By: Tracy Ssali
Medical Biophysics 3970z
April 4th 2012
Supervisors: Keith St. Lawrence, PhD
Udunna Anazodo, PhD candidate

Brain Tissue consists of Grey Matter (GM)
White Matter (WM) and Cerebral Spinal Fluid
(CSF)

Perfusion in the brain is indicative of function
 Irregular flow in grey matter is indicative of
disease state [1]

Arterial Spin Labeling is a novel technique
used to measure perfusion in the brain

Established techniques require radioactive
exogenous tracers which cannot be used on
certain patient populations, and require long
clearance times.[2]

ASL MRI uses magnetized water molecules in
arterial blood as a tracer to measure tissue
perfusion non-invasively

Creating the control image

Creating the tagged image
 Arterial blood is magnetically labeled using
radiofrequency pulses
 A delay time is allowed for the blood to reach the
brain
 When the labeled water interacts with the
magnetic field, it affects the signal being
produced
Subtract
ASL Image ≈ CBF
Adapted from Wolf and Detre Neurother Vol. 4, 346–359, July 2007

Perfusion images are
taken in quick
succession
 Information from the
labeled blood must be
captured before it
relaxes
 Blood water has a half
life of around 1-2s[3]
Pettersen Br J Radiology 2006

Point spread blurring

Resolution is not fine
enough to resolve GM,
WM and CSF
 Voxel size is
approximately 3 x 3 x
3mm [2]

Partial Volume Effects (PVE) correction
 Estimates the partial signal contribution based on
the contrast information from anatomical MRI
image volume

Kernel Regression Algorithm
 Based on the size of the kernel the algorithm
assesses a radius around the centre point to
reassign a partial volume


Signal – Mean signal of GM, WM or CSF
Noise – Standard deviation
40
20
Deibler et al AJNR march 2008

To measure the signal to noise ratio before
and after the partial volume effects
correction

5 Chronic Regional
Pain Syndrome
Patients (CRPS)

Image Preprocessing
 Remove the pixels
representing the skull
 Motion correction
Wolf and Detre Neurother Vol. 4, 346–359, July 2007

PVE correction
 Implemented an In-house written MATLAB code
created by Asllani et al. [2]
 Images from 5CRPS were processed using a
kernel size of 5 and 9

Kernel filter
 Adjust the kernel size from to 5, 7, 9, 11 and 15
 1 patient’s data


Significant
decrease
(P<0.05) in the
SNR
Variation in
the voxels due
to the noise
could have
prevented the
code from
working as
intended
Results & Discussion
SNR Before and After PVE
correction
Signal to Noise Ratio
K=5
2
1.5
1
0.5
0
Subject 1 Subject 2 Subject 3 Subject 4 Subject 5
CRPS Patient
Uncorrected SNR
PVE corrected SNR



Inconsistent
Results
There is no
significant
difference
(P>0.05)
It is likely that
the algorithm is
not functioning
as intended
Results & Discussion
SNR Before and After PVE
correction
Signal to Noise Ratio
K=9
3
2.5
2
1.5
1
0.5
0
Subject 1 Subject 2 Subject 3 Subject 4 Subject 5
CRPS Patient
Uncorrected SNR
PV corrected SNR
Subject 5 Results & Discussion

Larger kernel
have a greater
SNR
Small kernel
sizes are
sensitive to
noise and
variance
Kernel Size vs SNR
4
Signal to Noise Ratio

3.5
3
2.5
2
1.5
1
0.5
0
5
7
9
11
Kernel Size
Uncorrected Signal
Corrected Signal
15

The SNR decreased after the PVE correction

Kernel size needs to be chosen carefully

Our in-house implementation of the PVE
correction needs to be fine tuned

[1] Tracy, Melzer R. "Arterial Spin Labelling Reveals an Abnormal Cerebral
Perfusion Pattern in Parkinson’s Disease." Brain 134.3 (2011): 845-55.

[2] Asllani, Iris, Ajna Borogovac, and Truman R. Brown. "Regression
Algorithm Correcting for Partial Volume Effects in Arterial Spin Labeling
MRI." Magnetic Resonance in Medicine 60.6 (2008): 1362-371.

[3] Xu, Guofan, Howard A. Rowley, Gaohong Wu, David C. Alsop, Ajit
Shankaranarayanan, Maritza Dowling, Bradley T. Christian, Terrence R.
Oakes, and Sterling C. Johnson. "Reliability and Precision of Pseudocontinuous Arterial Spin Labeling Perfusion MRI on 3.0 T and Comparison
with 15O-water PET in Elderly Subjects at Risk for Alzheimer’s
Disease." NMR in Biomedicine 23.3 (2010): 286-93. Print.
Questions?