From the Nuffield Department of Clinical Neurosciences (B.S., G.D.), Oxford Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
Institute of Clinical Radiology (B.S., B.P.), Medical Faculty, University of Münster and University Hospital Münster, Münster, Germany.
AJNR Am J Neuroradiol. 2018 Dec;39(12):2326-2331. doi: 10.3174/ajnr.A5847. Epub 2018 Nov 1.
Functional MR imaging of the brain, used for both clinical and neuroscientific applications, relies on measuring fluctuations in blood oxygenation. Such measurements are susceptible to noise of vascular origin. The purpose of this study was to assess whether developmental venous anomalies, which are frequently observed normal variants, can bias fMRI measures by appearing as true neural signal.
Large developmental venous anomalies (1 in each of 14 participants) were identified from a large neuroimaging cohort ( = 814). Resting-state fMRI data were decomposed using independent component analysis, a data-driven technique that creates distinct component maps representing aspects of either structured noise or true neural activity. We searched all independent components for maps that exhibited a spatial distribution of their signals following the topography of developmental venous anomalies.
Of the 14 developmental venous anomalies identified, 10 were clearly present in 17 fMRI independent components in total. While 9 (52.9%) of these 17 independent components were dominated by venous contributions and 2 (11.8%) by motion artifacts, 2 independent components (11.8%) showed partial neural signal contributions and 5 independent components (29.4%) unambiguously exhibited typical neural signal patterns.
Developmental venous anomalies can strongly resemble neural signal as measured by fMRI. They are thus a potential source of bias in fMRI analyses, especially when present in the cortex. This could impede interpretation of local activity in patients, such as in presurgical mapping. In scientific studies with large samples, developmental venous anomaly confounds could be mainly addressed using independent component analysis-based denoising.
用于临床和神经科学应用的脑功能磁共振成像依赖于测量血氧水平的波动。这些测量易受到血管源性噪声的影响。本研究旨在评估发育性静脉异常(一种常见的正常变异)是否会通过表现为真实的神经信号而对 fMRI 测量产生偏差。
从一个大型神经影像学队列(=814)中确定了 14 名参与者中的每一个都存在的大的发育性静脉异常。使用独立成分分析(一种创建代表结构噪声或真实神经活动的不同成分图的数据驱动技术)对静息状态 fMRI 数据进行分解。我们搜索了所有独立成分,以寻找其信号的空间分布遵循发育性静脉异常的地形图的成分图。
在确定的 14 个发育性静脉异常中,共有 10 个在总共 17 个 fMRI 独立成分中明显存在。虽然这 17 个独立成分中有 9 个(52.9%)主要由静脉贡献,2 个(11.8%)由运动伪影主导,但有 2 个独立成分(11.8%)显示出部分神经信号贡献,5 个独立成分(29.4%)明确显示出典型的神经信号模式。
发育性静脉异常在 fMRI 测量中可以强烈地类似于神经信号。因此,它们是 fMRI 分析中的一个潜在偏差源,尤其是在皮层中存在时。这可能会妨碍对患者局部活动的解释,例如在术前映射中。在具有大样本的科学研究中,可以使用基于独立成分分析的去噪主要解决发育性静脉异常的混杂问题。