Analysis of errors in diffusion kurtosis imaging caused by slice crosstalk in simultaneous multi-slice imaging.

Simultaneous multi-slice (SMS) imaging techniques accelerate diffusion MRI data acquisition. However, slice separation is imperfect and results in residual signal leakage between the simultaneously excited slices. The resulting consistent bias may adversely affect diffusion model parameter estimation. Although this bias is usually small and might not affect the simplified diffusion tensor model significantly, higher order diffusion models such as kurtosis are likely to be more susceptible to such effects. In this work, two SMS reconstruction techniques and an alternative acquisition approach were tested to quantify the effects of slice crosstalk on diffusion kurtosis parameters. In reconstruction, two popular slice separation algorithms, slice GRAPPA and split-slice GRAPPA, are evaluated to determine the effect of slice leakage on diffusion kurtosis metrics. For the alternative acquisition, the slice pairings were varied across diffusion weighted images such that the signal leakage does not come from the same overlapped slice for all diffusion encodings. Simulation results demonstrated the potential benefits of randomizing the slice pairings. However, various experimental factors confounded the advantages of slice pair randomization. In volunteer experiments, region-of-interest analyses found high metric errors with each of the SMS acquisitions and reconstructions in the brain white matter.

Optimization of q-space sampling for mean apparent propagator MRI metrics using a genetic algorithm.

Mean Apparent Propagator (MAP) MRI is a recently introduced technique to estimate the diffusion probability density function (PDF) robustly. Using the estimated PDF, MAP MRI then calculates zero-displacement and non-Gaussianity metrics, which might better characterize tissue microstructure compared to diffusion tensor imaging or diffusion kurtosis imaging. However, intensive q-space sampling required for MAP MRI limits its widespread adoption. A reduced q-space sampling scheme that maintains the accuracy of the derived metrics would make it more practical. A heuristic approach for acquiring MAP MRI with fewer q-space samples has been introduced earlier with scan duration of less than 10 minutes. However, the sampling scheme was not optimized systematically to preserve the accuracy of the model metrics. In this work, a genetic algorithm is implemented to determine optimal q-space subsampling schemes for MAP MRI that will keep total scan time under 10 min. Results show that the metrics derived from the optimized schemes more closely match those computed from the full set, especially in dense fiber tracts such as the corpus callosum.

Chronic differences in white matter integrity following sport-related concussion as measured by diffusion MRI: 6-Month follow-up.

Recent studies demonstrated evidence of physiological changes in the brain following sport-related concussion (SRC) that persisted beyond the point at which athletes achieved full symptom recovery. Diffusion MRI techniques have been used to study brain white matter (WM) changes following SRC; however, longitudinal studies that follow injured athletes from the acute to chronic stages of injury are sparse. The current study explores potential persisting effects of the injury, which serves as a follow-up to our previous work that reported WM changes in the acute and subacute phase of SRC recovery. Concussed high school and collegiate football players (n = 17) and well-matched teammate controls (n = 20) were followed up at 6 months postinjury with diffusion tensor (DTI) and diffusion kurtosis imaging (DKI) as well as measures of self-reported symptoms, cognitive functioning, and balance. Results of tract-based spatial statistics (TBSS) analyses revealed continued widespread decreased mean and axial diffusivity compared to control subjects in 6-month follow-up scans. On the other hand, kurtosis metrics, which were significantly higher in concussed athletes in the acute phase, had normalized. WM tract regions-of-interest (ROIs) were created from significant clusters in the TBSS analysis, and linear mixed effects (LME) analyses were used to look at longitudinal changes in these ROIs over time. LME analyses revealed few time × group interactions indicating findings were relatively stable over time. In addition, acute concussion symptoms predicted diffusivity measures at 6 months postinjury. Findings indicate that DTI and DKI may be useful tools in assessing concussion severity, recovery, and possible long-term effects of concussion.

Assessing diffusion kurtosis tensor estimation methods using a digital brain phantom derived from human connectome project data.

PURPOSE: Diffusion kurtosis imaging (DKI) has gained popularity in recent years as an advanced diffusion-weighted MRI technique. This work aims to quantitatively compare the performance and accuracy of four DKI processing algorithms. For this purpose, a digital DKI brain phantom is developed. METHODS: Data from the Human Connectome Project database were used to generate a DKI digital phantom. In a Monte Carlo Rician noise simulation, four DKI processing algorithms were compared based on their mean squared error, squared bias, and variance. RESULTS: Algorithm performance was region-dependent and differed for each diffusion metric and noise level. Crossover between variance and squared bias error occurred between signal-to-noise ratios of 30 and 40. CONCLUSION: Through the framework presented here, DKI algorithms can be quantitatively compared via a ground truth data set. Error maps are critical as algorithm performance varies spatially. Bias-plus-variance decomposition provides a more complete picture than MSE alone. In combination with refinements in acquisition in future studies, the accuracy and efficiency of DKI will continue to improve promoting clinical adoption.

Acute white matter changes following sport-related concussion: A serial diffusion tensor and diffusion kurtosis tensor imaging study.

Recent neuroimaging studies have suggested that following sport-related concussion (SRC) physiological brain alterations may persist after an athlete has shown full symptom recovery. Diffusion MRI is a versatile technique to study white matter injury following SRC, yet serial follow-up studies in the very acute stages following SRC utilizing a comprehensive set of diffusion metrics are lacking. The aim of the current study was to characterize white matter changes within 24 hours of concussion in a group of high school and collegiate athletes, using Diffusion Tensor and Diffusion Kurtosis Tensor metrics. Participants were reassessed a week later. At 24 hours post-injury, the concussed group reported significantly more concussion symptoms than a well-matched control group and demonstrated poorer performance on a cognitive screening measure, yet these differences were nonsignificant at the 8-day follow-up. Similarly, within 24-hours after injury, the concussed group exhibited a widespread decrease in mean diffusivity, increased axial kurtosis and, to a lesser extent, decreased axial and radial diffusivities compared with control subjects. At 8 days post injury, the differences in these diffusion metrics were even more widespread in the injured athletes, despite improvement of symptoms and cognitive performance. These MRI findings suggest that the athletes might not have reached full physiological recovery a week after the injury. These findings have significant implications for the management of SRC because allowing an athlete to return to play before the brain has fully recovered from injury may have negative consequences. Hum Brain Mapp 37:3821-3834, 2016. © 2016 Wiley Periodicals, Inc.