Genetic markers of cholesterol transport and gray matter diffusion: a preliminary study of the CETP I405V polymorphism

Long-term sequelae of hippocampal lesions in patients with transient global amnesia: A multiparametric MRI study

BACKGROUND

MRI signal diffusion-weighted imaging (DWI) hyperintensity in the hippocampus in patients with transient global amnesia (TGA) are resolved within several days after the onset of TGA.

PURPOSE

To use multiparametric MRI to unravel the sequelae of TGA.

STUDY TYPE

A prospective longitudinal study.

POPULATION

Eight TGA patients.

FIELD STRENGTH/SEQUENCE

A 3.0T Siemens Tim Trio MRI scanner with T₁ -weighted MPRAGE, diffusion-weighted echo planar imaging, and multiecho gradient-recalled echo sequences.

ASSESSMENT

Brain MRI scanned within 72 hours, 2 weeks, and 3 months after onset of TGA, respectively. T₁ image hippocampus was first segmented into 12 subregions using FreeSurfer and registered to DWI to locate DWI lesion. Then a T₁ image with segmented hippocampus was registered to its corresponding apparent diffusion coefficient (ADC) map, fractional anisotropy (FA) map, and quantitative susceptibility map, respectively. Finally, the volume, water diffusion and anisotropy, and magnetic susceptibility of DWI lesion were analyzed.

STATISTICAL TESTS

A paired samples t-test was performed to detect measurement differences between three tests. Pearson correlation was used to assess the correlations between all measurements.

RESULTS

Hyperintensity was detected in the head, body, and caudate of CA1 and hippocampal tail. No significant changes existed in CA1/unit volume across the three timepoint measurements (all, P > 0.480). In Test 1, ratio ADC (DWI lesion / adjacent healthy, rADC) and ratio FA (rFA) decreased below, while ratio susceptibility increased above 1.0. In Test 2, all the episodes normalized around 1.0. In Test 3, rADC remained normalization, but rFA decreased and ratio susceptibility increased again. In Test 1 and Test 3 (vs. Test 2), decreased FA values were accompanied with lower axial diffusivity and/or higher radial diffusivity (all, P < 0.001). Moreover, rFA significantly correlated with ratio susceptibility in Test 3 (r = -0.665, P = 0.039).

DATA CONCLUSION

Microstructural sequelae in hippocampus were demonstrated, which indicates that ischemic lesions may be associated with TGA.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1350-1358.

REDUCING CSF PARTIAL VOLUME EFFECTS TO ENHANCE DIFFUSION TENSOR IMAGING METRICS OF BRAIN MICROSTRUCTURE

Technological advances over recent decades now allow for in vivo observation of human brain tissue through the use of neuroimaging methods. While this field originated with techniques capable of capturing macrostructural details of brain anatomy, modern methods such as diffusion tensor imaging (DTI) that are now regularly implemented in research protocols have the ability to characterize brain microstructure. DTI has been used to reveal subtle micro-anatomical abnormalities in the prodromal phase ofº various diseases and also to delineate "normal" age-related changes in brain tissue across the lifespan. Nevertheless, imaging artifact in DTI remains a significant limitation for identifying true neural signatures of disease and brain-behavior relationships. Cerebrospinal fluid (CSF) contamination of brain voxels is a main source of error on DTI scans that causes partial volume effects and reduces the accuracy of tissue characterization. Several methods have been proposed to correct for CSF artifact though many of these methods introduce new limitations that may preclude certain applications. The purpose of this review is to discuss the complexity of signal acquisition as it relates to CSF artifact on DTI scans and review methods of CSF suppression in DTI. We will then discuss a technique that has been recently shown to effectively suppress the CSF signal in DTI data, resulting in fewer errors and improved measurement of brain tissue. This approach and related techniques have the potential to significantly improve our understanding of "normal" brain aging and neuropsychiatric and neurodegenerative diseases. Considerations for next-level applications are discussed.