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合并形态测量估计值:一种统计等效性方法。

Pooling Morphometric Estimates: A Statistical Equivalence Approach.

作者信息

Pardoe Heath R, Cutter Gary R, Alter Rachel, Hiess Rebecca Kucharsky, Semmelroch Mira, Parker Donna, Farquharson Shawna, Jackson Graeme D, Kuzniecky Ruben

机构信息

Department of Neurology, Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY.

School of Public Health, University of Alabama at Birmingham, Birmingham, AL.

出版信息

J Neuroimaging. 2016 Jan-Feb;26(1):109-15. doi: 10.1111/jon.12265. Epub 2015 Jun 21.

Abstract

Changes in hardware or image-processing settings are a common issue for large multicenter studies. To pool MRI data acquired under these changed conditions, it is necessary to demonstrate that the changes do not affect MRI-based measurements. In these circumstances, classical inference testing is inappropriate because it is designed to detect differences, not prove similarity. We used a method known as statistical equivalence testing to address this limitation. Equivalence testing was carried out on 3 datasets: (1) cortical thickness and automated hippocampal volume estimates obtained from healthy individuals imaged using different multichannel head coils; (2) manual hippocampal volumetry obtained using two readers; and (3) corpus callosum area estimates obtained using an automated method with manual cleanup carried out by two readers. Equivalence testing was carried out using the "two one-sided tests" (TOST) approach. Power analyses of the TOST were used to estimate sample sizes required for well-powered equivalence testing analyses. Mean and standard deviation estimates from the automated hippocampal volume dataset were used to carry out an example power analysis. Cortical thickness values were found to be equivalent over 61% of the cortex when different head coils were used (q < .05, false discovery rate correction). Automated hippocampal volume estimates obtained using the same two coils were statistically equivalent (TOST P = 4.28 × 10(-15) ). Manual hippocampal volume estimates obtained using two readers were not statistically equivalent (TOST P = .97). The use of different readers to carry out limited correction of automated corpus callosum segmentations yielded equivalent area estimates (TOST P = 1.28 × 10(-14) ). Power analysis of simulated and automated hippocampal volume data demonstrated that the equivalence margin affects the number of subjects required for well-powered equivalence tests. We have presented a statistical method for determining if morphometric measures obtained under variable conditions can be pooled. The equivalence testing technique is applicable for analyses in which experimental conditions vary over the course of the study.

摘要

硬件或图像处理设置的变化是大型多中心研究中常见的问题。为了汇总在这些变化条件下采集的MRI数据,有必要证明这些变化不会影响基于MRI的测量。在这种情况下,经典的推断测试并不合适,因为它旨在检测差异,而不是证明相似性。我们使用了一种称为统计等效性测试的方法来解决这一局限性。对3个数据集进行了等效性测试:(1) 从使用不同多通道头部线圈成像的健康个体获得的皮质厚度和自动海马体积估计值;(2) 由两名读者获得的手动海马体积测量值;(3) 使用自动方法并由两名读者进行手动清理获得的胼胝体面积估计值。使用 “双单侧检验”(TOST)方法进行等效性测试。TOST的功效分析用于估计有效等效性测试分析所需的样本量。使用自动海马体积数据集的均值和标准差估计值进行了一个示例功效分析。当使用不同的头部线圈时,发现超过61% 的皮质的皮质厚度值是等效的(q <.05,错误发现率校正)。使用相同的两个线圈获得的自动海马体积估计值在统计学上是等效的(TOST P = 4.28 × 10(-15))。由两名读者获得的手动海马体积估计值在统计学上不等效(TOST P =.97)。使用不同的读者对自动胼胝体分割进行有限校正产生了等效的面积估计值(TOST P = 1.28 × 10(-14))。对模拟和自动海马体积数据的功效分析表明,等效性边界会影响有效等效性测试所需的受试者数量。我们提出了一种统计方法,用于确定在可变条件下获得的形态测量指标是否可以汇总。等效性测试技术适用于实验条件在研究过程中发生变化的分析。

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