Bio‐SCOPE: fast biexponential T_1ρ mapping of the brain using signal‐compensated low‐rank plus sparse matrix decomposition

Abstract

Purpose To develop and evaluate a fast imaging method based on signal‐compensated low‐rank plus sparse matrix decomposition to accelerate data acquisition for biexponential brain T1ρ mapping (Bio‐SCOPE). Methods Two novel strategies were proposed to improve reconstruction performance. A variable‐rate undersampling scheme was used with a varied acceleration factor for each k‐space along the spin‐lock time direction, and a modified nonlinear thresholding scheme combined with a feature descriptor was used for Bio‐SCOPE reconstruction. In vivo brain T1ρ mappings were acquired from 4 volunteers. The fully sampled k‐space data acquired from 3 volunteers were retrospectively undersampled by net acceleration rates (R) of 4.6 and 6.1. Reference values were obtained from the fully sampled data. The agreement between the accelerated T1ρ measurements and reference values was assessed with Bland‐Altman analyses. Prospectively undersampled data with R = 4.6 and R = 6.1 were acquired from 1 volunteer. Results T1ρ‐weighted images were successfully reconstructed using Bio‐SCOPE for R = 4.6 and 6.1 with signal‐to‐noise ratio variations <1 dB and normalized root mean square errors <4%. Accelerated and reference T1ρ measurements were in good agreement for R = 4.6 (T1ρs: 18.6651 ± 1.7786 ms; T1ρl: 88.9603 ± 1.7331 ms) and R = 6.1 (T1ρs: 17.8403 ± 3.3302 ms; T1ρl: 88.0275 ± 4.9606 ms) in the Bland‐Altman analyses. T1ρ parameter maps from prospectively undersampled data also show reasonable image quality using the Bio‐SCOPE method. Conclusion Bio‐SCOPE achieves a high net acceleration rate for biexponential T1ρ mapping and improves reconstruction quality by using a variable‐rate undersampling data acquisition scheme and a modified soft‐thresholding algorithm in image reconstruction.

Performance Comparison of Compressed Sensing Algorithms for Accelerating T1ρ Mapping of Human Brain

“…The results from this study suggested that the STFD technique worked better than L + S for this application. In a more recent paper by Zhu et al, 37 a variable rate sampled L + S technique for biexponential brain T 1ρ mapping was used with a T 1ρ estimation error as low as 2.3% for AF = 6, which is slightly better than the error we report at a comparable AF of 5.…”

A 4‐minute solution for submillimeter whole‐brain T1ρ quantification

“…In this study, the acquisition time is largely reduced at the order of 3.5 minutes, and therefore can effectively reduce the probability of subject motion compared with the fully sampled scan with 13 minutes and 20 seconds. In addition, we have shown in our previous study 38 that the signal‐compensated low‐rank plus sparse matrix decomposition method has the potential to compensate for motion. Therefore, the 4‐minute T 1ρ solution may reduce the sensitivity to motion.…”

Three‐Dimensional GRE T1ρ mapping of the brain using tailored variable flip‐angle scheduling

“…Relative SNR values of tailored VFA scheduling versus MAPSS for the 2D in vivo data were measured to be 1.2, 1.4, 1.9, and 4.5 for VPS = 32, 64, 128, and 256, respectively, compared with 1.2, 1.4, 2.0, and 4.5 estimated by simulation, and average T 1ρ quantification errors for VPS = 64, 128, and 256 were measured in vivo to be, respectively, 1.0%, 1.3%, and 2.0% with application of CSF nulling compared with the maximum errors of 0.9%, 1.1%, and 2.0% estimated by simulation. Note that tailored VFA scheduling is compatible with acceleration techniques such as partial Fourier, parallel imaging, and compressed sensing, which may be used to further improve SNR efficiency …”