Muscle Disorders: Diagnosis & Clinical Biomarkers
Pierre G. Carlier1

1Institute of Myology, Pitie-Salpetriere University Hospital, AIM & CEA NMR Laboratory, Paris, France

Synopsis

.

Muscle disorders can be divided in two main categories, the inherited ones and the acquired ones.

In both categories, chronic muscle damage results in fatty infiltration and replacement. Selective muscle involvement or sparing creates patterns of fatty infiltration, which may help to reach a diagnosis or even in some instances be specific of a particular gene mutation. In the most standard clinical approach, axial T1w SE images of the lower limbs (thigh and leg) are acquired. Inflammation, or more precisely oedema irrespective of its origin, or even in some instances myocyte disorganisation, is classically detected by fat saturated T2w sequences, most often STIR T2w or one of its many variants.

Modern clinical examination favour whole-body imaging schemes, whose introduction and acceptance is facilitated by faster acquisitions obtained with parallel imaging, compressed sensing and/or multiple slice excitation.

Qualitative imaging and visual appreciation offer very limited performance when it comes to monitor disease progression and response to treatment. Quantitative water-fat imaging, most often using a variant of the Dixon sequences family, is nowadays integrated in most clinical research protocols. State-of-the-art methodology implements multi-peak lipid quantification, either from a multi-TE GE sequence acquisition, or by assuming known ratios of lipid resonances in the reconstruction algorithm. Muscle fat fraction (FF), muscle cross sectional area (CSA), contractile or more exactly lean muscle CSA [cCSA = CSA.(1-FF)] are the variables usually extracted. They have shown a superior sensitivity to disease progression, in particular the FF which is able to pick up increases of the order of 1 percent and has been reported to have a higher discriminant power than clinical evaluation or functional evaluation in many diseases.

Water T2 is the quantitative counterpart of the qualitative STIR T2w contrast. It can be measured locally using single voxel 1H NMR spectroscopy or water T2 maps can be generated using multi-TE SE sequences. Water T2 changes are non-specific and may reflect a large range of diseases and conditions, oedema, inflammation, necrosis, muscle dystrophy… There is a transient physiological increase in T2 post-exercise. While non-specific, water T2 is relatively to highly sensitive to the intensity of the underlying mechanisms. In several diseases, a relation was found between the water T2 and the increase in FF in the subsequent months and years, which confers water T2 some predictive value.

Water-fat and water T2 imaging can be acquired simultaneously, either by integrating a Dixon motive in a multi TE SE echo train or by separating water and fat based on their T2 difference, also with a multi-TE SE sequence, but this time using a product sequence. Both approaches have been implemented in clinical studies.

Recently, muscle global T1 mapping was shown to be able to quantify fatty infiltration as efficiently as the chemical shift based reference Dixon sequences, while muscle water T1 was found to increase in inflammatory, oedematous muscles, contradicting a dogma dating back to the very origin of NMR imaging. Using a MR fingerprinting approach, both muscle fat fraction and water T1 can be measured with a single fast acquisition.

Modern 23Na NMR imaging evaluates not only total sodium content, but also, via T1 differences or quantum filters, it senses intra- and extracellular compartments and interaction with macromolecules. Muscle 23Na images were shown to be abnormal in channelopathies and in Duchenne muscular dystrophy. Intracellular sodium changes were detected in non-fatty infiltrated muscles displaying no water T2 increase, suggesting that it might be a very early marker of disease activity in Duchenne patients.

Other potential biomarkers of muscle disorder activity have been identified in dystrophic muscles: an alkaline intramyocytic pH which can be determined using the 1H NMR spectroscopy of carnosine, a decreased intracellular free magnesium concentration, calculated from the ATP 31P chemical shift dependence on Mg-binding, an increased phosphodiester level in the 31P spectrum at rest, that is present before any detectable fatty infiltration and likely reflects an abnormal membrane phospholipid turnover.

