1. Effect of Flip Angle Error for T1 Bias Correction in MRI Fat Fraction Estimation
March 22, 2011
Issac Yang
Supervisor: Charles McKenzie, PhD
Department of Medical Biophysics
University of Western Ontario

2. Background and Motivation
Non-Alcoholic Fatty Liver Disease (NAFLD) is becoming the most common chronic liver disease
Affects 30% of the Western population
Fat depositing in liver cells (steatosis)
Associated with metabolic syndromes
Obesity, type II diabetes
Normal
NAFLD is becoming, or not currently the most common chronic liver disease, affecting 30% of the western population
Involves fat deposits in liver cells – called steatosis
Point out the whites are fat deposits, which are not seen in normal liver tissue
NAFLD is associated with other metabolic syndromes such as obesity and type 2 diabetes
Fatty Liver

3. Background and Motivation
NAFLD is asymptomatic
Current procedure of detection is liver biopsy
Invasive procedure
Complications involves minor bleeding, hospitalization, and (rarely) death
Steatosis distribution is inhomogeneous
Prone to sampling error
MRI offers a non-invasive alternative
Unaffected by sampling error
NAFLD is asymptomatic.
Current method of detection and monitoring NAFLD is liver biospy
A painful procedure where a needle is used to obtain a liver sample, and analysed in a path lab.
Complications from this procedure involves bleeding, some cases requiring hospitalization and even death.
Another big problem is the inhomogeneous distribution of steatosis makes biopsy prone to sampling error
-show ROIs of another image, where one part has steatosis and another part doesn’t

4. Obtaining Fat Fractions
Fat + Water
An MRI technique called IDEAL was used
Allows production of separate fat and water signal images.
IDEAL
MRI technique called IDEAL is used to separate the acquired images into separate fat and water images.
Using these images, a fat fraction map is generated by dividing the fat image over the sum of fat and water images.
Fat Fraction = +
Water
Fat

5. Bias in Fat Fraction
Signals in each pixel is characterized by the equation
T1 values for fat is significantly different from T1 of water
Typically: T1f=382ms, T1w=809ms at 3.0 T in vivo
Difference in T1 values cause unequal weighting of water and fat signals in fat fraction equation
Signal is calculated by the equation shown here.
Aside from the relative concentration of protons in the voxel, it is also dependent on two other parameters:
-*CLICK* T1, a magnetic property of the nucleus, the spin-lattice relaxation time of the protons
-*CLICK* Flip angle, a parameter we set prior to the scan to set the weighting of T1 in the signal.
T1 for water and fat are significantly different. This difference causes unequal weighting of signals in fat fraction.
- Flip to next slide showing the effect

6. Normally, you’d expect the fat fraction we measure to be the true fat fraction i.e. in a voxel of 50% fat and 50% water, we expect to measure 50% fat and 50% water.
Due to difference in T1, we get an overestimation of fat fraction, or a bias
As T1 weighting increases with higher flip angle, we get an increase in the bias.

7. Current Method T1 weighting in the signal increases with flip angle
Current method of mitigating bias is to use a low flip angle.
Decreases signal intensity
Reduced Signal to Noise Ratio (SNR)
T1 weighting, or the influence of T1 in the acquired signal, scales with flip angle.
So…the current method of avoiding the bias is to use a low flip angle. Currently, this value is 5, but it is moving towards 3.
However, the trade off for using a low flip angle is reduced signal intensity, due to the loss of T1 contribution to the signal.
As a result, this method suffers from low SNR and loss of precision for the trade of increased accuracy
The current method of avoiding this bias is to decrease the influence of T1 by using low flip angles, which used to be 5, but 3 is now being considered.
The price being paid is a loss of precision due to decreased signal to noise ratio, or SNR

8. Bias Correction
Bias can be reduced by performing corrections to the image by using estimated T1 values.
This method assumes known and uniform flip angle
Untrue for fields of 3.0T and above due to RF pulse inhomogeneity
Flip angle measurements should be performed to further reduce error
One of our previous experiments have shown that we can use an estimated T1 value as part of a correction factor to reduce the obtained fat fraction bias.
This method assumes known and uniform flip angle
Untrue for fields of 3.0T and above due to inhomogeneity of radiofrequency pulse
Which is problematic, because the flip angle is set on the scanner console prior to the scan.
Flip angle measurements should be performed along with the scan to reduce any numerical errors in the correction.

9. Method Fat Fraction Map Fat Image Bias Correction Corrected Fat Image
T1f Estimate
Fat Image
Bias Correction
Corrected Fat Image
Fat Fraction Map
T1w Estimate
Bias Correction
Corrected Water Image
Water Image
We propose that, along with the fat and water images we obtain from IDEAL, we also acquire a flip angle map based on a double angle Look-Locker technique developed by Dr Trevor Wade as his PhD thesis.
Now, with known flip angle information, we can use the flip angle map, along with estimate T1 values to generate correction factors and obtain corrected fat and water images. Using these, we obtain a bias reduced fat fraction map.
We performed these steps on a set of phantoms of varying water and peanut oil volumes, to represent different fat fractions. We prescribed a flip angle of 12 for this scan.
Flip Angle Map

10. Results
Flip angle measurements show true flip angle to be 9 degrees on average
Prescribed 12 degrees
25% lower than expected
T1 measurements yielded:
T1w=274ms, T1f=181ms
Estimated values: T1w=350ms, T1f=200ms
Our obtained flip angle map show that the true flip angle within the slice is 9 degrees.
- We wanted 12 degrees. The flip angle turned out to be 25% lower than expected
Flip Angle Map

11. Correction Results Here are the correction results for the phantoms
It can be seen that by applying the normal T1 correction, measured fat fraction was brought closer to the true fat fraction.
However, by acquiring the true flip angle measurements via flip angle mapping, it can be seen in the mid fat fraction phantoms that the measured fat fraction was brought closer to the true value.

12. Discussion
Measured fat fractions was brought closer to the true fat fraction value for phantoms
It can be seen that, from our phantom measurements, fat fraction bias was further decreased when flip angle mapping was incorporated to generate fat fraction measurements.

13. Conclusion
Experiments suggest that including flip angle mapping into imaging protocol would decrease fat fraction bias
In conclusion, we have shown in our experiments that by incorporating flip angle mapping into our acquisition protocol, we can improve the T1 bias correction technique by further reducing bias.

14. Acknowledgement McKenzie Lab Bartha Lab Dr. Charles McKenzie
Curtis Wiens
Dr. Trevor Wade
Bryan Addeman
Dr. Lanette Friesen-Waldner
Yifan Cui
Samantha Flood
Bartha Lab
Dr. Robert Bartha
Dr. John Drozd
Jacob Penner
I’d like to thank members of my lab, as well as those of Dr Rob Bartha’s lab for helping me with analysing spectroscopy data of phantoms

15. Thank You For Your Attention
Questions?