Section for Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Neurobiol Aging. 2012 Dec;33(12):2733-45. doi: 10.1016/j.neurobiolaging.2012.01.010. Epub 2012 Feb 24.
This article investigates longitudinal imaging characteristics of early cognitive decline during normal aging, leveraging on high-dimensional imaging pattern classification methods for the development of early biomarkers of cognitive decline. By combining magnetic resonance imaging (MRI) and resting positron emission tomography (PET) cerebral blood flow (CBF) images, an individualized score is generated using high-dimensional pattern classification, which predicts subsequent cognitive decline in cognitively normal older adults of the Baltimore Longitudinal Study of Aging. The resulting score, termed SPARE-CD (Spatial Pattern of Abnormality for Recognition of Early Cognitive Decline), analyzed longitudinally for 143 cognitively normal subjects over 8 years, shows functional and structural changes well before (2.3-2.9 years) changes in neurocognitive testing (California Verbal Learning Test [CVLT] scores) can be measured. Additionally, this score is found to be correlated to the [(11)C] Pittsburgh compound B (PiB) PET mean distribution volume ratio at a later time. This work indicates that MRI and PET images, combined with advanced pattern recognition methods, may be useful for very early detection of cognitive decline.
本文研究了正常衰老过程中早期认知能力下降的纵向影像学特征,利用高维影像模式分类方法来开发认知能力下降的早期生物标志物。通过结合磁共振成像(MRI)和静息正电子发射断层扫描(PET)脑血流(CBF)图像,使用高维模式分类生成一个个体化评分,该评分可预测巴尔的摩老龄化纵向研究中认知正常的老年人随后的认知能力下降。所得评分称为 SPARE-CD(用于识别早期认知下降的异常空间模式),对 143 名认知正常的受试者进行了 8 年的纵向分析,显示出功能和结构的变化早于神经认知测试(加利福尼亚语言学习测试[CVLT]分数)的变化(2.3-2.9 年)可以测量。此外,该评分还与以后的[(11)C]匹兹堡化合物 B(PiB)PET 平均分布容积比相关。这项工作表明,MRI 和 PET 图像结合先进的模式识别方法,可能有助于非常早期检测认知能力下降。