T1ρ Mapping Research Articles

Baseline cartilage T1ρ and T2 predicted patellofemoral joint cartilage lesion progression and patient-reported outcomes after ACL reconstruction.

This study aims to determine if baseline T1ρ and T2 will predict cartilage morphological lesion progression in the patellofemoral joint (PFJ) and patient-reported outcomes at 2-year after anterior cruciate ligament (ACL) reconstruction (ACLR). Thirty-nine ACL-injured patients were studied at baseline and two-year after ACLR. 3 T MR T1ρ and T2 images and Knee Injury and Osteoarthritis Outcome Score (KOOS) were acquired at both time points. Voxel-based relaxometry (VBR) technique was used to detect local cartilage abnormalities. Patients were divided into progression and non-progression groups based on changes of the whole-organ magnetic resonance imaging scoring (WORMS) grading of cartilage in PFJ from baseline to 2-year, and into lower (more pain) and higher (less pain) KOOS pain groups based on 2-year KOOS pain scores, separately. Voxel-based analyses of covariance were used to compare T1ρ and T2 values at baseline between the defined groups. Using VBR analysis, the progression group at 2-year showed higher T1ρ and T2 compared with the non-progression group at baseline, with the medial femoral condyle showing the largest areas with significant differences. At two-year, 56% of patients were able to recover with respect to KOOS pain. The lower KOOS pain group at 2-year showed significantly elevated T1ρ and T2 in the patella at baseline compared with the higher KOOS pain group. In conclusion, baseline T1ρ and T2 mapping, combined with VBR analysis, may help identify ACLR patients at high risk of developing progressive PFJ cartilage lesions and worse clinical symptoms 2-year after surgery.

Magnetic resonance T1ρ quantification of human brain at 5.0 T: A pilot study

MR quantitative T1ρ mapping has gained increasing attention due to its capability to study low-frequency motional processes and chemical exchange in biological tissues. At ultra-high fields, the chemical exchange and proton diffusion in biological tissues should be more prominent. In this study, for the first time, we aim to test the feasibility of brain T 1ρ mapping at 5.0 T MR scanner and compare the T 1ρ values estimated using 3.0 T and 5.0 T scanners. Preliminary experimental results show that 5.0 T achieves T 1ρ -weighted images with a higher signal-to-noise ratio than those acquired at 3.0T. The SNR benefit at 5.0 T is more obvious in high-resolution imaging. The T 1ρ quantifications at 5.0 T are: Corpus callosum (67.4 ± 1.9 ms), Corona radiate (71.5 ± 1.8 ms), Superior frontal gyrus (67.6 ± 2.5 ms), Putamen (58.9 ± 1.2 ms), Centrum semiovale (84.0 ± 6.3 ms). Statistical analysis results indicate that the T 1ρ values at 5.0 T show no significant difference with those obtained at 3.0 T (all p > 0.05). The interfield agreements in terms of T 1ρ values between 3.0 T and 5.0 T were substantial (all ICCs >0.7). The coefficients of variation for T 1ρ measurements from 3.0 T to 5.0 T were all less than 6.50% (2.28%–6.32%).

Optimization of spin-lock times for T1ρ mapping of human knee cartilage with bi- and stretched-exponential models

Two optimization criteria based on Cramér-Rao Bounds are compared between each other and with non-optimized schedules for T1ρ mapping using synthetic data, model phantoms, and in-vivo knee cartilage. The curve fitting is done on complex-valued data using an iterative Nonlinear Least Squares (NLS) approach. The optimization criteria are compared based on the Mean Normalized Absolute Error (MNAE) and variance of the estimated parameters. The optimized spin-lock time (TSL) schedules provided improved results over the non-optimized schedules for all cases that were tested. The simulations showed that optimized schedules can reach the same precision and reduce acquisition times by 16.5 min (42%) for the bi-exponential model, and 6.6 min (22%) for the stretched-exponential model. In the model phantoms experiments, the bi-exponential MNAE was reduced from 0.47 to 0.36, while stretched-exponential from 0.28 to 0.20 with a Modified Cramér-Rao Lower Bound (MCRLB). In-vivo knee cartilage experiments show a reduction in bi-exponential MNAE from 0.47 to 0.31, and stretched-exponential from 0.047 to 0.039. The optimized spin-lock times criteria reduced the error in all cases, being more significant in the synthetic data and model phantoms. The optimized TSL schedules can be either used to improve the quality of parameter maps or reduce scan time.

Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing.

In this study, the feasibility of accelerated quantitative Ultrashort Echo Time Cones (qUTE-Cones) imaging with compressed sensing (CS) reconstruction is investigated. qUTE-Cones sequences for variable flip angle-based UTE T1 mapping, UTE adiabatic T1ρ mapping, and UTE quantitative magnetization transfer modeling of macromolecular fraction (MMF) were implemented on a clinical 3T MR system. Twenty healthy volunteers were recruited and underwent whole-knee MRI using qUTE-Cones sequences. The k-space data were retrospectively undersampled with different undersampling rates. The undersampled qUTE-Cones data were reconstructed using both zero-filling and CS reconstruction. Using CS-reconstructed UTE images, various parameters were estimated in 10 different regions of interests (ROIs) in tendons, ligaments, menisci, and cartilage. Structural similarity, percentage error, and Pearson’s correlation were calculated to assess the performance. Dramatically reduced streaking artifacts and improved SSIM were observed in UTE images from CS reconstruction. A mean SSIM of ~0.90 was achieved for all CS-reconstructed images. Percentage errors between fully sampled and undersampled CS-reconstructed images were below 5% for up to 50% undersampling (i.e., 2× acceleration). High linear correlation was observed (>0.95) for all qUTE parameters estimated in all subjects. CS-based reconstruction combined with efficient Cones trajectory is expected to achieve a clinically feasible scan time for qUTE imaging.

A robust adiabatic constant amplitude spin-lock preparation module for myocardial T1ρ quantification at 3T.

T1ρ quantification has the potential to assess myocardial fibrosis without contrast agent. However, its preparation spin-lock pulse is sensitive to B1 and B0 inhomogeneities, resulting in severe banding artifacts in the heart region, especially at high magnetic field such as 3T. We aimed to design a robust spin-lock (SL) preparation module that can be used in myocardial T1ρ quantification at 3T. We used the tan/tanh pulse to tip up and tip down the magnetization in the spin-lock preparation module (tan/tanh-SL). Bloch simulation was used to optimize pulse shape parameters of the tan/tanh with a pulse duration (Tp ) of 8, 4, and 2ms, respectively. The designed tan/tanh-SL modules were implemented on a 3-T MR scanner. They were evaluated in phantom studies under three different cases of B0 and B1 inhomogeneities, and tested in cardiac T1ρ quantification of healthy volunteers. The performance of the tan/tanh-SL was compared with the composite SL preparation pulses and the commonly used hyperbolic secant pulse for spin-lock (HS-SL). Feasible pulse shape parameters were obtained using Bloch simulation. Compared with HS-SL, the quantification error of tan/tanh-SL was reduced by 27.7% for Tp = 8ms (mean ∆Q = 126.15 vs. 174.42) and 75.6% for Tp = 4ms (mean ∆Q = 136.65 vs. 559.53). In the phantom study, tan/tanh-SL was less sensitive to B1 and B0 inhomogeneity compared with composite SL pulses and HS-SL. In cardiac T1ρ quantification, the T1ρ maps using tan/tanh-SL showed fewer banding artifacts than using composite SL pulses and HS-SL. The proposed tan/tanh-SL preparation module greatly improves the robustness to B0 and B1 field inhomogeneities and can be used in cardiac T1ρ quantification at 3T.

Data-driven optimization of sampling patterns for MR brain T1ρ mapping.

