Shinshu M ed J, 64⑶ :113〜121, 2016

Averaging Diﬀusion‑weighted Images Aﬀects
the Analysis of the Diﬀusion Tensor in Vivo
Tomoki KANEKO , Kikuko KANEKO and Masumi KADOYA
Department of Radiology, Shinshu University School of Medicine

Purpose:The objective of this study was to show an alteration in diﬀusion tensor indices caused by image
averaging.
Materials and Methods: We recruited four healthy volunteers. The diﬀusion tensor images (DTI) wereobtained with non‑collinear motion‑proving gradients along 12 axes and were repeated 10 times using a 3.0 T
MR scanner.The images were averaged in the order of the sessions.The fractional anisotropy(FA),apparent
diﬀusion coeﬃcient (ADC)and eigenvalues (λ1,λ2,λ3)were calculated based on the regions of interest (ROIs)
drawn on the commissural, association and projection ﬁbers. To determine the alterations to the FA caused
by image averaging, we performed a multiple regression analysis using statistical parametric mapping.
Results:The FA,ADC,λ1 and λ2 values tended to decrease,and theλ3 value tended to increase in proportion
to the number of averaging times in the ROI study. In the voxel‑based analysis, the FA values signiﬁcantly
decreased proportionally with the increasing number of averaging times.
Conclusions:DTI analysis after image averaging is not desirable because the sharpness of the tensor can belost.Shinshu Med J 64 : 113 ―121, 2016
(Received for publication October 19, 2015;accepted in revised form January 7, 2016)
Key words:diﬀusion tensor imaging, diﬀusion weighted image, averaging

Introductionλ3)and other values derived from the eigenvalues,
such as fractional anisotropy (FA), relative

In diﬀusion tensor imaging (DTI), the molecularanisotropy (RA) and volume ratio (VR)［4］. To

displacement of the hydrogen nuclei carried byobtain DWI,fast imaging technology,such as spin‑water molecules in the voxel is expressed as aecho echo‑planar imaging (SE‑EPI),has commonly

tensor . The diﬀusion tensor provides unique infor-

been used to detect the self‑diﬀusion of water

mation about the brain tissue calculated from eachmolecules in each voxel . The “single‑shot”spin‑voxel of the diﬀusion‑weighted images (DWI) . A

echo echo‑planar sequence is adopted for the acqui-series of diﬀusion‑weighted images with bipolar

sition of DWI at one time point using the M PG tomagnetic ﬁeld gradients,known as the motion‑prob-

conﬁrm the simultaneity of water moleculeing gradient (M PG), applied in non‑collinear anddiﬀusion. Thus, DWI using the single‑shot SE‑EPI

non‑coplanar directions are acquired to calculatesequence generates a low signal‑noise ratio and is

the tensor . The characteristic of the tensor isaﬀected by the susceptibility artifact .

determined using the eigenvalues (e.g., λ1, λ2 andThere are two major methods for improving a
low signal‑to‑noise ratio. One is to increase theCorresponding author:Tomoki Kaneko
Department of Radiology, Shinshu University School ofM edicine, 3‑1‑1 Asahi, M atsumoto, Nagano 390‑8621,

number of MPG axes, and the other is to increase
the number of times the images are averaged

.

Japan

The MRI operator must average the images theE‑mail:tk55＠shinshu‑u.ac.jp

appropriate number of times and use the appropri-

No. 3, 2016113

Kaneko T .Kaneko K .Kadoya

ate number of MPG axes because both methods

built‑in console oﬀered by the manufacturer. The

prolong the total scan time. Although there haveset of images obtained at the i(i＝1,2,...,10)session

been many reports on the relationships between thewas named si. The averaged images (named ni) ＝number of MPG axes and the signal‑noise ratio,the(s1＋s2＋...＋si)/i (2≦i≦10)・・・Eq. (1). We divid-

inﬂuence of the number of times the images are

ed the images into a group of reference images andaveraged on the DTI indices has rarelybeen studied.

a group of diﬀusion‑weighted images applying theWe estimated how the eigenvalues (λ1, λ2, λ3),

MPG with the same number of axes.We calculated

fractional anisotropy (FA) and apparent diﬀusion

the “arithmetic mean”of the images using equationcoeﬃcient (ADC)varied with changes in the number(1)above (Fig. 1).

of averaging times.

