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Keywords:

  • cingulate cortex;
  • magnetic resonance imaging;
  • obsessive–compulsive disorder;
  • voxel-based morphometry

Abstract

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. ACKNOWLEDGMENTS
  7. REFERENCES

Aims:  Previous morphometric studies using magnetic resonance imaging (MRI) have revealed structural brain abnormalities in obsessive–compulsive disorder (OCD). The aim of the present study was to investigate the alterations in brain structure of patients with OCD using a voxel-based morphometry (VBM) method.

Methods:  Sixteen patients with OCD free of comorbid major depression, and 32 sex- and age-matched healthy subjects underwent MRI using a 1.5-T MR scanner. OCD severity was assessed with the Yale–Brown Obsessive–Compulsive Scale (mean ± SD: 22 ± 7.6; range: 7–32). MR images were spatially normalized and segmented using the VBM5 package (http://dbm.neuro.uni-jena.de/vbm/). Statistical analysis was performed using statistical parametric mapping software.

Results:  Significant reductions in regional gray matter volume were detected in the left caudal anterior cingulate cortex and right dorsal posterior cingulate cortex in the patients with OCD as compared to healthy controls (uncorrected, P < 0.001). No significant differences in white matter volumes were observed in any brain regions of the patients. No significant correlation between Yale–Brown Obsessive–Compulsive Scale score and regional gray matter or white matter volume was observed.

Conclusions:  Regional gray matter alteration in the dorsal cingulate cortex, which is suggested to play a role in non-emotional cognitive processes, may be related to the pathophysiology in OCD.

OBSESSIVE–COMPULSIVE DISORDER (OCD) is a common chronic psychiatric disorder characterized by recurrent obsessions and compulsions. OCD has a high lifetime prevalence rate of 2–3% in the general population and is considered to be among the 20 leading causes of disability in the USA and other countries.1 Abnormal feedback loops within cortical–striatal–thalamic–cortical circuits have been hypothesized to play a key role in the pathophysiology of OCD.2,3 Functional neuroimaging studies have suggested that abnormalities in the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), striatum, and thalamus were involved in the pathophysiology of OCD.4

In structural neuroimaging studies using magnetic resonance imaging (MRI), a voxel-based morphometry (VBM) technique has been applied for neuropsychiatric disorders.5 Several VBM studies have been conducted for OCD, showing volume alterations in OFC, ACC, striatum, and thalamus, although the findings were not entirely consistent, as summarized in Table 1.6–12

Table 1.  Summary of previous voxel-based morphometry studies for patients with OCD
Author and yearSubjects (Pt vs Ctl)ComorbidityMedicationMethod, statistical threshold, and smoothing kernel sizeBrain regions
ReduceIncrease
  1. ACC, anterior cingulate cortex; AxD, anxiety disorder; BN, bulimia nervosa; Ctl, Control; FC, frontal cortex; GAD, general anxiety disorder; MDD, major depressive disorder; OCD, obsessive–compulsive disorder; OFC, orbitofrontal cortex; PCC, posterior cingulate cortex; PD, panic disorder; PFC, prefrontal cortex; Pt, Patents with OCD.

