Spin-lock Times Research Articles

Novel spin-lock time sampling strategies for improved reproducibility in quantitative T1ρ mapping.

This study aimed to optimize the sampling of spin-lock times (TSLs) in quantitative T1ρ mapping for improved reproducibility. Two new TSL sampling schemes were proposed: (i) reproducibility-guided random sampling (RRS) and (ii) reproducibility-guided optimal sampling (ROS). They were compared to the existing linear sampling (LS) and precision-guided sampling (PS) schemes for T1ρ reproducibility through numerical simulations, phantom experiments, and volunteer studies. Each study evaluated the four sampling schemes with three commonly used T1ρ preparations based on composite and balanced spin-locking. Additionally, the phantom and volunteer studies investigated the impact of B0 and B1 field inhomogeneities on T1ρ reproducibility, respectively. The reproducibility was assessed using the coefficient of variation (CoV) by repeating the T1ρ measurements eight times for phantom experiments and five times for volunteer studies. Numerical simulations resulted in lower mean CoVs for the proposed RRS (1.74%) and ROS (0.68%) compared to LS (2.93%) and PS (3.68%). In the phantom study, the mean CoVs were also lower for RRS (2.7%) and ROS (2.6%) compared to LS (4.1%) and PS (3.1%). Furthermore, the mean CoVs of the proposed RRS and ROS were statistically lower (P < 0.001) compared to existing LS and PS schemes at a B1 offset of 20%. In the volunteer study, consistently lower mean CoVs were observed in bilateral thigh muscles for RRS (9.3%) and ROS (9.2%) compared to LS (10.9%) and PS (10.2%), and the difference was more prominent at B0 offsets higher than 50 Hz. The proposed sampling schemes improve the reproducibility of quantitative T1ρ mapping by optimizing the selection of TSLs. This improvement is especially beneficial for longitudinal studies that track and monitor disease progression and treatment response.

Quantitative susceptibility and T1[formula omitted] mapping of knee articular cartilage at 3T

T1ρ and Quantitative Susceptibility Mapping (QSM) are evolving as substrates for quantifying the progressive nature of knee osteoarthritis. ObjectiveTo evaluate the effects of spin lock time combinations on depth-dependent T1ρ estimation, in adjunct to QSM, and characterize the degree of shared variance in QSM and T1ρ for the quantitative measurement of articular cartilage. DesignTwenty healthy participants (10 ​M/10F, 22.2 ​± ​3.4 years) underwent bilateral knee MRI using T1ρ MAPPS sequences with varying TSLs ([0–120] ms), along with a 3D spoiled gradient echo for QSM. Five total TSL combinations were used for T1ρ computation, and direct depth-based comparison. Depth-wide variance was assessed in comparison to QSM as a basis to assess for depth-specific variation in T1ρ computations across healthy cartilage. ResultsLonger T1ρ relaxation times were observed for TSL combinations with higher spin lock times. Depth-specific differences were documented for both QSM and T1ρ, with most change found at ∼60% depth of the cartilage, relative to the surface. Direct squared linear correlation revealed that most T1ρ TSL combinations can explain over 30% of the variability in QSM, suggesting inherent shared sensitivity to cartilage microstructure. ConclusionsT1ρ mapping is subjective to the spin lock time combinations used for computation of relaxation times. When paired with QSM, both similarities and differences in signal sensitivity may be complementary to capture depth-wide changes in articular cartilage.

Repeatability of Quantitative Knee Cartilage T1, T2, and T1ρ Mapping With 3D-MRI Fingerprinting.

