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儿童磁共振图像中的海马体和杏仁核体积:评估FreeSurfer和FSL相对于手动分割的准确性。

Hippocampus and amygdala volumes from magnetic resonance images in children: Assessing accuracy of FreeSurfer and FSL against manual segmentation.

作者信息

Schoemaker Dorothee, Buss Claudia, Head Kevin, Sandman Curt A, Davis Elysia P, Chakravarty M Mallar, Gauthier Serge, Pruessner Jens C

机构信息

McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada; Douglas Hospital Research Centre, Psychiatry Department, McGill University, Montreal, QC, Canada.

University of California at Irvine, CA, USA; Charité, Berlin, Germany.

出版信息

Neuroimage. 2016 Apr 1;129:1-14. doi: 10.1016/j.neuroimage.2016.01.038. Epub 2016 Jan 26.

Abstract

The volumetric quantification of brain structures is of great interest in pediatric populations because it allows the investigation of different factors influencing neurodevelopment. FreeSurfer and FSL both provide frequently used packages for automatic segmentation of brain structures. In this study, we examined the accuracy and consistency of those two automated protocols relative to manual segmentation, commonly considered as the "gold standard" technique, for estimating hippocampus and amygdala volumes in a sample of preadolescent children aged between 6 to 11 years. The volumes obtained with FreeSurfer and FSL-FIRST were evaluated and compared with manual segmentations with respect to volume difference, spatial agreement and between- and within-method correlations. Results highlighted a tendency for both automated techniques to overestimate hippocampus and amygdala volumes, in comparison to manual segmentation. This was more pronounced when using FreeSurfer than FSL-FIRST and, for both techniques, the overestimation was more marked for the amygdala than the hippocampus. Pearson correlations support moderate associations between manual tracing and FreeSurfer for hippocampus (right r=0.69, p<0.001; left r=0.77, p<0.001) and amygdala (right r=0.61, p<0.001; left r=0.67, p<0.001) volumes. Correlation coefficients between manual segmentation and FSL-FIRST were statistically significant (right hippocampus r=0.59, p<0.001; left hippocampus r=0.51, p<0.001; right amygdala r=0.35, p<0.001; left amygdala r=0.31, p<0.001) but were significantly weaker, for all investigated structures. When computing intraclass correlation coefficients between manual tracing and automatic segmentation, all comparisons, except for left hippocampus volume estimated with FreeSurfer, failed to reach 0.70. When looking at each method separately, correlations between left and right hemispheric volumes showed strong associations between bilateral hippocampus and bilateral amygdala volumes when assessed using manual segmentation or FreeSurfer. These correlations were significantly weaker when volumes were assessed with FSL-FIRST. Finally, Bland-Altman plots suggest that the difference between manual and automatic segmentation might be influenced by the volume of the structure, because smaller volumes were associated with larger volume differences between techniques. These results demonstrate that, at least in a pediatric population, the agreement between amygdala and hippocampus volumes obtained with automated FSL-FIRST and FreeSurfer protocols and those obtained with manual segmentation is not strong. Visual inspection by an informed individual and, if necessary, manual correction of automated segmentation outputs are important to ensure validity of volumetric results and interpretation of related findings.

摘要

脑结构的体积定量分析在儿科人群中具有重要意义,因为它有助于研究影响神经发育的不同因素。FreeSurfer和FSL都提供了常用的脑结构自动分割软件包。在本研究中,我们检验了这两种自动化方案相对于通常被视为“金标准”技术的手动分割的准确性和一致性,以估计6至11岁青春期前儿童样本中海马体和杏仁核的体积。对通过FreeSurfer和FSL-FIRST获得的体积进行了评估,并在体积差异、空间一致性以及方法间和方法内相关性方面与手动分割进行了比较。结果表明,与手动分割相比,两种自动化技术都有高估海马体和杏仁核体积的趋势。使用FreeSurfer时这种情况比使用FSL-FIRST时更明显,并且对于两种技术而言,杏仁核的高估比海马体更显著。Pearson相关性支持手动追踪与FreeSurfer在海马体(右侧r = 0.69,p < 0.001;左侧r = 0.77,p < 0.001)和杏仁核(右侧r = 0.61,p < 0.001;左侧r = 0.67,p < 0.001)体积上的中度关联。手动分割与FSL-FIRST之间的相关系数具有统计学意义(右侧海马体r = 0.59,p < 0.001;左侧海马体r = 0.51,p < 0.001;右侧杏仁核r = 0.35,p < 0.001;左侧杏仁核r = 0.31,p < 0.001),但对于所有研究结构而言,其相关性明显较弱。在计算手动追踪与自动分割之间的组内相关系数时,除了用FreeSurfer估计的左侧海马体体积外,所有比较均未达到0.70。当分别查看每种方法时,在使用手动分割或FreeSurfer评估时,左右半球体积之间的相关性显示双侧海马体和双侧杏仁核体积之间存在强关联。当用FSL-FIRST评估体积时,这些相关性明显较弱。最后,Bland-Altman图表明,手动分割与自动分割之间的差异可能受结构体积的影响,因为较小的体积与技术之间较大的体积差异相关。这些结果表明,至少在儿科人群中,通过自动化的FSL-FIRST和FreeSurfer方案获得的杏仁核和海马体体积与通过手动分割获得的体积之间的一致性不强。由专业人员进行视觉检查,并在必要时对手动分割输出进行手动校正,对于确保体积测量结果的有效性和相关研究结果的解释非常重要。

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