Su Yi, Blazey Tyler M, Owen Christopher J, Christensen Jon J, Friedrichsen Karl, Joseph-Mathurin Nelly, Wang Qing, Hornbeck Russ C, Ances Beau M, Snyder Abraham Z, Cash Lisa A, Koeppe Robert A, Klunk William E, Galasko Douglas, Brickman Adam M, McDade Eric, Ringman John M, Thompson Paul M, Saykin Andrew J, Ghetti Bernardino, Sperling Reisa A, Johnson Keith A, Salloway Stephen P, Schofield Peter R, Masters Colin L, Villemagne Victor L, Fox Nick C, Förster Stefan, Chen Kewei, Reiman Eric M, Xiong Chengjie, Marcus Daniel S, Weiner Michael W, Morris John C, Bateman Randall J, Benzinger Tammie L S
Department of Radiology, Washington University School of Medicine, Saint Louis, Missouri, United States of America.
Department of Neurology, Washington University School of Medicine, Saint Louis, Missouri, United States of America.
PLoS One. 2016 Mar 24;11(3):e0152082. doi: 10.1371/journal.pone.0152082. eCollection 2016.
Amyloid imaging plays an important role in the research and diagnosis of dementing disorders. Substantial variation in quantitative methods to measure brain amyloid burden exists in the field. The aim of this work is to investigate the impact of methodological variations to the quantification of amyloid burden using data from the Dominantly Inherited Alzheimer's Network (DIAN), an autosomal dominant Alzheimer's disease population. Cross-sectional and longitudinal [11C]-Pittsburgh Compound B (PiB) PET imaging data from the DIAN study were analyzed. Four candidate reference regions were investigated for estimation of brain amyloid burden. A regional spread function based technique was also investigated for the correction of partial volume effects. Cerebellar cortex, brain-stem, and white matter regions all had stable tracer retention during the course of disease. Partial volume correction consistently improves sensitivity to group differences and longitudinal changes over time. White matter referencing improved statistical power in the detecting longitudinal changes in relative tracer retention; however, the reason for this improvement is unclear and requires further investigation. Full dynamic acquisition and kinetic modeling improved statistical power although it may add cost and time. Several technical variations to amyloid burden quantification were examined in this study. Partial volume correction emerged as the strategy that most consistently improved statistical power for the detection of both longitudinal changes and across-group differences. For the autosomal dominant Alzheimer's disease population with PiB imaging, utilizing brainstem as a reference region with partial volume correction may be optimal for current interventional trials. Further investigation of technical issues in quantitative amyloid imaging in different study populations using different amyloid imaging tracers is warranted.
淀粉样蛋白成像在痴呆症的研究和诊断中起着重要作用。该领域在测量脑淀粉样蛋白负荷的定量方法上存在很大差异。这项工作的目的是利用来自显性遗传阿尔茨海默病网络（DIAN）（一种常染色体显性阿尔茨海默病群体）的数据，研究方法差异对淀粉样蛋白负荷定量的影响。对来自DIAN研究的横断面和纵向[11C] - 匹兹堡化合物B（PiB）PET成像数据进行了分析。研究了四个候选参考区域以估计脑淀粉样蛋白负荷。还研究了一种基于区域扩散函数的技术用于校正部分容积效应。在疾病过程中，小脑皮质、脑干和白质区域的示踪剂滞留均稳定。部分容积校正持续提高了对组间差异和随时间纵向变化的敏感性。白质参照提高了检测相对示踪剂滞留纵向变化的统计功效；然而，这种改善的原因尚不清楚，需要进一步研究。全动态采集和动力学建模提高了统计功效，尽管这可能会增加成本和时间。本研究考察了淀粉样蛋白负荷定量的几种技术差异。部分容积校正成为最能持续提高检测纵向变化和组间差异统计功效的策略。对于采用PiB成像的常染色体显性阿尔茨海默病群体，将脑干作为参考区域并进行部分容积校正可能是当前干预试验的最佳选择。有必要进一步研究使用不同淀粉样蛋白成像示踪剂在不同研究群体中进行定量淀粉样蛋白成像的技术问题。
