Neurobiological underpinnings of bipolar disorder focusing on findings of diffusion tensor imaging: a systematic review

Abstract

Objective:

To review the available data on diffusion tensor imaging (DTI) of subjects with bipolar disorder (BD), with a particular focus on fractional anisotropy (FA) in white matter (WM) tracts.

Methods:

The PubMed/MEDLINE database was searched for relevant articles, which were included in a systematic review of the literature. FA reductions and WM abnormalities were divided anatomically into three groups: commissural tracts, association tracts, and projection tracts.

Results:

Eighteen studies met the inclusion criteria. The corpus callosum was the main impaired commissural tract as demonstrated by FA reductions. Five studies reported FA reductions in the cingulum. Two studies reported decreased FA in the anterior thalamic radiation, and one in the corticospinal tract. Conversely, three studies found increased FA values in WM tracts involved in BD pathophysiology.

Conclusion:

Despite considerable heterogeneity, these results indicate a direct link between executive cognitive functioning and abnormal WM microstructural integrity of fronto-limbic tracts in patients with remitted BD, providing further evidence of the neuronal disruption that underlies BD symptomatology.

Bipolar disorder; diffusion tensor imaging; neuroimaging; diffusion tractography

Introduction

Bipolar disorder (BD) is a severe psychiatric disorder that affects approximately 1.5% of the world population¹,² and remains one of the leading worldwide causes of disability, morbidity, and mortality.³,⁴ The progression of BD is frequently associated with an increased number of episodes,⁵-⁸ subclinical symptoms in the interepisodic period,⁹,¹⁰ higher rates of comorbidities,¹¹ increased risk of suicide,¹² a higher number of hospital admissions,¹³ and poorer response to treatment.⁶ Furthermore, several studies have shown a strong association between number of mood episodes and unfavorable clinical outcomes, especially cognitive and functional impairment.¹⁴,¹⁵

In BD, neural substrate reactivity is changed by repeated mood episodes, which ultimately promote a brain rewiring that leads to increased vulnerability to life stress.¹⁶ -¹⁸ Changes in brain structure have been widely reported in BD patients.¹⁹ Over the past decade, substantial effort has been made in neuroimaging research to understand the neural system abnormalities that underlie BD, and significant progress has been made in identifying regional brain differences that could contribute to the symptoms of acute episodes.²⁰

Morphometric studies have demonstrated that patients with BD exhibit enlargement of the third and lateral ventricles; a reduction in the gray matter volumes of the orbital and medial prefrontal cortex, ventral striatum, and mesotemporal cortex; and enlargement of the amygdala. Such neuroanatomical changes tend to be more pronounced in patients who have experienced repeated episodes. With respect to neuropathological findings, recent data suggest that changes in neuroplasticity, particularly in cell resilience and connectivity, are the main findings associated with BD.²¹ -²⁵

Other studies suggest that structural brain changes are found mainly in the frontal, temporal, and limbic white matter (WM) regions.²⁶ -³¹ WM abnormalities have been widely detected in subjects with the pathophysiological features of BD, especially with diffusion tensor imaging (DTI) techniques.²⁹

Diffusion imaging principles are based on measurement of the motion of water molecules within tissues.³² Free water usually moves equally in all directions in an isotropic fashion. When the movement of water molecules is restricted, however, preferential directions are taken, and movement consequently becomes anisotropic. Therefore, water mobility in the brain is markedly reduced in compact tissue, such as WM, is reduced to a lesser extent in gray matter (GM), and is almost free in the cerebrospinal fluid (CSF). Pathological processes that alter the normal brain structure may affect water motion and thereby affect the resulting diffusion indexes.³³

Diffusion images can be acquired from a minimum of three gradient directions that yield two different types of sequences: diffusion-weighted imaging (DWI) and DTI. The use of more than six encoding directions improves the accuracy of tensor measurement for any arbitrary orientation (Figure 1).³⁴

Figure 1
Diffusion measurements along multiple axes. The shape and the orientation of a diffusion ellipsoid is estimated. From the estimated ellipsoid (A), the orientation of the longest axis can be found (B), which is assumed to represent the local fiber orientation. This orientation information is converted to a color at each pixel. By combining the intensity of the anisotropy map and color, a color-coded orientation map is created (C). The diffusion tensor image map is rendered in the axial (D), coronal (E), and sagittal (F) planes. The color coding depicts the local fiber orientation, i.e., the principal eigenvector of the diffusion tensor, with red indicating mediolateral, green denoting anteroposterior, and blue representing superoinferior. Color coding is also indicated by the red-green-blue sphere (C).

WM tracts can be divided anatomically into three groups: commissural tracts, projection tracts, and association tracts. Commissural tracts are fibers that interconnect the hemispheres of the brain, such as the corpus callosum (CC). Association tracts are groups of fibers that interconnect cortical areas within the same hemisphere, and projection tracts are efferent and afferent fibers that interconnect the cortex to subcortical structures.³⁵ -³⁸

Previous investigations have hypothesized that microstructural changes in the WM of frontal-subcortical circuits leads to a disconnection syndrome between the frontal and subcortical regions.³⁰ These network alterations have been associated with clinical symptoms of BD, which suggests that DTI is a promising technique for evaluation of the underpinnings of neuropathology in BD.³⁹

The aim of this paper is to conduct a systematic review of studies that have used DTI in patients with BD, with particular emphasis on fractional anisotropy (FA) findings, and discuss the relevance and connection of these findings to BD pathophysiology.

Methods

Systematic review

The recorded variables for each article included imaging technique (magnetic resonance imaging [MRI], DTI), imaging analysis (whole-brain/region of interest [ROI]), field strength, gender, mean age, exposure to medication, brain regions analyzed, and principal findings (BD vs. controls).

