Quantitative Skeletal Muscle Imaging Using 3D MR Fingerprinting With Water and Fat Separation

Reference Values for Water-Specific T1, Intermuscular and Intramuscular Fat Content in Skeletal Muscle at 2.89 T

BACKGROUND

MRI offers quantification of proton density fat fraction (PDFF) and tissue characteristics with T1 mapping. The influence of age, sex, and the potential confounding effects of fat on T1 values in skeletal muscle in healthy adults are insufficiently known.

PURPOSE

To determine the accuracy and repeatability of a saturation-recovery chemical-shift encoded multiparametric approach (SR-CSE) for quantification of T1Water and muscle fat content, and establish normative values (age, sex) from a healthy cohort.

STUDY TYPE

Prospective observational; phantoms (NiCL2-agarose T1 phantoms with no fat content; gadolinium T1 phantoms with mixed fat-water content).

POPULATIONS

A total of 130 healthy community-dwelling adults (63 male, 18-76 years) free of chronic health conditions that require regular prescription medication, and with no contraindications to MRI.

FIELD STRENGTH/SEQUENCE

2.89 T; gradient echo sequences including saturation-recovery chemical-shift encoded T1 mapping (SR-CSE); MOLLI; SASHA; CSE; and single voxel spectroscopy.

ASSESSMENT

SR-CSE provided T1Water and PDFF maps for assessment of intramuscular (MFIntra), intermuscular (MFInter), and subcutaneous fat and muscle volumes (thigh, paraspinal muscles). Comparison with MOLLI/SASHA T1 mapping.

STATISTICAL TESTS

Univariable and multivariable linear regression, general linear models, Bland and Altman, coefficient of variation (CV). P-value <0.05 was considered statistically significant.

RESULTS

Phantom and in vivo validation studies showed excellent accuracy of SR-CSE T1Water and PDFF vs. values from reference standards and repeatability CVs between 0.2% and 2.6% for T1Water, R2*, MFInter, MFIntra, subcutaneous fat and muscle volumes. Mean T1Water was 36 msec significantly higher in females (1445 ± 23 msec vs. 1409 ± 22 msec), with no age-effect (P = 0.35). Females had significantly higher values for MFInter (10.4% ± 4.8% vs. 7.1% ± 2.9%) and MFIntra (2.6% ± 1.0% vs. 2.3% ± 0.8%), both of which increased with age, secondary to lower muscle volume. MOLLI and SASHA T1 values had a fat-related bias of 21.7/35.0 msec per 1% increase in fat fraction (MFFIntra), in vivo, and a constant bias of -319.8/+35.6 msec, respectively.

DATA CONCLUSION

SR-CSE provides accurate (vs. phantoms) and repeatable assessment of water-specific T1 values and muscle and fat volumes. Conventional methods (SASHA, MOLLI) have a significant fat-modulated T1-bias. T1Water values are higher in females with no significant age dependence.

PLAIN LANGUAGE SUMMARY

We developed and tested the accuracy of a new MRI approach to measure tissue damage in skeletal muscle using a method called T1 mapping. The approach also provided matching images of fat within the muscle. We measured T1 values and muscle fat volumes in the thighs of 130 healthy adults to define normal values in healthy people and to understand if these values are influenced by age, sex, or weight. We found that our MRI technique accurately measured T1 values and fat volumes within muscle and we defined normal ranges of values, which were different in healthy males and females.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Bi-component dictionary matching for MR fingerprinting for efficient quantification of fat fraction and water T1 in skeletal muscle

PURPOSE

To propose an efficient bi-component MR fingerprinting (MRF) fitting method using a Variable Projection (VARPRO) strategy, applied to the quantification of fat fraction (FF) and water T1 (T 1 H 2 0 $$ \mathrm{T}{1}_{{\mathrm{H}}_20} $$ ) in skeletal muscle tissues.

METHODS

The MRF signals were analyzed in a two-step process by comparing them to the elements of separate water and fat dictionaries (bi-component dictionary matching). First, each pair of water and fat dictionary elements was fitted to the acquired signal to determine an optimal FF that was used to merge the fingerprints in a combined water/fat dictionary. Second, standard dictionary matching was applied to the combined dictionary for determining the remaining parameters. A clustering method was implemented to further accelerate the fitting. Accuracy, precision, and matching time of this approach were evaluated on both numerical and in vivo datasets, and compared to the reference dictionary-matching approach that includes FF as a dictionary parameter.

RESULTS

In numerical phantoms, all MRF parameters showed high correlation with ground truth for the reference and the bi-component method (R2  > 0.98). In vivo, the estimated parameters from the proposed method were highly correlated with those from the reference approach (R2  > 0.997). The bi-component method achieved an acceleration factor of up to 360 compared to the reference dictionary matching.

