Stefano Zanigni1,2, Stefania Evangelisti1,2, Claudia Testa1,2, David Neil Manners1,2, Giovanna Calandra-Buonaura1,3, Maria Guarino4, Anna Gabellini3,5, Luisa Sambati1,3, Pietro Cortelli1,3, Raffaele Lodi1,2, and Caterina Tonon1,2
1Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy, 2Policlinico S.Orsola-Malpighi, Functional MR Unit, Bologna, Italy, 3IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy, 4Policlinico S.Orsola-Malpighi, Neurology Unit, Bologna, Italy, 5Ospedale Maggiore, Neurology Unit, Bologna, Italy
Synopsis
We applied a probabilistic tractography FSL-based method to evaluate
alterations in the cortico-spinal tract (CST), middle and superior cerebellar
peduncles (MCP and SCP, respectively) in 90 patients with neurodegenerative
parkinsonisms (Progressive Supranuclear Palsy, Multiple System Atrophy, and
Parkinson’s disease). Patients and healthy controls were evaluated on a 1.5T GE
scanner. DTI metrics were evaluated in the whole CST, MCP and SCP tracts, and
in addition, an along tract analysis for CST has been performed. We found that
specific patterns of neurodegeneration within these specific tracts are evident
and that they reflect the neuropathological and clinical profile of each
syndrome.PURPOSE:
To evaluate alterations in the cortico-spinal tract (CST), middle and
superior cerebellar peduncles (MCP and SCP, respectively) by using a
probabilistic tractography method in a large sample of patients with
neurodegenerative parkinsonisms: Progressive Supranuclear Palsy – Richardson’s
Syndrome (PSP-RS), Multiple System Atrophy, Cerebellar and Parkinsonian
variants (MSA-C and –P, respectively) patients compared to Parkinson’s disease
(PD) patients and healthy controls (HC).
METHODS:
We enrolled in the study 90 patients with a clinical diagnosis of neurodegenerative
parkinsonism according to current criteria
1-3 and 27 HC, comparable
for age and sex. All subjects underwent a standardized brain MR protocol
including 25-direction diffusion imaging sequences on a 1.5 T scanner (GE Signa HDx 15). We applied the
FSL probabilistic tractography algorithm
4-5 in order to reconstruct
the CSTs, the MCPs and SCPs (Figure 1). The connectivity maps were normalized
by dividing values of connectivity by the waytotal, a number returned by the
tractography algorithm that corresponds to the total number of generated tracts
that have not been rejected by target masks criteria. Fractional Anisotropy
(FA), Mean Diffusivity (MD), Axial Diffusivity (AD) and Radial Diffusivity (RD)
were evaluated. For the CST we also performed an along-tract analysis
consisting in the subdivision of the tract into 100 percentiles along the z
direction in each subject-specific space, allowing a comparison of the corresponding
segments among different subjects.
We performed an ANCOVA
test followed by post hoc tests to
compare FA, MD, AD, RD and tract volume within all the whole tracts. When DTI
parameters were compared, sex, age and tract volume normalized by TIV were
added as covariates of no interest, while, when comparing the volume of the
tract, sex, age and TIV were added as covariates of no interest. For the
along-tract analysis, we performed comparisons at each percentile and adding as
covariates of no interest sex, age and percentile-specific volume of the tract
normalized by TIV when comparing DTI parameters and TIV when comparing the
along-tract volume. Comparisons were performed with a permutation-based
nonparametric method, correcting for multiple comparisons by controlling the
family-wise error rate. Moreover, results were then corrected for multiple
comparisons with Bonferroni method (p<0.0038, 13 comparisons).
RESULTS:
Main demographic and clinical features of the study sample are reported
in Figure 2. Whole-tract ANCOVA analysis of CST showed significant differences (p<0.05)
among groups in all DTI metrics bilaterally (Table 3, Table 2 supplementary).