The goal of this study was to apply a fast data-driven optimization algorithm, called bias-accelerated subset selection, for MR brain T1ρ mapping to generate optimized sampling patterns (SPs) for compressed sensing reconstruction of brain 3D-T1ρ MRI. Five healthy volunteers were recruited, and fully sampled Cartesian 3D-T1ρ MRIs were obtained. Variable density (VD) and Poisson disc (PD) undersampling was used as the input to SP optimization process. The reconstruction used 3 compressed sensing methods: spatiotemporal finite differences, low-rank plus sparse with spatial finite differences, and low rank. The performance of images and T1ρ maps using PD-SP and VD-SP and their optimized sampling patterns (PD-OSP and VD-OSP) were compared to the fully sampled reference using normalized root mean square error (NRMSE). The VD-OSP with spatiotemporal finite differences reconstruction (NRMSE=0.078) and the PD-OSP with spatiotemporal finite differences reconstruction (NRMSE=0.079) at the highest acceleration factors (AF=30) showed the largest improvement compared to the respective nonoptimized SPs (VD NRMSE=0.087 and PD NRMSE=0.149). Prospective undersampling was tested at AF=4, with VD-OSP NRMSE=0.057 versus PD-OSP NRMSE=0.060, with optimized sampling performing better that input PD or VD sampling. For brain T1ρ mapping, the VD-OSP with low rank reconstruction for AFs <10 and VD-OSP with spatiotemporal finite differences for AFs >10 perform better. The study demonstrated that the appropriate use of data-driven optimized sampling and suitable compressed sensing reconstruction technique can be employed to potentially accelerate 3D T1ρ mapping for brain imaging applications.

Highly accelerated MR parametric mapping by undersampling the k-space and reducing the contrast number simultaneously with deep learning

Introduction. To propose a novel deep learning-based method called RG-Net (reconstruction and generation network) for highly accelerated MR parametric mapping by undersampling k-space and reducing the acquired contrast number simultaneously. Methods. The proposed framework consists of a reconstruction module and a generative module. The reconstruction module reconstructs MR images from the acquired few undersampled k-space data with the help of a data prior. The generative module then synthesizes the remaining multi-contrast images from the reconstructed images, where the exponential model is implicitly incorporated into the image generation through the supervision of fully sampled labels. The RG-Net was trained and tested on the T1ρ mapping data from 8 volunteers at net acceleration rates of 17, respectively. Regional T1ρ analysis for cartilage and the brain was performed to assess the performance of RG-Net. Results. RG-Net yields a high-quality T1ρ map at a high acceleration rate of 17. Compared with the competing methods that only undersample k-space, our framework achieves better performance in T1ρ value analysis. Conclusion. The proposed RG-Net can achieve a high acceleration rate while maintaining good reconstruction quality by undersampling k-space and reducing the contrast number simultaneously for fast MR parametric mapping. The generative module of our framework can also be used as an insertable module in other fast MR parametric mapping methods.

Accelerated 3D free-breathing high-resolution myocardial T1ρ mapping at 3Tesla.

To develop a fast free-breathing whole-heart high-resolution myocardial T1ρ mapping technique with robust spin-lock preparation that can be performed at 3Tesla. An adiabatically excited continuous-wave spin-lock module, insensitive to field inhomogeneities, was implemented with an electrocardiogram-triggered low-flip angle spoiled gradient echo sequence with variable-density 3D Cartesian undersampling at a 3 Tesla whole-body scanner. A saturation pulse was performed at the beginning of each cardiac cycle to null the magnetization before T1ρ preparation. Multiple T1ρ -weighted images were acquired with T1ρ preparations with different spin-lock times in an interleaved fashion. Respiratory self-gating approach was adopted along with localized autofocus to enable 3D translational motion correction of the data acquired in each heartbeat. After motion correction, multi-contrast locally low-rank reconstruction was performed to reduce undersampling artifacts. The accuracy and feasibility of the 3D T1ρ mapping technique was investigated in phantoms and in vivo in 10 healthy subjects compared with the 2D T1ρ mapping. The 3D T1ρ mapping technique provided similar phantom T1ρ measurements in the range of 25-120 ms to the 2D T1ρ mapping reference over a wide range of simulated heart rates. With the robust adiabatically excited continuous-wave spin-lock preparation, good quality 2D and 3D in vivo T1ρ -weighted images and T1ρ maps were obtained. Myocardial T1ρ values with the 3D T1ρ mapping were slightly longer than 2D breath-hold measurements (septal T1ρ : 52.7 ± 1.4ms vs. 50.2 ± 1.8ms, P < 0.01). A fast 3D free-breathing whole-heart T1ρ mapping technique was proposed for T1ρ quantification at 3T with isotropic spatial resolution (2 mm3 ) and short scan time of ∼4.5min.

