Development and stability analysis of carpal kinematic metrics from 4D magnetic resonance imaging.

OBJECTIVE: To develop MRI-derived carpal kinematic metrics and investigating their stability. METHODS: The study used a 4D MRI method to track scaphoid, lunate, and capitate movements in the wrist. A panel of 120 metrics for radial-ulnar deviation and flexion-extension was created using polynomial models of scaphoid and lunate movements relative to the capitate. Intraclass correlation coefficients (ICCs) analyzed intra- and inter-subject stability in 49 subjects, 20 with and 29 without wrist injury history. RESULTS: Comparable degrees of stability were observed across the two different wrist movements. Among the total 120 derived metrics, distinct subsets demonstrated high stability within each type of movement. For asymptomatic subjects, 16 out of 17 metrics with high intra-subject stability also showed high inter-subject stability. The differential analysis of ICC values for each metric between asymptomatic and symptomatic cohorts revealed specific metrics (although relatively unstable) exhibiting greater variability in the symptomatic cohort, thereby highlighting the impact of wrist conditions on the variability of kinematic metrics. CONCLUSION: The findings demonstrate the developing potential of dynamic MRI for assessing and characterizing complex carpal bone dynamics. Stability analyses of the derived kinematic metrics revealed encouraging differences between cohorts with and without wrist injury histories. Although these broad metric stability variations highlight the potential utility of this approach for analyzing carpal instability, further studies are necessary to better characterize these observations.

Age and Gender-Dependence of Single-and Bi-Exponential T1ρ MR Parameters in Knee Ligaments.

BACKGROUND: There is limited understanding of differences in the composition and structure of ligaments between healthy males and females, and individuals of different ages. Females present higher risk for ligament injuries than males and there are conflicting reports on its cause. This study looks into T1ρ parameters for an explanation as it relates to proteoglycan, collagen, and water content in these tissues. PURPOSE: To investigate gender-related and age-related differences in T1ρ parameters in knee joint ligaments in healthy volunteers using a T1ρ -prepared zero echo-time (ZTE)-based pointwise-encoding time-reduction with radial acquisition (T1ρ -PETRA) sequence. STUDY TYPE: Prospective. POPULATION: The study group consisted of 22 healthy subjects (11 females, ages: 41 ± 18 years, and 11 males, ages: 41 ± 14 years) with no known inflammation, trauma, or pain in the knee joint. FIELD STRENGTH/SEQUENCE: A T1ρ -prepared 3D-PETRA sequence was used to acquire fat-suppressed images with varying spin-lock lengths (TSLs) of the knee joint at 3T. ASSESSMENT: Monoexponential, biexponential, and stretched-exponential 3D-PETRA-T1ρ parameters were measured in the anterior cruciate ligament (ACL), posterior cruciate ligament (PCL), and patellar tendon (PT) by manually drawing ROIs over the entirety of the tissues. STATISTICAL TESTS: Mann-Whitney U-tests were used to compare 3D-PETRA-T1ρ parameters in the ACL, PCL, and PT between males and females. Spearman correlation coefficients were used to determine the association between age and T1ρ parameters. Statistical significance was defined as P < 0.05. RESULTS: Significant correlations with age were found the three ligaments with most of the measured T1ρ parameters (rs = 0.28-0.74) with the exception of the short fraction in the PCL (P = 0.18), and the short relaxation time in the ACL (P = 0.58) and in the PCL (P = 0.14). DATA CONCLUSION: 3D-PETRA-T1ρ can detect age-related differences in monoexponential, biexponential, and stretched-exponential T1ρ parameters in three ligaments of healthy volunteers, which are thought to be related to changes in tissue composition and structure during the aging process. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

Development and Stability Analysis of Carpal Kinematic Metrics from 4D Magnetic Resonance Imaging.