Selection procedures

The inclusion criteria were: a) English-language original articles published in peer-reviewed journals, in which study participants were diagnosed with BD type I (BD-I) or BD type II (BD-II), and which employed structural or neurochemical imaging techniques. Studies were independently assessed for eligibility by two researchers.

Search strategies

The PubMed/MEDLINE database was searched using the following queries based on Medical Subject Headings (MeSH) descriptors: “imaging, diffusion tensor and bipolar disorder,” “diffusion tractography and bipolar disorder,” and “tractography, diffusion and bipolar disorder.” There were no limits regarding year of publication, and the search included papers published through January 2015.

Results

The search yielded 127 articles. Search strategies and exclusion criteria are summarized in Figure 2. We found 18 published DTI studies that identified WM changes in subjects with BD. We assessed FA in three different anatomical groups: commissural tracts, projection tracts, and association tracts. Tracts for which FA findings were reported in the included studies are presented in Figure 3.

Figure 2
Flowchart of identification and selection of studies for a systematic review of diffusion tensor imaging in bipolar disorder.

Figure 3
White matter tract reconstruction based on reported findings of decreased fractional anisotropy on diffusion tensor imaging: uncinate fasciculus,⁴⁰-⁴² corpus callosum/forceps,²⁹,³¹,⁴⁰,⁴³-⁴⁸ cingulum,²⁹,⁴³,⁴⁵,⁴⁸,⁴⁹ anterior thalamic radiation,³¹,⁴² superior longitudinal fasciculus,²⁹,³¹,⁴⁰,⁴³,⁵⁰ inferior longitudinal fasciculus,⁴⁰,⁴³,⁵⁰,⁵¹ corticospinal tract.⁵²

Results are highly heterogeneous, and most published papers have reported decreased FA values in WM tracts (Table 1). Overall, the most common finding is decreased FA values in commissural and association tracts, particularly in the fronto-limbic tracts (Table 2).⁴³,⁵³,⁵⁴

