Identification of structural brain alterations in adolescents with depressive symptomatology

Introduction: Depressive symptoms can emerge as early as childhood and may lead to adverse situations in adulthood. Studies have examined structural brain alternations in individuals with depressive symptoms, but findings remain inconclusive. Furthermore, previous studies have focused on adults or used a categorical approach to assess depression. The current study looks to identify grey matter volumes (GMV) that predict depressive symptomatology across a clinically concerning sample of adolescents. Methods: Structural MRI data were collected from 338 clinically concerning adolescents (mean age = 15.30 SD=2.07; mean IQ = 101.01 SD=12.43; 132 F). Depression symptoms were indexed via the Mood and Feelings Questionnaire (MFQ). Freesurfer was used to parcellate the brain into 68 cortical regions and 14 subcortical regions. GMV was extracted from all 82 brain areas. Multiple linear regression was used to look at the relationship between MFQ scores and region-specific GMV parameter. Follow up regressions were conducted to look at potential effects of psychiatric diagnoses and medication intake. Results: Our regression analysis produced a significant model (R2 = 0.446, F(86, 251) = 2.348, p \u3c 0.001). Specifically, there was a negative association between GMV of the left parahippocampal (B = -0.203, p = 0.005), right rostral anterior cingulate (B = -0.162, p = 0.049), and right frontal pole (B = -0.147, p = 0.039) and a positive association between GMV of the left bank of the superior temporal sulcus (B = 0.173, p = 0.029). Follow up analyses produced results proximal to the main analysis. Conclusions: Altered regional brain volumes may serve as biomarkers for the development of depressive symptoms during adolescence. These findings suggest a homogeneity of altered cortical structures in adolescents with depressive symptoms

Structural Brain Imaging of Long-Term Anabolic-Androgenic Steroid Users and Nonusing Weightlifters

AbstractBackgroundProlonged high-dose anabolic-androgenic steroid (AAS) use has been associated with psychiatric symptoms and cognitive deficits, yet we have almost no knowledge of the long-term consequences of AAS use on the brain. The purpose of this study is to investigate the association between long-term AAS exposure and brain morphometry, including subcortical neuroanatomical volumes and regional cortical thickness.MethodsMale AAS users and weightlifters with no experience with AASs or any other equivalent doping substances underwent structural magnetic resonance imaging scans of the brain. The current paper is based upon high-resolution structural T1-weighted images from 82 current or past AAS users exceeding 1 year of cumulative AAS use and 68 non–AAS-using weightlifters. Images were processed with the FreeSurfer software to compare neuroanatomical volumes and cerebral cortical thickness between the groups.ResultsCompared to non–AAS-using weightlifters, the AAS group had thinner cortex in widespread regions and significantly smaller neuroanatomical volumes, including total gray matter, cerebral cortex, and putamen. Both volumetric and thickness effects remained relatively stable across different AAS subsamples comprising various degrees of exposure to AASs and also when excluding participants with previous and current non-AAS drug abuse. The effects could not be explained by differences in verbal IQ, intracranial volume, anxiety/depression, or attention or behavioral problems.ConclusionsThis large-scale systematic investigation of AAS use on brain structure shows negative correlations between AAS use and brain volume and cortical thickness. Although the findings are correlational, they may serve to raise concern about the long-term consequences of AAS use on structural features of the brain

Association between Psychotic Symptoms and Cortical Thickness Reduction across the Schizophrenia Spectrum

