Purpose To develop a robust sequence that combines T1ρ and T2 quantifications and to examine the in-vivo repeatability and diurnal variation of T1ρ and T2 quantifications in knee cartilage. Materials and Methods Six healthy volunteers were scanned in the morning and afternoon on two days using a combined T1ρ and T2 quantification sequence developed in this study. Repeatability of T1ρ and T2 quantification was estimated using root-mean-square coefficients-of-variation (RMS-CV). T1ρ and T2 values from morning scans were compared to those from afternoon scans using paired t-tests. Results The overall RMS-CV of in-vivo T1ρ and T2 quantification was 5.3% and 5.2% respectively. The RMS-CV of AM scans was 4.2% and 5.0% while the RMS-CV of PM scans was 6.0% and 6.3% for T1ρ and T2 respectively. No significant difference was found between T1ρ or T2 values in the morning and in the afternoon. Conclusions A sequence that combines T1ρ and T2 quantification with scan time less than 10 minutes and is robust to B0 and B1 inhomogeneity was developed with excellent repeatability. For a cohort with low-level daily activity, although no significant diurnal variation of cartilage MR relaxation times was observed, the afternoon scans had inferior repeatability compared to morning scans.

OBJECTIVE To evaluate the longitudinal reproducibility and variations of cartilage T1ρ and T2 measurements using different coils, MR systems and sites. METHODS Single-Site study: Phantom data were collected monthly for up to 29 months on four GE 3T MR systems. Data from phantoms and human subjects were collected on two MR systems using the same model of coil; and were collected on one MR system using two models of coils. Multi-site study: Three participating sites used the same model of MR systems and coils, and identical imaging protocols. Phantom data were collected monthly. Human subjects were scanned and rescanned on the same day at each site. Two traveling human subjects were scanned at all three sites. RESULTS Single-Site Study: The phantom longitudinal RMS-CVs ranged from 1.8% to 2.7% for T1ρ and 1.8% to 2.8% for T2. Significant differences were found in T1ρ and T2 values using different MR systems and coils. Multi-Site Study: The phantom longitudinal RMS-CVs ranged from 1.3% to 2.6% for T1ρ and 1.2% to 2.7% for T2. Across three sites (n=16), the in-vivo scan-rescan RMS-CV was 3.1% and 4.0% for T1ρ and T2, respectively. Phantom T1ρ and T2 values were significantly different between three sites but highly correlated (R>0.99). No significant difference was found in T1ρ and T2 values of traveling controls, with cross-site RMS-CV as 4.9% and 4.4% for T1ρ and T2, respectively. CONCLUSION With careful quality control and cross-calibration, quantitative MRI can be readily applied in multi-site studies and clinical trials for evaluating cartilage degeneration.

Purpose Quantitative T1ρ imaging is beneficial for early detection for osteoarthritis, but has seen limited clinical use due to long scan times. This work evaluates the feasibility of accelerated T1ρ mapping for knee cartilage quantification using a combination of compressed sensing (CS) and data-driven parallel imaging (ARC). Methods A sequential combination of ARC and CS, both during data acquisition and reconstruction, was used to accelerate the acquisition of T1ρ maps. Phantom, ex vivo (porcine knee) and in vivo (human knee) imaging was carried out on a GE 3T MR750 scanner. T1ρ quantification post CS-accelerated acquisition was compared with non CS-accelerated acquisition for various cartilage compartments. Results Accelerating image acquisition using CS did not introduce major deviations in quantification. The coefficient of variation for the root mean squared error (CV(RMSE)) increased with increasing acceleration, but for in vivo measurements, it stayed under 5% for net acceleration factor up to 2, where the acquisition was 25% faster than the reference (only ARC). Conclusion To the best of our knowledge this is the first implementation of CS for in vivo T1ρ quantification. These early results show that this technique holds great promise in making quantitative imaging techniques more accessible for clinical applications.

The purpose of this work was to validate ventilation-weighted (VW) and perfusion-weighted (QW) Fourier decomposition (FD) magnetic resonance imaging (MRI) with hyperpolarized (3)He MRI and dynamic contrast-enhanced perfusion (DCE) MRI in a controlled animal experiment. Three healthy pigs were studied on 1.5-T MR scanner. For FD MRI, the VW and QW images were obtained by postprocessing of time-resolved lung image sets. DCE acquisitions were performed immediately after contrast agent injection. (3)He MRI data were acquired following the administration of hyperpolarized helium and nitrogen mixture. After baseline MR scans, pulmonary embolism was artificially produced. FD MRI and DCE MRI perfusion measurements were repeated. Subsequently, atelectasis and air trapping were induced, which followed with FD MRI and (3)He MRI ventilation measurements. Distributions of signal intensities in healthy and pathologic lung tissue were compared by statistical analysis. Images acquired using FD, (3)He, and DCE MRI in all animals before the interventional procedure showed homogeneous ventilation and perfusion. Functional defects were detected by all MRI techniques at identical anatomical locations. Signal intensity in VW and QW images was significantly lower in pathological than in healthy lung parenchyma. The study has shown usefulness of FD MRI as an alternative, noninvasive, and easily implementable technique for the assessment of acute changes in lung function.

Purpose To accelerate T1ρ quantification in cartilage imaging using combined compressed sensing with iterative locally adaptive support detection and JSENSE. Methods To reconstruct T1ρ images from accelerated acquisition at different time of spin-lock (TSLs), we propose an approach to combine an advanced compressed sensing (CS) based reconstruction technique, LAISD (Locally-Adaptive Iterative Support Detection), and an advanced parallel imaging technique, JSENSE. Specifically, the reconstruction process alternates iteratively among local support detection in the domain of principal component analysis, compressed sensing reconstruction of the image sequence, and sensitivity estimation with JSENSE. T1ρ quantification results from accelerated scans using the proposed method are evaluated using in vivo knee cartilage data from bi-lateral scans of three healthy volunteers. Result T1ρ maps obtained from accelerated scans (acceleration factors of 3 and 3.5) using the proposed method showed results comparable to conventional full scans. The T1ρ errors in all compartments are below 1%, which is well below the in vivo reproducibility of cartilage T1ρ reported from previous studies. Conclusion The proposed method can significantly accelerate the acquisition process of T1ρ quantification on human cartilage imaging without sacrificing accuracy, which will greatly facilitate the clinical translation of quantitative cartilage MRI.