Table 1
Diffusion tensor imaging studies in bipolar disorder

Study	Patients	Age	BD type I/II/ other	Disease duration (years)	Mood state	Substance use	Drugs	Tesla | direction	B-value	Software	Voxel size (mm3)	Measures	Results
Maller43	31 BD31 HC	43.29±9.1339.58±10.7	16/15/0	N/A	N/A	N/A	7 drug users (6.288) with BD-I/10 (5.738) with BD-II	1.5 | 12	0/1,000	FMRI Diffusion toolbox/TBSS	0.9x0.9x3	FA, AD, RD	Widespread, significant FA differences between controls and all BD subjects, primarily along the CC, cingulum bundles, fornices, SLF, ILF/FOFs, thalami, and UF. Significant differences in FA and all its constituent values between controls and BD-I and BD-II subjects separately.
Oertel-Knöchel31	21 BD20 HC	35.67±10.636.90±11.0	21/0/0	7.62	Euthymic	N/A	Mood stabilizers (n=21), antidepressants (n=9), neuroleptics (n=12), anxiolytics (n=3)	3 | 60	0/1,000	TBSS FSL 4.1	3x3x3	FA, MD, RD, AD	Patients with BD showed significantly higher MD, RD, and AD scores in comparison with HCs in the left superior longitudinal fascicle. FA scores were not significantly different between groups.
Sarrazin29	118 BD86 HC	36.32±10.437.26±11.2	118/0/0	15.57	Euthymic	25 alcohol	Lithium (n=39), other mood stabilizers (n=64), antipsychotics (n=52), antidepressants (n=54)	3 | 41	0 /1,000	Connectomist 2.0 and BrainVisa 4.2	2x2x2	GFA	Compared with controls, BD-I patients had significant reductions in mean GFA values along the body and splenium of the CC, the left cingulum, and the anterior part of the left arcuate fasciculus when controlling for age, gender, and acquisition site. Patients with a history of psychotic features had a lower mean GFA value along the body of the CC than those without such a history.
Oertel-Knöchel30	30 BD 32 HC	39.22±12.339.22±10.3	30/0/0	10.2	Euthymic	N/A	8.30 (7.40) years of medication use	3 | 60	0/1,000	FMRIB/MRIST/TBSS	1x1x1	AD, RD, FA, MD	Significantly lower FA values in BD patients than in controls. The CC tended to show lower FA and higher RD in BD patients compared with controls. The splenium and truncus showed significantly lower FA and the truncus showed higher RD in BD patients compared with controls. FA values were significantly reduced in BD patients in the right thalamic radiation and showed trend-level significance in the left ATR.
Canales-Rodríguez44	40 BD 40 HC	40.6±8.940.4±9.3	40/0/0	15.9	Euthymic	Excluded	39 mood stabilizers (n=39) or lithium alone in combination with others (n=30), valproate (n=2), lamotrigine (n=2), others (n=5); antidepressants (n=9). antipsychotics (n=22), combination (n=1)	1.5 | 55	0/1,500	Brain Extraction Tool (FSL)	2x2x3	FA, MD, PTO, GFA	Significant reductions in FA were observed in the splenium of CC and right insula. There was a widespread pattern of increased MD in gray and WM tissues including anterior cingulum, left insula, and subcortical nuclei, without significant decreases in BD patients. Three of the contrasts (FA, mean diffusivity, and GFA) revealed abnormalities in subcortical structures, including the hippocampus, thalamus, and caudate nucleus.
Ambrosi40	20 BD21 HC	41.95±13.134.61±10.8	0/20/0	12.6	Euthymic	Excluded	19 lithium (n=7), anticonvulsants (n=10), antidepressants (n=8), antipsychotics (n=10)	1.5 | 12	N/A	FSL/FMRIB/TBSS	N/A	FA	Significant, widespread FA reduction in patients with BD-II compared with controls in all major WM tracts studied, including cortico-cortical association tracts, i.e., uncinate, inferior fronto-occipital, inferior longitudinal, and superior longitudinal fasciculi, interhemispheric tracts, as well as limbic tracts and parahippocampal tract.
Emsell45	35 BD43 HC	44±1042±10	35/0/0	12	Euthymic	7 alcohol users	10 (7) years’ lithium use	1.5 | 64	0/1,300	Explore DTI	2.5x2.5x2.5	FA, MD, AD, RD	Significant differences between patients and control subjects in FA, MD, and RD in the CC. In the fornix, significant differences were found in MD, AD, and RD. In all cases, anisotropy decreased and diffusivity increased in patients compared with controls.
Leow46	25 BD24 HC	41.6±12.741.6±10.6	25/0/0	20.8	Euthymic	N/A	Valproic acid (n=7), carbamazepine (n=1), lamotrigine (n=3), antipsychotic (n=14), SSRI (n=8), antidepressants (n=5), benzodiazepines (n=3)	3 | 64	0/1,000	DTI Studio	1x1x1	FA, MD	Statistically significant group differences in FA, in including the genu, body, and splenium of CC. There was no significant between-group difference in MD for any WM structure, as the genu exhibited higher MD values in the bipolar group.
Torgerson52	27 BD26 HC	44.2±12.9 41.5±12.1	27/0/0	23.2	Euthymic	13 alcohol users, 7 drug abusers	Antipsychotics (n=16), anticonvulsants (n=15), antidepressants (n=14), benzodiazepines (n=5)	3 | 64	0/1,000	TrackVis	2x2x2	FA	No differences in fiber FA between BD subjects and healthy controls, except for reduced FA in one of the corticospinal tracts (CST-R2).
Benedetti49	40 BD 21 HC	47.79±13.2 39.86±11.0	40/0/0	13.54	Euthymic	Excluded	Lithium (n=14)	3 | N/A	0/900	TBSS	1.88x1.87x2.3	MD, FA, DI, RD	Compared with control subjects, patients showed lower FA in the genu of the CC and in the anterior and right superior-posterior corona radiata. Higher radial diffusivity values were found in WM tracts of the splenium, genu and body of CC, right mid-dorsal part of the cingulum bundle, left anterior and bilateral superior and posterior corona radiata, bilateral SLF, and right posterior thalamic radiation.
Wessa55	22 BD 21 HC	45.41±12.6 42.95±13.1	14/08/2	22	Euthymic	Excluded	Lithium (n=10), anticonvulsants (n=11), atypical antipsychotics (n=5)	1.5 | 41	0/700	BrainVisa 3/TBSS	1.88x1.87x2.3	MD, FA	FA was significantly increased in BD patients relative to healthy controls in medial frontal, precentral, inferior parietal, and occipital WM. No group differences in mean diffusivity were found.
Wang41	33 BD 31 HC	30.4±10.8 31.8±9.6	33/0/0	N/A	10 manic/hypomanic, depression, 16 euthymic	17 (13 alcohol and/or nine other substances, four other substances)	Lithium (n=9), anticonvulsants (n=16), antipsychotics (n=14), antidepressants (n=12), benzodiazepines (n=7)	3 | 32	0 /1,000	WFU Pick Atlas tool	1.5x1.5x1.5	FA	An association was found between pACC-amygdala functional connectivity measurements and the structural integrity of ventro-frontal WM, including the UF, where FA was significantly decreased in the BD group.
Zanetti50	37 BD 26 HC	34.1±9.1 28.8±9.5	37/0/0	11.6	16 depressed/21 remission	Excluded	Depression: lithium (n=6), valproate (n=6), lamotrigine (n=5), antipsychotics (n=8), antidepressants (n=7), benzodiazepines (n=6). Remission: lithium (n=6), valproate (n=2), carbamazepine (n=3), antipsychotics (n=11), antidepressants (n=9), benzodiazepine (n=4)	3 | 6	0/850	BioImage Suite 2.0	1.6x1.6x3	FA, MD	Significantly decreased FA and increased MD in bilateral prefronto-limbic-striatal WM and right inferior fronto-occipital, superior, and inferior longitudinal fasciculi were found in all BD-I patients vs controls and in depressed BD-I patients compared both to controls and to remitted BD-I patients. These findings suggest that depression in BD-I may be associated with acute microstructural WM changes.
Mahon56	30 BD 38 HC	33.4±8.7 31.9±8.6	25/2/3	N/A	N/A	11 alcohol or other substances	All treated with antidepressants and/or mood stabilizers	1.5 | 25	0/1,000	DTI Studio	N/A	AD, RD, FA	Voxelwise analysis of WM revealed three regions with higher FA in the right and left frontal WM and one region of lower FA in the left cerebellum in BD patients compared to healthy volunteers. These findings suggest that, compared to healthy volunteers, adult patients with BD have higher FA in the bilateral frontal WM, corresponding approximately to fibers of the corticopontine/corticospinal tract and SLF, as well as superior thalamic radiation fibers. In addition, FA was lower in the left cerebellar WM, thus corresponding approximately to the pontine crossing tract, in patients compared to healthy volunteers.
Versace42	21 BD 25 HC	35.9±8.9 29.48±9.4	31/0/0	12.29 depressed/11.82 remitted	14 depressed/17 remitted	10 alcohol or other substances	All medicated	3 | N/A	0/850	FSL/TBSS	N/A	N/A	Subjects with BD had significantly greater FA in the left UF (reduced radial diffusivity distally and increased longitudinal diffusivity centrally), left optic radiation (increased longitudinal diffusivity), and right ATR (no significant diffusivity change), as well as significantly reduced FA in the right UF (greater radial diffusivity), vs. controls. Decreased FA was observed in the left optic radiation and in the right ATR among subjects with BD taking mood stabilizers vs. those with BD not taking mood stabilizers, as well as in the left optic radiation among depressed vs. remitted subjects with BD.
Wang48	BD 42 HC 42	32.6±10.1 28.7±9.1	42/0/0	N/A	11 manic/hypomanic, 9 depressed, 22 euthymic	N/A	Lithium (n=11), anticonvulsants (n=20), antipsychotics (n=19), antidepressants (n=17), benzodiazepines (n=8), levothyroxine sodium (n=5)	3 | 32	0/1,000	BioImage Suite	N/A	FA	FA was significantly decreased in the anterior cingulum in the BD group compared with healthy controls; however, FA in the posterior cingulum did not differ significantly between groups.
Wang48	BD 33 HC 40	32±10.1 29.2±9.2	33/0/0	N/A	7 manic/hypomanic, 7 depressed, 19 euthymic	11 alcohol, 6 substance abuse, 3 other substances	No medication (n=6), lithium (n=8), anticonvulsants (n=17), atypical antipsychotics (n=17), benzodiazepines (n=8)	3 | 32	0/1,000	BioImage Suite	N/A	FA	Using complementary ROI- and voxel-based DTI methods, the authors found decreased FA values in participants with BD compared to HCs in the anterior and middle CC subregions encompassing the genu, rostral body, and anterior portion of the mid-body.
Bruno51	BD 36 HC 28	39	25/11/0	13.8	N/A	N/A	Lithium (n=23), sodium valproate (n=3), carbamazepine (n=4), lamotrigine (n=3), neuroleptic (n=9)	1.5 | 7	0/700	SPM2	N/A	MD, FA	In the patient group, mean diffusivity was increased in the right posterior frontal and bilateral prefrontal WM, while FA was increased in the inferior, middle temporal, and middle occipital regions.

