Lee Kevin, Cherel Marie, Budin Francois, Gilmore John, Consing Kirsten Zaldarriaga, Rasmussen Jerod, Wadhwa Pathik D, Entringer Sonja, Glasser Matthew F, Van Essen David C, Buss Claudia, Styner Martin
Department of Psychiatry, University of North Carolina, Chapel Hill.
Department of Pediatrics, University of California, Irvine.
Proc SPIE Int Soc Opt Eng. 2015;9417. doi: 10.1117/12.2082198. Epub 2015 Mar 17.
To develop and evaluate a novel processing framework for the relative quantification of myelin content in cerebral white matter (WM) regions from brain MRI data via a computed ratio of T1 to T2 weighted intensity values.
We employed high resolution (1mm isotropic) T1 and T2 weighted MRI from 46 (28 male, 18 female) neonate subjects (typically developing controls) scanned on a Siemens Tim Trio 3T at UC Irvine.
We developed a novel, yet relatively straightforward image processing framework for WM myelin content estimation based on earlier work by Glasser et al. We first co-register the structural MRI data to correct for motion. Then, background areas are masked out via a joint T1w and T2 foreground mask computed. Raw T1w/T2w-ratios images are computed next. For purpose of calibration across subjects, we first coarsely segment the fat-rich facial regions via an atlas co-registration. Linear intensity rescaling based on median T1w/T2w-ratio values in those facial regions yields calibrated T1w/T2w-ratio images. Mean values in lobar regions are evaluated using standard statistical analysis to investigate their interaction with age at scan.
Several lobes have strongly positive significant interactions of age at scan with the computed T1w/T2w-ratio. Most regions do not show sex effects. A few regions show no measurable effects of change in myelin content change within the first few weeks of postnatal development, such as cingulate and CC areas, which we attribute to sample size and measurement variability.
We developed and evaluated a novel way to estimate white matter myelin content for use in studies of brain white matter development.
通过计算T1加权与T2加权强度值的比率，开发并评估一种用于从脑MRI数据中相对定量脑白质（WM）区域髓磷脂含量的新型处理框架。
我们使用了来自46名（28名男性，18名女性）新生儿受试者（典型发育对照组）的高分辨率（各向同性1mm）T1加权和T2加权MRI，这些受试者在加州大学欧文分校的西门子Tim Trio 3T磁共振成像仪上进行扫描。
基于Glasser等人的早期工作，我们开发了一种新颖但相对简单的图像处理框架，用于估计WM髓磷脂含量。我们首先对结构MRI数据进行配准以校正运动。然后，通过计算联合T1加权和T2前景掩码来屏蔽背景区域。接下来计算原始T1加权/T2加权比率图像。为了在受试者之间进行校准，我们首先通过图谱配准粗略分割富含脂肪的面部区域。基于这些面部区域的T1加权/T2加权比率中值进行线性强度重新缩放，得到校准后的T1加权/T2加权比率图像。使用标准统计分析评估叶区域的平均值，以研究它们与扫描时年龄的相互作用。
几个脑叶在扫描时年龄与计算出的T1加权/T2加权比率之间具有强正显著相互作用。大多数区域没有显示出性别效应。少数区域在出生后发育的最初几周内未显示出髓磷脂含量变化的可测量效应，如扣带回和胼胝体区域，我们将其归因于样本量和测量变异性。
我们开发并评估了一种用于估计脑白质髓磷脂含量的新方法，可用于脑白质发育研究。
