white matter lesions in euthymic patients with bipolar disorder

White matter lesions in euthymic patientswith bipolar disorder

Introduction

Disruption to the structural and functional integ-rity of cerebral white matter has been implicated inthe pathophysiology of bipolar disorder, withmuch of the evidence arising from magneticresonance imaging (MRI) studies. One of theearliest and most consistently replicated imaging

findings in bipolar disorder was an excess ofhyperintensities in the white matter (1, 2), visual-ized on T2-weighted and FLAIR sequences. Whitematter hyperintensities (WMHI) are found innormal populations, where their prevalenceincreases with age and shows a relationship tovascular risk (3–9). In unipolar depression, thehyperintensities are mostly limited to the elderly,

Lloyd AJ, Moore PB, Cousins DA, Thompson JM, McAllister VL,Hughes JH, Ferrier IN, Young AH. White matter lesions in euthymicpatients with bipolar disorder.

Objective: We aimed to quantify both load and regional distributionsof hyperintensities on magnetic resonance imaging (MRI) inprospectively verified euthymic bipolar patients and matched controls.Method: Cerebral hyperintensities on T2, proton density and fluid-attenuated inversion recovery (FLAIR) MRI were compared between48 bipolar and 47 control subjects using semi-quantitative rating scales.Results: Bipolar subjects had more severe frontal deep white matterlesions (DWML). Hyperintensity load was independent of age inbipolar patients but increased with age in controls. Global prevalenceand severity of hyperintensities did not differ between groups.Exploratory analysis showed DWML in excess in the left hemisphere inbipolar subjects but not in controls.Conclusion: Findings are consistent with clinical, particularly someneurocognitive, features of bipolar disorder and implicate fronto-subcortical circuits in its neurobiology. They more probably reflect atrait abnormality or illness scar rather than a mood state-dependentfinding. Processes other than ageing and vascular factors may underlietheir development.

A. J. Lloyd, P. B. Moore,D. A. Cousins, J. M. Thompson,V. L. McAllister, J. H. Hughes,I. N. Ferrier, A. H. YoungPsychobiology Group and Stanley Research Centre,Institute of Neuroscience, University of Newcastle uponTyne, Newcastle upon Tyne, UK

Key words: brain; bipolar disorder; magneticresonance imaging

Dr Adrian J Lloyd, Institute of Neuroscience, Psychiatry,Leazes Wing, Royal Victoria Infirmary, Newcastle uponTyne NE1 4LP, UK.E-mail: [email protected]

Accepted for publication May 6, 2009

Significant outcomes

• White matter MRI hyperintensities appear to be preferentially located in the frontal lobes ineuthymic bipolar patients.

• Preliminary results suggest greater asymmetrical lateralized distribution of hyperintensity load inbipolar patients but not in controls.

Limitations

• Subjects were selected to have low vascular risk and bipolar subjects were those likely to remaineuthymic, to some extent modifying generalizabilty.

• Bipolar subjects were taking a wide range of medications that could not be readily controlled for.• Laterality results are from post hoc analysis and therefore require replication.

Acta Psychiatr Scand 2009: 120: 481–491All rights reservedDOI: 10.1111/j.1600-0447.2009.01416.x

� 2009 John Wiley & Sons A/S

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particularly those with late-onset illness (2, 10–12).However, in bipolar disorder, rates of hyperinten-sities exceed those of healthy controls across alladult age groups (2, 10, 13–20) and adolescence(21–23). There are relatively few negative studies inbipolar disorder (24–28), although a publicationbias towards positive reports has been identified(1). The clinical associations of hyperintensitiesreported in bipolar disorder include a familyhistory of affective illness, winter birth, risk ofsuicide, treatment resistance and a greater num-ber of hospitalizations (14, 16, 29–33). However,WMHIs have not been associated with the pres-ence of psychosis or the severity of depressionper se (14–16, 25, 31). As much of the previouswork has examined mixed groups of subjects invarious illness phases, it is unclear whether hyper-intensities precede illness onset, are related toillness phase or result from repeated exposure topathological mood states over time.Deep white matter lesions (DWML) can be

distinguished from periventricular lesions (PVL)on image analysis, although few MRI studies inbipolar disorder have specifically considered thisdifference. Importantly, the two types of lesionprobably differ to some degree in their neuro-pathological basis (34–36). Although WMHIs areobserved throughout the brain, laterality may beimportant with a greater degree of significantdifference from normal controls reached for righthemisphere lesions in a recent meta-analysis (1).One study found more right hemisphere lesions inbipolar patients than in controls and more lefthemisphere lesions in controls than in bipolarsubjects, although low subject numbers and the useof categorical, un-standardized ratings were impor-tant limitations (37).The cognitive deficits observed in episodes of

bipolar disorder frequently persist into euthymia(25, 38–41) with sustained attention and frontalexecutive task dysfunctions being prominent (40).Such impairments may arise from dysfunction inthe reciprocal neural circuits that link the lateralorbitofrontal, dorsolateral prefrontal and anteriorcingulate cortex to the striatum and thence globuspallidus ⁄ substantia nigra and thalamus, as theseloops have been defined as of particular impor-tance in affective disorders (42, 43). WMHIs inbipolar disorder have been associated withimpaired cognitive function in some (14, 31) butnot in all studies (25).Given the prominence of frontal executive dys-

function in bipolar disorder, its persistence intoeuthymia and the potential association withWMHIs, there is a need for additional informationon the regional distribution of lesions when illness

phase is controlled for. To this end, we investigatedthe regional distribution of hyperintensities inbipolar disorder, specifically considering deep andPVLs separately and examining their lobar distri-bution by comparing bipolar subjects verifiedprospectively as euthymic with healthy controls.

Aims of the study

i) To investigate the load and regional distribu-tion of white matter hyperintensities in euthymicbipolar patients compared with that in healthycontrols; ii) to explore the hypotheses that hyper-intensities would be more common in bipolarsubjects than in controls and that they would bepresent to a greater degree in the frontal lobes thanin other brain regions and iii) to undertake anexploratory analysis of lesion laterality.