• AD = axial diffusivity; ATR = anterior thalamic radiation; BD = bipolar disorder; BD-I = bipolar I disorder; BD-II = bipolar II disorder; CC = corpus callosum; FA = fractional anisotropy; FMRI = functional magnetic resonance imaging; FOFs = fronto-occipital fasciculi; GFA = generalized fractional anisotropy; HC = healthy controls; ILF = inferior longitudinal fasciculi; MD = mean diffusivity; N/A = not mentioned in text; PTO = probability of return to the origin; RD = radial diffusivity; ROI = region of interest; SLF = superior longitudinal fasciculi; SPM = statistical parametric mapping; SSRI = selective serotonin reuptake inhibitors; TBSS = tract-based spatial statistics; UF = uncinate fasciculus; WFU = Wake Forest University School of Medicine PickAtlas; WM = white matter.

Table 2
White matter tracts with decreased fractional anisotropy values on diffusion tensor imaging studies

White matter tracts/studies	Main results
Commissural tracts
Maller43	Corpus callosum, fornix
Sarrazin29	Corpus callosum
Oertel-Knöchel31	Corpus callosum, fornix
Emsell45	Corpus callosum
Leow46	Corpus callosum
Canales-Rodríguez44	Corpus callosum
Ambrosi40	Interhemispheric tracts
Benedetti49	Corpus callosum
Wang48	Corpus callosum
Association tracts
Maller43	Cingulum bundles, superior longitudinal fasciculi, inferior longitudinal fasciculi, fronto-occipital fasciculi, uncinate fasciculi
Sarrazin29	Cingulum, arcuate fasciculus
Emsell45	Cingulum
Ambrosi40	Uncinate, inferior fronto-occipital, inferior longitudinal, superior longitudinal fasciculi
Canales-Rodríguez44	Cingulum bundle, superior fronto-occipital fasciculus
Zanetti50	Prefrontal-limbic-striatal white matter, inferior fronto-occipital, inferior longitudinal, superior longitudinal fasciculi
Versace42	Uncinate fasciculus
Wang48	Cingulum
Bruno51	Inferior longitudinal fasciculus
Projection tracts
Maller43	Thalami (not specified)
Canales-Rodríguez44	Corona radiata
Benedetti49	Corona radiata
Versace42	Optic radiation, anterior thalamic radiation
Oertel-Knöchel31	Right thalamic radiation
Other tracts
Torgerson52	Corticospinal tract

FA and WM tracts

With respect to the commissural tracts, most authors found decreased FA values in the CC.²⁹-³¹,⁴⁰,⁴³-⁴⁶,⁴⁹

Regarding association tracts, five studies found decreased FA values in the cingulum.²⁹,⁴³,⁴⁵,⁴⁸,⁴⁹ With respect to the projection tracts, two studies noted decreased FA in the ATR, and one study found decreased FA in the corticospinal tract (CST) (Table 2).

Conversely, three studies reported increased FA values. Wessa et al.⁵⁵ found increased FA values in the medial frontal, precentral, inferior parietal, and occipital WM. Mahon et al.⁵⁶ observed higher FA levels within the right and left frontal WM, while Versace et al.⁴² observed increased FA in the left uncinate fasciculus (UF) (reduced radial diffusivity distally and increased longitudinal diffusivity centrally), left optic radiation (increased longitudinal diffusivity), and right anterior thalamic radiation (ATR).

Discussion

Most studies reported decreased FA values in regions involved in emotion processing, such as the commissural tracts, especially the CC, and the association tracts.⁴³,⁵³,⁵⁴,⁵⁷ -⁶⁰ The latter include the UF,⁴⁷,⁶¹-⁶³ the ATR,⁶²,⁶³ and the cingulum.⁴⁵,⁶¹

The findings of decreased FA values are consistent with the description of BD as a disconnection syndrome.⁶⁴,⁶⁵ The two major symptom domains in BD are mood instability and poor cognitive control over executive functions.⁵⁷ Historically, the aforementioned regions have been found to be involved in emotional processing. In 1937, Papez⁶⁶ proposed that emotion regulation is enabled through rich reciprocal connections between parts of the prefrontal cortex with the amygdala, anterior temporal regions, subgenual anterior cingulate cortex, striatum, and thalamus.

