Medical Physics Group, Institute of Diagnostic and Interventional Radiology I, Jena University Hospital-Friedrich Schiller University Jena, Philosophenweg 3, Gebäude 5, 07743, Jena, Germany.
MAGMA. 2012 Oct;25(5):321-33. doi: 10.1007/s10334-012-0305-z. Epub 2012 Feb 25.
Referencing metabolite intensities to the tissue water intensity is commonly applied to determine metabolite concentrations from in vivo (1)H-MRS brain data. However, since the water concentration and relaxation properties differ between grey matter, white matter and cerebrospinal fluid (CSF), the volume fractions of these compartments have to be considered in MRS voxels.
The impact of partial volume correction was validated by phantom measurements in voxels containing mixtures of solutions with different NAA and water concentrations as well as by analyzing in vivo (1)H-MRS brain data acquired with various voxel compositions.
Phantom measurements indicated substantial underestimation of NAA concentrations when assuming homogeneously composed voxels, especially for voxels containing solution, which simulated CSF (error: ≤ 92%). This bias was substantially reduced by taking into account voxel composition (error: ≤ 10%). In the in vivo study, tissue correction reduced the overall variation of quantified metabolites by up to 35% and revealed the expected metabolic differences between various brain tissues.
Tissue composition affects extraction of metabolite concentrations and may cause misinterpretations when comparing measurements performed with different voxel sizes. This variation can be reduced by considering the different tissue types by means of combined analysis of spectroscopic and imaging data.
将代谢物强度参照到组织水强度通常应用于从体内（1）H-MRS 脑数据中确定代谢物浓度。然而，由于灰质、白质和脑脊液（CSF）之间的水浓度和弛豫特性不同，因此必须在 MRS 体素中考虑这些隔室的体积分数。
通过含有不同 NAA 和水浓度的溶液混合物的体素中的体模测量以及通过分析具有不同体素组成的体内（1）H-MRS 脑数据来验证部分体积校正的影响。
体模测量表明，当假设均匀组成的体素时，NAA 浓度会被严重低估，特别是对于模拟 CSF 的体素（误差：≤92%）。通过考虑体素组成（误差：≤10%），可以大大减少这种偏差。在体内研究中，组织校正将定量代谢物的总体变化降低了多达 35%，并揭示了不同脑组织之间预期的代谢差异。
组织组成会影响代谢物浓度的提取，当比较使用不同体素大小进行的测量时，可能会导致误解。通过结合光谱和成像数据的分析来考虑不同的组织类型，可以减少这种变化。
