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Accelerated simultaneous T2 and T2* mapping of multiple sclerosis lesions using compressed sensing reconstruction of radial RARE-EPI MRI

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Item Type:Article
Title:Accelerated simultaneous T2 and T2* mapping of multiple sclerosis lesions using compressed sensing reconstruction of radial RARE-EPI MRI
Creators Name:Herrmann, C.J.J., Starke, L., Millward, J.M., Kuchling, J., Paul, F. and Niendorf, T.
Abstract:(1) BACKGROUND: Radial RARE-EPI MRI facilitates simultaneous T2 and T2* mapping (2in1-RARE-EPI). With modest undersampling (R = 2), the speed gain of 2in1-RARE-EPI relative to Multi-Spin-Echo and Multi-Gradient-Recalled-Echo references is limited. Further reduction in scan time is crucial for clinical studies investigating T2 and T2* as imaging biomarkers. We demonstrate the feasibility of further acceleration, utilizing compressed sensing (CS) reconstruction of highly undersampled 2in1-RARE-EPI. (2) METHODS: Two-fold radially-undersampled 2in1-RARE-EPI data from phantoms, healthy volunteers (n = 3), and multiple sclerosis patients (n = 4) were used as references, and undersampled (Rextra = 1–12, effective undersampling Reff = 2–24). For each echo time, images were reconstructed using CS-reconstruction. For T2 (RARE module) and T2* mapping (EPI module), a linear least-square fit was applied to the images. T2 and T2* from CS-reconstruction of undersampled data were benchmarked against values from CS-reconstruction of the reference data. (3) RESULTS: We demonstrate accelerated simultaneous T2 and T2* mapping using undersampled 2in1-RARE-EPI with CS-reconstruction is feasible. For Rextra = 6 (TA = 01:39 min), the overall MAPE was ≤8% (T2*) and ≤4% (T2); for Rextra = 12 (TA = 01:06 min), the overall MAPE was <13% (T2*) and <5% (T2). (4) CONCLUSION: Substantial reductions in scan time are achievable for simultaneous T2 and T2* mapping of the brain using highly undersampled 2in1-RARE-EPI with CS-reconstruction.
Keywords:MRI, Parametric Mapping, Transversal Relaxation Time, Brain, Multiple Sclerosis, Compressed Sensing
Source:Tomography
ISSN:2379-1381
Publisher:MDPI
Volume:9
Number:1
Page Range:299-314
Date:31 January 2023
Official Publication:https://doi.org/10.3390/tomography9010024
PubMed:View item in PubMed

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