Three-dimensional MR fingerprinting (3D-MRF) techniques have been recently described for simultaneous multiparametric mapping of knee cartilage. However, investigation of repeatability remains limited. To assess the intra-day and inter-day repeatabilities of knee cartilage T1, T2, and T1ρ maps using a 3D-MRF sequence for simultaneous measurement. Prospective. Fourteen healthy subjects (35.4 ± 9.3 years, eight males), scanned on Day 1 and Day 7. 3 T/3D-MRF, T1, T2, and T1ρ maps. The acquisition of 3D-MRF cartilage (simultaneous acquisition of T1, T2, and T1ρ maps) were acquired using a dictionary pattern-matching approach. Conventional cartilage T1, T2, and T1ρ maps were acquired using variable flip angles and a modified 3D-Turbo-Flash sequence with different echo and spin-lock times, respectively, and were fitted using mono-exponential models. Each sequence was acquired on Day 1 and Day 7 with two scans on each day. The mean and SD for cartilage T1, T2, and T1ρ were calculated in five manually segmented regions of interest (ROIs), including lateral femur, lateral tibia, medial femur, medial tibia, and patella cartilages. Intra-subject and inter-subject repeatabilities were assessed using coefficient of variation (CV) and intra-class correlation coefficient (ICC), respectively, on the same day and among different days. Regression and Bland-Altman analysis were performed to compare maps between the conventional and 3D-MRF sequences. The CV in all ROIs was lower than 7.4%, 8.4%, and 7.5% and the ICC was higher than 0.56, 0.51, and 0.52 for cartilage T1, T2, and T1ρ, respectively. The MRF results had a good agreement with the conventional methods with a linear regression slope >0.61 and R2 > 0.59. The 3D-MRF sequence had high intra-subject and inter-subject repeatabilities for simultaneously measuring knee cartilage T1, T2, and T1ρ with good agreement with conventional sequences. 1 TECHNICAL EFFICACY: Stage 1.

Poster 137: Influence of Body Mass Index on T1ρ Relaxation Times for Patellofemoral Cartilage: Patellar Dislocation Patients vs. Healthy Controls

Objectives: Patellar dislocations are associated with patellofemoral cartilage degradation following injury and a high risk of patellofemoral post-traumatic osteoarthritis (PTOA). Obesity is also a primary risk factor for patellofemoral cartilage degradation and OA, but the influence of obesity on cartilage degradation follow patellar dislocations is unknown. The current study uses T1ρ-based relaxation time mapping of patellofemoral cartilage to evaluate the influence of body mass index (BMI) on cartilage properties in the acute phase following a patellar dislocation, and compares the results to healthy knees. The hypothesis of the study is increasing BMI is associated with cartilage matrix degeneration for injured and healthy knees. Methods: The IRB-approved study focused on a BMI range from underweight to obese (&lt; 40 kg/m2). The population included 18 patients being treated conservatively for a unilateral, first-time patellar dislocation (20 ± 8 years, 9 females, BMI: 24 ± 5 kg/m2, 56 ± 39 days since dislocation), 12 patients being treated conservatively for multiple unilateral dislocations (19 ± 6 years, 9 females, 24 ± 5 kg/m2, 67 ± 35 days since most recent dislocation), and 16 healthy controls (21 ± 7 years, 7 females; 21 ± 7 kg/m2). MRI scans included a 3D water excitation double echo steady state (DESS) scan of the knee for segmentation of the cartilage surfaces (slice thickness of 0.7 mm) and a T1ρ relaxation time scan (fat saturated scan, slice thickness = 4 mm, spin lock times = 0, 10, 40, and 80 ms, spin-lock frequency = 500 Hz). Long T1ρ relaxation times indicate low proteoglycan concentration within cartilage. Automated algorithms based on machine learning were used to segment cartilage on the patella and within the trochlear groove. Additional automated algorithms mapped T1ρ relaxation times to the reconstructed cartilage surfaces (Fig. 1). Mean T1ρ relaxation times were quantified for patellar and trochlear groove cartilage for each knee. Linear regression were used to correlate T1ρ relaxation times with BMI for the single dislocation, multiple dislocations, and control groups. Statistical significance was set at p &lt; 0.05. Results: Patellofemoral T1ρ relaxation times increased with BMI for healthy control subjects, but decreased with BMI following patellar dislocation. For control subjects, the increase in T1ρ relaxation times with BMI was significant for cartilage on the patella and within the trochlear groove (r2 &gt; 0.4, p &lt; 0.01). For patients being treated for a single dislocation and multiple dislocations, the decrease in T1ρ relaxation times with increasing BMI was significant for cartilage on the patella and within the trochlear groove (r2 &gt; 0.25, p &lt; 0.025 for single dislocations, r2 &gt; 0.3, p &lt; 0.05 for multiple dislocations). Conclusions: The expected increase in T1ρ relaxation times with BMI was observed for healthy control subjects, but not for patients being treated for patellar dislocations. Elevated T1ρ values indicate loss of proteoglycan content that reduces cartilage integrity and could be an initiation point for progression to OA. For cartilage throughout the patellofemoral joint, T1ρ relaxation times decreased as BMI increased following patellar dislocation. The relationships were similar following one dislocation and multiple dislocations. The regression lines for injured knees and controls crossed at a BMI of approximately 25 for patellar and trochlear groove cartilage, indicating T1ρ relaxation times are higher for injured knees than healthy controls only for patients with a BMI &lt; 25 (underweight or healthy weight). Multiple previous studies have identified elevated patellofemoral cartilage relaxation times from quantitative MRI following single and multiple patellar dislocations, but no study has previously attributed the difference to patients with a low BMI. The mechanism by which a high BMI limits cartilage degradation following patellar dislocation is currently unknown. The opposing relationships between T1ρ relaxation times and BMI for injured knees and controls occur despite similar ranges for T1ρ times and BMI. The primary difference between injured knees and controls is the recent dislocation event, and the ensuing inflammatory response. The single and multiple dislocation groups have a recent dislocation and inflammation in common despite differences in time since the first dislocation. Impact injury to cartilage is primarily limited to the medial patella, so is unlikely to cause the difference in trends. Pathologic patellofemoral anatomy is a characteristic of knees with patellar instability that could also influence the relationship with BMI. Additional enrollment and characterization of anatomical factors and inflammatory conditions is needed to identify factors that interact with BMI. Follow up analyses are also needed to determine if these relationships weaken with time from injury.

