An evaluation of automated tracing for orbitofrontal cortex sulcogyral pattern typing.

An evaluation of automated tracing for orbitofrontal cortex sulcogyral pattern typing.
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DOI:
10.1016/j.jneumeth.2019.108386
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发表时间:
2019-10-01
影响因子:
3
通讯作者:
Troiani V
Troiani V
中科院分区:
医学4区
文献类型:
--
作者:
Snyder W;Patti M;Troiani V

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由内侧和外侧眶额沟(MOS和LOS)形成的定型眶额皮质(OFC)沟回模式的特征可以用来表征个体差异;然而,在实践中,解剖学分类的可靠性和可重复性存在问题,因为目前的方法依赖于人工追踪。我们评估了自动追踪程序是否有助于表征OFC的神经循环模式。从已出版的双相情感障碍、精神分裂症和典型对照患者的手动OFC追踪和特征收集中选出100名受试者,用于评估使用BrainVISA Morphologist Pipeline实现的自动追踪程序。发现内侧(MOSc/MOSr)和外侧(LOSc/LOSr)眶额沟的尾侧和吻侧段,以及中间(IOS)和横向眶额沟(TOS)的自动示踪可以准确识别OFC沟,准确描绘沟的连续性,并可靠地为手动沟回模式表征提供信息。自动示踪产生了明显相似的OFC沟示踪,消除了定位沟的主观影响。半自动管道的自动跟踪和人工时序模式表征可以消除手工管道最耗时的过程中直接输入的需要。结果表明,使用BrainVISA Morphologist的自动化OFC脑沟追踪方法在半自动化管道中表征OFC脑沟回模式是可行和有用的。自动化OFC沟槽追踪方法将提高沟槽特征的可靠性和可重复性,并且可以在更大的样本量中进行沟槽模式类型的表征,这是以前使用传统的人工追踪程序无法实现的。
Characterization of stereotyped orbitofrontal cortex (OFC) sulcogyral patterns formed by the medial and lateral orbitofrontal sulci (MOS and LOS) can be used to characterize individual variability; however, in practice, issues exist for reliability and reproducibility of anatomical classifications, as current methods rely on manual tracing. We assessed whether an automated tracing procedure would be useful for characterizing OFC sulcogyral patterns. 100 subjects from a published collection of manual OFC tracings and characterizations of patients with bipolar disorder, schizophrenia, and typical controls were used to evaluate an automated tracing procedure implemented using the BrainVISA Morphologist Pipeline. Automated tracings of caudal and rostral segments of the medial (MOSc/MOSr) and lateral (LOSc/LOSr) orbitofrontal sulci, as well as the intermediate (IOS) and transverse orbitofrontal sulci (TOS) were found to accurately identify OFC sulci, accurately portray sulci continuity, and reliably inform manual sulcogyral pattern characterization. Automated tracings produced visibly similar tracings of OFC sulci and removed subjective influence from locating sulci. The semi-automated pipeline of automated tracing and manual sulcogyral pattern characterization can eliminate the need for direct input during the most time-consuming process of the manual pipeline. The results suggest that automated OFC sulci tracing methods using BrainVISA Morphologist are feasible and useful in a semi-automated pipeline to characterize OFC sulcogyral patterns. Automated OFC sulci tracing methods will improve reliability and reproducibility of sulcogyral characterizations and can allow for characterizations of sulcal patterns types in larger sample sizes, previously unattainable using traditional manual tracing procedures.
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