The PaleoArchiNeo (PAN) human brain atlas: A dataset on a standard neuroanatomical MRI template following a phylogenetic approach.

Cortical atlases provide consistent divisions of the human cortex into areas that have common structural as well as meaningful and distinctive functional characteristics. They constitute a fundamental tool to study and quantify changes in healthy and pathological states. Historically, the most widely used atlases follow the cytoarchitecture described by Brodmann and/or the myeloarchitectonic characteristics described by Vogt-Vogt. These histological approaches have since been combined to the standard anatomical nomenclature of gyri and sulci, referring to the corresponding cytoarchitectonic area(s) present in a gyrus, when applicable or necessary (e.g. area 4 of Brodmann in the pre-central gyrus). More recently, common functional features depicted by resting state functional MRI have guided the division of the cortex into functional regions of interest. However, to date, there are no human MRI atlases that divide the cortex considering the common evolutionary changes experienced by the mammalian cortex. Hence, the present dataset describes the PaleoArchiNeo (PAN) Human Brain, a voxel-based atlas that divides the human cortex into five regions of interest (ROIs) following a phylogenetic approach: 1- archicortex, 2- paleocortex, 3- peri-archicortex, 4- proisocortex, 5- neocortex, and thirty neocortical sub-ROIs that follow the gyral Terminologia Anatomica.The masks of the ROIs and sub-ROIs were segmented on the T1-weighted MNI ICBM 152 2009c symmetric average brain MRI model, the latest version of the most widely used standard brain template. The segmentations have been performed manually by anatomist experts, following the MRI anatomical landmarks that have been previously described, correlated, and validated with histology by other groups.

Comparison of Multiple Sclerosis Cortical Lesion Types Detected by Multicontrast 3T and 7T MRI.

BACKGROUND AND PURPOSE: Our aims were the following: 1) to compare multicontrast cortical lesion detection using 3T and 7T MR imaging, 2) to compare cortical lesion type frequency in relapsing-remitting and secondary-progressive MS, and 3) to assess whether detectability is related to the magnetization transfer ratio, an imaging marker sensitive to myelin content. MATERIALS AND METHODS: Multicontrast 3T and 7T MR images from 10 participants with relapsing-remitting MS and 10 with secondary-progressive MS. We used the following 3T contrast sequences: 3D-T1-weighted, quantitative T1, FLAIR, magnetization-transfer, and 2D proton-density- and T2-weighted. We used the following 7T contrast sequences: 3D-T1-weighted, quantitative T1, and 2D-T2*-weighted. RESULTS: Cortical lesion counts at 7T were the following: 720 total cortical lesions, 420 leukocortical lesions (58%), 27 intracortical lesions (4%), and 273 subpial lesions (38%). Cortical lesion counts at 3T were the following: 424 total cortical, 393 leukocortical (93%), zero intracortical, and 31 subpial (7%) lesions. Total, intracortical, and subpial 3T lesion counts were significantly lower than the 7T counts (P < .002). Leukocortical lesion counts were not significantly different between scanners. Total and leukocortical lesion counts were significantly higher in secondary-progressive MS, at 3T and 7T (P ≤ .02). Subpial lesions were significantly higher in secondary-progressive MS at 7T (P = .006). The magnetization transfer ratio values of leukocortical lesions visible on both scanners were significantly lower than the magnetization transfer ratio values of leukocortical lesions visible only at 3T. No significant difference was found in magnetization transfer ratio values between subpial lesions visible only at 7T and subpial lesions visible on both 3T and 7T. CONCLUSIONS: Detection of leukocortical lesions at 3T is comparable with that at 7T MR imaging. Imaging at 3T is less sensitive to intracortical and subpial lesions. Leukocortical lesions not visible on 7T T2*-weighted MRI may be associated with less demyelination than those that are visible. Detectability of subpial lesions does not appear to be related to the degree of demyelination.

Manual Segmentation of MS Cortical Lesions Using MRI: A Comparison of 3 MRI Reading Protocols.

BACKGROUND AND PURPOSE: Double inversion recovery has been suggested as the MR imaging contrast of choice for segmenting cortical lesions in patients with multiple sclerosis. In this study, we sought to determine the utility of double inversion recovery for cortical lesion identification by comparing 3 MR imaging reading protocols that combine different MR imaging contrasts. MATERIALS AND METHODS: Twenty-five patients with relapsing-remitting MS and 3 with secondary-progressive MS were imaged with 3T MR imaging by using double inversion recovery, dual fast spin-echo proton-density/T2-weighted, 3D FLAIR, and 3D T1-weighted imaging sequences. Lesions affecting the cortex were manually segmented by using the following 3 MR imaging reading protocols: Protocol 1 (P1) used all available MR imaging contrasts; protocol 2 (P2) used all the available contrasts except for double inversion recovery; and protocol 3(P3) used only double inversion recovery. RESULTS: Six hundred forty-three cortical lesions were identified with P1 (mean = 22.96); 633, with P2 (mean = 22.6); and 280, with P3 (mean = 10). The counts obtained by using P1 and P2 were not significantly different (P = .93). The counts obtained by using P3 were significantly smaller than those obtained by using either P1 (P < .001) or P2 (P < .001). The intraclass correlation coefficients were P1 versus P2 = 0.989, P1 versus P3 = 0.615, and P2 versus P3 = 0.588. CONCLUSIONS: MR imaging cortical lesion segmentation can be performed by using 3D T1-weighted and 3D FLAIR images acquired with a 1-mm isotropic voxel size, supported by conventional T2-weighted and proton-density images with 3-mm-thick sections. Inclusion of double inversion recovery in this multimodal reading protocol did not significantly improve the cortical lesion identification rate. A multimodal approach is superior to using double inversion recovery alone.