Material and methods

Subjects

The study was approved by the Newcastle andNorth Tyneside joint ethics committee. Clinicallyeuthymic individuals referred from clinical psychi-atry services were screened for inclusion andexclusion criteria; 49 patients were recruited. Onebipolar subject�s scan was unusable because ofmovement artefact; thus, 48 patients� data wereanalysed. Forty-seven control subjects wererecruited from the community by advertisementand personal contacts. Controls were matched tothe bipolar subjects for age, gender, handedness(44), highest achieved occupational status (45) andpremorbid IQ [National Adult Reading Test,NART (46)]. Following full explanation of thestudy to the subjects, written informed consent wasobtained prior to participation.

Diagnosis and assessment

All patients fulfilled DSM-IV criteria for bipolaraffective disorder type I (40 subjects) or II (8subjects) diagnosed by experienced psychiatristsusing the Structured Clinical Interview for DSM-IV (SCID) (47). Euthymia was defined as a score ofseven or less on both the 17-item Hamiltondepression rating scale (HAM_D) (48) and theYoung mania rating scale (YMRS) (49) performedat initial assessment and on the day of scanning1 month later. Self-rated scales for depression – theBeck Depression Inventory (BDI) (50) and manicsymptoms – the Altman Self-Rating Mania Scale(AMRS) (51) were completed 4 weeks prior toscanning to assess mood stability. Controls were

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subject to the same clinical rating scales as patientsincluding the SCID to exclude psychiatric illnessbut completed self-rating scales only once (in theweek prior to scanning). Total number and cumu-lative duration of illness episodes in bipolar sub-jects were assessed by interview and review of casenotes.Exclusion criteria for bipolar subjects were

other comorbid psychiatric conditions, learningdisability and ECT within 1 year of scanning.The Mini-Mental State Examination (MMSE)(52) was used to screen for cognitive impairment(no subject scored <28 ⁄30). The Alcohol UseDisorders Identification Test (AUDIT) (53) andSCID substance use rating were applied. Individ-uals meeting the criteria for substance abuse inthe previous 6 months were excluded. Exclusioncriteria included the presence or history ofcerebrovascular disease, neurodegenerative disor-ders, severe head injury, epilepsy, Parkinson�sdisease, systemic illness with cerebral conse-quences, focal neurological signs, hepatic disor-ders, cardiovascular disease, renal failure,hypertension (BP >150 ⁄100 or treatment forhypertension), endocrine disorders (except cor-rected hypothyroidism), corticosteroid medicationand any contraindication to MRI. Exclusioncriteria for controls were identical with additionalrequirements of no current axis I or II psychi-atric diagnosis, past psychiatric history, familyhistory of psychiatric illness in first-degree rela-tives and no current medication other than oralcontraceptives.

Magnetic resonance imaging

Scans were performed on a General Electric Signa1.5-T scanner (General Electric, Milwaukee, WI,USA). T2-weighted (repetition time,TR=3420 ms,echo time, TE = 97.2 ms, number of excitations,NEX = 2, matrix 256·256, 5 mm slice thickness,2 mm gap), proton density (TR = 2040 ms, TE =10.1 ms, NEX = 2, matrix 256·256, 5 mm slicethickness, 2 mmgap) and fluid-attenuated inversionrecovery (FLAIR;TR = 10 002 ms,TE = 142 ms,inversion time 2100 ms; NEX = 1, matrix 256·192,5 mm slice thickness, 2 mmgap) axial data sets wereacquired. Small areas of fluid (e.g. Virchow–Robinspaces) that appear hyperintense on T2-weightedscans can be mistaken as punctate hyperintensities.FLAIR gives excellent contrast for hyperintensities,whilst fluid remains dark. As many other studieshave used T2-weighted and proton density proto-cols, we examined these alongside FLAIR to ensurecomparability with previous literature. Lesionswereto be considered present if visible on FLAIR and at

least on one other sequence. All lesions were, in fact,visible on all three sequences.

Image analysis

Hyperintensities were categorized as PVL, DWMLand basal ganglia hyperintensities (including basalganglia grey nuclei and internal ⁄ external capsule).Hard copies of scans were rated simultaneously butindependently by two raters (AJL ⁄PBM), blindedto subject group and characteristics, for the pres-ence and severity of hyperintensities. Lesion sizewas measured on the FLAIR images using calli-pers. Any disagreement was resolved by discussionand a consensus rating reached. Two scales,Scheltens� scale (54) and Fazekas� scale (31, 55),were used. Both rate global hyperintensity severity,but the Scheltens� scale additionally assesses lesionload in specific brain regions. Scoring for the twoscales is summarized in Table 1. Validity and inter-rater reliability of these scales are established (54,56) as is the approach to image analysis describedabove (57, 58). Global hyperintensity ratings forDWML and PVL were carried out with bothscales. Correlation between the two scales wasundertaken for DWML and showed good agree-ment (q = 0.86, P < 0.001). Regional ratingswere undertaken with the Scheltens� scale, withdefinitions of lobar regions taken from Talairachand Tournoux (59). The Fazekas� scale allowscommonly seen mild periventricular change to beconsidered a normal variant, but the Scheltens�scale rates such subjects as having a low butpositive score. As this feature of the Scheltens� scale

Table 1. Description of hyperintensity ratings on Fazekas� and Scheltens� scales

Fazekas' score DescriptionPVL 0 Absent

1* Minimal change considered normal variant1 Caps and ⁄ or pencil thin lining2 Smooth halo3 Irregular periventricular lesions extending

into deep white matterDWML ⁄ grey

nuclei lesions0 Absent1 Punctate foci2 Beginning of confluence of lesions3 Large confluent areas

Scheltens� score DescriptionPVL (caps

and bands)0 Absent1 £5 mm2 ‡6 mm

DWML ⁄ greynuclei lesions

0 Absent1 £3 mm, £5 lesions2 £3 mm, ‡6 lesions3 4–10 mm, £5 lesions4 4–10 mm, ‡6 lesions5 ‡11 mm, at least 1 lesion6 Confluent lesions

PVL, periventricular lesions; DWML, deep white matter lesions.

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provides no specific advantage over the Fazekas�rating (54), the latter was used as the primaryrating for global PVL and in the analysis of lesionprevalence. As neither scale formally considers thelaterality of lesions, scans were given an unmod-ified Scheltens� rating for each hemisphere sepa-rately to allow an exploratory but systematizedanalysis of left–right distribution.