Contrary to the predominant findings, Wessa et al.,⁵⁵ Mahon et al.,⁵⁶ and Versace et al.⁴² found increased FA values in different WM tracts. Despite a lack of support in the literature, a number of variables may explain these results. For example, most of these studies were performed before 2009 and used either fewer DTI directions or older versions of reconstruction software, or involved patient selection bias.

The main region exhibiting decreased FA values was the CC, the major interhemispheric WM connection that integrates emotional, cognitive, motor, and sensory information. The anterior CC regions integrate all right and left prefrontal cortex, anterior cingulate, and insula regions implicated in emotional deregulation, a core symptom of BD.

With respect to the association tracts, several studies have reported impairment in WM connection in patients with BD, with most indicating impairment in the cingulum²⁹,⁴³-⁴⁵,⁴⁸ and the UF.⁴⁰,⁴²,⁴³ The cingulum is a complex fiber system that forms a central component of the entire limbic network where the UF carries association fibers between the medial prefrontal cortex and the anterior temporal lobe, including the amygdala. These regions have been extensively related to the pathophysiology of BD.⁶⁷ -⁶⁹

In projection fibers, three studies described decreased FA values in the ATR. The ATR connects the dorsomedial and anterior thalamic nuclei with the prefrontal cortex, and the anterior part of the ATR is connected with the hippocampus through the fornix. Alterations in the connections between the thalamus and limbic areas may be relevant to cognitive processing and to clinical symptoms observed in patients with BD.⁴⁹,⁷⁰ Alterations in ATR fiber integrity have been previously reported in BD patients, consistent with functional magnetic resonance imaging (fMRI) and structural findings.¹⁹

Certain important pathways could also be related to the pathophysiology of BD. The fornix is a projection tract that is located underneath the CC and connects the hippocampus with the mammillary body as well as with other cortical and subcortical structures.³⁰ Both structures are part of the limbic system and known to be involved in memory processes. The lack of previous reports regarding fornix alterations in BD may be due to the anatomic characteristics of the fornix and to the spatial resolution of current MRI methods.⁴⁹

Previous investigations have hypothesized that microstructural changes in the WM of the frontal-subcortical circuits lead to a disconnection syndrome between the frontal and subcortical regions.³⁹ These results suggest a direct link between executive cognitive functioning and abnormal WM microstructural integrity of the fronto-limbic tracts in remitted BD patients, and provide further evidence of the neuronal disruption that underlies the residual symptomatology of BD.

It is not clear whether number of episodes, duration of illness, and other clinical progression characteristics are associated with decreased FA values. However, BD has a poorer long-term outcome than previously thought, with persistent cognitive impairment and functional decline.⁷¹,⁷² Cognitive impairment has been found to affect executive functions predominantly, while moderate cognitive deficits have been observed in other cognitive tests, such as verbal memory, response inhibition, sustained attention, psychomotor speed, abstraction, and set-shifting.⁷³ These cognitive impairment domains seem to have a close correlation with WM and brain connectivity deterioration.⁷⁴ -⁷⁶

Recently, a neuroinflammatory component has been implicated in the pathophysiology of certain psychiatric disorders,⁷⁷ and offers a plausible explanation as to why WM lesions are present in patients with BD.⁷⁸ Of note, WM is particularly vulnerable to the inflammatory neurotoxic effects of BD.⁷⁹ The cognitive decline that occurs over the course of the disease seems to be associated, at least in part, with vulnerability to the toxic effects of inflammation.⁷⁹ Additionally, immune disturbances have been linked to BD and symptom severity, mood episodes, staging, effect of medications, metabolic disturbances, neurotrophin alterations, and increased frequency of comorbid autoimmune and allergic disorders.⁸⁰ In this context, DTI findings could provide a better understanding of the neurobiological underpinnings of pathophysiology in BD.

