Combined analyses of thalamic volume, shape and white matter integrity in first-episode schizophrenia

NeuroImage 47 (2009) 1163–1171

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NeuroImage j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / y n i m g

Combined analyses of thalamic volume, shape and white matter integrity in first-episode schizophrenia Anqi Qiu a,b,c,⁎, Jidan Zhong d, Steven Graham b,e, Ming Ying Chia f, Kang Sim f,g a

Division of Bioengineering, National University of Singapore, Singapore Clinical Imaging Research Center, National University of Singapore, Singapore Singapore Institute for Clinical Sciences, the Agency for Science, Technology and Research, Singapore d NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore e Department of Psychology, National University of Singapore, Singapore f Research Department, Institute of Mental Health, Singapore g Department of General Psychiatry, Institute of Mental Health, Singapore b c

a r t i c l e

i n f o

Article history: Received 11 January 2009 Revised 26 March 2009 Accepted 8 April 2009 Available online 16 April 2009 Keywords: Thalamic shape First-episode schizophrenia Executive functioning Spatial working memory Large deformation diffeomorphic metric mapping Parallel transport Magnetic resonance imaging Diffusion tensor imaging

a b s t r a c t The thalamus has been considered to be integral to the pathophysiology of schizophrenia. To determine whether its anatomical abnormalities may be associated with cognitive deficits in the onset of schizophrenia, we assessed thalamic volume, shape, white matter integrity, and their correlations with cognition in patients with first-episode schizophrenia. T1-weighted magnetic resonance and diffusion tensor (DT) images were collected in 49 healthy comparison controls (CON) and 32 patients with FES (FES). Large deformation diffeomorphic metric mapping (LDDMM) algorithms were used to delineate and assess the thalamic shape from MRI scans. The thalamic white matter integrity was quantified by fractional anisotropy (FA) and mean diffusivity (MD) averaged over the thalamus using DTI. Our analysis revealed that FES did not differ from CON in FA and MD but did differ markedly from them in the thalamic volume and shape. Patients with FES also performed poorly in spatial working memory and executive tasks. The correlation study found that regional thalamic shapes highly correlate with the two cognitive scores in the entire sample and healthy comparison controls but not in patients with FES even though no correlation was found between the thalamic volumes with the two cognitive scores in any group. Left thalamic FA was correlated with spatial working memory deficits in FES. Our findings suggest that thalamic volume and shape abnormalities are evident at the onset of FES prior to thalamic abnormal white matter integrity. Altered microstructural white matter integrity assessed using DTI may not be apparent in FES but may be observed as the disease progresses. Cognitive deficits related to spatial working memory and executive functioning in FES were observed in the context of loss of their normal relationship with the thalamic shapes, that is, regionallyspecific thalamic shape compression is associated with poor performance in executive functioning and spatial working memory. © 2009 Elsevier Inc. All rights reserved.

Introduction The thalamus has been considered to be integral to the pathophysiology of schizophrenia due to its central anatomy and functional connections with the frontal and limbic system that are implicated in the development of schizophrenia symptoms (Andreasen et al., 1999; Sim et al., 2006). Magnetic resonance-based volumetric analysis has been used to study the thalamic volume in patients with schizophrenia (Bagary et al., 2002; Deicken et al., 2002; Hulshoff Pol et al., 2001; James et al., 2004; Konick and Friedman, 2001), primarily pursuing the hypothesis that schizophrenia would be associated with smaller

⁎ Corresponding author. Division of Bioengineering, National University of Singapore, 7 Engineering Drive 1, Block E3A #04-15, 117574 Singapore. Fax: +65 6872 3069. E-mail address: [email protected] (A. Qiu). 1053-8119/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2009.04.027

thalamic volumes. These studies have yielded conflicting results, where some have found smaller thalamic volumes in schizophrenia (Hulshoff Pol et al., 2001; James et al., 2004; Konick and Friedman, 2001), while others found no difference between schizophrenia and healthy comparison cohorts (Bagary et al., 2002; Deicken et al., 2002). These discrepancies may be due to methodological differences in thalamic anatomical definitions or differences in the populations studied, which could reflect the underlying biological heterogeneity of schizophrenia. Potential confounds of this heterogeneity have been suggested in illness chronicity and prior treatment. Thus one would be expect that studies of first-episode schizophrenia (FES) patients would confer the opportunity to study thalamic changes which are less confounded by the effects of illness chronicity or treatment with medications. Against this background, this study sought to determine thalamic volume and shape abnormalities in FES. Most studies on the thalamus

