Statistical analysis of hippocampal asymmetry in schizophrenia

Validity of large-deformation high dimensional brain mapping of the basal ganglia in adults with Tourette syndrome

The basal ganglia and thalamus may play a critical role for behavioral inhibition mediated by prefrontal, parietal, temporal, and cingulate cortices. The cortico-basal ganglia-thalamo-cortical loop with projections from frontal cortex to striatum, then to globus pallidus or to substantia nigra pars reticulata, to thalamus and back to cortex, provides the anatomical substrate for this function. In-vivo neuroimaging studies have reported reduced volumes in the thalamus and basal ganglia in individuals with Tourette Syndrome (TS) when compared with healthy controls. However, patterns of neuroanatomical shape that may be associated with these volume differences have not yet been consistently characterized. Tools are being developed at a rapid pace within the emerging field of computational anatomy that allow for the precise analysis of neuroanatomical shape derived from magnetic resonance (MR) images, and give us the ability to characterize subtle abnormalities of brain structures that were previously undetectable. In this study, T1-weighted MR scans were collected in 15 neuroleptic-naïve adults with TS or chronic motor tics and 15 healthy, tic-free adult subjects matched for age, gender and handedness. We demonstrated the validity and reliability of large-deformation high dimensional brain mapping (HDBM-LD) as a tool to characterize the basal ganglia (caudate, globus pallidus and putamen) and thalamus. We found no significant volume or shape differences in any of the structures in this small sample of subjects.

Hippocampal abnormalities and memory deficits: new evidence of a strong pathophysiological link in schizophrenia

The central goals of this manuscript are (1) to better characterize what appears to be the most parsimonious account of schizophrenic long-term memory impairment in the neuropsychological literature: a contextual binding deficit rooted in the medial temporal lobes; (2) to link this deficit to concrete abnormalities at the level of the hippocampus; and (3) to suggest that this deficit could lead to the functional impairment experienced by schizophrenia patients in their daily lives. As far as long-term memory is concerned in schizophrenia, there seems to be a general agreement to conclude that explicit mechanisms are disturbed compared to relatively spared implicit mechanisms. More precisely, both subsystems of explicit memory (i.e., episodic and semantic) appear to be dysfunctional in this patient population. Errors during the encoding processes could be responsible for this dysfunction even if retrieval per se is not totally spared. Recently, a number of studies have suggested that impairments in conscious recollection and contextual binding are closely linked to episodic memory deficit. Since the hippocampal formation is considered to be the central element in the neural support for contextual binding and episodic memory, we have conducted an extensive review of the literature concerning the hippocampal formation in schizophrenia. Emerging evidence from varying disciplines confirm the coherence of the different anomalies reported concurrently at the neuroanatomical, neurodevelopmental, biochemical, and genetic levels. It seems highly probable that the synaptic disorganization in the hippocampus concerns the regions crucial for encoding and contextual binding memory processes. The consequences of these deficits could result in schizophrenia patients experiencing major difficulties when facing usual events which have not been encoded with their proper context.

COMPARE: classification of morphological patterns using adaptive regional elements

This paper presents a method for classification of structural brain magnetic resonance (MR) images, by using a combination of deformation-based morphometry and machine learning methods. A morphological representation of the anatomy of interest is first obtained using a high-dimensional mass-preserving template warping method, which results in tissue density maps that constitute local tissue volumetric measurements. Regions that display strong correlations between tissue volume and classification (clinical) variables are extracted using a watershed segmentation algorithm, taking into account the regional smoothness of the correlation map which is estimated by a cross-validation strategy to achieve robustness to outliers. A volume increment algorithm is then applied to these regions to extract regional volumetric features, from which a feature selection technique using support vector machine (SVM)-based criteria is used to select the most discriminative features, according to their effect on the upper bound of the leave-one-out generalization error. Finally, SVM-based classification is applied using the best set of features, and it is tested using a leave-one-out cross-validation strategy. The results on MR brain images of healthy controls and schizophrenia patients demonstrate not only high classification accuracy (91.8% for female subjects and 90.8% for male subjects), but also good stability with respect to the number of features selected and the size of SVM kernel used.

Structural analysis of the basal ganglia in schizophrenia

Increases in the total volume of basal ganglia structures have been reported in schizophrenia. However, patterns of basal ganglia shape change, which can reveal localized changes in substructure volumes, have not been investigated. In this study, the total volume and shape of several basal ganglia structures were compared in subjects with and without schizophrenia. T(1)-weighted magnetic resonance scans were collected in 54 schizophrenia and 70 comparison subjects. High-dimensional (large-deformation) brain mapping was used to assess the shape and volume of several basal ganglia structures. The relationships of shape and volume measures with psychopathology, cognition and motor function were also assessed. Left and right volumes of the caudate and putamen, as well as the right globus pallidus volume, were significantly increased in subjects with schizophrenia as compared to comparison subjects after total brain volume was included as a covariate. Significant differences in shape accompanied these volume changes in the caudate, putamen and globus pallidus, after their total volumes were included as covariates. There were few significant correlations between volume or shape measures and either cognitive function or clinical symptoms, other than a positive correlation between an attention/vigilance cognitive dimension and the volume of the caudate and putamen, and a negative correlation between nucleus accumbens volume and delusions. In conclusion, basal ganglia volumes relative to total brain volume were larger in schizophrenia subjects than healthy comparison subjects. Specific patterns of shape change accompanied these volume differences.