The current study provides a complete MRI analysis of thickness throughout the cerebral cortical mantle in patients with schizophrenia (SZ) and rigorously screened and matched unaffected relatives and controls and an assessment of its relation to psychopathology and subjective cognitive function. We analyzed 3D-anatomical magnetic resonance imaging data sets, obtained at 3 Tesla, from three different subject groups: 25 SZ patients, 29 first-degree relatives and 37 healthy control subjects. We computed whole-brain cortical thickness using the Freesurfer software and assessed group differences. We also acquired clinical and psychometric data. The results showed markedly reduced cortical thickness in SZ patients compared with controls, most notably in the frontal and temporal lobes, in the superior parietal lobe and several limbic areas, with intermediate levels of cortical thickness in relatives. In both patients and relatives, we found an association between subjective cognitive dysfunction and reduced thickness of frontal cortex, and predisposition towards hallucinations and reduced thickness of the superior temporal gyrus. Our findings suggest that changes in specific cortical areas may predispose to specific symptoms, as exemplified by the association between temporal cortex thinning and hallucinations

Segmentation of medical images under topological constraints

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2006.Includes bibliographical references (p. 135-142).Major advances in the field of medical imaging over the past two decades have provided physicians with powerful, non-invasive techniques to probe the structure, function, and pathology of the human body. This increasingly vast and detailed amount of information constitutes a great challenge for the medical imaging community, and requires significant innovations in all aspect of image processing. To achieve accurate and topologically-correct delineations of anatomical structures from medical images is a critical step for many clinical and research applications. In this thesis, we extend the theoretical tools applicable to the segmentation of images under topological control, apply these new concepts to broaden the class of segmentation methodologies, and develop generally applicable and well-founded algorithms to achieve accurate segmentations of medical images under topological constraints. First, we introduce a digital concept that offers more flexibility in controlling the topology of digital segmentations. Second, we design a level set framework that offers a subtle control over the topology of the level set components. Our method constitutes a trade-off between traditional level sets and topology-preserving level sets.(cont.) Third, we develop an algorithm for the retrospective topology correction of 3D digital segmentations. Our method is nested in the theory of Bayesian parameter estimation, and integrates statistical information into the topology correction process. In addition, no assumption is made on the topology of the initial input images. Finally, we propose a genetic algorithm to accurately correct the spherical topology of cortical surfaces. Unlike existing approaches, our method is able to generate several potential topological corrections and to select the maximum-a-posteriori retessellation in a Bayesian framework. Our approach integrates statistical, geometrical, and shape information into the correction process, providing optimal solutions relatively to the MRI intensity profile and the expected curvature.by Florent Ségonne.Ph.D

Functional Brain Organization in Space and Time

The brain is a network functionally organized at many spatial and temporal scales. To understand how the brain processes information, controls behavior and dynamically adapts to an ever-changing environment, it is critical to have a comprehensive description of the constituent elements of this network and how relationships between these elements may change over time. Decades of lesion studies, anatomical tract-tracing, and electrophysiological recording have given insight into this functional organization. Recently, however, resting state functional magnetic resonance imaging (fMRI) has emerged as a powerful tool for whole-brain non-invasive measurement of spontaneous neural activity in humans, giving ready access to macroscopic scales of functional organization previously much more difficult to obtain. This thesis aims to harness the unique combination of spatial and temporal resolution provided by functional MRI to explore the spatial and temporal properties of the functional organization of the brain. First, we establish an approach for defining cortical areas using transitions in correlated patterns of spontaneous BOLD activity (Chapter 2). We then propose and apply measures of internal and external validity to evaluate the credibility of the areal parcellation generated by this technique (Chapter 3). In chapter 4, we extend the study of functional brain organization to a highly sampled individual. We describe the idiosyncratic areal and systems-level organization of the individual relative to a standard group-average description. Further, we develop a model describing the reliability of BOLD correlation estimates across days that accounts for relevant sources of variability. Finally, in Chapter 5, we examine whether BOLD correlations meaningfully vary over the course of single resting-state scans

Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

Surface-based analysis of cortical thickness in healthy and remitted depressed subjects

