Pienaar R, Fischl B, Caviness V, Makris N, Grant P E
Int J Imaging Syst Technol. 2008 Jun 1;18(1):42-68. doi: 10.1002/ima.v18:1.
The character and timing of gyral development is one manifestation of the complex orchestration of human brain development. The ability to quantify these changes would not only allow for deeper understanding of cortical development, but also conceivably allow for improved detection of pathologies. This paper describes a FreeSurfer based image-processing analysis "pipeline" or methodology that inputs an MRI volume, corrects possible contrast defects, creates surface reconstructions, and outputs various curvature-based function analyses. A technique of performing neonate reconstructions using FreeSurfer, which has not been possible previously due to inverted image contrast in pre-myelinated brains, is described. Once surfaces are reconstructed, the analysis component of the pipeline incorporates several surface-based curvature functions found in literature (principle curvatures, Gaussian, mean curvature, "curvedness", and Willmore Bending Energy). We consider the problem of analyzing curvatures from different sized brains by introducing a Gaussian-curvature based variable-radius filter. Segmented volume data is also analyzed for folding measures: a gyral folding index (gyrification-white index GWI), and a gray-white matter junction folding index (WMF). A very simple curvature-based classifier is proposed that has the potential to discriminate between certain classes of subjects. We also present preliminary results of this curvature analysis pipeline on nine neonate subjects (30.4 weeks through 40.3 weeks Corrected Gestational Age), 3 children (2, 3, and 7 years) and 3 adults (33, 37, and 39 years). Initial results demonstrate that curvature measures and functions across our subjects peaked at term, with a gradual decline through early childhood and further decline continuing through to adults. We can also discriminate older neonates, children, and adults based on curvature analysis. Using a variable radius Gaussian-curvature filter, we also observed that the per-unit bending energy of neonate brain surfaces was also much higher than the children and adults.
脑回发育的特征和时间是人类大脑发育复杂协调过程的一种表现。量化这些变化的能力不仅有助于更深入地理解皮层发育，还可能改善对病变的检测。本文描述了一种基于FreeSurfer的图像处理分析“流程”或方法，该方法输入MRI体积数据，校正可能的对比度缺陷，创建表面重建，并输出各种基于曲率的功能分析。文中还描述了一种使用FreeSurfer进行新生儿重建的技术，由于未髓鞘化大脑中的图像对比度倒置，以前无法实现这一点。一旦表面重建完成，该流程的分析组件会纳入文献中发现的几种基于表面的曲率函数（主曲率、高斯曲率、平均曲率、“弯曲度”和威尔莫尔弯曲能量）。我们通过引入基于高斯曲率的可变半径滤波器来考虑分析不同大小大脑曲率的问题。还对分割后的体积数据进行折叠测量分析：脑回折叠指数（脑回化-白质指数GWI）和灰白质交界折叠指数（WMF）。提出了一种非常简单的基于曲率的分类器，它有可能区分某些类别的受试者。我们还展示了该曲率分析流程对9名新生儿受试者（矫正胎龄30.4周至40.3周）、3名儿童（2岁、3岁和7岁）和3名成人（33岁、37岁和39岁）的初步结果。初步结果表明，我们受试者的曲率测量值和功能在足月时达到峰值，在幼儿期逐渐下降，并在成年期继续进一步下降。我们还可以通过曲率分析区分年龄较大的新生儿、儿童和成人。使用可变半径高斯曲率滤波器，我们还观察到新生儿脑表面的单位弯曲能量也远高于儿童和成人。
