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

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

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

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

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

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.

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

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.

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

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

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.

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.

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.

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

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