Multi-parametric assessment of thigh muscles in patients with limb girdle muscular dystrophies (LGMD): preliminary results.
Alberto De Luca1,2, Maria Grazia D'Angelo3, Denis Peruzzo2, Fabio Triulzi4, Alessandra Bertoldo1, and Filippo Arrigoni2

1Department of Information Engineering, University of Padova, Padova, Italy, 2Neuroimaging Lab, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini (LC), Italy, 3Functional Rehabilitation Unit, Neuromuscular Disorders, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini (LC), Italy, 4Department of Neuroradiology, Scientific Institute IRCCS Ca Granda Foundation - Ospedale Maggiore Policlinico, Milan, Italy

Synopsis

Limb girdle muscular dystrophies (LGMD) are a heterogeneous family of disorders characterized by the substitution of muscles with fat and fibrotic tissue. In this work we show the initial results of our acquisition protocol, that included DW-MRI, T2 mapping and DIXON imaging, on two subtypes of LGMD (type 2A and 2B). Statistical tests and Pearson’s correlation were performed on parametric maps at single muscle level. Preliminary results show that multi-parametric MRI is promising in the characterization of LGMD subtypes on the thigh. Considered MRI techniques show different sensibilities to damages induced by muscular dystrophies and can be considered complimentary.

Purpose

Limb girdle muscular dystrophies (LGMD) are a heterogeneous family of disorders characterized by the substitution of muscles with fat and fibrotic tissue, with a predominant involvement of the shoulder and pelvic girdle1,2. In this work we show the initial results of our acquisition protocol and analysis pipeline targeted to a muscle level characterization in two subtypes of LGMD.

Methods

Four healthy volunteers(HCs) (35±7 years old, 2M and 2F), 6 patients affected by LGMD2A (Calpain 3 deficiency, 42±10 years old, 2M and 4F) and 2 patients affected by LGMD2B (Dysferlin deficiency, 60±15 years old, 1M and 1F) underwent MRI of the thigh with a 3T scanner. Acquisition protocol included a diffusion weighted (DW) sequence (TE/TR=42/7000ms, 5 b=0s/mm2, 15 directions b=250s/mm2, 15 directions b=400s/mm2, 4 directions at b=50,100,150,200,300s/mm2, resolution 1.5x1.5x6mm3), a multi-echo sequence (15 echoes,TE1 9.3ms,δTE 12.5ms,1.7x1.7x5mm3) for T2 quantification and a DIXON sequence (12 echoes, TE1 2.7ms,δTE 1.2ms) for fat fraction (FF) quantification. DW data was pre-processed with FSL3,4, then fractional anisotropy (FA) and mean diffusivity (MD) maps were computed with Camino5,6. T2 images were moved to the DIXON space and, subsequently to the DW space using a non-linear registration7 to account for EPI distortions. Regions of interest (ROIs) were drawn on muscles Gracilis and Vastus Lateralis, and used to compute boxplots of FA, FF and T2. T-tests (two sided, p=0.05) were performed to assess differences between muscles in HC, testing Vastus against Gracilis, and to assess differences between matching ROI of different populations, testing HC against patients and HC against LGMD2A. Cross correlations between the considered metrics and correlations between metrics and age (ρ) were computed for each ROI as attempt to disentangle the information from each sequence.

