324 research outputs found
Description of volume data and viscoelasticity parameters.
<p>The standard deviations (SD) are given in brackets.</p>a<p>dm<sup>3</sup>,</p>b<p>kPa.</p
Brain shear elasticity modulus averaged over the entire parenchyma visible in four image slices of all volunteers.
<p>Linear and quadratic regression is shown to indicate the order of softening of brain tissue with years of age.</p
MRE experimental setup.
<p><b>a:</b> Typical positions of four adjacent image slices used for multifrequency MRE (slice thickness 6 mm). The image slices were angulated around the left-right axis to compensate for neck flexion, yielding slices parallel to genu and splenium of the corpus callosum. <b>b:</b> Sketch of the imaging sequence. A spin-echo single-shot echo-planar imaging (EPI) sequence was sensitized to motion by a sinusoidal motion encoding gradient (MEG) comprising four cycles of 60 Hz sinusoids. MEG direction was through-plane. The wave generator was triggered by the sequence at the time points demarcated by the asterisks. The waveform was composed by four harmonic frequencies from 25 to 62.5 Hz. The wave trigger was shifted consecutively 32 times relative to the MEG in order to capture the propagation of the waves through the head.</p
Age dependencies of volume data and viscoelasticity parameters.
<p>The annual change is the slope of the regression line with dimensions</p>a<p>cm<sup>3</sup>/year,</p>b<p>Pa/year and</p>c<p>mm<sup>2</sup>/year.</p
Four image slices from T1-weighted volume MRI data compliant with MRE slice positions (upper row).
<p>Color-coded MRE wave data of 50 Hz vibrations. Blue colors scale vibrations towards the reader, while red to yellow colors scale motion beneath the image plane. The maximum tissue deflection is approximately 80<i> µ</i>m (mid row). Real-part modulus images corresponding to 50 Hz vibration frequency with specific regions of interest (ROIs) investigated in this study. Green lines: <i>ROI</i><sub>full</sub>, blue lines: <i>ROI</i><sub>inner</sub>, red lines: <i>ROI</i><sub>frontal</sub>, magenta lines: <i>ROI</i><sub>posterior</sub>, outer green lines excluding ventricles: <i>ROI</i><sub>full</sub> (bottom line).</p
Regional variation in the shear modulus of in vivo brain.
<p>All differences between the regions are statistically significant (p<0.001). The boxplot depicts the lower and upper quartiles as well as the median. Full data range (without outliers) is presented by whiskers. Crosses depict outliers.</p
Statistical analysis.
<p>*Kruskal-Wallis-test; for further analysis Man-Whitney-U-test was used.</p
Regional variation in the parameter <i>α</i> representing the slope of the modulus dispersion and according to the springpot model.
<p>As <i>α</i> is sensitive to the microstructure geometry of biological tissue it is named ‘geometry’ parameter. Similar to <i>µ</i> (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0023451#pone-0023451-g003" target="_blank">Figure 3</a>), all regional differences are statistically significant (p<0.001).</p
sj-tiff-3-mso-10.1177_20552173221109770 - Supplemental material for Prediction of high and low disease activity in early MS patients using multiple kernel learning identifies importance of lateral ventricle intensity
Supplemental material, sj-tiff-3-mso-10.1177_20552173221109770 for Prediction of high and low disease activity in early MS patients using multiple kernel learning identifies importance of lateral ventricle intensity by Claudia Chien, Moritz Seiler, Fabian Eitel, Tanja Schmitz-Hübsch, Friedemann Paul and Kerstin Ritter in Multiple Sclerosis Journal – Experimental, Translational and Clinical</p
sj-docx-1-mso-10.1177_20552173221109770 - Supplemental material for Prediction of high and low disease activity in early MS patients using multiple kernel learning identifies importance of lateral ventricle intensity
Supplemental material, sj-docx-1-mso-10.1177_20552173221109770 for Prediction of high and low disease activity in early MS patients using multiple kernel learning identifies importance of lateral ventricle intensity by Claudia Chien, Moritz Seiler, Fabian Eitel, Tanja Schmitz-Hübsch, Friedemann Paul and Kerstin Ritter in Multiple Sclerosis Journal – Experimental, Translational and Clinical</p
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