Brain structure alterations in girls with central precocious puberty

PurposeCentral precocious puberty (CPP) is puberty that occurs at an unusually early age with several negative psychological outcomes. There is a paucity of data on the morphological characteristics of the brain in CPP. This study aimed to determine the structural differences in the brain of patients with CPP.MethodsWe performed voxel- and surface-based morphometric analyses of 1.5 T T1-weighted brain images scanned from 15 girls with CPP and 13 age-matched non-CPP controls (NC). All patients with CPP were diagnosed by gonadotropin-releasing hormone (GnRH) stimulation test. The magnetic resonance imaging (MRI) data were evaluated using Levene’s test for equality of variances and a two-tailed unpaired t-test for equality of means. False discovery rate correction for multiple comparisons was applied using the Benjamini–Hochberg procedure.ResultsMorphometric analyses of the brain scans identified 33 candidate measurements. Subsequently, increased thickness of the right precuneus was identified in the patients with CPP using general linear models and visualizations of cortical thickness with a t-statistical map and a random field theory map.ConclusionThe brain scans of the patients with CPP showed specific morphological differences to those of the control. The features of brain morphology in CPP identified in this study could contribute to further understanding the association between CPP and detrimental psychological outcomes

Quantification of sulcal emergence timing and its variability in early fetal life: Hemispheric asymmetry and sex difference

Human fetal brains show regionally different temporal patterns of sulcal emergence following a regular timeline, which may be associated with spatiotemporal patterns of gene expression among cortical regions. This study aims to quantify the timing of sulcal emergence and its temporal variability across typically developing fetuses by fitting a logistic curve to presence or absence of sulcus. We found that the sulcal emergence started from the central to the temporo-parieto-occipital lobes and frontal lobe, and the temporal variability of emergence in most of the sulci was similar between 1 and 2 weeks. Small variability (\u3c 1 week) was found in the left central and postcentral sulci and larger variability (\u3e2 weeks) was shown in the bilateral occipitotemporal and left superior temporal sulci. The temporal variability showed a positive correlation with the emergence timing that may be associated with differential contributions between genetic and environmental factors. Our statistical analysis revealed that the right superior temporal sulcus emerged earlier than the left. Female fetuses showed a trend of earlier sulcal emergence in the right superior temporal sulcus, lower temporal variability in the right intraparietal sulcus, and higher variability in the right precentral sulcus compared to male fetuses. Our quantitative and statistical approach quantified the temporal patterns of sulcal emergence in detail that can be a reference for assessing the normality of developing fetal gyrification

The role of cortical structural variance in deep learning-based prediction of fetal brain age

BackgroundDeep-learning-based brain age estimation using magnetic resonance imaging data has been proposed to identify abnormalities in brain development and the risk of adverse developmental outcomes in the fetal brain. Although saliency and attention activation maps have been used to understand the contribution of different brain regions in determining brain age, there has been no attempt to explain the influence of shape-related cortical structural features on the variance of predicted fetal brain age.MethodsWe examined the association between the predicted brain age difference (PAD: predicted brain age–chronological age) from our convolution neural networks-based model and global and regional cortical structural measures, such as cortical volume, surface area, curvature, gyrification index, and folding depth, using regression analysis.ResultsOur results showed that global brain volume and surface area were positively correlated with PAD. Additionally, higher cortical surface curvature and folding depth led to a significant increase in PAD in specific regions, including the perisylvian areas, where dramatic agerelated changes in folding structures were observed in the late second trimester. Furthermore, PAD decreased with disorganized sulcal area patterns, suggesting that the interrelated arrangement and areal patterning of the sulcal folds also significantly affected the prediction of fetal brain age.ConclusionThese results allow us to better understand the variance in deep learning-based fetal brain age and provide insight into the mechanism of the fetal brain age prediction model

Clinical Value of Machine Learning in the Automated Detection of Focal Cortical Dysplasia Using Quantitative Multimodal Surface-Based Features