References

• ¹
  Angst J. The emerging epidemiology of hypomania and bipolar II disorder. J Affect Disord. 1998;50:143-51.
• ²
  Narrow WE, Rae DS, Robins LN, Regier DA. Revised prevalence estimates of mental disorders in the United States: using a clinical significance criterion to reconcile 2 surveys' estimates. Arch Gen Psychiatry. 2002;59:115-23.
• ³
  Goodwin FK, Jamison KR, Ghaemi SN. Manic-depressive illness: bipolar disorders and recurrent depression. New York: Oxford University Press; 2007.
• ⁴
  Murray CJ, Lopez AD. Evidence-based health policy—lessons from the Global Burden of Disease Study. Science. 1996;274:740-3.
• ⁵
  Ketter TA, Houston JP, Adams DH, Risser RC, Meyers AL, Williamson DJ, et al. Differential efficacy of olanzapine and lithium in preventing manic or mixed recurrence in patients with bipolar I disorder based on number of previous manic or mixed episodes. J Clin Psychiatry. 2006;67:95-101.
• ⁶
  Swann AC, Bowden CL, Calabrese JR, Dilsaver SC, Morris DD. Differential effect of number of previous episodes of affective disorder on response to lithium or divalproex in acute mania. Am J Psychiatry. 1999;156:1264-6.
• ⁷
  Scott J, Paykel E, Morriss R, Bentall R, Kinderman P, Johnson T, et al. Cognitive-behavioural therapy for severe and recurrent bipolar disorders: randomised controlled trial. Br J Psychiatry. 2006;188:313-20.
• ⁸
  Kapczinski F, Magalhães PV, Balanzá-Martinez V, Dias VV, Frangou S, Gama CS, et al. Staging systems in bipolar disorder: an International Society for Bipolar Disorders Task Force Report. Acta Psychiatr Scand. 2014;130:354-63.
• ⁹
  Altshuler LL, Post RM, Black DO, Keck PE Jr, Nolen WA, Frye MA, et al. Subsyndromal depressive symptoms are associated with functional impairment in patients with bipolar disorder: results of a large, multisite study. J Clin Psychiatry. 2006;67:1551-60.
• ¹⁰
  Judd LL, Schettler PJ, Solomon DA, Maser JD, Coryell W, Endicott J, et al. Psychosocial disability and work role function compared across the long-term course of bipolar I, bipolar II and unipolar major depressive disorders. J Affect Disord. 2008;108:49-58.
• ¹¹
  Matza LS, Rajagopalan KS, Thompson CL, de Lissovoy G. Misdiagnosed patients with bipolar disorder: comorbidities, treatment patterns, and direct treatment costs. J Clin Psychiatry. 2005;66:1432-40.
• ¹²
  Hawton K, Sutton L, Haw C, Sinclair J, Harriss L. Suicide and attempted suicide in bipolar disorder: a systematic review of risk factors. J Clin Psychiatry. 2005;66:693-704.
• ¹³
  Goldberg JF, Ernst CL. Features associated with the delayed initiation of mood stabilizers at illness onset in bipolar disorder. J Clin Psychiatry. 2002;63:985-91.
• ¹⁴
  Martinez-Aran A, Vieta E, Torrent C, Sanchez-Moreno J, Goikolea JM, Salamero M, et al. Functional outcome in bipolar disorder: the role of clinical and cognitive factors. Bipolar Disord. 2007;9:103-13.
• ¹⁵
  Hayes JF, Miles J, Walters K, King M, Osborn DP. A systematic review and meta-analysis of premature mortality in bipolar affective disorder. Acta Psychiatr Scand. 2015;131:417-25.
• ¹⁶
  Kapczinski F, Vieta E, Andreazza AC, Frey BN, Gomes FA, Tramontina J, et al. Allostatic load in bipolar disorder: implications for pathophysiology and treatment. Neurosci Biobehav Rev. 2008;32:675-92.
• ¹⁷
  Vieta E, Popovic D, Rosa AR, Solé B, Grande I, Frey BN, et al. The clinical implications of cognitive impairment and allostatic load in bipolar disorder. Eur Psychiatry. 2013;28:21-9.
• ¹⁸
  Grande I, Magalhães PV, Kunz M, Vieta E, Kapczinski F. Mediators of allostasis and systemic toxicity in bipolar disorder. Physiol Behav. 2012;106:46-50.
• ¹⁹
  Strakowski SM, Adler CM, Almeida J, Altshuler LL, Blumberg HP, Chang KD, et al. The functional neuroanatomy of bipolar disorder: a consensus model. Bipolar Disord. 2012;14:313-25.
• ²⁰
  Womer FY, Kalmar JH, Wang F, Blumberg HP. A ventral prefrontal-amygdala neural system in bipolar disorder: a view from neuroimaging research. Acta Neuropsychiatr. 2009;21:228-38.
• ²¹
  Gama CS, Kunz M, Magalhães PV, Kapczinski F. Staging and neuroprogression in bipolar disorder: a systematic review of the literature. Rev Bras Psiquiatr. 2013;35:70-4.
• ²²
  Hoge EA, Friedman L, Schulz SC. Meta-analysis of brain size in bipolar disorder. Schizophr Res. 1999;37:177-81.
• ²³
  Vita A, De Peri L, Sacchetti E. Gray matter, white matter, brain, and intracranial volumes in first-episode bipolar disorder: a meta-analysis of magnetic resonance imaging studies. Bipolar Disord. 2009;11:807-14.
• ²⁴
  Hajek T, Kopecek M, Kozeny J, Gunde E, Alda M, Höschl C. Amygdala volumes in mood disorders--meta-analysis of magnetic resonance volumetry studies. J Affect Disord. 2009;115:395-410.
• ²⁵
  Pfaffenseller B, Gama CS, Kapczinski F, Duarte JA, Kunz M. Anatomical faces of neuroprogression in bipolar disorder. Neuropsychiatry 2012;2:279-80.
• ²⁶
  Haller S, Xekardaki A, Delaloye C, Canuto A, Lövblad KO, Gold G, et al. Combined analysis of grey matter voxel-based morphometry and white matter tract-based spatial statistics in late-life bipolar disorder. J Psychiatry Neurosci. 2011;36:391-401.