INTRODUCTION: Wrist instability remains a common health concern. The potential of dynamic Magnetic Resonance Imaging (MRI) in assessing carpal dynamics associated with this condition is a field of ongoing research. This study contributes to this line of inquiry by developing MRI-derived carpal kinematic metrics and investigating their stability. METHODS: A previously described 4D MRI approach for tracking the movements of carpal bones in the wrist was deployed in this study. A panel of 120 metrics characterizing radial/ulnar deviation and flexion extension movements was constructed by fitting low order polynomial models of scaphoid and lunate degrees of freedom against that of the capitate. Intraclass Correlation Coefficients were utilized to analyze intra- and inter-subject stability within a mixed cohort of 49 subjects, including 20 with and 29 without a history of wrist injury. RESULTS: A comparable degree of stability across the two different wrist movements. Out of the total 120 derived metrics, distinct subsets demonstrated high stability within each type of movement. Among asymptomatic subjects, 16 out of 17 metrics with high intra-subject stability also showed high inter-subject stability. Interestingly, some quadratic term metrics, although relatively unstable within asymptomatic subjects, showed increased stability within this group, hinting at potential differentiation in their behavior across different cohorts. CONCLUSION: This study showed the developing potential of dynamic MRI to characterize complex carpal bone dynamics. Stability analyses of the derived kinematic metrics showed encouraging differences between cohorts with and without a history of wrist injury. Although these broad metric stability variations highlight the potential utility of this approach for analysis of carpal instability, further studies are necessary to better characterize these observations.

Three-dimensional multi-parameter brain mapping using MR fingerprinting.

The purpose of this study was to develop and test a 3D multi-parameter MR fingerprinting (MRF) method for brain imaging applications. The subject cohort included 5 healthy volunteers, repeatability tests done on 2 healthy volunteers and tested on two multiple sclerosis (MS) patients. A 3D-MRF imaging technique capable of quantifying T1, T2 and T1ρ was used. The imaging sequence was tested in standardized phantoms and 3D-MRF brain imaging with multiple shots (1, 2 and 4) in healthy human volunteers and MS patients. Quantitative parametric maps for T1, T2, T1ρ, were generated. Mean gray matter (GM) and white matter (WM) ROIs were compared for each mapping technique, Bland-Altman plots and intra-class correlation coefficient (ICC) were used to assess repeatability and Student T-tests were used to compare results in MS patients. Standardized phantom studies demonstrated excellent agreement with reference T1/T2/T1ρ mapping techniques. This study demonstrates that the 3D-MRF technique is able to simultaneously quantify T1, T2 and T1ρ for tissue property characterization in a clinically feasible scan time. This multi-parametric approach offers increased potential to detect and differentiate brain lesions and to better test imaging biomarker hypotheses for several neurological diseases, including MS.

Age-Dependent Changes in Knee Cartilage T1 , T2 , and T1p Simultaneously Measured Using MRI Fingerprinting.

BACKGROUND: Magnetic resonance fingerprinting (MRF) techniques have been recently described for simultaneous multiparameter cartilage mapping of the knee although investigation of their ability to detect early cartilage degeneration remains limited. PURPOSE: To investigate age-dependent changes in knee cartilage T1 , T2 , and T1p relaxation times measured using a three-dimensional (3D) MRF sequence in healthy volunteers. STUDY TYPE: Prospective. SUBJECTS: The study group consisted of 24 healthy asymptomatic human volunteers (15 males with mean age 34.9 ± 14.4 years and 9 females with mean age 44.5 ± 13.1 years). FIELD STRENGTH/SEQUENCE: A 3.0 T gradient-echo-based 3D-MRF sequence was used to simultaneously create proton density-weighted images and T1 , T2 , and T1p maps of knee cartilage. ASSESSMENT: Mean global cartilage and regional cartilage (lateral femur, lateral tibia, medial femur, medial tibia, and patella) T1 , T2 , and T1ρ relaxation times of the knee were measured. STATISTICAL TESTS: Kruskal-Wallis tests were used to compared cartilage T1 , T2 , and T1ρ relaxation times between different age groups, while Spearman correlation coefficients was used to determine the association between age and cartilage T1 , T2 , and T1ρ relaxation times. The value of P < 0.05 was considered statistically significant. RESULTS: Higher age groups showed higher global and regional cartilage T1 , T2 , and T1ρ . There was a significant difference between age groups in global cartilage T2 and T1ρ but no significant difference (P = 0.13) in global cartilage T1. Significant difference was also present between age groups in cartilage T2 and T1ρ for medial femur cartilage and medial tibia cartilage. There were significant moderate correlations between age and T2 and T1ρ for global cartilage (R2  = 0.63-0.64), medial femur cartilage (R2  = 0.50-0.56), and medial tibia cartilage (R2  = 0.54-0.66). CONCLUSION: Cartilage T2 and T1p relaxation times simultaneously measured using a 3D-MRF sequence in healthy volunteers showed age-dependent changes in knee cartilage, primarily within the medial compartment.

