Abstract
Purpose: Neuromuscular diseases (NMD) frequently cause severe disability. Magnetic resonance imaging (MRI) based calculation of the so-called fat fraction (FFR) in affected muscles was recently described as reliable biomarker for monitoring progression of NMDs. This is of high interest as newly available modern gene therapies, currently subject to intensive investigations, may provide at least palliation of these severely disabling diseases. In this retrospective study feasibility of advanced image analysis potentially extending the possibilities of using FFR in lower limbs in patients suffering various NMDs was investigated. Methods: Patients receiving MRI due to manifestation of proven NMDs (amyotrophic lateral sclerosis [n=6], spinobulbar muscular atrophy [n=4], limb girdle muscular dystrophy [n=5], metabolic myopathy [n=2]) in lower limbs were compared to patients without NMD [n=9]. We used both, the correlation of FFR and advanced parameters with clinical grades of strength obtained using the MRC-scale (Medical Research Council for Muscle Strength). In contrast to FFR, displaying the fat partition in muscles only, the full image information gained by MRI was transformed into standardised MRI-feature based matrices and Principal (PCA) and Independent Component Analysis (ICA) were employed to define parameters describing the full data obtained in more detail. Results: PCA- and ICA-based full image parameters remained strongly correlated to FFR (Spearman coefficient 0.96 – 0.59), but generally showed stronger correlations with the MRC-score in lower limbs (Spearman coefficient; FFR= -0.71; PCA & ICA parameters = -0.76 – -0.78). Age was no significant confounder in full image-assessment. Conclusion: While effectively extending the information gained by FFR the proposed advanced image analysis in NMDs is technically feasible and, so far, appears robust to age related effects.
Highlights
Neuromuscular diseases (NMDs), low in prevalence (1–3/100,000 persons), are known to show either slow or sometimes fast progression of symptoms leading to severe disabilities, currently without the opportunity of an effective treatment
Throughout all regions, i.e., ROIs for thigh (ROIT), ROIC, and ROILL, most parameters were significantly different between clinically healthy patients (MRC score: 5) and those with Medical Research Council (MRC) scores 4 or 3
The correlation between the MRC score and PCA- and independent component analyses (ICA)-derived parameters was in large part stronger than that found for fat fraction (FF) (Table 4), which indicates that FF may not reveal all the information about subtle but relevant alterations in the muscular texture depicted in Magnetic resonance imaging (MRI)
Summary
Neuromuscular diseases (NMDs), low in prevalence (1–3/100,000 persons), are known to show either slow or sometimes fast progression of symptoms leading to severe disabilities, currently without the opportunity of an effective treatment. Disease-modifying therapies are subject to intensive investigations in order to provide at least palliation of the often heavily disabling symptoms of NMDs [1] In parallel, this requires the development of objective and sensitive methods enhancing the diagnostic algorithm and reliably measuring alterations in affected muscle tissue over time to prove effectiveness and validity of therapeutic interventions. Magnetic resonance imaging (MRI)–based high-resolution myometry with quantification of the fat fraction (FF) was validated as a sensitive biomarker for both myopathies and neuropathies showing strong correlations with clinical and functional scores [2, 3] In this context, certain MRI techniques, as described by Dixon [4], enable the direct determination of signal contributions from either structurally bound or highly mobile protons. Separate water and fat images can be generated, where FF calculates the proportion of fat signal from the signal totally gained from both, i.e., water and fat, proton pools [5]
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