Statistical analysis

Data were analysed using the Statistical Packagefor Social Sciences (spss 11.0, SPSS Inc., Chicago,IL, USA). Continuous variables were examined fornormality of distribution using the Kolmogorov–Smirnov test and Q–Q plots. Student�s t-test wasused for group comparisons of normally distributedvariables and the Mann–Whitney U-test for non-parametric data, with Spearman rank test (q) forcorrelations. Categorical data sets were analysedusing chi-squared test. Tests were two tailed and avalue of P £ 0.05 was considered statistically sig-nificant. Main results were re-analysed for bipolar Ipatients only, but analysis of the bipolar II groupalone and comparison of type I and type II BipolarDisorder were not attempted because of the lownumber of bipolar II subjects. Correlations with ageand number of illness episodes were limited to asingle measure each of DWML, PVL and fron-tal DWML. Scheltens� scale was used for allcorrelations as this gives a wider range of scoresthan the Fazekas�. A secondary analysis of lateral-ity was undertaken within each diagnostic groupfor global deep and PVL load and frontal deephyperintensities using the Wilcoxon signed ranktest.

Results

Subject characteristics

These are summarized in Table 2. Groups werecomparablewith respect to age, handedness, gender,years in education and occupational classification.There was no difference in global cognitive function(MMSE) or premorbid intellectual level (NART).No subject�s score on HAM_D indicated depressedmood (all £7) on initial rating or day of scanning,although the bipolar group scores were statisticallysignificantly higher than the controls. BDI scores inpatients were low throughout the 4 weeks prior toscanning in patients but again were statisticallyhigher in patients than in controls in the4 weeks of comparison. Groups did not differ onobserver-rated or self-rated manic symptoms, withbipolar subjects having low self-rated scores across

the 4 weeks.Themeannumber of illness episodes forbipolar subjects was 20 (range 2–166, 95% CI 12–28). Only two bipolar subjects were drug free, withthe remainder taking medication either as mono-therapy or in various combinations (see Table 3).Bipolar and control groups did not differ in alcoholuse (AUDIT score: U = 1112.0, P = 0.905; UKalcohol units:U = 923.0,P = 0.125) or prevalenceof diabetes (nil in both groups).Nine controls and 18bipolar patientswere smokers (d.f. = 1,v2=3.931,P = 0.047). Eight patients and no controls had ahistory of previous substance misuse (alcohol 5,drugs 2, alcohol and drugs 1).

Hyperintensities

Prevalence of all WMHI and of PVL (Table 4)showed a trend towards being greater in bipolarsubjects than in controls but this did not reachstatistical significance [difference between bipolarand control subjects; 17% for all lesions(P = 0.09), 12% for PVL (P = 0.082) and 16%for DWML (P = 0.123)].Regional analysis of lesion severity using the

Scheltens� scale showed a significant excess(U = 845.5, P = 0.024) of frontal DWML inpatients (Table 4) with bipolar disorder (type Iand II combined). Statistical significance was notmaintained when data from the bipolar II subjectswere excluded (U = 758.0, P = 0.091). Groupsdid not differ significantly in hyperintensity load inother lobar regions or the basal ganglia. There wasno significant excess of global DWML load inbipolar subjects, although this approached statis-tical significance on Fazekas� ratings (U = 907.5,P = 0.071). No significant difference in PVLseverity was detected either globally or on regionalanalysis. When data were re-analysed excludingeach set of subjects with previous substance misuse,only small changes in P-values and no change inthe pattern of results (frontal lobe DWML differ-ences remained significant at P £ 0.026) occurred,indicating that the inclusion of these individualshad little impact on the results.Smoking status did not have any significant

effect on scores for global hyperintensity load:Scheltens� scale [mean (95% CI)] did not differbetween smokers and non-smokers in the controlgroup [smokers, n = 9: 4.1 ()1.7–9.9); non-smokers,n = 38: 3.4 (2.3–4.5); U = 145.5, P = 0.48] or inthe bipolar group [smokers, n = 18: 4.0 (2.6–5.4);non-smokers, n = 30: 5.3 (2.9–7.7); U = 227.5,P = 0.36] or when the controls and bipolarsubjects were combined as a single group [smokers,n = 27: 4.0 (2.2–5.9); non-smokers, n = 68: 4.2(3.0–5.4); U = 844.0, P = 0.54].

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Although subjects were euthymic as defined bystudy criteria, there was a difference in sub-syndromal depressive features indicated by thehigher HAM_D score in bipolar subjects. Datawere therefore examined for any evidence of arelationship between HAM_D and frontal hyper-intensity scores: there was no significant correla-tion between the Scheltens� frontal DWML scoreand the HAM_D score in the combined controland bipolar sample (screen HAM_D: q = 0.05,

P = 0.629; pre-MRI HAM_D: q = 0.18, P =0.079), the control subjects alone (screen HAM_D:q = )0.15, P = 0.302; pre-MRI HAM_D: q =0.19, P = 0.207) or the bipolar group alone (screenHAM_D: q = 0.07, P = 0.626, pre-MRIHAM_D: q = 0.07, P = 0.647). The numbers ofsubjects receiving treatment with particular combi-nations of medication were (Table 3) too small toallow meaningful statistical analysis of possiblemedication effects on the prevalence or severity ofhyperintensities.Neither number of previous illness episodes nor

total cumulative duration of illness episodes inbipolar subjects correlated significantly with PVL(number of episodes: q = 0.262, P = 0.078;total duration: q = 0.163, P = 0.278), DWML(number: q = 0.201, P = 0.180; duration: q =0.236, P = 0.115) or frontal DWML (number:q = 0.240, P = 0.108; duration: q = 0.226,P = 0.131).Control subjects� ages correlated positively and

significantly for global PVL (q = 0.432,P = 0.002) and DWML (q = 0.470, P = 0.001)and also positively with frontal DWML(q = 0.346, P = 0.017). By contrast, there wasno significant relationship between age and these

Table 2. Characteristics of bipolar and controlgroups Bipolar group (n = 48) Control group (n = 47) Comparison

Age (years) 44.5 € 8.9 45.8 € 8.6 NS: t = 0.792, d.f. = 93, P = 0.460Male : female 22 : 26 19 : 28 NS: d.f. = 1, v2 = 0.283, P = 0.595% right-handed 88 92 NS: d.f. = 2, v2 = 3.144, P = 0.208Duration of

education (years)14.7 € 3.0 14.3 € 3.2 NS: t = )0.549, d.f. = 93, P = 0.584

Occupational classI 8 (17%) 8 (17%) NS: d.f. = 5, v2 = 9.09, P = 0.106II 23 (48%) 12 (26%)III manual 5 (10%) 3 (6%)III non-manual 8 (17%) 20 (43%)IV 2 (4%) 2 (4%)V 2 (4%) 2 (4%)