Statistical analyses of brain surfaces using Gaussian random fields on 2-D manifolds

Interest in the morphometric analysis of the brain and its subregions has recently intensified because growth or degeneration of the brain in health or illness affects not only the volume but also the shape of cortical and subcortical brain regions, and new image processing techniques permit detection of small and highly localized perturbations in shape or localized volume, with remarkable precision. An appropriate statistical representation of the shape of a brain region is essential, however, for detecting, localizing, and interpreting variability in its surface contour and for identifying differences in volume of the underlying tissue that produce that variability across individuals and groups of individuals. Our statistical representation of the shape of a brain region is defined by a reference region for that region and by a Gaussian random field (GRF) that is defined across the entire surface of the region. We first select a reference region from a set of segmented brain images of healthy individuals. The GRF is then estimated as the signed Euclidean distances between points on the surface of the reference region and the corresponding points on the corresponding region in images of brains that have been coregistered to the reference. Correspondences between points on these surfaces are defined through deformations of each region of a brain into the coordinate space of the reference region using the principles of fluid dynamics. The warped, coregistered region of each subject is then unwarped into its native space, simultaneously bringing into that space the map of corresponding points that was established when the surfaces of the subject and reference regions were tightly coregistered. The proposed statistical description of the shape of surface contours makes no assumptions, other than smoothness, about the shape of the region or its GRF. The description also allows for the detection and localization of statistically significant differences in the shapes of the surfaces across groups of subjects at both a fine and coarse scale. We demonstrate the effectiveness of these statistical methods by applying them to study differences in shape of the amygdala and hippocampus in a large sample of normal subjects and in subjects with attention deficit/hyperactivity disorder (ADHD).

Advances in magnetic resonance imaging methods for the evaluation of bipolar disorder

This article reviews the current state of magnetic resonance imaging techniques as applied to bipolar disorder. Addressed are conventional methods of structural neuroimaging and recently developed techniques. This latter group comprises volumetric analysis, voxel-based morphometry, the assessment of T2 white matter hyperintensities, shape analysis, cortical surface-based analysis, and diffusion tensor imaging. Structural analysis methods used in magnetic resonance imaging develop exponentially, and now present opportunities to identify disease-specific neuroanatomic alterations. Greater acuity and complementarity in measuring these alterations has led to the generation of further hypotheses regarding the pathophysiology of bipolar disorder. Included in the summary of findings is consideration of a resulting neuroanatomic model. Integrative issues and future directions in this relatively young field, including multi-modal approaches enabling us to produce more comprehensive results, are discussed.

MR-based neurological disease classification methodology: Application to lateralization of seizure focus in temporal lobe epilepsy

Classification approaches for neurological diseases tend to concentrate on specific structures such as the hippocampus (HC). The hypothesis for the novel methodology presented in this work is that pathologies will impact large tissue areas with detectable variations of T1-weighted MR signal intensity and registration metrics. The technique is applied to lateralization of seizure focus in 127 patients with intractable temporal lobe epilepsy (TLE), in which the site of seizure onset was determined by comprehensive evaluation (69 with left MTL seizure focus (SF) (group "L") and 58 with right SF (group "R")). The method analyses large, non-specific Volumes of Interest (VOI) centered on the left and right medial temporal lobes (MTL) (55 x 82 x 80 voxels) in pre-processed scans aligned in stereotaxic space. Extracted VOIs are linearly and nonlinearly registered to a reference target image. Principal Components Analyses of (i) the normalized intensity and (ii) the trace, a measure of local volume change, are used to generate a multidimensional reference space from a set of 152 neurologically healthy subjects. VOIs from TLE patients, processed in a similar fashion, are projected in this space, and leave-one-out, forward stepwise linear discriminant analysis of the eigencoordinate distributions is used for classification. Following manual MRI volumetric analysis, 80 patients had HC atrophy (group "HA") ipsilateral to the SF (42 with left SF or "LHA", and 38 with right or "RHA"), and the remaining 47 had normal HC volumes (group "HNV") (27 with left SF or "LNV", and 20 with right SF or "RNV"). The automated method was 100% accurate at separating "HA" vs. "HNV", "LHA" vs. "RHA", and "LNV" vs "RNV". It was also 96% accurate at separating "L" vs. "R". Our results indicate that MR data projected in multidimensional feature domains can lateralize SF in epilepsy patients with a high accuracy, irrespective of HC volumes. This single-scan, practical and objective method holds promise for the pre-surgical evaluation of TLE patients.

Symmetric atlasing and model based segmentation: an application to the hippocampus in older adults

In model-based segmentation, automated region identification is achieved via registration of novel data to a pre-determined model. The desired structure is typically generated via manual tracing within this model. When model-based segmentation is applied to human cortical data, problems arise if left-right comparisons are desired. The asymmetry of the human cortex requires that both left and right models of a structure be composed in order to effectively segment the desired structures. Paradoxically, defining a model in both hemi-spheres carries a likelihood of introducing bias to one of the structures. This paper describes a novel technique for creating a symmetric average model in which both hemispheres are equally represented and thus left-right comparison is possible. This work is an extension of that proposed by Guimond et al. Hippocampal segmentation is used as a test-case in a cohort of 118 normal eld-erly subjects and results are compared with expert manual tracing.

Behavioural changes and psychological symptoms in dementia disorders

The traditional view of dementia is that the features most important to accurate diagnosis and management are cognitive decline and functional disability. Behavioural and psychological symptoms have generally been thought to be of secondary importance, but new evidence suggests that these are important determinants of patients' distress, carer burden, and outcome in dementia; they can also be valuable diagnostic pointers to the underlying pathological cause and disease diagnosis. Better methods to detect and measure the severity of behavioural and psychological symptoms are needed and these could be used in well-designed intervention trials. Although pharmacological management is a commonly used option, it is often limited in its effects and can be associated with a substantial risk of side-effects. Progress in understanding the pathophysiological mechanisms underpinning behavioural and psychological symptoms in dementia will assist in developing more effective treatment approaches.