Paper 05: Patellar Dislocation in Adolescent Patients: Influence on Patellofemoral and Tibiofemoral Cartilage based on T1ρ Relaxation Times

Paper 05: Patellar Dislocation in Adolescent Patients: Influence on Patellofemoral and Tibiofemoral Cartilage based on T1ρ Relaxation Times

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 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.

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.

Accelerating the 3D T1ρ mapping of cartilage using a signal-compensated robust tensor principal component analysis model.

Magnetic resonance (MR) quantitative T1ρ imaging has been increasingly used to detect the early stages of osteoarthritis. The small volume and curved surface of articular cartilage necessitate imaging with high in-plane resolution and thin slices for accurate T1ρ measurement. Compared with 2D T1ρ mapping, 3D T1ρ mapping is free from artifacts caused by slice cross-talk and has a thinner slice thickness and full volume coverage. However, this technique needs to acquire multiple T1ρ-weighted images with different spin-lock times, which results in a very long scan duration. It is highly expected that the scan time can be reduced in 3D T1ρ mapping without compromising the T1ρ quantification accuracy and precision. To accelerate the acquisition of 3D T1ρ mapping without compromising the T1ρ quantification accuracy and precision, a signal-compensated robust tensor principal component analysis method was proposed in this paper. The 3D T1ρ-weighted images compensated at different spin-lock times were decomposed as a low-rank high-order tensor plus a sparse component. Poisson-disk random undersampling patterns were applied to k-space data in the phase- and partition-encoding directions in both retrospective and prospective experiments. Five volunteers were involved in this study. The fully sampled k-space data acquired from 3 volunteers were retrospectively undersampled at R=5.2, 7.7, and 9.7, respectively. Reference values were obtained from the fully sampled data. Prospectively undersampled data for R=5 and R=7 were acquired from 2 volunteers. Bland-Altman analyses were used to assess the agreement between the accelerated and reference T1ρ measurements. The reconstruction performance was evaluated using the normalized root mean square error and the median of the normalized absolute deviation (MNAD) of the reconstructed T1ρ-weighted images and the corresponding T1ρ maps. T1ρ parameter maps were successfully estimated from T1ρ-weighted images reconstructed using the proposed method for all accelerations. The accelerated T1ρ measurements and reference values were in good agreement for R=5.2 (T1ρ: 40.4±1.4 ms), R=7.7 (T1ρ: 40.4±2.1 ms), and R=9.7 (T1ρ: 40.9±2.2 ms) in the Bland-Altman analyses. The T1ρ parameter maps reconstructed from the prospectively undersampled data also showed promising image quality using the proposed method. The proposed method achieves the 3D T1ρ mapping of in vivo knee cartilage in eight minutes using a signal-compensated robust tensor principal component analysis method in image reconstruction.

Staging Liver Fibrosis: Comparison of Native T1 Mapping, T2 Mapping, and T1ρ: An Experimental Study in Rats With Bile Duct Ligation and Carbon Tetrachloride at 11.7T MRI.