Kim et al. (2001)825 vs 2521 pure 3 MDD, 1 BNNo dataP < 0.001, uncorrected, >50 voxels, 12 mmLeft cuneus Left cerebellumLeft OFC, Thalamus
Pujol et al. (2004)972 vs 72Pre-MDD: 26 Other AxD1418 free 54 underP < 0.001, uncorrected, 1000 voxels (=1500 mm3), 12 mmMedial FC and OFC, Left insulo-opercularBilateral putamen, anterior cerebellum
Valente et al. (2005)1019 vs 157 MDD, 2 past-MDD, 10 Phobia, 3 GAD, 1 PD11 under, 5 free, 3 naïveOptimized, P < 0.001, uncorrected >20 voxels (=160 mm3), 12 mmLeft ACC, FC, right angular and supramarginal gyriPosterior OFC, insula, Parahippocampal gyrus
Carmona et al. (2007)1918 vs 18Pure pediatric OCD8 naïve, underOptimized, P < 0.005, uncorrected, >40 voxels (=70 mm3), 12 mmDorsal ACC and PCC, dorsolateral FC 
Yoo et al. (2008)671 vs 714 MDD 4 AxD12 free 59 underOptimized, P < 0.001, uncorrected >20 voxels (=160 mm3), 12 mmFC, ACC, insular cortex, superior temporalPostcentral, thalamus, putamen
Gilbert et al. (2008)1125 vs 20Primary OCD not excluded25 underOptimized, P < 0.001, uncorrected >1voxels, 12 mmPFCMidbrain
Gilbert et al. (2008)1210 vs 10Pure pediatricNaïveOptimized, P < 0.001, uncorrected, no description, 12 mmLeft ACC, bilateral medial superior FC 
Szeszko et al. (2008)737 vs 2623: pure OCD pediatricNaïveOptimized, P < 0.005, uncorrected >200voxels (=265 mm3), 8 mmOccipitalLeft putamen, right lateral OFC

The aim of this study was to investigate morphological abnormalities in gray matter (GM) in patients with OCD using a VBM method that can reduce the misinterpretation of volumetric differences as a result of the normalization procedure compared to standard VBM (details are described in Methods).13

METHODS

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. ACKNOWLEDGMENTS
  7. REFERENCES

Subjects

Sixteen patients with OCD (seven men and nine women) and 32 healthy control subjects (14 men and 18 women) participated in this study. Fourteen in the OCD group and 27 in the control group were right-handed. Patients were recruited from the outpatient units of Jikei University School of Medicine in Tokyo and their affiliated psychiatric hospitals, and psychiatric divisions of general hospitals in Chiba prefecture. All patients met the DSM-IV criteria for OCD. Clinical diagnosis was completed by three trained psychiatrists. Patients with OCD were aged 32.8 ± 7.5 years (mean ± SD). Based on conventional unstructured interviews and medical histories, we excluded patients with psychiatric disorders other than OCD, such as current major depressive disorder, schizophrenia, bipolar disorders, and substance abuse. All patients had physical, neurological, blood, and urine examinations to exclude somatic disorders. Four patients were psychotropic-naive, six were drug-free for at least 5 weeks before MRI scan, and six were under selective serotonin reuptake inhibitor medication on the day of MRI scan. Twelve of the 16 patients were receiving cognitive behavioral therapy. The severity of obsessive–compulsive (OC) symptoms was assessed using the Japanese version of the Yale–Brown Obsessive–Compulsive Scale (Y-BOCS) on the day of the MRI scan (mean ± SD: 22 ± 7.6; range: 7–32).14–16

The age- and sex-matched healthy control subjects, recruited from the surrounding community, were 32.6 ± 8.7 years old. Based on unstructured psychiatric screening interviews, the control subjects were free of current and past psychiatric or somatic disorders, and had no history of drug abuse. For all subjects, no abnormalities were observed on either T1- or T2-weighted MRI.

After providing a complete explanation of the study, written informed consent was obtained from all subjects. This study was approved by the Ethics and Radiation Safety Committee of the National Institute of Radiological Sciences, Chiba, Japan.

MRI procedures

All MRI studies were performed with a 1.5-T MRI scanner (Philips Medical Systems, Best, the Netherlands). Three-dimensional volumetric acquisition of a T1-weighted gradient echo sequence produced a gapless series of thin transverse sections (echo time [TE]: 9.2 ms; repetition time [TR]: 21 ms; flip angle: 30°; field of view: 256 mm; acquisition matrix: 256 × 256; slice thickness: 1 mm). Two-dimensional volumetric acquisition of a T2-weighted gradient echo sequence produced a gapless series of thin transverse sections (TE: 100 ms; TR: 12554 ms; flip angle: 90°; field of view: 256 mm; acquisition matrix: 256 × 256; slice thickness: 2 mm).

