Lucignani Martina, Breschi Laura, Espagnet Maria Camilla Rossi, Longo Daniela, Talamanca Lorenzo Figà, Placidi Elisa, Napolitano Antonio
Medical Physics Department, Bambino Gesù Children's Hospital IRCCS, Rome, Italy.
Neuroradiology Unit, Bambino Gesù Children's Hospital IRCCS, Rome, Italy; Nesmos Department, Sapienza University, Rome, Italy.
Neuroimage. 2021 Sep;238:118234. doi: 10.1016/j.neuroimage.2021.118234. Epub 2021 Jun 4.
Neurite Orientation Dispersion and Density Imaging (NODDI) and Bingham-NODDI diffusion MRI models are nowadays very well-known models in the field of diffusion MRI as they represent powerful tools for the estimation of brain microstructure. In order to efficiently translate NODDI imaging findings into the diagnostic clinical practice, a test-retest approach would be useful to assess reproducibility and reliability of NODDI biomarkers, thus providing validation on precision of different fitting toolboxes. In this context, we conducted a test-retest study with the aim to assess the effects of different factors (i.e. fitting algorithms, multiband acceleration, shell configuration, age of subject and hemispheric side) on diffusion models reliability, assessed in terms of Intra-class Correlation Coefficient (ICC) and Variation Factor (VF). To this purpose, data from pediatric and adult subjects were acquired with Simultaneous-MultiSlice (SMS) imaging method with two different acceleration factor (AF) and four b-values, subsequently combined in seven shell configurations. Data were then fitted with two different GPU-based algorithms to speed up the analysis. Results show that each factor investigated had a significant effect on reliability of several diffusion parameters. Particularly, both datasets reveal very good ICC values for higher AF, suggesting that faster acquisitions do not jeopardize the reliability and are useful to decrease motion artifacts. Although very small reliability differences appear when comparing shell configurations, more extensive diffusion parameters variability results when considering shell configuration with lower b-values, especially for simple model like NODDI. Also fitting tools have a significant effect on reliability, but their difference occurs in both datasets and AF, so it appears to be independent from either misalignment and motion artifacts, or noise and SNR. The main achievement of the present study is to show how 10 min multi-shell diffusion MRI acquisition for NODDI acquisition can have reliable results in WM. More complex models do not appear to be more prone to less data acquisition as well as noisier data thus stressing the idea of Bingham-NODDI having greater sensitivity to true subject variability.
神经突方向离散度和密度成像（NODDI）以及宾汉 - NODDI扩散磁共振成像模型如今在扩散磁共振成像领域是非常知名的模型，因为它们是估计脑微结构的强大工具。为了有效地将NODDI成像结果转化为诊断临床实践，重测方法将有助于评估NODDI生物标志物的可重复性和可靠性，从而验证不同拟合工具箱的精度。在此背景下，我们进行了一项重测研究，旨在评估不同因素（即拟合算法、多频段加速、壳层配置、受试者年龄和半球侧）对扩散模型可靠性的影响，通过组内相关系数（ICC）和变异系数（VF）进行评估。为此，使用同时多层（SMS）成像方法，以两种不同的加速因子（AF）和四个b值采集儿科和成人受试者的数据，随后将其组合成七种壳层配置。然后使用两种不同的基于图形处理器（GPU）的算法对数据进行拟合，以加快分析速度。结果表明，所研究的每个因素对几个扩散参数的可靠性都有显著影响。特别是，两个数据集对于较高的AF都显示出非常好的ICC值，这表明更快的采集不会损害可靠性，并且有助于减少运动伪影。尽管在比较壳层配置时出现的可靠性差异非常小，但在考虑具有较低b值的壳层配置时，会出现更广泛的扩散参数变异性，特别是对于像NODDI这样的简单模型。拟合工具对可靠性也有显著影响，但它们的差异在两个数据集和AF中都存在，所以似乎与失准和运动伪影、噪声和信噪比无关。本研究的主要成果是表明，对于NODDI采集，10分钟的多壳层扩散磁共振成像采集在白质中可以获得可靠的结果。更复杂的模型似乎并不更容易受到较少数据采集以及噪声较大数据的影响，因此强调了宾汉 - NODDI对真实受试者变异性具有更高敏感性的观点。
