Correction for the T1 effect incorporating flip angle estimated by Kalman filter in cardiac-gated functional MRI.
Saved in:
| Title: | Correction for the T1 effect incorporating flip angle estimated by Kalman filter in cardiac-gated functional MRI. |
|---|---|
| Authors: | Shin, Jaemin1, Ahn, Sinyeob1, Hu, Xiaoping1 |
| Source: | Magnetic Resonance in Medicine. Dec2013, Vol. 70 Issue 6, p1626-1633. 8p. |
| Abstract: | Purpose To develop an improved and generalized technique for correcting T1-related signal fluctuations (T1 effect) in cardiac-gated functional magnetie resonance imaging (fMRI) data with flip angle estimation. Theory and Methods Spatial maps of flip angle and T1 are jointly estimated from cardiac-gated time series using a Kalman filter. These maps are subsequently used for removing the T1 effect in the presence of B1 inhomogeneity. The new technique was compared with a prior technique that uses T1 only while assuming a homogeneous flip angle of 90°. The robustness of the new technique is demonstrated with simulated and experimental data. Results Simulation results revealed that the new method led to increased temporal signal-to-noise ratio across a large range of flip angles, T1s, and stimulus onset asynchrony means compared to the T1 only approach. With the experimental data, the new approach resulted in higher average gray matter temporal signal-to-noise ratio of seven subjects (84 vs. 48). The new approach also led to a higher statistical score of activation in the lateral geniculate nucleus ( P < 0.002). Conclusion The new technique is able to remove the T1 effect robustly and is a promising tool for improving the ability to map activation in fMRI, especially in subcortical regions. Magn Reson Med 70:1626-1633, 2013. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR] |
| Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!