Asymmetries in the spatial distributions of enhancing lesions and black holes in relapsing-remitting MS

Magnetic resonance imaging (MRI) is the most important paraclinical test in the diagnosis of multiple sclerosis (MS) and for delineating its natural history. We investigate MRIs from a longitudinal study of 24 relapsing-remitting MS patients who had monthly MRI examinations for one year, and were not receiving active MS therapy during this period. We hypothesized that lesions occur randomly throughout the brain, and that patients are homogeneous with regard to spatial patterns of lesion presentation. We recorded the numbers and locations of enhancing lesions and hypointense lesions (black holes) in all scans, and found asymmetrical patterns of lesions about the mid-transaxial, mid-coronal, and mid-sagittal planes. Furthermore, in distinct subsets of patients, enhancing lesions and black holes tend to occur in the same locations. Clustering in lesion locations may be of functional significance, with consequent therapeutic implications.

Does Alzheimer's disease affect hippocampal asymmetry? Evidence from a cross-sectional and longitudinal volumetric MRI study

OBJECTIVE

To determine whether Alzheimer's disease (AD) is associated with preferential atrophy of either the left or right hippocampus.

METHODS

We examined right-left asymmetry in hippocampal volume and atrophy rates in 32 subjects with probable AD and 50 age-matched controls. Hippocampi were measured on two serial volumetric MRI scans using a technique that minimizes laterality bias.

RESULTS

We found a non-significant trend for right > left (R > L) asymmetry in controls at both time points (R > L: 1.7%; CI: -0.3-3.7%; p = 0.1). AD subjects showed a similar non-significant trend for R > L asymmetry at baseline (R > L: 1.8%; CI: -1.9-5.5%; p = 0.32), but not at repeat (p = 0.739). Change in R/L ratio between visits in AD patients was significant (p = 0.02). The AD group had significantly higher variance in these ratios than the controls at baseline (p = 0.02), but not repeat (p = 0.06). AD patients had higher atrophy rates than controls (p < 0.001). Mean (CI) annualized atrophy rates for left and right hippocampi were 1.2% (0.5-1.8%) and 1.1% (0.5-1.8%) for the controls, and 4.6% (3.3-6.0%) and 6.3% (4.9-7.8%) for AD subjects. There was no significant asymmetry in atrophy rates in controls (p = 0.9), but borderline significantly higher atrophy rates in the right hippocampus of the AD group (p = 0.05) compared to the left. Presence of an APOEepsilon4 allele had no significant effect on the size, asymmetry or atrophy rates in AD (p > 0.20).

CONCLUSIONS

We report minor R > L asymmetry in hippocampal volumes in controls and present some evidence to suggest that there is a change in the natural R > L asymmetry during the progression of AD.

Asymmetry analysis of deformable hippocampal model using the principal component in schizophrenia

The hippocampus is thought to play an important role in learning and memory processing, and impairments in memory, attention, and decision making are found commonly in schizophrenia. Although many studies have reported decreases in hippocampal volume in the left hemisphere in schizophrenia, regionally specific hippocampal volume loss has not been revealed consistently using volume analysis. Recently, many studies have analyzed shape asymmetry using 3-D models; however, inconsistent results have been reported, mainly due to methodologic differences. We therefore used an active, flexible, deformable shape model for surface parameterization, and compared shape asymmetry based on principal component analysis (PCA) in the hippocampi of schizophrenic patients with those of the normal controls. Although the overall pattern of the statistical results did not change according to the number of principal components, the reconstructed results based on six major components were much more distinguishable. Although the left hemispheric hippocampal volume was larger than the right hemispheric was in this study, the difference was not significant. In shape asymmetry analysis, the right hemisphere hippocampus was bilaterally larger than the left hemisphere hippocampus was in the head of the superior CA1 and smaller in the tail and head of the inferior CA1. The asymmetry in the schizophrenia group was statistically smaller than that in the control group through reduction of the left hemisphere hippocampus volume.

ROC-based assessments of 3D cortical surface-matching algorithms

Algorithms for the semi-automated analysis of brain surfaces have recently received considerable attention, and yet, they rarely receive a rigorous assessment of their performance. We present a method for the quantitative assessment of performance across differing surface analysis algorithms and across various modifications of a single algorithm. The sensitivity and specificity of an algorithm for detecting known deformations added synthetically to the brains being studied are assessed using curves for Receiver Operating Characteristics (ROC). We also present a method for the isolation of sources of variance in MRI data sets that can contribute to degradation in performance of surface-matching algorithms. Isolation of these sources of variance allows determination of whether degradation in performance of surface-matching algorithms derives primarily from errors in registration of brains to a common coordinate space, from errors in placement of the known deformation, or from interindividual or between-group variability in morphology of the cortical surface. We apply these methods to the study of surface-matching algorithms that are based on fluid flow (FF) deformation, geodesic (GD) interpolation, or nearest neighbor (NN) proximity. We show that the performances of surface-matching algorithms depend on the presence of interindividual and between-group variability in the surfaces surrounding the cortical deformation. We also show that, in general, the FF algorithm performs as well as or better than the GD and NN algorithms. The large variance in identifying point correspondences across brain surfaces using the GD and the NN algorithms suggests strongly that these point correspondences are less valid than those determined by the FF algorithm. The GD and NN algorithms, moreover, are both vulnerable to detecting false-positive activations at points of high curvature, particularly along large fissures, cisterns, and cortical sulci.

