A critical analysis of neuroanatomical software protocols reveals clinically relevant differences in parcellation schemes

Mikhael, Shadia; Hoogendoorn, Corné; Valdés-Hernández, Maria del C.; Pernet, Cyril

doi:10.1016/j.neuroimage.2017.02.082

Cited by 24 publications

(28 citation statements)

References 158 publications

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“…Therefore, ground truth segmentations of the superior frontal cortex were generated on a randomly selected subsample of data sets from 34 subjects following a detailed protocol based on the Ono [14] and Duvernoy [15] brain atlases and considering the recommendations from Mikhael et al. (2017) [16] . Every SFG was delineated by drawing two open curves; an outer curve for the gray matter boundary with the subarachnoid space (red) and another demarcating the inner white matter boundary of the gyrus as Fig.…”

Section: Methodsmentioning

confidence: 99%

Do 2‐year changes in superior frontal gyrus and global brain atrophy affect cognition?

Hernández

Reid

Mikhael

et al. 2018

Alz & Dem Diag Ass & Dis Mo

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Introduction Metabolic alterations to the superior frontal gyrus (SFG) have been linked to cognitive decline. Whether these indicate structural atrophy, which could be screened for at a larger scale using noninvasive structural imaging, is unknown. Methods We assessed annual structural magnetic resonance imaging scans and cognitive data from 3 consecutive years from 204 participants from the AD Neuroimaging Initiative database (mean age 72.24 [8.175] years). We evaluated associations between brain structural changes and performance in the Montreal Cognitive Assessment, Everyday Cognition Visuospatial subtest (ECog Visuospatial), and Functional Assessment Questionnaire. Results Changes in the surface area of the SFG were associated with changes in the outcome of the ECog Visuospatial test ( P < .05), but an inconsistent pattern of association was found between the 2-year global brain atrophy progression and changes in the outcome from the three cognitive tests selected. Discussion The extent into which (and if) changes in the SFG influence cognition warrant further evaluation in a larger period in more heterogeneous population.

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Section: Methodsmentioning

confidence: 99%

Do 2‐year changes in superior frontal gyrus and global brain atrophy affect cognition?

Hernández

Reid

Mikhael

et al. 2018

Alz & Dem Diag Ass & Dis Mo

Self Cite

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“…While this automatic segmentation method has been used frequently in past research 80 , its application has been mostly limited to the processing of brains with no atrophy 81,82 , as well as detection of gross segments such as tumours 83 . This highlights the importance of validation studies such as ours to gain a greater understanding of the applications and limitations of different methods [84][85][86][87] .…”

Section: Discussionmentioning

confidence: 94%

A Large-scale Comparison of Cortical and Subcortical Structural Segmentation Methods in Alzheimer’s Disease: a Statistical Approach

Zamani

Sadr

Javadi

2020

Preprint

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Alzheimer's disease (AD) is a neurodegenerative disease that leads to anatomical atrophy, as evidenced by magnetic resonance imaging (MRI). Automated segmentation methods are developed to help with the segmentation of different brain areas. However, their reliability has yet to be fully investigated. To have a more comprehensive understanding of the distribution of changes in AD, as well as investigating the reliability of different segmentation methods, in this study we compared volumes of cortical and subcortical brain segments, using automated segmentation methods in more than 60 areas between AD and healthy controls (HC). A total of 44 MRI images (22 AD and 22 HC, 50% females) were taken from the minimal interval resonance imaging in Alzheimer's disease (MIRIAD) dataset. HIPS, volBrain, CAT and BrainSuite segmentation methods were used for the subfields of hippocampus, and the rest of the brain. While HIPS, volBrain and CAT showed strong conformity with the past literature, BrainSuite misclassified several brain areas. Additionally, the volume of the brain areas that successfully discriminated between AD and HC showed a correlation with mini mental state examination (MMSE) scores. The two methods of volBrain and CAT showed a very strong correlation. These two methods, however, did not correlate with BrainSuite. Our results showed that automated segmentation methods HIPS, volBrain and CAT can be used in the classification of AD and HC. This is an indication that such methods can be used to inform researchers and clinicians of underlying mechanisms and progression of AD.

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“…The atlas was done following previously described MRI protocols (Pruessner, Li et al 2000); (Ulmer and Jansen 2013); (Gonçalves Pereira, Insausti et al 2005); (Frankó, Insausti et al 2014); (Mikhael, Hoogendoorn et al 2018); (McCormick, Ziebell et al 2006); (Palomero-Gallagher, Mohlberg et al 2008); (Pruessner, Köhler et al 2002); (Insausti, Juottonen et al 1998); (Ding, Royall et al 2016) that described the segmentation of the parcels included within the archicortex (e.g. hippocampi), paleocortex (e.g.…”

Section: Methodsmentioning

confidence: 99%

PhyloBrain atlas: a cortical brain MRI atlas following a phylogenetic approach

Zhernovaia

Dadar

Mahmoud

et al. 2020

Preprint

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Cortical atlases constitute a consistent division of the human cortex into areas that have common structural as well as meaningful and distinctive functional characteristics. The most widely used atlases follow the cytoarchitectonic and myeloarchitectonic characteristics of the cortex and have been combined to the standard anatomical nomenclature of gyri and sulci. More recently, common functional features depicted by resting state functional MRI have also guided the division of the cortical brain in functional regions of interest. However, to date, there are no atlases that divide the cortex considering the common evolutionary changes experienced by the mammalian cortex.Hence, the present study proposes the division of cortical areas into five main regions of interest (ROIs) following a phylogenetic approach: 1- archicortex, 2- paleocortex, 3- peri-archicortex, 4- proisocortex, 5-neocortex, and twelve neocortical sub-ROIs: 5.1.temporopolar, 5.2.post-central, 5.3.pre-central, 5.4.pericalcarine, 5.5.superior temporal, 5.6.middle temporal, 5.7.precuneus, 5.8.insular, 5.9.inferior parietal, 5.10.caudal anterior, 5.11.posterior cingulate, and 5.12.lingual gyrus.The segmentations were done using the T1-weighted MNI-ICBM152 non-linear 6th generation symmetric average brain MRI model.

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A critical analysis of neuroanatomical software protocols reveals clinically relevant differences in parcellation schemes

Cited by 24 publications

References 158 publications

Do 2‐year changes in superior frontal gyrus and global brain atrophy affect cognition?

Do 2‐year changes in superior frontal gyrus and global brain atrophy affect cognition?

A Large-scale Comparison of Cortical and Subcortical Structural Segmentation Methods in Alzheimer’s Disease: a Statistical Approach

PhyloBrain atlas: a cortical brain MRI atlas following a phylogenetic approach

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