D

Materials and M ethods
This study was approved by the local ethics

Diﬀusion Tensor Imaging analysis
The image data (s1, s2, ..., s10, n2, n3, ..., n10)for

each subject were analyzed on a stand‑alone PC.
The following results were obtained using the freecommittees.

software dTV for MR‑DTI analysis developed by

A Subjects

the Image Computing and Analysis Laboratory,

We recruited four participants for this study.All

Department of Radiology,The University of Tokyo

participants were male, and their age ranged from

Hospital, Japan. The dTV software was available

23 to 53 years (median 24). Informed consent was

via the following URL : http://www.ut‑radiology.

obtained from each participant. Furthermore, weumin.jp/people/masutani/dTV.htm.

added a phantom scan to observe unique motion

E Data acquisition

artifacts during the DTI.Details of the structure of

1 Scalar value using the region of interest (ROI)

the phantom are:φ220 mm×135 mm, 5.6 kg, ﬁlled

To precisely deﬁne the regions‑of‑interest (ROIs)

with polyvinyl alcohol (PVA)gel material sealed byon the commissural, association and projection

acrylic plate,meeting the criterion of the Americanﬁbers, we used the 3 diﬀusion anisotropy coding (3Association of Physicists in Medicine (AAPM)andDAC) image, which allows the target ﬁber to be

the National Electrical M anufacturers Association

easily recognized on the color‑coded map.The two(NEMA) (type 90‑401, Nikko Fines industries,

radiologists drew the ROIs corresponding to theTokyo, Japan).

ﬁber tracts on the three DAC images: corpus cal-B MRI acquisition

losum (CC),cingulum (Ci)and pyramidal tract (Py).

M R images were acquired using a 3.0 T MR

Finally, the eigenvalues (λ1, λ2, λ3), fractionalscanner Trio (Siemens,Erlange,Germany)with a 16

anisotropy (FA), and apparent diﬀusion coeﬃcientch. head coil. DTI images were obtained using a(ADC) were obtained from this DTI analysis. In

single shot spin‑echo echo‑planar sequence in axial

addition to these values, we also calculated theorientation. The DTI acquisitions were performed

mean of the DTI values of each session in number

with non‑collinear MPGs along 12 axes and wereorder. This was an important element of our data

repeated 10 times.Each DTI data set was composed

analysis because it allowed us to compare the scalarof one reference image (b factor＝0)and the follow-

averaging values of each session with the values ofing diﬀusion‑weighted images using non‑collinear

the post‑image averaging. The eigenvalues of DTI

MPGs along 12 axes. The DTI parameters were as(λ1‑λ3), FA and ADC values are shown in Fig. 2.

follows:repetition time＝5300 msec, echo time＝90

2 Voxel based analysis

msec,b factor＝1000 s/mm ,matrix＝128×128,and

According to the reported (analytical) procedure

slice thickness/gap＝3/0 mm.

for voxel‑based morphometry using Statistical

C Image averaging

Parametric Mapping (SPM),we examined the inﬂu-

One radiologist performed image averaging at a114

ence of the number of excitations on the FA value.
Shinshu M ed J Vol. 64

Averaging DWIs aﬀects the DTI

Fig. 1

Method for averaging the diﬀusion‑weighted images for each session. We divided the images into agroup of reference images and a group of diﬀusion‑weighted images applying M PG from the same
direction.Then we calculated the arithmetic mean of the images using the equation described above(1).

a To assess the FA value, the following proce-

FA map aided in the development of the new FA

dures were performed .

template,which was based on the provided FA map.

(1) Image preparations:both the reference images(4) Re‑normalizing : we re‑normalized the FA

and the FA images of all sessions (s1,s2,...,s10,and

maps directly to the standard space using then2,n3,...,n10)were prepared (before the processing

smoothed‑averaged FA map.This process standar-step).

dized each FA map to FA template automatically,(2) Spatial normalization :we normalized the orig-

and enabled the voxel‑based analysis throughout

inal reference image to the standard space using thethe brain.

“
spatial normalization”function of the SPM8, andb Statistical analysis

we obtained the normalization parameter subse-

We estimated the inﬂuence on the FA values of 1)

quently. Then the FA map was converted to thethe repeated scanning of DTI sessions(s1 to s10)and

same space using the obtained normalization

2)image averaging (n2 to n10)by using voxel‑based

parameters.

analysis of whole brain. We used the multiple(3) Making FA template:the arithmetic mean ofregression analysis of the SPM to observe the ten-

all of the spatial normalized FA maps was calcu-

dency of FA values, because a linear regression islated using the image calculator provided with

ﬁtted to the time course of each voxel.

