Shape analysis of the cingulum, uncinate and arcuate fasciculi in patients with bipolar disorder

Abstract

Background:
Abnormal maturation of brain connectivity is supposed to underlie the dysfunctional emotion regulation in patients with bipolar disorder (BD). To test this hypothesis, white matter integrity is usually investigated using measures of water diffusivity provided by MRI. Here we consider a more intuitive aspect of the morphometry of the white matter tracts: the shape of the fibre bundles, which is associated with neurodevelopment. We analyzed the shape of 3 tracts involved in BD: the cingulum (CG), uncinate fasciculus (UF) and arcuate fasciculus (AF).

Methods:
We analyzed diffusion MRI data in patients with BD and healthy controls. The fibre bundles were reconstructed using Q-ball-based tractography and automated segmentation. Using Isomap, a manifold learning method, the differences in the shape of the reconstructed bundles were visualized and quantified.

Results:
We included 112 patients and 82 controls in our analysis. We found the left AF of patients to be further extended toward the temporal pole, forming a tighter hook than in controls. We found no significant difference in terms of shape for the left UF, the left CG or the 3 right fasciculi. However, in patients compared with controls, the ventrolateral branch of the left UF in the orbitofrontal region had a tendency to be larger, and the left CG of patients had a tendency to be smaller in the frontal lobe and larger in the parietal lobe.

Limitations:
This was a cross-sectional study.

Conclusion:
Our results suggest neurodevelopmental abnormalities in the left AF in patients with BD. The statistical tendencies observed for the left UF and left CG deserve further study.

Full text

J Psychiatry Neurosci 2017;42(1) 27
© 2017 Joule Inc. or its licensors
Research Paper
Shape analysis of the cingulum, uncinate and arcuate
fasciculi in patients with bipolar disorder
Zhong Yi Sun, PhD; Josselin Houenou, MD, PhD; Delphine Duclap, MSc; Samuel Sarrazin, MD;
Julia Linke, PhD; Claire Daban, PhD; Nora Hamdani, MD, PhD; Marc-Antoine d’Albis, MD;
Philippe Le Corvoisier, MD, PhD; Pamela Guevara, PhD; Marine Delavest, MD;
Frank Bellivier, MD, PhD; Jorge Almeida, MD, PhD; Amelia Versace, MD, PhD;
Cyril Poupon, PhD; Marion Leboyer, MD, PhD; Mary Phillips, MD, PhD;
Michèle Wessa, PhD; Jean-François Mangin, PhD
Introduction
Models of bipolar disorder (BD) assume that an altered
neuro development leads to a dysfunctional corticolimbic
connectivity, causing an emotional dysregulation.1 The corti-
colimbic communication largely relies on structural brain
connectivity, through white matter tracts, such as the unci-
nate fasciculus (linking prefrontal [orbitofrontal] cortices and
temporal limbic regions, including the hippocampus and
amygdala) and the cingulum.
Diffusion-weighted imaging (DWI) is widely used for the
study of white matter changes in patients with psychiatric
disorders.2 Voxel-based methods, such as tract-based spatial
statistics (TBSS), can be used to perform whole brain studies.3
Alternatively, bundle-based methods rely on tractography to
reconstruct white matter tracts before using them as regions
of interest for quantication of their microstructural status.4
These methods focus on water diffusivity in the tracts using
metrics such as fractional anisotropy (FA), mean diffusivity
(MD) or volume of the tract.
A few investigations of white matter changes in patients
with BD have been carried out,5 usually by assessing struc-
tural changes with FA, which gives information on the struc-
tural integrity of the white matter tracts. These studies re-
ported changes of FA along the white matter of the frontal,
occipital and limbic regions in patients with BD, including
tracts such as the uncinate fasciculus (UF), the anterior tha-
lamic radiations, the corpus callosum, the fornix, the cingu-
lum (CG) and the arcuate fasciculus (AF). However, these re-
sults were not conclusive in terms of FA changes:5 although
Correspondence to: J. Houenou, INSERM U955, IMRB, Equipe 15, Psychiatrie Translationnelle, 40 rue de Mesly, 94000 Créteil, France;
josselin.houenou@inserm.fr
Submitted Sept. 2, 2015; Revised Jan. 1, 2016; Revised Jan. 29, 2016; Revised Feb. 2, 2016; Accepted Feb. 3, 2016; Early-released June 28, 2016
DOI: 10.1503/jpn.150291
Background: Abnormal maturation of brain connectivity is supposed to underlie the dysfunctional emotion regulation in patients with
bipolar disorder (BD). To test this hypothesis, white matter integrity is usually investigated using measures of water diffusivity provided
by MRI. Here we consider a more intuitive aspect of the morphometry of the white matter tracts: the shape of the fibre bundles, which is
associated with neurodevelopment. We analyzed the shape of 3 tracts involved in BD: the cingulum (CG), uncinate fasciculus (UF) and
arcuate fasciculus (AF). Methods: We analyzed diffusion MRI data in patients with BD and healthy controls. The fibre bundles were re-
constructed using Q-ball–based tractography and automated segmentation. Using Isomap, a manifold learning method, the differences
in the shape of the reconstructed bundles were visualized and quantified. Results: We included 112 patients and 82 controls in our
analysis. We found the left AF of patients to be further extended toward the temporal pole, forming a tighter hook than in controls. We
found no significant difference in terms of shape for the left UF, the left CG or the 3 right fasciculi. However, in patients compared with
controls, the ventrolateral branch of the left UF in the orbitofrontal region had a tendency to be larger, and the left CG of patients had a
tendency to be smaller in the frontal lobe and larger in the parietal lobe. Limitations: This was a cross-sectional study. Conclusion:
Our results suggest neurodevelopmental abnormalities in the left AF in patients with BD. The statistical tendencies observed for the left
UF and left CG deserve further study.