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in patients with FES have thus far been limited to examination of whole thalamic volumes and are prone to missing localized abnormalities. Large deformation diffeomorphic metric mapping (LDDMM) (Qiu and Miller 2008; Vaillant and Glaunes 2005; Vaillant et al., 2007) is a powerful computational tool that provides detailed analysis of the morphological shape of brain regions, thereby allowing for precise examination of these structures, well beyond what has been examined in prior MRI studies, including those of the thalami in patients with FES. Thus far, LDDMM has widely been used to study neurodegenerative diseases and neurodevelopment disorders, such as Alzheimer's disease (AD) and attention deficit hyperactivity disorder (ADHD), and has revealed specific-regional shape changes associated with the diseases (Qiu et al., 2009a,b, 2007). In schizophrenia, LDDMM offers a critical opportunity to precisely localize differences within the thalamus. Furthermore, it can be used to determine the nature of those differences, both in terms of direction (inward or outward deformation) and degree. In doing so, it is possible to further specify FES-associated differences in brain structures observed using volumetric techniques and more importantly to detect localized differences for shedding light on inconsistent thalamic volumetric findings in schizophrenia. Based on previous findings revealing gray matter volume loss and neuronal number reduction in specific thalamic nuclei associated with schizophrenia (Byne et al., 2001, 2008a,b; Dorph-Petersen et al., 2004; Konick and Friedman, 2001), our study hypothesized thalamic volume reduction and regional-specific shape abnormalities in FES and examined this hypothesis using the state of the art LDDMM techniques. Additionally, recent post-mortem studies suggested that variations in thalamic oligodendrocyte number in schizophrenia may reflect variations in the myelination of axons originating from or passing through the thalamic nuclei (Byne et al., 2008b). We thus sought to investigate mean diffusivity (MD) and fractional anisotropy (FA) of the thalamus using diffusion tensor imaging (DTI) for evaluating altered white matter integrity in the thalamus in patients with FES. To the best of our knowledge, there is no study to date which concomitantly evaluates thalamic structural characteristics in terms of its volume, shape, the integrity of the white matter in FES. Given the diffuse cortical projections of the thalamus, its anomalous anatomy would be expected to disrupt a multiplicity of cognitive functions. In particular, executive functioning and spatial working memory appear to represent core features of schizophrenia mainly reflected by dysfunctions of the dorsolateral prefrontal cortex. We thus also explored the association of thalamic anatomical features with executive functioning and spatial working memory in FES.

Methods Subjects The subjects with FES and healthy comparison subjects (CON) for this study were respectively recruited from the Institute of Mental Health, Singapore and the community by advertisements. The study was approved by the Institutional Review Boards of the Institute of Mental Health, Singapore, as well as that of the National Neuroscience Institute, Singapore. All subjects gave their written informed consent following a complete description of the study. Demographic information for the two groups of subjects is given in Table 1. Thirty-two patients with DSM-IV diagnosis of FES participated this study. Confirmation of the diagnosis was made for all patients by a psychiatrist using information obtained from the clinical history, existing medical records, interviews with significant others as well as the administration of the Structured Clinical Interview for DSM-IV disorders-Patient Version (SCID-P). The patients were maintained on a stable dose of antipsychotic medications (22 on second generation antipsychotics, 8 on first generation antipsychotics and 2 were on a combination of first and second generation antipsychotics; mean daily chlorpromazine equivalents of 186 mg (range 30 to 600 mg) for at least 2 weeks, and did not have their medications withdrawn for the purpose of the study). There was no history of any significant neurological illness such as seizure disorder, head trauma, or cerebrovascular accident. No subject met DSM-IV criteria for alcohol or other substance abuse within the preceding 3 months. Forty-nine healthy comparison subjects were screened using the SCID-NP to be free of any Axis I psychiatric disorder, and had no history of any major neurological, medical illnesses, substance abuse or psychotropic medication use. Clinical and neurocognitive measures The Positive and Negative Symptom Scale (PANSS) was used to assess psychopathology and symptom severity, while the Global Assessment of Functioning (GAF) Scale was used to assess the level of psychosocial functioning. Both scales were administered by a psychiatrist to all the participants. A trained psychometrist administered the battery of neuropsychological assessments which assessed (a) abstract reasoning and non-verbal intelligence (Raven's Progressive Matrices), (b) attention/vigilance (Conners' Continuous Performance Test II), (c) executive functioning (Wisconsin Card Sorting Test), (d) verbal and spatial working memory span (Digit and Spatial Span subtest of the Weschsler Adult Intelligence Scale-III, WAIS-III), and (e) visuo-constructional skills (Block Design subtest of the WAIS-III).