SCID GAF 78.7 € 8.4 90.9 € 3.7 t = 9.2, d.f. = 64.9 P < 0.001MMSE 29.6 € 0.6 29.8 € 0.6 NS: t = 1.536, d.f. = 93, P = 0.012NART 109.9 € 10.7 109.9 € 9.1 NS: t = )0.001, d.f. = 93, P = 0.999HAM_D

Screening 1.4 (1.0–1.9) 0.6 (0.3–0.9) U = 745.5, P = 0.002Pre-MRI 1.5 (0.9–2.0) 0.6 (0.2–0.9) U = 775.5, P = 0.006

YMRSScreening 0.9 (0.4–1.3) 0.4 (0.1–0.6) NS: U = 978.0, P = 0.143Pre-MRI 1.1 (0.5–1.6) 0.4 (0.1–0.6) NS: U = 951.0, P = 0.136

BDI week 1 6.2 (4.4–7.9)BDI week 2 5.0 (3.4–6.6)BDI week 3 4.7 (2.9–6.3)BDI week 4 4.6 (3.0–6.0) 1.9 (1.2–2.5) U = 799.0, P = 0.009AMRS week 1 3.2 (2.2–4.2)AMRS week 2 2.4 (1.6–3.1)AMRS week 3 2.0 (1.4–2.7)AMRS week 4 2.2 (1.5–2.9) 1.9 (1.3–2.5) NS: U = 1078.0, P = 0.576

Continuous variables expressed as mean € SD for parametric data; mean (95% confidence interval) for nonparametricdata. SCID GAF, Structured Clinical Interview for DSM-IV global assessment of functioning; MMSE, Mini-Mental StateExamination; NART, National Adult Reading Test; HAM_D, Hamilton Depression Inventory 17 item scale; YMRS, YoungMania Rating Scale; BDI, Beck Depression Inventory; AMRS, Altman Self-rating Mania Rating; NS, non-significant.

Table 3. Medication details of bipolar patients

Medication group n (total 48)

Drug free 2Lithium only 10Anticonvulsant only 6Antidepressant only 1Antipsychotic only 2Lithium + anticonvulsant 8Lithium + antidepressant 6Lithium + antipsychotic 4Anticonvulsant + antidepressant 3Anticonvulsant + antipsychotic 2Lithium + anticonvulsant + antidepressant 1Lithium + anticonvulsant + antipsychotic 3


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ratings in bipolar subjects (PVL: q = )0.044,P = 0.769; DWML: q = 0.092, P = 0.533; fron-tal DWML: q = 0.157, P = 0.285) despite thefact that the groups have comparable age distri-butions.

Lesion laterality

Laterality of lesion load within each group wasassessed using the Scheltens� scale, examiningscores for PVL, global DWML and frontalDWML in each hemisphere (see Table 4). Therewas a significant excess of DWML in the lefthemisphere as a whole compared with the right inbipolar subjects (z = )2.883, P = 0.005) but notin controls (z = )1.081, P = 0.280). As with theglobal brain lesion load, this result became statis-tically non-significant when the bipolar II patientswere excluded from the analysis (z = )1.093,P = 0.057). No significant laterality differencewas found for frontal DWML or PVL scores ineither group.

Discussion

These data demonstrate: i) an excess DWML loadin the frontal lobes of euthymic bipolar patientscompared with that in controls; ii) a correlationbetween the global DWML, frontal DWML and

global PVL lesion severity and age in controls butnot in bipolar subjects; iii) a greater lesion load inthe left hemisphere of bipolar subjects but not incontrols in an exploratory analysis.The excess of frontal DWML in bipolar patients

is consistent with the limited literature availableregarding the regional distribution of hyperinten-sities in this illness (13, 14, 20). As all of ourpatients were prospectively verified as euthymic,the imaging findings are independent of the imme-diate effects of acute illness or the presence ofclinically disordered mood. Consequently, thenotion of excess frontal hyperintensities being anenduring feature of bipolar disorder is supported.We did not demonstrate the hypothesized

increase in the prevalence or severity of hyperin-tensities globally in the brains of bipolar subjects.The majority of studies in this field have found anexcess of WMHI in bipolar patients, with frequen-cies ranging 19–66% compared with 0–36% forcontrols (10), although there are a number ofnegative reports (24–27). The odds ratio for thepresence of hyperintensities in bipolar subjectswhen compared with controls ranges from 2.5 to3.3 prior to inclusion of our data (1, 16). The lackof difference in global ratings of WMHI prevalencebetween patients and controls in our study may bea reflection of the clinical characteristics of oursubjects. Other studies that have demonstrated no

Table 4. Prevalence, severity and laterality of white matter hyperintensities

Scale RegionBipolar group

(n = 48)Control group

(n = 47) Comparison

Prevalence Fazekas� Any abnormal PVL 21% 9% NS: d.f. = 1, v2 = 2.870, P = 0.09Any DWML 56% 40% NS: d.f. = 1, v2 = 2.381, P = 0.123Any hyperintensity 60% 43% NS: d.f. = 1, v2 = 3.034, P = 0.082

Severityscore

PVL Fazekas� Abnormal PVL 0.3 (0.1–0.5) 0.1 (0.0–0.2) NS: U = 987, P = 0.088PVL Scheltens� Total PVL 1.8 (1.4–2.2) 1.4 (1.2–1.7) NS: U = 976.5, P = 0.240Regional PVL Scheltens� Frontal caps 0.9 (0.8–1.1) 0.8 (0.7–1.0) NS: U = 1044, P = 0.395

Occipital caps 0.4 (0.2–0.6) 0.2 (0.1–0.3) NS: U = 954, P = 0.092Bands 0.5 (0.3–0.7) 0.5 (0.3–0.6) NS: U = 1081, P = 0.687

DWML Fazekas� Global rating 0.8 (0.6–1.1) 0.5(0.3–0.7) NS: U = 907.5, P = 0.071DWML Scheltens� Global rating 3.0 (1.6–4.1) 2.0 (1.0–3.2) NS: U = 964, P = 0.203Regional DWML Scheltens� Frontal 1.3 (0.9–1.8) 0.7 (0.4–1.1) U = 845.5, P = 0.024