T1, T2, and T1ρ might be potential biomarkers for assessing liver fibrosis. However, few studies reported the value of them in different animal models. To investigate and compare the performances of T1, T2, and T1ρ for noninvasively staging liver fibrosis in bile duct ligation (BDL) or carbon tetrachloride (CCl4 ) model. Prospective animal model. Liver fibrosis was induced by BDL or injection of CCl4 in 120 rats. 11.7T, T1 mapping with 10 repetition times, T2 mapping with 32 echo times, and T1ρ with 10 spin-lock times. T1, T2, and T1ρ were measured and correlated with liver fibrosis stages, as well as the degree of inflammation, steatosis, iron deposition, and the expression of cytokeratin 19. The discriminative performance of T1, T2, and T1ρ for staging liver fibrosis was compared. One-way analysis of variance (ANOVA), Spearman's correlation analysis, factorial design ANOVA, and receiver operating characteristic curves (P < 0.05 was considered statistically significant). T1, T2, and T1ρ (BDL: rho=0.73, 0.85, 0.68; CCl4 : rho=0.80, 0.29, 0.61) were significantly correlated with liver fibrosis stages, while there was no significant difference in T2 among stage F0-F4 in the CCl4 model (P=0.204). The area under the curves (AUCs) range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.76-0.95, 0.89-0.98, and 0.80-0.94 in the CCl4 model. For the CCl4 model, the AUCs range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.83-0.95, 0.61-0.74, and 0.73-0.89, respectively. T2 had significantly higher AUC in the BDL model than CCl4 model for diagnosing liver fibrosis. The most sensitive and accurate method for staging liver fibrosis appeared to be T1 in our animal models followed by T1ρ. T2 may not be suitable for evaluating liver fibrosis. 1 TECHNICAL EFFICACY STAGE: 2.

Endogenous assessment of myocardial injury with single-shot model-based non-rigid motion-corrected T1 rho mapping

BackgroundCardiovascular magnetic resonance T1ρ mapping may detect myocardial injuries without exogenous contrast agent. However, multiple co-registered acquisitions are required, and the lack of robust motion correction limits its clinical translation. We introduce a single breath-hold myocardial T1ρ mapping method that includes model-based non-rigid motion correction.MethodsA single-shot electrocardiogram (ECG)-triggered balanced steady state free precession (bSSFP) 2D adiabatic T1ρ mapping sequence that collects five T1ρ-weighted (T1ρw) images with different spin lock times within a single breath-hold is proposed. To address the problem of residual respiratory motion, a unified optimization framework consisting of a joint T1ρ fitting and model-based non-rigid motion correction algorithm, insensitive to contrast change, was implemented inline for fast (~ 30 s) and direct visualization of T1ρ maps. The proposed reconstruction was optimized on an ex vivo human heart placed on a motion-controlled platform. The technique was then tested in 8 healthy subjects and validated in 30 patients with suspected myocardial injury on a 1.5T CMR scanner. The Dice similarity coefficient (DSC) and maximum perpendicular distance (MPD) were used to quantify motion and evaluate motion correction. The quality of T1ρ maps was scored. In patients, T1ρ mapping was compared to cine imaging, T2 mapping and conventional post-contrast 2D late gadolinium enhancement (LGE). T1ρ values were assessed in remote and injured areas, using LGE as reference.ResultsDespite breath holds, respiratory motion throughout T1ρw images was much larger in patients than in healthy subjects (5.1 ± 2.7 mm vs. 0.5 ± 0.4 mm, P < 0.01). In patients, the model-based non-rigid motion correction improved the alignment of T1ρw images, with higher DSC (87.7 ± 5.3% vs. 82.2 ± 7.5%, P < 0.01), and lower MPD (3.5 ± 1.9 mm vs. 5.1 ± 2.7 mm, P < 0.01). This resulted in significantly improved quality of the T1ρ maps (3.6 ± 0.6 vs. 2.1 ± 0.9, P < 0.01). Using this approach, T1ρ mapping could be used to identify LGE in patients with 93% sensitivity and 89% specificity. T1ρ values in injured (LGE positive) areas were significantly higher than in the remote myocardium (68.4 ± 7.9 ms vs. 48.8 ± 6.5 ms, P < 0.01).ConclusionsThe proposed motion-corrected T1ρ mapping framework enables a quantitative characterization of myocardial injuries with relatively low sensitivity to respiratory motion. This technique may be a robust and contrast-free adjunct to LGE for gaining new insight into myocardial structural disorders.