Table 1 Demographic, clinical and neurocognitive features in this study. CON N = 49 Age (SD) Sex (% female) Handness (% right) Years of education (SD) Mean illness duration (years) (SD) Nonverbal intelligence Executive functioning (SD) (perservative errors) Spatial working memory (SD) Verbal working memory (SD) Attention (SD) Visuo-constructional skills (SD) Antipsychotic dose (mg CPZ equivalents) PANSS total scores GAF Total intracranial volume (cm3) (SD)

31.1 (9.6) 32.6% (16/49) 87.7% (43/49) 14.2 (2.0) – 54.5 (4.0) 12.4 (8.5) 8.9 (1.7) 10.5 (2.2) 51.7 (10.5) 47.3 (11.9) – – – 1540.7 (160.9)

Key: CON — healthy controls, FES —patients with first-episode schizophrenia, SD—standard deviation.

FES N = 32

Test statistic

p-value

28.0 (6.4) 25.0% (8/32) 90.6% (29/32) 11.2 (2.9) 2.8 (2.1) 47.7 (10.5) 19.9 (14.9) 7.8 (2.2) 11.3 (2.8) 52.8 (10.3) 44.5 (13.5) 186.0 (146.0) 41.0 (8.8) 51.5 (17.9) 1491.1 (126.3)

t79 = 1.63 χ1 = 0.54 χ1 = 0.30 t79 = 3.82 – t79 = 3.19 t79 = 2.32 t79 = 2.17 t79 = 1.19 t79 = 0.39 t79 = 0.85 – – – t79 = 1.47

0.1064 0.5391 0.2953 0.0003 – 0.0020 0.0237 0.0368 0.2360 0.6960 0.3980 – – – 0.1453

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Image acquisition

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We shall call the logarithmic scale of the Jacobian determinant as deformation map. Its value represents the ratio of each subject's thalamic volume to the template volume in the logarithmic scale: i.e. positive values correspond to the expansion of a subject's thalamus relative to the template at a particular location, while negative values denote the compression of subject's thalamus relative to the template.

Both T1-weighted image and DTI were acquired at the National Neuroscience Institute, Singapore, on a 3-Tesla whole body scanner (Philips Achieva, Philips Medical System, Eindhoven, The Netherlands) with a SENSE head coil. Stability of a high signal to noise ratio was assured through a regular automated quality control procedure. High-resolution T1-weighted Magnetization Prepared Rapid Gradient Recalled Echo (MPRAGE) were acquired (TR = 7.2 ms; TE = 3.3 ms; flip angle = 8°). Each volume consisted of 180 axial slices of 0.9 mm thickness with no gap (field of view, 230 mm × 230 mm; acquisition matrix, 256 × 256). A single-shot echo-planar sequence (TR = 3725 ms; TE = 56 ms; flip angle = 90°, b = 800 s/mm2) was used to acquire DTI data with 15 different non-parallel directions and the baseline image without diffusion weighting (b = 0). The imaging matrix was 112 × 109 with a field of view of 230 mm × 230 mm, which was zero-filled to 256 × 256. Axial slices of 3.0 mm thickness were acquired parallel to the anterior–posterior commissure line. A total of 42 slices covered the entire brain and brainstem without gaps. The T1-weighted and DTI data were sequentially acquired in a single scan time without position change.