Depression gehört zu den weltweit vier häufigsten Ursachen von Krankheitslast und ist assoziiert mit medizinischer Morbidität und Mortalität. Charakteristisch für Depression sind funktionelle und strukturelle Veränderungen des Gehirns als Zeichen dysfunktionaler Gehirnschaltkreise der Emotionsverarbeitung sowie der kognitiven Kontrolle. Viele Studien haben sich hauptsächlich mit der akuten Phase von Depression beschäftigt, in der sich in erster Linie vermutlich zustandsabhängige pathophysiologische Veränderungen zeigen, wodurch die eigentlichen neurobiologischen Veränderungen, die im Zusammenhang mit genetischer Vulnerabilität für Depression stehen, verschleiert werden. Um tatsächliche Merkmals-Marker zu finden, setzt die vorliegende Diplomarbeit den Schwerpunkt auf remittierte Depression unter Verwendung der kortikalen Dicke als Maß für die morphologische Integrität. Strukturelle Magnetresonanztomographie-Scans wurden an 28 remittiert Depressiven, die keine Form von Behandlung innerhalb der letzten drei Monate erhalten haben und ohne aktuelle medikamentöse Behandlung bzw. psychiatrische Erkrankung waren, sowie an 28, in Bezug auf Alter und Geschlecht abgestimmte, Gesunden durchgeführt. Die erhobenen, strukturellen Bilder wurden mittels eines oberflächen-basierten Verfahrens, welches im Kontrast zu reinen volumetrischen Ansätzen, die topologischen Faltungsmuster des Kortex realitätsgetreu abbildet, wodurch die anatomische Variabilität reduziert und die statistische Power erhöht werden, ausgewertet. Mit dem Ziel mögliche Gruppenunterschiede zwischen Depressiven und Gesunden ausfindig zu machen, wurden die Daten im Anschluss an die Präprozessierung mittels eines ‚Allgemeinen linearen Modells’ statistisch analysiert. Um mögliche Einflüsse von Persönlichkeitsmerkmalen zu untersuchen, wurden zusätzlich psychometrische Variablen in das Modell integriert. Die statistische Analyse konnte Unterschiede in der kortikalen Dicke zwischen Depressiven und Gesunden zeigen, die im anterioren midzingulären Kortex lokalisiert sind. In Anbetracht dessen dass der anteriore midzinguläre Kortex eine wichtige Rolle bei der Emotionskontrolle bzw. –regulation spielt, deuten die Ergebnisse auf eine beeinträchtigte Top-Down-Kontrolle von Emotionshirnschaltkreisen hin, was sich auf der Verhaltensebene vermutlich in Form eine erhöhten Empfindlichkeit gegenüber Stresseinflüssen äußert. Die vorliegenden Ergebnisse können hoffentlich zu einem vertieften Verständnis der neurobiologischen Grundlagen von Depression beitragen und legen womöglich einen potentiellen, strukturellen Krankheitsmarker, der die Vulnerabilität für Depression widerspiegelt, nahe.Major depressive disorder (MDD) is among the four leading causes of disease burden throughout the world and is associated with medical morbidity and mortality across the lifespan. It is characterized by functional and structural alterations of the brain reflecting dysfunctional brain circuits of emotion processing and cognitive control. A vast number of studies have focussed on alterations in the acute state of depression which may primarily represent state-dependent pathophysiological changes thereby masking those neurobiological changes mainly associated with genetic susceptibility to depression. Thus, the present diploma thesis focuses on the remitted state of MDD aiming to reveal trait markers of MDD by using cortical thickness as a measure of morphological integrity. Structural magnetic resonance imaging scans of 28 remitted major depressive patients without any current drug treatment or psychiatric illness, who did not receive any treatment for at least three months before assessment and 28 age and gender-matched healthy controls, were obtained. Structural images were analyzed using a mere surface-based approach, which, in contrast to standard volumetric methods, preserves the topological folding patterns of the cortex, and, by that, reduces anatomical variability thereby increasing statistical power. After standard preprocessing the data were analyzed within a general linear model assessing the effects of group differences between patients and healthy controls. Additionally, psychometric variables were included in statistical analysis aiming to investigate potential influences of personality traits. Analysis revealed cortical thickness alterations in remitted MDD patients compared to healthy controls localized within the anterior midcingulate cortex. Since the anterior midcingulate cortex is mainly implicated in emotional control and regulation, these results might suggest impaired top-down control over limbic circuits on a functional level indicating increased stress responsiveness even when mood is restored on a behavioural level. These findings may enhance the understanding of the neurobiology of remitted MDD and provide a putative structural disease marker reflecting vulnerability to depression