Diffusion weighted imaging, diffusion tensor imaging sequences and fiber tracking algorithms developed for brain applications have been adapted for skeletal muscle applications. Most studies published so far have detected an increase in apparent diffusion coefficient and a reduced fractional anisotropy in diseased muscle, with no clear demonstration of a real added value compared to water T2 maps. Refined acquisition schemes to sense diffusion restriction combined with efficient fat suppression and development of muscle specific models will likely provide much deeper insight into muscle micro-architecture alterations in disease.

Muscle perfusion can be dynamically and non-invasively assessed using arterial spin labelling (ASL). No satisfactory solution has yet been found to prevent the ASL signal to disappear in the noise generated by an isotonic exercise but post ischemic or post-exercise ASL measurements of perfusion have been realised in a number of exercise physiology of clinical research studies. A negative BOLD signal develops during muscle ischemia and a positive BOLD appears during reactive hyperemia, which has been taken as a surrogate for perfusion measurements in volunteers and in patients. NMR venous blood oximetry has been proposed based either on T2 relaxometry or on intravascular susceptibility measurements and has been elegantly combined with ASL perfusion measurements to calculate muscle oxygen consumption using Fick principle.

For more than three decades, dynamic 31P spectroscopy of skeletal muscle has been the preferred method to investigate muscle energetics non-invasively. Changes in pH, phosphocreatine, and calculated ADP concentration, the key regulator of the mitochondrial oxidative phosphorylation, can be monitored during incremental exercise and maximum mitochondrial ATP production can be measured from the creatine rephosphorylation rate during exercise recovery. 31P spectroscopy can objectify exercise intolerance, diagnose glycogenosis type III, V and VII by an absence of muscle acidification and mitochondrial myopathy, when the mitochondrial gene defect is expressed in the muscle investigated.

Interleaved acquisitions measuring simultaneously muscle perfusion, oxygenation and ATP production were first developed on research spectrometers and were recently implemented in clinical scanners. Several studied have been published and demonstrate the versatility and the potential of the method, for instance to refine our understanding of energy production control in athletes or to identify limiting factors of performance in elderly subjects.

In relation with the investigation of muscle disorders, some of the current unmet or only partially unmet needs or prerequisites are:

- quantitative measurements interpretation relies on validated reference values. In many instances, particularly but not exclusively for muscle trophicity indices, these reference values are missing and most useful but unrewarding efforts have to be devoted to such benchmarking, with a special emphasis on pediatric populations;

- muscle disorders are rare diseases and, apart from purely diagnostic investigation, multicentre trials are the rule. Introduction of more advanced sequences in clinical research is considerably slowed down by the necessity to rewrite sequences for each different platform. Using a generic programming environment would greatly facilitate the task;

- fast is never fast enough. Knowing the time constraints of clinical NMR examinations, the faster the sequences are, the more contrasts can be investigated;

- manual muscle segmentation is a bottleneck in the data processing workflow. Previous attempts of using automatic segmentation software have essentially failed. Artificial intelligence using convolutional neuronal network has already produced promising results and will have to confirm its potentialities;

- muscle interstitial fibrosis is the other chronic degenerative change that characterizes many diseases, with deleterious functional consequences ranging from muscle stiffness, altered microcirculatory adaptation to impaired muscle regeneration. A whole lot of NMR contrasts are more or less sensitive to fibrosis, but with no specificity, and the frequent concurrent pathological changes that are also impacting these contrasts in one direction or another make disentangling and quantification of fibrosis a most challenging and currently unsolved problem;

- advanced diffusion sequences and diffusion models finely tuned for the skeletal muscle specificities, starting with its much shorter T2 than the brain, are awaited to better understand tissue microarchitecture alteration in diseases, including abnormal sarcolemma permeability in dystrophinopathies;

- while we already have a number of interesting options, some summarized above, identification of novel imaging and also spectroscopic predictive biomarkers of disease progression and very early indicators of muscle response to treatment remains a top priority and should receive the highest level of attention.

Acknowledgements

No acknowledgement found.

References

Boesch C (2007) Musculoskeletal spectroscopy. J Magn Reson Imaging. 25:321-38.

