Thompson Paul M, Hayashi Kiralee M, De Zubicaray Greig I, Janke Andrew L, Rose Stephen E, Semple James, Hong Michael S, Herman David H, Gravano David, Doddrell David M, Toga Arthur W
Laboratory of Neuro Imaging, Brain Mapping Division, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA.
Neuroimage. 2004 Aug;22(4):1754-66. doi: 10.1016/j.neuroimage.2004.03.040.
We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Sixty-two [corrected] high-resolution MRI scans were acquired from 12 AD patients (mean [corrected] age +/- SE at first scan: 68.7 +/- 1.7 [corrected] years) and 14 matched controls (age: 71.4 +/- 0.9 years) [corrected] each scanned twice (1.9 +/- 0.2 [corrected] years apart, when all subjects are pooled [corrected] 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.
我们开发了一种解剖学映射技术,以检测阿尔茨海默病(AD)患者海马体和脑室的变化。随着疾病进展,生成的图谱对脑结构的纵向变化具有敏感性。将解剖学表面建模方法与基于表面的统计方法相结合,以可视化连续MRI扫描中的萎缩区域和速率,并确定这些变化与认知衰退的关联位置。从12名AD患者(首次扫描时的平均[校正后]年龄±标准误:68.7±1.7[校正后]岁)和14名匹配的对照者(年龄:71.4±0.9岁)[校正后]中获取了62次[校正后]高分辨率MRI扫描,每人扫描两次(间隔1.9±0.2[校正后]年,当所有受试者合并时)[校正后]在连续扫描中创建海马体和颞角的3D参数网格模型,并对受试者进行平均以识别萎缩的系统模式。作为径向萎缩的指标,生成了3D距离场,将每个解剖表面点与沿着每个结构中轴线向下延伸的内侧曲线相关联。使用基于表面的置换检验对海马体萎缩率和脑室扩张进行统计学评估,结果显示AD患者比对照组更快。通过颜色编码图谱和视频序列,随着时间的推移,这些变化在解剖学上的进展得以可视化。额外的图谱定位了萎缩变化与认知衰退相关的区域。颞角扩张图谱比海马体萎缩图谱对AD进展更敏感,但两种图谱均与临床恶化相关。这些对衰老和AD中海马体萎缩和脑室扩张率的定量、动态可视化,可能为药物试验中追踪AD进展提供一种有前景的测量方法。