Parietal 0.9 (0.4–1.4) 0.6 (0.2–1.0) NS: U = 1042.5, P = 0.451Temporal 0.2 (0.0–0.4) 0.2 ()0.1–0.5) NS: U = 1109.5, P = 0.786Occipital 0.4 (0.0–0.8) 0.4 (0.1–0.8) NS: U = 1043.5, P = 0.334

Subcortical grey nuclei Scheltens� Basal ganglia and internal⁄ external capsule

0.1 (0.0–0.3) 0.1 (0.0–0.2) NS: U = 1106, P = 0.718

Laterality Scheltens� score for individualhemispheres

DWML entire left hemisphere 2.6 (1.4–3.8)* 1.6 (0.6–2.6)*DWML entire right hemisphere 1.9 (0.9–2.8)* 1.2 (0.6–1.9)*DWML frontal left hemisphere 1.2 (0.7–1.6)� 0.5 (0.3–0.8)�DWML frontal right hemisphere 1.0 (0.5–1.4)� 0.6 (0.3–0.9)�PVL entire left hemisphere 1.7 (1.3–2.1)� 1.4 (1.1–1.6)�PVL entire right hemisphere 1.8 (1.4–2.2)� 1.4 (1.1–1.7)�

Results are expressed as mean (95% confidence interval). PVL, periventricular lesions; DWML, deep white matter lesions; NS, non-significant.Left hemisphere versus right hemisphere within-group comparisons:*Bipolar: z = )2.883, P = 0.005; control: z = )1.081, P = 0.280.�Bipolar: z = )1.369, P = 0.171; control: z = )0.265, P = 0.792.�Bipolar: z = )1.414, P = 0.157; control: z = )1.000, P = 0.317.

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difference in prevalence have typically includedsubjects with mild-to-moderate illness (27) orconsidered only euthymic patients (25), consistentwith the putative link to more severe illness (14, 16,30).Although some indicators of a more severe

illness [poor treatment response (30), more fre-quent hospitalization (14) and a diagnosis ofbipolar I rather than bipolar II disorder (16)]have been associated with a greater prevalence ofhyperintensities, we detected no relationshipbetween lesion load and the number of, or cumu-lative exposure to, episodes of illness. Our samplecomprised mostly of bipolar I subjects who hadexperienced numerous episodes of illness, but atthe time of investigation all subjects had recoveredsymptomatically and were living in the community.Our results indicate that frontal DWML in bipolardisorder persist beyond illness recovery, may beindependent of progressive exposure to episodes ofillness and as such may represent an enduringfeature. This is in agreement with previous workshowing no change in hyperintensities with moodstate or the passage of time (14), and with theproposal that lesions may arise with or evenpredate the onset of illness (21–23).The prevalence of WMHI increases with age in

most populations studied (3–9). An excess oflesions has been reported in bipolar disorderacross all age groups and, although there is somedispute regarding prevalence early in the course ofillness (18, 21, 22, 28), WMHIs are generallyreported to increase with age (2, 10, 16, 60) withonly occasional findings to the contrary (18). Thecorrelation between the severity of hyperintensitieswith age in our control subjects but not in ourbipolar patients is therefore of interest. The prev-alence of abnormal hyperintensities (21%) in ourbipolar patients is in keeping with the age of thegroup, and contrasts with the figure of around10% reported in younger subjects (28, 61). Vascu-lar risk factor burden is thought to be important indetermining rates of MRI hyperintensities. Evi-dence from other disorders shows the strikingimportance of vascular pathology in DWML,lesions in sub-cortical grey matter and in largerPVL (34–36). There is direct evidence for vascularpathology in DWML in unipolar depression (62),but similar studies have not been conducted inbipolar disorder. Our selection criteria are likely tohave excluded those with gross vascular disease;however, subtle vascular pathology may accountfor the observed correlation of hyperintensitieswith age in our control subjects. Hyperintensityscores were not related to smoking status, incontrast to the majority of previous reports (63,

64). Although smoking may be an independent riskfactor for worsening WMHI in elderly popula-tions, the relationship could be mediated throughvascular damage (64). The lack of an associationbetween smoking and hyperintensities in our studymay therefore be a consequence of excluding thosewith overt vascular disease.It is plausible that the subtle age-related changes

observed in controls may have been masked inbipolar patients by an as yet unidentified illness-related pathological process, particularly if thiswere present from the onset of the illness. Neuro-pathological studies of subcortical areas in bipolardisorder are few (65), but there is evidence fordisordered oligodendrocyte and myelin function(66), perhaps arising at a genetic level. A recentstudy (67) reported reduced myelin staining in thefrontal white matter of bipolar subjects, whichmight be consistent with DWML occurring in thisregion. However, imaging was not conducted andas other brain regions were not examined it is notpossible to know whether this was a localized orgeneralized change.A significant excess of deep WMHI in the left

hemisphere was present in our bipolar subjectscompared with that in controls. Whilst this result isfrom a secondary analysis, we believe it to be animportant and original contribution regarding thelaterality of lesions within bipolar disorder. Itstands in contrast to the lack of left ⁄ right differ-ence in matched controls and indicates a need forfurther investigation.Our findings of increased frontal lobe DWML in

the bipolar group supports the putative derange-ment of fronto-subcortical circuitry reported in thepathophysiology of affective disorders in general,and in bipolar disorder in particular (42, 43). It mayalso explain, in part, the observation of prominentfrontal-executive task deficits reported in euthymicbipolar disorder subjects (40). The prefrontalcortex and striatum are linked to medial temporallobe structures (amygdala and hippocampus) andthence to the cerebellum, all of which are impor-tant in emotional processing (2). A number ofstudies have reported structural brain changes inbipolar disorder in these brain regions (2), but aconsistent pattern of abnormalities is not apparentin meta-analysis (1, 68). Conceptualizing anatom-ical changes in terms of network dysfunctionallows a fuller interpretation of diverse findings,places disturbed white matter function in a primeposition and highlights the importance of consid-ering region-to-region connectivity (43). FrontalWMHI can be linked to disturbed cognitive andemotional processes in bipolar disorder, althoughwe must recognize that the data presented here do


