan: insights from diffusion tensor imaging studies

Delineating the normal development of brain white matter (WM) over the human lifespan is crucial to improved understanding of underlying WM pathology in neuropsychiatric and neurological conditions. We review the extant literature concerning diffusion tensor imaging studies of brain WM development in healthy individuals available until October 2012, summarise trends of normal development of human brain WM and suggest possible future research directions. Temporally, brain WM maturation follows a curvilinear pattern with an increase in fractional anisotropy (FA) from newborn to adolescence, decelerating in adulthood till a plateau around mid-adulthood, and a more rapid decrease of FA from old age onwards. Spatially, brain WM tracts develop from central to peripheral regions, with evidence of anterior-to-posterior maturation in commissural and projection fibres. The corpus callosum and fornix develop first and decline earlier, whilst fronto-temporal WM tracts like cingulum and uncinate fasciculus have protracted maturation and decline later. Prefrontal WM is most vulnerable with greater age-related FA reduction compared with posterior WM. Future large scale studies adopting longitudinal design will better clarify human brain WM changes over time.

Diffusion Tensor Imaging Findings of White Matter Changes in First Episode Schizophrenia: A Systematic Review

Earlier structural magnetic resonance imaging in schizophrenia have noted smaller white matter volumes in diverse brain regions and recent diffusion tensor imaging (DTI) studies have allowed better elucidation of changes in brain white matter integrity within the illness. As white matter abnormalities have been reported to occur early in the course of schizophrenia, we systematically review extant DTI studies of anomalies of white matter integrity in first episode schizophrenia (FES) up till October 2011. Overall, disruptions of white matter integrity were found in the cortical, subcortical brain regions and white matter associative and commissural tracts, suggesting that changes of cortical-subcortical white matter integrity were found at an early stage of the disorder. These changes in white matter integrity were correlated with specific cognitive deficits (verbal and spatial working memory) as well as psychopathology (positive more than negative symptoms) in patients with FES. The correlation of these white matter integrity changes with cognitive and phenomenological factors may shed light on neurobiological substrates underlying these clinical manifestations. Future studies need to validate these findings in larger samples of subjects and in different populations as well as chart the progress of these cerebral white matter changes over time so as to better appreciate their trajectory with illness course, treatment and chronicity.

Transcranial direct current stimulation and EEG-based motor imagery BCI for upper limb stroke rehabilitation

Clinical studies had shown that EEG-based motor imagery Brain-Computer Interface (MI-BCI) combined with robotic feedback is effective in upper limb stroke rehabilitation, and transcranial Direct Current Stimulation (tDCS) combined with other rehabilitation techniques further enhanced the facilitating effect of tDCS. This motivated the current clinical study to investigate the effects of combining tDCS with MI-BCI and robotic feedback compared to sham-tDCS for upper limb stroke rehabilitation. The stroke patients recruited were randomized to receive 20 minutes of tDCS or sham-tDCS prior to 10 sessions of 1-hour MI-BCI with robotic feedback for 2 weeks. The online accuracies of detecting motor imagery from idle condition were assessed and offline accuracies of classifying motor imagery from background rest condition were assessed from the EEG of the evaluation and therapy parts of the 10 rehabilitation sessions respectively. The results showed no evident differences between the online accuracies on the evaluation part from both groups, but the offline analysis on the therapy part yielded higher averaged accuracies for subjects who received tDCS (n=3) compared to sham-tDCS (n=2). The results suggest towards tDCS effect in modulating motor imagery in stroke, but a more conclusive result can be drawn when more data are collected in the ongoing study.

Robust and high resolution hyperpolarized metabolic imaging of the rat heart at 7 T with 3D spectral-spatial EPI.

Hyperpolarized metabolic imaging has the potential to revolutionize the diagnosis and management of diseases where metabolism is dysregulated, such as heart disease. We investigated the feasibility of imaging rodent myocardial metabolism at high resolution at 7 T.

Evaluation of EPI distortion correction methods for quantitative MRI of the brain at high magnetic field

High field MRI has been applied to high-resolution structural and functional imaging of the brain. Echo planar imaging (EPI) is an ultrafast acquisition technique widely used in diffusion imaging, functional MRI and perfusion imaging. However, it suffers from geometric and intensity distortions caused by static magnetic field inhomogeneity, which is worse at higher field strengths. Such susceptibility artifacts are particularly severe in relation to the small size of the mouse brain. In this study we compared different distortion correction methods, including nonlinear registration, field map-based, and reversed phase-encoding-based approaches, on quantitative imaging of T1 and perfusion in the mouse brain acquired by spin-echo EPI with inversion recovery and pseudo-continuous arterial spin labeling, respectively, at 7 T. Our results showed that the 3D reversed phase-encoding correction outperformed other methods in terms of geometric fidelity, and that conventional field map-based correction could be improved by combination with affine transformation to reduce the bias in the field map. Both methods improved quantification with smaller fitting error and regional variation. These approaches offer robust correction of EPI distortions at high field strengths and hence could lead to more accurate co-registration and quantification of imaging biomarkers in both clinical and preclinical applications.