The diffusion-weighted (DW) images were corrected for motion and eddy current distortions using affine transformation to the image without diffusion weighting (b = 0). For each subject, these DW images were then registered to the T1-weighted image via rigid transformation between the image without diffusion weighting and the T1-weighted images. All DTI measurements listed below are thus in the space of the T1-weighted images. Six elements of the diffusion tensor were determined by multivariate least-squares fitting. The tensor was diagonalized to obtain three eigenvalues and eigenvectors. Anisotropy was measured by fractional anisotropy (FA). Mean diffusivity (MD) was computed by averaging the three eigenvalues. Mean values of FA and MD in the thalamus were computed based on the thalamus mask delineated in the previous section.

Thalamus delineation and shape analysis

Statistical testing on shapes

The thalamic anatomy in this study includes all thalamic nuclei except for lateral and medial geniculate bodies. The left and right thalami are separated medially by the third ventricle, cerebrospinal fluid (CSF), or the cerebral exterior midline. They are bound laterally by the internal capsule. The thalami anteriorly extend to the interventricular foramen (foramen of Monroe), and posteriorly overlaps the midbrain and is bordered by CSF. The inferior border is the hypothalamic fissure, or the hippocampus in the most posterior extent. The thalami superiorly extend to the transverse cerebral fissure (TCF), lateral ventricle, white matter, or in the anterior portion, the caudate. We automatically delineated the thalamus from the intensity-inhomogeneity corrected T1-weighted MR images (Sled et al., 1998) using a Markov random field model that incorporates the thalamic anatomical definition as prior. The Markov random field model was first applied to label each voxel in the image volume as gray matter, or white matter, or CSF, or subcortical structures (Fischl et al., 2002). Due to no constraints of structural shapes, this process introduced unsmoothness and topological errors (e.g. holes) on the thalamic boundary. This may increase shape variation and thus reduce statistical power to detect group difference in shape. To avoid this issue, we generated the thalamus shapes of each individual subject with properties of smoothness and topology by injecting a template shape into them using the LDDMM-image mapping algorithm (Qiu and Miller, 2008). The thalamic template shape was created from 41 manually labeled thalami via a large deformation diffeomorphic template generation algorithm (Qiu et al., submitted for publication). Each thalamic volume was approximated by the transformed template through the LDDMM diffeomorphic map. The mathematical derivation of this template injection procedure and its evaluation on a variety of subcortical structures have been detailed elsewhere (Qiu and Miller, 2008). This delineation approach has been successfully used to investigate the subcortical shapes in Alzheimer's disease (Qiu et al., 2009b), hippocampal shapes in geriatric depression (Qiu et al., 2009c), and the basal ganglia shapes in ADHD (Qiu et al., 2009a). The surface representation of the thalamic shape was created by composing the diffeomorphic map on the template surface. We applied the LDDMM-surface mapping algorithm (Vaillant and Glaunes, 2005; Vaillant et al., 2007) to map the template surface to each thalamic surface. The Jacobian determinant of the deformation in the logarithmic scale was computed in the local coordinates of the template for statistical shape comparison across clinical populations.

To reduce the dimensionality of the deformation map, we represented it as a linear combination of the Laplace–Beltrami (LB) basis functions defined on the thalamic template surface (Qiu et al., 2006, 2008). Unlike basis functions via principal component analysis (PCA), the LB basis functions are deterministic and only dependent on the geometry of the template surface (Qiu et al., 2006, 2008). The finite number of LB-coefficients associated with the LB basis functions was used to represent the deformation map on which statistical tests were then performed. The number of LB-coefficients is determined based on the least square fitting error of 5%. To compare the shape between any two groups, we modeled each LB-coefficient using linear regression with diagnosis (CON and FES) as main factor covarying with the total intracranial volume and years of education. A subset of the LB-coefficients with p-values less than 0.05 was selected to represent shape difference between the two groups.