• ²⁷
  Ellison-Wright I, Bullmore E. Anatomy of bipolar disorder and schizophrenia: a meta-analysis. Schizophr Res. 2010;117:1-12.
• ²⁸
  Selvaraj S, Arnone D, Job D, Stanfield A, Farrow TF, Nugent AC, et al. Grey matter differences in bipolar disorder: a meta-analysis of voxel-based morphometry studies. Bipolar Disord. 2012;14:135-45.
• ²⁹
  Sarrazin S, Poupon C, Linke J, Wessa M, Phillips M, Delavest M, et al. A multicenter tractography study of deep white matter tracts in bipolar I disorder: psychotic features and interhemispheric disconnectivity. JAMA Psychiatry. 2014;71:388-96.
• ³⁰
  Oertel-Knöchel V, Reinke B, Alves G, Jurcoane A, Wenzler S, Prvulovic D, et al. Frontal white matter alterations are associated with executive cognitive function in euthymic bipolar patients. J Affect Disord. 2014;155:223-33.
• ³¹
  Oertel-Knöchel V, Reinke B, Feddern R, Knake A, Knöchel C, Prvulovic D, et al. Episodic memory impairments in bipolar disorder are associated with functional and structural brain changes. Bipolar Disord. 2014;16:830-45.
• ³²
  Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology. 1986;161:401-7.
• ³³
  Sbardella E, Tona F, Petsas N, Pantano P. DTI measurements in multiple sclerosis: evaluation of brain damage and clinical implications. Mult Scler Int. 2013;2013:671730.
• ³⁴
  Jellison BJ, Field AS, Medow J, Lazar M, Salamat MS, Alexander AL. Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. AJNR Am J Neuroradiol. 2004;25:356-69.
• ³⁵
  Standring S. Gray's anatomy: the anatomical basis of clinical practice. 40th ed. Hardcover: Elsevier; 2008.
• ³⁶
  Faria AV, Oishi K, Mori S. Study of white matter anatomy and 3D tract reconstruction by diffusion tensor imaging. Int J Imaging Syst Technol. 2010;20:51-6.
• ³⁷
  Gray H. Anatomy: descriptive and surgical. London: JW Parker; 1858.
• ³⁸
  Moore KL, Dalley A, Agur A. Clinically oriented anatomy. 7th ed. Baltimore: Lippincott Williams & Wilkins; 2014.
• ³⁹
  Schneider MR, DelBello MP, McNamara RK, Strakowski SM, Adler CM. Neuroprogression in bipolar disorder. Bipolar Disord. 2012;14:356-74.
• ⁴⁰
  Ambrosi E, Rossi-Espagnet MC, Kotzalidis GD, Comparelli A, Del Casale A, Carducci F, et al. Structural brain alterations in bipolar disorder II: a combined voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) study. J Affect Disord. 2013;150:610-5.
• ⁴¹
  Wang F, Kalmar JH, He Y, Jackowski M, Chepenik LG, Edmiston EE, et al. Functional and structural connectivity between the perigenual anterior cingulate and amygdala in bipolar disorder. Biol Psychiatry. 2009;66:516-21.
• ⁴²
  Versace A, Almeida JR, Hassel S, Walsh ND, Novelli M, Klein CR, et al. Elevated left and reduced right orbitomedial prefrontal fractional anisotropy in adults with bipolar disorder revealed by tract-based spatial statistics. Arch Gen Psychiatry. 2008;65:1041-52.
• ⁴³
  Maller JJ, Thaveenthiran P, Thomson RH, McQueen S, Fitzgerald PB. Volumetric, cortical thickness and white matter integrity alterations in bipolar disorder type I and II. J Affect Disord. 2014;169:118-27.
• ⁴⁴
  Canales-Rodríguez EJ, Pomarol-Clotet E, Radua J, Sarró S, Alonso-Lana S, Del Mar Bonnín C, et al. Structural abnormalities in bipolar euthymia: a multicontrast molecular diffusion imaging study. Biol Psychiatry. 2014;76:239-48.
• ⁴⁵
  Emsell L, Leemans A, Langan C, Van Hecke W, Barker GJ, McCarthy P, et al. Limbic and callosal white matter changes in euthymic bipolar I disorder: an advanced diffusion magnetic resonance imaging tractography study. Biol Psychiatry. 2013;73:194-201.
• ⁴⁶
  Leow A, Ajilore O, Zhan L, Arienzo D, GadElkarim J, Zhang A, et al. Impaired inter-hemispheric integration in bipolar disorder revealed with brain network analyses. Biol Psychiatry. 2013;73:183-93.
• ⁴⁷
  Benedetti F, Absinta M, Rocca MA, Radaelli D, Poletti S, Bernasconi A, et al. Tract-specific white matter structural disruption in patients with bipolar disorder. Bipolar Disord. 2011;13:414-24.
• ⁴⁸
  Wang F, Jackowski M, Kalmar JH, Chepenik LG, Tie K, Qiu M, et al. Abnormal anterior cingulum integrity in bipolar disorder determined through diffusion tensor imaging. Br J Psychiatry. 2008;193:126-9.
• ⁴⁹
  Benedetti F, Yeh PH, Bellani M, Radaelli D, Nicoletti MA, Poletti S, et al. Disruption of white matter integrity in bipolar depression as a possible structural marker of illness. Biol Psychiatry. 2011;69:309-17.
• ⁵⁰
  Zanetti MV, Jackowski MP, Versace A, Almeida JR, Hassel S, Duran FL, et al. State-dependent microstructural white matter changes in bipolar I depression. Eur Arch Psychiatry Clin Neurosci. 2009;259:316-28.
• ⁵¹
  Bruno S, Cercignani M, Ron MA. White matter abnormalities in bipolar disorder: a voxel-based diffusion tensor imaging study. Bipolar Disord. 2008;10:460-8.
• ⁵²
  Torgerson CM, Irimia A, Leow AD, Bartzokis G, Moody TD, Jennings RG, et al. DTI tractography and white matter fiber tract characteristics in euthymic bipolar I patients and healthy control subjects. Brain Imaging Behav. 2013;7:129-39.
• ⁵³