3D magnetic resonance fingerprinting for rapid simultaneous T1, T2, and T1ρ volumetric mapping of human articular cartilage at 3 T.

Quantitative MRI can detect early biochemical changes in cartilage; however, the conventional techniques only measure one parameter (e.g., T1 , T2 , and T1ρ ) at a time while also being comparatively slow. We implemented a 3D magnetic resonance fingerprinting (3D-MRF) technique for simultaneous, volumetric mapping of T1 , T2 , and T1ρ 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 T1 , T2, T1ρ relaxation times, and B1 + 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 T1 , T2 , and T1ρ , respectively. The in vivo knee study showed excellent repeatability with rmsCV less than 1%, 2%, and 1% for T1 , T2 , and T1ρ , respectively. T1ρ 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 B1 + inhomogeneity, and can simultaneously measure the T1 , T2 , T1ρ , and B1 + volumetric maps of the knee joint in a single scan within a clinically feasible scan time.

Optimization of spin-lock times in T1ρ mapping of knee cartilage: Cramér-Rao bounds versus matched sampling-fitting.

PURPOSE: To compare different optimization approaches for choosing the spin-lock times (TSLs), in spin-lattice relaxation time in the rotating frame (T1ρ ) mapping. METHODS: Optimization criteria for TSLs based on Cramér-Rao lower bounds (CRLB) are compared with matched sampling-fitting (MSF) approaches for T1ρ mapping on synthetic data, model phantoms, and knee cartilage. The MSF approaches are optimized using robust methods for noisy cost functions. The MSF approaches assume that optimal TSLs depend on the chosen fitting method. An iterative non-linear least squares (NLS) and artificial neural networks (ANN) are tested as two possible T1ρ fitting methods for MSF approaches. RESULTS: All optimized criteria were better than non-optimized ones. However, we observe that a modified CRLB and an MSF based on the mean of the normalized absolute error (MNAE) were more robust optimization approaches, performing well in all tested cases. The optimized TSLs obtained the best performance with synthetic data (3.5-8.0% error), model phantoms (1.5-2.8% error), and healthy volunteers (7.7-21.1% error), showing stable and improved quality results, comparing to non-optimized approaches (4.2-13.3% error on synthetic data, 2.1-6.2% error on model phantoms, 9.8-27.8% error on healthy volunteers). CONCLUSION: A modified CRLB and the MSF based on MNAE are robust optimization approaches for choosing TSLs in T1ρ mapping. All optimized criteria allowed good results even using rapid scans with two TSLs when a complex-valued fitting is done with iterative NLS or ANN.

Simultaneous bilateral T1 , T2 , and T1ρ relaxation mapping of the hip joint with magnetic resonance fingerprinting.

Quantitative MRI can detect early biochemical changes in cartilage, but its bilateral use in clinical routines is challenging. The aim of this prospective study was to demonstrate the feasibility of magnetic resonance fingerprinting for bilateral simultaneous T1 , T2 , and T1ρ mapping of the hip joint. The study population consisted of six healthy volunteers with no known trauma or pain in the hip. Monoexponential T1 , T2 , and T1ρ relaxation components were assessed in femoral lateral, superolateral, and superomedial, and inferior, as well as acetabular, superolateral, and superomedial subregions in left and right hip cartilage. Aligned ranked nonparametric factorial analysis was used to assess the side's impact on the subregions. Kruskal-Wallis and Wilcoxon tests were used to compare subregions, and coefficient of variation to assess repeatability. Global averages of T1 (676.0 ± 45.4 and 687.6 ± 44.5 ms), T2 (22.5 ± 2.6 and 22.1 ± 2.5 ms), and T1ρ (38.2 ± 5.5 and 38.2 ± 5.5 ms) were measured in the left and right hip, and articular cartilage, respectively. The Kruskal-Wallis test showed a significant difference between different subregions' relaxation times regardless of the hip side (p < 0.001 for T1 , p = 0.012 for T2 , and p < 0.001 for T1ρ ). The Wilcoxon test showed that T1 of femoral layers was significantly (p < 0.003) higher than that for acetabular cartilage. The experiments showed excellent repeatability with CVrms of 1%, 2%, and 4% for T1 , T2 , and T1ρ, respectively. It was concluded that bilateral T1 , T2 , and T1ρ relaxation times, as well as B1+ maps, can be acquired simultaneously from hip joints using the proposed MRF sequence.

