Quantitative assessment of structural image quality.
Quantitative assessment of structural image quality.
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DOI：
10.1016/j.neuroimage.2017.12.059
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发表时间：
2018-04-01
期刊：
影响因子：
5.7
通讯作者：
Satterthwaite TD
中科院分区：
文献类型：
--
作者：
Rosen AFG;Roalf DR;Ruparel K;Blake J;Seelaus K;Villa LP;Ciric R;Cook PA;Davatzikos C;Elliott MA;Garcia de La Garza A;Gennatas ED;Quarmley M;Schmitt JE;Shinohara RT;Tisdall MD;Craddock RC;Gur RE;Gur RC;Satterthwaite TD
数据质量越来越被认为是脑成像研究中最重要的混杂因素之一。这对大脑发育的研究尤其重要，因为年龄与扫描仪内的运动和数据质量有系统的关系。先前的工作已经证明，扫描仪中的头部运动会对结构性神经成像措施的估计产生偏差。然而，对于大多数结构脑图像来说，数据质量的客观衡量是不可用的。在这里，我们试图确定T1加权体积的数据质量的量化指标，描述这些质量指标如何与皮质厚度相关，并描绘出这反过来可能如何偏向与青年年龄相关的推断。三名训练有素的评分员提供了1840份原始T1加权卷的手动评级。这些图像包括来自费城神经发育队列(PNC)的1065张图像的训练集，来自PNC的533张图像的测试集，以及由242名成年人组成的外部测试集，这些图像是在不同的扫描仪上获取的。将手动评级与由预处理Connectomes Project的质量保证协议(QAP)提供的自动质量测量以及Freesurfer的Euler数进行比较，后者总结了重建皮质表面的拓扑复杂性。结果显示，欧拉数与样本中的手动评级一致相关。此外，欧拉数可以用来识别由人类评分员以高精度(AUC：0.98-0.99)评分为“不可用”的图像，并且优于在同一扫描会话中获得的功能时间序列的代理测量。Euler数也与皮质厚度显著相关，这种区域异质性模式在数据集上是一致的，并复制了先前的结果。最后，在青春期，数据质量夸大和模糊了与年龄的联系。综上所述，这些结果表明，可以从T1加权体积自动得出可靠的数据质量衡量标准，如果不能控制数据质量，可能会系统性地偏离大脑成熟研究的结果。
Data quality is increasingly recognized as one of the most important confounding factors in brain imaging research. It is particularly important for studies of brain development, where age is systematically related to in-scanner motion and data quality. Prior work has demonstrated that in-scanner head motion biases estimates of structural neuroimaging measures. However, objective measures of data quality are not available for most structural brain images. Here we sought to identify quantitative measures of data quality for T1-weighted volumes, describe how such measures of quality relate to cortical thickness, and delineate how this in turn may bias inference regarding associations with age in youth. Three highly-trained raters provided manual ratings of 1,840 raw T1-weighted volumes. These images included a training set of 1,065 images from Philadelphia Neurodevelopmental Cohort (PNC), a test set of 533 images from the PNC, as well as an external test set of 242 adults acquired on a different scanner. Manual ratings were compared to automated quality measures provided by the Preprocessed Connectomes Project's Quality Assurance Protocol (QAP), as well as FreeSurfer's Euler number, which summarizes the topological complexity of the reconstructed cortical surface. Results revealed that the Euler number was consistently correlated with manual ratings across samples. Furthermore, the Euler number could be used to identify images scored “unusable” by human raters with a high degree of accuracy (AUC: 0.98-0.99), and out-performed proxy measures from functional timeseries acquired in the same scanning session. The Euler number also was significantly related to cortical thickness in a regionally heterogeneous pattern that was consistent across datasets and replicated prior results. Finally, data quality both inflated and obscured associations with age during adolescence. Taken together, these results indicate that reliable measures of data quality can be automatically derived from T1-weighted volumes, and that failing to control for data quality can systematically bias the results of studies of brain maturation.
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DOI：
10.1073/pnas.0402680101
发表时间：
2004-05-25
影响因子：
11.1
作者：
Gogtay, N;Giedd, JN;Thompson, PM
通讯作者：
Thompson, PM
影响因子：
5.7
作者：
Jenkinson, M;Bannister, P;Smith, S
通讯作者：
Smith, S
影响因子：
4.5
作者：
Forbes, Courtney;Blanchard, Jack J.;Bennett, Melanie;Horan, William P.;Kring, Ann;Gur, Raquel
通讯作者：
Gur, Raquel
影响因子：
3.5
作者：
Pizarro RA;Cheng X;Barnett A;Lemaitre H;Verchinski BA;Goldman AL;Xiao E;Luo Q;Berman KF;Callicott JH;Weinberger DR;Mattay VS
通讯作者：
Mattay VS
影响因子：
5.7
作者：
Lee, Jun Ki;Lee, Jong-Min;Kim, Sun I.
通讯作者：
Kim, Sun I.