DTI processing

Point-wise Pearson's correlation analysis At each point on the template surface, the Pearson's correlation analysis was assessed between the thalamic shape and cognitive measures — executive and spatial working memory. The correlation results were corrected for multiple comparisons using permutation tests to determine the overall significance of the correlation maps. In each permutation trial, cognitive measures were randomly assigned to each subject and the number of points with significant correlation (p b 0.05) was recorded. After 10,000 permutation trials, the overall significance was computed as the fraction of the time that the suprathreshold area was greater in the randomized maps than the real effect (Nichols and Holmes 2002). Results Sample demographics and clinical/cognitive features Demographic variables and clinical measures (Table 1) were compared using two sample Student's t-test for continuous variables and chi-square test for categorical variables. Compared to healthy controls (CON), patients with FES had fewer years of education (p b 0.0005), lower scores on non-verbal intelligence (p = 0.0020), and poorer performance on tasks of executive functioning in terms of more perseverative errors (p = 0.0237), and spatial working memory

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Fig. 1. Panels (a, b) show the distributions of thalamic fractional anisotropy (FA) within the groups of healthy comparison controls (CON) and patients with first-episode schizophrenia (FES). Panels (c, d) illustrate the distributions of thalamic mean diffusivity (MD) within the groups of CON and FES. Horizontal bars denote the locations of the mean values in each group. The mean (SD) values of the FA in CON and FES respectively are 0.31 (0.02), 0.30 (0.02) for the left thalamus and 0.32 (0.03), 0.31 (0.02) for the right thalamus. The mean (SD) values of the MD in CON and FES respectively are 0.89 (0.07) × 10− 3 mm2/s, 0.90 (0.06) × 10− 3 mm2/s for the left thalamus and 0.87 (0.06) × 10− 3 mm2/s, 0.89 (0.07) × 10− 3 mm2/s for the right thalamus.

(p = 0.0368). There was no significant group difference in age (p = 0.1064), sex (p = 0.5391), handness (p = 0.2953), total intracranial volume (p = 0.1453), scores on tasks assessing for attention (p = 0.6960), and visuo-constructional skills (p = 0.3980). Average duration of illness in the FES group was 2.8 years.

p = 0.2639 for the left thalamus and F1,78 = 1.80, p = 0.1837 for the right thalamus; MD: F1,78 = -0.69, p = 0.4929 for the left thalamus and F1,78 = 2.71, p = 0.1038 for the right thalamus).

Thalamic FA and MD

Fig. 2 illustrates the distribution of thalamic volumes within the groups of CON and FES. Linear regression (after covarying with total intracranial volume and years of education) revealed a significant group difference in the left thalamic volume (F1,78 = 4.17, p = 0.0445). The right thalamic volume approached significant group difference (F1,78 = 3.68, p = 0.0588).

Fig. 1 illustrates the distributions of thalamic FA and MD within the groups of CON and FES. After controlling the years of education, linear regression revealed no significant difference in thalamic FA and MD between the two groups of controls and subjects (FA: F1,78 = 1.27,

Thalamic volumes

Fig. 2. Panels (a, b) show the volume distributions of the left and right thalamic structures within the groups of healthy comparison controls (CON) and patients with first-episode schizophrenia (FES). Horizontal bars denote the locations of the mean values in each group. The mean (SD) values of the left thalamic volumes in the groups of CON and FES are respectively 6470.4 mm3 (681.2), 6231.9 mm3 (627.6); the mean values of the right thalamic volumes in the groups of CON and FES are respectively 6191.4 mm3 (704.7), 5980.6 mm3 (595.5).

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Fig. 3. Thalamic shape abnormalities in the group of patients with first-episode schizophrenia (FES). Warm color denotes the regions with compression deformation and cool color denotes the regions with expansion deformation in FES when compared with healthy comparison controls. The anterior, posterior, and superior views are respectively illustrated from the left to right panels. Key: L — left; R — right; S — superior; I — inferior; A — anterior; P — posterior.