Prospective acceleration of diffusion tensor imaging with compressed sensing using adaptive dictionaries

Diffusion MRI requires acquisition of multiple diffusion‐weighted images, resulting in long scan times. Here, we investigate combining compressed sensing and a fast imaging sequence to dramatically reduce acquisition times in cardiac diffusion MRI.

Mapping cardiac microstructure of rabbit heart in different mechanical states by high resolution diffusion tensor imaging: A proof-of-principle study.

Myocardial microstructure and its macroscopic materialisation are fundamental to the function of the heart. Despite this importance, characterisation of cellular features at the organ level remains challenging, and a unifying description of the structure of the heart is still outstanding. Here, we optimised diffusion tensor imaging data to acquire high quality data in ex vivo rabbit hearts in slack and contractured states, approximating diastolic and systolic conditions. The data were analysed with a suite of methods that focused on different aspects of the myocardium. In the slack heart, we observed a similar transmural gradient in helix angle of the primary eigenvector of up to 23.6°/mm in the left ventricle and 24.2°/mm in the right ventricle. In the contractured heart, the same transmural gradient remained largely linear, but was offset by up to +49.9° in the left ventricle. In the right ventricle, there was an increase in the transmural gradient to 31.2°/mm and an offset of up to +39.0°. The application of tractography based on each eigenvector enabled visualisation of streamlines that depict cardiomyocyte and sheetlet organisation over large distances. We observed multiple V- and N-shaped sheetlet arrangements throughout the myocardium, and insertion of sheetlets at the intersection of the left and right ventricle. This study integrates several complementary techniques to visualise and quantify the heart’s microstructure, projecting parameter representations across different length scales. This represents a step towards a more comprehensive characterisation of myocardial microstructure at the whole organ level.

Biomimetic Phantom for Cardiac Diffusion MRI

Diffusion magnetic resonance imaging (MRI) is increasingly used to characterize cardiac tissue microstructure, necessitating the use of physiologically relevant phantoms for methods development. Existing phantoms are generally simplistic and mostly simulate diffusion in the brain. Thus, there is a need for phantoms mimicking diffusion in cardiac tissue.

Anomalous Diffusion in Cardiac Tissue as an Index of Myocardial Microstructure.

Diffusion in biological tissues is known to be hindered by the structural complexity of the underlying medium. In the heart, improved characterisation on how this complexity influences acquired diffusion weighted signals is key to advancing our interpretation of diffusion magnetic resonance imaging, as well as to propose novel biomarkers to further characterise myocardial microstructure. In this work, we propose stretched Mittag-Leffler signal decay models for the quantification of the anomalous decay observed in acquired diffusion weighted signals. Our results, analysed in ex vivo healthy, fixed rat ventricles, indicate that such a representation suffices to capture the anomalous signal decay observed in the myocardial syncytium. The subdiffusive order of signal decay is shown to encode independent information to that encapsulated by standard diffusion tensor metrics, and thus may provide additional information on tissue microstructure. Moreover, subdiffusion gradients are shown to be indicative of the total structural heterogeneity spanning the left ventricular wall, which includes progressive myolaminae branching and spatially varying densities of perimysial collagen, microvasculature and adipose tissue. The proposed approach may therefore have important implications for the characterisation of tissue microstructure, both in cardiac and other tissue types.

Resolving Fine Cardiac Structures in Rats with High-Resolution Diffusion Tensor Imaging.

Cardiac architecture is fundamental to cardiac function and can be assessed non-invasively with diffusion tensor imaging (DTI). Here, we aimed to overcome technical challenges in ex vivo DTI in order to extract fine anatomical details and to provide novel insights in the 3D structure of the heart. An integrated set of methods was implemented in ex vivo rat hearts, including dynamic receiver gain adjustment, gradient system scaling calibration, prospective adjustment of diffusion gradients, and interleaving of diffusion-weighted and non-diffusion-weighted scans. Together, these methods enhanced SNR and spatial resolution, minimised orientation bias in diffusion-weighting, and reduced temperature variation, enabling detection of tissue structures such as cell alignment in atria, valves and vessels at an unprecedented level of detail. Improved confidence in eigenvector reproducibility enabled tracking of myolaminar structures as a basis for segmentation of functional groups of cardiomyocytes. Ex vivo DTI facilitates acquisition of high quality structural data that complements readily available in vivo cardiac functional and anatomical MRI. The improvements presented here will facilitate next generation virtual models integrating micro-structural and electro-mechanical properties of the heart.