SPM8.The averaged FA map was smoothed adopt-

At ﬁrst, we examined whether the FA values

ing an 8 mm ﬁlter. Then this smoothed‑averaged

increased or decreased in proportion to the timeNo. 3, 2016115

Kaneko T .Kaneko K .Kadoya

Fig. 2Diﬀusion tensor indices (FA,ADC,λ1 to λ3)calculated from the region ofinterest.Blue columns:“
s1 to s10”columns show the values of each session.Purple columns:the“mean”column shows themean value of all sessions (s1 to s10), and the “
n2 to n10”columns show the values of the naveraged session.

course of sessions (s1 to s10).Fig. 3 A, B.Secondly,

the results clinically.

to estimate the eﬀects of the image averaging, we

3 Observation of head and phantom rotation

examined whether the FA values increased or de-

To observe the degree of rotation and the spatial

creased with an increasing number of image averag-shift of the head and phantom, we executed theing times.Fig.3 C,D.To avoid type 1 error,family‑“
Realign”function of the SPM for all of the b＝0

wise error (FWE) maintenance was recommended

map. The degree of rotation (yaw, pitch, roll) andwhen applying a signiﬁcance level in SPM.Thus,wethe spatial shift (x, y, z) during DTI are shown in

adopted FWE management (p＜0.05)to make use of

Fig. 4.

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Shinshu M ed J Vol. 64

Averaging DWIs aﬀects the DTI

Fig. 3

Voxel‑based morphometry for the FA using the SPM .The glass brains are indicated on the left,and
design matrix on the right.T value maintained by the family‑wise error rate(FWE)is under the glass
brains. Gray columns of the upper section of design matrixes show the increase of the FA values
examined (upward column) and the decrease of the FA values examined (downward column). The
signiﬁcant voxels are drawn on the glass brain.
Positive (A)and negative (B)correlations of the FA in proportion to increasing number of sessions(s1 to s10)were calculated.Neither a positive nor a negative tendency is shown on either map.In thesame manner, positive (C) and negative (D) correlations of the FA in proportion to the increasing
number of averaged sessions (n2 to n10)were calculated. Although no positive tendency is shown on
map (C), there were multiple coordinates that indicated a negative tendency on map (D).

Results

91, p＜0.05) between any sessions (s1 to s10). Thismeans the repeated scan would not impinge on the

In Fig. 2, by comparing the ROI data (FA, ADC,

diﬀusion tensor analysis. On the other hand, multi-

λ1 to λ3) of the scalar averaging of each series

ple signiﬁcant voxels appeared (t＝5.99, p＜0.05) in(from s1 to s10)to the post‑image‑averaging (fromFig. 3D. This means that the increasing number ofn2 to n10),we found a tendency of FA,ADC,λ1 andaveraging times would impact more signiﬁcantly on

λ2 to decrease and a tendency of the λ3 to increase

the diﬀusion tensor analysis.

with an increasing number of image averaging
times.

As the scanning time passed,Fig.4 shows that theposition and the angle of the head from the ﬁrst‑

Fig. 3 shows the signiﬁcant voxels on the glass

scanned b＝0 map widened.We were not able to ﬁnd

brain calculated throughout the brain by using

any kind of tendencies about the head movement.

voxel‑based analysis of SPM.There was no signiﬁ-

The translations of the phantom were 1/2 or less ofcant increase (Fig. 3A)or decrease (Fig. 3B)(t＝5.

the human, and the rotations were 1/5 or less.

No. 3, 2016

117

Kaneko T .Kaneko K .Kadoya

Fig. 4118

Variances in the rotation and shift of the head and phantom.A)to D)show the rotation andshift of the head and E)shows that of the phantom.

Shinshu M ed J Vol. 64

Averaging DWIs aﬀects the DTI

Eq. (2)

Discussion

In our study, as the scanning time passed, theThe “single‑shot” spin‑echo echo‑planar se-

position and the angle of the head dislocated gradu-

quence made it possible to scan the diﬀusion‑weigh-ally (Fig. 4). We were not able to detect any trend

ted images of the whole brain by applying one

or characteristic movement of the translation andbipolar magnetic ﬁeld gradient. Namely, the SE‑

rotation among the DTI scans. The rotation angle

EPI sequence showed synchronization of a timeof the phantom was negligiblysmall,but the disloca-

phase of the diﬀusion information of the entire

tion in the z‑axis direction was noticeable asbrain.Conversely,the susceptibilityartifact,low

compared with others. Although the phantom wassignal‑noise ratio and eddy current artifact were

ﬁxed rigidly by ﬁlling the gap between the coil andprominent in comparison with the routine T1/T2‑

the phantom with gel pads, rostrocaudal (z‑axis

weighted spin‑echo sequences .

