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Axial Signs and Magnetic Resonance Imaging Correlates in Parkinson's Disease

Published online by Cambridge University Press:  02 December 2014

Hernish J. Acharya
Affiliation:
Department of Medicine, Division of Neurology, University of Alberta, Edmonton, Alberta, Canada
Thomas P. Bouchard
Affiliation:
Department of Medicine, Division of Neurology, University of Alberta, Edmonton, Alberta, Canada
Derek J. Emery
Affiliation:
Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada
Richard M. Camicioli
Affiliation:
Department of Medicine, Division of Neurology, University of Alberta, Edmonton, Alberta, Canada
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Abstract

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Background:

Age-related brain changes may contribute to axial features in Parkinson's disease (PD).

Objectives:

To determine if ventricular volume and white matter high signal changes (WMC) are related to motor signs in PD and controls independent of age.

Methods:

Patients were rated with the Unified Parkinson's Disease Rating Scale (subscore A: tremor, rigidity, bradykinesia, and facial expression; subscore B: speech and axial impairment). Steps and time taken to walk 9.144 meters were measured. Total ventricular volume (TVV) and intracranial volume (ICV) were measured on T1-weighted MRI using manual tracing software. WMC were rated on axial T2-weighted, dual-echo or FLAIR MR images using a visual scale.

Results:

TVV (cm3) (PD: 36.48 ± 15.93; controls: 32.16 ± 14.20, p = 0.21) and WMC did not differ between groups (PD: 3.7 ± 4.2; controls: 3.2 ± 3.1, p = 0.55). Age correlated positively with ICV-corrected TVV and WMC in PD (cTVV: r = 0.48, p = 0.003; WMC: r=0.42, p=0.01) and controls (cTVV: r = 0.31, p = 0.04; WMC: r=0.44, p=0.003). Subscore B (r = 0.42, p = 0.01) but not subscore A (r = 0.25, p = 0.14) correlated with cTVV in PD. Steps and walking time correlated with cTVV and WMC in PD; cadence correlated with cTVV and steps with WMC in controls. Age-adjustment eliminated correlations.

Conclusion:

Subscore B, but not subscore A correlated positively with ventricular volume in PD, though this association was accounted for by age. Age-related brain change super-imposed on PD may contribute to axial features.

Résumé:

RÉSUMÉ: Contexte:

Les changements du cerveau qui sont reliés à l'âge peuvent contribuer aux manifestations axiales dans la maladie de Parkinson (MP).

Objectifs:

Déterminer si le volume ventriculaire et les changements du signal élevé de la substance blanche (CSB) sont reliés aux signes moteurs chez des patients atteints de MP et chez des sujets témoins, sans égard à l'âge.

Méthodes:

Les patients étaient évalués au moyen de la Unified Parkinson's Disease Rating Scale (sous-score A : tremblement, rigidité, bradycinésie et expression faciale; sous-score B : dysarthrie et manifestations axiales). Les pas et le temps requis pour parcourir 9.144 mètres ont été mesurés. Le volume ventriculaire total (VVT) et le volume intracrânien (VIC) ont été mesurés par IRM pondérée en T1, au moyen d'un logiciel de calque manuel. Les CSB ont été évalués au moyen d'une échelle visuelle sur des images axiales pondérées en T2, double écho ou FLAIR.

Résultats:

Le VVT (cm3 ) (MP : 36,48 ± 15,93; témoins : 32,16 ± 14,20; p = 0,21) et les CSB n'étaient pas différents entre les groupes (MP : 3,7 ± 4,2; témoins : 3,2 ± 3,1; p = 0,55). L'âge était corrélé au VVT corrigé pour le VIC et les CSB dans la MP (VVTc : r = 0,48; p = 0,003; CSB : r = 0,42; p = 0,01) et les témoins (VVTc : r = 0,31; p = 0,04; CSB : r = 0,44; p = 0,003). Le sous-score B (r = 0,42; p = 0,01) était corrélé au VVTc chez les patients atteints de MP, mais non le sous-score A (r = 0,25; p = 0,14). Les pas et le temps de marche étaient corrélés au VVT et aux CSB dans la MP; la cadence était corrélée au VVTc et les pas aux CSB chez les témoins. L'ajustement pour l'âge annulait les corrélations.