MR-based in vivo hippocampal volumetrics: 1. Review of methodologies currently employed

The advance of neuroimaging techniques has resulted in a burgeoning of studies reporting abnormalities in brain structure and function in a number of neuropsychiatric disorders. Measurement of hippocampal volume has developed as a useful tool in the study of neuropsychiatric disorders. We reviewed the literature and selected all English-language, human subject, data-driven papers on hippocampal volumetry, yielding a database of 423 records. From this database, the methodology of all original manual tracing protocols were studied. These protocols differed in a number of important factors for accurate hippocampal volume determination including magnetic field strength, the number of slices assessed and the thickness of slices, hippocampal orientation correction, volumetric correction, software used, inter-rater reliability, and anatomical boundaries of the hippocampus. The findings are discussed in relation to optimizing determination of hippocampal volume.

MR-based in vivo hippocampal volumetrics: 2. Findings in neuropsychiatric disorders

Magnetic resonance imaging (MRI) has opened a new window to the brain. Measuring hippocampal volume with MRI has provided important information about several neuropsychiatric disorders. We reviewed the literature and selected all English-language, human subject, data-driven papers on hippocampal volumetry, yielding a database of 423 records. Smaller hippocampal volumes have been reported in epilepsy, Alzheimer's disease, dementia, mild cognitive impairment, the aged, traumatic brain injury, cardiac arrest, Parkinson's disease, Huntington's disease, Cushing's disease, herpes simplex encephalitis, Turner's syndrome, Down's syndrome, survivors of low birth weight, schizophrenia, major depression, posttraumatic stress disorder, chronic alcoholism, borderline personality disorder, obsessive-compulsive disorder, and antisocial personality disorder. Significantly larger hippocampal volumes have been correlated with autism and children with fragile X syndrome. Preservation of hippocampal volume has been reported in congenital hyperplasia, children with fetal alcohol syndrome, anorexia nervosa, attention-deficit and hyperactivity disorder, bipolar disorder, and panic disorder. Possible mechanisms of hippocampal volume loss in neuropsychiatric disorders are discussed.

Computational anatomy: shape, growth, and atrophy comparison via diffeomorphisms

Computational anatomy (CA) is the mathematical study of anatomy I in I = I(alpha) o G, an orbit under groups of diffeomorphisms (i.e., smooth invertible mappings) g in G of anatomical exemplars I(alpha) in I. The observable images are the output of medical imaging devices. There are three components that CA examines: (i) constructions of the anatomical submanifolds, (ii) comparison of the anatomical manifolds via estimation of the underlying diffeomorphisms g in G defining the shape or geometry of the anatomical manifolds, and (iii) generation of probability laws of anatomical variation P(.) on the images I for inference and disease testing within anatomical models. This paper reviews recent advances in these three areas applied to shape, growth, and atrophy.

Three-dimensional deformation-based hippocampal surface anatomy, projected on MRI images

The objectives of the present study were to illustrate three-dimensional hippocampal surface anatomy using deformation-based composite segmentations, superimposed on two-dimensional MRI (magnetic resonance images) in standard and oblique planes. The hippocampi from five normal volumetric MRI studies were segmented using a semiautomated, deformation-based technique. Segmentations were then processed to combine hippocampal surfaces, generating a composite (or average) deformation for each of the five left and five right hippocampi. Composite hippocampal surfaces were then projected on two-dimensional MRIs, with verification of projections using three-dimensional coordinate data. Composite hippocampal surfaces show anatomical details of hippocampal substructures, including the pes hippocampi, intralimbic gyrus, and uncinate gyrus. Projection on two-dimensional MRI helps to define hippocampal anatomy in relationship to surrounding structures. Composite images highlight specific features of normal hippocampal surface anatomy, and demonstrate the structural relationship of the hippocampus to surrounding structures on MRI.

Characterizing changes in MR images with color-coded Jacobians

Image registration is the process of establishing spatial correspondence between two images or between two image volumes. Registration can be achieved by rigid, elastic, or a combination of rigid and elastic transforms that attempt to bring the two images into coincidence. A rigid transform accounts for differences in positioning and an elastic transform describes deformations due to differences in tissue properties, temporal changes due to growth or atrophy, or differences between individuals. Deformation-based morphometry uses the resulting deformation fields from these transforms to evaluate differences between the images being registered. Three methods of registration were evaluated: rigid (affine) transformation, elastic optical flow transformation, and elastic spline transformation. All three methods produce vector deformation fields that map each point in one image to a point in the other image. A 12-color map of the transformation Jacobian was used to represent local volume changes. Using the three registration methods, color-mapped Jacobians were determined using a simulated three-dimensional block with known translation, rotation, expansion, contraction, and intensity modulations. Color-coded Jacobians were also generated for experimentally measured magnetic resonance image volumes of water-filled balloons and 7-year-old twin boys. Color-coded Jacobians overlaid on anatomical images provide a convenient method to identify regional tissue expansion and contraction.