Lower extremity MRI following 10-week supervised exercise intervention in patients with diabetic peripheral neuropathy.

INTRODUCTION: The purpose of this study was to characterize using MRI the effects of a 10-week supervised exercise program on lower extremity skeletal muscle composition, nerve microarchitecture, and metabolic function in individuals with diabetic peripheral neuropathy (DPN). RESEARCH DESIGN AND METHODS: Twenty participants with DPN completed a longitudinal trial consisting of a 30-day control period, during which subjects made no change to their lifestyle, followed by a 10-week intervention program that included three supervised aerobic and resistance exercise sessions per week targeting the upper and lower extremities. The participants' midcalves were scanned with multinuclear MRI two times prior to intervention (baseline1 and baseline2) and once following intervention to measure relaxation times (T1, T1ρ, and T2), phosphocreatine recovery, fat fraction, and diffusion parameters. RESULTS: There were no changes between baseline1 and baseline2 MRI metrics (p>0.2). Significant changes (p<0.05) between baseline2 and postintervention MRI metrics were: gastrocnemius medialis (GM) T1 -2.3%±3.0% and soleus T2 -3.2%±3.1%. Trends toward significant changes (0.050.3) and tibial nerve fractional anisotropy (p>0.6) and apparent diffusion coefficient (p>0.4). CONCLUSIONS: The 10-week supervised exercise intervention program successfully reduced adiposity and altered resting tissue properties in the lower leg in DPN. Gastrocnemius mitochondrial oxidative capacity and tibial nerve microarchitecture changes were not observed, either due to lack of response to therapy or to lack of measurement sensitivity.

Simultaneous T1 , T2 , and T1ρ relaxation mapping of the lower leg muscle with MR fingerprinting.

PURPOSE: To develop a novel MR-fingerprinting (MRF) pulse sequence that is insensitive to B1+ and B0 imperfections for simultaneous T1 , T2 , and T1ρ relaxation mapping. METHODS: We implemented a totally balanced spin-lock (TB-SL) module to encode T1ρ relaxation into an existing MRF framework that encoded T1 and T2 . The spin-lock module used two 180° pulses with compensatory phases to reduce T1ρ sensitivity to B1 and B0 inhomogeneities. We compared T1ρ measured using TB-SL MRF in Bloch simulations, model agar phantoms, and in vivo experiments to those with a self-compensated spin-lock preparation module (SC-SL). The TB-SL MRF repeatability was evaluated in maps acquired in the lower leg skeletal muscle of 12 diabetic peripheral neuropathy patients, scanned two times each during visits separated by about 30 days. RESULTS: The phantom relaxation times measured with TB-SL and SC-SL MRF were in good agreement with reference values in regions with low B1 inhomogeneities. Compared with SC-SL, TB-SL MRF showed in experiments greater robustness against severe B1 inhomogeneities and in Bloch simulations greater robustness against B1 and B0 . We measured with TB-SL MRF an average T1 = 950.1 ± 28.7 ms, T2 = 26.0 ± 1.2 ms, and T1ρ = 31.7 ± 3.2 ms in skeletal muscle across patients. Bland-Altman analysis demonstrated low bias between TB-SL and SC-SL MRF and between TB-SL MRF maps acquired in two visits. The coefficient of variation was less than 3% for all measurements. CONCLUSION: The proposed TB-SL MRF sequence is fast and insensitive to B1+ and B0 imperfections. It can simultaneously map T1 , T2 , T1ρ , and B1+ in a single scan and can potentially be used to study muscle composition.

Rapid mono and biexponential 3D-T1ρ mapping of knee cartilage using variational networks.

