Giannelli Marco, Toschi Nicola
Unit of Medical Physics, Pisa University Hospital "Azienda Ospedaliero-Universitaria Pisana", Pisa, Italy.
Department of Biomedicine and Prevention, Medical Physics Section, University of Rome "Tor Vergata", Rome, Italy; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, U.S.A.; Harvard Medical School, Boston, MA, U.S.A.
Magn Reson Imaging. 2016 May;34(4):502-7. doi: 10.1016/j.mri.2015.12.013. Epub 2015 Dec 17.
Diffusional kurtosis imaging (DKI) has proven to be a promising diffusion-MRI technique whose first and most established applications are in neuroimaging. Recently, a number of preliminary studies have assessed the feasibility and potential usefulness of DKI in extra-cranial regions such as prostate, liver, kidney, bladder and breast. The stringent time constraints in most routine body MRI exams frequently mandate the acquisition of diffusion-weighted images (DWIs) with (only) three diffusion weighting directions (i.e. the main orthogonal directions). The aim of this study was to evaluate the potential error introduced in the estimation of the average of the three directional diffusional kurtosis values (K) by using, for each b-value, the geometric mean (trace-weighted image) of acquired DWIs (as is common practice in most diffusion-MRI studies of the body) instead of fitting the DKI model to DWIs acquired along each direction prior to averaging. By solving the DKI model analytically while imposing three orthogonal diffusion weighting directions and two non-null b-values (800 and 2000s/mm(2)), extensive simulations were performed for different K values (0-3) and a wide range of diffusion anisotropy values. The error in the estimates of K induced by geometrical averaging of DWIs was assessed and compared to the uncertainty in K caused by DWIs noise for low (20), medium (40) and high (80) signal-to-noise ratio (SNR) values. The simulations showed that geometrical averaging of the DWIs introduces a noticeable error in estimated K. While the error in K varies non-monotonically with K and with the degree of diffusion anisotropy, there is a trend of increasing absolute error with both increasing K and increasing degree of diffusion anisotropy. In particular, for values of K close to 1 and low/moderate (0-0.4) diffusion anisotropy degrees (typical of various body tissues), the absolute error in K can range up to 60% of K. In this case, at all SNR values (20, 40, 80), the absolute error in K can be greater than the uncertainty introduced by noise. In clinical body applications of DKI, the widespread and growing practice of using trace-weighted images to estimate K can introduce a substantial error, hence hampering interpretation of results as well as multi-center comparisons, and should therefore be avoided.
扩散峰度成像（DKI）已被证明是一种很有前景的扩散磁共振成像技术，其最初且最成熟的应用领域是神经成像。最近，一些初步研究评估了DKI在前列腺、肝脏、肾脏、膀胱和乳腺等颅外区域的可行性和潜在用途。在大多数常规身体磁共振成像检查中，严格的时间限制常常要求（仅）在三个扩散加权方向（即主要正交方向）上采集扩散加权图像（DWI）。本研究的目的是评估在估计三个方向扩散峰度值（K）的平均值时，通过使用每个b值下采集的DWI的几何平均值（迹加权图像）（这是大多数身体扩散磁共振成像研究中的常见做法），而不是在平均之前将DKI模型拟合到沿每个方向采集的DWI上所引入的潜在误差。通过在施加三个正交扩散加权方向和两个非零b值（800和2000 s/mm²）的情况下解析求解DKI模型，针对不同的K值（0 - 3）和广泛的扩散各向异性值进行了大量模拟。评估了DWI几何平均所引起的K估计误差，并与低（20）、中（40）和高（80）信噪比（SNR）值下DWI噪声导致的K的不确定性进行了比较。模拟结果表明，DWI的几何平均在估计的K中引入了显著误差。虽然K的误差随K以及扩散各向异性程度呈非单调变化，但随着K的增加和扩散各向异性程度的增加，绝对误差有增大的趋势。特别是，对于接近1的K值和低/中等（约0 - 0.4）扩散各向异性程度（各种身体组织的典型特征），K的绝对误差可达K的60%。在这种情况下，在所有SNR值（20、40、80）下，K的绝对误差可能大于噪声引入的不确定性。在DKI的临床身体应用中，广泛且越来越普遍地使用迹加权图像来估计K会引入相当大的误差，从而妨碍结果的解释以及多中心比较，因此应避免这种做法。
