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Dennis Velakoulis

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7 papers

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YNICL Journal 2023 Journal Article

Structural and microstructural thalamocortical network disruption in sporadic behavioural variant frontotemporal dementia

David Jakabek
Brian D. Power
Nicola Spotorno
Matthew D. Macfarlane
Mark Walterfang
Dennis Velakoulis
Christer Nilsson
Maria Landqvist Waldö

Using multi-block methods we combined multimodal neuroimaging metrics of thalamic morphology, thalamic white matter tract diffusion metrics, and cortical thickness to examine changes in behavioural variant frontotemporal dementia. (bvFTD). Twenty-three patients with sporadic bvFTD and 24 healthy controls underwent structural and diffusion MRI scans. Clinical severity was assessed using the Clinical Dementia Rating scale and behavioural severity using the Frontal Behaviour Inventory by patient caregivers. Thalamic volumes were manually segmented. Anterior and posterior thalamic radiation fractional anisotropy and mean diffusivity were extracted using Tract-Based Spatial Statistics. Finally, cortical thickness was assessed using Freesurfer. We used shape analyses, diffusion measures, and cortical thickness as features in sparse multi-block partial least squares (PLS) discriminatory analyses to classify participants within bvFTD or healthy control groups. Sparsity was tuned with five-fold cross-validation repeated 10 times. Final model fit was assessed using permutation testing. Additionally, sparse multi-block PLS was used to examine associations between imaging features and measures of dementia severity. Bilateral anterior-dorsal thalamic atrophy, reduction in mean diffusivity of thalamic projections, and frontotemporal cortical thinning, were the main features predicting bvFTD group membership. The model had a sensitivity of 96%, specificity of 68%, and was statistically significant using permutation testing (p = 0.012). For measures of dementia severity, we found similar involvement of regional thalamic and cortical areas as in discrimination analyses, although more extensive thalamo-cortical white matter metric changes. Using multimodal neuroimaging, we demonstrate combined structural network dysfunction of anterior cortical regions, cortical-thalamic projections, and anterior thalamic regions in sporadic bvFTD.

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YNICL Journal 2022 Journal Article

Cortico-cognition coupling in treatment resistant schizophrenia

Warda T. Syeda
Cassandra M.J. Wannan
Antonia H. Merritt
Jayachandra M. Raghava
Mahesh Jayaram
Dennis Velakoulis
Tina D. Kristensen
Rigas Filippos Soldatos

BACKGROUND: Brain structural alterations and cognitive dysfunction are independent predictors for poor clinical outcome in schizophrenia, and the associations between these domains remains unclear. We employed a novel, multiblock partial least squares correlation (MB-PLS-C) technique and investigated multivariate cortico-cognitive patterns in patients with treatment-resistant schizophrenia (TRS) and matched healthy controls (HC). METHOD: Forty-one TRS patients (age 38.5 ± 9.1, 30 males (M)), and 45 HC (age 40.2 ± 10.6, 29 M) underwent 3T structural MRI. Volumes of 68 brain regions and seven variables from CANTAB covering memory and executive domains were included. Univariate group differences were assessed, followed by the MB-PLS-C analyses to identify group-specific multivariate patterns of cortico-cognitive coupling. Supplementary three-group analyses, which included 23 non-affected first-degree relatives (NAR), were also conducted. RESULTS: Univariate tests demonstrated that TRS patients showed impairments in all seven cognitive tasks and volume reductions in 12 cortical regions following Bonferroni correction. The MB-PLS-C analyses revealed two significant latent variables (LVs) explaining > 90% of the sum-of-squares variance. LV1 explained 78.86% of the sum-of-squares variance, describing a shared, widespread structure-cognitive pattern relevant to both TRS patients and HCs. In contrast, LV2 (13.47% of sum-of-squares variance explained) appeared specific to TRS and comprised a differential cortico-cognitive pattern including frontal and temporal lobes as well as paired associates learning (PAL) and intra-extra dimensional set shifting (IED). Three-group analyses also identified two significant LVs, with NARs more closely resembling healthy controls than TRS patients. CONCLUSIONS: MB-PLS-C analyses identified multivariate brain structural-cognitive patterns in the latent space that may provide a TRS signature.