Sun et al.
28 J Psychiatry Neurosci 2017;42(1)
many studies found reduced FA in some of these tracts,6–8
several studies found no change in FA.4
In the present study, we used the volumetric information
offered by bundle-based tractography methods to analyze
the shape of the white matter bundles. Brain shapes are sup-
posed to be strongly driven by neurodevelopmental fac-
tors.9,10 Since most of the brain shapes emerge early during
ontogenesis, abnormal shape is often the hallmark of abnor-
mal development.11 Our shape analysis methodology is de-
rived from a technique initially developed for the study of
the variability of cortical folding patterns.12 For each bundle,
shape variability is projected into a simple 2-dimensional
space obtained from an Isomap algorithm, a modern multi-
dimensional scaling method13 (Fig. 1). This approach pro-
vides a powerful way to perform quantication of complex
shapes, which has been illustrated by the discovery of a de-
velopmental feature of the central sulcus: the shape of the
hand knob was found to be associated with innate handed-
ness even after a forced switch of the writing hand at
school.12 In the present study, we analyzed the shape of 3 of
the main tracts involved in BD: the UF, AF and CG. We hy-
pothesized that the shape of these 3 bundles would be altered
in patients with BD compared with controls.
Methods
Participants
Adult inpatients and outpatients with BD type I (DSM-IV-R)
were recruited from 4 university-afliated participating cen-
tres: APHP Henri Mondor hospitals, Créteil, France; Fernand
Widal hospital, Paris, France; Western Psychiatric Institute
and Clinic, UPMC, Pittsburgh, USA; and Central Institute for
Mental Health, Mannheim, Germany. We recruited healthy
controls with no personal or family history of Axis I mood
disorders, schizophrenia or schizo affective disorder via
media announcements and registry ofces. All participants
were clinically assessed by trained raters (S.S., J.L., C.D.,
N.H., M.A.D., M.D. and A.V.) using the Diagnosis Interview
for Genetic Study14 at the French sites and the Structured
Clinical Interview for DSM-IV15 at the German and American
sites, the Montgomery-Åsberg Depression Rating Scale16 or
the Hamilton Rating Scale for Depression,17 the Young Mania
Rating Scale18 and the National Adult Reading Test19 in all
sites. Exclusion criteria for both patients and controls were
history of neurologic disease or head trauma with loss of con-
sciousness and MRI contraindications. Twenty-four of the
patients (20.34%) had participated in a previous single-centre
tractography study8 with different aims, DTI sequence and
processing pipeline. The multicentre data set was used for a
bundle-based FA analysis, which found a BD-associated de-
crease of FA in the corpus callosum, left CG and left AF.20 All
participants were given full verbal and written information
about the aims, methods and risks of the present study and
were given the option to decline participation. They were in-
vited to ask questions about the research and about the con-
sent form, with replies contributing to ensuring their in-
formed participation. Patients with enforced hospitalization
or under conservatorship were not included in the study, nor
were patients in an active psychotic state that may have inter-
fered with their ability to give informed consent. Such pro-
cesses were assessed through clinical examination and con-
sultation with the medical team involved in the patients’
care, as appropriate. After a complete description of the
study each participant gave written informed consent. The
local ethics committees of each centre (the Ethical Committee
of the Medical Faculty Mannheim, Heidelberg University; the
Institutional Review Board of the University of Pittsburgh;
and the Comité de Protection des Personnes Ile-de-France IX)
approved the study protocol.
Data acquisition
To minimize between-sites bias, we obtained diffusion-
weighted and T1-weighted images for all participants using
the same hardware in the 3 MRI acquisition sites (Siemens,
Magnetom TrioTim 3 T Syngo MR B17, 12-channel head-
coil). The MRI protocol included a high-resolution T1-
weighted acquisition (echo time [TE] 2.98 ms, repetition time
[TR] 2300ms, 160 slices, 1.0 × 1.0 × 1.1 mm) and a shared
diffusion-weighted sequence along 41 directions (2.0 × 2.0 ×
2.0mm, b = 1000 s/mm2 plus a b = 0 image, TE 87 or 84 ms,
TR 14000 ms, 60 or 64 axial slices, no gap, field of view
256 mm, number of excitations = 1, acquisition time
10.5min). Two operators (J.H. and S.S.) blind to the diagnosis
assessed the data for movement, susceptibility and noise arti-
facts. Participants with significant artifacts or movements
and with missing information were consensually excluded
from further analysis. For T1 images, we corrected the eld
inhomogeneity bias using an algorithm detailed previously.21
Whole brain tractography
Tractography and bundles segmentation involved a method
we used in a previous multisite study.20,22 The diffusion-
weighted MRI data were processed using Connectomist 2.0
and the T1-weighted MRI data were processed using Mor-
phologist 2012 (www.brainvisa.info). An orientation distri-
bution function (ODF) was computed at each voxel using an
analytical Q-ball model, which improves tractography in
complex white matter areas relative to classical diffusion
tensor imaging (DTI) models with regards to crossing or
kissing bres.
For each participant, a T1-based tractography mask was
computed in native space. We performed whole brain tractog-
raphy using a regularized streamline deterministic algorithm.
Bundle segmentation
Whole brain tractograms were then compressed into clusters
of streamlines with similar trajectories. Each cluster was
nally labelled according to the distance between its centroid
streamline and the centroids of the labelled bundles of a
multi subject atlas after afne normalization into Talairach
space. With regard to the Guevara atlas labels, the tracts of
interest were dened as the UF, CG long tracts and AF long