Collagen deposition in the liver is strongly and positively associated with T1rho elongation while fat deposition is associated with T1rho shortening: an experimental study of methionine and choline-deficient (MCD) diet rat model.

A number of questions concerning the histological mechanism of elongated T1rho in liver fibrosis remain unanswered. Using a rat model of non-alcoholic fatty liver disease (NAFLD) induced with methionine and choline-deficient (MCD) diet, the primary aim of this study is to clarify whether collagen deposition per se causes liver T1rho elongation. There were 45 rats in the NAFLD model group and 8 rats in the control group. NAFLD model rats were fed MCD diet for 1, 2, 4, 6, 8, or 10 weeks, respectively. At the endpoint, the rats had in vivo MRI at 3.0 T and followed by histology. For T1rho data acquisition, a rotary echo spin-lock pulse was implemented in a three-dimensional fast field echo sequence with frequency selective fat suppression. The spin-lock frequency was set to 500 Hz, and the spin-lock times of 5, 10, 40, and 50 ms were used. Liver specimens were processed with hematoxylin-eosin staining for steatosis and inflammation evaluation, and Masson's trichrome staining for collagen visualization. The semiquantitative histopathological evaluation was based on NASH Clinical Research Network criteria. Histomorphometric analysis calculated percentages of fat and collagen accumulations in the livers. A strong (r=0.82) and significant (P<0.0001) positive correlation between liver collagen content and liver T1rho was observed. Rats with no or minimal inflammation could have very long T1rho value. Among experimental rats without a positive fibrosis grading, five rats did not have an inflammation score (i.e., had minimal inflammation or no inflammation) while four had a positive inflammation score; the difference in liver T1rho between these two types of rats was minimal. Eight control rat livers and 15 stage-1 fibrosis rat livers were separated by liver T1rho completely. When four subgroups of experiment rats were selected where the liver collagen had a very narrow range within these subgroups, all these four subgroups showed a trend of negative correlation between liver fat and liver T1rho. Collagen deposition in the live strongly contributes to liver T1rho elongation, while fat deposition contributes to T1rho shortening. In a well-controlled experimental setting, T1rho measure alone allows separation of healthy livers and stage-1 liver fibrosis in the MCD rat liver model.

Rapid T1rho dispersion imaging for improved characterization of myocardial tissue using synthetic dispersion reconstruction

Abstract Introduction Over the past decade, CMRI has become the method of choice for characterizing fibrotic scars. Native T1ρ mapping offers an alternative to conventional T1 and T2 quantification techniques due to its high sensitivity to low-frequency processes. In addition, there is the possibility of T1ρ dispersion imaging, which could be used as a sensitive biomarker for assessing myocardial fibrosis [1]. However, due to a very long measurement time, T1ρ dispersion quantification in myocardium can hardly be done in the limited time of a small animal study. In this work we present a concept for rapid T1ρ dispersion quantification based on the new approach of synthetic dispersion reconstruction (SynDR). Theory A T1ρ map is calculated by measuring Nt T1ρ weighted images using different spin lock (SL) times. T1ρ dispersion quantification requires Nf T1ρ maps with different SL amplitudes. Hence the measurement time is very time consuming, because it requires the acquisition of Nt*Nf images (full mapping). With our new approach (SynDR), only a single T1ρ reference map and a series of dispersion weighted images need to be acquired. The T1ρ dispersion can be reconstructed by synthetically generated maps, whereby each map is calculated from the reference map and the dispersion weighted images, only requiring Nt+Nf images. Methods All measurements were performed on a 7T small animal scanner. The method was based on an optional cartesian/radial gradient echo sequence using large flip angles (45°) and an optimized readout sorting. The quantification accuracy of SynDR was compared with full mapping measurements in a phantom experiment and validated in vivo on mice. The synthetic T1ρ maps were used to perform a dispersion analysis in myocardium. Results The comparison between SynDR and the full mapping reference in phantoms showed a very high quantification accuracy with a mean/maximum deviation of 1.1% and 1.7%. Fig. 1 shows synthetic T1ρ maps (a) in healthy mice and the obtained dispersion map (b) using SynDR. In the dispersion analysis (c) a T1ρ slope of 5.6±1.5ms/kHz was obtained for myocardium. Here an acceleration factor of 4 could be realized in comparison to full mapping. In further measurements, an acceleration of 7.4 could be reached using a radial readout with KWIC filter view sharing. Discussion In this work, a novel T1ρ dispersion imaging method was presented that far exceeds the speed of conventional full mapping methods. The acceleration is based on avoiding unnecessary measurements of T1ρ weighted images through more efficient mathematical modeling. Further acceleration could be achieved using an optimized radial data acquisition. The method shows good image quality and high quantification accuracy both in phantom and in vivo. Based on the promising results, further studies in mice are planned to investigate the dispersion character of healthy and diseased tissues. Reference [1] Yin Q et al. Magn Reson Imaging. 2017 Oct; 42:69–73. SynDR method and T1ρ dispersion analysis Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): BRD, Bundesministerium für Bildung und Forschung

