Elisabetta Pagani1, Maria Assunta Rocca1,2, Paolo Preziosa1, Sarlota Mesaros3, Jelena Drulovic3, and Massimo Filippi1,2
1Neuroimaging Research Unit, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, 2Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, 3Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Yugoslavia
Synopsis
In
this study we investigated the regional patterns
of atrophy progression over a five year follow-up in multiple
sclerosis (MS) patients and their association with clinical and
cognitive deterioration. Clinical (EDSS and phenotype
changes), neuropsychological (Rao’s battery) and brain MRI
assessment were performed at baseline and after 5 years from 66 MS
patients. Compared to stable MS patients, those
with clinical and cognitive worsening showed a left-lateralized
pattern of atrophy. A different vulnerability of the two brain
hemispheres to irreversible structural damage may be among the
factors contributing to clinical and cognitive worsening in these
patients.Background
Irreversible
tissue loss occurs from the earliest phases of multiple sclerosis
(MS) and is correlated with clinical disability and cognitive
impairment.
Purpose
To investigate the regional patterns of gray
matter (GM) and white matter (WM) atrophy progression over a five
year follow-up in MS patients and their association with clinical and
cognitive deterioration.
Methods
Clinical
(Expanded Disability Status Scale [EDSS] score
and phenotype changes), neuropsychological (Rao’s battery)
and brain MRI (dual-echo and 3D T1-weighted sequences) assessment
were performed at baseline (T0) and after 5 years (Y5) from 66 MS
patients with different clinical phenotypes and 7 controls. At T0
and Y5, measures of brain lesion volume and regional atrophy were
obtained. Tensor-based morphometry (1) and SPM12
(http://www.fil.ion.ucl.ac.uk/spm/software/spm12/) was used to map
regional changes of volumes over time in the two groups of subjects:
pairwise longitudinal registration (2) was used to align the first
and second scan of each subject. The method is based on pairwise
inverse-consistent registration and incorporates a bias field
correction. The rate of volume change was quantified by saving the
map of divergence of the velocity field, where positive values
indicate expansion and negative values contraction. The mid-point
average template image was also saved and used for groupwise
alignment (3) to the final customized template
and then to the standard space (MNI
atlas). Voxelwise
longitudinal changes of GM and WM volumes in MS patients were
evaluated according to the presence of neurologic
deterioration, phenotype modification and cognitive worsening.
Results
At Y5, 36/66 (55%) MS patients showed a
significant disability worsening, 14/66 (21%) evolved to a worse
clinical phenotype and 18/63 (29%) had a cognitive deterioration
(Table 1). At T0, compared to controls, MS patients showed a
widespread pattern of GM and WM atrophy. At Y5, MS patients developed
further GM atrophy of deep GM nuclei (thalami, putamen and caudate
nuclei), as well as of several fronto-temporo-parieto-occipital
regions and cerebellum. Progression of atrophy of the main WM tracts
was also detected. Compared to stable MS patients, those with
clinical and cognitive worsening showed a left-lateralized pattern of
GM and WM atrophy, involving the thalamus, caudate nucleus and
putamen, several fronto-temporo-parieto-occipital regions, the
cerebellum and the majority of WM tracts (Figure 1).
Conclusions
GM and WM atrophy of relevant brain regions occurs
in MS after 5 years. A different vulnerability of the two brain
hemispheres to irreversible structural damage may be among the
factors contributing to clinical and cognitive worsening in these
patients.
Acknowledgements
No acknowledgement found.References
1)
Ashburner J. Computational anatomy with the SPM software. Magn
Reson Imaging. 2009;27(8):1163-74.
2)
Ashburner J, Ridgway GR. Symmetric
diffeomorphic modeling of longitudinal structural MRI. Front Neurosci
2012; 6:197.
3)
Ashburner J. A fast diffeomorphic image registration
algorithm.Neuroimage. 2007;38(1):95-113.