Bundle shapes in bipolar disorder
J Psychiatry Neurosci 2017;42(1) 29
tracts. While other bundles of interest in patients with BD
may be reconstructed using this processing pipeline, we de-
cided to exclude the anterior thalamic radiations and the cor-
pus callosum owing to the complexity of the associated fans
of bundles and we excluded the fornix owing to its small
diameter leading to frequent tractography issues. We vis-
ually checked segmentation for each participant.
Bundle sampling
The manifold learning strategy initially designed to study
the shape of cortical sulci12 was adapted to bre bundles.
First, we converted each bre bundle into a streamline den-
sity map sampled at the diffusion acquisition resolution.
This density map was thresholded at a value of 30 stream-
lines for a voxel of 2 mm in-plane resolution in order to get
a list of voxels belonging to the core shape of the bundle. To
check the robustness of the approach to the choice of this
threshold, we reproduced each analysis with 4 additional
thresholds, 24, 27, 33 and 36, leading to average changes of
the bundle volume of –20%, –10%, +10% and +20%, respect-
ively (Fig. 2). To control for the inuence of brain size vari-
ability, we further normalized the voxel coordinates to stan-
dard Talairach reference space using a 9-parameter afne
transformation. The bundles of the right hemisphere were
finally flipped relative to the interhemispheric plane to
allow asymmetry studies.
Shape quantication
For each bundle of interest, we used the Isomap algorithm13
to capture a low-dimensional approximation of the high-
dimensional space spanned by the bundle shape. Isomap ap-
plies multidimensional scaling to a matrix of distances com-
puted along the bundle manifold approximated as a nearest
neighbour graph of the participants’ individual bundles. This
graph is built from a similarity matrix where the similarity in
shape between 2 individual bundles is coded by the average
quadratic distance between their 3-dimensional (3-D) repre-
sentations after pairwise alignment using an iterative closest
point algorithm.23 We used the rst 2 dimensions of the Iso-
map, which capture the 2 main shape variations. For each par-
ticipant’s bundle, the 2 coordinates in the associated Isomap
provide a quantication of its shape relative to these 2princi-
pal kinds of variations. Hence, this approach allows a com-
pact quantication of shape change, alleviating the problem of
multiple comparisons disturbing voxel-based or deformation-
based approaches. Since the volume of the bundles may vary
extensively among participants in spite of the afne normal-
ization to Talairach space, we assume that one of the dimen-
sions shall be related to volume while the other embeds pure
shape variations. We used correlations of each dimension
with the volume of the tract to test our assumption. Bundle
volume was estimated from a smooth 3-D meshed represen-
tation of the core shape.
Shape averaging
In order to clarify the shape features coded in each of the
Isomap dimensions, local averages of the bundles are calcu-
lated at regularly spaced locations.23 This process results in a
series of moving average shapes (MAS) capturing the shape
evolution along the Isomap axis. For visualization, each
MAS is translated in anteroposterior direction according to
Fig. 1: Isomap algorithm capacity. (Left) Isomap automatically finds the manifold of dimension 2 embedded in a Swiss roll (the manifold is an
abstract mathematical space). (Right) Isomap creates a manifold of dimension 2 approximating the high-dimensional space of manually
drawn digits (http://scikit-learn.org/).
4
4
4
4
4
4
4
44
2
2
2
3
3
3
3
3
3
3
3
3
3
33
33
3
3
22
2
2
2
22
2
2
2
2
2
2
4
4
44
4
11
11
1
1
4
55
555
5
5
5
5
5
5
5
5
5
5
5
5
5
55
4
0
0
0
0
00
0
0
0
0
0
0
Unrolling a Swiss roll
3D
2D
Isomap projection of the digits