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YNIMG Journal 2017 Journal Article

Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients

Mireille Nieuwenhuis
Hugo G. Schnack
Neeltje E. van Haren
Julia Lappin
Craig Morgan
Antje A. Reinders
Diana Gutierrez-Tordesillas
Roberto Roiz-Santiañez

Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n=67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n=97); University of São Paulo (Brazil) (n=64); University of Cantabria, Santander (Spain) (n=107); and University of Melbourne (Australia) (n=54). All images were acquired on 1. 5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either “continuous” (n=94) or “remitting” (n=118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p<0. 001). In the single- or multi-center models, illness course could not be predicted with significant accuracy. However, when reducing heterogeneity by restricting the analyses to male patients only, classification accuracy improved in some samples. This study provides proof of concept that combining multi-center MRI data to create a well performing classification model is possible. However, to create complex multi-center models that perform accurately, each center should contribute a sample either large or homogeneous enough to first allow accurate classification within the single-center.

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YNIMG Journal 2010 Journal Article

Hippocampal pathology in individuals at ultra-high risk for psychosis: A multi-modal magnetic resonance study

Stephen J. Wood
Damien Kennedy
Lisa J. Phillips
Marc L. Seal
Murat Yücel
Barnaby Nelson
Alison R. Yung
Graeme Jackson

Although the hippocampus is a key brain region in the pathophysiology of schizophrenia, it is unclear whether structural or biochemical abnormalities predate illness onset. In this study, we used magnetic resonance imaging and spectroscopy data acquired prior to both the onset of psychosis and treatment with antipsychotics to determine this. Sixty-six young people clinically at ultra high-risk of development of psychosis were recruited, 59 of whom did not later develop a psychotic disorder and 7 who had done so after at least 24months follow-up. These participants were compared with 29 healthy comparison subjects on multiple independent magnetic resonance measures: hippocampal volume, hippocampal T2 relaxation time, and medial temporal lobe metabolite concentrations (including N-acetylaspartate). We found similar reductions in left hippocampal volume in the at-risk group compared to comparison subjects regardless of later transition status; on the right this only reached significance for the at-risk group who did not transition to psychosis. T2 relaxation time in the left hippocampal head was significantly elevated in the later-psychotic group, and this elevation positively correlated with total positive symptoms in the UHR group as a whole. Medial temporal lobe metabolite concentrations did not differ. These findings suggest that there are subtle pathological changes in the hippocampus prior to the development of psychosis, but that they are limited to the left hippocampal head. However, standard measures of neuroanatomical disturbance do not appear to be predictive of later transition, and instead are likely to be non-specific and common in cases that later develop a non-psychotic disorder.

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YNIMG Journal 2010 Journal Article

Shape analysis of the neostriatum in frontotemporal lobar degeneration, Alzheimer's disease, and controls

Jeffrey Chee Leong Looi
Mark Walterfang
Martin Styner
Leif Svensson
Olof Lindberg
Per Östberg
Lisa Botes
Eva Örndahl

Background and purpose: Frontostriatal circuit mediated cognitive dysfunction has been implicated in frontotemporal lobar degeneration (FTLD), but not Alzheimer's disease, or healthy aging. We measured the neostriatum (caudate nucleus and putamen) volume in FTLD (n =34), in comparison with controls (n =27) and Alzheimer's disease (AD, n =19) subjects. Methods: Diagnoses were based on international consensus criteria. Manual bilateral segmentation of the caudate nucleus and putamen was conducted blind to diagnosis by a single analyst, on MRI scans using a standardized protocol. Intra-cranial volume was calculated via a stereological point counting technique and was used for scaling the shape analysis. The manual segmentation binaries were analyzed using UNC Shape Analysis tools (University of North Carolina) to perform comparisons among FTLD, AD, and controls for global shape, local p-value significance maps, and mean magnitude of shape displacement. Results: Shape analysis revealed that there was significant shape difference between FTLD, AD, and controls, consistent with the predicted frontostriatal dysfunction and of significant magnitude, as measured by displacement maps. There was a lateralized difference in shape for the left caudate for FTLD compared to AD; non-specific global atrophy in AD compared to controls; while FTLD showed a more specific pattern in regions relaying fronto- and corticostriatal circuits. Conclusions: Shape analysis shows regional specificity of atrophy, manifest as shape deflation, with implications for frontostriatal and corticostriatal motoric circuits, in FTLD, AD, and controls.

