Cai Leon Y, Tanase Costin, Anderson Adam W, Ramadass Karthik, Rheault Francois, Lee Chelsea A, Patel Niral J, Jones Sky, LeStourgeon Lauren M, Mahon Alix, Pruthi Sumit, Gwal Kriti, Ozturk Arzu, Kang Hakmook, Glaser Nicole, Ghetti Simona, Jaser Sarah S, Jordan Lori C, Landman Bennett A
Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.
Department of Psychiatry, University of California, Davis, Davis, CA, USA.
Proc SPIE Int Soc Opt Eng. 2022 Feb-Mar;12032. doi: 10.1117/12.2611553. Epub 2022 Apr 4.
Type 1 diabetes (T1D) affects over 200,000 children and is associated with an increased risk of cognitive dysfunction. Prior imaging studies suggest the neurological changes underlying this risk are multifactorial, including macrostructural, microstructural, and inflammatory changes. However, these studies have yet to be integrated, limiting investigation into how these phenomena interact. To better understand these complex mechanisms of brain injury, a well-powered, prospective, multisite, and multimodal neuroimaging study is needed. We take the first step in accomplishing this with a preliminary characterization of multisite, multimodal MRI quality, motion, and variability in pediatric T1D. We acquire structural T1 weighted (T1w) MRI, diffusion tensor MRI (DTI), functional MRI (fMRI), and magnetic resonance spectroscopy (MRS) of 5-7 participants from each of two sites. First, we assess the contrast-to-noise ratio of the T1w MRI and find no differences between sites. Second, we characterize intervolume motion in DTI and fMRI and find it to be on the subvoxel level. Third, we investigate variability in regional gray matter volumes and local gyrification indices, bundle-wise DTI microstructural measures, and N-acetylaspartate to creatine ratios. We find the T1-based measures to be comparable between sites before harmonization and the DTI and MRS-based measures to be comparable after. We find a 5-15% coefficient of variation for most measures, suggesting ~150-200 participants per group on average are needed to detect a 5% difference across these modalities at 0.9 power. We conclude that multisite, multimodal neuroimaging of pediatric T1D is feasible with low motion artifact after harmonization of DTI and MRS.
1型糖尿病(T1D)影响着超过20万名儿童,并且与认知功能障碍风险增加相关。先前的影像学研究表明,这种风险背后的神经学变化是多因素的,包括宏观结构、微观结构和炎症变化。然而,这些研究尚未整合,限制了对这些现象如何相互作用的调查。为了更好地理解这些复杂的脑损伤机制,需要进行一项样本量充足、前瞻性、多中心和多模态的神经影像学研究。我们通过对儿科T1D多中心、多模态MRI质量、运动和变异性进行初步表征,迈出了实现这一目标的第一步。我们从两个地点分别采集了5 - 7名参与者的结构T1加权(T1w)MRI、扩散张量MRI(DTI)、功能MRI(fMRI)和磁共振波谱(MRS)。首先,我们评估了T1w MRI的对比噪声比,并发现各地点之间没有差异。其次,我们对DTI和fMRI中的体间运动进行了表征,发现其处于亚体素水平。第三,我们研究了区域灰质体积和局部脑回指数、束状DTI微观结构测量以及N - 乙酰天门冬氨酸与肌酸比值的变异性。我们发现基于T1的测量在标准化之前各地点之间具有可比性,而基于DTI和MRS的测量在标准化之后具有可比性。我们发现大多数测量的变异系数为5% - 15%,这表明平均每组大约需要150 - 200名参与者,才能在0.9的检验效能下检测出这些模态之间5%的差异。我们得出结论,在对DTI和MRS进行标准化后,儿科T1D的多中心、多模态神经影像学检查在低运动伪影情况下是可行的。