Hogan R E, Wang L, Bertrand M E, Willmore L J, Bucholz R D, Nassif A S, Csernansky J G
Department of Neurology, Saint Louis University, St. Louis, MO, USA.
AJNR Am J Neuroradiol. 2006 Nov-Dec;27(10):2149-54.
We objectively assessed surface structural changes of the hippocampus in mesial temporal sclerosis (MTS) and assessed the ability of large-deformation high-dimensional mapping (HDM-LD) to demonstrate hippocampal surface symmetry and predict group classification of MTS in right and left MTS groups compared with control subjects.
Using eigenvector field analysis of HDM-LD segmentations of the hippocampus, we compared the symmetry of changes in the right and left MTS groups with a group of 15 matched controls. To assess the ability of HDM-LD to predict group classification, eigenvectors were selected by a logistic regression procedure when comparing the MTS group with control subjects.
Multivariate analysis of variance on the coefficients from the first 9 eigenvectors accounted for 75% of the total variance between groups. The first 3 eigenvectors showed the largest differences between the control group and each of the MTS groups, but with eigenvector 2 showing the greatest difference in the MTS groups. Reconstruction of the hippocampal deformation vector fields due solely to eigenvector 2 shows symmetrical patterns in the right and left MTS groups. A "leave-one-out" (jackknife) procedure correctly predicted group classification in 14 of 15 (93.3%) left MTS subjects and all 15 right MTS subjects.
Analysis of principal dimensions of hippocampal shape change suggests that MTS, after accounting for normal right-left asymmetries, affects the right and left hippocampal surface structure very symmetrically. Preliminary analysis using HDM-LD shows it can predict group classification of MTS and control hippocampi in this well-defined population of patients with MTS and mesial temporal lobe epilepsy (MTLE).
我们客观评估了内侧颞叶硬化(MTS)中海马的表面结构变化,并评估了大变形高维映射(HDM-LD)展示海马表面对称性以及预测MTS左右组与对照组之间MTS组分类的能力。
利用海马HDM-LD分割的特征向量场分析,我们将MTS左右组的变化对称性与一组15名匹配的对照组进行了比较。为了评估HDM-LD预测组分类的能力,在将MTS组与对照组进行比较时,通过逻辑回归程序选择特征向量。
对前9个特征向量的系数进行多变量方差分析,占组间总方差的75%。前3个特征向量在对照组与每个MTS组之间显示出最大差异,但特征向量2在MTS组中显示出最大差异。仅由特征向量2引起的海马变形向量场重建在MTS左右组中显示出对称模式。“留一法”(刀切法)程序在15名左侧MTS受试者中的14名(93.3%)以及所有15名右侧MTS受试者中正确预测了组分类。
海马形状变化主要维度的分析表明,在考虑正常左右不对称后,MTS非常对称地影响左右海马表面结构。使用HDM-LD的初步分析表明,它可以在这一明确的MTS和内侧颞叶癫痫(MTLE)患者群体中预测MTS和对照海马的组分类。