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| Home > Publications database > Improved [Formula: see text] determination in 23Na, 35Cl, and 17O MRI using iterative partial volume correction based on 1H MRI segmentation. |
| Home > Publications database > Improved [Formula: see text] determination in 23Na, 35Cl, and 17O MRI using iterative partial volume correction based on 1H MRI segmentation. |
| Journal Article | DKFZ-2017-06193 |
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2017
Springer
Heidelberg
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Please use a persistent id in citations: doi:10.1007/s10334-017-0623-2
Abstract: Functional parameters can be measured with the help of quantitative non-proton MRI where exact relaxometry parameters are needed. Investigation of [Formula: see text] is often biased by strong partial volume (PV) effects. Hence, in this work a PV correction algorithm approach was evaluated that uses iteratively adapted [Formula: see text]-values and high-resolution structural 1H data to determine transverse relaxation in non-proton MRI more accurately.Simulations, a phantom study and in vivo 23Na, 17O and 35Cl MRI measurements of five healthy volunteers were performed to evaluate the algorithm. [Formula: see text] values of grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF) were obtained. Data were acquired at B 0 = 7T with nominal spatial resolutions of (4-7 mm)3 using a density-adapted radial sequence. The resulting transverse relaxation times were used for quantification of 17O data.The conducted simulations and phantom study verified the correction performance of the algorithm. For in vivo measured [Formula: see text] values, the correction of PV effects leads to an increase in CSF and to a decrease in GM/WM (23Na MRI: long/short GM, WM [Formula: see text]: 36.4 ± 3.1/5.4 ± 0.2, 23.3 ± 2.6/3.5 ± 0.1 ms; 35Cl MRI: 8.9 ± 1.4/1.0 ± 0.4, 5.9 ± 0.3/0.4 ± 0.1 ms; 17O MRI: 2.5 ± 0.1, 2.8 ± 0.1 ms). Iteratively corrected in vivo [Formula: see text] values of the 17O study resulted in improved water content quantification.The proposed iterative algorithm for PV correction leads to more accurate [Formula: see text] values and, thus, can improve accuracy in quantitative non-proton MRI.
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