Objective: To automatically detect focal cortical dysplasia (FCD) lesion by combining quantitative multimodal surface-based features with machine learning and to assess its clinical value.Methods: Neuroimaging data and clinical information for 74 participants (40 with histologically proven FCD type II) was retrospectively included. The morphology, intensity and function-based features characterizing FCD lesions were calculated vertex-wise on each cortical surface and fed to an artificial neural network. The classifier performance was quantitatively and qualitatively assessed by performing statistical analysis and conventional visual analysis.Results: The accuracy, sensitivity, specificity of the neural network classifier based on multimodal surface-based features were 70.5%, 70.0%, and 69.9%, respectively, which outperformed the unimodal classifier. There was no significant difference in the detection rate of FCD subtypes (Pearson’s Chi-Square = 0.001, p = 0.970). Cohen’s kappa score between automated detection outcomes and post-surgical resection region was 0.385 (considered as fair).Conclusion: Automated machine learning with multimodal surface features can provide objective and intelligent detection of FCD lesion in pre-surgical evaluation and can assist the surgical strategy. Furthermore, the optimal parameters, appropriate surface features and efficient algorithm are worth exploring

Preserved Cognition Despite Amyloid Burden: Cortical Thickness as a Marker of Brain Reserve

Une détection précoce des troubles neurocognitifs majeurs comme la maladie d’Alzheimer (MA) requiert une meilleure compréhension des changements cérébraux survenant lors du vieillissement. Un fardeau amyloïde élevé est perçu comme le reflet d’une MA préclinique, mais n’est pas toujours associé à un déclin des fonctions cognitives. Cette discordance pourrait s’expliquer par la présence de réserve cérébrale (RC). L’épaisseur corticale (EC) pourrait constituer un marqueur de RC dans le vieillissement normal et moduler l’expression du déclin cognitif chez certains individus. Afin de vérifier notre hypothèse, nous avons extrait des mesures d’EC à partir d’imagerie par résonance magnétique (IRM) anatomique T1 chez 116 personnes âgées cognitivement normales (65 à 87 ans). La moyenne d’EC obtenues dans 11 régions corticales impliquées précocement dans la maladie d’Alzheimer a permis d’obtenir une mesure spécifique d’EC (ALZ). Les participants ont été divisés en ALZ+ si leur EC dans les régions ALZ était plus d’un écart-type sous la moyenne, donc considéré à haut risque de MA préclinique (n=19). Les sujets restants ont été classifiés ALZ- (n=97). Le fardeau amyloïde a été mesuré avec la tomographie d’émission par positrons (TEP) en utilisant le radiotraceur PiB; les participants ont été divisés en PiB+ (SUVR>1.24) et PiB-. Une évaluation neuropsychologique de la mémoire épisodique (ME) et des fonctions exécutives (FE) a été menée. Le groupe ALZ+ avait une plus faible performance de ME comparativement au groupe ALZ- (p=0.01), bien que le fardeau amyloïde entre ces deux groupes soit similaire. Les analyses de régression menées ont également permis de montrer que le score de ME est prédit par l’EC des régions ALZ (p=0.03) et par le PiB (p=0.005), mais pas par l’âge (p>0.9). De plus, l’EC dans les régions ALZ et le PiB ne sont pas associés entre eux (R2=0.008). La performance au test de ME était similaire entre les groupes PiB+ et PiB- parmi les sujets ALZ- (p>0.1), mais différait lorsque l’ensemble de la cohorte était considéré (p=0.02). Ce faisant, nous avons pu montrer au cours de ce projet que l’EC pourrait servir de marqueur de réserve cérébrale et expliquer pourquoi certains individus semblent mieux résister à la pathologie amyloïde. Cette étude montre également notre manque de connaissance quant à la dynamique des biomarqueurs impliqués dans la MA, et la réserve dont il faut faire preuve quant aux cadres de recherche proposant des classifications de sujets se basant sur cette dynamique mal comprise des biomarqueurs.Abstract: Early detection of major neurocognitive disorders requires a better understanding of cerebral changes occuring during aging. Important amyloid burden is often perceived as a reflection of preclinical Alzheimer’s disease (AD), but is not always associated with cognitive decline. Such discrepancy could be explained partly by preserved brain reserve (BR), which could help some individuals better resist amyloid pathology. Cortical thickness (CoT) could provide a marker of BR in normal aging and modulate expression of cognitive decline amongst some individuals. To verify this hypothesis, CoT measures were extracted using anatomic T1 MRI images acquired in 116 cognitively normal elderly individuals aged 65 to 87 years. CoT was averaged in 11 cortical regions affected early on in the course of AD to obtain a specific CoT measure (ALZ). Participants were then divided into ALZ+ if their CoT in ALZ regions was more than 1 standard deviation below the mean, hence considered high risk for preclinical AD (n=19). Remaining subjects were classified as ALZ-, hence low risk for preclinical AD (n=97). Amyloid burden was measured with PET imaging using Pittsburgh Compound B (PiB) as radiotracer; participants were divided into PiB+ (SUVR>1.24) and PiB-. Neuropsychological evaluation was conducted for episodic memory and executive function. EM performance was similar between PiB+ and PiB- groups amongst ALZ- subjects (p>0.1), but differed when all subjects were considered (p=0.02). Participants in the ALZ+ group had poorer EM performance compared to ALZ- participants (p=0.01), although amyloid burden amongst the two groups was similar. Regression analysis also showed EM score was predicted by CoT in ALZ regions (p=0.03) and PiB (p=0.005), but not by age. Furthermore, Pearson correlation showed there was no association between CoT in ALZ regions and PiB (R2=0.008). Our results suggest CoT could serve as a proxy for brain reserve and partly explain why some indivuduals tend to better resist amyloid pathology. This study further underlines proposed research framework for clinical research may be premature, as the relative dynamics of biomarkers in the preclinical phase of AD may not be fully understood