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not allow testing of the direction of causalitybetween hyperintensities and bipolar disorder.Few other studies have considered regional

distribution of hyperintensities, including thosethat have typically included bipolar subjects expe-riencing a range of mood states when tested (13, 14,20). This study adds to these limited data and doesso in a cohort of bipolar subjects who were rated aseuthymic for at least 1 month prior to the principalassessments. Our sample size was reasonably largeand the groups were well matched on demographicvariables as well as estimates of premorbid educa-tional level and IQ.There are a number of limitations to our study

that warrant discussion. Typically, the bipolarsubjects recruited into this study were taking arange of different drugs, often in combination(Table 3). This diversity of treatment is somewhatinevitable in clinical populations but limits theconclusions that can be drawn with regard tospecific medication effects. Subjects were compliantwith research and recruited with the expectationthat they were likely to remain euthymic for thestudy duration, restricting the generalizability ofthe results. Although a retrospective assessment,the number and duration of episodes as establishedat interview were supplemented by a review of theclinical records. Recent reviews and publisheddatabases (1) have demonstrated that largesample sizes are required when investigating thepotentially subtle differences in brain structure inbipolar disorder. Our study was probably at thelower limit of power for the detection of whitematter lesion differences, especially given the lowvascular burden imposed by the inclusion ⁄ exclu-sion criteria chosen. Our statistical analysis wasalso constrained by the presence of nonparametricdata, although this was not unexpected given thenature of the rating scales used. Drawing on theprinciple of asymptotic relative efficiency to esti-mate the power of the nonparametric Mann–Whitney U-test (with the Student�s t-test taken asthe reference), the worst-case scenario of the lowestpotential power for samples in this study would bea power of 80% to detect a medium effect size of0.63 significant at the 5% level, and 60% for aneffect size 0.50. For this reason, the eight bipolar IIsubjects were retained in all main analyses, whilstrecognizing that this may have introduced a degreeof pathophysiological heterogeneity. Although theremoval of the type II patients from the analyseshad little impact on the overall pattern of theresults, between-group differences were no longersignificant for frontal lobe DWML lesion load(U = 758.0, P = 0.091) and laterality contrast inbipolar patients (z = )1.093, P = 0.057). Given

the limitations in power, and in order to avoidinappropriate acceptance of the null hypothesis(69), formal adjustments for multiple comparisonsduring analysis were not made.In this study, the presence of WMHI was

determined by visual inspection of individualMRI scans, and the severity estimated usingestablished rating scales. The Scheltens� and Faze-kas� scales are both reliable and valid, and instru-ments of this type have previously been applied topatient populations similar to that reported here.The use of such rating scales appears unlikely tobias the direction of results, as both positive andnegative findings have been reported in earlierstudies [Fazekas� or Fazekas-like scales (16, 18, 19,24, 25, 27); regional analysis scales (13–15, 26)].However, their specific limitations should be rec-ognized. The ratings are semi-quantitative, poten-tially open to human error and were largelyvalidated in elderly populations where the extentof the lesion load is likely to exceed that observedin our patient group. The range and diversity oflesions in a younger population may be differentfrom that observed in the validation studies, andwe cannot be certain that the underlying pathologyis similar because of lack of data. The scales yieldordinal data, but it must be recognized that theclassification of lesion severity in this way essen-tially loses information from a number of contin-uous variables (size ⁄volume, number and shape oflesions). There is an inherent risk that such aconversion introduces ceiling effects, limits thepower of the study to detect subtle differences andrestricts the statistical analysis to largely nonpara-metric techniques. The regional classification ofDWML is based on the major anatomical lobarregions rather than functional division but shouldbe considered as an initial step towards systematicanalysis of hyperintensities in finer resolution thana simple global rating.Quantitative measurement of hyperintensity

volume is now practicable and early studies indicatethat bipolar patients have a greater white matterlesion load compared with controls (29). Suchtechniques have the advantage of generatingdirectly comparable volumes of tissue affectedwithout the limitations of visual rating scales,although the approach is not standardized. Somemethods rely on experienced investigators to iden-tify and delineate lesions prior to volumetricestimation (29), whilst others use a more automatedthreshold and erosion technique (70). Further, it isnot clear whether such relative volume measure-ments truly reflect the severity of the pathology orhave the capacity to embrace the diversity of theabnormalities present (one large lesion may be

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equivalent to several smaller ones in terms ofvolume but not in terms of cause or effect).Future studies would benefit from synthesizing

data from quantitative analysis techniques as wellas visual ratings, and our results indicate that ahypothesis-driven inspection of frontal lobe whitematter lesion load may prove fruitful. Such studiesshould ideally include those that control for moodstate at the time of scanning and specificallyexamine the regional distribution and laterality oflesions in conjunction with other localizing tech-niques such as neuropsychological functions.Whilst our findings indicate that frontal hyper-

intensities appear to be present in euthymia and donot to correlate with illness exposure, we cannotyet deduce whether the lesions are a trait marker ora consequence of the illness process. Prospectivestudies investigating premorbid individuals at riskof bipolar disorder are necessary to address thisissue definitively.

Acknowledgements

This paper is dedicated to the memory of Dr Vic McAllister, avalued colleague who provided the research group with expertneuro-radiological advice over a number of years and whosadly died prior to the publication of this study.The study wasfunded by the Stanley Medical Research Institute.

Declaration of interests

The authors of this paper do not have any commercialassociations that might pose a conflict of interest in connectionwith this manuscript.

References

1. Kempton MJ, Geddes JR, Ettinger U, Williams SC, Grasby

PM. Meta-analysis, database, and meta-regression of 98structural imaging studies in bipolar disorder. Arch GenPsychiatry 2008;65:1017–1032.

2. Soares JC, Mann JJ. The anatomy of mood disorders –review of structural neuroimaging studies. Biol Psychiatry1997;41:86–106.

3. Christiansen P, Larsson HB, Thomsen C, Wieslander SB,Henriksen O. Age-dependent white-matter lesions andbrain volume changes in healthy volunteers. Acta Radiol1994;35:117–122.

4. de Leeuw FE, de Groot JC, Achten E et al. Prevalence ofcerebral white matter lesions in elderly people: a populationbased magnetic resonance imaging study. The RotterdamScan Study. J Neurol Neurosurg Psychiatry 2001;70:9–14.

5. Ylikoski A, Erkinjuntti T, Raininko R, Sarna S, Sulkava R,Tilvis R. White matter hyperintensities on MRI in theneurologically nondiseased elderly. Analysis of cohorts ofconsecutive subjects aged 55 to 85 years living at home.Stroke 1995;26:1171–1177.

