Assessment of myofiber microstructure changes due to atrophy and recovery with time-dependent diffusion MRI

Magnetic Resonance Imaging Biomarkers of Muscle

This review is focused on the current status of quantitative MRI (qMRI) of skeletal muscle. The first section covers the techniques of qMRI in muscle with the focus on each quantitative parameter, the corresponding imaging sequence, discussion of the relation of the measured parameter to underlying physiology/pathophysiology, the image processing and analysis approaches, and studies on normal subjects. We cover the more established parametric mapping from T1-weighted imaging for morphometrics including image segmentation, proton density fat fraction, T2 mapping, and diffusion tensor imaging to emerging qMRI features such as magnetization transfer including ultralow TE imaging for macromolecular fraction, and strain mapping. The second section is a summary of current clinical applications of qMRI of muscle; the intent is to demonstrate the utility of qMRI in different disease states of the muscle rather than a complete comprehensive survey.

From Voxels to Physiology: A Review of Diffusion Magnetic Resonance Imaging Applications in Skeletal Muscle

Skeletal muscle has a classic structure function relationship; both skeletal muscle microstructure and architecture are directly related to force generating capacity. Biopsy, the gold standard for evaluating muscle microstructure, is highly invasive, destructive to muscle, and provides only a small amount of information about the entire volume of a muscle. Similarly, muscle fiber lengths and pennation angles, key features of muscle architecture predictive of muscle function, are traditionally studied via cadaveric dissection. Noninvasive techniques such as diffusion magnetic resonance imaging (dMRI) offer quantitative approaches to study skeletal muscle microstructure and architecture. Despite its prevalence in applications for musculoskeletal research, clinical adoption is hindered by a lack of understanding regarding its sensitivity to clinically important biomarkers such as muscle fiber cross-sectional area. This review aims to elucidate how dMRI has been utilized to study skeletal muscle, covering fundamentals of muscle physiology, dMRI acquisition techniques, dMRI modeling, and applications where dMRI has been leveraged to noninvasively study skeletal muscle changes in response to disease, aging, injury, and human performance. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Time-dependent diffusion tensor imaging and diffusion modeling of age-related differences in the medial gastrocnemius and feasibility study of correlations to histopathology

PURPOSE

Implement STEAM-DTI to model time-dependent diffusion eigenvalues using the random permeable barrier model (RPBM) to study age-related differences in the medial gastrocnemius (MG) muscle. Validate diffusion model-extracted fiber diameter for histological assessment.

METHODS

Diffusion imaging at different diffusion times (Δ) was performed on seven young and six senior participants. Time-dependent diffusion eigenvalues (λ2 (t), λ3 (t), and D⊥ (t); average of λ2 (t) and λ3 (t)) were fit to the RPBM to extract tissue microstructure parameters. Biopsy of the MG tissue for histological assessment was performed on a subset of participants (four young, six senior).

RESULTS

λ3 (t) was significantly higher in the senior cohort for the range of diffusion times. RPBM fits to λ2 (t) yielded fiber diameters in agreement to those from histology for both cohorts. The senior cohort had lower values of volume fraction of membranes, ζ, in fits to λ2 (t), λ3 (t), and D⊥ (t) (significant for fit to λ3 (t)). Fits of fiber diameter from RPBM to that from histology had the highest correlation for the fit to λ2 (t).

CONCLUSION

The age-related patterns in λ2 (t) and λ3 (t) could tentatively be explained from RPBM fits; these patterns may potentially arise from a decrease in fiber asymmetry and an increase in permeability with age.

Double pulsed field gradient diffusion MRI to assess skeletal muscle microstructure

PURPOSE

Preliminary study to determine whether double pulsed field gradient (PFG) diffusion MRI is sensitive to key features of muscle microstructure related to function.

METHODS

The restricted diffusion profile of molecules in models of muscle microstructure derived from histology were systematically simulated using a numerical simulation approach. Diffusion tensor subspace imaging analysis of the diffusion signal was performed, and spherical anisotropy (SA) was calculated for each model. Linear regression was used to determine the predictive capacity of SA on the fiber area, fiber diameter, and surface area to volume ratio of the models. Additionally, a rat model of muscle hypertrophy was scanned using a single PFG and a double PFG pulse sequence, and the restricted diffusion measurements were compared with histological measurements of microstructure.

RESULTS

Excellent agreement between SA and muscle fiber area (r2  = 0.71; p < 0.0001), fiber diameter (r2  = 0.83; p < 0.0001), and surface area to volume ratio (r2  = 0.97; p < 0.0001) in simulated models was found. In a scanned rat leg, the distribution of these microstructural features measured from histology was broad and demonstrated that there is a wide variance in the microstructural features observed, similar to the SA distributions. However, the distribution of fractional anisotropy measurements in the same tissue was narrow.

CONCLUSIONS

This study demonstrates that SA-a scalar value from diffusion tensor subspace imaging analysis-is highly sensitive to muscle microstructural features predictive of function. Furthermore, these techniques and analysis tools can be translated to real experiments in skeletal muscle. The increased dynamic range of SA compared with fractional anisotropy in the same tissue suggests increased sensitivity to detecting changes in tissue microstructure.