In this study we use undersampled MRI acquisition methods to obtain accelerated 3D mono and biexponential spin-lattice relaxation time in the rotating frame (T1ρ) mapping of knee cartilage, reducing the usual long scan time. We compare the accelerated T1ρ maps obtained by deep learning-based variational network (VN) and compressed sensing (CS). Both methods were compared with spatial (S) and spatio-temporal (ST) filters. Complex-valued fitting was used for T1ρ parameters estimation. We tested with seven in vivo and six synthetic datasets, with acceleration factors (AF) from 2 to 10. Median normalized absolute deviation (MNAD), analysis of variance (ANOVA), and coefficient of variation (CV) were used for analysis. The methods CS-ST, VN-S, and VN-ST performed well for accelerating monoexponential T1ρ mapping, with MNAD around 5% for AF = 2, which increases almost linearly with the AF to an MNAD of 13% for AF = 8, with all methods. For biexponential mapping, the VN-ST was the best method starting with MNAD of 7.4% for AF = 2 and reaching MNAD of 13.1% for AF = 8. The VN was able to produce 3D-T1ρ mapping of knee cartilage with lower error than CS. The best results were obtained by VN-ST, improving CS-ST method by nearly 7.5%.

MR fingerprinting for rapid simultaneous T1 , T2 , and T1ρ relaxation mapping of the human articular cartilage at 3T.

PURPOSE: To implement a novel technique for simultaneous, quantitative multiparametric mapping of the knee articular cartilage. METHODS: A novel MR fingerprinting pulse sequence is proposed and implemented for simultaneous measurements of proton density, T1 , T2, and T1ρ relaxation times at 3T. The repeatability and reproducibility of the proposed technique were assessed in model phantoms. Institutional review board-approved MR fingerprinting imaging sequence was performed on healthy volunteers and patients with mild knee osteoarthritis. The Wilcoxon test was used to compare healthy controls and patients. The intra- and intersubject repeatability were assessed with coefficient of variation and the RMS coefficient of variation, respectively RESULTS: The Bland-Altman plots demonstrated an average difference of 4.67 ms, -0.09 ms, and 0.05 ms between 2 scans in the same scanner; and 9.68 ms, 0.29 ms, and -0.72 ms between the scans acquired on 2 different scanners for T1 , T2 , and T1ρ , respectively. The in vivo knee study showed excellent repeatability with RMS coefficient of variation less than 3%, 6%, and 5% for T1 , T2 , and T1ρ , respectively. The Wilcoxon test showed a significant difference between control and mild osteoarthritis patients for T1 (P = .04), T2 (P = .01), and T1ρ (P = .02) relaxation time in medial tibial cartilage, as well as for T2 relaxation time (P = .02) in medial femoral cartilage. CONCLUSION: The proposed MRF sequence is fast and can simultaneously measure the T1 , T2 , T1ρ , and B1+ maps in a single scan. It is able to discriminate between mild osteoarthritis patients and healthy volunteers.

Fast multicomponent 3D-T1ρ relaxometry.

NMR relaxometry can provide information about the relaxation of the magnetization in different tissues, increasing our understanding of molecular dynamics and biochemical composition in biological systems. In general, tissues have complex and heterogeneous structures composed of multiple pools. As a result, bulk magnetization returns to its original state with different relaxation times, in a multicomponent relaxation. Recovering the distribution of relaxation times in each voxel is a difficult inverse problem; it is usually unstable and requires long acquisition time, especially on clinical scanners. MRI can also be viewed as an inverse problem, especially when compressed sensing (CS) is used. The solution of these two inverse problems, CS and relaxometry, can be obtained very efficiently in a synergistically combined manner, leading to a more stable multicomponent relaxometry obtained with short scan times. In this paper, we will discuss the details of this technique from the viewpoint of inverse problems.

Accelerated mono- and biexponential 3D-T1ρ relaxation mapping of knee cartilage using golden angle radial acquisitions and compressed sensing.

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 (T1ρ ) mapping of knee cartilage. METHODS: Golden-angle radial stack-of-stars and Cartesian 3D-T1ρ -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 T1ρ -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 T1ρ 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-T1ρ 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.

