Whole Brain Magnetic Resonance Image Atlases: A Systematic Review of Existing Atlases and Caveats for Use in Population Imaging

Abstract

Brain MRI atlases may be used to characterize brain structural changes across the life course. Atlases have important applications in research, e.g., as registration and segmentation targets to underpin image analysis in population imaging studies, and potentially in future in clinical practice, e.g., as templates for identifying brain structural changes out with normal limits, and increasingly for use in surgical planning. However, there are several caveats and limitations which must be considered before successfully applying brain MRI atlases to research and clinical problems. For example, the influential Talairach and Tournoux atlas was derived from a single fixed cadaveric brain from an elderly female with limited clinical information, yet is the basis of many modern atlases and is often used to report locations of functional activation. We systematically review currently available whole brain structural MRI atlases with particular reference to the implications for population imaging through to emerging clinical practice. We found 66 whole brain structural MRI atlases world-wide. The vast majority were based on T1, T2, and/or proton density (PD) structural sequences, had been derived using parametric statistics (inappropriate for brain volume distributions), had limited supporting clinical or cognitive data, and included few younger (>5 and <18 years) or older (>60 years) subjects. To successfully characterize brain structural features and their changes across different stages of life, we conclude that whole brain structural MRI atlases should include: more subjects at the upper and lower extremes of age; additional structural sequences, including fluid attenuation inversion recovery (FLAIR) and T2* sequences; a range of appropriate statistics, e.g., rank-based or non-parametric; and detailed cognitive and clinical profiles of the included subjects in order to increase the relevance and utility of these atlases.

A Multi‐Atlas Label Fusion Tool for Neonatal Brain MRI Parcellation and Quantification

“…Structure‐by‐structure analysis, in which the brain is parcellated based on structural units that follow standard ontology in brain anatomy, is widely used to investigate disease‐related changes seen on brain magnetic resonance imaging (MRI) scans . Numerous tools for brain parcellation methods have been proposed in the past and their accuracy has continuously improved, especially in the past decade since the introduction of multi‐atlas label fusion (MALF) algorithms .…”

Construction of 4D infant cortical surface atlases with sharp folding patterns via spherical patch‐based group‐wise sparse representation

“…Due in part to the invention of the MRI, researchers can now construct brain atlas from in vivo brain images, which has greatly enriched the understanding and analysis on brains. Generally, there are two types of brain atlases: (a) volumetric atlases (Dickie, Shenkin, Anblagan, et al, ; Shi et al, ; Tzourio‐Mazoyer et al, ) (which are directly constructed from volumetric brain MR images), and (b) cortical surface atlases (which are constructed based on the reconstructed cortical surfaces from volumetric MR images) (Fischl, Sereno, Tootell, et al, ; Lyttelton, Boucher, Robbins, & Evans, ; Toro & Burnod, ; Van Essen & Dierker, ). Compared to volumetric atlases, cortical surface atlases provide more valuable and accurate references for brain studies by respecting the topology of the highly convoluted cerebral cortex (Glasser et al, ; Li, Nie, Wang, Shi, Lyall, et al, ; Li et al, ; Li, Lin, Gilmore, & Shen, ; Van Essen, Drury, Joshi, et al, , ; Van Essen, Smith, Barch, et al, ; Van Essen, Snyder, Raichle, et al, ).…”

White Matter Extension of the Melbourne Children’s Regional Infant Brain Atlas: M-CRIB-WM

“…For example, Shi et al (Shi et al, 2011) warped the adult parcellated 'Automated Anatomical Labelling' (AAL) atlas (Tzourio-Mazoyer et al, 2002) (defined based on T 1 images) to an infant longitudinal sample. However, it is generally acknowledged that warping adult atlases to infant space offers limited accuracy, due to morphological differences between the adult brain and the developing neonatal brain (Alexander et al, 2017;Blesa et al, 2016;Dickie et al, 2017;Fillmore, Richards, Phillips-Meek, Cryer, & Stevens, 2015;Kazemi, Moghaddam, Grebe, Gondry-Jouet, & Wallois, 2007;Richards, Sanchez, Phillips-Meek, & Xie, 2016;Sanchez, Richards, & Almli, 2012). Additionally, warping a single parcellated image to multiple participants, even those of the same age, is likely to introduce labelling error related to imperfect registration aligning different target brains.…”