Suppr超能文献

MRI 扫描仪移位后的重测信度和样本量估计。

Test-retest reliability and sample size estimates after MRI scanner relocation.

机构信息

Department of Medicine, University of Otago, Christchurch, New Zealand; New Zealand Brain Research Institute, Christchurch, New Zealand; Brain Research New Zealand - Rangahau Roro Aotearoa Centre of Research Excellence, New Zealand.

New Zealand Brain Research Institute, Christchurch, New Zealand; Department of Radiology, Christchurch Hospital, Christchurch, New Zealand; Pacific Radiology Group, Christchurch, New Zealand.

出版信息

Neuroimage. 2020 May 1;211:116608. doi: 10.1016/j.neuroimage.2020.116608. Epub 2020 Feb 4.

Abstract

OBJECTIVE

Many factors can contribute to the reliability and robustness of MRI-derived metrics. In this study, we assessed the reliability and reproducibility of three MRI modalities after an MRI scanner was relocated to a new hospital facility.

METHODS

Twenty healthy volunteers (12 females, mean age (standard deviation) ​= ​41 (11) years, age range [25-66]) completed three MRI sessions. The first session (S1) was one week prior to the 3T GE HDxt scanner relocation. The second (S2) occurred nine weeks after S1 and at the new location; a third session (S3) was acquired 4 weeks after S2. At each session, we acquired structural T1-weighted, pseudo-continuous arterial spin labelled, and diffusion tensor imaging sequences. We used longitudinal processing streams to create 12 summary MRI metrics, including total gray matter (GM), cortical GM, subcortical GM, white matter (WM), and lateral ventricle volume; mean cortical thickness; total surface area; average gray matter perfusion, and average diffusion tensor metrics along principal white matter pathways. We compared mean MRI values and variance at the old scanner location to multiple sessions at the new location using Bayesian multi-level regression models. K-fold cross validation allowed identification of important predictors. Whole-brain analyses were used to investigate any regional differences. Furthermore, we calculated within-subject coefficient of variation (wsCV), intraclass correlation coefficient (ICC), and dice similarity index (SI) of cortical segmentations across scanner relocation and within-site. Additionally, we estimated sample sizes required to robustly detect a 4% difference between two groups across MRI metrics.

RESULTS

All global MRI metrics exhibited little mean difference and small variability (bar cortical gray matter perfusion) both across scanner relocation and within-site repeat. T1- and DTI-derived tissue metrics showed ​< ​|0.3|% mean difference and <1.2% variance across scanner location and <|0.4|% mean difference and <0.8% variance within the new location, with between-site intraclass correlation coefficient (ICC) ​> ​0.80 and within-subject coefficient of variation (wsCV) ​< ​1.4%. Mean cortical gray matter perfusion had the highest between-session variability (6.7% [0.3, 16.7], estimate [95% uncertainty interval]), and hence the smallest ICC (0.71 [0.44,0.92]) and largest wsCV (13.4% [5.4, 18.1]). No global metric exhibited evidence of a meaningful mean difference between scanner locations. However, surface area showed evidence of a mean difference within-site repeat (between S2 and S3). Whole-brain analyses revealed no significant areas of difference between scanner relocation or within-site. For all metrics, we found no support for a systematic difference in variance across relocation sites compared to within-site test-retest reliability. Necessary sample sizes to detect a 4% difference between two independent groups varied from a maximum of n ​= ​362 per group (cortical gray matter perfusion), to total gray matter volume (n ​= ​114), average fractional anisotropy (n ​= ​23), total gray matter volume normalized by intracranial volume (n ​= ​19), and axial diffusivity (n ​= ​3 per group).

CONCLUSION

Cortical gray matter perfusion was the most variable metric investigated (necessitating large sample sizes to identify group differences), with other metrics showing substantially less variability. Scanner relocation appeared to have a negligible effect on variability of the global MRI metrics tested. This manuscript reports within-site test-retest variability to act as a tool for calculating sample size in future investigations. Our results suggest that when all other parameters are held constant (e.g., sequence parameters and MRI processing), the effect of scanner relocation is indistinguishable from within-site variability, but may need to be considered depending on the question being investigated.

摘要

目的

许多因素会影响 MRI 衍生指标的可靠性和稳健性。在这项研究中,我们评估了在将 MRI 扫描仪迁移到新医院设施后三种 MRI 模式的可靠性和可重复性。

方法

20 名健康志愿者(12 名女性,平均年龄(标准差)= 41(11)岁,年龄范围 [25-66])完成了三次 MRI 扫描。第一次扫描(S1)在 3T GE HDxt 扫描仪迁移前一周进行。第二次扫描(S2)在 S1 后 9 周且在新地点进行;第三次扫描(S3)在 S2 后 4 周进行。在每次扫描中,我们都采集了结构 T1 加权、伪连续动脉自旋标记和弥散张量成像序列。我们使用纵向处理流来创建 12 个总结 MRI 指标,包括总灰质(GM)、皮质 GM、皮质下 GM、白质(WM)和侧脑室容积;平均皮质厚度;总表面积;平均灰质灌注和沿主要白质通路的平均弥散张量指标。我们使用贝叶斯多级回归模型比较了旧扫描仪位置和新位置的多次扫描的平均 MRI 值和方差。K 折交叉验证允许确定重要的预测因素。全脑分析用于研究任何区域差异。此外,我们计算了皮质分割在扫描仪搬迁和内部站点内的个体内变异系数(wsCV)、组内相关系数(ICC)和骰子相似性指数(SI)。此外,我们还估计了在不同 MRI 指标之间检测到两组之间 4%差异所需的样本量。

结果

所有全局 MRI 指标在扫描仪搬迁和内部站点重复过程中都表现出较小的均值差异和较小的变异性(皮质 GM 灌注除外)。基于 T1 和 DTI 的组织指标在扫描仪位置之间显示出<|0.3|%的均值差异和<1.2%的方差,在新位置<|0.4|%的均值差异和<0.8%的方差,在站点间的组内相关系数(ICC)>0.80 和个体内变异系数(wsCV)<1.4%。平均皮质 GM 灌注具有最高的组间变异性(6.7%[0.3, 16.7],估计值[95%置信区间]),因此 ICC 最低(0.71[0.44,0.92]),wsCV 最高(13.4%[5.4, 18.1])。没有全局指标显示出在扫描仪位置之间存在有意义的均值差异。然而,表面积显示出在内部站点重复(S2 和 S3 之间)存在均值差异。全脑分析显示,在扫描仪搬迁或内部站点内均未发现明显的差异区域。对于所有指标,我们发现与内部站点测试-再测试可靠性相比,在搬迁站点之间没有系统的方差差异的支持。在两个独立组之间检测到 4%差异所需的最大样本量从皮质 GM 灌注的最大 n=362 个(n=362)到总灰质体积(n=114)、平均分数各向异性(n=23)、总灰质体积除以颅内体积(n=19)和轴向扩散率(每组 n=3)。

结论

皮质 GM 灌注是研究中最具变异性的指标(需要大量样本量才能识别组间差异),其他指标的变异性要小得多。扫描仪搬迁似乎对所测试的全局 MRI 指标的变异性几乎没有影响。本研究报告了内部站点测试-再测试变异性,作为未来研究中计算样本量的工具。我们的结果表明,当其他所有参数保持不变(例如,序列参数和 MRI 处理)时,扫描仪搬迁的影响与内部站点变异性无法区分,但根据正在研究的问题,可能需要考虑。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验