Clinical applications of skeletal muscle diffusion tensor imaging

Diffusion tensor imaging (DTI) may allow the determination of new threshold values, based on water anisotropy, to differentiate between healthy muscle and various pathological processes. Additionally, it may quantify treatment monitoring or training effects. Most current studies have evaluated the potential of DTI of skeletal muscle to assess sports-related injuries or therapy, and training monitoring. Another critical area of application of this technique is the characterization and monitoring of primary and secondary myopathies. In this manuscript, we review the application of DTI in the evaluation of skeletal muscle in these and other novel clinical scenarios, with emphasis on the use of quantitative imaging-derived biomarkers. Finally, the main limitations of the introduction of DTI in the clinical setting and potential areas of future use are discussed.

Diffusion-tensor magnetic resonance imaging captures increased skeletal muscle fibre diameters in Becker muscular dystrophy

BACKGROUND

Becker muscular dystrophy (BMD) is an X-linked disorder characterized by slow, progressive muscle damage and muscle weakness. Hallmarks include fibre-size variation and replacement of skeletal muscle with fibrous and adipose tissues, after repeated cycles of regeneration. Muscle histology can detect these features, but the required biopsies are invasive, are difficult to repeat and capture only small muscle volumes. Diffusion-tensor magnetic resonance imaging (DT-MRI) is a potential non-invasive alternative that can calculate muscle fibre diameters when applied with the novel random permeable barrier model (RPBM). In this study, we assessed muscle fibre diameters using DT-MRI in BMD patients and healthy controls and compared these with histology.

METHODS

We included 13 BMD patients and 9 age-matched controls, who underwent water-fat MRI and DT-MRI at multiple diffusion times, allowing RPBM parameter estimation in the lower leg muscles. Tibialis anterior muscle biopsies were taken from the contralateral leg in 6 BMD patients who underwent DT-MRI and from an additional 32 BMD patients and 15 healthy controls. Laminin and Sirius-red stainings were performed to evaluate muscle fibre morphology and fibrosis. Twelve ambulant patients from the MRI cohort underwent the North Star ambulatory assessment, and 6-min walk, rise-from-floor and 10-m run/walk functional tests.

RESULTS

RPBM fibre diameter was significantly larger in BMD patients (P = 0.015): mean (SD) = 68.0 (25.3) μm versus 59.4 (19.2) μm in controls. Inter-muscle differences were also observed (P ≤ 0.002). Both inter- and intra-individual RPBM fibre diameter variability were similar between groups. Laminin staining agreed with the RPBM, showing larger median fibre diameters in patients than in controls: 72.5 (7.9) versus 63.2 (6.9) μm, P = 0.006. However, despite showing similar inter-individual variation, patients showed more intra-individual fibre diameter variability than controls-mean variance (SD) = 34.2 (7.9) versus 21.4 (6.9) μm, P < 0.001-and larger fibrosis areas: median (interquartile range) = 21.7 (5.6)% versus 14.9 (3.4)%, P < 0.001. Despite good overall agreement of RPBM and laminin fibre diameters, they were not associated in patients who underwent DT-MRI and muscle biopsy, perhaps due to lack of colocalization of DT-MRI with biopsy samples.

CONCLUSIONS

DT-MRI RPBM metrics agree with histology and can quantify changes in muscle fibre size that are associated with regeneration without the need for biopsies. They therefore show promise as imaging biomarkers for muscular dystrophies.

Metabolic activity diffusion imaging (MADI): I. Metabolic, cytometric modeling and simulations

Evidence mounts that the steady-state cellular water efflux (unidirectional) first-order rate constant (k_io [s^-1 ]) magnitude reflects the ongoing, cellular metabolic rate of the cytolemmal Na⁺ , K⁺ -ATPase (NKA), ^c MR_NKA (pmol [ATP consumed by NKA]/s/cell), perhaps biology's most vital enzyme. Optimal ¹ H₂ O MR k_io determinations require paramagnetic contrast agents (CAs) in model systems. However, results suggest that the homeostatic metabolic k_io biomarker magnitude in vivo is often too large to be reached with allowable or possible CA living tissue distributions. Thus, we seek a noninvasive (CA-free) method to determine k_io in vivo. Because membrane water permeability has long been considered important in tissue water diffusion, we turn to the well-known diffusion-weighted MRI (DWI) modality. To analyze the diffusion tensor magnitude, we use a parsimoniously primitive model featuring Monte Carlo simulations of water diffusion in virtual ensembles comprising water-filled and -immersed randomly sized/shaped contracted Voronoi cells. We find this requires two additional, cytometric properties: the mean cell volume (V [pL]) and the cell number density (ρ [cells/μL]), important biomarkers in their own right. We call this approach metabolic activity diffusion imaging (MADI). We simulate water molecule displacements and transverse MR signal decays covering the entirety of b-space from pure water (ρ = V = 0; k_io undefined; diffusion coefficient, D₀ ) to zero diffusion. The MADI model confirms that, in compartmented spaces with semipermeable boundaries, diffusion cannot be described as Gaussian: the nanoscopic D (D_n ) is diffusion time-dependent, a manifestation of the "diffusion dispersion". When the "well-mixed" (steady-state) condition is reached, diffusion becomes limited, mainly by the probabilities of (1) encountering (ρ, V), and (2) permeating (k_io ) cytoplasmic membranes, and less so by D_n magnitudes. Importantly, for spaces with large area/volume (A/V; claustrophobia) ratios, this can happen in less than a millisecond. The model matches literature experimental data well, with implications for DWI interpretations.