Progression of brain atrophy in spinocerebellar ataxia type 2: A longitudinal tensor-based morphometry study

Mario Mascalchi, Stefano Diciotti, Marco Giannelli, Andrea Ginestroni, Andrea Soricelli, Emanuele Nicolai, Marco Aiello, Carlo Tessa, Lucia Galli, Maria Teresa Dotti, Silvia Piacentini, Elena Salvatore, Nicola Toschi

Research output: Contribution to journalArticlepeer-review


Spinocerebellar ataxia type 2 (SCA2) is the second most frequent autosomal dominant inherited ataxia worldwide. We investigated the capability of magnetic resonance imaging (MRI) to track in vivo progression of brain atrophy in SCA2 by examining twice 10 SCA2 patients (mean interval 3.6 years) and 16 age- and gender-matched healthy controls (mean interval 3.3 years) on the same 1.5 T MRI scanner. We used T1-weighted images and tensor-based morphometry (TBM) to investigate volume changes and the Inherited Ataxia Clinical Rating Scale to assess the clinical deficit. With respect to controls, SCA2 patients showed significant higher atrophy rates in the midbrain, including substantia nigra, basis pontis, middle cerebellar peduncles and posterior medulla corresponding to the gracilis and cuneatus tracts and nuclei, cerebellar white matter (WM) and cortical gray matter (GM) in the inferior portions of the cerebellar hemisphers. No differences in WM or GM volume loss were observed in the supratentorial compartment. TBM findings did not correlate with modifications of the neurological deficit. In conclusion, MRI volumetry using TBM is capable of demonstrating the progression of pontocerebellar atrophy in SCA2, supporting a possible role of MRI as biomarker in future trials.

Original languageEnglish
Article numbere89410
JournalPLoS One
Issue number2
Publication statusPublished - Feb 25 2014

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)


Dive into the research topics of 'Progression of brain atrophy in spinocerebellar ataxia type 2: A longitudinal tensor-based morphometry study'. Together they form a unique fingerprint.

Cite this