Thalamic shapes We statistically investigated shape differences between CON and FES via the surface deformation maps. The left and right deformation maps were respectively characterized by the first 24 LB basis functions at the least square error of 5%. The linear regression was applied to each LB-coefficient and revealed the 13th LB basis function with a significant group difference (p = 0.0132) in the left thalamic surface deformation between CON and FES after controlling for the total intracranial volume and years of education. After controlling for the total intracranial volume and years of education, linear regression revealed the 12th LB basis function (p = 0.0204) with a significant group difference in the right thalamic shape. For the visualization purpose, we constructed the shape difference patterns between these two groups based on these LB basis functions, which is illustrated in the anterior, posterior, and superior views of the thalamus in Fig. 3. Color encodes the ratio of the local thalamic volume in CON to one in FES in the logarithmic scale. Fig. 3 suggests that the shape alteration of the thalamus in FES is not uniformly distributed on the surface. Regions with pronounced volume compression in FES included the lateral and dorsal aspects as well as the middle body of the left and right thalamus. Regions with mild volume compression in FES

included the anterior–medial and posterior–lateral aspects of the left thalamus, as well as the anterior–ventral aspect and medial body of the right thalamus. Correlation of structural measures with cognition Pearson's correlation analysis was used to assess the relationship between the structural measures and cognitive domain scores (executive functioning and spatial working memory) in the CON and FES subjects. The largest correlation was found between the left thalamic FA and spatial working memory score in FES (Pearson's r = 0.43, p = 0.0167). The two cognitive domain scores did not correlate with other structural measures, including total intracranial volume, thalamic volumes, and thalamic MD. Point-wise Pearson's correlation analysis revealed a regionalspecific correlation between the executive functioning and thalamic shape in the entire sample, healthy comparison controls, but not in patients with FES (Fig. 4). In both the entire sample and the CON group, the thalamic shape in the anterior lateral and medial aspects showed a significant negative correlation with perseverative errors during executive functioning. This negative correlation indicates that the shape compression is the significant predictor of poor performance on

Fig. 4. Correlation maps of executive functioning and thalamic shape in the entire sample and in the CON group only. The top and bottom rows respectively illustrate the correlation maps in the entire sample and in the CON group in the anterior, posterior, and superior views of the thalamus. The regions with no significant correlation are in white, while the region with significant correlation (uncorrected p-value less than 0.05) is colored by the Pearson correlation coefficient.

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Fig. 5. Correlation maps of spatial working memory and thalamic shape in the entire sample and group of healthy comparison controls (CON). The top and bottom rows respectively illustrate the correlation maps in the entire sample and in the CON group in the anterior, posterior, and superior views of the thalamus. The regions with no significant correlation are in white, while the region with significant correlation (uncorrected p-value less than 0.05) is colored by the Pearson correlation coefficient.

executive functioning. Permutation tests confirmed the overall significance of these correlation maps in Fig. 4 less than p = 0.0001. No significant correlations of the thalamic shapes with the perseverative errors during executive functioning were found in the FES group, but Fig. 6a suggests the trends were in the same direction as for the healthy comparison controls. Point-wise Pearson's correlation analysis revealed regional-specific correlation between the spatial working memory and thalamic shape in the entire sample, healthy comparison controls, but not in patients with FES (Fig. 5). In the entire sample, the shape in the anterior aspect of the left thalamus and small area of the medial dorsal and ventral aspects of the right thalamus showed a significant positive correlation with spatial working memory (top row of Fig. 5). In contrast, the healthy comparison controls showed more pronounced positive correlation and the correlation pattern in the right dorsal thalamus slightly moved towards to the lateral (bottom row of Fig. 5). This positive correlation indicates that the shape compression is the significant predictor of poor performance on spatial working memory. Permutation tests confirmed the overall significance of these correlation maps in Fig. 5 less than p = 0.0001. No significant correlations of the thalamic shapes with the spatial working memory were found in

the FES group, but Fig. 6b suggests the trends were in the same direction as for the healthy comparison controls. Discussion In this study, we evaluated the volume, shape, diffusivity, and anisotropy of the thalamus and their correlations with executive function and spatial working memory in patients with FES and healthy comparison controls. This is the first study which combined analyses of thalamic volume, shape and white matter integrity in appreciating thalamic abnormalities within patients with FES. Patients with FES did not differ from healthy comparison controls in diffusivity and anisotropy measured in DTI but did differ markedly from them in the thalamic volume and shape. In the correlation study of thalamic structural measures with cognition, executive functioning and spatial working memory were selected due to poorer performance in FES and their relationship with the dorsolateral prefrontal cortex in schizophrenia. Left thalamic FA was correlated with spatial working memory deficits in FES. Regionally-specific thalamic shapes highly correlate with the two cognitive scores in the entire sample and the CON group (but not in the FES group) even though no correlation was found

Fig. 6. Panel (a) illustrates the average correlation coefficient between the executive functioning and thalamic shape in the region with significant correlation as given on the top row of Fig. 4. Panel (b) shows the average correlation coefficient between the spatial working memory and thalamic shape in the region with significant correlation as given on the bottom row of Fig. 5. Black bar denotes the group of controls (CON); White bar represents the group of patients with schizophrenia (FES).