Sun et al.
30 J Psychiatry Neurosci 2017;42(1)
its Isomap coordinate. Hence a difference between 2 groups of
participants relative to their coordinates in this Isomap axis
has to be interpreted according to the regular gradual change
of the average shapes along the axis. Note that the shape vari-
ations coded by the Isomap axis are specic to each bundle.
Statistical analysis
For each of the 12 Isomap dimensions, we used analysis of
covariance (ANCOVA) to compare coordinates between pa-
tients with BD and healthy controls. Comparisons were per-
formed independently for the left and the right hemispheres.
The model included diagnosis (BD v. control) as a factor of
interest, sex as a confounding factor, age as a confounding
covariate, the site of inclusion as a confounding factor to con-
trol for potential site-specic effects, and FA as a confound-
ing factor that could impact the behaviour of tractography.
We considered results to be signicant for p values below
TBonferroni = 0.05 ÷ 12, to account for multiple testing. Simple
asymmetry tests related to volume and Isomap coordinates
were performed for the complete population using the
Wilcoxon signed-rank test. We also used Pearson correlation
to test if clinical variables (age at onset, depressive symp-
toms), bundle volume or FA were associated with shapes.
Results
Of the participants who met our inclusion criteria, 9 who had
signicant artifacts or movements and 1 patient with missing
information were consensually dropped out from the initial
sample, leading to a nal sample of 194 participants (112 pa-
tients and 82 controls) for our analysis (Table 1 and Table 2).
Uncinate fasciculus
The UF was found in both hemispheres for all participants. It
was highly asymmetric in volume in favour of the right
hemisphere (left: 44 ± 29 cm3; right: 56 ± 27 cm3, p < 0.001).
Patients with BD had a tendency to have a larger UF volume
than controls in the left (48 ± 30 cm3 v. 40 ± 27cm3, p = 0.05)
and in the right hemisphere (58 ± 26 cm3 v. 53 ± 27 cm3, p =
0.10). The rst dimension of the Isomap was correlated to the
bundle volume (r = 0.4, p < 0.001) while the second dimen-
sion was not.
For the rst dimension, Fig. 3 plots 6 MAS computed along
the Isomap axis across the coordinate range including the left
and right bundles. For the rst dimension, as the volume of the
bundle increased from the left to the right of the Isomap axis,
the frontal horn assumed a more “fanned out” characteristic
while the temporal horn shape remained relatively stable. At
the right of the axis the frontal horn showed a Y shape induced
by the emergence of the ventrolateral branch in the orbitofron-
tal region that did not exist in the left-most MAS. For the rst
dimension, patients with BD had a tendency to differ from
controls in the left hemisphere (F1,187 = 4.4, p = 0.036). The
ventrolateral branch of patients with BD had a tendency to
belarger than in controls (Fig.3). This tendency was qualita-
tively equivalent for the 4 alternative thresholds (Fig. 2). This
Fig. 2: Sample for each bundle of interest (cingulum, uncinate, arcuate) with the streamline representations obtained from tractography. Three
alternative voxel-based representations are obtained for each bundle with different thresholds on the number of streamlines crossing the voxels.
The threshold used in our study was considered optimal, preventing spurious voxels including few streamlines to be selected (see the uncinate
representation for a low threshold) and preserving the topology of the bundle (see the split representation of arcuate branches for a high thresh-
old). Note that from the low to the right threshold, the diameter of the bundle core decreases without qualitative changes in the shape.
Lowest
threshold
Initial
threshold
Highest
threshold Streamlines
Cingulum
Uncinate
Arcuate