Results

LGMD2B patients showed, on structural T2-w images, a diffuse pattern of muscle degeneration and fatty infiltration involving both anterior and posterior thigh muscles, while LGMD2A patients had a more heterogeneous pattern of degeneration, involving posterior muscles more severely (Figure 1). Figure 2 shows an example slice of the maps obtained from a HC and a patient affected by LGMD2A. FA, FF and T2 maps are homogeneous for the muscle of the HC subject, conversely on the patients, FA exhibits high heterogeneity, FF is increased within the muscle, and T2 values are higher, especially in the Vastus. Figure 3 reports the boxplots of all parametric maps for both ROIs. FA, FF and T2 values were consistent for the HCs, with different MD (p=0.029) and FA (p=0.045) values between Vastus and Gracilis. Parametric maps values between HC and patients were different in the Vastus (FA p=0.050, FF p=0.001, T2 p=0.037) and in the Gracilis (FF p=0.012). Considering only LGMD2A patients against HCs, significant differences were found for both the Vastus (FA, p=0.048, FF p=0.002) and the Gracilis (FF p=0.018). Significant correlations were found in the Gracilis between FF and both FA (ρ=0.81, p=0.015) and MD (ρ=-0.78, p=0.024) for patients (Figure 4). Conversely, correlations were not significant in the Vastus, as well as correlations between T2 and FA/MD in both muscles. Age was significantly correlated only with Gracilis FA in the LGMD2A group, ρ=-0.85 with p=0.033, meaning that FA decreases over time for this group. Same correlation in the HC group was not significant but opposite in sign. No significant correlations between age and metrics were found in the whole group of patients.

Discussion

All considered parameters showed stable and homogeneous distributions (Figure 2) in the HCs, while patients were characterized by variable and heterogeneous values, even across the same dystrophy subtype, highlighting the variety of LGMD effects. FF was significantly different in all performed t-tests, showing to be a very sensible marker of muscle substitution process. All considered quantities were significantly different in muscle Vastus, that it is probably affected by the majority of considered dystrophies. The Gracilis seems to be less (or later) affected, especially in the LGMD2A group. Correlations between FF and the other computed metrics were high in the Gracilis of patients, nonetheless FA was the only measure significantly correlated to age in the LGMD2A group. The absence of correlation between age and metrics in whole patients group can be due to heterogeneity of the group itself.

Conclusion

Preliminary results of this study are promising in the characterization of LGMD subtypes on the thigh. Considered MRI techniques show different sensibilities to damages induced my muscular dystrophies and can be considered complimentary. The limited sample size requires the results to be confirmed on a larger cohort of subjects.

Acknowledgements

No acknowledgement found.

References

1. Gallardo, E., Saenz, A. & Illa, I. Limb-girdle muscular dystrophy 2A. Handbook of Clinical Neurology 101, (Elsevier B.V., 2011).

2. Nigro, V., Aurino, S. & Piluso, G. Limb girdle muscular dystrophies: update on genetic diagnosis and therapeutic approaches. Curr. Opin. Neurol. 24, 429–36 (2011).

3. Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W. & Smith, S. M. FSL. Neuroimage 62, 782–90 (2012).

4. Smith, S. M. et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23 Suppl 1, S208–19 (2004).

5. Jones, D. K. & Basser, P. J. ‘Squashing peanuts and smashing pumpkins’: how noise distorts diffusion-weighted MR data. Magn. Reson. Med. 52, 979–93 (2004).

6. Alexander, D. C. & Barker, G. J. Optimal imaging parameters for fiber-orientation estimation in diffusion MRI. Neuroimage 27, 357–67 (2005).

7. Jenkinson, M. & Smith, S. A global optimisation method for robust affine registration of brain images. Med. Image Anal. 5, 143–56 (2001).

Figures

Figure 1 - Axial T2 weighted image of each patient considered in the study. Muscle substitution is noticeable in all subjects and does not appear to be age related. Vastus and Gracilis of subject (F,44) appears to be not yet affected.

Figure 2 - Example slice of the maps used in the analysis for a healthy subject and a patient affected by LGMD2A dystrophy. FF is in %. T2 units are [ms].

Figure 3 - Boxplots of FA, FF and T2 for each ROI. Values are consistent and similar for HC, while patients group exhibit high variability, especially between Vastus and Gracilis. L2A is LGMD2A, L2B is LGMD2B. For one of L2A patients T2 acquisition was not available.

Figure 4 - Correlations between FA, MD and FF in the patients group. Correlations were significant for the Gracilis but not for the Vastus.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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