VBM procedure

VBM was performed using the VBM5 toolbox (http://vbm.neuro.uni-jena.de/vbm) with the Statistical Parametric Mapping 5 (SPM5) software package (http://www.fil.ion.ucl.ac.uk/spm) running on Matlab 7.4. The VBM toolbox used the segmentation algorithm from SPM5, which has been demonstrated to be superior to previous SPM versions.17 Each MR T1-weighted image was segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) compartments. As the whole GM and WM volume were not changed in the present subjects (see Results), we put the emphasis of our analysis on the regional concentration differences between the OCD group and the healthy control group in the present study. We did not use the processing of modulation with the Jacobian determinants of the deformation parameters obtained by normalization to the Montreal Neurological Institute (MNI) standard space. Finally, all normalized, segmented modulated GM images were smoothed with a 12-mm full width at half maximum isotropic Gaussian kernel.18

Additionally, global GM, global WM and total intracranial (GM ± WM ± CSF) volumes were computed using the native-space tissue maps of each subject.

Statistical analysis

Global GM, global WM, and total intracranial volumes were compared between the patients with OCD and the controls using the Student's t-test. P-values less than 0.05 were considered significant.

Only voxels with values above an absolute GM and WM threshold of 0.25 entered statistical analysis so as to analyze only voxels with sufficient GM (GM value range, 0.0–1.0) and WM (WM value range, 0.0–1.0). For group comparison between OCD patients and controls, the threshold was set at P < 0.001, uncorrected for multiple comparisons (T = 3.50) and 400 or more contiguous voxels (voxel size = 1 × 1 × 1 mm). In the analysis of GM volumes, measures of GM, GM ± WM, and GM ± WM ± CSF volumes were entered as confounder in the ancova.5 In the analysis of WM volumes, measures of WM, GM ± WM, and GM ± WM ± CSF volume were entered as confounder in the ancova.5 This covariate was given by the total number of voxels within the GM, WM, and CSF compartments of each subject.

Within the OCD group, correlation between regional GM volumes or WM volumes and OC symptom severity measured using Y-BOCS was evaluated using SPM5. The age and total intracranial volume of patients with OCD were entered as confounder in the ancova. The threshold was set at P < 0.001, uncorrected for multiple comparisons (= 3.50) and 400 or more contiguous voxels (>400 mm3).

The regions showing significant volume alterations were localized in the Brodmann area (BA) as follows. MNI coordinates were converted to Talairach and Tournoux coordinates using Ginger ALE 2.0 (http://www.brainmap.org/ale/index.html). Then, BA corresponding to those regions were confirmed using Talairach Applet software (http://www.talairach.org/applet/).

RESULTS

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. ACKNOWLEDGMENTS
  7. REFERENCES

The averages of GM volumes and WM volumes were 705.8 ± 70.1 mm3 and 486.1 ± 51.6 mm3 in the OCD group and 720.3 ± 64.8 mm3 and 474.2 ± 42.8 mm3 in healthy control subjects, respectively. The intracranial volumes (GM ± WM ± CSF) were 1522.6 ± 120.2 mm3 and 1512.8 ± 119.1 mm3. There were no significant differences between the OCD and healthy control groups.

As there were no apparent differences between using different covariates (e.g. GM, WM, GM ± WM, GM ± WM ± CSF) (data not shown), we showed the data of VBM analysis for GM and WM using the GM volume or WM volume as a covariate, respectively. Significant reductions in regional GM volume were observed in the left caudal anterior cingulate cortex (ACC) (BA24) and right dorsal posterior cingulate cortex (PCC) (BA23 and BA31) in the patients with OCD as compared to healthy controls (Fig. 1 and Table 2). No significant differences in WM volumes were observed in any brain regions of the patients as compared to healthy controls.

image

Figure 1. Statistical parametric mapping (SPM) showing areas of decreased gray matter in patients with obsessive–compulsive disorder relative to healthy controls. SPM5 projections superimposed on representative transaxial, sagittal, and coronal magnetic resonance images (threshold for display: P < 0.001, uncorrected with 400 or more contiguous voxels; voxel size = 1 × 1 × 1 mm).