Endogenous assessment of late gadolinium enhancement grey zone in patients with non-ischaemic cardiomyopathy with T1ρ and native T1 mapping.

This study aims to validate and compare the feasibility of T1ρ and native longitudinal relaxation time (T1) mapping in detection of myocardial fibrosis in patients with non-ischaemic cardiomyopathy, focusing on the performance of both methods in identifying late gadolinium enhancement (LGE) grey zone. Twenty-seven hypertrophic cardiomyopathy (HCM) patients, 16 idiopathic dilated cardiomyopathy (DCM) patients, and 18 healthy controls were prospectively enrolled for native T1 and T1ρ mapping imaging and then all the patients underwent enhancement scan for LGE extent and extracellular volume (ECV) values. In LGE positive patients, the LGE areas were divided into LGE core (6 SDs above remote myocardium) and grey zone (2-6 SDs above remote myocardium) according to the signal intensity of LGE. Both HCM and DCM patients showed significantly higher native T1 values and T1ρ values than controls no matter the presence of LGE (all P < 0.01). There were significant differences in native T1 and T1ρ values among four different types of myocardia (LGE core, grey zone, remote area and control, P < 0.0001). However, the T1ρ values of grey zone were significantly higher than control (P < 0.01), while the native T1 values were not (P = 0.089). T1ρ values were significantly associated with both native T1 values (r = 0.54, P < 0.001) and ECV values (r = 0.54, P < 0.001). T1ρ mapping is a feasible method to detect myocardial fibrosis in patients with non-ischaemic cardiomyopathy no matter the presence of LGE. Compared with native T1, T1ρ may serve as a better discriminator in the identification of LGE grey zone.

Paper 01: ACL Reconstructed Knees Had Significantly Higher MR T1ρ and T2 Values in Cartilage but not in Meniscus Compared to Contralateral Knees at 10 Years after ACL Reconstruction

Paper 01: ACL Reconstructed Knees Had Significantly Higher MR T1ρ and T2 Values in Cartilage but not in Meniscus Compared to Contralateral Knees at 10 Years after ACL Reconstruction

Embedded Quantitative MRI T1ρ Mapping Using Non-Linear Primal-Dual Proximal Splitting.

Quantitative MRI (qMRI) methods allow reducing the subjectivity of clinical MRI by providing numerical values on which diagnostic assessment or predictions of tissue properties can be based. However, qMRI measurements typically take more time than anatomical imaging due to requiring multiple measurements with varying contrasts for, e.g., relaxation time mapping. To reduce the scanning time, undersampled data may be combined with compressed sensing (CS) reconstruction techniques. Typical CS reconstructions first reconstruct a complex-valued set of images corresponding to the varying contrasts, followed by a non-linear signal model fit to obtain the parameter maps. We propose a direct, embedded reconstruction method for T mapping. The proposed method capitalizes on a known signal model to directly reconstruct the desired parameter map using a non-linear optimization model. The proposed reconstruction method also allows directly regularizing the parameter map of interest and greatly reduces the number of unknowns in the reconstruction, which are key factors in the performance of the reconstruction method. We test the proposed model using simulated radially sampled data from a 2D phantom and 2D cartesian ex vivo measurements of a mouse kidney specimen. We compare the embedded reconstruction model to two CS reconstruction models and in the cartesian test case also the direct inverse fast Fourier transform. The T RMSE of the embedded reconstructions was reduced by 37–76% compared to the CS reconstructions when using undersampled simulated data with the reduction growing with larger acceleration factors. The proposed, embedded model outperformed the reference methods on the experimental test case as well, especially providing robustness with higher acceleration factors.

