Increased-contrast, high-spatial-resolution, diffusion-weighted, spin-echo, echo-planar imaging

Influence of noise correction on intra- and inter-subject variability of quantitative metrics in diffusion kurtosis imaging

Diffusion kurtosis imaging (DKI) is a promising extension of diffusion tensor imaging, giving new insights into the white matter microstructure and providing new biomarkers. Given the rapidly increasing number of studies, DKI has a potential to establish itself as a valuable tool in brain diagnostics. However, to become a routine procedure, DKI still needs to be improved in terms of robustness, reliability, and reproducibility. As it requires acquisitions at higher diffusion weightings, results are more affected by noise than in diffusion tensor imaging. The lack of standard procedures for post-processing, especially for noise correction, might become a significant obstacle for the use of DKI in clinical routine limiting its application. We considered two noise correction schemes accounting for the noise properties of multichannel phased-array coils, in order to improve the data quality at signal-to-noise ratio (SNR) typical for DKI. The SNR dependence of estimated DKI metrics such as mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) is investigated for these noise correction approaches in Monte Carlo simulations and in in vivo human studies. The intra-subject reproducibility is investigated in a single subject study by varying the SNR level and SNR spatial distribution. Then the impact of the noise correction on inter-subject variability is evaluated in a homogeneous sample of 25 healthy volunteers. Results show a strong impact of noise correction on the MK estimate, while the estimation of FA and MD was affected to a lesser extent. Both intra- and inter-subject SNR-related variability of the MK estimate is considerably reduced after correction for the noise bias, providing more accurate and reproducible measures. In this work, we have proposed a straightforward method that improves accuracy of DKI metrics. This should contribute to standardization of DKI applications in clinical studies making valuable inferences in group analysis and longitudinal studies.

Comprehensive framework for accurate diffusion MRI parameter estimation

During the last decade, many approaches have been proposed for improving the estimation of diffusion measures. These techniques have already shown an increase in accuracy based on theoretical considerations, such as incorporating prior knowledge of the data distribution. The increased accuracy of diffusion metric estimators is typically observed in well-defined simulations, where the assumptions regarding properties of the data distribution are known to be valid. In practice, however, correcting for subject motion and geometric eddy current deformations alters the data distribution tremendously such that it can no longer be expressed in a closed form. The image processing steps that precede the model fitting will render several assumptions on the data distribution invalid, potentially nullifying the benefit of applying more advanced diffusion estimators. In this work, we present a generic diffusion model fitting framework that considers some statistics of diffusion MRI data. A central role in the framework is played by the conditional least squares estimator. We demonstrate that the accuracy of that particular estimator can generally be preserved, regardless the applied preprocessing steps, if the noise parameter is known a priori. To fulfill that condition, we also propose an approach for the estimation of spatially varying noise levels.

Magnetic resonance imaging of the neonatal brain

Neonatal magnetic resonance (MR) imaging is rapidly becoming the preferred modality for the evaluation of central nervous system disorders in the newborn. Recent literature supports the value of this imaging technique in diagnosing ischemic, hemorrhagic and infectious disease processes in the premature and full-term neonatal brain. Recent data in premature newborns with neurological injury also suggest a role for MR imaging in determining long-term neurodevelopmental outcomes. This review article provides a framework and overview on neonatal MR imaging techniques and examines the literature or radiological disease patterns and prognostic implications in common neurological disorders.

Mapping of the cerebral response to hypoxia measured using graded asymmetric spin echo EPI

Graded asymmetric spin echo-echo planar imaging (ASE-EPI) was used to measure transient alterations in cerebral oxygenation resulting from 60 seconds of anoxia in alpha-chloralose anaesthetised rats. The anoxic period induced a transient fall ( approximately 1 min) in signal intensity followed by a prolonged signal overshoot consistent with an autoregulatory response to oxygen deprivation. The magnitude of signal response, integrated over the entire brain, increased linearly with the echo asymmetry (t(ge)). However, that increase in sensitivity was offset by a reduced signal to noise ratio and quality of the image data. The responses of four regions of interest within the brain to the anoxic stimulus, and the effect of increasing the echo asymmetry, were compared. A comparable magnitude of signal decrease was observed in all brain regions except the superficial cortex that included pial vessels. As t(ge) was incremented differences in signal attenuation between regions became more pronounced. The signal overshoot observed upon restoration of normal breathing gases showed similar trends, producing similar normalised vascular responses for all regions of interest studied. Different regions of interest showed comparable time courses of the signal overshoot suggesting that similar autoregulatory vascular mechanisms operate in all brain regions. These findings additionally show that the use of graded ASE-EPI produced a characteristic profile of maximum signal change measured during and following the anoxic period for each brain region. They suggest that the shape of this profile was determined by the local vasculature within each region of interest; this feature could be exploited in activation studies to eliminate regions with significant signal changes originating from large draining vessels. Finally, the consistent physiological response observed, when the overshoot was compared to the magnitude of the signal drop, demonstrated that modification of the spin echo offset parameter did not mask or detrimentally alter the signal change resulting from the underlying physiological perturbation.