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between the thalamic volumes and the two cognitive scores in any group. This highlights the sensitivity of LDDMM shape analysis to detect correlations with cognition that were not apparent with thalamic volumetric analysis. Compared with healthy comparison controls, our finding of no thalamic MD change in FES is in contrast with that in the previous study with schizophrenic patients with a longer (average 13 years) duration of illness (Rose et al., 2006). Moreover, our study also provided FA analysis to quantify thalamic white matter pathophysiology in schizophrenia. Our findings differed from those reported by (Rose et al., 2006), suggesting that altered white matter integrity assessed through DTI may not be apparent in FES but which may be observed as the disease progresses or that medication may confound diffusion properties (Kargieman et al., 2007). Although researchers tend to link increased MD with an increase in the extracellular space due to altered cytoarchitecture (Kantarci et al., 2001) and decreased FA with the disruption of the white matter fiber tracts (e.g. demyelination), the precise neural correlations of altered FA/MD measures are uncertain. Thus, measures associated with specific microstructural alterations need to be developed, involving new image acquisition and other measures from DTI such as radial, axial diffusivities (Ashtari et al., 2007; Seal et al., 2008), geometric indices (Westin et al., 2002). Furthermore, it will be helpful to link the DTI measures with microstructural alterations of the thalamus in FES (e.g. variations in oligodendrocyte number) by combining neuroimaging and post-mortem techniques. The finding of smaller left thalamic volume in our subjects with FES was consistent with some but not all earlier studies (Cahn et al., 2002; Coscia et al., 2008; Gur et al., 1998; Lang et al., 2006; Preuss et al., 2005). It is conceivable that this could be due to a variety of factors including population differences (e.g. age, duration of illness), medication (Dazzan et al., 2005; Khorram et al., 2006), and thalamic anatomical definitions. Reductions in thalamic volumes in previous studies of high risk individuals (Lawrie et al., 2001; Seidman et al., 1999; Staal et al., 1998) may also suggest that thalamic volume changes are dynamic and can progress over the course of illness and may be associated with genetic liability towards the onset of schizophrenia. Our deformation map in Fig. 3 gives the detailed locations where the volume loss occurs, which shed light on regions of the thalamic volume loss in FES. Our study adds new information to the results of previous volumetric studies in the sense that we were able to show specific patterns of disturbances in the thalamic shape. The shape pattern of volume compression in FES suggests the involvement of nuclei in the anterior (and posterior) lateral and dorsal aspect as well as middle body of the thalamus, which is consistent with thalamic shape findings in previous studies (Csernansky et al., 2004; Harms et al., 2007). The affected anterior region of the thalamus contains the anterior, medio-dorsal, ventral lateral, and pulvinar nuclei — regions in which earlier studies have found smaller volumes and fewer neurons in schizophrenia subjects (Byne et al., 2002; Popken et al., 2000). The specific-regional volume loss of these various thalamic nuclei in schizophrenia is of particular interest because of their connections with the association cortices (Sim et al., 2006). The anterior (Barbas et al., 1991; Goldman-Rakic and Porrino, 1985; Yeterian and Pandya, 1988) and medio-dorsal thalamic nuclei (Barbas et al., 1991; Goldman-Rakic and Porrino, 1985) have reciprocal connections with the hippocampus within the limbic system and prefrontal cortex respectively. The pulvinar nuclei are important in visual and possibly auditory attention, and they also have prominent interconnections with the temporal lobe, a second area of morphometric and functional changes in schizophrenia. Several MR-based morphometric studies reported the volume loss in the pulvinar nuclei but questioned bilaterality and involvement of medial and lateral divisions (Byne et al., 2001; Byne et al., 2007; Gilbert et al., 2001; Grieve et al., 2000; Highley et al., 2003; Kemether et al., 2003). Our