R1ρ at high spin-lock frequency could be a complementary imaging biomarker for liver iron overload quantification

PurposeTo compare the correlations among the R1ρ, R2, and R2* relaxation rates with liver iron concentration (LIC) in the assessment of rat liver iron content and explore the application potential of R1ρ in assessing liver iron content. MethodsIron dextran (dosage of 0, 25, 50, 100, and 200 mg/kg body weight) was injected into 35 male rats to increase the amount of iron storage in the liver. After one week, all rats were euthanized with isoflurane. A portion of the largest hepatic lobe was extracted to quantify the LIC by inductively coupled plasma, and the remaining liver tissue was stored in 4% buffered paraformaldehyde for 24 h before MRI. Spin-lock preparation with a RARE (rapid acquisition with relaxation enhancement) readout (9 different spin-lock times and 7 different spin-lock frequencies (FSLs)) and multi-echo UTE (ultrashort TE) pulses were developed to quantify R1ρ and R2 * on a Bruker 11.7 T MR system. For comparisons with R1ρ and R2*, R2 was acquired using the CPMG sequence. ResultsMean R1ρ values displayed dispersion, with decrease in R1ρ at higher FSLs. Spearman's correlation analysis (two-tailed) indicated that the R1ρ values were significantly associated with LIC at FSL = 2000, 2500, and 3000 Hz (r = 0.365 and P = 0.031, r = 0.608 and P < 0.001, and r = 0.764 and P < 0.001, respectively), and were not significantly associated with LIC at FSL = 500, 1000, 1250, and 1500 Hz (all P > 0.05). R2 and R2* showed significant linear correlations with LIC (r = 0.787 and P < 0.001, and r = 0.859 and P < 0.001, respectively). Correlation analysis across R1ρ, R2, and R* also suggested that the correlation strength between R1ρ and R2 and between R1ρ and R* showed an increasing trend with increase in FSL. ConclusionIn this study, a strong association was observed between R1ρ and LIC at high FSLs further confirming previous findings. The results demonstrated that R1ρ at high FSL might serve as a complementary imaging biomarker for liver iron overload quantification.

Non-Gaussian Diffusion Models and T1 rho Quantification in the Assessment of Hepatic Sinusoidal Obstruction Syndrome in Rats.

Non-Gaussian diffusion models and T1 rho quantification may reflect the changes in tissue heterogeneity in hepatic sinusoidal obstruction syndrome (SOS). To investigate the feasibility of diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and T1 rho quantification in detecting and staging SOS in a monocrotaline (MCT)-induced rat model. Animal study. Thirty male Sprague-Dawley rats gavaged with MCT to induce hepatic SOS and six male rats without any intervention. 3.0T, DWI with five b-values (0-2000 s/mm2 ) and T1 rho with five spin lock times (1-60 msec). MRI was performed 1 day before and 1, 3, 5, 7, and 10 days after MCT administration. The corrected apparent diffusion coefficient (Dapp ), kurtosis coefficient (Kapp ), distributed diffusion coefficient (DDC), and intravoxel water molecular diffusion heterogeneity (α) were calculated from the corresponding non-Gaussian diffusion model. The T1 rho value was calculated using a monoexponential model. Specimens obtained from the six timepoints were categorized into normal liver (n = 6), early-stage (n = 16), and late-stage (n = 14) SOS in accordance with the pathological score. Parametric statistical methods and receiver operating characteristic (ROC) curves were employed to determine diagnostic accuracy. The Dapp , Kapp , DDC, α, and T1 rho values were correlated with pathological score with r values of -0.821, 0.726, -0.828, -0.739, and 0.714 (all P < 0.001), respectively. DKI (combined Dapp and Kapp ) and SEM (combined DDC and α) were better than T1 rho for staging SOS. The areas under the ROC curve of DKI, SEM, and T1 rho for differentiating normal liver and early-stage SOS were 0.97, 1.00, and 0.79, whereas those of DKI, SEM, and T1 rho for differentiating early-stage and late-stage SOS were 1.00, 0.97, and 0.92, respectively. DKI, SEM, and T1 rho may be helpful in staging SOS. 2 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:1110-1121.

