Elisa Vegezzi1,2, Andrea Cortese3,4, Laura Obici5, Anna Pichiecchio1,6, Niels Bergsland7,8, Roberta Mussinelli5, Matteo Paoletti6, Francesca Solazzo9, Riccardo Currò1,10, Lucia Ascagni11, Ilaria Callegari12, Ilaria Quartesan1, Alessandro Lozza5, Xeni Deligianni13,14, Francesco Santini13,14, Enrico Marchioni2, Giuseppe Cosentino1,15, Enrico Alfonsi15, Cristina Tassorelli1,16, Stefano Bastianello1,6, Giampaolo Merlini5,17, Giovanni Palladini5,17. 1. Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. 2. Neuroncology and Neuroinflammation Unit, IRCCS Mondino Foundation, Pavia, Italy. 3. Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. andrea.cortese@unipv.it. 4. Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology and Neurosurgery, London, UK. andrea.cortese@unipv.it. 5. Amyloidosis Research and Treatment Center, Fondazione IRCCS Policlinico San Matteo, University of Pavia, Pavia, Italy. 6. Neuroradiology Department, Advanced Imaging and Radiomics Center, IRCCS Mondino Foundation, Pavia, Italy. 7. Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA. 8. IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy. 9. Specialization School in Occupational Medicine, University of Pavia, Pavia, Italy. 10. Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology and Neurosurgery, London, UK. 11. Neuroscience Department, Meyer Children's University Hospital, University of Florence, Florence, Italy. 12. Department of Biomedicine, University Hospital Basel, University of Basel, Hebelstrasse 20, 4031, Basel, Switzerland. 13. Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland. 14. Department of Biomedical Engineering, Basel Muscle MRI Group, University of Basel, Allschwil, Switzerland. 15. Translational Neurophysiology Research Unit, IRCCS Mondino Foundation, Pavia, Italy. 16. Headache Science and Neurorehabilitation Center, IRCCS Mondino Foundation, Pavia, Italy. 17. Department of Molecular Medicine, University of Pavia, Pavia, Italy.
Abstract
BACKGROUND: The development of reproducible and sensitive outcome measures has been challenging in hereditary transthyretin (ATTRv) amyloidosis. Recently, quantification of intramuscular fat by magnetic resonance imaging (MRI) has proven as a sensitive marker in patients with other genetic neuropathies. The aim of this study was to investigate the role of muscle quantitative MRI (qMRI) as an outcome measure in ATTRv. METHODS: Calf- and thigh-centered multi-echo T2-weighted spin-echo and gradient-echo sequences were obtained in patients with ATTRv amyloidosis with polyneuropathy (n = 24) and healthy controls (n = 12). Water T2 (wT2) and fat fraction (FF) were calculated. Neurological assessment was performed in all ATTRv subjects. Quantitative MRI parameters were correlated with clinical and neurophysiological measures of disease severity. RESULTS: Quantitative imaging revealed significantly higher FF in lower limb muscles in patients with ATTRv amyloidosis compared to controls. In addition, wT2 was significantly higher in ATTRv patients. There was prominent involvement of the posterior compartment of the thighs. Noticeably, FF and wT2 did not exhibit a length-dependent pattern in ATTRv patients. MRI biomarkers correlated with previously validated clinical outcome measures, Polyneuropathy Disability scoring system, Neuropathy Impairment Score (NIS) and NIS-lower limb, and neurophysiological parameters of axonal damage regardless of age, sex, treatment and TTR mutation. CONCLUSIONS: Muscle qMRI revealed significant difference between ATTRv and healthy controls. MRI biomarkers showed high correlation with clinical and neurophysiological measures of disease severity making qMRI as a promising tool to be further investigated in longitudinal studies to assess its role at monitoring onset, progression, and therapy efficacy for future clinical trials on this treatable condition.
BACKGROUND: The development of reproducible and sensitive outcome measures has been challenging in hereditary transthyretin (ATTRv) amyloidosis. Recently, quantification of intramuscular fat by magnetic resonance imaging (MRI) has proven as a sensitive marker in patients with other genetic neuropathies. The aim of this study was to investigate the role of muscle quantitative MRI (qMRI) as an outcome measure in ATTRv. METHODS: Calf- and thigh-centered multi-echo T2-weighted spin-echo and gradient-echo sequences were obtained in patients with ATTRv amyloidosis with polyneuropathy (n = 24) and healthy controls (n = 12). Water T2 (wT2) and fat fraction (FF) were calculated. Neurological assessment was performed in all ATTRv subjects. Quantitative MRI parameters were correlated with clinical and neurophysiological measures of disease severity. RESULTS: Quantitative imaging revealed significantly higher FF in lower limb muscles in patients with ATTRv amyloidosis compared to controls. In addition, wT2 was significantly higher in ATTRv patients. There was prominent involvement of the posterior compartment of the thighs. Noticeably, FF and wT2 did not exhibit a length-dependent pattern in ATTRv patients. MRI biomarkers correlated with previously validated clinical outcome measures, Polyneuropathy Disability scoring system, Neuropathy Impairment Score (NIS) and NIS-lower limb, and neurophysiological parameters of axonal damage regardless of age, sex, treatment and TTR mutation. CONCLUSIONS: Muscle qMRI revealed significant difference between ATTRv and healthy controls. MRI biomarkers showed high correlation with clinical and neurophysiological measures of disease severity making qMRI as a promising tool to be further investigated in longitudinal studies to assess its role at monitoring onset, progression, and therapy efficacy for future clinical trials on this treatable condition.
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