Peter Latta

Diffusion Kurtosis Imaging Detects Microstructural Alterations in Brain of α-Synuclein Overexpressing Transgenic Mouse Model of Parkinson’s Disease: A Pilot Study

Evidence suggests that accumulation and aggregation of α-synuclein contribute to the pathogenesis of Parkinson’s disease (PD). The aim of this study was to evaluate whether diffusion kurtosis imaging (DKI) will provide a sensitive tool for differentiating between α-synuclein-overexpressing transgenic mouse model of PD (TNWT-61) and wild-type (WT) littermates. This experiment was designed as a proof-of-concept study and forms a part of a complex protocol and ongoing translational research. Nine-month-old TNWT-61 mice and age-matched WT littermates underwent behavioral tests to monitor motor impairment and MRI scanning using 9.4 Tesla system in vivo. Tract-based spatial statistics (TBSS) and the DKI protocol were used to compare the whole brain white matter of TNWT-61 and WT mice. In addition, region of interest (ROI) analysis was performed in gray matter regions such as substantia nigra, striatum, hippocampus, sensorimotor cortex, and thalamus known to show higher accumulation of α-synuclein. For the ROI analysis, both DKI (6 b-values) protocol and conventional (2 b-values) diffusion tensor imaging (cDTI) protocol were used. TNWT-61 mice showed significant impairment of motor coordination. With the DKI protocol, mean, axial, and radial kurtosis were found to be significantly elevated, whereas mean and radial diffusivity were decreased in the TNWT-61 group compared to that in the WT controls with both TBSS and ROI analysis. With the cDTI protocol, the ROI analysis showed decrease in all diffusivity parameters in TNWT-61 mice. The current study provides evidence that DKI by providing both kurtosis and diffusivity parameters gives unique information that is complementary to cDTI for in vivo detection of pathological changes that underlie PD-like symptomatology in TNWT-61 mouse model of PD. This result is a crucial step in search for a candidate diagnostic biomarker with translational potential and relevance for human studies.

Late‐stage α‐synuclein accumulation in TNWT‐61 mouse model of Parkinson's disease detected by diffusion kurtosis imaging

Diffusion kurtosis imaging (DKI) by measuring non‐Gaussian diffusion allows an accurate estimation of the distribution of water molecule displacement and may correctly characterize microstructural brain changes caused by neurodegeneration. The aim of this study was to evaluate the ability of DKI to detect changes induced by α‐synuclein (α‐syn) accumulation in α‐syn over‐expressing transgenic mice (TNWT‐61) in both gray matter (GM) and white matter (WM) using region of interest (ROI) and tract‐based spatial statistics analyses, respectively, and to explore the relationship between α‐syn accumulation and DKI metrics in our regions of interest. Fourteen‐month‐old TNWT‐61 mice and wild‐type (WT) littermates underwent in vivo DKI scanning using the Bruker Avance 9.4 Tesla magnetic resonance imaging system. ROI analysis in the GM regions substantia nigra, striatum, hippocampus, sensorimotor cortex, and thalamus and tract‐based spatial statistics analysis in WM were performed. Immunohistochemistry for α‐syn was performed in TNWT‐61 mice and correlated with DKI findings. We found increased kurtosis and decreased diffusivity values in GM regions such as the thalamus and sensorimotor cortex, and in WM regions such as the external and internal capsule, mamillothalamic tract, anterior commissure, cingulum, and corpus callosum in TNWT‐61 mice as compared to WT mice. Furthermore, we report for the first time that α‐syn accumulation is positively correlated with kurtosis and negatively correlated with diffusivity in the thalamus. The study provides evidence of an association between the amount of α‐syn and the magnitude of DKI metric changes in the ROIs, with the potential of improving the clinical diagnosis of Parkinsons disease.

K-space trajectory mapping and its application for ultrashort Echo time imaging

MR images are affected by system delays and gradient field imperfections which induce discrepancies between prescribed and actual k-space trajectories. This could be even more critical for non-Cartesian data acquisitions where even a small deviation from the assumed k-space trajectory results in severe image degradation and artifacts. Knowledge of the actual k-space trajectories is therefore crucial and can be incorporated in the reconstruction of high quality non-Cartesian images. A novel MR method for the calibration of actual gradient waveforms was developed using a combination of phase encoding increments and subsequent detection of the exact time point at which the corresponding trajectory is crossing the k-space origin. The measured sets of points were fitted to a parametrical model to calculate the complete actual acquisition trajectory. Measurements performed on phantoms and volunteers, positioned both in- and off-isocenter of the magnet, clearly demonstrate the improvement in reconstructed ultrashort echo time (UTE) images, when information from calibration of k-space sampling trajectories is employed in the MR image reconstruction procedure. The unique feature of the proposed method is its robustness and simple experimental setup, making it suitable for quick acquisition trajectory calibration procedures e.g. for non-Cartesian radial fast imaging.