The results of the post-hoc analysis are reported in Figure 3. The along tract
analysis of CST showed a bilateral increase in MD in PSP-RS compared to PD and
HC in the part of the tract passing through the corona radiata (Figure 4). We
found no volumetric differences in CST segments among groups.The whole-tract ANCOVA
analysis of MCPs yielded significant differences (p<0.05) among groups in
all DTI metrics bilaterally and in left MCP volume (Figure 3). The results of
post-hoc analysis are shown in Figure 3. The whole tract ANCOVA analysis of
SCPs showed significant (p<0.05) differences among groups in all DTI metrics
and tract volume bilaterally (Figure 3). The results of post-hoc analysis are
shown in Figure 3.
DISCUSSION:
Our study demonstrated a specific pattern of neurodegeneration,
involving CST, MCPs and SCPs. In particular, we demonstrated bilateral
neurodegenerative changes in both CSTs and SCPs in our PSP-RS sample, according
with previous neuropathological and neuroimaging evidences
6-9. Notably,
CST neurodegenerative alterations were limited to the portion of the tract
within the corona radiata; this portion of the tract includes neurons belonging
to the corticostriatal tract, whose alterations have been related to motor
control deficits and behavioural/cognitive dysfunction
10. MSA-C
displayed predominant neurodegenerative changes in MCPs, and with a smaller
extent to SCPs. This pattern of neurodegeneration is typical of this disorder
in which cerebellar dysfunction is usually prominent
6,11-12.
The MSA-P group
showed significant alterations in MCPs compared to PD and HC: these changes are
in line with the clinical and neuropathological description of this MSA variant
in which cerebellar alterations are present, compared to PD and HC, and they
are usually milder when compared to MSA-C
6,9,12.
CONCLUSION:
Atypical parkinsonisms are characterized by
disease-specific patterns of white matter alterations, reflecting the
neuropathology and the clinical features of the disorder, and these changes can
be detected in vivo by using probabilistic tractography. These results
contribute to the understanding of the physiopathology of neurodegenerative parkinsonisms,
supporting the role of advanced brain MR analysis of targeted regions of
interest in the in vivo differential diagnosis among parkinsonisms.
Acknowledgements
No acknowledgement found.References
1.
Litvan I, Agid Y, Jankovic J, et al. Accuracy of clinical criteria for the
diagnosis of progressive supranuclear palsy (Steele-Richardson-Olszewski
syndrome). Neurology 1996;46:922-930.
2.
Gelb DJ, Oliver E, Gilman S. Diagnostic criteria for Parkinson disease.
Arch Neurol. 1999;56:33-39.
3.
Gilman S, Wenning GK, Low PA, et al. Second consensus statement on the
diagnosis of multiple system atrophy. Neurology 2008;71:670-676.
4.
Behrens
TEJ, Woolrich MW, Jenkinson M, et al. Characterization and propagation of
uncertainty in diffusion-weighted MR imaging. Magn Reson Med. 2003;50(5):1077-1088.
5.
Behrens
TE, Berg HJ, Jbabdi S, et al. Probabilistic diffusion tractography with
multiple fibre orientations: What can we gain? Neuroimage. 2007;34(1):144-155.
6. Nilsson C, Markenroth Bloch K, et al. Tracking the
neurodegeneration of parkinsonian disorders--a pilot study. Neuroradiology
2007;49(2):111-119.
7.
Dickson DW, Ahmed Z, Algom AA, et al. Neuropathology of variants of
progressive supranuclear palsy. Curr Opin Neurol 2010;23:394-400.
8. Canu
E, Agosta F, Baglio F, et al. Diffusion
tensor magnetic resonance imaging tractography in progressive supranuclear
palsy. Mov Disord 2011;26(9):1752-1755.
9. Surova Y, Szczepankiewicz F, Lätt J, et al. Assessment
of global and regional diffusion changes along white matter tracts in parkinsonian
disorders by MR tractography. PLoS One 2013;8(6):e66022.
10. Shepherd
GM. Corticostriatal connectivity and its role in disease. Nat Rev Neurosci.
2013;14(4):278-291.
11.
Halliday GM, Holton JL, Revesz T, et al. Neuropathology underlying clinical
variability in patients with synucleinopathies. Acta Neuropathol.
2011;122:187-204.
12.
Dickson DW. Parkinson's disease and parkinsonism: neuropathology. Cold
Spring Harb Perspect Med. 2012;2(8):a009258.