Mapping hippocampal and ventricular change in Alzheimer disease

We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Sixty-two [corrected] high-resolution MRI scans were acquired from 12 AD patients (mean [corrected] age +/- SE at first scan: 68.7 +/- 1.7 [corrected] years) and 14 matched controls (age: 71.4 +/- 0.9 years) [corrected] each scanned twice (1.9 +/- 0.2 [corrected] years apart, when all subjects are pooled [corrected] 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

Sex-specific, postpuberty changes in mouse brain structures revealed by three-dimensional magnetic resonance microscopy

Sexual dimorphism of brain structures has been reported in some species. We report that sex-dependent developmental structure changes exist in the C57Bl/6(J) mouse, a common model for the genetic analysis of brain function. High resolution, three-dimensional (3D) magnetic resonance microscopy (MRM) images were obtained in intact brains of male and female adult and peripubertal mice. The lateral and third ventricles, hippocampus, amygdala, striatum, and total brain were reconstructed in 3D. As observed in humans, there was overall cerebral growth from peripuberty to adulthood in both sexes. After correcting for the increased brain size, the hippocampus and amygdala were disproportionately larger in adult compared to peripubertal mice. Several sexual dimorphisms were also observed. The lateral ventricles were larger, while the amygdala (the left side in particular) was smaller in females compared to males. Lateral and third ventricles were reduced over time in males only, exhibiting a sex-specific developmental profile. The striatal size was uniform among the groups studied. The surface area of the segmented structures was assayed. Possible shape distortions were detected for the lateral ventricles, hippocampus, and overall brain structure based on a lack of covariance between the surface area and volumetric measurements. Although many sexually dimorphic changes are reported perinatally, our results suggest that there are additional sex-specific transformations that occur around puberty and persist in adulthood.

Asymmetry of the hippocampus and amygdala in MRI volumetric measurements of normal adults

Multiple studies have explored the relationship between MRI-based volumetric measurements of the hippocampus and amygdala, the degree of volumetric asymmetry of these structures, and symptom manifestation. However, considerable variability exists with regard to the reported volumetric values of these structures. The present study employed meta-analytic procedures to provide a systematic analysis of the normal population parameters of hippocampal and amygdala volumetric asymmetry as well as the absolute intrahemispheric volumes of these structures in normal adults. A literature review of studies published between 1990 and 2002 resulted in a representative sample of 82 studies (N = 3,564 participants) providing volumetric information of the hippocampus and 51 studies (N = 2,000 participants) providing volumetric information of the amygdala. Results revealed that both the hippocampus and the amygdala are reliably asymmetrical structures in normal adults, with larger right hippocampal (D = 0.21, p.001) and right amygdala (D = 0.09, p.01) volumes. Additional analyses indicated that differences in MRI magnet field strength and slice thickness values might differentially contribute to volumetric asymmetry estimates. These results expand on previous volumetric normative studies and may be relevant to investigators studying the clinical correlates of hippocampal and amygdala volumes.

Deformable model with surface registration for hippocampal shape deformity analysis in schizophrenia

Changes to the hippocampal structure have been reported as consistent structural abnormalities in schizophrenic patients and have been related to the learning and memory deficits in such patients. Although many magnetic resonance (MR) imaging studies have focused on the hippocampal volume, local structural changes were difficult to discriminate from normal neuroanatomical variations. 3D shape deformation analysis of the brain structure may reflect localized schizophrenic abnormalities. A deformable model, evolved from the ellipsoid to hippocampal surface, with 2562 vertexes, was developed to analyze the left and right hippocampus shapes in 22 schizophrenic patients and 22 healthy age and gender matched controls. One of the most critical issues in the shape analysis is the determination of homologous points between two objects. To determine more accurate corresponding points, an alignment procedure, consisting of coarse and fine steps, following a deformation process, was applied. The performance of the alignment process was tested using artificial data, to get the alignment error to within 3 degrees for each angle. A volume analysis indicated the hippocampal volume to be bilaterally reduced in schizophrenic patients compared to the normal controls, with a shape analysis showing a deformity pattern of the hippocampal surface. Bilateral inward deformities in the anterior and posterior hippocampus and a unilateral outward deformity in the right anterior hippocampus were observed, respectively.

A study of hippocampal shape anomaly in schizophrenia and in families multiply affected by schizophrenia or bipolar disorder

Hippocampal shape anomaly (HSA), characterised by a rounded hippocampus, has been documented in congenital malformations and epileptic patients. Subtle structural hippocampal abnormalities have been demonstrated in patients with schizophrenia. We tested the hypothesis that HSA is more frequent in schizophrenia, particularly in patients from families multiply affected by schizophrenia, and that HSA is transmitted within these families. We also aimed to define the anatomical features of the hippocampus and other cerebral structures in the HSA spectrum and to determine the prevalence of HSA in a control group. We reviewed the magnetic resonance imaging of a large number of subjects with schizophrenia and bipolar disorder, many of who came from multiply affected families, relatives of the affected probands, and controls. Quantitative measures of hippocampal shape and position and other qualitative anatomical measures were performed (including depth of dominant sulcus cortical cap, angle of dominant sulcus and hippocampal fissure, bulk of collateral white matter, prominence of temporal horn lateral recess and blurring of internal hippocampal architecture) on subjects with HSA. A spectrum of mild, moderate and severe HSA was defined. The prevalence of HSA was, 7.8% for the controls (n=218), 9.3% for all schizophrenic subjects (n=151) and 12.3% for familial schizophrenic subjects (n=57). There was a greater prevalence of moderate or severe forms of HSA in familial schizophrenics than controls. However, there was no increase in the prevalence of HSA in the unaffected first-degree relatives of schizophrenic patients or in patients with familial bipolar disorder. HSA was rarely transmitted in families. HSA was frequently associated with a deep, vertical collateral/occipito-temporal sulcus and a steep hippocampal fissure. Our data raise the possibility that HSA is linked to disturbances of certain neurodevelopmental genes associated with schizophrenia. However, the lack of any increase in prevalence in the unaffected relatives of patients and the lack of clustering within individual pedigrees argues against this developmental anomaly being commonly associated with genetic predisposition to the illness.