Volumetric multicomponent T1ρ relaxation mapping of the human liver under free breathing at 3T.

PURPOSE: To develop a 3D sequence for T1ρ relaxation mapping using radial volumetric encoding (3D-T1ρ -RAVE) and to evaluate the multi relaxation components in the liver of healthy controls and chronic liver disease (CLD) patients. METHODS: Fat saturation and T1ρ preparation modules were followed by a train of gradient-echo acquisitions and T1 restoration delay. The series of T1ρ -weighted images were fitted using mono-exponential, bi-exponential, and stretched-exponential models. The repeatability and reproducibility of the proposed technique were evaluated on National Institute of Standards and Technology phantom by calculating the coefficient of variation between test-retest scans on the same scanner and between two different 3T scanners, respectively. Mann-Whitney U-test was performed to assess differences in T1ρ components among patients (n = 3) and a control group (n = 10). RESULTS: The phantom study showed an error of 8.9% and 11.5% in mono T2 relaxation time measurement relative to the reference on 2 different scanners. The coefficient of variation for test-retest scans performed on the same scanner was 5.7% and 2.4% for scans performed on 2 scanners. The comparison between healthy controls and CLD patients showed a significant difference (P < .05) in mono relaxation time (P = .002), stretched-exponential relaxation parameter (P = .04). The Akaike information criteria C criterion showed 2.53 ± 0.9% (2.3 ± 0.3% for CLD) of the voxels are bi-exponential while in 65.3 ± 5.8% (81.2 ± 0.06% for CLD) of the liver voxels, the stretched-exponential model was preferred. CONCLUSION: The 3D-T1ρ -RAVE sequence allows volumetric, multicomponent T1ρ assessment of the liver during free breathing and can distinguish between healthy volunteers and CLD patients.

3D-T1ρ prepared zero echo time-based PETRA sequence for in vivo biexponential relaxation mapping of semisolid short-T2 tissues at 3 T.

BACKGROUND: In addition to the articular cartilage, osteoarthritis (OA) affects several other tissues such as tendons, ligaments, and subchondral bone. T1ρ relaxation study of these short T2 tissues may provide a more comprehensive evaluation of OA. PURPOSE: To develop a 3D spin-lattice relaxation in the rotating frame (T1ρ ) prepared zero echo time (ZTE)-based pointwise encoding time reduction with radial acquisition (3D-T1ρ -PETRA) sequence for relaxation mapping of semisolid short-T2 tissues on a clinical 3 T scanner. STUDY TYPE: Prospective. POPULATION: Phantom, two bovine whole knee joint and Achilles tendon specimens, 10 healthy volunteers with no known inflammation, trauma or pain in the knee or ankle. FIELD STRENGTH/SEQUENCE: A customized PETRA sequence to acquire fat-suppressed 3D T1ρ -weighted images tissues with semisolid short T2 / T2* relaxation times in the knee and ankle joints at 3 T. ASSESSMENT: Mono- and biexponential T1ρ relaxation components were assessed in the patellar tendon (PT), anterior cruciate ligament (ACL), posterior cruciate ligament (PCL), and Achilles tendon (AT). STATISTICAL TESTS: Kruskal-Wallis with post-hoc Dunn's test for multiple pairwise comparisons. RESULTS: Phantom and ex vivo studies showed the feasibility of T1ρ relaxation mapping using the proposed 3D-T1ρ -PETRA sequence. The in vivo study demonstrated an averaged mono-T1ρ relaxation of (median [IQR]) 15.9 [14.5] msec, 23.6 [9.4] msec, 17.4 [7.4] msec, and 5.8 [10.2] msec in the PT, ACL, PCL, and AT, respectively. The bicomponent analysis showed the short and long components (with their relative fractions) of 0.65 [1.0] msec (46.9 [15.3]%) and 37.3 [18.4] msec (53.1 [15.3]%) for PT, 1.7 [2.1] msec (42.5 [12.5]%) and 43.7 [17.8] msec (57.5 [12.5]%) for ACL, and 1.2 [1.9] msec (42.6 [14.0]%) and 27.7 [14.7] msec (57.3 [14.0]%) for PCL and 0.4 [0.02] msec (58.8 [13.3]%/) and 31.3 [10.8] msec (41.2 [13.3]%) for AT. Statistically significant (P ≤ 0.05) differences were observed in the mono- and biexponential relaxation between several regions. DATA CONCLUSION: The 3D-T1ρ -PETRA sequence allows volumetric, isotropic (0.78 × 0.78 × 0.78 mm), biexponential T1ρ assessment with corresponding fractions of the tissues with semisolid short T2 / T2* . LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;50:1207-1218.

