Interaction of Developmental Venous Anomalies with Resting-State Functional MRI Measures

Abstract

Background and purpose: 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.

Materials and methods: Large developmental venous anomalies (1 in each of 14 participants) were identified from a large neuroimaging cohort (n = 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.

Results: 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.

Conclusions: 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.

Fig 1.

Overview of dominant effects represented by the independent components which included unique contributions of DVAs.

Fig 2.

An example of a unique contribution of a DVA with deep drainage in an IC dominated by venous pulsations (subject 5). Typical anatomic features of the DVA (arrow, A) with a caput medusae appearance, unique contribution following the course of the DVA through the parenchyma (arrow, B) and contributions attributable to normal subependymal veins in the periventricular white matter (asterisk, B). C, Midsagittal view representing the typical venous character of this component, including venous sinuses and deep veins.

Fig 3.

An example of a unique contribution of a DVA (arrows) in an IC exhibiting typical characteristics of a neural signal component (subject 3).