Regional specificity of hippocampal volume reductions in first-episode schizophrenia

Hippocampal volume reductions are widely observed in schizophrenia. Some studies suggest anterior hippocampal regions are more susceptible and associated with frontal lobe dysfunctions, while others implicate posterior regions. Using high-resolution MR images and novel computational image analysis methods, we identified the hippocampal subregions most vulnerable to disease processes in 62 (45 m/17 f) first-episode schizophrenia patients compared to 60 (30 m/30 f) healthy controls, similar in age. The hippocampi were traced on coronal brain slices and hemispheric volumes were compared between diagnostic groups. Regional structural abnormalities were identified by comparing distances, measured from homologous hippocampal surface points to the central core of each individual's hippocampal surface model, between groups in 3D. CSF concentrations were also compared statistically at homologous hippocampal surface points to localize corresponding gray matter reductions. Significant bilateral hippocampal volume reductions were observed in schizophrenia irrespective of brain size corrections. Statistical mapping results, confirmed by permutation testing, showed pronounced left hemisphere shape differences in anterior and midbody CA1 and CA2 regions in patients. Significant CSF increases surrounding the hippocampus were observed in a similar spatial pattern in schizophrenia. Results confirm that hippocampal volume reductions are a robust neuroanatomical correlate of schizophrenia and are present by first episode. Mid- to antero-lateral hippocampal regions show pronounced volume changes and complementary increases in peri-hippocampal CSF, suggesting that these hippocampal regions are more susceptible to disease processes in schizophrenia. Targeting regional hippocampal abnormalities may help dissociate schizophrenia patients from other groups exhibiting global hippocampal volume changes, and better focus systems-level pathophysiological hypotheses.

Shape of caudate nucleus and its cognitive correlates in neuroleptic-naive schizotypal personality disorder

BACKGROUND

We measured the shape of the head of the caudate nucleus with a new approach based on magnetic resonance imaging (MRI) in schizotypal personality disorder (SPD) subjects in whom we previously reported decreased caudate nucleus volume. We believe MRI shape analysis complements traditional MRI volume measurements.

METHODS

Magnetic resonance imaging scans were used to measure the shape of the caudate nucleus in 15 right-handed male subjects with SPD, who had no prior neuroleptic exposure, and in 14 matched normal comparison subjects. With MRI processing tools, we measured the head of the caudate nucleus using a shape index, which measured how much a given shape deviates from a sphere.

RESULTS

In relation to comparison subjects, neuroleptic never-medicated SPD subjects had significantly higher (more "edgy") head of the caudate shape index scores, lateralized to the right side. Additionally, for SPD subjects, higher right and left head of the caudate SI scores correlated significantly with poorer neuropsychological performance on tasks of visuospatial memory and auditory/verbal working memory, respectively.

CONCLUSIONS

These data confirm the value of measuring shape, as well as volume, of brain regions of interest and support the association of intrinsic pathology in the caudate nucleus, unrelated to neuroleptic medication, with cognitive abnormalities in the schizophrenia spectrum.

Computational anatomy and neuropsychiatric disease: probabilistic assessment of variation and statistical inference of group difference, hemispheric asymmetry, and time-dependent change

Three components of computational anatomy (CA) are reviewed in this paper: (i) the computation of large-deformation maps, that is, for any given coordinate system representations of two anatomies, computing the diffeomorphic transformation from one to the other; (ii) the computation of empirical probability laws of anatomical variation between anatomies; and (iii) the construction of inferences regarding neuropsychiatric disease states. CA utilizes spatial-temporal vector field information obtained from large-deformation maps to assess anatomical variabilities and facilitate the detection and quantification of abnormalities of brain structure in subjects with neuropsychiatric disorders. Neuroanatomical structures are divided into two types: subcortical structures-gray matter (GM) volumes enclosed by a single surface-and cortical mantle structures-anatomically distinct portions of the cerebral cortical mantle layered between the white matter (WM) and cerebrospinal fluid (CSF). Because of fundamental differences in the geometry of these two types of structures, image-based large-deformation high-dimensional brain mapping (HDBM-LD) and large-deformation diffeomorphic metric matching (LDDMM) were developed for the study of subcortical structures and labeled cortical mantle distance mapping (LCMDM) was developed for the study of cortical mantle structures. Studies of neuropsychiatric disorders using CA usually require the testing of hypothesized group differences with relatively small numbers of subjects per group. Approaches that increase the power for testing such hypotheses include methods to quantify the shapes of individual structures, relationships between the shapes of related structures (e.g., asymmetry), and changes of shapes over time. Promising preliminary studies employing these approaches to studies of subjects with schizophrenia and very mild to mild Alzheimer's disease (AD) are presented.