Cortical Cartography: Mapping Functional Areas Across the Human Brain with Resting State Functional Connectivity MRI

Human behavior and cognition are largely supported by the cerebral cortex, a structure organized at many physical scales ranging from individual neurons up to distributed systems of multiple interconnected “functional areas”. Each functional area possesses a unique combination of inputs, outputs, and internal structure, and is thought to make a distinct contribution to information processing. Thus, the study of each area\u27s normal function, developmental trajectory, and modified responses following loss or injury may greatly enhance our understanding of cognition. Indeed, one of the: often unsaid) overarching goals of functional neuroimaging is to use differential activity between conditions to identify specific information processing operations reflected in these functional areas. Unfortunately, delineating a complete collection of functional areas in any mammal, let alone non-invasively in humans, is not straightforward and currently incomplete. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity: rs-fcMRI), are especially promising as a way to delineate functional areas since they localize differences in patterns of correlated activity across large expanses of cortex. Presented here is the exploration, development, initial application, and first order validation of rs-fcMRI mapping, the non-invasive delineation of putative functional areas and boundaries across the cortical surface in individual humans using rs-fcMRI. rs-fcMRI ‘contour’ maps can be created in individual subjects which delineate sharp transitions and stable locations in correlation patterns. Several of the strongest and most resilient of these features can be consistently detected both across time within subject, are comparable across subject, independent cohort, and scanner, and appear to represent known functional-anatomical divisions. An initial validation of rs-fcMRI mapping against task-related activity, finds consistency with task-related fMRI results for two separate tasks in two groups of subjects, as well as in individual data. These results provide a proof-of-concept for using rs-fcMRI mapping to describe a putative distribution of functional areas and boundaries within single individuals, as well as to potentially improve functional neuroimaging studies in basic, translational, and clinical settings through the independent delineation of functional areas that can be compared across subjects, groups, and studies

Análisis de volumetría y espesor cortical en imágenes de resonancia magnética estructural para cuantificar alteraciones cerebrales causadas por el trastorno del espectro autista