Učinak perinatalne hipoksijsko – ishemijske encefalopatije na projekcijske puteve moždanoga debla u nedonoščeta [Impact of hypoxic-ischemic encephalopathy on projection pathways of the premature infant brainstem]

Introduction: Improved perinatal care has led to increased survival of premature infants. These children often have different motoric, cognitive and psychological disorders. Perinatal hypoxic-ischemic encephalopathy (HIE) is a major cause of white matter injury and long-term neurological deficits in children. The aim of this study is to analyze cerebral volumes and DTI parameters as major site of white matter injury and compare them with recipient areas in pons and cerebellum in order to find possible selective vulnerability for corticospinal tracts, corticopontine pathways, medial lemnisci and superior, medial and inferior cerebellar peduncles. Material and methods: In our research we had three groups of participants. The first group consisted of 5 normal term infants (control), the second group included 16 normotypic premature infants without perinatal HIE lesions (normotypic), and the third group included 22 premature infants with perinatal HIE (HIE). Diagnosis of perinatal HIE was based on both MRI and clinical exams. Parental consent for MRI scanning was obtained and all examinations were controlled and approved by the Institutional Review Board of the University of Zagreb School of Medicine. MRI images were obtained using 3T MRI scanner (Magnetom TrioTim, Siemens, Germany), with high resolution T1 MPRAGE sequence in sagittal plane (voxel size = 1x1x1 mm) and dwi sequences (voxel size 1.6x1.6x3 mm). All groups were scanned at two different time points, first at the term or corrected term age and second at the age of two years. Cerebral and cerebellar volumes were measured using semi-automated software (MNI toolbox, Montreal, Canada), and brainstem (mesencephalon, pons, medulla oblongata) was measured using manual segmentation methods (Analyze 8.1, Mayo Clinic, USA). Axonal pathways (corticospinal tracts, corticopontine pathways, medial lemnisci and superior, medial and inferior cerebellar peduncles) were reconstructed and all parameters (volume, FA- fractional anisotropy and ADC-apparent diffusion coefficient) have been measured using Diffusion Toolkit and TrackVis software. Statistical analysis was done using MedCalc v12. Results: Normotypic group showed decreased volumes at corrected term age, but their volumes compensate during growth and at the age of 2 years correspond to control group. Unlike normotypic, group with HIE lesions shows statistically significant reduction of measured volumes during corrected term age comparing with normal group, and also at the age of 2 years comparing with both normal and normotypic group. Volumetric analysis of brainstem parts (mesencephalon, pons, medulla oblongata) and its layers (base, tegmentum, tectum) follows that pattern as well as volumetric analysis of brainstem in general, cerebellum and total brain volume. Parameters measured during DTI analysis (volume, FA- fractional anisotropy and ADC-apparent diffusion coefficient) for named axonal pathways showed similar pattern in observed groups. Conclusion: Origin, trajectory and termination areas of measured axonal pathways are reduced after perinatal HIE. We have found that all measured pathways are regularly damaged in perinatal HIE, as a part of general white matter pathology. Our finding is in the agreement that pathways which are part of the periventricular fiber system and periventricular crossroads are vulnerable in HIE. Also, due to the topographical relationship, damaged periventricular fibers will contribute to reduction of brainstem, expecially pons, as well as cerebellum

