MR signal intensity of gray matter/white matter contrast and intracranial fat: effects of age and sex

Cortical gray to white matter signal intensity ratio as a sign of neurodegeneration and cognition independent of β-amyloid in dementia

Cortical gray to white matter signal intensity ratio (GWR) measured from T1-weighted magnetic resonance (MR) images was associated with neurodegeneration and dementia. We characterized topological patterns of GWR during AD pathogenesis and investigated its association with cognitive decline. The study included a cross-sectional dataset and a longitudinal dataset. The cross-sectional dataset included 60 cognitively healthy controls, 61 mild cognitive impairment (MCI), and 63 patients with dementia. The longitudinal dataset included 26 participants who progressed from cognitively normal to dementia and 26 controls that remained cognitively normal. GWR was compared across the cross-sectional groups, adjusted for amyloid PET. The correlation between GWR and cognition performance was also evaluated. The longitudinal dataset was used to investigate GWR alteration during the AD pathogenesis. Dementia with β-amyloid deposition group exhibited the largest area of increased GWR, followed by MCI with β-amyloid deposition, MCI without β-amyloid deposition, and controls. The spatial pattern of GWR-increased regions was not influenced by β-amyloid deposits. Correlation between regional GWR alteration and cognitive decline was only detected among individuals with β-amyloid deposition. GWR showed positive correlation with tau PET in the left supramarginal, lateral occipital gyrus, and right middle frontal cortex. The longitudinal study showed that GWR increased around the fusiform, inferior/superior temporal lobe, and entorhinal cortex in MCI and progressed to larger cortical regions after progression to AD. The spatial pattern of GWR-increased regions was independent of β-amyloid deposits but overlapped with tauopathy. The GWR can serve as a promising biomarker of neurodegeneration in AD.

[A Review of Current Knowledge for X-ray Energy in CT: Practical Guide for CT Technologist]

In computed tomography (CT) systems, the optimal X-ray energy in imaging depends on the material composition and the subject size. Among the parameters related to the X-ray energy, we can arbitrarily change only the tube voltage. For years, the tube voltage has often been set at 120 kVp. However, since about 2000, there has been an increasing interest in reducing radiation dose, and it has led to the publication of various reports on low tube voltage. Furthermore, with the spread of dual-energy CT, virtual monochromatic X-ray images are widely used since the contrast can be adjusted by selecting the optional energy. Therefore, because of the renewed interest in X-ray energy in CT imaging, the issue of energy and imaging needs to be summarized. In this article, we describe the basics of physical characteristics of X-ray attenuation with materials and its influence on the process of CT imaging. Moreover, the relationship between X-ray energy and CT imaging is discussed for clinical applications.

Quantitative T1 and T2 MRI signal characteristics in the human brain: different patterns of MR contrasts in normal ageing

Objective

The objective of this study was to examine age-dependent changes in both T₁-weighted and T₂-weighted image contrasts and spin-echo T₂ relaxation time in the human brain during healthy ageing.

Methods

A total of 37 participants between the ages of 49 and 87 years old were scanned with a 3 Tesla system, using T₁-weighted, T₂ weighted and quantitative spin-echo T₂ imaging. Contrast between image intensities and T₂ values was calculated for various regions, including between individual hippocampal subfields.

Results

The T₁ contrast-to-noise (CNR) and gray:white signal intensity ratio (GWR) did not change in the hippocampus, but it declined in the cingulate cortex with age. In contrast, T₂ CNR and GWR declined in both brain regions. T₂ relaxation time was almost constant in gray matter and most (but not all) hippocampal subfields, but increased substantially in white matter, pointing to an age effect on water relaxation in white matter.

Conclusions

Changes in T₁ and T₂ MR characteristics influence the appearance of brain images in later life and should be considered in image analyses of aged subjects. It is speculated that alterations at the cell biology level, with concomitant alterations to the local magnetic environment, reduce dephasing and subsequently prolong spin-echo T₂ through reduced diffusion effects in later life.

Electronic supplementary material

The online version of this article (doi:10.1007/s10334-016-0573-0) contains supplementary material, which is available to authorized users.

Maximum-uncertainty linear discrimination analysis of first-episode schizophrenia subjects

Recent techniques of image analysis brought the possibility to recognize subjects based on discriminative image features. We performed a magnetic resonance imaging (MRI)-based classification study to assess its usefulness for outcome prediction of first-episode schizophrenia patients (FES). We included 39 FES patients and 39 healthy controls (HC) and performed the maximum-uncertainty linear discrimination analysis (MLDA) of MRI brain intensity images. The classification accuracy index (CA) was correlated with the Positive and Negative Syndrome Scale (PANSS) and the Global Assessment of Functioning scale (GAF) at 1-year follow-up. The rate of correct classifications of patients with poor and good outcomes was analyzed using chi-square tests. MLDA classification was significantly better than classification by chance. Leave-one-out accuracy was 72%. CA correlated significantly with PANSS and GAF scores at the 1-year follow-up. Moreover, significantly more patients with poor outcome than those with good outcome were classified correctly. MLDA of brain MR intensity features is, therefore, able to correctly classify a significant number of FES patients, and the discriminative features are clinically relevant for clinical presentation 1 year after the first episode of schizophrenia. The accuracy of the current approach is, however, insufficient to be used in clinical practice immediately. Several methodological issues need to be addressed to increase the usefulness of this classification approach.

Effects of age and sex on volumes of the thalamus, pons, and cortex

Volumes of thalamus, pons, cortical gray matter, and white matter were derived from MR brain images of healthy men and women spanning the adult age range in order to delineate patterns of aging and to compare age and sex effects in thalamus and pons with such effects in cortical gray and white matter volumes. Men had larger intracranial volume (ICV) than women, but ICV did not correlate with age in either sex. Thalamic, pontine, and cortical white matter volumes did not differ between men and women once ICV differences were taken into account, but men had more cortical gray matter than women even after accounting for ICV. Volumes of pons and thalamus were associated, independent of ICV, in women but not in men. Thalamic volume declined linearly with age at a similar rate in both men and women, whereas cortical gray matter volume declined more steeply with age in men than women. Both pontine and cortical white matter volumes remained stable across the age span in both men and women.