Quantitative T2 and T1ρ mapping are sensitive to ischemic injury to the epiphyseal cartilage in an in vivo piglet model of Legg-Calvé-Perthes disease

To determine if the quantitative MRI techniques T2 and T1ρ mapping are sensitive to ischemic injury to epiphyseal cartilage in vivo in a piglet model of Legg-Calvé-Perthes disease using a clinical 3T MRI scanner. We hypothesized that T2 and T1ρ relaxation times would be increased in the epiphyseal cartilage of operated vs contralateral-control femoral heads 1week following onset of ischemia. Unilateral femoral head ischemia was surgically induced in eight piglets. Piglets were imaged 1week post-operatively in vivo at 3T MRI using a magnetization-prepared 3D fast spin echo sequence for T2 and T1ρ mapping and a 3D gradient echo sequence for cartilage segmentation. Ischemia was confirmed in all piglets using gadolinium contrast-enhanced MRI. Median T2 and T1ρ relaxation times were measured in the epiphyseal cartilage of the ischemic and control femoral heads and compared using paired t-tests. Histological assessment was performed on a subset of five piglets. T2 and T1ρ relaxation times were significantly increased in the epiphyseal cartilage of the operated vs control femoral heads (ΔT2=11.9±3.7ms, 95% CI=[8.8, 15.0] ms, P<0.0001; ΔT1ρ=12.8±4.1ms, 95% CI=[9.4, 16.2] ms, P<0.0001). Histological assessment identified chondronecrosis in the hypertrophic and deep proliferative zones within ischemic epiphyseal cartilage. T2 and T1ρ mapping are sensitive to ischemic injury to the epiphyseal cartilage in vivo at clinical 3T MRI. These techniques may be clinically useful to assess injury and repair to the epiphyseal cartilage to better stage the extent of ischemic damage in Legg-Calvé-Perthes disease.

Biomechanical Effects of Chronic Ankle Instability on the Talar Cartilage Matrix: The Value of T1ρ Relaxation Mapping Without and With Mechanical Loading.

T1ρ mapping has been proposed for the detection of early cartilage degeneration associated with chronic ankle instability (CAI). However, there are limited data surrounding the influence of ankle loading on T1ρ relaxation. To evaluate T1ρ relaxation times of talar cartilage, as an indicator of early degenerative changes, associated with CAI and to investigate the influence of acute axial in situ loading on T1ρ values in CAI patients and healthy controls. Prospective. A total of 9 patients (age=21.8 ± 2.5 years, male/female=2/7) with chronic ankle instability and 18 healthy control subjects (age=22.8 ± 3.6 years, male/female=5/13). 3 T. 3D gradient echo fast low-angle shot (FLASH) sequence augmented with a variable spin-lock preparation period. Ankle T1ρ mapping was performed without and with axial loading of 500 N. The talar cartilage was segmented in five coronal slices covering the central talocrural joint. Median talar T1ρ values were separately calculated for the medial and lateral facets. Mann-Whitney U and Wilcoxon signed-rank tests, significance level: P < 0.05. For the combined cohorts, the statistical analysis yielded significantly lower T1ρ values with loading compared to the no-load measurement for both the lateral (no load: [51.0 ± 4.0] msec, load: [49.5 ± 5.4] msec) as well as the medial compartment (no load: [50.0 ± 5.4] msec, load: [47.8 ± 6.8] msec). In the unloaded scans, the CAI patients showed significantly increased talar T1ρ values ([53.0 ± 7.4] mse ) compared to the healthy control subjects ([48.8 ± 4.1] msec) in the medial compartment. Increased talar T1ρ relaxation times in CAI patients compared to healthy controls suggest that T1ρ relaxation is a sensitive biomarker for CAI-induced early-stage cartilage degeneration. However, the load-induced T1ρ change did not prove to be a viable marker for the altered biomechanical properties of the hyaline talar cartilage. 2 LEVEL OF EFFICACY: Stage 2.

Imaging Evaluation of Intervertebral Disc Degeneration and Painful Discs-Advances and Challenges in Quantitative MRI.