Biexponential T1ρ relaxation mapping of human knee menisci.

BACKGROUND: Measuring T1ρ in the knee menisci can potentially be used as noninvasive biomarkers in detecting early-stage osteoarthritis (OA). PURPOSE: To demonstrate the feasibility of biexponential T1ρ relaxation mapping of human knee menisci. STUDY TYPE: Prospective. POPULATION: Eight healthy volunteers with no known inflammation, trauma, or pain in the knee and three symptomatic subjects with early knee OA. FIELD STRENGTH/SEQUENCE: Customized Turbo-FLASH sequence to acquire 3D-T1ρ -weighted images on a 3 T MRI scanner. ASSESSMENT: T1ρ relaxation values were assessed in 11 meniscal regions of interest (ROIs) using monoexponential and biexponential models. STATISTICAL TESTS: Nonparametric rank-sum tests, Kruskal-Wallis test, and coefficient of variation. RESULTS: The mean monoexponential T1ρ relaxation in the lateral menisci were 28.05 ± 4.2 msec and 37.06 ± 10.64 msec for healthy subjects and early knee OA patients, respectively, while the short and long components were 8.07 ± 0.5 msec and 72.35 ± 3.2 msec for healthy subjects and 2.63 ± 2.99 msec and 55.27 ± 24.76 msec for early knee OA patients, respectively. The mean monoexponential T1ρ relaxation in the medial menisci were 34.30 ± 3.8 msec and 37.26 ± 11.38 msec for healthy and OA patients, respectively, while the short and long components were 7.76 ± 0.7 msec and 72.19 ± 4.2 msec for healthy subjects and 3.06 ± 3.24 msec and 55.27 ± 24.59 msec for OA patients, respectively. Statistically significant (P ≤ 0.05) differences were observed in the monoexponential relaxation between some of the ROIs. The T1ρ,short was significantly lower (P = 0.02) in the patients than controls. The rmsCV% ranges were 1.51-16.6%, 3.59-14.3%, and 4.91-15.6% for T1ρ -mono, T1ρ -short, and T1ρ -long, respectively. DATA CONCLUSION: Our results showed that in all ROIs, T1ρ relaxation times of outer zones (red zones) were less than inner zones (white zones). Monoexponential T1ρ was increased in medial, lateral, and body menisci of early OA while the biexponential numbers were decreased in early OA patients. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2019;50:824-835.

Compressed sensing acceleration of biexponential 3D-T1ρ relaxation mapping of knee cartilage.

PURPOSE: Use compressed sensing (CS) for 3D biexponential spin-lattice relaxation time in the rotating frame (T1ρ ) mapping of knee cartilage, reducing the total scan time and maintaining the quality of estimated biexponential T1ρ parameters (short and long relaxation times and corresponding fractions) comparable to fully sampled scans. METHODS: Fully sampled 3D-T1ρ -weighted data sets were retrospectively undersampled by factors 2-10. CS reconstruction using 12 different sparsifying transforms were compared for biexponential T1ρ -mapping of knee cartilage, including temporal and spatial wavelets and finite differences, dictionary from principal component analysis (PCA), k-means singular value decomposition (K-SVD), exponential decay models, and also low rank and low rank plus sparse models. Synthetic phantom (N = 6) and in vivo human knee cartilage data sets (N = 7) were included in the experiments. Spatial filtering before biexponential T1ρ parameter estimation was also tested. RESULTS: Most CS methods performed satisfactorily for an acceleration factor (AF) of 2, with relative median normalized absolute deviation (MNAD) around 10%. Some sparsifying transforms, such as low rank with spatial finite difference (L + S SFD), spatiotemporal finite difference (STFD), and exponential dictionaries (EXP) significantly improved this performance, reaching MNAD below 15% with AF up to 10, when spatial filtering was used. CONCLUSION: Accelerating biexponential 3D-T1ρ 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%.