Respiratory motion-compensated high-resolution 3D whole-heart T1\u03c1 mapping

BackgroundCardiovascular magnetic resonance (CMR) T1ρ mapping can be used to detect ischemic or non-ischemic cardiomyopathy without the need of exogenous contrast agents. Current 2D myocardial T1ρ mapping requires multiple breath-holds and provides limited coverage. Respiratory gating by diaphragmatic navigation has recently been exploited to enable free-breathing 3D T1ρ mapping, which, however, has low acquisition efficiency and may result in unpredictable and long scan times. This study aims to develop a fast respiratory motion-compensated 3D whole-heart myocardial T1ρ mapping technique with high spatial resolution and predictable scan time.MethodsThe proposed electrocardiogram (ECG)-triggered T1ρ mapping sequence is performed under free-breathing using an undersampled variable-density 3D Cartesian sampling with spiral-like order. Preparation pulses with different T1ρ spin-lock times are employed to acquire multiple T1ρ-weighted images. A saturation prepulse is played at the start of each heartbeat to reset the magnetization before T1ρ preparation. Image navigators are employed to enable beat-to-beat 2D translational respiratory motion correction of the heart for each T1ρ-weighted dataset, after which, 3D translational registration is performed to align all T1ρ-weighted volumes. Undersampled reconstruction is performed using a multi-contrast 3D patch-based low-rank algorithm. The accuracy of the proposed technique was tested in phantoms and in vivo in 11 healthy subjects in comparison with 2D T1ρ mapping. The feasibility of the proposed technique was further investigated in 3 patients with suspected cardiovascular disease. Breath-hold late-gadolinium enhanced (LGE) images were acquired in patients as reference for scar detection.ResultsPhantoms results revealed that the proposed technique provided accurate T1ρ values over a wide range of simulated heart rates in comparison to a 2D T1ρ mapping reference. Homogeneous 3D T1ρ maps were obtained for healthy subjects, with septal T1ρ of 58.0 ± 4.1 ms which was comparable to 2D breath-hold measurements (57.6 ± 4.7 ms, P = 0.83). Myocardial scar was detected in 1 of the 3 patients, and increased T1ρ values (87.4 ± 5.7 ms) were observed in the infarcted region.ConclusionsAn accelerated free-breathing 3D whole-heart T1ρ mapping technique was developed with high respiratory scan efficiency and near-isotropic spatial resolution (1.7 × 1.7 × 2 mm3) in a clinically feasible scan time of ~ 6 mins. Preliminary patient results suggest that the proposed technique may find applications in non-contrast myocardial tissue characterization.

Age- and Gender-Associated Liver Physiological T1rho Dynamics Demonstrated with a Clinically Applicable Single-Breathhold Acquisition.

To understand women's and men's physiological ranges of liver T1rho relaxation time measured with a single breathhold black blood sequence, this healthy volunteer study was conducted in 62 women (mean age, 38.9 y; range, 18-75 y) and 34 men (mean age, 44.7 y; range, 24-80 y). Approval from the institutional ethics committee was obtained. Magnetic resonance imaging was performed with a 3.0T scanner with six spin-lock times of 0, 10, 20, 25, 35, and 50 ms and a single breathhold of 12 s per slice acquisition. Six slices were acquired for each examination. The results demonstrated that the female liver T1rho value ranged between 35.07 and 51.97 ms and showed an age-dependent decrease, with younger women having a higher measurement. The male liver T1rho value ranged between 34.94 and 43.39 ms, with no evidential age dependence. Postmenopausal women had similar liver T1rho values as men. For women, there was a trend that the liver T1rho value could be 4% to 5% lower during the menstrual phase than during the nonmenstrual phase. For both women and men, no evidential association was seen between body mass index and liver T1rho.

Breath-hold black-blood T1rho mapping improves liver T1rho quantification in healthy volunteers.