In recent years, various quantitative and functional magnetic resonance imaging (MRI) sequences have been developed and used in clinical practice for the diagnosis of patients with low back pain (LBP). Until now, T2-weighted imaging (T2WI), a visual qualitative evaluation method, has been used to diagnose intervertebral disc (IVD) degeneration. However, this method has limitations in terms of reproducibility and inter-observer agreement. Moreover, T2WI observations do not directly relate with LBP. Therefore, new sequences such as T2 mapping, T1ρ mapping, and MR spectroscopy have been developed as alternative quantitative evaluation methods. These new quantitative MRIs can evaluate the anatomical and physiological changes of IVD degeneration in more detail than conventional T2WI. However, the values obtained from these quantitative MRIs still do not directly correlate with LBP, and there is a need for more widespread use of techniques that are more specific to clinical symptoms such as pain. In this paper, we review the state-of-the-art methodologies and future challenges of quantitative MRI as an imaging diagnostic tool for IVD degeneration and painful discs.

Efficient phase-cycling strategy for high-resolution 3D gradient-echo quantitative parameter mapping.

Magnetization-prepared (MP) gradient-echo (GRE) sequences suffer from signal contaminations from T1 recovery during the readout train, which can be eliminated by paired RF phase cycling (PC) at the cost of doubling the scan time. The objective of this study was to develop and validate a novel unpaired PC strategy to eliminate the time penalty for high-resolution quantitative parameter mapping in 3D MP-GRE sequences. Based on the observation that the contaminating T1 recovery signal along the GRE readout train is independent of magnetization preparation, its impact can be eliminated using a novel curve-fitting approach with complex-valued data without needing paired PC acquisitions. Four new unpaired PC schemes were compared with two traditional paired PC schemes in both phantom and in vivo human knee studies at 3 T using a MP angle-modulated partitioned k-space spoiled gradient-echo snapshots (MAPSS) T1ρ mapping sequence. In the phantom study, all methods resulted in consistent T1ρ measurements (∆T1ρ < 0.5%) at the center slice when B0 /B1 values were uniform. Results were not consistent when off-center slices with nonideal B0 /B1 were included. Two unpaired PC schemes had comparable or significantly improved quantitative accuracy and scan-rescan reproducibility compared with the paired PC schemes. There was no significant T1ρ quantitative variability increase or spatial fidelity loss using the new unpaired PC schemes. Unpaired PC schemes also had different T1ρ spectral responses at different B0 frequency offsets, which can potentially be exploited to reduce sensitivity to B0 field inhomogeneities. The human knee study results were consistent with the phantom study findings. In conclusion, an unpaired PC strategy potentially allows more accurate quantitative parameter mapping with halved scan time compared with the paired PC approach to eliminate signal contaminations from T1 recovery. It therefore offers additional flexibility in SNR optimization, spatial resolution improvement, and choice of imaging sampling points to obtain more accurate quantitative parameter mapping.

Quantification correction for free-breathing myocardial T1ρ mapping in mice using a recursively derived description of a T1ρ* relaxation pathway

BackgroundFast and accurate T1ρ mapping in myocardium is still a major challenge, particularly in small animal models. The complex sequence design owing to electrocardiogram and respiratory gating leads to quantification errors in in vivo experiments, due to variations of the T1ρ relaxation pathway. In this study, we present an improved quantification method for T1ρ using a newly derived formalism of a T1ρ* relaxation pathway.MethodsThe new signal equation was derived by solving a recursion problem for spin-lock prepared fast gradient echo readouts. Based on Bloch simulations, we compared quantification errors using the common monoexponential model and our corrected model. The method was validated in phantom experiments and tested in vivo for myocardial T1ρ mapping in mice. Here, the impact of the breath dependent spin recovery time Trec on the quantification results was examined in detail.ResultsSimulations indicate that a correction is necessary, since systematically underestimated values are measured under in vivo conditions. In the phantom study, the mean quantification error could be reduced from − 7.4% to − 0.97%. In vivo, a correlation of uncorrected T1ρ with the respiratory cycle was observed. Using the newly derived correction method, this correlation was significantly reduced from r = 0.708 (p < 0.001) to r = 0.204 and the standard deviation of left ventricular T1ρ values in different animals was reduced by at least 39%.ConclusionThe suggested quantification formalism enables fast and precise myocardial T1ρ quantification for small animals during free breathing and can improve the comparability of study results. Our new technique offers a reasonable tool for assessing myocardial diseases, since pathologies that cause a change in heart or breathing rates do not lead to systematic misinterpretations. Besides, the derived signal equation can be used for sequence optimization or for subsequent correction of prior study results.

