Advanced diffusion imaging for assessing normal white matter development in neonates and characterizing aberrant development in congenital heart disease.
Advanced diffusion imaging for assessing normal white matter development in neonates and characterizing aberrant development in congenital heart disease.
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DOI：
10.1016/j.nicl.2018.04.032
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Grant PE
中科院分区：
文献类型：
--
作者：
Karmacharya S;Gagoski B;Ning L;Vyas R;Cheng HH;Soul J;Newberger JW;Shenton ME;Rathi Y;Grant PE
阐明脑白质(WM)微结构的发育轨迹对于了解几种大脑疾病的正常发育和局部脆弱性至关重要。弥散加权成像(DWI)是目前体内脑白质评估的首选方法。大多数新生儿研究使用标准的扩散张量成像(DTI)模型，但更先进的模型，如轴突定向、弥散和密度成像(NODI)模型和高斯混合模型(GMM)已用于成年人群。在这项研究中，我们比较了这三种扩散模型检测典型发育对照(TDC)新生儿局部白质成熟和先天性心脏病(CHD)新生儿局部异常的能力。对38~47周(GW)的TDC新生儿(N = 16)和37 ~41 周的冠心病新生儿(N = 19)进行多个b值弥散磁共振成像(DMRI)。根据扩散信号计算的指标不仅包括标准DTI模型得出的平均扩散系数(MD)和分数各向异性(FA)，还包括三个先进的扩散指标，即从Node模型得出的纤维取向弥散指数(ODI)、各向同性体积分数(Viso)和细胞内体积分数(Vic)。此外，我们使用了来自非参数GMM的两个新的度量，即返回原点概率(RTOP)和返回轴向概率(RTAP)，它们分别对轴突/细胞体积和密度敏感。采用基于图谱的配准方法，选择22个白质区域(每侧大脑半球6个投射、4个联合和1个胼胝体通路)，计算每个区域所有7个测量指标的平均值。这些值被用作因变量，GW作为线性回归模型中的自变量。最后，在剔除年龄相关趋势后，我们在每个ROI中比较了CHD组和TDC组的这些指标。在TDC人群的线性分析中，MD、Vic、RTAP的12条投影路径和RtoP的11条路径与GW(年龄)显著相关。MD、Vic、RTAP和RtoP的几条关联途径也与GW显著相关。在Vic中，右侧胼胝体通路与GW显著相关。与CHD发展改变的病理生理学相一致，弥散测量显示语言系统所涉及的联系途径不同，即钩状束(UF)、额枕下束(IFOF)和上纵束(SLF)。总体而言，CHD和TDC之间的组比较显示，在a)UF、b)胼胝体(CC)和c)额枕上束(SFOF)，CHD患者的双侧FA、Vic、RTAP和RtoP较低。此外，冠心病的FA在a)左侧SLF、b)双侧放射状前冠(ACR)和左侧内囊豆状核后部(RIC)较低。CHD患者左后肢内囊(PLIC)的VIC也较低。冠心病组ODI在左CC较高。冠心病患者左IFOF的RTAP较低，而CHD患者的RTAP较低：a)左ACR，b)左IFOF和c)右内囊前肢(ALIC)。在这项研究中，三种方法都揭示了出生后早期WM区域的预期变化；然而，GMM优于DTI和NODI，因为它在检测TDC和CHD新生儿之间的差异时显示出明显更大的效应大小。未来基于更大样本的研究需要证实这些结果并探索临床相关性。确定典型发育中新生儿的几个白质区域的发育轨迹。比较先天性心脏病新生儿和典型发育中的对照组的脑区白质异常。比较DTI、NODI和高斯混合模型(GMM)，发现GMM对组织异常最敏感。
Elucidating developmental trajectories of white matter (WM) microstructure is critically important for understanding normal development and regional vulnerabilities in several brain disorders. Diffusion Weighted Imaging (DWI) is currently the method of choice for in-vivo white matter assessment. A majority of neonatal studies use the standard Diffusion Tensor Imaging (DTI) model although more advanced models such as the Neurite Orientation Dispersion and Density Imaging (NODDI) model and the Gaussian Mixture Model (GMM) have been used in adult population. In this study, we compare the ability of these three diffusion models to detect regional white matter maturation in typically developing control (TDC) neonates and regional abnormalities in neonates with congenital heart disease (CHD). Multiple b-value diffusion Magnetic Resonance Imaging (dMRI) data were acquired from TDC neonates (N = 16) at 38 to 47 gestational weeks (GW) and CHD neonates (N = 19) aged 37 weeks to 41 weeks. Measures calculated from the diffusion signal included not only Mean Diffusivity (MD) and Fractional Anisotropy (FA) derived from the standard DTI model, but also three advanced diffusion measures, namely, the fiber Orientation Dispersion Index (ODI), the isotropic volume fraction (Viso), and the intracellular volume fraction (Vic) derived from the NODDI model. Further, we used two novel measures from a non-parametric GMM, namely the Return-to-Origin Probability (RTOP) and Return-to-Axis Probability (RTAP), which are sensitive to axonal/cellular volume and density respectively. Using atlas-based registration, 22 white matter regions (6 projection, 4 association, and 1 callosal pathways bilaterally in each hemisphere) were selected and the mean value of all 7 measures were calculated in each region. These values were used as dependent variables, with GW as the independent variable in a linear regression model. Finally, we compared CHD and TDC groups on these measures in each ROI after removing age-related trends from both the groups. Linear analysis in the TDC population revealed significant correlations with GW (age) in 12 projection pathways for MD, Vic, RTAP, and 11 pathways for RTOP. Several association pathways were also significantly correlated with GW for MD, Vic, RTAP, and RTOP. The right callosal pathway was significantly correlated with GW for Vic. Consistent with the pathophysiology of altered development in CHD, diffusion measures demonstrated differences in the association pathways involved in language systems, namely the Uncinate Fasciculus (UF), the Inferior Fronto-occipital Fasciculus (IFOF), and the Superior Longitudinal Fasciculus (SLF). Overall, the group comparison between CHD and TDC revealed lower FA, Vic, RTAP, and RTOP for CHD bilaterally in the a) UF, b) Corpus Callosum (CC), and c) Superior Fronto-Occipital Fasciculus (SFOF). Moreover, FA was lower for CHD in the a) left SLF, b) bilateral Anterior Corona Radiata (ACR) and left Retrolenticular part of the Internal Capsule (RIC). Vic was also lower for CHD in the left Posterior Limb of the Internal Capsule (PLIC). ODI was higher for CHD in the left CC. RTAP was lower for CHD in the left IFOF, while RTOP was lower in CHD in the: a) left ACR, b) left IFOF and c) right Anterior Limb of the Internal Capsule (ALIC). In this study, all three methods revealed the expected changes in the WM regions during the early postnatal weeks; however, GMM outperformed DTI and NODDI as it showed significantly larger effect sizes while detecting differences between the TDC and CHD neonates. Future studies based on a larger sample are needed to confirm these results and to explore clinical correlates. Determine developmental trajectories of several white matter regions in typically developing neonates. Compare white matter abnormalities in brain regions between congenital heart disease neonates and typically developing controls. Compare DTI, NODDI and Gaussian mixture model (GMM) and found GMM to be most sensitive to tissue abnormalities.
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