Neonatal Brain Development assessed by new
quantitative Analysis of 3-Tesla MRI and DTI
1,2G
Gerig, 2Pierre Fillard, 2M Prastawa, 3W Lin, 1John Gilmore,
Departments of 1Psychiatry, 2Computer Science, 3Radiology
University of North Carolina, Chapel Hill,NC 27614, USA,
gerig@cs.unc.edu / http://www.cs.unc.edu/~gerig
Diffusion Tensor Imaging (DTI)
SUMMARY
• Research: Quantitative MRI to study
unsedated newborns at risk for
neurodevelopmental disorders.
• Clinical Study: 120 newborns to e
brecruited at UNC, age at MRI about 2
weeks
• Motivation: Early detection of
abnormalities  Possibility for early
intervention and therapy.
• Imaging: High field (3T Siemens
Allegra), high resolution (T1 1mm3,
FSE 0.9x0.9x3mm3), high-speed
Adult
imaging (12’ for T1, FSE and DTI).
T1 3D MPRage
1x1x1 mm3
FSE T2w
1x1x3 mm3
Conventional ROI Analysis (one axial slice only)
Neonate
• Challenge: Very
low CNR,
heterogeneous
tissue, early
myelination
regions, reverse
contrast wm/gm.
• Standard brain
tissue
segmentation fails.
FSE PDw
1x1x3 mm3
Structural MRI
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0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
adult
neonate
adult
neonate
Neonates
G
M
fro
nt
al
oc
cip
it a
l
In
te
rn
al
ca
p
Adults
ge
nu
sp
le
ni
um
FA (%)
Fractional Anisotropy
Apparent Diffusion Coefficient
ADC (mm2/sec)
Hypothesis:
• DTI reflects degree of myelination
and structure of fiber tracts.
• Decrease of fractional anisotropy
(FA) from interior to the periphery.
• Higher ADC values compared to a
matured brain (adult).
• Lower FA values compared to adults.
• DTI reflects degree of axon pruning
and myelination.
200
180
160
140
120
100
80
60
40
20
0
Neonates
Adults
Zhai G, Lin W, Wilber K, Gerig G, Gilmore JH (2003):
Comparisons of regional white matter fractional
anisotropy in healthy neonates and adults using a 3T
head-only scanner. Radiology (in print).
New Method: Diffusion along fiber tract via Tractography
Tracing of the commissural fiber tracts through the genu in five neonates
splenium
Approach:
• Atlas-moderated EM segmentation (cf. Leemput and Warfield)
• Tissue intensity model for white matter (non-myelinated and myelinated wm
form bimodal distribution) (cf. Cocosco, Prastawa)
Fractional Anisotropy (FA) along splenium/genu bundles
FA
Building of Atlas Template
Template MRI
white matter
gray matter
FA
• Fractional Anisotropy (FA)
quickly drops with
increasing distance from
midsagittal plane
• Drop off more pronounced
in genu than in splenium
csf
Change of FA along splenium/genu across time
Here Text
Here Text
Tissue Probability Maps
• Comparisum adults, 2yrs
olds and neonates
• FA in neonates significantly
lower than in 2 yrs old
subjects and adults
• 2yrs old subjects show
similar values as adults
T1-only segmentation
white
gray
csf
myelin.
hyperintense
motor
cortex
early
myelinated
corticospinal
tract
CONCLUSIONS
• It is feasible to study brain development in unsedated newborns using 3T MRI
• Study will likely provide a vastly improved understanding of early brain
development and its relationship to neuropsychiatric disorders.
• Novelty: Tissue model for segmentation of myelinated/nonmyel. white matter.
• Novelty: Use of tractography for complex regions of interest analysis.
Literature
• Gilmore JH, Gerig G, Specter B, Charles HC, Wilber JS, Hertzberg BS, Kliewer MA (2001a): Neonatal cerebral ventricle
volume: a comparison of 3D ultrasound and magnetic resonance imaging. Ultrasound Med and Biol 27:1143-1146.
Preliminary Results UNC Neonate Study
Brain Tissue Volume Neonates
• Zhai G, Lin W, Wilber K, Gerig G, Gilmore JH (2003): Comparison of regional white matter fractional anisotrophy in healthy
neonates and adults using a 3T head-only scanner. Radiology 229, 2003, pp. 673-681
600.00
500.00
400.00
wm-myel
300.00
csf
200.00
gm
100.00
cases
n40
n33
n32
n31
n26
n25
n23
n18
n10
n0002
0.00
• Warfield, S., Kaus, M., Jolesz, F., Kikinis, R.: Adaptive template moderated spa-tially varying statistical classification. In
Wells, W.M.e.a., ed.: Medical Image Computing and Computer-Assisted Intervention (MICCAI’98). Volume 1496 of LNCS.,
Springer 1998
• Van Leemput, K., Maes, F., Vandermeulen, D., Suetens, P.: Automated model-based tissue classification of MR images of
the brain. IEEE Transactions on Medical Imaging 18 (1999) 897–908
wm-nonmyel
n0001
volume (ml)
• Preliminary Study: 20 normal neonates
(10 males, 10 females)
• Age 16 ± 4 days
• Siemens 3T head-only scanner
• Neonates were fed prior to scanning,
swaddled, fitted with ear protection and
had their heads fixed in a vac-fix device
• A pulse oximeter was monitored by a
physician or research nurse
• Most neonates slept during the scan
• Motion-free scans in 13-15 infants
• Conte Center: Total of 120 infants
• Huppi PS, Warfield S, Kikinis R, Barnes PD, Zientara GP, Jolesz FA, Tsuji MK, Volpe JJ (1998b): Quantitative magnetic
resonance imaging of brain development in premature and normal newborns. Ann Neurol 43: 224-235.
• Pierre Fillard, John Gilmore, Weili Lin, Guido Gerig, "Quantitative Analysis of White Matter Fiber Properties along Geodesic
Paths", Lecture Notes in Computer Science LNCS #2879 Springer, Nov. 2003, pp. 16-23
• Guido Gerig, Marcel Prastawa, Weili Lin and John Gilmore, "Assessing Early Brain Development in
Neonates by Segmentation of High-Resolution 3T MRI", LNCS #2879, Springer, Nov. 2003,
Supported by NIH Conte Center MH064065, Neurodevelopmental
Disorders Research Center HD 03110 and the Theodore and Vada
Stanley Foundation.