631827 research-article2016

ANP0010.1177/0004867416631827ANZJP ArticlesLandin-Romero et al.

Research Australian & New Zealand Journal of Psychiatry 1­–13 DOI: 10.1177/0004867416631827

Surface-based brain morphometry and diffusion tensor imaging in schizoaffective disorder

© The Royal Australian and New Zealand College of Psychiatrists 2016 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav anp.sagepub.com

Ramón Landin-Romero1,2,3,4,5, Erick J Canales-Rodríguez1,2, Fiona Kumfor3,4,5, Ana Moreno-Alcázar1,2, Mercè Madre1,6,7, Teresa Maristany8, Edith Pomarol-Clotet1,2 and Benedikt L Amann1,2

Abstract Background: The profile of grey matter abnormalities and related white-matter pathology in schizoaffective disorder has only been studied to a limited extent. The aim of this study was to identify grey- and white-matter abnormalities in patients with schizoaffective disorder using complementary structural imaging techniques. Methods: Forty-five patients meeting Diagnostic and Statistical Manual of Mental Disorders–Fourth Edition criteria and Research Diagnostic Criteria for schizoaffective disorder and 45 matched healthy controls underwent structural-T1 and diffusion magnetic resonance imaging to enable surface-based brain morphometry and diffusion tensor imaging analyses. Analyses were conducted to determine group differences in cortical volume, cortical thickness and surface area, as well as in fractional anisotropy and mean diffusivity. Results: At a threshold of p = 0.05 corrected, all measures revealed significant differences between patients and controls at the group level. Spatial overlap of abnormalities was observed across the various structural neuroimaging measures. In grey matter, patients with schizoaffective disorder showed abnormalities in the frontal and temporal lobes, striatum, fusiform, cuneus, precuneus, lingual and limbic regions. White-matter abnormalities were identified in tracts connecting these areas, including the corpus callosum, superior and inferior longitudinal fasciculi, anterior thalamic radiation, uncinate fasciculus and cingulum bundle. Conclusion: The spatial overlap of abnormalities across the different imaging techniques suggests widespread and consistent brain pathology in schizoaffective disorder. The abnormalities were mainly detected in areas that have commonly been reported to be abnormal in schizophrenia, and to some extent in bipolar disorder, which may explain the clinical and aetiological overlap in these disorders. Keywords Magnetic resonance imaging, schizoaffective disorder, cortical thickness, diffusion tensor imaging, grey and white matter

1FIDMAG

Research Foundation Germanes Hospitalàries, Barcelona, Spain de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain 3Neuroscience Research Australia, Sydney, NSW, Australia 4School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia 5ARC Centre of Excellence in Cognition and its Disorders, Sydney, NSW, Australia 6Departament de Psiquiatria i Medicina Legal, Doctorat de Psiquiatria i Psicologia Clínica, Universitat Autònoma de Barcelona, Barcelona, Spain 7Benito Menni CASM, Sant Boi de Llobregat, Spain 8Department of Radiology, Hospital San Juan de Déu, Barcelona, Spain 2Centro

Corresponding author: Benedikt L Amann, FIDMAG Research Foundation Germanes Hospitalàries, Dr. Antoni Pujadas 38, 08830 Sant Boi de Llobregat, Spain. Email: [email protected]