Anatomical Correlates of Working Memory Deficits in Schizophrenia

La mémoire de travail — c’est-à-dire la capacité limitée de retenir et de manipuler temporairement l’information — est un déficit cognitif central en schizophrénie. La perturbation de cette fonction possède un fort impact dans la vie quotidienne des patients. Des travaux récents de notre laboratoire ont pu mettre en évidence que ces troubles de mémoire de travail ne sont pas homogènes et que certains processus sont plus perturbés que d’autres. Par exemple, une méta-analyse du laboratoire a démontré que l’encodage volontaire d’information est une des fonctions spécifiquement affectée en schizophrénie (Grot, Potvin et al. 2014). Plus spécifiquement, l’association volontaire d’informations distinctes en un ensemble cohérent (par exemple, un objet et sa position spatiale) est déficitaire chez les patients. Ce déficit spécifique est notamment sous-tendu par une hypoactivation du cortex préfrontal et pariétal chez les patients (Grot, Légaré et al. 2017). Ces deux régions sont liées à l’attention, à la manipulation d’information, et aux stratégies d’encodage, ce qui confère l’habilité et la flexibilité nécessaire à la mémoire de travail (Kane and Engle2002, Baddeley2003). Il est intéressant de noter que de nombreuses études rapportent aussi une réduction de l’épaisseur corticale de ces régions chez les patients, ainsi qu’une altération des fibres blanches les interconnectant (Goldman, Pezawas et al. 2009). En ce sens, notre étude a montré qu’une modification anatomique du réseau préfrontal-pariétal pourrait expliquer le déficit spécifique de mémoire de travail en schizophrénie. Plus spécifiquement, la latéralisation gauche de ce réseau serait atténuée en schizophrénie, et engendrerait le déficit observé en mémoire de travail.Working memory, which is the limited capacity to temporarily maintain and manipulate information, is a core cognitive deficit in schizophrenia. This impairment has a strong impact on the daily lives of patients. A previous study of our laboratory observed that working memory deficits are not homogeneous and that some processes are more disturbed than others (Grot, Potvin et al., 2014). This was supported by a subsequent study, which showed that the voluntary association of distinct information into a coherent whole (i.e. an object and its spatial position) was specifically impaired in patients with schizophrenia (Grot, Légaré et al., 2017). This specific deficit, which is referred to as active binding, is underpinned by a hypoactivation of the left prefrontal and parietal cortex in patients (Grot, Légaré et al., 2017). These two regions are related to attentional processes, manipulation, and encoding strategies, which confer the skills and flexibility required for working memory (Kane and Engle 2002, Baddeley 2003). Interestingly, numerous studies report a cortical thickness reduction in these regions, as well as an alteration of the white fibres interconnecting them in patients with schizophrenia (Goldman, Pezawas et al., 2009). Accordingly, our study showed that anatomical modifications of this network could underpin the specific active binding deficit observed in schizophrenia patients. More specifically, a reduced leftward lateralization of the prefrontal-parietal network could contribute to this specific working memory deficit in patients

Cortical Morphology and MRI Signal Intensity Analysis in Paediatric Epilepsy

Epilepsy encompasses a great variety of aetiologies, and as such is not a single disease but a group of diseases characterised by unprovoked seizures.The primary aim of the work presented in this thesis was to use multimodal structural imaging to improve understanding of epilepsy related brain pathology, both the epileptogenic lesions themselves and extralesional pathology, in order to improve pre-surgical planning in medicationresistant epilepsy and improve understanding of the underlying pathogenic mechanisms. The work focuses on 2 epilepsy aetiologies: focal cortical dysplasia (FCD) (chapters 2 and 3) and mesial temporal lobe epilepsy (chapters 4 & 5). Chapter 2 of this thesis develops surface-based, structural MRI post-processing techniques that can be applied to clinical T1 and FLAIR images to complement current MRI-based diagnosis of focal cortical dysplasias. Chapter 3 uses the features developed in Chapter 2 within a machine learning framework to automatically detect FCDs, obtaining 73% sensitivity using a neural network. Chapter 4 develops an in vivo method to explore neocortical gliosis in adults with TLE, while Chapter 5 applies this method to a paediatric cohort. Finally, the concluding chapter discusses contributions, main limitations and outlines options for future research