6. Liao DP, Cooper L, Cai J et al. The prevalence and severityof white matter lesions, their relationship with age, eth-nicity, gender, and cardiovascular disease risk factors: theARIC Study. Neuroepidemiology 1997;16:149–162.

7. Bots ML, van Swieten JC, Breteler MM et al. Cerebralwhite matter lesions and atherosclerosis in the RotterdamStudy. Lancet 1993;341:1232–1237.

8. de Leeuw FE, de Groot JC, Oudkerk M et al. Atrial fibril-lation and the risk of cerebral white matter lesions. Neu-rology 2000;54:1795–1801.

9. Skoog I. A review on blood pressure and ischaemic whitematter lesions. Dement Geriatr Cogn Disord 1998;9(suppl1):13–19.

10. Videbech P. MRI findings in patients with affective disor-der: a meta-analysis. Acta Psychiatr Scand 1997;96:157–168.

11. O�Brien JT, Ames D, Schweitzer I. White matter changes indepression and Alzheimer�s disease: a review of magneticresonance imaging studies. Int J Geriatr Psychiatry 1996;11:681–694.

12. Iidaka T, Nakajima T, Kawamoto K et al. Signal hyperin-tensities on brain magnetic resonance imaging in elderlydepressed patients. Eur Neurol 1996;36:293–299.

13. Dupont RM, Butters N, Schafer K, Wilson T, Hesselink J,Gillin JC. Diagnostic specificity of focal white matterabnormalities in bipolar and unipolar mood disorder. BiolPsychiatry 1995;38:482–486.

14. Dupont RM, Jernigan TL, Butters N et al. Subcorticalabnormalities detected in bipolar affective disorder usingmagnetic resonance imaging. Clinical and neuropsycho-logical significance. Arch Gen Psychiatry 1990;47:55–59.

15. Figiel GS, Krishnan KR, Rao VP et al. Subcortical hyper-intensities on brain magnetic resonance imaging: a com-parison of normal and bipolar subjects. J NeuropsychiatryClin Neurosci 1991;3:18–22.

16. Altshuler LL, Curran JG, Hauser P, Mintz J, Denicoff K,Post R. T2 hyperintensities in bipolar disorder: magneticresonance imaging comparison and literature meta-analy-sis. Am J Psychiatry 1995;152:1139–1144.

17. Swayze VW 2nd, Andreasen NC, Alliger RJ, Ehrhardt JC,Yuh WT. Structural brain abnormalities in bipolar affectivedisorder. Ventricular enlargement and focal signal hyper-intensities. Arch Gen Psychiatry 1990;47:1054–1059.

18. McDonald WM, Tupler LA, Marsteller FA et al. Hyper-intense lesions on magnetic resonance images in bipolardisorder. Biol Psychiatry 1999;45:965–971.

19. Woods BT, Yurgelun-Todd D, Mikulis D, Pillay SS. Age-related MRI abnormalities in bipolar illness: a clinicalstudy. Biol Psychiatry 1995;38:846–847.

20. Aylward EH, Roberts-Twillie JV, Barta PE et al. Basalganglia volumes and white matter hyperintensities in pa-tients with bipolar disorder. Am J Psychiatry 1994;151:687–693.

21. Botteron KN, Figiel GS, Wetzel MW, Hudziak J, Van-

Eerdewegh M. MRI abnormalities in adolescent bipolaraffective disorder. J Am Acad Child Adolesc Psychiatry1992;31:258–261.

22. Botteron KN, Vannier MW, Geller B, Todd RD, Lee BCP.Preliminary study of magnetic resonance imaging (MRI)characteristics in 8- to 16- year olds with mania. J AmAcad Child Adolesc Psychiatry 1995;34:742–749.

23. Pillai JJ, Friedman L, Stuve TA et al. Increased presence ofwhite matter hyperintensities in adolescent patients withbipolar disorder. Psychiatry Res 2002;114:51–56.

24. Brown FW, Lewine RJ, Hudgins PA, Risch SC. White matterhyperintensity signals in psychiatric and nonpsychiatricsubjects. Am J Psychiatry 1992;149:620–625.

25. Krabbendam L, Honig A, Wiersma J et al. Cognitive dys-functions and white matter lesions in patients with bipolardisorder in remission. Acta Psychiatr Scand 2000;101:274–280.


489

26. Persaud R, Russow H, Harvey I et al. Focal signal hy-perintensities in schizophrenia. Schizophr Res 1997;27:55–64.

27. Sassi RB, Brambilla P, Nicoletti M et al. White matterhyperintensities in bipolar and unipolar patients with rel-atively mild-to-moderate illness severity. J Affect Disord2003;77:237–245.

28. Strakowski SM, Woods BT, Tohen M, Wilson DR, Douglass

AW, Stoll AL. MRI subcortical signal hyperintensities inmania at first hospitalization. Biol Psychiatry 1993;33:204–206.

29. Regenold WT, Hisley KC, Phatak P et al. Relationship ofcerebrospinal fluid glucose metabolites to MRI deep whitematter hyperintensities and treatment resistance in bipolardisorder patients. Bipolar Disord 2008;10:753–764.

30. Moore PB, Shepherd DJ, Eccleston D et al. Cerebral whitematter lesions in bipolar affective disorder: relationship tooutcome. Br J Psychiatry 2001;178:172–176.

31. Dupont RM, Jernigan TL, Heindel W et al. Magnetic reso-nance imaging and mood disorders. Localization of whitematter and other subcortical abnormalities. Arch GenPsychiatry 1995;52:747–755.

32. Moore PB, El-Badri SM, Cousins D et al. White matterlesions and season of birth of patients with bipolar affec-tive disorder. Am J Psychiatry 2001;158:1521–1524.

33. Pompili M, Ehrlich S, De Pisa E et al. White matter hyper-intensities and their associations with suicidality in patientswith major affective disorders. Eur Arch Psychiatry ClinNeurosci 2007;257:494–499.

34. Awad IA, Johnson PC, Spetzler RF, Hodak JA. Incidentalsubcortical lesions identified on magnetic resonanceimaging in the elderly. II. Postmortem pathological cor-relations. Stroke 1986;17:1090–1097.

35. Fazekas F, Kleinert R, Offenbacher H et al. Pathologiccorrelates of incidental MRI white matter signal hyperin-tensities. Neurology 1993;43:1683–1689.