Australian & New Zealand Journal of Psychiatry

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Introduction Schizoaffective disorder is a severe mental health disorder characterized by both psychotic and mood symptoms, either concurrently or at different time points during the illness. In the initial stages of defining the new Diagnostic and Statistical Manual of Mental Disorders–Fifth Edition (DSM-5), the removal of schizoaffective disorder as a separate diagnostic category was considered, with mood symptoms instead being added as a dimension to schizophrenia and schizophreniform disorder. The disorder was, however, ultimately maintained as an independent diagnostic category as it was felt that there was insufficient neurobiological data to support this substantial change (Cosgrove and Suppes, 2013). Therefore, recent neuroimaging studies have focused on improving the understanding of brain abnormalities in patients with schizoaffective disorder, with the view to better characterizing this disorder at the neurobiological level. Three voxel-based morphometry (VBM) neuroimaging studies comparing healthy controls with well-defined groups of patients with schizoaffective disorder have been reported to date. Results from these studies suggest that extensive neocortical grey matter volume reductions are present in patients with this disorder. The main abnormalities were located in fronto-temporal, parietal, cingulate and insular cortices (Amann et al., 2015; Ivleva et al., 2012, 2013). Additional structural brain imaging techniques enabling the mapping of brain alterations without a priori assumptions, such as surface-based morphometry, may offer further potential in increasing our understanding of schizoaffective disorder. In contrast to VBM, which identifies regional differences in volume, surface-based morphometry allows independent measurement of cortical thickness (CT) and cortical surface area (SA). CT and SA have independent genetic aetiologies and result from different ontogenic stages during corticogenesis (Pontious et al., 2008). Because cortical volume (CV) is a product of CT and SA, a reduction in CV may reflect reduced thickness, reduced area or both. Thus, the individual examination of these measures provides an opportunity to determine the extent to which these divergent neurobiological processes are compromised in the disorder. To date, five neuroimaging studies using surface-based morphometry have investigated patients with schizoaffective disorder. Four of those studies combined them with patients with other mental health disorders (e.g. schizophrenia, bipolar disorder) and did not carry out separate analyses focusing on patients with schizoaffective disorder only (Goldman et al., 2009; Haukvik et al., 2014; Rimol et al., 2010, 2012). A more recent study examined surface-based measures in a large sample of well-defined patients with schizoaffective disorder (Padmanabhan et al., 2015). However, this study focused on within-group correlations between symptom dimensions of psychosis and regional surface-based

ANZJP Articles morphometry measures and did not directly investigate differences in CV, CT and SA between patients with schizoaffective disorder and healthy controls. Of relevance to the present study, the investigation of cortical grey matter measures can be supplemented with the investigation of micro-structural alterations in white matter using diffusion tensor imaging (DTI). This approach ascertains several measures of molecular diffusion, including (1) fractional anisotropy (FA), a measure sensitive to alterations in fibre density, orientational coherence, axonal diameter and myelination of white matter and (2) mean diffusivity (MD), an index sensitive to alterations in tissue water content in white and grey matter due to ischaemic lesions, oedema, neuroinflammation, cell proliferation or necrosis (Alexander et al., 2007). To date, evidence of white-matter alterations in patients with schizoaffective disorder is scarce and, similar to cortical neuroimaging studies, only indirect conclusions can be drawn from previous studies using mixed samples of patients with psychotic spectrum disorders (Antonius et al., 2011; Hatton et al., 2014).

Aims of the study and hypothesis In this study, we aimed to investigate for the first time greyand white-matter abnormalities in a well-characterized sample of patients with schizoaffective disorder in relation to healthy matched controls. In order to improve the characterization of abnormalities in both tissues, a combination of advanced surface-based morphometry and DTI techniques were employed. We predicted (1) that individuals with schizoaffective disorder would show consistent cortical grey- and white-matter abnormalities compared to matched healthy controls, evidenced by spatial overlap of between group differences across different neuroimaging outcome measures; (2) that local abnormalities in CV would be differentially influenced by abnormalities in CT and SA and these would affect the underlying diffusion properties and (3) that individuals with schizoaffective disorder would show widespread abnormalities in regions linked to the emergence of clinical symptoms in the disorder, including the frontal cortex, insula, cingulated, temporal lobes and the primary white-matter tracts connecting these regions.

Methods Subjects A total of 46 patients with a diagnosis of schizoaffective disorder, bipolar type, were recruited for this study from the inpatient and outpatient departments of two community hospitals and one University hospital from the Barcelona area. Patients were diagnosed using Diagnostic and Statistical Manual of Mental Disorders–Fourth Edition (DSM-IV) criteria and the somewhat stricter Research