CONCLUSION

The proposed bi-component fitting approach enables a significant acceleration of the reconstruction of MRF parameter maps for fat-water imaging, while maintaining comparable precision and accuracy to the reference on FF andT 1 H 2 0 $$ \mathrm{T}{1}_{{\mathrm{H}}_20} $$ estimation.

Magnetic Resonance Fingerprinting: A Review of Clinical Applications

ABSTRACT

Magnetic resonance fingerprinting (MRF) is an approach to quantitative magnetic resonance imaging that allows for efficient simultaneous measurements of multiple tissue properties, which are then used to create accurate and reproducible quantitative maps of these properties. As the technique has gained popularity, the extent of preclinical and clinical applications has vastly increased. The goal of this review is to provide an overview of currently investigated preclinical and clinical applications of MRF, as well as future directions. Topics covered include MRF in neuroimaging, neurovascular, prostate, liver, kidney, breast, abdominal quantitative imaging, cardiac, and musculoskeletal applications.

3D MR fingerprinting using Seiffert spirals

PURPOSE

Seiffert spirals were recently explored as an efficient way to traverse 3D k-space compared to traditional 3D techniques. Several studies have shown the ability of 3D MR fingerprinting (MRF) techniques to acquire T₁ and T₂ relaxation maps in a short period of time. However, these sequences do not sample across a large region of 3D k-space every TR, especially in the way that Seiffert trajectories can.

METHODS

A 3D MRF sequence was designed using 8 Seiffert spirals rotated in 3D k-space, with flip angle modulation for T₁ and T₂ sensitivity. The sequence was compared to an MRF sequence using a 2D spiral rotated in 3D k-space using the tiny golden angle acquisition with similar resolution/readout duration. Both sequences were evaluated using simulations, phantom validation, and in vivo imaging.

RESULTS

In all experiments, the Seiffert spiral MRF sequence performed similar to if not better than the multi-axis 2D spiral MRF sequence. Strong intraclass correlation coefficients (> 0.9) were found between conventional and MRF sequences in phantoms, whereas the in vivo results showed slightly less aliasing artifact with the Seiffert trajectory.

CONCLUSION

In this study, Seiffert spirals were used within the MRF framework to acquire high-resolution T₁ and T₂ relaxation time maps in less than 2.5 min. The reduced aliasing artifacts seen with the Seiffert sequence suggests that sampling over 3D k-space evenly each TR can improve quantification or shorten scan times.

Whole-brain 3D MR fingerprinting brain imaging: clinical validation and feasibility to patients with meningioma

Purpose

MR fingerprinting (MRF) is a MR technique that allows assessment of tissue relaxation times. The purpose of this study is to evaluate the clinical application of this technique in patients with meningioma.

Materials and methods

A whole-brain 3D isotropic 1mm³ acquisition under a 3.0T field strength was used to obtain MRF T₁ and T₂-based relaxometry values in 4:38 s. The accuracy of values was quantified by scanning a quantitative MR relaxometry phantom. In vivo evaluation was performed by applying the sequence to 20 subjects with 25 meningiomas. Regions of interest included the meningioma, caudate head, centrum semiovale, contralateral white matter and thalamus. For both phantom and subjects, mean values of both T₁ and T₂ estimates were obtained. Statistical significance of differences in mean values between the meningioma and other brain structures was tested using a Friedman’s ANOVA test.

Results

MR fingerprinting phantom data demonstrated a linear relationship between measured and reference relaxometry estimates for both T₁ (r² = 0.99) and T₂ (r² = 0.97). MRF T₁ relaxation times were longer in meningioma (mean ± SD 1429 ± 202 ms) compared to thalamus (mean ± SD 1054 ± 58 ms; p = 0.004), centrum semiovale (mean ± SD 825 ± 42 ms; p < 0.001) and contralateral white matter (mean ± SD 799 ± 40 ms; p < 0.001). MRF T₂ relaxation times were longer for meningioma (mean ± SD 69 ± 27 ms) as compared to thalamus (mean ± SD 27 ± 3 ms; p < 0.001), caudate head (mean ± SD 39 ± 5 ms; p < 0.001) and contralateral white matter (mean ± SD 35 ± 4 ms; p < 0.001)

Conclusions

Phantom measurements indicate that the proposed 3D-MRF sequence relaxometry estimations are valid and reproducible. For in vivo, entire brain coverage was obtained in clinically feasible time and allows quantitative assessment of meningioma in clinical practice.