Conclusion:

Il y avait une corrélation positive entre le sous-score B et le volume ventriculaire dans la MP, ce qui n'était pas le cas du sous-score A, mais cette association était due à l'âge. Les changements reliés à l'âge surajoutés à la MP peuvent contribuer aux manifestations axiales chez les patients atteints de MP.

Type
Original Articles
Copyright
Copyright © The Canadian Journal of Neurological 2007

References

1. Braak, H, Braak, E. Pathoanatomy of Parkinson’s disease. J Neurol. 2000; 247 Suppl 2: II310.CrossRefGoogle ScholarPubMed
2. Levy, G, Louis, ED, Cote, L, Perez, M, Mejia-Santana, H, Andrews, H, et al. Contribution of aging to the severity of different motor signs in Parkinson disease. Arch Neurol. 2005; 62: 46772.CrossRefGoogle Scholar
3. Bonnet, AM, Loria, Y, Saint-Hilaire, MH, Lhermitte, F, Agid, Y. Does long-term aggravation of Parkinson’s disease result from nondopaminergic lesions? Neurology. 1987; 37: 153942.CrossRefGoogle ScholarPubMed
4. Pillon, B, Dubois, B, Cusimano, G, Bonnet, AM, Lhermitte, F, Agid, Y. Does cognitive impairment in Parkinson’s disease result from non-dopaminergic lesions? J Neurol Neurosurg Psychiatry. 1989; 52: 2016.CrossRefGoogle ScholarPubMed
5. Blin, J, Dubois, B, Bonnet, AM, Vidailhet, M, Brandabur, M, Agid, Y. Does aging aggravate parkinsonian disability? J Neurol Neurosurg Psychiatry. 1991; 54: 7802.CrossRefGoogle ScholarPubMed
6. Camicioli, R, Moore, MM, Sexton, G, Howieson, DB, Kaye, JA. Age-related brain changes associated with motor function in healthy older people. J Am Geriatr Soc. 1999; 47: 3304.CrossRefGoogle ScholarPubMed
7. Schneider, E, Becker, H, Fischer, PA, Grau, H, Jacobi, P, Brinkmann, R. The course of brain atrophy in Parkinson’s disease. Arch Psychiatr Nervenkr. 1979; 227: 8995.CrossRefGoogle ScholarPubMed
8. Kitani, M, Kobayashi, S, Yamaguchi, S. Computerized tomography with longitudinal follow-up of brain atrophy in patients with Parkinson’s disease. Gerontology. 1990; 36: 3618.CrossRefGoogle ScholarPubMed
9. Starkstein, SE, Leiguarda, R. Neuropsychological correlates of brain atrophy in Parkinson’s disease: a CT-scan study. Mov Disord. 1993; 8: 515.CrossRefGoogle ScholarPubMed
10. Steiner, I, Gomori, JM, Melamed, E. Features of brain atrophy in Parkinson’s disease. A CT scan study. Neuroradiology. 1985; 27: 15860.CrossRefGoogle ScholarPubMed
11. Durif, F, Pollak, P, Hommel, M, Ardouin, C, Le Bas, JF, Crouzet, G, et al. Relationship between levodopa-independent symptoms and central atrophy evaluated by magnetic resonance imaging in Parkinson’s disease. Eur Neurol. 1992; 32: 326.CrossRefGoogle ScholarPubMed
12. Hu, MT, White, SJ, Chaudhuri, KR, Morris, RG, Bydder, GM, Brooks, DJ. Correlating rates of cerebral atrophy in Parkinson’s disease with measures of cognitive decline. J Neural Transm. 2001; 108: 57180.CrossRefGoogle ScholarPubMed
13. Alegret, M, Junque, C, Pueyo, R, Valldeoriola, F, Vendrell, P, Tolosa, E, et al. MRI atrophy parameters related to cognitive and motor impairment in Parkinson’s disease. Neurologia. 2001; 16: 639.Google ScholarPubMed