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± 45.4and 687.6± 44.5ms), T2 (22.5±2.6 and 22.1±2.5ms), and T1ρ (38.2±5.5and 38.2±5.5ms) 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.

Assessment of Calf Skeletal Muscle in Male Type 2 Diabetes Mellitus Patients With Different Courses Using T1ρ Mapping.

The current clinical methods for detecting skeletal muscle complications of type 2 diabetes mellitus (T2DM) are invasive and insensitive. There is an urgent need for noninvasive assessment of skeletal muscle microstructure changes during the disease progression and treatment to assist the clinical management. This work aimed to investigate the T2DM caused changes in the fast-twitch tibialis anterior (TA) and slow-twitch soleus (SOL) skeletal muscles using T1ρ magnetic resonance imaging (MRI). This cross-sectional study took place from December 2014 to December 2020 at Zhongda Hospital Southeast University. A total of 26 new-onset and 15 long-term T2DM patients were enrolled, with the addition of 20 young and 13 older healthy volunteers as age-matched controls. T1ρ relaxation times of SOL and TA muscles in different groups were measured. Parametric and nonparametric tests were used to analyze the relationship between the T1ρ values in SOL and TA muscles and the length of illness, level of fasting blood glucose, and status of homeostasis model assessment of insulin resistance (HOMA-IR). T1ρ relaxation times of SOL and TA muscles both of new-onset and long-term T2DM patients were significantly higher than those of the young (P < .01, P < .05) and older healthy controls (P < .05, P < .01). Positive correlations were observed between the T1ρ relaxation times of the TA or SOL and the duration of T2DM (R2 = 0.420, R2 = 0.326), the level of fasting blood glucose (R2 = 0.253, R2 = 0.071) and HOMA-IR (R2 = 0.232, R2 = 0.414). Quantitative MRI measurement of T1ρ provides a noninvasive tool to assess T2DM-induced changes in the skeletal muscles of T2DM patients.

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

To compare different optimization approaches for choosing the spin-lock times (TSLs), in spin-lattice relaxation time in the rotating frame (T1ρ ) mapping. 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. 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). 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.

In-Situ Cartilage Functionality Assessment Based on Advanced MRI Techniques and Precise Compartmental Knee Joint Loading through Varus and Valgus Stress.

Stress MRI brings together mechanical loading and MRI in the functional assessment of cartilage and meniscus, yet lacks basic scientific validation. This study assessed the response-to-loading patterns of cartilage and meniscus incurred by standardized compartmental varus and valgus loading of the human knee joint. Eight human cadaveric knee joints underwent imaging by morphologic (i.e., proton density-weighted fat-saturated and 3D water-selective) and quantitative (i.e., T1ρ and T2 mapping) sequences, both unloaded and loaded to 73.5 N, 147.1 N, and 220.6 N of compartmental pressurization. After manual segmentation of cartilage and meniscus, morphometric measures and T2 and T1ρ relaxation times were quantified. CT-based analysis of joint alignment and histologic and biomechanical tissue measures served as references. Under loading, we observed significant decreases in cartilage thickness (p < 0.001 (repeated measures ANOVA)) and T1ρ relaxation times (p = 0.001; medial meniscus, lateral tibia; (Friedman test)), significant increases in T2 relaxation times (p ≤ 0.004; medial femur, lateral tibia; (Friedman test)), and adaptive joint motion. In conclusion, varus and valgus stress MRI induces meaningful changes in cartilage and meniscus secondary to compartmental loading that may be assessed by cartilage morphometric measures as well as T2 and T1ρ mapping as imaging surrogates of tissue functionality.