Bundle shapes in bipolar disorder
J Psychiatry Neurosci 2017;42(1) 31
coordinate also signicantly depended on FA and scanning
site (Table2). The correlation between FA and the Isomap rst
coordinate was 0.43, which means that FA increases when the
ventrolateral branch gets larger. No difference was found for
the second dimension.
Cingulum
The CG was found to be highly asymmetric in volume in
favour of the left hemisphere (left: 44 ± 19 cm3; right: 37 ±
15cm3, p < 0.001). Patients with BD had a tendency to have a
smaller CG volume than controls in the left hemisphere (42 ±
18 cm3 v. 47 ± 20 cm3, p = 0.10). The rst dimension of the Iso-
map was correlated to the bundle volume (r = 0.6, p < 0.001)
while the second dimension was not.
For the second dimension (Fig. 4), the shape feature cap-
tured by the Isomap was related to the different size of the
frontal and the parietal extremities of the CG. From the left to
the right of the Isomap axis, the volume of the frontal extrem-
ity increased while the volume of the parietal extremity de-
creased. Hemisphere asymmetry was observed where the left
hemisphere was more toward the right side of this Isomap axis
(p = 0.011). Patients with BD had a tendency to differ from con-
trols in the left hemisphere (F1,187 = 4.99, p = 0.027). They had a
tendency to have a smaller frontal extremity and a larger pari-
etal extremity. This Isomap coordinate did not depend signi-
cantly on FA and scanning site. The tendency remained quali-
tatively equivalent for the 4 alternative thresholds (Fig. 2).
Arcuate fasciculus
The left AF was found for all participants while the right AF
did not pass our threshold on streamline density for 5 controls
and 6 patients. In agreement with this observation, for the par-
ticipants with adequate streamline density of AF in both hemi-
spheres, we observed the well-known volume asymmetry to-
ward the left hemisphere usually associated with language
lateralization (left: 109 ± 51 cm3; right: 53 ± 52 cm3, p < 0.001).
The rst Isomap dimension of AF was strongly correlated to
the bundle volume (r = 0.2, p < 0.001) and embedded a massive
asymmetry (p < 0.001). While the correlation with volume was
borderline for the second dimension (r = 0.1, p = 0.042), and
asymmetry was straightforward (p < 0.001).
We observed that this second dimension captured a purer
shape variation related to the size of the temporal horn
Table 1: Demographic and clinical characteristics of the sample
Group; no. (%) or mean ± SD [range]
Characteristic BD, n = 118 Control, n = 86
Scan site
Centre 1 24 (20.5) 22 (25.6)
Centre 2 53 (45.3) 26 (30.2)
Centre 3 40 (34.2) 38 (44.2)
Male sex 47 (40.2) 41 (47.7)
Age at MRI, yr 36.5 ± 10.4 [18–63] 37.3 ± 11.22 [19–66]
Right-handedness 110 (96.5) 84 (97.7)
IQ* 108.7 ± 10.58 107.39 ± 10.06
Medication
Lithium 39 (33.3) —
Anticonvulsants 64 (54.7) —
Antipsychotic 52 (44.4) —
Antidepressant 54 (46.2) —
Age at onset, yr 20.8 ± 8.0 —
YMRS score†‡§ 2.6 ± 3.7 —
MADRS score†§ 3.5 ± 5.4 —
HAMD-17 score‡ 9.9 ± 7.9 —
BD = bipolar disorder; HAMD-17= Hamilton Rating Scale for Depression; NART =
National Adult Reading Test; MADRS = Montgomery–Asberg Depression Rating
Scale; SD = standard deviation; YMRS = Young Mania Rating Scale.
*Assessed using the NART.
†Recorded at centre 1.
‡Recorded at centre 2.
§Recorded at centre 3.
Table 2: Comparison of shapes between patients with bipolar disorder and healthy controls
Bundle Df Dim
Diagnosis FA Scanner Age Sex
F1p value F1p value F2p value F1p value F1p value
Left AF 187 1 1.4 0.23 14.2 < 0.001* 2.1 0.13 5.1 0.026 0.8 0.78
2 15.1 < 0.001* 24.5 < 0.001* 1.9 0.16 3.5 0.06 0.3 0.61
Right AF 176 1 3.2 0.07 11.1 0.001† 0.6 0.54 7.8 0.006† 0.7 0.39
2 0.1 0.84 1.3 0.24 4.4 0.014 0 0.96 0.7 0.39
Left CG 187 1 0.4 0.54 48.6 < 0.001* 0.73 0.48 0 0.89 0.39 0.53
2 4.99 0.027† 0 0.87 2.5 0.08 0.8 0.37 0.3 0.56
Right CG 187 1 0. 0.91 32.4 < 0.001* 8.3 < 0.001† 0 0.99 0.8 0.91
2 3.5 0.06 1.5 0.22 10.7 < 0.001* 0.7 0.40 0 0.87
Left UN 187 1 4.4 0.036† 30.3 < 0.001* 26.1 < 0.001* 4.9 0.029† 2.8 0.10
2 1. 0.31 0.5 0.48 7.7 < 0.001† 3.0 0.08 1.7 0.20
Right UN 187 1 2. 0.16 3.0 0.08 39.7 < 0.001* 10.2 0.002† 0.3 0.57
2 2.9 0.09 2.8 0.09 36.1 < 0.001* 0 0.97 0.4 0.51
AF = arcuate fasciculus; CG = cingulum; Df = degrees of freedom; Dim = dimension; FA = fractional anisotropy; UN = uncinate fasciculus.
*Significant effect after Bonferroni correction for multiple tests (p < 4 × 10-4)
†Trend toward significance after Bonferroni correction for multiple tests (4 × 10-4 < p < 0.05).

