Quantitative Water Content Mapping Research Articles

Investigating obesity-associated brain inflammation using quantitative water content mapping.

There is growing evidence that obesity is associated with inflammation in the brain, which could contribute to the pathogenesis of obesity. In humans, it is challenging to detect brain inflammation in vivo. Recently, quantitative magnetic resonance imaging (qMRI) has emerged as a tool for characterising pathophysiological processes in the brain with reliable and reproducible measures. Proton density imaging provides quantitative assessment of the brain water content, which is affected in different pathologies, including inflammation. We enrolled 115 normal weight, overweight and obese men and women (body mass index [BMI] range 20.1-39.7kgm-2 , age range 20-75years, 60% men) to acquire cerebral water content mapping in vivo using MRI at 3Tesla. We investigated potential associations between brain water content with anthropometric measures of obesity, body fat distribution and whole-body metabolism. No global changes in water content were associated with obesity. However, higher water content values in the cerebellum, limbic lobe and sub-lobular region were detected in participants with higher BMI, independent of age. More specifically, the dorsal striatum, hypothalamus, thalamus, fornix, anterior limb of the internal capsule and posterior thalamic radiation showed the strongest relationship with BMI, independent of age. In a subgroup with available measurements (n=50), we identified visceral adipose tissue to be the strongest tested link between higher water content values and obesity. Individuals with metabolic syndrome had the highest water content values in the hypothalamus and the fornix. There is accumulating evidence that inflammation of the hypothalamus contributed to obesity-associated insulin resistance in that area. Whether brain inflammation is a cause or consequence of obesity in humans still needs to be investigated using a longitudinal study design. Using qMRI, we were able to detect marked water content changes in young and older obese adults, which is most likely the result of chronic low-grade inflammation.

A Single-Scan, Rapid Whole-Brain Protocol for Quantitative Water Content Mapping With Neurobiological Implications.

Water concentration is tightly regulated in the healthy human brain and changes only slightly with age and gender in healthy subjects. Consequently, changes in water content are important for the characterization of disease. MRI can be used to measure changes in brain water content, but as these changes are usually in the low percentage range, highly accurate and precise methods are required for detection. The method proposed here is based on a long-TR (10 s) multiple-echo gradient-echo measurement with an acquisition time of 7:21 min. Using such a long TR ensures that there is no T1 weighting, meaning that the image intensity at zero echo time is only proportional to the water content, the transmit field, and to the receive field. The receive and transmit corrections, which are increasingly large at higher field strengths and for highly segmented coil arrays, are multiplicative and can be approached heuristically using a bias field correction. The method was tested on 21 healthy volunteers at 3T field strength. Calibration using cerebral-spinal fluid values (~100% water content) resulted in mean values and standard deviations of the water content distribution in white matter and gray matter of 69.1% (1.7%) and 83.7% (1.2%), respectively. Measured distributions were coil-independent, as seen by using either a 12-channel receiver coil or a 32-channel receiver coil. In a test-retest investigation using 12 scans on one volunteer, the variation in the mean value of water content for different tissue types was ~0.3% and the mean voxel variability was ~1%. Robustness against reduced SNR was assessed by comparing results for 5 additional volunteers at 1.5T and 3T. Furthermore, water content distribution in gray matter is investigated and regional contrast reported for the first time. Clinical applicability is illustrated with data from one stroke patient and one brain tumor patient. It is anticipated that this fast, stable, easy-to-use, high-quality mapping method will facilitate routine quantitative MR imaging of water content.

Quantitative water content mapping at clinically relevant field strengths: A comparative study at 1.5 T and 3 T

PurposeQuantitative water content mapping in vivo using MRI is a very valuable technique to detect, monitor and understand diseases of the brain. At 1.5T, this technology has already been successfully used, but it has only recently been applied at 3T because of significantly increased RF field inhomogeneity at the higher field strength. To validate the technology at 3T, we estimate and compare in vivo quantitative water content maps at 1.5T and 3T obtained with a protocol proposed recently for 3T MRI. MethodsThe proposed MRI protocol was applied on twenty healthy subjects at 1.5T and 3T; the same post-processing algorithms were used to estimate the water content maps. The 1.5T and 3T maps were subsequently aligned and compared on a voxel-by-voxel basis. Statistical analysis was performed to detect possible differences between the estimated 1.5T and 3T water maps. ResultsOur analysis indicates that the water content values obtained at 1.5T and 3T did not show significant systematic differences. On average the difference did not exceed the standard deviation of the water content at 1.5T. Furthermore, the contrast-to-noise ratio (CNR) of the estimated water content map was increased at 3T by a factor of at least 1.5. ConclusionsVulnerability to RF inhomogeneity increases dramatically with the increasing static magnetic field strength. However, using advanced corrections for the sensitivity profile of the MR coils, it is possible to preserve quantitative accuracy while benefiting from the increased CNR at the higher field strength. Indeed, there was no significant difference in the water content values obtained in the brain at 1.5T and 3T.

Enhancing the precision of quantitative water content mapping by optimizing sequence parameters

This article describes a methodology for determining the precision of a recently published method for quantitative water content mapping using MRI. A framework for calculating the random error component as a function of sequence parameters is provided and predictions are compared with experimental results obtained in a phantom. The experimental and theoretical results are in good agreement and demonstrate that the precision of quantitative water content mapping can be significantly increased by a proper and objective choice of acquisition parameters.