direction)ﬁxation was not conducted.It was consid-

There are two major methods for improving aered that the mechanical vibration of the DTI scan

low signal‑noise ratio. One is to increase the num-

induced the dislocation of the phantom between theber of MPG axes, and the other is to increase the

1 and 2 scan, but we were unable to ﬁnd persist-number of averaging times.Increasing the num-ent dislocation after the 2 scan.Although continu-

ber of MPG axes is useful for accurately measuring

ous translation in the phase encoding direction

diﬀusion tensor because of the phenomenon ofduring EPI imaging was reported, we thought that

ﬂuctuation of water molecule diﬀusion in vivo.

the dislocation of the phantom was just slippage due

Thus, the applied directions and the number of theto mechanical vibration . As a result, the angle ofaxes of the MPG were examined for robust estima-

the diﬀusion tensor calculated from each session

tion of the DTI.Conversely,the prolongation of

was altered. In addition, the directions of thethe scan time was inevitable when increasing thediﬀusion tensor of each session might not be uni-

number of averaging times and M PG axes. The

form because of bulk ﬂow and pulsation in vivo.

MRI operator had to adopt the appropriate number

If the number of ﬁber tracts in diﬀerent orienta-of averaging times and MPG axes to set the total

tions,which are approximated based on the tensors

scan time in an adequate range .It has been report-with diﬀerent angular axes,crossed in the voxel,theed that 20 directions of M PG axes for anisotropy

signal of the diﬀusion‑weighted image (Sig Nnanalysis and 30 directions of MPG axes for FA

cross)was calculated as follows;

analysis generate suﬃcient conditions for mean＝

diﬀusibility analysis and the orientation of the−diﬀusion tensor;however, 20 directions or more of
MPG axes are permissible in vivo

exp

1

2

−

1

＋

＋…

−

.

In our study,the FA values,λ1,and λ2 tended toEq. (3)decrease,and λ3 tended to increase in proportion to
the number of averaging times. The signal of thediﬀusion‑weighted images of the nth session (Sn)Eq. (4)was named “
Sig Sn”, and the signal of the nth

The averaging of the diﬀusion‑weighted signals

averaged image (Nn) was named “
Sig Nn”. The

for each session performed with equation (2)above“
Sig Nn”was calculated as follows;

resulted in the averaging of the tensor having＝

1

diﬀerent angular axes, such as crossing ﬁber tracts
exp −
exp −

＋
No. 3, 2016

1
2

−

＋

＋…

(3)(4);thus,the diﬀusion tensor lost its sharpness as
the averaging times increased.Adjusting the motion
artifact by, for example, shifting and rotating the119Kaneko T .Kaneko K .Kadoya

head was performed after scanning automaticallyeach diﬀusion‑weighted image are desirable.

or manually using the program provided by various

Conclusion

researchers. Only adjusting the shift among thediﬀusion‑weighted images appeared to be useful fora robust analysis. However, adjusting the rota-tion of the head is necessary for adjusting the

DTI analysis using the diﬀusion‑weighted images
after image averaging is not desirable because it
causes the sharpness of the tensor to be lost.

angular information of the applied MPG direction

Limitation

simultaneously . The averaging of the image
should be calculated using the diﬀusion‑weighted

We recruited only four healthy participants forimages with the same M PG directions. Adjusting

the MR examination.However,when manysubjects

the rotational angle alters the information of the

who are unstable or are not used to MR examina-

MPG directions; thus, averaging should not betion are recruited, we believe that the results will

performed on the diﬀusion‑weighted images after

support our current conclusion because morerotational angle adjustment. Although image aver-somatic motion of the patients leads to instabilityofaging is an excellent procedure for improving thethe diﬀusion tensor.

signal‑noise ratio,the qualityof the averaged image

Conﬂict of Interest

may be decreased bythose data aﬀected bysubstantial motion‑induced artifacts during the encoding of
the diﬀusion gradient . In addition, we recruited

The authors declare no conﬂict of interest in thiswork.

healthy participants for this study,and patients are

Acknowledgements

typically more unstable than healthy persons.
Furthermore,image averaging causes DTI analysis

We are grateful to Drs.Y.Fujinaga and K.Ueda

to lose its sharpness for the tensor and aﬀects thefor assistance in manuscript preparation.We thank

DTI analysis to some extent. Thus, increasing the

Mr. Y. Kito and H. Ueda for providing technicalnumber of MPG axes and,if possible,adjusting theadvice.

rotational angle of the applied M PG direction ofReferences
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（2015.10.19 received ; 2016. 1. 7 accepted）

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