[ES] El trastorno del espectro autista (TEA) es un conjunto de desórdenes en el desarrollo neurológico caracterizados por anomalías en la cognición social, déficits en la comunicación y patrones de comportamiento repetitivos. Diversos estudios han investigado las anomalías estructurales asociadas a este trastorno mediante técnicas de neuroimagen, con el fin de obtener un diagnóstico cuantitativo y poder desarrollar tratamientos. Sin embargo, los resultados obtenidos han sido muy variados. Debido a la complejidad y heterogeneidad del TEA, se necesita una amplia muestra para revelar sus mecanismos neurales. La base de datos ABIDE (Autism Brain Imaging Data Exchange) surgió con el objetivo de juntar las bases de datos de distintos centros de investigación y posibilitar su acceso a la comunidad científica. Esta base de datos contiene imágenes de resonancia magnética estructural y funcional de 1112 sujetos (personas con TEA y controles sanos). El objetivo de este Trabajo Fin de Grado es el análisis de las diferencias en volumen cerebral total, volumen de materias y en volumen, área y espesor de las regiones corticales y subcorticales, entre personas autistas y controles. Se han analizado sujetos controles y autistas de ABIDE, emparejados por diversas variables demográficas. Se han dividido los sujetos en cuatro rangos de edad para analizar cómo varían estas diferencias con los años. Los resultados obtenidos en los cuatro rangos de edad han sido distintos. Se han obtenido una serie de regiones corticales y subcorticales con diferencias en volumen y espesor (p < 0,05), aunque no se ha observado ninguna diferencia en área. Respecto al volumen de materias, sólo se han obtenido diferencias significativas en el grupo de adultos (≥ 23 años) donde el grupo de controles ha presentado un mayor volumen de sustancia blanca. Estos resultados confirman el conocimiento obtenido por otros autores en estudios previos.[CA] El trastorn de l’espectre autista (TEA) és un conjunt de desordres en el desenvolupament neurològic caracteritzats per anomalies en la cognició social, dèficits en la comunicació i patrons de comportament repetitius. Són diversos els estudis que han buscat anomalies estructurals associades a aquest trastorn mitjançant tècniques de neuroimatge, amb la finalitat d’obtindre un diagnòstic objectiu i poder desenvolupar tractaments per al TEA, però els resultats obtinguts per diversos autors han sigut molt variats. Degut a la complexitat i heterogeneïtat del TEA, es necessita una àmplia mostra per a revelar els seus mecanismes neurals. La base de dades ABIDE (Autism Brain Imaging Data Exchange) va sorgir amb l’objectiu d’unir bases de dates de distints centres d’investigació i possibilitar el seu accés a la comunitat científica. Esta base de dates conté imatges de ressonància magnètica estructural i funcional de 1112 subjectes (persones amb TEA i controls sans). L’objectiu d’aquest Treball de Fi de Grau es l’anàlisi de les diferències en volum cerebral total, volum de matèries i en volum, àrea i espessor de les regions corticals i subcorticals, entre persones autistes i controls. S’han analitzat subjectes controls i autistes d’ABIDE, emparellats per diverses variables demogràfiques. S’han dividit els subjectes en quatre rangs d’edat per analitzar com varien aquestes diferències amb els anys. Els resultats obtinguts en els quatre rangs d’edat han sigut distints. S’han obtingut una sèrie de regions corticals i subcorticals amb diferències en volum i espessor (p < 0,05) però no s’ha observat ninguna diferència en àrea. Respecte a les diferències en volum de matèries, sols s’han obtingut diferències significatives en el grup d’adults (≥ 23 anys) on el grup de controls ha presentat un major volum de substància blanca. Alguns dels descobriments realitzats repliquen els resultats obtinguts per altres autors en estudis previs.[EN] Autism spectrum disorder (ASD) is a group of developmental neurologic disorders characterized by anomalies in social cognition, communication deficits and repetitive behavior patterns. Many studies have looked for structural anomalies associated with this disorder with the aim of providing a quantitative diagnosis and developing some treatments. However, there are discrepancies in the obtained results. Due to the complexity and heterogeneity of ASD, a large sample is needed to reveal ASD’s neural mechanisms. ABIDE database (Autism Brain Imaging Data Exchange) emerged with the aim of joining different investigation center databases and enabling its access to the scientific community. This database contains structural and functional magnetic resonance images of 1112 subjects (patients with ASD and healthy controls). The objective of this final degree project is to analyze differences in total cerebral volume, tissue volume and volume, area and thickness of the cortical and subcortical cerebral regions between patients with autism and controls. It has been checked that the sets of subjects used in the study were homogeneous. Individuals have been matched using a serial of demographical variables. Subjects are divided in four age ranges to analyze how these differences vary with the years. Results obtained in the four age ranges have been different. Some cortical and subcortical regions have thickness and volume differences (p < 0,05). However, no differences in area have been obtained. Regarding tissue volume differences, significant differences have only been obtained in the adults group (≥ 23 years old) where control group has an increased white matter volume. These findings replicate results obtained by other authors in previous studies.Ferrero Montes, L. (2017). Análisis de volumetría y espesor cortical en imágenes de resonancia magnética estructural para cuantificar alteraciones cerebrales causadas por el trastorno del espectro autista. http://hdl.handle.net/10251/85690.TFG