Burakiewicz J, Sinclair CDJ, Fischer D, et al (2017) Quantifying fat replacement of muscle by quantitative MRI in muscular dystrophy. J Neurol 264:2053–67.

Carlier PG, Bertoldi D, Baligand C, et al (2006) Muscle blood flow and oxygenation measured by NMR. NMR Biomed. 19:954-67.

Carlier PG, Marty B, Scheidegger O, et al (2016) Skeletal muscle quantitative nuclear magnetic resonance imaging and spectroscopy as an outcome measure for clinical trials. J Neuromuscul Dis 3:1–28.

Damon BM, Froeling M, Buck AKW, et al (2017) Skeletal muscle diffusion tensor-MRI fiber tracking: rationale, data acquisition and analysis methods, applications and future directions. NMR Biomed.30:e3563.

Duteil S, Bourrilhon C, Raynaud JS, et al (2004). Metabolic and vascular support for the role of myoglobin in humans: A multiparametric NMR study. Am J Physiol Regul Integr Comp Physiol. 287:R1441-9.

Englund EK, Langham MC, Ratcliffe SJ, et al (2015) Multiparametric assessment of vascular function in peripheral artery disease: Dynamic measurement of skeletal muscle per- fusion, blood-oxygen-level dependent signal, and venous oxygen saturation. Circ Cardiovasc Imaging. 8: doi: 10.1161/CIRCIMAGING.114.00267.

Fischer D, Bonati U, Wattjes MP (2016) Recent developments in muscle imaging of neuromuscular disorders. Curr Opin Neurol 29:614-20.

Hollingsworth KG, de Sousa PL, Carlier PG (2012) Towards harmonization of protocols for MRI outcome measures in skeletal muscle studies: Consensus recommendations from two TREAT-NMD NMR workshops, 2 May 2010, Stockholm, Sweden, 1–2 October 2009, Paris, France. Neuromuscul Disord 22:54–67.

Hooijmans MT, Niks EH, Burakiewicz J, et al (2016) Elevated phosphodiester and T2 levels can be measured in the absence of fat infiltration in Duchenne muscular dystrophy patients. NMR Biomed. 30: doi: 10.1002/nbm.3667.

Hu HH, Kan HE (2013) Quantitative proton MR techniques for measuring fat. NMR Biomed 26:1609–29.

Jacobi B, Bongartz G, Partovi S, et al. Skeletal muscle BOLD MRI (2012) From underlying physiological concepts to its usefulness in clinical conditions. J Magn Reson Imaging. 35:1253-65.

Kemp GJ, Ahmad RE, Nicolay K, Prompers JJ (2015) Quantification of skeletal muscle mitochondrial function by 31P magnetic resonance spectroscopy techniques: a quantitative review. Acta Physiol (Oxf) 213:107–44.

Oudeman J, Nederveen AJ, Strijkers GJ, et al (2016) Techniques and applications of skeletal muscle diffusion tensor imaging: A review. J Magn Reson Imaging 43:773–788.

Paoletti M, Pichiecchio A, Cotti Piccinelli S, et al (2019) Advances in Quantitative Imaging of Genetic and Acquired Myopathies: Clinical Applications and Perspectives. Front Neurol 10:1–21.

Raynaud JS, Duteil S, Vaughan JT, et al (2001) Determination of skeletal muscle perfusion using arterial spin labeling NMRI: Validation by comparison with venous occlusion plethysmography. Magn Reson Med. 46:305-11.

Strijkers GJ, Araujo ECA, Azzabou N, et al (2019) Exploration of new contrasts, targets, and MR imaging and spectroscopy techniques for neuromuscular disease-A workshop report of working group 3 of the biomedicine and molecular biosciences COST action BM1304 MYO-MRI. J Neuromuscul Dis 6:1–30.

Wattjes MP, Kley RA, Fischer D (2010) Neuromuscular imaging in inherited muscle diseases. Eur Radiol 20:2447–60.


Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)