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findings emphasized the bilateral pulvinar involvement and more pronounced in the medial aspect. Unlike measuring the volumes of the pulvinar nuclei (Byne et al., 2001,2007; Highley et al., 2003; Kemether et al., 2003), the shape deformation given in this study detailed the anatomical location of the volume loss. Additionally, the involvement of these thalamic nuclei in FES is consistent with recent findings in gray matter loss in the prefrontal cortex and limbic system (Buchanan et al., 1998; Csernansky et al., 1998; Qiu et al., 2007) and increased diffusivity in the prefrontal cortex (Rose et al., 2006). Although the association between medio-dorsal thalamic volume loss and cortical thinning in the prefrontal cortex has been questioned (Dorph-Petersen et al., 2004), it is reasonable to hypothesize that anomalies of the medio-dorsal thalamic projection to the prefrontal cortex might contribute to the cortical thinning. In our study, patients with FES showed poorer cognitive performance related to spatial working memory and executive functioning. These deficits were observed in the context of loss of their normal relationship with the thalamic shapes, that is, regionallyspecific thalamic shape compression is associated with poor performance in executive functioning and spatial working memory. The thalamus plays an important role in the integration of thought processes (Jones 1997) and abnormal prefrontal–thalamic connectivity has been postulated to be involved in cognitive impairment in patients with schizophrenia (Andreasen 1997; Andreasen 1999). Thus any pathology affecting the thalamus and specific nuclei may have impact on the functions served by these connections. Our study shows greater correlation of the anterior thalamus (connected with the hippocampus) with spatial working memory in the healthy controls but not in the patients with schizophrenia. The cognitive deficits in spatial working memory may thus be related to pathology in thalamic nuclei and disruption of its connections with associated structures in the medial temporal lobe (Insausti et al., 1987). In a similar way, disruptions in connections between the thalami and frontal lobes may account for the greater perseverative errors shown by patients with FES. Executive functioning and spatial working memory deficits found in our FES patients are consistent with those of a recent study by Coscia et al. (2008) which also showed reduced thalamic volumes in FES patients. Furthermore, a functional study with schizophrenia patients showed that poorer N-back working memory performance was associated with reduced thalamic fMRI activation in sub-regions including the anterior nuclei and centromedian nucleus (Andrews et al., 2006). Thus cognitive deficits observed in patients with schizophrenia appear to be related to both shape changes and functional activity in the thalamus. Because of its many interconnections with other brain regions, the thalamus could therefore be an important structure involved in the cognitive deficits associated with schizophrenia. There are several strengths in this study. First, this is the first to combine analyses of thalamic volume, shape and white matter integrity in patients with FES. Second, the use of meticulous region of interest methods allows automatic delineation of the thalami within each subject. The comparison of MD and FA were examined in the subject native space and thus our findings are not affected by misregistration. Third, the LDDMM mapping was used to assess thalamic shapes and their correlation with cognitive scores. Our shape findings are consistent with a previous study in schizophrenia subjects with much longer duration of illness (Csernansky et al., 2004) and are much pronounced than a recent study in FES (Coscia et al., 2008). One potential advantage of our study could be attributed to the sensitivity of the LDDMM in detecting and characterizing shape variations across subjects (Kirwan et al., 2007; Miller et al., 2005; Vaillant et al., 2007). At the same time, we acknowledge several limitations. The study was performed on a small group of subjects and the findings would benefit from replication in larger samples. Due to the sample size and sex balance in the groups of CON and FES, we did not consider the effects of sex and its interaction with schizophrenia,

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which can be investigated when larger samples are available. In addition, the FES patients included in this study were under antipsychotic medications. A future study on medication effects on thalamic diffusion properties and shape is needed to be conducted. Furthermore, our surface-based shape analysis examined the overall shape of the thalamus, which cannot give the shape deformation inside the thalamus. Shape analysis on each individual thalamic nucleus will provide more detailed thalamic shape variations in FES and their association with cognition. Acknowledgments This work has not been presented at any meeting or journal. We would like to thank all the patients, their families and the staff for their support for this project. 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