Changes in hippocampal volume and shape across time distinguish dementia of the Alzheimer type from healthy aging☆

Rates of hippocampal volume loss have been shown to distinguish subjects with dementia of the Alzheimer type (DAT) from nondemented controls. In this study, we obtained magnetic resonance scans in 18 subjects with very mild DAT (CDR 0.5) and 26 age-matched nondemented controls (CDR 0) 2 years apart. Large-deformation high-dimensional brain mapping was used to quantify and compare changes in hippocampal shape as well as volume in the two groups of subjects. Hippocampal volume loss over time was significantly greater in the CDR 0.5 subjects (left = 8.3%, right = 10.2%) than in the CDR 0 subjects (left = 4.0%, right = 5.5%) (ANOVA, F = 7.81, P = 0.0078). We used singular-value decomposition and logistic regression models to quantify hippocampal shape change across time within individuals, and this shape change in the CDR 0.5 and CDR 0 subjects was found to be significantly different (Wilks's lambda, P = 0.014). Further, at baseline, CDR 0.5 subjects, in comparison to CDR 0 subjects, showed inward deformation over 38% of the hippocampal surface; after 2 years this difference grew to 47%. Also, within the CDR 0 subjects, shape change between baseline and follow-up was largely confined to the head of the hippocampus and subiculum, while in the CDR 0.5 subjects, shape change involved the lateral body of the hippocampus as well as the head region and subiculum. These results suggest that different patterns of hippocampal shape change in time as well as different rates of hippocampal volume loss distinguish very mild DAT from healthy aging.

Automatic construction of 3-D statistical deformation models of the brain using nonrigid registration

In this paper, we show how the concept of statistical deformation models (SDMs) can be used for the construction of average models of the anatomy and their variability. SDMs are built by performing a statistical analysis of the deformations required to map anatomical features in one subject into the corresponding features in another subject. The concept of SDMs is similar to statistical shape models (SSMs) which capture statistical information about shapes across a population, but offers several advantages over SSMs. First, SDMs can be constructed directly from images such as three-dimensional (3-D) magnetic resonance (MR) or computer tomography volumes without the need for segmentation which is usually a prerequisite for the construction of SSMs. Instead, a nonrigid registration algorithm based on free-form deformations and normalized mutual information is used to compute the deformations required to establish dense correspondences between the reference subject and the subjects in the population class under investigation. Second, SDMs allow the construction of an atlas of the average anatomy as well as its variability across a population of subjects. Finally, SDMs take the 3-D nature of the underlying anatomy into account by analysing dense 3-D deformation fields rather than only information about the surface shape of anatomical structures. We show results for the construction of anatomical models of the brain from the MR images of 25 different subjects. The correspondences obtained by the nonrigid registration are evaluated using anatomical landmark locations and show an average error of 1.40 mm at these anatomical landmark positions. We also demonstrate that SDMs can be constructed so as to minimize the bias toward the chosen reference subject.

Structural and radiometric asymmetry in brain images

This paper presents a general framework for analyzing structural and radiometric asymmetry in brain images. In a healthy brain, the left and right hemispheres are largely symmetric across the mid-sagittal plane. Brain tumors may belong to one or both of the following categories: mass-effect, in which the diseased tissue displaces healthy tissue; and infiltrating, in which healthy tissue has become diseased. Mass-effect brain tumors cause structural asymmetry by displacing healthy tissue, and may cause radiometric asymmetry in adjacent normal structures due to edema. Infiltrating tumors have a different radiometric response from healthy tissue. Thus, structural and radiometric asymmetries across the mid-sagittal plane in brain images provide important cues that tumors may be present. We have developed a framework that registers images with their reflections across the mid-sagittal plane. The registration process accounts for tissue displacement through large deformation image warping. Radiometric differences are taken into account through an additive intensity field. We present an efficient multi-scale algorithm for the joint estimation of structural and radiometric asymmetry. Results for nine MR images of patients with tumors and four normal control subjects are presented.

Asymmetry of the brain surface from deformation field analysis

The detection of asymmetry of exposed brain surfaces is examined, and a new method, deformation-based asymmetry (DBA), is introduced. DBA is based on analysis of two high-resolution magnetic resonance brain images, each with features representative of the subject group from which they were derived. Warping of individual brain images to their group representative image using octree spatial normalization provides sets of displacement vectors that are used in estimating deformation variance. For DBA group-representative left and right hemisphere images are compared. Representative hemisphere images are warped to each other and asymmetry analyzed using standardized d-values calculated as the ratio of displacement vector magnitude to the estimated component of variance in the direction of the displacement vector for each surface voxel. D-values were calculated within hemispheres by dividing subjects into two equal groups and comparing left-to-left and right-to-right. D-values from this ipsilateral hemisphere grouping were pooled. D-values from contralateral hemispheres were compared with the pooled ipsilateral hemisphere data. The proportion of d-values above a fixed level was used to test for difference between the two groups. High-resolution magnetic resonance (MR) images from 20 young, right-handed males were studied using DBA. No significant differences were seen between sub-grouped ipsilateral d-values (P > 0.10). Highly significant asymmetries (P < 0.0001) were found between hemispheres, and in each lobe. Common right frontal and left occipital petalias were seen. The DBA method can theoretically be applied to any two groups of globally similar structures where analysis of dissimilarity of regional features is sought.

Anterior hippocampal volume reduction in male patients with schizophrenia

Quantitative high resolution magnetic resonance imaging (MRI) was utilized to measure anterior, posterior, and total hippocampal volumes in 27 male patients with chronic schizophrenia and 24 male controls. To optimize measurement techniques, hippocampal volumes were: (1) acquired with 1.4-mm slices; (2) excluded with the amygdala; (3) normalized for position; and (4) corrected for total intracranial volume (ICV). The results of a linear mixed effects regression analysis, which made it possible to analyze total anterior and total posterior hippocampal volumes separately, indicated that the anterior hippocampus was significantly smaller in the schizophrenic group relative to the control group. There were no significant group differences with respect to posterior hippocampal volumes, and no significant correlations between hippocampal volumes and illness duration. A significant lateralized asymmetry was also noted in both groups with the right hippocampal volume being larger than the left. These preliminary findings support a significant anterior hippocampal volume reduction in men with schizophrenia as well as a similar hippocampal volume asymmetry in both male controls and schizophrenics.

