Purpose Magnetization transfer in white matter (WM) causes biexponential relaxation, but most quantitative T1 measurements fit data assuming monoexponential relaxation. The resulting monoexponential T1 estimate varies based on scan parameters and represents a source of variation between studies, especially at high fields. In this study, we characterized WM T1 relaxation and performed simulations to determine how to minimize this deviation. Methods To characterize biexponential relaxation, four volunteers were scanned at 3T and 7T using inversion recovery fast spin echo (IR-FSE) with 13 inversion times (TIs). Three volunteers were scanned with IR-FSE using TIs chosen by simulations to reduce T1 deviation, and with MP2RAGE. Results At 3T, the biexponential relaxation has a short component of T1 = 48 ms (9%) and a long component of T1 = 939 ms. At 7T the short component is T1 = 57 ms (11%) and the long component is 1349 ms (89%). For IR-FSE, acquiring four TIs with a minimum of 150 ms (3T) or 200 ms (7T) yielded monoexponential T1 estimates that match the long component to within 10 ms. For MP2RAGE, significant differences (90 ms at 3T, 125 ms at 7T) remain at all parameter values. Conclusion Many T1 mapping sequences yield robust estimates of the long T1 component with suitable choice of TIs, allowing reproducible, sequence-independent T1 values to be measured. However, this is not true of MP2RAGE in its current implementation.
Image quality metrics (IQMs) such as root mean square error (RMSE) and structural similarity index (SSIM) are commonly used in the evaluation and optimization of accelerated magnetic resonance imaging (MRI) acquisition and reconstruction strategies. However, it is unknown how well these indices relate to a radiologist's perception of diagnostic image quality. In this study, we compare the image quality scores of five radiologists with the RMSE, SSIM, and other potentially useful IQMs: peak signal to noise ratio (PSNR) multi-scale SSIM (MSSSIM), information-weighted SSIM (IWSSIM), gradient magnitude similarity deviation (GMSD), feature similarity index (FSIM), high dynamic range visible difference predictor (HDRVDP), noise quality metric (NQM), and visual information fidelity (VIF). The comparison uses a database of MR images of the brain and abdomen that have been retrospectively degraded by noise, blurring, undersampling, motion, and wavelet compression for a total of 414 degraded images. A total of 1017 subjective scores were assigned by five radiologists. IQM performance was measured via the Spearman rank order correlation coefficient (SROCC) and statistically significant differences in the residuals of the IQM scores and radiologists' scores were tested. When considering SROCC calculated from combining scores from all radiologists across all image types, RMSE and SSIM had lower SROCC than six of the other IQMs included in the study (VIF, FSIM, NQM, GMSD, IWSSIM, and HDRVDP).In no case did SSIM have a higher SROCC or significantly smaller residuals than RMSE. These results should be considered when choosing an IQM in future imaging studies.
We introduce a noninvasive, quantitative magnetic resonance imaging (MRI) wind-tunnel measurement in flowing gas (>10 m s(-1)) at high Reynolds numbers (Re>10(5)). The method pertains to liquids and gases, is inherently three dimensional, and extends the range of Re to which MRI is applicable by orders of magnitude. There is potential for clear time savings over traditional pointwise techniques. The mean velocity and turbulent diffusivity of gas flowing past a bluff obstruction and a wing section at realistic stall speeds were measured. The MRI data are compared with computational fluid dynamics.
Purpose Magneto-endosymbionts (MEs) show promise as living magnetic resonance imaging (MRI) contrast agents for in vivo cell tracking. Here we characterize the biomedical imaging properties of ME contrast agents, in vitro and in vivo. Procedures By adapting and engineering magnetotactic bacteria to the intracellular niche, we are creating magneto-endosymbionts (MEs) that offer advantages relative to passive iron-based contrast agents (superparamagnetic iron oxides, SPIOs) for cell tracking. This work presents a biomedical imaging characterization of MEs including: MRI transverse relaxivity (r2) for MEs and ME-labeled cells (compared to a commercially available iron oxide nanoparticle); microscopic validation of labeling efficiency and subcellular locations; and in vivo imaging of a MDA-MB-231BR (231BR) human breast cancer cells in a mouse brain. Results At 7T, r2 relaxivity of bare MEs was higher (250 s−1 mM−1) than that of conventional SPIO (178 s−1 mM−1). Optimized in vitro loading of MEs into 231BR cells yielded 1–4 pg iron/cell (compared to 5–10 pg iron/cell for conventional SPIO). r2 relaxivity dropped by a factor of ~3 upon loading into cells, and was on the same order of magnitude for ME-loaded cells compared to SPIO-loaded cells. In vivo, ME-labeled cells exhibited strong MR contrast, allowing as few as 100 cells to be detected in mice using an optimized 3D SPGR gradient-echo sequence. Conclusions Our results demonstrate the potential of magneto-endosymbionts as living MR contrast agents. They have r2 relaxivity values comparable to traditional iron oxide nanoparticle contrast agents, and provide strong MR contrast when loaded into cells and implanted in tissue.
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