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Accelerated mono‐ and biexponential 3D‐T1ρ relaxation mapping of knee cartilage using golden angle radial acquisitions and compressed sensing
Author(s) -
Zibetti Marcelo V. W.,
Sharafi Azadeh,
Otazo Ricardo,
Regatte Ravinder R.
Publication year - 2020
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.28019
Subject(s) - cartesian coordinate system , sampling (signal processing) , exponential function , principal component analysis , mathematics , physics , mathematical analysis , geometry , statistics , optics , detector
Purpose To use golden‐angle radial sampling and compressed sensing (CS) for accelerating mono‐ and biexponential 3D spin‐lattice relaxation time in the rotating frame (T 1ρ ) mapping of knee cartilage. Methods Golden‐angle radial stack‐of‐stars and Cartesian 3D‐T 1ρ ‐weighted knee cartilage datasets ( n = 12) were retrospectively undersampled by acceleration factors (AFs) 2‐10. CS‐based reconstruction using 8 different sparsifying transforms were compared for mono‐ and biexponential T 1ρ ‐mapping of knee cartilage, including spatio‐temporal finite differences, wavelets, dictionary from principal component analysis, and exponential decay models, and also low rank and low rank plus sparse models (L+S). Complex‐valued fitting was used and Marchenko‐Pastur principal component analysis filtering also tested. Results Most CS methods performed well for an AF of 2, with relative median normalized absolute deviation below 10% for monoexponential and biexponential mapping. For monoexponential mapping, radial sampling obtained a median normalized absolute deviation below 10% up to AF of 10, while Cartesian obtained this level of error only up to AF of 4. Radial sampling was also better with biexponential T 1ρ mapping, with median normalized absolute deviation below 10% up to AF of 6. Conclusion Golden‐angle radial acquisitions combined with CS outperformed Cartesian acquisitions for 3D‐T 1ρ mapping of knee cartilage, being it is a good alternative to Cartesian sampling for reducing scan time and/or improving image and mapping quality. The methods exponential decay models, spatio‐temporal finite differences, and low rank obtained the best results for radial sampling patterns.