Accelerating 3D-T mapping of cartilage with CS is feasible up to AF of 10 when using STFD, EXP or L+S SFD regularizers. These three best CS methods performed satisfactorily on synthetic phantom and in vivo knee cartilage for AFs up to 10, with T error of 6.5%.

Purpose To demonstrate the feasibility of biexponential T1ρ relaxation mapping of human knee cartilage in-vivo. Methods A 3D customized Turbo-Flash sequence was used to acquire T1ρ-weighted images from healthy volunteers employing a standard 3T MRI clinical scanner. Series of T1ρ-weighted images were fitted using monoexponential as well as biexponential models with two- and four- parametric non-linear approach, respectively. Non-parametric Kruskal-Wallis and Mann-Whitney U statistical tests were used to evaluate the regional relaxation and gender differences respectively with a significance level, p-value of 0.05. Results Biexponential relaxations were detected in the cartilage of all volunteers. Short/long relaxation components of T1ρ were estimated to be 6.9/51.0ms respectively. Similarly, the fractions of short/long T1ρ were 37.6/62.4%. The monoexponential relaxation of T1ρ was 32.6ms. The experiments showed good repeatability with coefficient of variation (CV) of less than 20% Conclusion Biexponential relaxation model better fit to T1ρ relaxation decay than monoexponential model in the knee cartilage(R2.4.1). Biexponential T1ρ components could potentially be used to increase the specificity to detect early osteoarthritis by measuring different water compartments and their fractions.

Accelerating biexponential 3D-T mapping of knee cartilage with CS is feasible. The best results were obtained by STFD, EXP, and L + S SFD regularizers combined with spatial prefiltering. These 3 CS methods performed satisfactorily on synthetic phantom as well as in vivo knee cartilage for AFs up to 10, with median error below 15%.

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:809-819.

The spin-lattice relaxation time in the rotating frame (T 1ρ ) has shown sensitiveness to loss of proteoglycan content in the cartilage 1,2 and T 1ρ relaxation mapping can be useful for early detection of osteoarthritis (OA). 3 To produce good and stable T 1ρ maps, many T 1ρ -weighted images must be acquired, taking a long acquisition time if a good signalto-noise ratio (SNR) and small variance in the estimated parameters are desired.

Detection of multiple relaxation pools using MRI is useful in a number of neuro-pathologies including multiple sclerosis (MS), Alzheimer’s, and stroke. In this study we evaluate the feasibility of using T1ρ imaging for the detection of bi-exponential decays in the human brain. A prospective T1ρ imaging study was performed on model relaxation phantoms (eggs) and 7 healthy volunteers. The data was fitted using a single pool and a 2-pool model to estimate mono- and bi-exponential T1ρ maps, respectively. Bi-exponential decays were identified in the gray matter (GM) and white matter (WM) of the brain with 40.5% of GM, and 65.1% of WM pixels showing two T1ρ relaxation pools (significance level P < 0.05). Detection of T1ρ based bi-exponential decays in the brain provides complimentary information to T2 based contrast regarding the in vivo micro-environment in the brain.

Quantitative MRI can detect early biochemical changes in cartilage; however, the conventional techniques only measure one parameter (e.g., T 1 , T 2 , and T 1ρ ) at a time while also being comparatively slow. We implemented a 3D magnetic resonance fingerprinting (3D-MRF) technique for simultaneous, volumetric mapping of T 1 , T 2 , and T 1ρ in knee articular cartilage in under 9 min. It is evaluated on 11 healthy volunteers (mean age: 53 ± 9 years), five mild knee osteoarthritis (OA) patients (Kellgren-Lawrence (KL) score: 2, mean age: 60 ± 4 years), and the National Institute of Standards and Technology (NIST)/International Society for Magnetic Resonance in Medicine (ISMRM) system phantom. Proton density image, and T 1 , T 2, T 1ρ relaxation times, and B 1 + were estimated in the NIST/ISMRM system phantom as well as in the human knee medial and lateral femur, medial and lateral tibia, and patellar cartilage. The repeatability and reproducibility of the proposed technique were assessed in the phantom using analysis of the Bland-Altman plots. The intrasubject repeatability was assessed with the coefficient of variation (CV) and root mean square CV (rmsCV). The Mann-Whitney U test was used to assess the difference between healthy subjects and mild knee OA patients.The Bland-Altman plots in the NIST/ISMRM phantom demonstrated an average difference of 0.001% ± 015%, 1.2% ± 7.1%, and 0.47% ± 3% between two scans from the same 3-T scanner (repeatability), and 0.002% ± 015%, 0.62% ± 10.5%, and 0.97% ± 14% between the scans acquired on two different 3-T scanners (reproducibility) for T 1 , T 2 , and T 1ρ , respectively. The in vivo knee study showed excellent repeatability with rmsCV less than 1%, 2%, and 1% for T 1 , T 2 , and T 1ρ , respectively. T 1ρ relaxation time in the mild knee OA patients was significantly higher (p < 0.05) than in healthy subjects. The proposed 3D-MRF sequence is fast, reproducible, robust to B 1 + inhomogeneity, and can simultaneously measure the T 1 , T 2 , T 1ρ , and B 1 + volumetric maps of the knee joint in a single scan within a clinically feasible scan time.

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.