Preprocessing methods for morphometric brain analysis and quality assurance of structural magnetic resonance images

Gegenstand der Dissertation ist die Neuentwicklung und Validierung von Verfahren zur Aufbereitung von anatomischen Daten, die mittels Magnetresonanztomographie gewonnen wurden. Ziel ist dabei die Erfassung von morphometrischen Kennwerten zur Beschreibung der Struktur und Form des Gehirns, wie beispielsweise Volumen, Fläche, Dicke oder Faltung der Großhirnrinde. Die Kennwerte erlauben sowohl die Erforschung individueller gesunder und pathologischer Entwicklung als auch der evolutionären Anpassung des Gehirns. Die zur Datenanalyse notwendige Vorverarbeitung beinhaltet dabei die Angleichung von Bildeigenschaften und individueller Anatomie. Die fortlaufende Weiterentwicklung der Scanner- und Rechentechnik ermöglicht eine zunehmend genauere Bildgebung, erfordert aber die kontinuierliche Anpassung existierender Verfahren. Die Schwerpunkte dieser Dissertation lagen in der Entwicklung neuer Verfahren zur (i) Klassifikation der Hirngewebe (Segmentierung), (ii) räumlichen Abbildung des individuellen Gehirns auf ein Durchschnittsgehirn (Registrierung), (iii) Bestimmung der Dicke der Großhirnrinde und Rekonstruktion einer repräsentativen Oberfläche und (iv) Qualitätssicherung der Eingangsdaten. Die Segmentierung gleicht die Bildeigenschaften unterschiedlicher Protokolle an, während die Registrierung anatomische Merkmale normalisiert und so den Vergleich verschiedener Gehirne ermöglicht. Die Rekonstruktion von Oberflächen erlaubt wiederum die Gewinnung einer Vielzahl weiterer morphometrischer Maße zur spezifischen Charakterisierung des Gehirns und seiner Entwicklung. Anhand von simulierten und realen Daten wird die Validität der neuen Methoden belegt und mit anderen Ansätzen verglichen. Die Verfahren sind Bestandteil der Computational Anatomy Toolbox (CAT; http://dbm.neuro.uni-jena.de/cat), deren Schwerpunkt die Vorverarbeitung von strukturellen Daten ist und die Teil des Statistical Parametric Mapping (SPM) Softwarepaketes in MATLAB ist.This Ph.D. thesis focuses on the development, optimization and validation of preprocessing methods of structural magnetic resonance images of the brain. The preprocessing describes the creation of morphometric data that support a statistical analysis of brain anatomy. Image interferences have to be removed to allow a tissue classification (segmentation). In order to compare different subjects a spatial normalization to an average-shaped brain (template) is required, where atlas maps allow identification of specific brain structures and regions of interest. Beside the analysis in a voxel-grid, the cortex can be represented by surfaces that allow further measures such as the cortical thickness or folding. The derived brain features (such as volume, area, and thickness) permit the individual study of normal and pathological development during the lifespan but also of the evolutionary adaption of the brain. The ongoing progress of imaging and computing technology demands continous enhancement of preprocessing tools but also facilitates the exploration of novel approaches and models. The basis of this thesis is the development of a method that uses a tissue segmentation to estimate the cortical thickness and the central surface in one integrated step. Further essential improvements of surface reconstruction algorithms were achieved by specific refinement of processing steps such as (i) the classification of brain tissue (segmentation), (ii) the spatial mapping of the individual brain to an average brain (registration), (iii) determining the thickness of the cerebral cortex and reconstructing a representative surface and (iv) the quality assurance of input data. The validity of the new methods is proven and compared with other approaches by simulated and real data. The procedures are part of the Computational Anatomy Toolbox (CAT; http://dbm.neuro.uni-jena.de/cat), which focuses on the preprocessing of structural data and is part of the Statistical Parametric Mapping (SPM) software package in MATLAB