Isotropic morphometry and multicomponent T1 ρ mapping of human knee articular cartilage in vivo at 3T.

BACKGROUND: The progressive loss of hyaline articular cartilage due to osteoarthritis (OA) changes the functional and biochemical properties of cartilage. Measuring the T1 ρ along with the morphological assessment can potentially be used as noninvasive biomarkers in detecting early-stage OA. To correlate the biochemical and morphological data, submillimeter isotropic resolution for both studies is required. PURPOSE: To implement a high spatial resolution 3D-isotropic-MRI sequence for simultaneous assessment of morphological and biexponential T1 ρ relaxometry of human knee cartilage in vivo. STUDY TYPE: Prospective. POPULATION: Ten healthy volunteers with no known inflammation, trauma, or pain in the knee. FIELD STRENGTH/SEQUENCE: Standard FLASH sequence and customized Turbo-FLASH sequence to acquire 3D-isotropic-T1 ρ-weighted images on a 3T MRI scanner. ASSESSMENT: The mean volume and thickness along with mono- and biexponential T1 ρ relaxations were assessed in the articular cartilage of 10 healthy volunteers. STATISTICAL TESTS: Nonparametric rank-sum tests. Bland-Altman analysis and coefficient of variation. RESULTS: The mean monoexponential T1 ρ relaxation was 40.7 ± 4.8 msec, while the long and short components were 58.2 ± 3.9 msec and 6.5 ± 0.6 msec, respectively. The mean fractions of long and short T1 ρ relaxation components were 63.7 ± 5.9% and 36.3 ± 5.9%, respectively. Statistically significant (P ≤ 0.03) differences were observed in the monoexponential and long components between some of the regions of interest (ROIs). No gender differences between biexponential components were observed (P > 0.05). Mean cartilage volume and thickness were 25.9 ± 6.4 cm3 and 2.2 ± 0.7 mm, respectively. Cartilage volume (P = 0.01) and thickness (P = 0.03) were significantly higher in male than female participants across all ROIs. Bland-Altman analysis showed agreement between two morphological methods with limits of agreement between -1000 mm3 and +1100 mm3 for volume, and -0.78 mm and +0.46 mm for thickness, respectively. DATA CONCLUSION: Simultaneous assessment of morphological and multicomponent T1 ρ relaxation of knee joint with 0.7 × 0.7 × 0.7 mm isotropic spatial resolution is demonstrated in vivo. Comparison with a standard method showed that the proposed technique is suitable for assessing the volume and thickness of articular cartilage. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;48:1707-1716.

Accelerating 3D-T1ρ mapping of cartilage using compressed sensing with different sparse and low rank models.

PURPOSE: To evaluate the feasibility of using compressed sensing (CS) to accelerate 3D-T1ρ mapping of cartilage and to reduce total scan times without degrading the estimation of T1ρ relaxation times. METHODS: Fully sampled 3D-T1ρ datasets were retrospectively undersampled by factors 2-10. CS reconstruction using 12 different sparsifying transforms were compared, including finite differences, temporal and spatial wavelets, learned transforms using principal component analysis (PCA) and K-means singular value decomposition (K-SVD), explicit exponential models, low rank and low rank plus sparse models. Spatial filtering prior to T1ρ parameter estimation was also tested. Synthetic phantom (n = 6) and in vivo human knee cartilage datasets (n = 7) were included. RESULTS: Most CS methods performed satisfactorily for an acceleration factor (AF) of 2, with relative T1ρ error lower than 4.5%. Some sparsifying transforms, such as spatiotemporal finite difference (STFD), exponential dictionaries (EXP) and low rank combined with spatial finite difference (L+S SFD) significantly improved this performance, reaching average relative T1ρ error below 6.5% on T1ρ relaxation times with AF up to 10, when spatial filtering was used before T1ρ fitting, at the expense of smoothing the T1ρ maps. The STFD achieved 5.1% error at AF = 10 with spatial filtering prior to T1ρ fitting. CONCLUSION: Accelerating 3D-T1ρ 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 T1ρ error of 6.5%.