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Optimization of hyperparameters for SMS reconstruction. Magn Reson Imaging 2020 Nov;73:91-103

Date

08/25/2020

Pubmed ID

32835848

DOI

10.1016/j.mri.2020.08.006

Scopus ID

2-s2.0-85089907300 (requires institutional sign-in at Scopus site)   2 Citations

Abstract

PURPOSE: Simultaneous multi-slice (SMS) imaging accelerates MRI data acquisition by exciting multiple image slices with a single radiofrequency pulse. Overlapping slices encoded in acquired signal are separated using a mathematical model, which requires estimation of image reconstruction kernels using calibration data. Several parameters used in SMS reconstruction impact the quality and fidelity of final images. Therefore, finding an optimal set of reconstruction parameters is critical to ensure that accelerated acquisition does not significantly degrade resulting image quality.

METHODS: Gradient-echo echo planar imaging data were acquired with a range of SMS acceleration factors from a cohort of five volunteers with no known neurological pathology. Images were collected using two available phased-array head coils (a 48-channel array and a reduced diameter 32-channel array) that support SMS. Data from these coils were identically reconstructed offline using a range of coil compression factors and reconstruction kernel parameters. A hybrid space (k-x), externally-calibrated coil-by-coil slice unaliasing approach was used for image reconstruction. The image quality of the resulting reconstructed SMS images was assessed by evaluating correlations with identical echo-planar reference data acquired without SMS. A finger tapping functional MRI (fMRI) experiment was also performed and group analysis results were compared between data sets reconstructed with different coil compression levels.

RESULTS: Between the two RF coils tested in this study, the 32-channel coil with smaller dimensions clearly outperformed the larger 48-channel coil in our experiments. Generally, a large calibration region (144-192 samples) and small kernel sizes (2-4 samples) in ky direction improved image quality. Use of regularization in the kernel fitting procedure had a notable impact on the fidelity of reconstructed images and a regularization value 0.0001 provided good image quality. With optimal selection of other hyperparameters in the hybrid space SMS unaliasing algorithm, coil compression caused small reduction in correlation between single-band and SMS unaliased images. Similarly, group analysis of fMRI results did not show a significant influence of coil compression on resulting image quality.

CONCLUSIONS: This study demonstrated that the hyperparameters used in SMS reconstruction need to be fine-tuned once the experimental factors such as the RF receive coil and SMS factor have been determined. A cursory evaluation of SMS reconstruction hyperparameter values is therefore recommended before conducting a full-scale quantitative study using SMS technologies.

Author List

Muftuler LT, Arpinar VE, Koch K, Bhave S, Yang B, Kaushik S, Banerjee S, Nencka A

Authors

Kevin M. Koch PhD Center Director, Professor in the Radiology department at Medical College of Wisconsin
Lutfi Tugan Muftuler PhD Associate Professor in the Neurosurgery department at Medical College of Wisconsin
Andrew S. Nencka PhD Director, Associate Professor in the Radiology department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Acceleration
Algorithms
Artifacts
Brain
Calibration
Data Compression
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Radio Waves