Diagnosis of early mild cognitive impairment using a multiobjective optimization algorithm based on T1-MRI data

Alzheimer’s disease (AD) is the most prevalent form of dementia. The accurate diagnosis of AD, especially in the early phases is very important for timely intervention. It has been suggested that brain atrophy, as measured with structural magnetic resonance imaging (sMRI), can be an efficacy marker of neurodegeneration. While classification methods have been successful in diagnosis of AD, the performance of such methods have been very poor in diagnosis of those in early stages of mild cognitive impairment (EMCI). Therefore, in this study we investigated whether optimisation based on evolutionary algorithms (EA) can be an effective tool in diagnosis of EMCI as compared to cognitively normal participants (CNs). Structural MRI data for patients with EMCI (n = 54) and CN participants (n = 56) was extracted from Alzheimer’s disease Neuroimaging Initiative (ADNI). Using three automatic brain segmentation methods, we extracted volumetric parameters as input to the optimisation algorithms. Our method achieved classification accuracy of greater than 93%. This accuracy level is higher than the previously suggested methods of classification of CN and EMCI using a single- or multiple modalities of imaging data. Our results show that with an effective optimisation method, a single modality of biomarkers can be enough to achieve a high classification accuracy

Robust estimation of sulcal morphology

While it is well established that cortical morphology differs in relation to a variety of inter-individual factors, it is often characterized using estimates of volume, thickness, surface area, or gyrification. Here we developed a computational approach for estimating sulcal width and depth that relies on cortical surface reconstructions output by FreeSurfer. While other approaches for estimating sulcal morphology exist, studies often require the use of multiple brain morphology programs that have been shown to differ in their approaches to localize sulcal landmarks, yielding morphological estimates based on inconsistent boundaries. To demonstrate the approach, sulcal morphology was estimated in three large sample of adults across the lifespan, in relation to aging. A fourth sample is additionally used to estimate test-retest reliability of the approach.This toolbox is now made freely available as supplemental to this paper: https://cmadan.github.io/calcSulc/

Development and application of a human cortical brain atlas on MRI considering phylogeny = Développement et emploi d'un atlas du cortex cérébral humain réalisé sur IRM et tenant compte de la phylogénie

Le cortex cérébral est une structure en couches complexe qui remplit différents types de fonctions. Au cours de l’histoire des neurosciences, plusieurs atlas corticaux ont été développés pour classifier différentes régions du cortex en tant que zones aux caractéristiques structurelles ou fonctionnelles communes, afin d'étudier et de quantifier les changements aux états sain et pathologique. Cependant, il n'existe pas d'atlas suivant une approche phylogénétique, c'est-à-dire, basée sur les critères d'évolution communs. Ce mémoire présente les étapes de création d'un nouvel atlas dans un modèle d’imagerie par résonance magnétique (IRM) en espace standard (pseudo-Talairach) : le PAN-Atlas, basé sur l'origine phylogénétique commune de chaque zone corticale, et son application sur des scans d’IRM de dix individus pour évaluer sa performance. D’abord, nous avons regroupé les différentes régions corticales en cinq régions d'intérêt (RdI) d'origine phylogénétique connue (archicortex, paléocortex, périarchicortex, proïsocortex, isocortex ou néocortex) sur la base de protocoles de segmentation validés histologiquement par d'autres groupes de chercheurs. Puis, nous avons segmenté ces régions manuellement sur le modèle d’IRM cérébrale moyen MNI-ICBM 2009c, en formant des masques. Par la suite, on a utilisé un pipeline multi-étapes de traitement des images pour réaliser le recalage des masques de notre atlas aux scans pondérés T1 de dix participants sains, en obtenant ainsi des masques automatiques pour chaque RdI. Les masques automatiques ont été évalués après une correction manuelle par le biais de l’indice Dice-kappa, qui quantifie la colocalisation des voxels de chaque masque automatique vs. le masque corrigé manuellement. L’indice a montré une très bonne à excellente performance de notre atlas. Cela a permis l’évaluation et comparaison des volumes corticales de chaque région et la quantification des valeurs de transfert de magnétisation (ITM), qui sont sensibles à la quantité de myéline présente dans le tissu. Ce travail montre que la division régionale du cortex en IRM avec une approche phylogénétique est réalisable à l'aide de notre PAN-Atlas en espace standard et que les masques peuvent être utilisés pour différents types de quantifications, comme les volumes corticaux, ou l’estimation des valeurs de ITM. Notre atlas pourrait éventuellement servir à évaluer les différences entre personnes saines et celles atteintes par des maladies neurodégénératives ou d’autres maladies neurologiques.The cerebral cortex is a complex layered structure that performs different types of functions. Throughout the history of neuroscience, several cortical atlases have been developed to classify/divide different regions of the cortex into areas with common structural or functional characteristics, to then study and quantify changes in healthy and pathological states. However, to date, there is no atlas following a phylogenetic approach, i.e. based on the common evolution criteria. This thesis presents the steps of creation of a new atlas corresponding to a standard MRI template: the PAN-Atlas, based on the common phylogenetic origin of each cortical zone, and its application on MRI scans of ten healthy participants to assess its performance. First, we grouped the different cortical regions into five regions of interest (ROI) of known phylogenetic origin (archicortex, paleocortex, periarchicortex, proisocortex, isocortex or neocortex) based on MRI protocols previously validated through histology by other groups of researchers. Then, we manually segmented these ROIs on the MNI-ICBM 2009c average brain MRI template, creating corresponding masks. We then used a multi-step image processing pipeline to register the atlas’ masks to T1 weighted images of ten healthy participants, generating automatic masks for each scan. The accuracy of these automatic atlas’ masks was assessed after manual correction using Dice-kappa similarity index, to quantify the colocalization of the automatic vs. the manually corrected masks. The Dice-kappa values showed a very good to excellent performance of the automatic atlas’ masks. This allowed the evaluation and comparison of cortical volumes of each ROI, as well as the quantification of magnetization transfer ratio (MTR) values, which are sensitive to myelin content. This work shows that the division of the cortex on MRI following a phylogenetic approach is feasible using our PAN Atlas, and that the masks of the atlas can be used to perform different types of quantifications, such as the ones presented here (cortical volume and MTR per ROI). Our atlas could similarly be used to assess differences between the cortex of healthy individuals and people affected by neurodegenerative diseases and other neurological disorders