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YNIMG Journal 2009 Journal Article

Morphometric abnormalities and hyperanxiety in genetically epileptic rats: A model of psychiatric comorbidity?

Viviane Bouilleret
R. Edward Hogan
Dennis Velakoulis
Michael R. Salzberg
Lei Wang
Gary F. Egan
Terence J. O'Brien
Nigel C. Jones

Background Imaging studies of epilepsy patients with comorbid affective disturbance demonstrate morphometric changes in limbic brain regions implicated in psychiatric disease. Genetic Absence Epilepsy Rats from Strasbourg (GAERS), specifically bred for their epilepsy phenotype, also exhibit elevated anxiety-like behaviors suggesting a common causality. Here we examined whether relevant cerebral morphological alterations exist in this rat strain using volumetric measurements and large deformation high dimensional mapping (HDM-LD), a tool recently validated to produce accurate three-dimensional surface representations of the hippocampus. Methods Volumetric MRI and the Open Field test of anxiety were performed in adult female GAERS (n =12) and Non-Epileptic Controls (NEC; n =11). The volumes of selected brain regions, including cortex, hippocampus, amygdala, thalamus, hypothalamus and lateral ventricles, were measured using Region-Of-Interest analysis from the MRI data and total volumes compared between the two strains. Results GAERS had increased amygdala (right: p =0. 003; left p <0. 001), cortices (right: p =0. 006; left p =0. 012) and ventricular volumes (p =0. 002) when compared with NEC rats. Further, HDM-LD showed GAERS to have hippocampal volume loss in two regions: the medial hippocampal surface immediately caudal to the hippocampal commissure, and the lateral hippocampal surface over the mid-portion of the septotemporal axis. GAERS exhibited increased anxiety in the Open Field compared with NEC rats: reduced distance traveled (p <0. 001) and reduced time in the centre area (p =0. 042). Conclusions Morphometric brain changes in GAERS could be relevant to their hyperanxious and epileptic phenotypes. This model may be useful in illuminating the pathogenesis of affective disorders generally, as well as modeling psychiatric comorbidities of epilepsy.

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YNIMG Journal 2006 Journal Article

The influence of sulcal variability on morphometry of the human anterior cingulate and paracingulate cortex

Alex Fornito
Sarah Whittle
Stephen J. Wood
Dennis Velakoulis
Christos Pantelis
Murat Yücel

Human anterior cingulate (ACC) and paracingulate (PaC) cortices play an important role in cognitive and affective regulation and have been implicated in numerous psychiatric and neurological conditions. The region they comprise displays marked inter-individual variability in sulcal and gyral architecture, and although recent evidence suggests that this variability has functional significance, it is often ignored in automated and region-of-interest (ROI) morphometric investigations. This has lead to confounded interpretation of results and inconsistent findings across a number of studies and in a variety of clinical populations. In this paper, we present a reliable method for parcellating the dorsal, ventral, and subcallosal ACC and PaC that accounts for individual variation in the local cortical folding pattern. We also investigated the effect of one well characterized morphological variation, the incidence of the paracingulate sulcus (PCS), on regional volumes in 24 (12 male, 12 female) healthy participants. The presence of a PCS was shown to affect both ACC and PaC volumes, such that it was associated with an 88% increase in paracingulate cortex and a concomitant 39% decrease in cingulate cortex. These findings illustrate the potential confounds inherent in morphometric approaches that ignore or attempt to minimize inter-individual variations in sulcal and gyral anatomy and underscore the need to consider this variability when attempting to understand disease processes or characterize brain structure–function relationships.

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