Geisinger-Bucknell Autism & Developmental Medicine Institute, Lewisburg, PA United States.
Geisinger-Bucknell Autism & Developmental Medicine Institute, Lewisburg, PA United States.
J Neurosci Methods. 2019 Oct 1;326:108386. doi: 10.1016/j.jneumeth.2019.108386. Epub 2019 Aug 1.
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.
通过内侧眶额沟(MOS)和外侧眶额沟(LOS)来对刻板的眶额皮质(OFC)脑回模式进行特征描述,可以用来对个体差异进行分类;然而,在实际应用中,目前的解剖学分类方法存在可靠性和可重复性的问题,因为这些方法依赖于手动追踪。
我们评估了自动化追踪程序是否可用于对 OFC 脑回模式进行特征描述。我们使用了发表的手动 OFC 追踪和双相障碍、精神分裂症和典型对照组患者 OFC 特征描述的集合中的 100 个主体,以评估使用 BrainVISA Morphologist Pipeline 实现的自动化追踪程序。
MOS 尾端和头端(MOSc/MOSr)、LOS 尾端和头端(LOSc/LOSr)、中间(IOS)和横向眶额沟(TOS)的自动追踪,准确地识别了 OFC 沟,准确地描绘了沟的连续性,并可靠地提供了手动脑回模式特征描述的信息。
自动追踪产生的 OFC 沟的轨迹与手动追踪相似,并且消除了定位沟时的主观影响。自动化追踪和手动脑回模式特征描述的半自动化流水线可以消除手动流水线中最耗时过程中直接输入的需要。
结果表明,使用 BrainVISA Morphologist 的自动 OFC 沟追踪方法在半自动流水线中是可行和有用的,可用于对 OFC 脑回模式进行特征描述。自动 OFC 沟追踪方法将提高脑回特征描述的可靠性和可重复性,并允许对以前使用传统手动追踪程序无法获得的更大样本量的脑沟模式类型进行特征描述。