Computer-assisted imaging to assess brain structure in healthy and diseased brains

Neuroanatomical structures may be profoundly or subtly affected by the interplay of genetic and environmental factors, age, and disease. Such effects are particularly true in healthy ageing individuals and in those who have neurodegenerative diseases. The ability to use imaging to identify structural brain changes associated with different neurodegenerative disease states would be useful for diagnosis and treatment. However, early in the progression of such diseases, neuroanatomical changes may be too mild, diffuse, or topologically complex to be detected by simple visual inspection or manually traced measurements of regions of interest. Computerised methods are being developed that can capture the extraordinary morphological variability of the human brain. These methods use mathematical models sensitive to subtle changes in the size, position, shape, and tissue characteristics of brain structures affected by neurodegenerative diseases. Neuroanatomical features can be compared within and between groups of individuals, taking into account age, sex, genetic background, and disease state, to assess the structural basis of normality and disease. In this review, we describe the strengths and limitations of algorithms of existing computer-assisted tools at the most advanced stage of development, together with available and foreseeable evidence of their usefulness at the clinical and research level.

On the metrics and euler-lagrange equations of computational anatomy

This paper reviews literature, current concepts and approaches in computational anatomy (CA). The model of CA is a Grenander deformable template, an orbit generated from a template under groups of diffeomorphisms. The metric space of all anatomical images is constructed from the geodesic connecting one anatomical structure to another in the orbit. The variational problems specifying these metrics are reviewed along with their associated Euler-Lagrange equations. The Euler equations of motion derived by Arnold for the geodesics in the group of divergence-free volume-preserving diffeomorphisms of incompressible fluids are generalized for the larger group of diffeomorphisms used in CA with nonconstant Jacobians. Metrics that accommodate photometric variation are described extending the anatomical model to incorporate the construction of neoplasm. Metrics on landmarked shapes are reviewed as well as Joshi's diffeomorphism metrics, Bookstein's thin-plate spline approximate-metrics, and Kendall's affine invariant metrics. We conclude by showing recent experimental results from the Toga & Thompson group in growth, the Van Essen group in macaque and human cortex mapping, and the Csernansky group in hippocampus mapping for neuropsychiatric studies in aging and schizophrenia.

Amygdala-hippocampal shape differences in schizophrenia: the application of 3D shape models to volumetric MR data

Evidence suggests that some structural brain abnormalities in schizophrenia are neurodevelopmental in origin. There is also growing evidence to suggest that shape deformations in brain structure may reflect abnormalities in neurodevelopment. While many magnetic resonance (MR) imaging studies have investigated brain area and volume measures in schizophrenia, fewer have focused on shape deformations. In this MR study we used a 3D shape representation technique, based on spherical harmonic functions, to analyze left and right amygdala-hippocampus shapes in each of 15 patients with schizophrenia and 15 healthy controls matched for age, gender, handedness and parental socioeconomic status. Left/right asymmetry was also measured for both shape and volume differences. Additionally, shape and volume measurements were combined in a composite analysis. There were no differences between groups in overall volume or shape. Left/right amygdala-hippocampal asymmetry, however, was significantly larger in patients than controls for both relative volume and shape. The local brain regions responsible for the left/right asymmetry differences in patients with schizophrenia were in the tail of the hippocampus (including both the inferior aspect adjacent to parahippocampal gyrus and the superior aspect adjacent to the lateral geniculate nucleus and more anteriorly to the cerebral peduncles) and in portions of the amygdala body (including the anterior-superior aspect adjacent to the basal nucleus). Also, in patients, increased volumetric asymmetry tended to be correlated with increased left/right shape asymmetry. Furthermore, a combined analysis of volume and shape asymmetry resulted in improved differentiation between groups. Classification function analyses correctly classified 70% of cases using volume, 73.3% using shape, and 87% using combined volume and shape measures. These findings suggest that shape provides important new information toward characterizing the pathophysiology of schizophrenia, and that combining volume and shape measures provides improved group discrimination in studies investigating brain abnormalities in schizophrenia. An evaluation of shape deformations also suggests local abnormalities in the amygdala-hippocampal complex in schizophrenia.

Hippocampal neurons in schizophrenia

The hippocampus is crucial for normal brain function, especially for the encoding and retrieval of multimodal sensory information. Neuropsychiatric disorders such as temporal lobe epilepsy, amnesia, and the dementias are associated with structural and functional abnormalities of specific hippocampal neurons. More recently we have also found evidence for a role of the hippocampus in the pathophysiology of schizophrenia. The most consistent finding is a subtle, yet significant volume difference in schizophrenia. Here we review the cellular and molecular basis of smaller hippocampal volume in schizophrenia. In contrast to neurodegenerative disorders, total hippocampal cell number is not markedly decreased in schizophrenia. However, the intriguing finding of a selective loss of hippocampal interneurons deserves further study. Two neurotransmitter receptors, the GABAA and AMPA/kainate glutamate receptors, appear to be abnormal, whereas changes of the NMDA glutamate receptor are less robust. The expression of several genes, including those related to the GABAergic system, neurodevelopment, and synaptic function, is decreased in schizophrenia. Taken together, recent studies of hippocampal cell number, protein expression, and gene regulation point towards an abnormality of hippocampal architecture in schizophrenia.