36. Grafton ST, Sumi SM, Stimac GK, Alvord EC Jr, Shaw CM,Nochlin D. Comparison of postmortem magnetic reso-nance imaging and neuropathologic findings in the cerebralwhite matter. Arch Neurol 1991;48:293–298.

37. Gulseren S, Gurcan M, Gulseren L, Gelal F, Erola A. T2Hyperintensities in bipolar patients and their healthy sib-lings. Arch Med Res 2006;37:79–85.

38. Morice R. Cognitive inflexibility and pre-frontal dysfunc-tion in schizophrenia and mania. Br J Psychiatry 1990;157:50–54.

39. van Gorp WG, Altshuler L, Theberge DC, Wilkins J, Dixon

W. Cognitive impairment in euthymic bipolar patients withand without prior alcohol dependence. A preliminarystudy. Arch Gen Psychiatry 1998;55:41–46.

40. Thompson JM, Gallagher P, Hughes JH et al. Neurocogni-tive impairment in euthymic patients with bipolar affectivedisorder. Br J Psychiatry 2005;186:32–40.

41. Jamrozinski K, Gruber O, Kemmer C, Falkai P, Scherk H.Neurocognitive functions in euthymic bipolar patients.Acta Psychiatr Scand 2008;119:1–10.

42. Cummings JL. Frontal-subcortical circuits and humanbehavior. Arch Neurol 1993;50:873–880.

43. Adler CM, DelBello MP, Strakowski SM. Brain networkdysfunction in bipolar disorder. CNS Spectr 2006;11:312–320.

44. Briggs GG, Nebes RD. Patterns of hand preference in astudent population. Cortex 1975;11:230–238.

45. OPCS. Standard occupational classification. London:HMSO, 1991.

46. Nelson HE. National adult reading test. Windsor: NFER-Nelson, 1982.

47. First MB, Spitzer RL, Gibbon M, Williams JBW. Structuredclinical interview for DSM-IV axis I disorders, researchversion. New York: Biometrics Research, 1997.

48. Hamilton M. A rating scale for depression. J Neurol Neu-rosurg Psychiatry 1960;23:56–62.

49. Young RC, Biggs JT, Ziegler VE, Meyer DA. A rating scalefor mania: reliability, validity and sensitivity. Br J Psychi-atry 1978;133:429–435.

50. Beck AT, Ward CH, Mendelson M et al. An inventory formeasuring depression. Arch Gen Psychiatry 1961;4:561–571.

51. Altman EG, Hedeker D, Peterson JL et al. The Altman Self-Rating Mania Scale. Biol Psychiatry 1997;42:948–955.

52. Folstein MF, Folstein SE, McHugh PR. ‘‘Mini-mentalstate’’. A practical method for grading the cognitive stateof patients for the clinician. J Psychiatr Res 1975;12:189–198.

53. Babor TF, De La Fuente JR, Saunders J, Grant M. AUDIT:The alcohol use disorders identification test: Guidelines foruse in primary health care. Geneva: World Health Orga-nisation, 1992.

54. Scheltens P, Barkhof F, Leys D et al. A semiquantitativerating scale for the assessment of signal hyperintensities onmagnetic resonance imaging. J Neurol Sci 1993;114:7–12.

55. Fazekas F, Chawluk JB, Alavi A, Hurtig HI, Zimmerman RA.MR signal abnormalities at 1.5 T in Alzheimer�s dementiaand normal aging. Am J Roentgenology 1987;149:351–356.

56. Kapeller P, Barber R, Vermeulen RJ et al. Visual rating ofage-related white matter changes on magnetic resonanceimaging: scale comparison, interrater agreement, and cor-relations with quantitative measurements. Stroke 2003;34:441–445.

57. Lloyd AJ, Ferrier IN, Barber R, Gholkar A, Young AH,O�Brien JT. Hippocampal volume change in depression:late- and early-onset illness compared. Br J Psychiatry2004;184:488–495.

58. Wiseman RM, Saxby BK, Burton EJ, Barber R, Ford GA,O�Brien JT. Hippocampal atrophy, whole brain volume,and white matter lesions in older hypertensive subjects.Neurology 2004;63:1892–1897.

59. Talairach J, Tournoux P. Co-planar stereotaxic atlas of thehuman brain. Stuttgart; New York: Thieme, 1988.

60. Steffens DC, Krishnan KR. Structural neuroimaging andmood disorders: recent findings, implications for classifica-tion, and future directions. Biol Psychiatry 1998;43:705–712.

61. El-Badri SM, Cousins DA, Parker S et al. Magnetic reso-nance imaging abnormalities in young euthymic patientswith bipolar affective disorder. Br J Psychiatry 2006;189:81–82.

62. Thomas AJ, O�Brien JT, Davis S et al. Ischemic basis fordeep white matter hyperintensities in major depression: aneuropathological study. Arch Gen Psychiatry 2002;59:785–792.

63. Brody AL, Mandelkern MA, Jarvik ME et al. Differencesbetween smokers and nonsmokers in regional gray mattervolumes and densities. Biol Psychiatry 2004;55:77–84.

64. Swan GE, Lessov-Schlaggar CN. The effects of tobaccosmoke and nicotine on cognition and the brain. Neuro-psychol Rev 2007;17:259–273.

65. Harrison PJ. The neuropathology of primary mood disor-der. Brain 2002;125:1428–1449.

66. Tkachev D, Mimmack ML, Ryan MM et al. Oligodendrocytedysfunction in schizophrenia and bipolar disorder. Lancet2003;362:798–805.

67. Regenold WT, Phatak P, Marano CM, Gearhart L, Viens

CH, Hisley KC. Myelin staining of deep white matter in thedorsolateral prefrontal cortex in schizophrenia, bipolar

Lloyd et al.

490

disorder, and unipolar major depression. Psychiatry Res2007;151:179–188.

68. McDonald C, Zanelli J, Rabe-Hesketh S et al. Meta-analy-sis of magnetic resonance imaging brain morphometrystudies in bipolar disorder. Biol Psychiatry 2004;56:411–417.

69. Perneger TV. What�s wrong with Bonferroni adjustments.BMJ 1998;316:1236–1238.

70. Louis ED, Brickman AM, DeCarli C et al. Quantitativebrain measurements in community-dwelling elderly per-sons with mild Parkinsonian signs. Arch Neurol2008;65:1649–1654.


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