Background Recent researches suggest that T1rho may be a non-invasive and quantitative technique for detecting and grading liver fibrosis. Purpose To compare a multi-breath-hold bright-blood fast gradient echo (GRE) imaging and a single breath-hold single-shot fast spin echo (FSE) imaging with black-blood effect for liver parenchyma T1rho measurement and to study liver physiological T1rho value in healthy volunteers. Material and Methods The institutional Ethics Committee approved this study. 28 healthy participants (18 men, 10 women; age = 29.6 ± 5.1 years) underwent GRE liver T1rho imaging, and 20 healthy participants (10 men, 10 women; age = 36.9 ± 10.3 years) underwent novel black-blood FSE liver T1rho imaging, both at 3T with spin-lock frequency of 500 Hz. The FSE technique allows simultaneous acquisition of four spin lock times (TSLs; 1 ms, 10 ms, 30 ms, 50msec) in 10 s. Results For FSE technique the intra-scan repeatability intraclass correlation coefficient (ICC) was 0.98; while the inter-scan reproducibility ICC was 0.82 which is better than GRE technique's 0.76. Liver T1rho value in women tended to have a higher value than T1rho values in men (FSE: 42.28 ± 4.06 ms for women and 39.13 ± 2.12 ms for men; GRE: 44.44 ± 1.62 ms for women and 42.36 ± 2.00 ms for men) and FSE technique showed liver T1rho value decreased slightly as age increased. Conclusion Single breath-hold black-blood FSE sequence has better scan-rescan reproducibility than multi-breath-hold bright-blood GRE sequence. Gender and age dependence of liver T1rho in healthy participants is observed, with young women tending to have a higher T1rho measurement.

Black blood T1rho MR imaging may diagnose early stage liver fibrosis: a proof-of-principle study with rat biliary duct ligation model.

To explore black blood T1rho (T1ρ) liver imaging and investigate the earliest stage when biliary duct ligation (BDL) induced liver fibrosis can be diagnosed. MR was performed at 3 Tesla. A T1ρ prepared 2D fast spin echo (FSE) sequence with acquisition of four spin lock times (TSLs: 1, 10, 30, and 50 msec) and spin-lock frequency of 500 Hz was applied. Inherent black blood effect of FSE and double inversion recovery (DIR) achieved blood signal suppression, and 3 axial sections per liver were obtained. Male Sprague-Dawley rats were scanned at baseline (n=32), and on day-3 (n=13), day-5 (n=11), day-7 (n=10), day-10 (n=4) respectively after BDL. Hematoxylin-eosin (HE) and picrosirius red staining liver histology was obtained at these time points. The physiological liver parenchyma T1ρ was 38.38±1.53 msec (range, 36.05-41.53 msec). Liver T1ρ value elevated progressively after BDL. On day-10 after BDL all experimental animals can be separated from normal liver based on T1ρ measurement with lowest value being 42.82 msec. Day-7 and day-10 liver resembled METAVIR stage-F1/F2 fibrosis, and fibrous area counted for 0.22%±0.13% and 0.38%±0.44% of liver parenchyma area, respectively. This study provides the first proof-of-principle that T1ρ might diagnose early stage liver fibrosis.

In vivo quantitative whole-brain T1 rho MRI of multiple sclerosis.

To apply quantitative whole-brain T1 -rho (T1ρ ) and T2 imaging to the detection and quantification of brain changes resulting from multiple sclerosis (MS). Twenty-three MS patients with clinically isolated syndrome (10) and relapsing remitting MS (13) phenotypes, compared with 24 age-matched healthy controls were imaged at 3 Tesla. An axial T1ρ -weighted three-dimensional turbo spin echo sequence with a variable flip angle and fluid suppression was used. Spin-lock times of 0, 20, 40, 60, 80, and 100 ms were used. Corresponding T2 maps were also acquired. Whole brain white matter (WM) T1ρ maps were elevated compared with controls (P = 0.002). WM lesion T1ρ and T2 values were highly correlated (r = 0.83), but T1ρ demonstrated 25% better contrast to noise ratio (P < 0.001). WM lesion T1ρ correlated with disease duration. Gray matter T1ρ was negatively correlated with the Expanded Disability Status Scale, r = -0.45, P = 0.03. Normal appearing gray matter and cortical gray matter lesions were negatively correlated on T1ρ , but not on T2 (rT1ρ = -0.63, pT1ρ = 0.03; rT2 = -0.17, pT2 = 0.6). T1ρ MRI demonstrates enhanced lesion contrast compared with T2 , and in some cases may provide complementary information. T1ρ may provide a useful measure of demyelinating processes in MS.