Early and progressive microstructural brain changes in mice overexpressing human α-Synuclein detected by diffusion kurtosis imaging

Diffusion kurtosis imaging (DKI) is sensitive in detecting α-Synuclein (α-Syn) accumulation-associated microstructural changes at late stages of the pathology in α-Syn overexpressing TNWT-61 mice. The aim of this study was to perform DKI in young TNWT-61 mice when α-Syn starts to accumulate and to compare the imaging results with an analysis of motor and memory impairment and α-Syn levels. Three-month-old (3mo) and six-month-old (6mo) mice underwent DKI scanning using the Bruker Avance 9.4T magnetic resonance imaging system. Region of interest (ROI) analyses were performed in the gray matter; tract-based spatial statistics (TBSS) analyses were performed in the white matter. In the same mice, α-Syn expression was evaluated using quantitative immunofluorescence. Mean kurtosis (MK) was the best differentiator between TNWT-61 mice and wildtype (WT) mice. We found increases in MK in 3mo TNWT-61 mice in the striatum and thalamus but not in the substantia nigra (SN), hippocampus, or sensorimotor cortex, even though the immunoreactivity of human α-Syn was similar or even higher in the latter regions. Increases in MK in the SN were detected in 6mo mice. These findings indicate that α-Syn accumulation-associated changes may start in areas with a high density of dopaminergic nerve terminals. We also found TBSS changes in white matter only at 6mo, suggesting α-Syn accumulation-associated changes start in the gray matter and later progress to the white matter. MK is able to detect microstructural changes induced by α-Syn overexpression in TNWT-61 mice and could be a useful clinical tool for detecting early-stage Parkinsons disease in human patients.

Influence of k-space trajectory corrections on proton density mapping with ultrashort echo time imaging: Application for imaging of short T2 components in white matter

PURPOSEnTo evaluate the impact of MR gradient system imperfections and limitations for the quantitative mapping of short T2* signals performed by ultrashort echo time (UTE) acquisition approach.nnnMATERIALS AND METHODSnThe measurement of short T2* signals from a phantom and a healthy volunteer study (8 subjects of average age 28u202f±u202f4u202fyears) were performed on a 3T scanner. The characteristics of the gradient system were obtained using calibration method performed directly on the measured subject or phantom. This information was used to calculate the actual sampling trajectory with the help of a parametric eddy current model. The actual sample positions were used to reconstruct corrected images and compared with uncorrected data.nnnRESULTSnComparison of both approaches, i.e., without and with correction of k-space sampling trajectories revealed substantial improvement when correction was applied. The phantom experiments demonstrate substantial in-plane signal intensity variations for uncorrected sampling trajectories. In the case of the volunteer study, this led to significant differences in relative proton density (RPD) estimation between the uncorrected and corrected data (Pu202f=u202f0.0117 by Wilcoxon matched-pairs test) and provides for about ~15% higher values for short T2* components of white matter (WM) in the case of uncorrected images.nnnCONCLUSIONnThe imperfection of the applied gradients could induce errors in k-space data sampling which further propagates into the fidelity of the UTE images and jeopardizes precision of quantification. However, the study proved that measurement of gradient errors together with correction of sample positions can contribute to increased accuracy and unbiased characterization of short T2* signals.

K-space trajectory calibration for improved precision of quantitative ultrashort echo time imaging

Ultrashort echo time imaging (UTE) is often the method of choice for measurement of short-lived T2 signals from biological tissues. The UTE acquisition is based on radial or spiral sampling schemes which, in general, are sensitive to small discrepancies between prescribed and actual trajectories. Such errors are usually observed as image quality degradation, visible as ghosting or intensity variation. This is even more serious for quantitative applications when intensity variation can cause serious bias in the estimation of measured parameters such as proton density (PD). Here we investigate such behavior of UTE acquisition and demonstrate that proper calibration of the gradient channels could minimize these type of the errors. Phantom experiments proved the efficiency of the application trajectory calibration approach.

ID 179 – Alpha-synuclein accumulation induced changes in white and gray matter detected by diffusion kurtosis imaging in TNWT-61 mouse model of Parkinson’s disease

Introduction DKI by measuring non-Gaussian diffusion may better characterize the microstructural brain changes as compared to traditional DTI. The aim was to evaluate the capability of DKI for detecting the microstructural changes induced by alpha-synuclein accumulation in TNWT-61 mice using the tract based spatial statistics (TBSS) and region of interest (ROI) analyses. Methods Fourteen month old TNWT-61 mice and wild-type (WT) littermates underwent DKI scanning using 9.4 Tesla MRI system in vivo. TBSS and ROI analysis was performed to detect the changes in white and gray matter in TNWT-61 and WT mice. Immunohistochemistry for alpha-synuclein was performed in 5 TNWT-61 mice and correlated with DKI findings. Results The principle findings of this study were increase in mean kurtosis and decrease in mean diffusivity in thalamus, sensorimotor cortex, hippocampus, external capsule and basolateral amygdaloid nucleus in 14xa0month TNWT-61 mice as compared to WT littermates. We also found significant correlations between alpha-synuclein accumulation and increase in kurtosis and decrease in diffusivity in the thalamus. Conclusion Our results reveal that DKI is sensitive in detecting microstructural changes due to alpha-synuclein accumulation in both GM and WM. These findings suggest that in PD patients DKI should be preferred to routine DTI despite a longer acquisition protocol.