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Landin-Romero et al. Diagnostic Criteria (RDC) (Heckers, 2012). Diagnoses were made based on a detailed clinical interview and review of case-notes (B.L.A.). Patients also received a follow-up of at least 6 months to longitudinally confirm the diagnosis. Of the 46 patients recruited, 45 were included in the final analyses as one patient was excluded due to a change of diagnosis. At the time of diagnosis and magnetic resonance imaging (MRI) session, 15 patients showed only minor clinical symptoms. The remaining 30 were experiencing psychotic symptoms, and of these, 15 were in the manic phase and 15 were in the depressive phase of their illness. All patients were taking medication either as monotherapy or as a combination of two or three medication classes. Patients were prescribed anticonvulsants (n = 20), lithium (n = 10) or typical or atypical neuroleptics (mean daily dose in chlorpromazine equivalents: 709.01 mg, standard deviation [SD] = 599.11 mg, range 106.70–3303.24 mg). Exclusion criteria for all participants included left-handedness, age 65 years, history of neurological disease or brain injury and/or alcohol/substance abuse in the 12 months prior to participation. All participants were required to have a premorbid IQ in the normal range, as estimated using the Word Accentuation Test (Test de Acentuación de Palabras, TAP) (Gomar et al., 2011), which requires pronunciation of Spanish words which have had the accents removed. The control sample consisted of 45 healthy subjects selected to be individually matched to the patients with schizoaffective disorder for age, sex and premorbid IQ and met the same exclusion criteria described above. Healthy controls were nonmedical staff working in the hospital, their acquaintances or individuals from the community. Healthy controls were interviewed and excluded if they reported a history of mental illness or treatment with psychotropic medication. All patients with schizoaffective disorder and healthy controls underwent structural and diffusion MRI scanning in a single session, using the same 1.5 T GE Sigma scanner (General Electric Medical Systems, Milwaukee, WI, USA), at the Sant Joan de Déu Hospital in Barcelona (Spain). Only images that passed a set of quality-control measures (see image processing steps below) were included. Following quality control, structural MRI data were available for 44 patients and 45 controls and diffusion MRI data were available for 38 patients and 37 matched controls. The study was carried out in accordance with the latest version of the Declaration of Helsinki. The study design was reviewed by the ethical committee ‘Comité Ético de Investigación Clínica de las Hermanas Hospitalarias’ (Barcelona, Spain) and written informed consent of the participants was obtained after the nature of the procedures had been fully explained. All participants were also informed that non-participation would have no direct or indirect influence or consequence on their usual treatment.

MRI data acquisition High-resolution structural-T1 MRI data were acquired with the following acquisition parameters: matrix size 512 × 512; 180 contiguous axial slices; voxel resolution 0.47 × 0.47 × 1 mm3; echo (TE), repetition (TR) and inversion (TI) times, (TE/TR/TI) = 3.93 ms/2000 ms/710 ms, respectively; flip angle 15°. Diffusion-weighted images were recorded using a spinecho echo-planar pulse sequence along 25 gradient directions using three different b-values (500, 750 and 1000 s/ mm2) together with three unweighted T2-b0 (b = 0) images, for a total of 78 volumes per subject. For each image, the following parameters were used: field of view = 289 × 289 mm2, matrix size 128 × 128; number of slices 28, voxel resolution 1.13 × 1.13 × 5 mm3, TE = 107 ms, TR = 8000 ms and flip angle = 90°.

Surface-based morphometry Structural MRI data were analysed with the FreeSurfer image analysis suite, (http://surfer.nmr.mgh.harvard.edu/). Briefly, the pre-processing included motion correction, removal of non-brain tissue, automated Talairach transformation, tessellation of the grey- and white-matter boundaries and surface deformation (Fischl et al., 2002). A number of deformation procedures were performed in the data analysis pipeline, including surface inflation and registration to a spherical atlas. This method uses both intensity and continuity information from the entire three dimensional images in the segmentation and deformation procedures to produce vertex-wise representations of CT, SA and CV, calculated as the element-wise multiplication of CT and SA in each vertex across the cortical mantle, that is, CV = CT × SA. The resultant maps are sensitive to sub-millimetre differences between groups, and have been validated against histological data (Rosas et al., 2002). Prior to the statistical analyses, the individual CT, SA and CV maps were smoothed using a Gaussian filter with full width at half maximum (FWHM) of 15 mm. Finally, vertexwise general linear models were applied to the individual maps. Intracranial volume was included as a covariate in the models (Palaniyappan and Liddle, 2012). Statistical inference was carried out with FreeSurfer tools based on non-parametric permutation testing, using a cluster-wise correction method for multiple comparisons with initial cluster-forming threshold of p 

Surface-based brain morphometry and diffusion tensor imaging in schizoaffective disorder.

The profile of grey matter abnormalities and related white-matter pathology in schizoaffective disorder has only been studied to a limited extent. The...
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