Construction of brain atlases based on a multi-center MRI dataset of 2020 Chinese adults

Liang, Peipeng; Shi, Lin; Chen, Nan; Luo, Yishan; Wang, Xing; Li, Kai; Mok, Vincent; Chu, Winnie C.W.; Wang, Defeng; Li, Kuncheng

doi:10.1038/srep18216

Cited by 72 publications

(69 citation statements)

References 22 publications

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“…The development of magnetic resonance imaging (MRI) has allowed sophisticated computational algorithms [3][4][5] to reveal structural and functional variations in living brains due to neurological developments and disorders. Often averaged from multiple subjects, the newer MRI brain atlases [6][7][8][9] provide high-quality anatomical and physiological information, which can be mapped to an individual's brain to facilitate further analyses. Despite the advancements to improve resolution, MRI signals remain at macroscopic resolutions.…”

Section: Background and Summarymentioning

confidence: 99%

“…As both natural ageing and neurological disorders can influence the anatomical features of the brain (e.g., tissue atrophy), population-specific atlases [7][8][9] are created to ensure the quality of neuroimage analysis and surgical planning. Aiming to facilitate the research and surgical treatment of Parkinson's disease (PD), the MNI PD25 population-averaged atlases 7,12 were constructed from 3T MRI scans 13 of 25 PD patients, and contain five different image contrasts, including T1w, T2*w, T1-T2* fusion, phase, and an R2* map.…”

Section: Background and Summarymentioning

confidence: 99%

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Bridging micro and macro: accurate registration of the BigBrain dataset with the MNI PD25 and ICBM152 atlases

Xiao

Anderson³

et al. 2019

Preprint

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Brain atlases that encompass detailed anatomical or physiological features are instrumental in the research and surgical planning of various neurological conditions. Magnetic resonance imaging (MRI) has played important roles in neuro-image analysis while histological data remain crucial as a gold standard to guide and validate such analyses. With cellular-scale resolution, the BigBrain atlas offers 3D histology of a complete human brain, and is highly valuable to the research and clinical community. To bridge the insights at macro-and microlevels, accurate mapping of BigBrain and established MRI brain atlases is necessary, but the existing registration is unsatisfactory. The described dataset includes co-registration of the BigBrain atlas to the MNI PD25 atlas and the ICBM152 2009b atlases (symmetric and asymmetric versions) in addition to manual segmentation of the basal ganglia, red nucleus, and hippocampus for all mentioned atlases. The dataset intends to provide a bridge between insights from histological data and MRI studies in research and neurosurgical planning. The registered atlases, anatomical segmentations, and deformation matrices are available at: https://osf.io/xkqb3/.

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Section: Background and Summarymentioning

confidence: 99%

Section: Background and Summarymentioning

confidence: 99%

Bridging micro and macro: accurate registration of the BigBrain dataset with the MNI PD25 and ICBM152 atlases

Xiao

Anderson³

et al. 2019

Preprint

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“…This additional conversion step requires knowing the AC-PC distance of the cohort, which is rarely reported (for exceptions see Papavassiliou et al, 2004; Ponce et al, 2015). The AC-PC distance varies between Talairach and MNI space, from 19 to 32 mm across single subjects, and from 24.9 to 28.3 mm across different populations (Figure 1; Fiandaca et al, 2011; Lee et al, 2008; Liang et al, 2015; Papavassiliou et al, 2004). Moreover, the exact landmarks used to define the AC and PC themselves vary across centers (Weiss et al, 2003; Figure 1 b).…”

Section: Introductionmentioning

confidence: 99%

Probabilistic conversion of neurosurgical DBS electrode coordinates into MNI space

et al. 2017

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In neurosurgical literature, findings such as deep brain stimulation (DBS) electrode positions are conventionally reported in relation to the anterior and posterior commissures of the individual patient (AC/PC coordinates). However, the neuroimaging literature including neuroanatomical atlases, activation patterns, and brain connectivity maps has converged on a different population-based standard (MNI coordinates). Ideally, one could relate these two literatures by directly transforming MRIs from neurosurgical patients into MNI space. However obtaining these patient MRIs can prove difficult or impossible, especially for older studies or those with hundreds of patients. Here, we introduce a methodology for mapping an AC/PC coordinate (such as a DBS electrode position) to MNI space without the need for MRI scans from the patients themselves. We validate our approach using a cohort of DBS patients in which MRIs are available, and test whether several variations on our approach provide added benefit. We then use our approach to convert previously reported DBS electrode coordinates from eight different neurological and psychiatric diseases into MNI space. Finally, we demonstrate the value of such a conversion using the DBS target for essential tremor as an example, relating the site of the active DBS contact to different MNI atlases as well as anatomical and functional connectomes in MNI space.

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“…Finally, the current results were attained based on the Caucasian brain atlas. As the morphological characteristics of the western and Chinese populations are significantly different, in the future, the statistical Chinese brain atlas, such as Chinese2020 [53], may be used.…”

Section: Discussionmentioning

confidence: 99%

White Matter Abnormalities in Two Different Subtypes of Amnestic Mild Cognitive Impairment

et al. 2017

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White matter (WM) degeneration has been found during the course of cognitive decline in both Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI), however, it is unclear whether there are different WM microstructural abnormalities between two subtypes of aMCI, including single domain aMCI (aMCI-s) and multiple domain aMCI (aMCI-m). Thirty-two patients of aMCI single-domain (aMCI-s), twenty-three patients of aMCI multiple-domain (aMCI-m) and twenty-three healthy normal controls (NC) participated in this study. Neuropsychological measures and diffusion tensor imaging (DTI) data were acquired from each subject and tract-based spatial statistics (TBSS) was implemented. It was found that both aMCI groups showed significantly reduced fractional anisotropy (FA) in the right superior longitudinal fasciculus (SLF) than NC. It was also identified that, as compared to aMCI-m, aMCI-s showed significantly decreased FA in the left SLF, left uncinate fasciculus (UF) and left inferior longitudinal fasciculus (ILF), while significantly increased FA in the left anterior thalamic radiation (ATR). The correlation analysis showed that FA values in the regions with group difference were significantly correlated with cognitive functions as measured by Boston naming test and trail making test. These results suggested that the variations of aMCI may be differentiated by FA indexes and DTI may help to understand why specific signs and symptoms occur in patients.

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Construction of brain atlases based on a multi-center MRI dataset of 2020 Chinese adults

Cited by 72 publications

References 22 publications

Bridging micro and macro: accurate registration of the BigBrain dataset with the MNI PD25 and ICBM152 atlases

Bridging micro and macro: accurate registration of the BigBrain dataset with the MNI PD25 and ICBM152 atlases

Probabilistic conversion of neurosurgical DBS electrode coordinates into MNI space

White Matter Abnormalities in Two Different Subtypes of Amnestic Mild Cognitive Impairment

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