  Liu JX, Chen YS, Hsieh JC, Su TP, Yeh TC, Chen LF. Differences in white matter abnormalities between bipolar I and II disorders. J Affect Disord. 2010;127:309-15.
• ⁵⁴
  Caseras X, Lawrence NS, Murphy K, Wise RG, Phillips ML. Ventral striatum activity in response to reward: differences between bipolar I and II disorders. Am J Psychiatry. 2013;170:533-41.
• ⁵⁵
  Wessa M, Houenou J, Leboyer M, Chanraud S, Poupon C, Martinot JL, et al. Microstructural white matter changes in euthymic bipolar patients: a whole-brain diffusion tensor imaging study. Bipolar Disord. 2009;11:504-14.
• ⁵⁶
  Mahon K, Wu J, Malhotra AK, Burdick KE, DeRosse P, Ardekani BA, et al. A voxel-based diffusion tensor imaging study of white matter in bipolar disorder. Neuropsychopharmacology. 2009;34:1590-600.
• ⁵⁷
  Agarwal N, Port JD, Bazzocchi M, Renshaw PF. Update on the use of MR for assessment and diagnosis of psychiatric diseases. Radiology. 2010;255:23-41.
• ⁵⁸
  Adler CM, Holland SK, Schmithorst V, Wilke M, Weiss KL, Pan H, et al. Abnormal frontal white matter tracts in bipolar disorder: a diffusion tensor imaging study. Bipolar Disord. 2004;6:197-203.
• ⁵⁹
  Haznedar MM, Roversi F, Pallanti S, Baldini-Rossi N, Schnur DB, Licalzi EM, et al. Fronto-thalamo-striatal gray and white matter volumes and anisotropy of their connections in bipolar spectrum illnesses. Biol Psychiatry. 2005;57:733-42.
• ⁶⁰
  Beyer JL, Taylor WD, MacFall JR, Kuchibhatla M, Payne ME, Provenzale JM, et al. Cortical white matter microstructural abnormalities in bipolar disorder. Neuropsychopharmacology. 2005;30:2225-9.
• ⁶¹
  Versace A, Andreazza AC, Young LT, Fournier JC, Almeida JR, Stiffler RS, et al. Elevated serum measures of lipid peroxidation and abnormal prefrontal white matter in euthymic bipolar adults: toward peripheral biomarkers of bipolar disorder. Mol Psychiatry. 2014;19:200-8.
• ⁶²
  Lin F, Weng S, Xie B, Wu G, Lei H. Abnormal frontal cortex white matter connections in bipolar disorder: a DTI tractography study. J Affect Disord. 2011;131:299-306.
• ⁶³
  McIntosh AM, Muãoz Maniega S, Lymer GK, McKirdy J, Hall J, Sussmann JE, et al. White matter tractography in bipolar disorder and schizophrenia. Biol Psychiatry. 2008;64:1088-92.
• ⁶⁴
  Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B. 1996;111:209-19.
• ⁶⁵
  Sexton CE, Mackay CE, Ebmeier KP. A systematic review of diffusion tensor imaging studies in affective disorders. Biol Psychiatry. 2009;66:814-23.
• ⁶⁶
  Papez JW. A proposed mechanism of emotion. Arch NeurPsych. 1937;38:18.
• ⁶⁷
  Mahon K, Burdick KE, Szeszko PR. A role for white matter abnormalities in the pathophysiology of bipolar disorder. Neurosci Biobehav Rev. 2010;34:533-54.
• ⁶⁸
  Heilbronner SR, Haber SN. Frontal cortical and subcortical projections provide a basis for segmenting the cingulum bundle: implications for neuroimaging and psychiatric disorders. J Neurosci. 2014;34:10041-54.
• ⁶⁹
  Brambilla P, Bellani M, Yeh PH, Soares JC, Tansella M. White matter connectivity in bipolar disorder. Int Rev Psychiatry. 2009;21:380-6.
• ⁷⁰
  Birbaumer N, Schmidt R. Biologische psychologie. Heidelberg: Springer; 2006.
• ⁷¹
  Kauer-Sant'Anna M, Kapczinski F, Andreazza AC, Bond DJ, Lam RW, Young LT, et al. Brain-derived neurotrophic factor and inflammatory markers in patients with early- vs. late-stage bipolar disorder. Int J Neuropsychopharmacol. 2009;12:447-58.
• ⁷²
  Rosa AR, Magalhães PV, Czepielewski L, Sulzbach MV, Goi PD, Vieta E, et al. Clinical staging in bipolar disorder: focus on cognition and functioning. J Clin Psychiatry. 2014;75:e450-6.
• ⁷³
  Czepielewski LS, Massuda R, Goi P, Sulzbach-Vianna M, Reckziegel R, Costanzi M, et al. Verbal episodic memory along the course of schizophrenia and bipolar disorder: a new perspective. Eur Neuropsychopharmacol. 2015;25:169-75.
• ⁷⁴
  Charlton RA, Barrick TR, McIntyre DJ, Shen Y, O'Sullivan M, Howe FA, et al. White matter damage on diffusion tensor imaging correlates with age-related cognitive decline. Neurology. 2006;66:217-22.
• ⁷⁵
  Bennett IJ, Madden DJ. Disconnected aging: cerebral white matter integrity and age-related differences in cognition. Neuroscience. 2014;276:187-205.
• ⁷⁶
  Debette S, Markus HS. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ. 2010;341:c3666.
• ⁷⁷
  Berk M, Kapczinski F, Andreazza AC, Dean OM, Giorlando F, Maes M, et al. Pathways underlying neuroprogression in bipolar disorder: focus on inflammation, oxidative stress and neurotrophic factors. Neurosci Biobehav Rev. 2011;35:804-17.
• ⁷⁸
  Najjar S, Pearlman DM, Alper K, Najjar A, Devinsky O. Neuroinflammation and psychiatric illness. J Neuroinflammation. 2013;10:43.
• ⁷⁹
  Fotuhi M, Do D, Jack C. Modifiable factors that alter the size of the hippocampus with ageing. Nat Rev Neurol. 2012;8:189-202.
• ⁸⁰
  Makris N, Worth AJ, Sorensen AG, Papadimitriou GM, Wu O, Reese TG, et al. Morphometry of in vivo human white matter association pathways with diffusion-weighted magnetic resonance imaging. Ann Neurol. 1997;42:951-62.

Publication Dates

• Publication in this collection
  22 Mar 2016
• Date of issue
  Apr-Jun 2016

History

• Received
  10 Aug 2015
• Accepted
  2 Sept 2015