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Using 3D-SHORE and MAP-MRI to Obtain Both
Tractography and Microstructural Contrast
from a Clinical di usion MRI Acquisition
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Rutger Fick , Mauro Zucchelli , Gabriel Girard , Maxime Descoteaux , Gloria Menegaz , Rachid Deriche
1
1
Athena, INRIA Sophia Antipolis, France
2
University of Verona, Italy
Always Spread Your Sample On More Shells
No Increase in Acquisition Time
More Recovered Tissue Information
Acquisitions in Di usion MRI (dMRI)
are time consuming.
Current clinical protocols measure
between 30 - 90 dMRI images per
patient. Depending on the scanner
this can take 10 - 30 min.
2
The strength and orientation of the di usion gradients over
dMRI images must be spread to get the most information.
Current Clinical Practice
(Single-Shell)
What Is More Useful
(Multi-Shell)
b-value (s/mm2)
b-value (s/mm2)
b=0
b=0
Multi-Shell
dMRI Signal
MAP-MRI
3D-SHORE
Di usion
Propagator
Pore Model
Tissue Structure
Information
MAP-MRI2 is a functional basis that simultaneously describes the
3D di usion signal attenuation
and di usion propagator
as a series of basis functions.
Here wave vector is related to b-value as
.
MAP-MRI's basis functions
and
are Fourier Transforms
of each other, so the dMRI signal and di usion propagator are
described by the same coe cients.
b=1000
No Data
The basis is tted using regularized least squares 3. Its rst basis
function, i.e.
, is equivalent to an anisotropic DTI tensor.
3D-SHORE is a special case of MAP-MRI where
is isotropic.
b=2000
b=3000
b=3000
From Multi-Shell to Microstructure
The di usion propagator links the dMRI signal to the
tissue microstructure, and represents the probability that a
particle will travel a distance in the given di usion time.
We must get the most out of this investment
1
With the same number of images over multiple shells ,
we obtain the same tractography results as single-shell
dMRI, but we gain access to microstructural contrasts.
3
SCIL, Univerity of Sherbrooke, Canada
Main Contributions
Introduction
MRI Scanner
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Peak and Tractography Results
We compare peak recovery between (single shell) constrained spherical
deconvolution (CSD)4, 3D-SHORE and MAP-MRI (below). We nd:
- 3D-SHORE and MAP-MRI can infer smaller crossings than CSD.
- MAP-MRI has estimation bias (green = ground truth, red = recovered)
Di usion Propagator to White Matter Directionality
We obtain the orientation distribution function (ODF) by integrating
radially.
is a sharpening factor.
Di usion Propagator to Microstructure Parameters
We model tissue as pores (astrocytes as sphere, axons as cylinders)
Given long di usion time, we estimate mean pore volume and
mean cross-sectional area through the return to origin and axis
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probability (RTOP and RTAP) :
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Microstructural Contrasts
Despite MAP-MRI's bias in angle, it's signal recovery is better than
3D-SHORE. We use the Human Connectome Project (HCP) data 6.
We can recover RTOP and RTAP with just 60 samples.
We use Tractometer5 on the 2013 ISBI challenge data (below) to
quantify tractography (SNR=10,20,30). There are 27 arti cial bundles.
(T) ISBI challenge data. (L) Seed
points in green. (M/R) (in)valid connection.
Conclusion
b-max
3,000
Above: MGH HCP data. b-values=1000,3000,5000,
10.000 s/mm2 with 64, 64, 128, 256 samples.
The relative di erence in axon radius remains even with a
(clinically feasable) b-value of just 3000 s/mm2.
By just spreading the same number of dMRI samples over multiple
shells, we can still recover accurate tractography, and we gain access
to tissue constrasts such as the axon radius, which should prove
helpful in understanding normal and pathologic nervous tissue.
ISBI, April 2015, New York City, New York
We also estimate the axon
radius from RTAP in di erent
parts of the Corpus Callosum.
In agreement with literature7,
we estimate larger axon
radii in the midbody than
in the genu or splenium.
radius ( m)
b-max
5,000
We nd (graphs below) that 3D-SHORE and
CSD are similar in VCCR, and 3D-SHORE is
always higher in CSR. MAP-MRI is never best.
Above: WU-Minn HCP data. b-values=1000,2000,3000 s/mm 2 with 90 samples per shell.
b-max
10,000
We use 2 evaluation criteria 7:
- Valid Connection to Connection Ratio (VCCR)
- Connection to Seed Ratio (CSR)
were provided [in part] by the Human Connectome Project. This research has
Acknowledgements Data
been partly supported by project MOSIFAH (ANR-13-MONU-0009-01)
Caruyer et al. MRM, 2013. 2. Ozarslan et al. Neuroimage, 2013. 3. Fick et al, ISBI, 2015. 4.
References 1.
Tournier et al. NeuroImage, 2007. 5. Cote et al. MIA, 2013. 6. Van Essen et al. NeuroImage, 2013.
7. Aboitz et al, Brain Research, 1992.
Contact: rutger. [email protected], url: http://www-sop.inria.fr/athena