Implementation of Dual-Source RF Excitation in 3 T MR-Scanners Allows for Nearly Identical ADC Values Compared to 1.5 T MR Scanners in the Abdomen

Background: To retrospectively and prospectively compare abdominal apparent diffusion coefficient (ADC) values obtained within in a 1.5 T system and 3 T systems with and without dual-source parallel RF excitation techniques. Methodology/Principal Findings: After IRB approval, diffusion-weighted (DW) images of the abdomen were obtained on three different MR systems (1.5 T, a first generation 3 T, and a second generation 3 T which incorporates dual-source parallel RF excitation) on 150 patients retrospectively and 19 volunteers (57 examinations total) prospectively. Seven regions of interest (ROI) were throughout the abdomen were selected to measure the ADC. Statistical analysis included independent two-sided t-tests, Mann-Whitney U tests and correlation analysis. In the DW images of the abdomen, mean ADC values were nearly identical with nonsignificant differences when comparing the 1.5 T and second generation 3 T systems in all seven anatomical regions in the patient population and six of the seven in the volunteer population (p.0.05 in all distributions). The strength of correlation measured in the volunteer population between the two scanners in the kidneys ranged from r = 0.64–0.88 and in the remaining regions (besides the spleen), r.0.85. In the patient population the first generation 3 T scanner had different mean ADC values with significant differences (p,0.05) compared to the other two scanners in each of the seven distributions. In the volunteer population, the kidneys shared similar ADC mean values in comparison to the other two scanners with nonsignificant differences

Diagnostic accuracy of contrast-enhanced MR angiography in severe carotid stenosis: meta-analysis with metaregression of different techniques

Contrast-enhanced magnetic resonance angiography (CE-MRA) has become a well-established noninvasive imaging method for the assessment of severe carotid stenosis (70–99% by NASCET criteria). However, CE-MRA is not a standardised technique, but encompasses different concurrent techniques. This review analyses possible differences. A bivariate random effects meta-analysis of 17 primary diagnostic accuracy studies confirmed a high pooled sensitivity of 94.3% and specificity of 93.0% for carotid CE-MRA in severe carotid stenosis. Sensitivity was fairly uniform among the studies, while specificity showed significant variation (I2 = 73%). Metaregressions found significant differences for specificity with two covariates: specificity was higher when using not only maximum intensity projection (MIP) images, but also three-dimensional (3D) images (P = 0.01). Specificity was also higher with electronic images than with hardcopies (P = 0.02). The timing technique (bolus-timed, fluoroscopically triggered or time-resolved) did not result in any significant differences in diagnostic accuracy. Some nonsignificant trends were found for the percentages of severe carotid disease, acquisition time and voxel size. In conclusion, in CE-MRA of severe carotid stenosis the three major timing techniques yield comparably high diagnostic accuracy, electronic images are more specific than hardcopies, and 3D images should be used in addition to MIP images to increase the specificity

Cerebrovascular reactivity among native-raised high altitude residents: an fMRI study

Background: The impact of long term residence on high altitude (HA) on human brain has raised concern among researchers in recent years. This study investigated the cerebrovascular reactivity among native-born high altitude (HA) residents as compared to native sea level (SL) residents. The two groups were matched on the ancestral line, ages, gender ratios, and education levels. A visual cue guided maximum inspiration task with brief breath holding was performed by all the subjects while Blood-Oxygenation-Level-Dependent (BOLD) functional Magnetic Resonance Imaging (fMRI) data were acquired from them

Neuromuscular imaging in inherited muscle diseases

Driven by increasing numbers of newly identified genetic defects and new insights into the field of inherited muscle diseases, neuromuscular imaging in general and magnetic resonance imaging (MRI) in particular are increasingly being used to characterise the severity and pattern of muscle involvement. Although muscle biopsy is still the gold standard for the establishment of the definitive diagnosis, muscular imaging is an important diagnostic tool for the detection and quantification of dystrophic changes during the clinical workup of patients with hereditary muscle diseases. MRI is frequently used to describe muscle involvement patterns, which aids in narrowing of the differential diagnosis and distinguishing between dystrophic and non-dystrophic diseases. Recent work has demonstrated the usefulness of muscle imaging for the detection of specific congenital myopathies, mainly for the identification of the underlying genetic defect in core and centronuclear myopathies. Muscle imaging demonstrates characteristic patterns, which can be helpful for the differentiation of individual limb girdle muscular dystrophies. The aim of this review is to give a comprehensive overview of current methods and applications as well as future perspectives in the field of neuromuscular imaging in inherited muscle diseases. We also provide diagnostic algorithms that might guide us through the differential diagnosis in hereditary myopathies

On the computational assessment of white matter hyperintensity progression: difficulties in method selection and bias field correction performance on images with significant white matter pathology

Introduction Subtle inhomogeneities in the scanner’s magnetic fields (B0 and B1) alter the intensity levels of the structural magnetic resonance imaging (MRI) affecting the volumetric assessment of WMH changes. Here, we investigate the influence that (1) correcting the images for the B1 inhomogeneities (i.e. bias field correction (BFC)) and (2) selection of the WMH change assessment method can have on longitudinal analyses of WMH progression and discuss possible solutions. Methods We used brain structural MRI from 46 mild stroke patients scanned at stroke onset and 3 years later. We tested three BFC approaches: FSL-FAST, N4 and exponentially entropy-driven homomorphic unsharp masking (E2D-HUM) and analysed their effect on the measured WMH change. Separately, we tested two methods to assess WMH changes: measuring WMH volumes independently at both time points semi-automatically (MCMxxxVI) and subtracting intensity-normalised FLAIR images at both time points following image gamma correction. We then combined the BFC with the computational method that performed best across the whole sample to assess WMH changes. Results Analysis of the difference in the variance-to-mean intensity ratio in normal tissue between BFC and uncorrected images and visual inspection showed that all BFC methods altered the WMH appearance and distribution, but FSL-FAST in general performed more consistently across the sample and MRI modalities. The WMH volume change over 3 years obtained with MCMxxxVI with vs. without FSL-FAST BFC did not significantly differ (medians(IQR)(with BFC) = 3.2(6.3) vs. 2.9(7.4)ml (without BFC), p = 0.5), but both differed significantly from the WMH volume change obtained from subtracting post-processed FLAIR images (without BFC)(7.6(8.2)ml, p < 0.001). This latter method considerably inflated the WMH volume change as subtle WMH at baseline that became more intense at follow-up were counted as increase in the volumetric change. Conclusions Measurement of WMH volume change remains challenging. Although the overall volumetric change was not significantly affected by the application of BFC, these methods distorted the image intensity distribution affecting subtle WMH. Subtracting the FLAIR images at both time points following gamma correction seems a promising technique but is adversely affected by subtle WMH. It is important to take into account not only the changes in volume but also in the signal intensity