Sun et al.
32 J Psychiatry Neurosci 2017;42(1)
toward the temporal pole. We found a signicant effect of BD
on this second dimension (F1,187 = 14.2, p < 0.001) that re-
mained signicant for the 4 alternative thresholds (Fig. 2).
This Isomap coordinate also signicantly depended on FA
(F1,187 = 24.5, p < 0.001). The correlation between the second
Isomap dimension and FA was 0.32, which means that FA in-
creases when the temporal horn gets longer.
No difference was found between patients and controls for
the rst dimension, whereas for the second dimension, the
left AF of the patients was more extended toward the tem-
poral pole, and in general the left AF had a longer temporal
horn than the right AF. Fig. 5 plots 6 MAS computed along
the second dimension Isomap of AF across the range of co-
ordinates including the participants’ left and right bundles.
From this series of MAS, the shape feature could also be in-
terpreted as a transition from a “looser” to a “tighter” arch or
hook around the Sylvian ssure.
For the 3 relevant dimensions of these 3 bundles, we did
not observe any effect of age at onset or depressive symptoms
(all p > 0.10).
Discussion
To our knowledge, our paper reports the rst tractography
study exploring the potential of the whole bundle shapes to
improve our understanding of white matter changes associ-
ated with BD. The most striking shape change observed in
these patients relative to healthy controls was a signicantly
longer extension toward the temporal pole of the left AF.
The implication of AF in BD is not well understood despite
several studies exhibiting FA abnormalities.2 A recent meta-
analysis of DTI studies points to AF as one of the prominent
regions of relevance to BD,2 which is consistent with the high
statistical signicance of our result. However, AF alterations
are not yet integrated in recent models of BD.24 Changes in
the AF are more consistently linked with models of schizo-
phrenia.25 Our previous findings about FA with this data
set,20 however, were located in the frontal part of the AF, in
the anterior segment, whereas our ndings about shape are
in the temporal lobe. Hence, further investigation is required
to explore the microstructure of the temporal horn. In our
Fig. 3: First dimension of the left uncinate fasciculus Isomap. (Top) Moving average shapes (MAS) along the Isomap observed with 2 different
orientations (for each orientation, the frontal horn of the bundle is on the left). The extreme MAS (green and magenta) are combined to high-
light the shape feature encoded by the Isomap. This dimension captures the volume variability of the bundles. From the left to the right of the
Isomap axis, the volume increases, while the bundle becomes more “fanned out” in the frontal lobe. More particularly, the ventrolateral orbito-
frontal branch emerges toward the right of the axis. (Middle) Individual bundles are superimposed over the same MAS along the Isomap axis
to show their distributions for both groups. (Bottom) Uncinate fasciculus sample and overall and centre-based boxplots of the localization in
the isomap after adjustment for fractional anisotropy, age and sex.
Isomap axis
Left uncinate fasciculus Overall
–40 –30 –20 –10 010 20 30 –40 –30 –20 –10 010 20 30–30 –20 –10 01020 –30 30–20 –10 01020
Bipolar
disorder
Control
Centre 1 Centre 2 Centre 3
Cont Bi
Bi
Bi
Bi
Cont
Cont
Cont

Bundle shapes in bipolar disorder
J Psychiatry Neurosci 2017;42(1) 33
study, the extended streamlines detected in the patients with
BD resulted from local changes of the microstructure beyond
the scope of traditional methodologies. The design of rened
methods taking potential shape change into account should
further clarify the ndings.
Regarding the UF, it is worth noting that the observed
trend toward a global increase of the frontal lobe volume of
the UF in patients (controlled for brain size variability by the
normalization to Talairach space) is in agreement with previ-
ous results for the left UF using streamline count.4 This al-
tered shape may result from abnormal developmental pro-
cesses, such as defective neural pruning, as suggested by
recent models of BD.24 Adolescence is a critical time of onset
of BD, and this has been assumed to be related to abnormal
white matter maturation.26 The UF is one of the main tracts
linking prefrontal (orbitofrontal) cortices and temporal limbic
regions, including the hippocampus and amygdala. In pa-
tients with BD, recent neural models assume a disrupted con-
nectivity between these regions, leading to an inability of the
prefrontal cortices to regulate an overreactive amygdala.1
Therefore, abnormal neurodevelopment of this fasciculus
may be involved in disrupted or altered frontolimbic connec-
tivity, contributing to aberrant interpretation, reaction and
decision-making regarding emotional information.29
We also found a trend toward a smaller frontal extremity and
a larger parietal extremity of the left CG in patients with BD
than in controls. The CG contains bres running from the sub-
genual and anterior cingulate frontal areas to retrosplenial tem-
poral regions and the occipital lobe. It therefore links several
parts of the limbic system and is involved in emotional regula-
tion. It has been repeatedly found to be altered in MRI studies of
BD,6,20,27–29 mostly left-sided.2,30 Many studies found a left-sided
lateralization of this tract31,32 in healthy adults; loss of this asym-
metry has been associated with higher neuroticism scores.33
Before the advent of tractography, in vivo assessment of
white matter bundle shapes was beyond reach, except at the
level of bottlenecks, such as the corpus callosum. Abnormal-
ities of the shape of a midsagittal section of the corpus callo-
sum have been demonstrated in patients with schizophre-
nia34 and BD.35 To our knowledge, the only previous work
Fig. 4: Second dimension of the cingulum fasciculus Isomap. (Top) Moving average shapes (MAS) along the Isomap axis observed with 2 dif-
ferent orientations (for each orientation, the frontal horn of the bundle is on the left). The extreme MAS (green and magenta) are combined to
highlight the shape feature encoded by the Isomap. This dimension captures a pure shape feature. From the left to the right of the Isomap
axis, the volume of the frontal extremity increases while the volume of the parietal extremity decreases. (Middle) Distributions along the Iso-
map axis of the left bundles of patients with bipolar disorder versus controls superimposed over the same MAS. (Bottom) Cingulum sample
and the corresponding uncinate fasciculus and overall and centre-based boxplots of the localization in the isomap after adjustment for frac-
tional anisotropy, age and sex.
Isomap axis
Left uncinate fasciculus Overall
–20 –10 010 –20 –10–10 010 –10–15–15–15 –5–5–5 00 555 1010 15
Bipolar disorder
Control
Centre 1 Centre 2 Centre 3
Cont Bi
Bi
Bi
Bi
Cont
Cont
Cont

