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On the reproducibility of in vivo temporal signal-to-noise ratio and its utility as a predictor of subject-level t-values in a functional magnetic resonance imaging study
International Journal of Imaging Systems and Technology ( IF 3.0 ) Pub Date : 2021-06-29 , DOI: 10.1002/ima.22617
Susanna Gobbi 1 , Yoojin Lee 1 , István Homolya 2 , Philippe N. Tobler 1 , Todd A. Hare 1 , Zoltan Nagy 1
Affiliation  

The aim of this study was to evaluate the reproducibility of voxel-wise temporal signal-to-noise ratio (tSNR) on repeated scans across runs, sessions, and days. A group of 21 participants was scanned 16 times (4 runs per session, 2 sessions per day, 2 separate days) in a functional magnetic resonance imaging (fMRI) study on a 3T Philips Achieva scanner. For each run, we calculated t-value and tSNR maps. To ascertain that the results were not specific to the scanner, one volunteer was scanned with four fMRI runs in a single session on the above 3T Philips scanner as well as a 3T Siemens Prisma scanner. The coefficient of variation of voxel-wise tSNR across the 16 repeats was up to 25%, while the range relative to the mean of all observations was up to 80%. The voxel-wise variability of tSNR on the two different scanners was similar, indicating a general issue. Despite its use in evaluating the quality of fMRI data, we found only a weak relationship between tSNR and t-values. There is very high variability in voxel-wise tSNR, which should be considered while planning future studies that aim to identify small and focal fMRI effects or the benefits of incremental improvement in methods.

中文翻译:

关于体内时间信噪比的再现性及其作为功能磁共振成像研究中受试者水平 t 值预测因子的效用

本研究的目的是评估体素时间信噪比 (tSNR) 在跨运行、会话和天重复扫描时的再现性。在 3T 飞利浦 Achieva 扫描仪上进行的功能磁共振成像 (fMRI) 研究中,一组 21 名参与者被扫描了 16 次(每节 4 次,每天 2 节,2 天)。对于每次运行,我们计算了 t 值和 tSNR 图。为了确定结果不是特定于扫描仪的,一名志愿者在上述 3T 飞利浦扫描仪和 3T Siemens Prisma 扫描仪上在一次会话中进行了四次 fMRI 运行扫描。16 次重复中体素 tSNR 的变异系数高达 25%,而相对于所有观察平均值的范围高达 80%。两种不同扫描仪上 tSNR 的体素变异性相似,表示一般问题。尽管它用于评估 fMRI 数据的质量,但我们发现 tSNR 和 t 值之间的关系很弱。体素 tSNR 的变异性非常高,在规划旨在识别小而焦点 fMRI 效应或方法增量改进的好处的未来研究时应考虑到这一点。
更新日期:2021-06-29
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