Harris Ashley D, Puts Nicolaas A J, Wijtenburg S Andrea, Rowland Laura M, Mikkelsen Mark, Barker Peter B, Evans C John, Edden Richard A E
Department of Radiology, University of Calgary, Calgary, AB, Canada; Child and Adolescent Imaging Research (CAIR) Program, Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
Magn Reson Imaging. 2017 Oct;42:8-15. doi: 10.1016/j.mri.2017.04.013. Epub 2017 May 4.
Standardization of results is an important milestone in the maturation of any truly quantitative methodology. For instance, a lack of measurement agreement across imaging platforms limits multisite studies, between-study comparisons based on the literature, and inferences based on and the generalizability of results. In GABA-edited MEGA-PRESS, two key sources of differences between implementations are: differences in editing efficiency of GABA and the degree of co-editing of macromolecules (MM). In this work, GABA editing efficiency κ and MM-co-editing μ constants are determined for three widely used MEGA-PRESS implementations (on the most common MRI platforms; GE, Philips, and Siemens) by phantom experiments. Implementation-specific κ,μ-corrections were then applied to two in vivo datasets, one consisted of 8 subject scanned on the three platforms and the other one subject scanned eight times on each platform. Manufacturer-specific κ and μ values were determined as: κ=0.436, κ=0.366 and κ=0.394 and μ=0.83, μ=0.625 and μ=0.75. Applying the κ,μ-correction on the Cr-referenced data decreased the coefficient of variation (CV) of the data for both in vivo data sets (multisubjects: uncorrected CV=13%, κ,μ-corrected CV=5%, single subject: uncorrected CV=23%, κ,μ-corrected CV=13%) but had no significant effect on mean GABA levels. For the water-referenced results, CV increased in the multisubject data (uncorrected CV=6.7%, κ,μ-corrected CV=14%) while it decreased in the single subject data (uncorrected CV=24%, κ,μ-corrected CV=21%) and manufacturer was a significant source of variance in the κ,μ-corrected data. Applying a correction for editing efficiency and macromolecule contamination decreases the variance between different manufacturers for creatine-referenced data, but other sources of variance remain.
结果标准化是任何真正定量方法成熟过程中的一个重要里程碑。例如，不同成像平台之间缺乏测量一致性限制了多中心研究、基于文献的研究间比较以及基于结果的推断和结果的可推广性。在GABA编辑的MEGA-PRESS中，不同实现之间差异的两个关键来源是：GABA编辑效率的差异和大分子（MM）的共编辑程度。在这项工作中，通过体模实验确定了三种广泛使用的MEGA-PRESS实现（在最常见的MRI平台上；GE、飞利浦和西门子）的GABA编辑效率κ和MM共编辑μ常数。然后将特定于实现的κ，μ校正应用于两个体内数据集，一个由在三个平台上扫描的8名受试者组成，另一个由在每个平台上扫描8次的一名受试者组成。特定于制造商的κ和μ值确定为：κ = 0.436，κ = 0.366和κ = 0.394，μ = 0.83，μ = 0.625和μ = 0.75。对以肌酸为参考的数据应用κ，μ校正降低了两个体内数据集数据的变异系数（CV）（多受试者：未校正CV = 13%，κ，μ校正CV = 5%，单受试者：未校正CV = 23%，κ，μ校正CV = 13%），但对平均GABA水平没有显著影响。对于以水为参考的结果，多受试者数据中的CV增加（未校正CV = 6.7%，κ，μ校正CV = 14%），而单受试者数据中的CV降低（未校正CV = 24%，κ，μ校正CV = 21%），并且制造商是κ，μ校正数据中方差的一个重要来源。对编辑效率和大分子污染进行校正可减少不同制造商之间以肌酸为参考的数据的方差，但其他方差来源仍然存在。