Sun et al.
34 J Psychiatry Neurosci 2017;42(1)
exploiting tractography to study white matter shape in a
psychiatric syndrome was limited to the changes of the fan
geometry of bres passing through the corpus callosum in
patients with schizophrenia.36
Linking our observations with the decrease of FA ob-
served for the same tracts in the current literature is an open
issue.6–8 A decrease of FA is usually associated with changes
in the microstructural properties of the bre pathways, such
as decreased axonal diameter or density, reduced myelina-
tion, or decreased white matter coherence.37 Hence, the de-
crease of FA observed in patients with BD could be associ-
ated with either a lack of maturation, with a degenerative
process akin to aging, or both.38 In the present study, how-
ever, we found that whatever the status of the participant,
the longer temporal part of the AF correlated with higher
global FA for the bundle. These correlations could mean
that higher FA results in better tractography, or that larger
bundles result in higher FA because of lower partial vol-
ume. More importantly, this observation could mean that
FA changes associated with BD are probably heterogeneous
across the bundle. Hence, taking into account bundle shape
changes could shed some light on the inconsistencies in the
literature on microstructure ndings using parameters such
as FA: shape differences could have a complex impact on
the measurements using different methodologies.
To our knowledge, this report relies on the largest multi-
centre sample of patients with BD involved in a tractography
study to date, thus reducing the risks associated with re-
strained statistical power and single-centre recruitment. Fur-
thermore, the MRI acquisition protocol and hardware have
been harmonized to reduce site-specic effects, and replica-
tion of the results with different parameters of the tractog-
raphy method has been achieved. Finally, to our knowledge,
this is the rst systematic study of disease-related changes of
the shape of bre bundles ever reported.
Limitations
The ndings described in this paper tend to support the mal-
formation of the frontotemporal connectivity stemming from
Fig. 5: Second dimension of the arcuate fasciculus Isomap. (Top) Moving average shapes (MAS) along the Isomap axis observed with 2 different
orientations (for each orientation, the frontal horn of the bundle is on the left). The extreme MAS (green and magenta) are combined to highlight
the shape feature encoded by the Isomap. This dimension captures a pure shape feature: the extent of the development of the bundle toward the
temporal pole. (Middle) Distributions along the Isomap axis of the left bundles of patients with bipolar disorder versus controls superimposed over
the same MAS. (Bottom) Arcuate fasciculus sample and overall and centre-based boxplots of the localization in the Isomap after adjustment for
fractional anisotropy, age and sex.
Isomap axis
Left uncinate fasciculus Overall
–20–30–40 –10 0 10 20 –40 –20–10 0 10 –10–20–30–20 –10 00 10 1020 20
Bipolar disorder
Control
Centre 1 Centre 2 Centre 3
Cont Bi
Bi
Bi
Bi
Cont
Cont
Cont

