Mario Mascalchi1,2, Nicola Toschi3,4,5, Marco Giannelli6, Andrea Ginestroni7, Riccardo Della Nave8, Carlo Tessa9, Silvia Piacentini10, Maria Teresa Dotti11, Marco Aiello12, Emanuele Nicolai12, Andrea Soricelli12,13, Fabrizio Salvi14, Stefano Diciotti15. 1. Quantitative and Functional Neuroradiology Research Unit at Meyer Children and Careggi Hospitals of Florence, Florence, Italy. 2. "Mario Serio" Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence, Italy. 3. Medical Physics Section, Department of Biomedicine and Prevention, University of Rome "Tor Vergata,", Rome, Italy. 4. Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA. 5. Harvard Medical School, Boston, MA. 6. Unit of Medical Physics, Pisa University Hospital "Azienda Ospedaliero-Universitaria Pisana,", Pisa, Italy. 7. Neuroradiology Unit, Careggi General Hospital, Florence, Italy. 8. "San Giuseppe" Hospital, Azienda USL 11 Empoli, Empoli (Fi), Italy. 9. Unit of Radiology, Versilia Hospital, Azienda USL 12 Viareggio, Lido di Camaiore (Lu), Italy. 10. NEUROFARBA Department, University of Florence, Florence, Italy. 11. Department of Neurological Sciences, University of Siena, Siena, Italy. 12. IRCSS SDN Foundation, Naples, Italy. 13. University of Naples Parthenope, Naples, Italy. 14. "Il Bene" Centre for Immunological and Rare Diseases, Bellaria Hospital, IRCSS Neurologia Città di Bologna, Bologna, Italy. 15. Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi,", University of Bologna, Cesena, Italy.
Abstract
BACKGROUND AND PURPOSE: Imaging biomarkers of disease progression are desirable in inherited ataxias. MRI has demonstrated brain damage in Friedreich ataxia (FRDA) in form of regional atrophy of the medulla, peridentate cerebellar white matter (WM) and superior cerebellar peduncles (visible in T1-weighted images) and of change of microstructural characteristics of WM tracts of the brainstem, cerebellar peduncles, cerebellum, and supratentorial structures (visible through diffusion-weighted imaging). We explored the potential of brain MR morphometry and diffusion tensor imaging (DTI) to track the progression of neurodegeneration in FRDA. METHODS: Eight patients (5F, 3M; age 13.4-41.2 years) and 8 healthy controls (2F, 6M; age 26.2-48.3 years) underwent 2 MRI examinations (mean 3.9 and 4.1 years apart, respectively) on the same 1.5T scanner. The protocol included 3D T1-weighted images and axial diffusion-weighted images (b-value 1,000 s/mm(2)) for calculating maps of fractional anisotropy, mean, axial and radial diffusivity, and mode of anisotropy. Tensor-based morphometry was used to investigate regional volume changes and tract-based spatial statistics was used to investigate microstructural changes in WM tracts. RESULTS: Longitudinal analyses showed no differences in regional volume changes but a significant difference in axial diffusivity changes in cerebral and corpus callosum WM of patients as compared to controls (mean longitudinal rate of change for axial diffusivity: -.02 × 10(-3) mm(2)/s/year in patients vs. .01 × 10(-3) mm(2)/s/year in controls). No correlation with number of triplets, disease duration, and worsening of the clinical deficit was observed. CONCLUSION: DTI can track brain microstructural changes in FRDA and can be considered a potential biomarker of disease progression.
BACKGROUND AND PURPOSE: Imaging biomarkers of disease progression are desirable in inherited ataxias. MRI has demonstrated brain damage in Friedreich ataxia (FRDA) in form of regional atrophy of the medulla, peridentate cerebellar white matter (WM) and superior cerebellar peduncles (visible in T1-weighted images) and of change of microstructural characteristics of WM tracts of the brainstem, cerebellar peduncles, cerebellum, and supratentorial structures (visible through diffusion-weighted imaging). We explored the potential of brain MR morphometry and diffusion tensor imaging (DTI) to track the progression of neurodegeneration in FRDA. METHODS: Eight patients (5F, 3M; age 13.4-41.2 years) and 8 healthy controls (2F, 6M; age 26.2-48.3 years) underwent 2 MRI examinations (mean 3.9 and 4.1 years apart, respectively) on the same 1.5T scanner. The protocol included 3D T1-weighted images and axial diffusion-weighted images (b-value 1,000 s/mm(2)) for calculating maps of fractional anisotropy, mean, axial and radial diffusivity, and mode of anisotropy. Tensor-based morphometry was used to investigate regional volume changes and tract-based spatial statistics was used to investigate microstructural changes in WM tracts. RESULTS: Longitudinal analyses showed no differences in regional volume changes but a significant difference in axial diffusivity changes in cerebral and corpus callosum WM of patients as compared to controls (mean longitudinal rate of change for axial diffusivity: -.02 × 10(-3) mm(2)/s/year in patients vs. .01 × 10(-3) mm(2)/s/year in controls). No correlation with number of triplets, disease duration, and worsening of the clinical deficit was observed. CONCLUSION: DTI can track brain microstructural changes in FRDA and can be considered a potential biomarker of disease progression.
Authors: Mario Mascalchi; Andrea Bianchi; Stefano Ciulli; Andrea Ginestroni; Marco Aiello; Maria Teresa Dotti; Fabrizio Salvi; Emanuele Nicolai; Andrea Soricelli; Stefano Diciotti Journal: J Neurol Date: 2017-06-15 Impact factor: 4.849
Authors: Ian H Harding; Louise A Corben; Louisa P Selvadurai; Nellie Georgiou-Karistianis; Rosita Shishegar; Cathlin Sheridan; Gary F Egan; Martin B Delatycki Journal: J Neurol Date: 2021-04-15 Impact factor: 4.849
Authors: Louisa P Selvadurai; Louise A Corben; Martin B Delatycki; Elsdon Storey; Gary F Egan; Nellie Georgiou-Karistianis; Ian H Harding Journal: Hum Brain Mapp Date: 2020-01-06 Impact factor: 5.038
Authors: Mario Mascalchi; Chiara Marzi; Marco Giannelli; Stefano Ciulli; Andrea Bianchi; Andrea Ginestroni; Carlo Tessa; Emanuele Nicolai; Marco Aiello; Elena Salvatore; Andrea Soricelli; Stefano Diciotti Journal: PLoS One Date: 2018-07-12 Impact factor: 3.240