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Table 2.  Significant regional gray matter volume differences between patients with OCD and healthy controls. The x, y, and z coordinates were provided by Statistical Parametric Mapping, which approximates the Montreal Neurological Institute brain space and Brodmann Area
Direction of differenceNumber of voxelsPeak T scoresCoordinatesBrain regions (Brodmann area)
xyz
  1. Voxel size = 1 × 1 × 1 mm.

  2. ACC, anterior cingulate cortex; PCC, posterior cingulate cortex.

OCD group < healthy group7074.1211−2234Right dorsal PCC(23)
8793.75−8−842Left caudal ACC(31)
 3.57−7−435 (24)
 3.37−10934(31)
OCD group > healthy groupNone

There were no significant correlations between Y-BOCS score and regional GM volume or WM volume.

DISCUSSION

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. ACKNOWLEDGMENTS
  7. REFERENCES

In the present study, the VBM approach revealed significant reduction of regional GM volume in the left caudal ACC and right dorsal PCC in the OCD patients, who were free of major depression, as compared to healthy controls. Previous VBM studies also showed volume reduction in ACC6,10,12,19 and dorsal PCC.19 Especially, in two of the studies, reductions in dorsal cingulate GM volume were reported in pediatric OCD.12,19 Thus, the reduction of cingulate GM volume may reflect a critical factor in the pathophysiology of OCD.

The cingulate cortex consists of several subregions that are characterized by different cytoarchitecture, anatomical connectivity, and function.20 ACC can be divided into subregions, such as caudal, rostral, and subgenual regions. Dorsal ACC is suggested to be involved with cognitive control related to conflict.21,22 One of the core aspects of obsessions is their intrusive features,23 which are inconsistent with core values of self.24 Thus, obsessions may cause emotional and cognitive conflict. Actually, the dysfunction of conflict monitoring is known to be apparent in OCD.4 On the other hand, subgenual ACC is thought to be involved in emotional processing and mood disorder.25 Among PCC subregions, dorsal PCC is suggested to be involved with non-emotional cognitive processes, compared to ventral PCC.25 In the present study, comorbid major depression was excluded. Thus, the volume reduction in the dorsal cingulate cortex might be involved in non-emotional cognitive dysfunction, especially the deficit of cognitive conflict controlling, in OCD.

As one of the dominant hypotheses of the pathophysiology of OCD, abnormalities in the OFC, striatum, and thalamus regions are thought to play an important role in the pathophysiology of OCD.2,3 However, the present subjects did not show any significant regional volume alterations in those regions, in contrast to previous VBM studies6–11 (Table 1). As summarized in Table 1, there are many inconsistencies in the VBM studies, and they can be partly explained by the heterogeneity of subjects with OCD, as OCD is clinically heterogeneous and different symptom dimensions might be involved in different neural components.26,27 Another explanation might be the use of a different version of VBM and extent statistical threshold (cluster size) as shown in Table 1. Additionally, choosing a different smoothing kernel size may have an impact on the findings.28

There are some limitations in the present study. First, there are methodological limitations in VBM, such as difficulties in the alignment of non-homologous brains.29 Second, the statuses of medication were mixed. A previous structural MR image study showed the possible effect on regional brain volume by selective serotonin reuptake inhibitor.30 Third, comorbid anxiety disorder was not excluded as in previous VBM studies8–11 (Table 1), while the present subjects with OCD were free from current major depressive disorder.

In conclusion, the VBM approach revealed regional GM volume reductions in the dorsal cingulate cortex consisting of caudal ACC and dorsal PCC in patients with OCD. The regional GM alteration in the dorsal cingulate cortex, which is suggested to play an important role in conflict monitoring, may be related to non-emotional cognitive dysfunction in OCD.

ACKNOWLEDGMENTS

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. ACKNOWLEDGMENTS
  7. REFERENCES

This study was supported in part by a Grant-in-Aid for the Molecular Imaging Program from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japanese Government. We thank Ms Yoshiko Fukushima for her help as clinical research coordinator.

REFERENCES

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. ACKNOWLEDGMENTS
  7. REFERENCES