Bundle shapes in bipolar disorder
J Psychiatry Neurosci 2017;42(1) 35
development. A common limitation of cross-sectional studies
is the inability to determine whether the observed alterations
precede the onset or develop during the course of the dis-
ease.38 However, white matter abnormalities have been re-
ported in patients with BD at onset and in samples of unaf-
fected relatives.27 Another limitation is the intersite effect in
our results, as this is the case for most multisite neuroim-
aging studies. Intersite differences may arise from both tech-
nical factors (we attempted to limit these by homogenizing
scanners, data acquisition and processing) and clinical differ-
ences between populations. Bipolar disorder is a highly het-
erogeneous condition, although we do not precisely know
which clinical factors have a strong neurobiological basis.
This is a clear limitation that has to be addressed in future
studies. In spite of this limitation, our results were consistent
across sites relative to displacements of means and quartiles
between groups, supporting an effect shared across sites
(Fig.3, Fig. 4 and Fig. 5). Potential effect of medications was
not investigated in this study; however, evidence suggests
that medications are not a major confounder in imaging
studies of white matter in patients with BD.39
Alternatively, shape modication may be associated with
processes other than neurodevelopment (e.g., neuroprogres-
sive effects), with medication usage, or with disease effects.
We cannot rule them out in this cross-sectional study, but
disease effects are not likely to yield larger tracts as seen here
for the AF. Additionally, recent reviews suggest no effects or
minimal effects of medication on DTI parameters.39
It is important to realize that the observed shape abnor-
malities can result either from an actual anatomic difference
or from a different behaviour of tractography in the 2 popu-
lations. The main confounding factor that may modulate the
shape of a bre bundle resulting from tractography is the
erroneous estimation of bre directions in complex voxels,
including crossing or kissing bres.40 Therefore, some of the
changes observed between patients and controls could re-
sult from changes in the neighbourhood of the tracts of in-
terest. A lighter density of crossing bres in patients with
BD would simplify tractography and reveal some segments
of the tracts usually lost in healthy controls. Further study
involving not only deep white matter bundles, but also su-
percial U-bre bundles will be required to tackle this issue.
In the present study, the use of Q-ball imaging alleviated
the risk of such mistakes relative to standard DTI, but fur-
ther improvement of tractography methods, such as global
tractography, would be of interest.40
Finally, another limitation of this study is the possible het-
erogeneity of the samples recruited and the different clinical
tools used in the different centres. This limitation pertains to
the multisite design of the study.
Conclusion
Our observation of an altered shape of the left AF suggests
neurodevelopmental abnormalities in patients with BD. Fu-
ture studies comparing patients with schizophrenia and pa-
tients with BD may enlighten the specicity of this nding
and its link with psychosis. The differences found in the left
AF support recent reports of predominantly left-sided
changes in patients with BD. Links between disturbance of
asymmetry and neurodevelopment in BD warrant further ex-
ploration, as do the statistical tendencies observed for the left
UF and the left CG.
Acknowledgements: The authors thank all those who participated in
this study and the personnel of participating centres for their help
with data collection.
Afliations: From the UNATI, Neurospin, I2BM, CEA Saclay, Gif-
Sur-Yvette, France (Sun, Mangin); the UNIACT, Psychiatry Team,
Neurospin, I2BM, CEA Saclay, Gif-Sur-Yvette, France (Houenou,
Sarrazin); INSERM, U955, IMRB, Equipe 15 Psychiatrie Translation-
nelle, Créteil F-94000, France (Houenou, Sarrazin, Hamdani, d’Albis,
Leboyer); the Fondation Fondamental, Créteil F-94010, France
(Houenou, Sarrazin, Hamdani, d’Albis, Delavest, Bellivier, Leboyer);
the AP-HP, Hôpitaux Universitaires Mondor, Pôle de Psychiatrie,
DHU PePsy, Université Paris Est, Créteil F-94000, France (Sarrazin,
Daban, Hamdani, d’Albis, Leboyer); the UNIRS, Neurospin, I2BM,
CEA Saclay, Gif-Sur-Yvette, France (Duclap, Poupon); the Depart-
ment of Clinical Psychology and Neuropsychology, Johannes Guten-
berg University, Mainz, Germany (Linke, Wessa); INSERM, Centre
d’Investigation Clinique 1430 and APHP, GH Henri Mondor, Créteil
F-94000, France (Le Corvoisier); the University of Concepción, Con-
cepción, Chile (Guevara); the AP-HP, Groupe Saint-Louis, Lari-
boisière-Fernand Widal, Pôle Neurosciences, Paris, France (Delavest,
Bellivier); the Department of Psychiatry, Western Psychiatric Insti-
tute and Clinic, University of Pittsburgh School of Medecine, Pitts-
burgh, PA, USA (Almeida, Versace, Phillips); the Faculté de méde-
cine, Universite Paris Est, Créteil, France (Leboyer); and the CATI
Multicenter Neuroimaging Platform, France (Sun, Poupon, Mangin).
Funding: This work was supported by public funding from the Alli-
ance pour les Sciences de la Vie et de la Santé (ITMO Neurosciences),
the Agence Nationale pour la Recherche (ANR MNP VIP 2008 and
ANR-11-IDEX-0004 Labex BioPsy), the Fondation pour la Recherche
Médicale (Appel d’offres analyse bioinformatique pour la recherche
en biologie 2014), the Deutsche Forschungsgemeinschaft (SFB636/C6
and We3638/3-1), and the NIMH R01 MH076971. S.Sarrazin is sup-
ported by a grant from the Agence Régionale de Santé Ile-de-France.
The funders did not participate in the design and conduct of the
study, in the collection, analysis or interpretation of the data; or in
the preparation, review or approval of the manuscript.
Competing interests: S. Sarrazin declares travel expenses from Otsuka
outside the submitted work. M. Phillips is a consultant with Roche.
Contributors: J. Houenou, D. Duclap, P. Le Corvoisier, M. Delavest,
A.Versace, C. Poupon and M. Leboyer designed the study. J. Houenou,
S. Sarrazin, J. Linke, C. Daban, N. Hamdani, M.-A. d’Albis,
P. Le Corvoisier, F. Bellivier, J. Almeida, A. Versace, M. Phillips,
M.Wessa and J.-F. Mangin acquired the data, which Z. Sun,
J.Houenou, S. Sarrazin, P. Guevara, C. Poupon, M. Phillips and
J.-F. Mangin analyzed. Z. Sun, J. Houenou and J.-F. Mangin wrote
the article, which all authors reviewed and approved for publication.
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