A statistical atlas of cerebral arteries generated using multi-center MRA datasets from healthy subjects

• Published in: Scientific data Vol. 6; no. 1; p. 29
• Main Authors: Mouches, Pauline, Forkert, Nils D.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 11.04.2019; Nature Publishing Group
• Subjects: 631/1647/245/1628; 631/443/592/75; 692/53/2421; 692/698; 692/700/1421/65; Adult; Aged; Aged, 80 and over; Angiography; Cerebral Arteries - diagnostic imaging; Data Descriptor; Data processing; Datasets; Female; Healthy Volunteers; Humanities and Social Sciences; Humans; Image processing; Magnetic Resonance Angiography; Magnetic resonance imaging; Male; Medical imaging; Middle Aged; Morphology; multidisciplinary; Neuroimaging; Neurological diseases; Risk factors; Science; Science (multidisciplinary); Segmentation; Statistics; Vascular diseases; Veins & arteries
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-019-0034-5

Magnetic resonance angiography (MRA) can capture the variation of cerebral arteries with high spatial resolution. These measurements include valuable information about the morphology, geometry, and density of brain arteries, which may be useful to identify risk factors for cerebrovascular and neurological diseases at an early time point. However, this requires knowledge about the distribution and morphology of vessels in healthy subjects. The statistical arterial brain atlas described in this work is a free and public neuroimaging resource that can be used to identify vascular morphological changes. The atlas was generated based on 544 freely available multi-center MRA and T1-weighted MRI datasets. The arteries were automatically segmented in each MRA dataset and used for vessel radius quantification. The binary segmentation and vessel size information were non-linearly registered to the MNI brain atlas using the T1-weighted MRI datasets to construct atlases of artery occurrence probability, mean artery radius, and artery radius standard deviation. This public neuroimaging resource improves the understanding of the distribution and size of arteries in the healthy human brain. Design Type(s) feature extraction objective • anatomical image analysis objective • data integration objective Measurement Type(s) brain blood vessel Technology Type(s) MRI-Based Angiogram Factor Type(s) age • ethnic group • sex Sample Characteristic(s) Homo sapiens • brain Machine-accessible metadata file describing the reported data (ISA-Tab format)