14. Piccini, P, Pavese, N, Canapicchi, R, Paoli, C, Del Dotto, P, Puglioli, M, et al. White matter hyperintensities in Parkinson’s disease. Clinical correlations. Arch Neurol. 1995; 52: 1914.CrossRefGoogle ScholarPubMed
15. Beyer, MK, Aarsland, D, Greve, OJ, Larsen, JP. Visual rating of white matter hyperintensities in Parkinson’s disease. Mov Disord. 2006; 21: 2239.CrossRefGoogle ScholarPubMed
16. Jankovic, J, McDermott, M, Carter, J, Gauthier, S, Goetz, C, Golbe, L, et al. Variable expression of Parkinson’s disease: a base-line analysis of the DATATOP cohort. The Parkinson Study Group. Neurology. 1990; 40: 152934.CrossRefGoogle ScholarPubMed
17. Jankovic, J, Kapadia, AS. Functional decline in Parkinson disease. Arch Neurol. 2001; 58: 161115.CrossRefGoogle ScholarPubMed
18. Burn, DJ, Rowan, EN, Allan, LM, Molloy, S, O’Brien, J T, McKeith, IG. Motor subtype and cognitive decline in Parkinson’s disease, Parkinson’s disease with dementia, and dementia with Lewy bodies. J Neurol Neurosurg Psychiatry. 2006; 77: 5859.CrossRefGoogle ScholarPubMed
19. Levy, G, Tang, MX, Cote, LJ, Louis, ED, Alfaro, B, Mejia, H, et al. Motor impairment in PD: relationship to incident dementia and age. Neurology. 2000; 55: 53944.CrossRefGoogle ScholarPubMed
20. Litvan, I, Bhatia, KP, Burn, DJ, Goetz, CG, Lang, AE, McKeith, I, et al. Movement Disorders Society Scientific Issues Committee report: SIC Task Force appraisal of clinical diagnostic criteria for Parkinsonian disorders. Mov Disord. 2003; 18: 46786.CrossRefGoogle ScholarPubMed
21. Hoehn, MM, Yahr, MD. Parkinsonism: onset, progression, and mortality. 1967. Neurology. 2001; 57: S1126.Google ScholarPubMed
22. Morris, JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology. 1993; 43: 241214.CrossRefGoogle ScholarPubMed
23. Folstein, MF, Folstein, SE, McHugh, PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975; 12: 18998.CrossRefGoogle ScholarPubMed
24. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Text Revision. Washington, D.C.: American Psychiatric Association, 2000.Google Scholar
25. Gancher, ST. Scales for the assessment of movement disorders. Handbook of neurologic rating scales 1997:81106.Google Scholar
26. Brown, GG, Rahill, AA, Gorell, JM, McDonald, C, Brown, SJ, Sillanpaa, M, et al. Validity of the Dementia Rating Scale in assessing cognitive function in Parkinson’s disease. J Geriatr Psychiatry Neurol. 1999; 12: 1808.CrossRefGoogle ScholarPubMed
27. Eritaia, J, Wood, SJ, Stuart, GW, Bridle, N, Dudgeon, P, Maruff, P, et al. An optimized method for estimating intracranial volume from magnetic resonance images. Magn Reson Med. 2000; 44: 9737.3.0.CO;2-H>CrossRefGoogle ScholarPubMed
28. Buchsbaum, MS, Yang, S, Hazlett, E, Siegel, BV Jr., Germans, M, Haznedar, M, et al. Ventricular volume and asymmetry in schizotypal personality disorder and schizophrenia assessed with magnetic resonance imaging. Schizophr Res. 1997; 27: 4553.CrossRefGoogle ScholarPubMed
29. Brambilla, P, Harenski, K, Nicoletti, M, Mallinger, AG, Frank, E, Kupfer, DJ, et al. MRI study of posterior fossa structures and brain ventricles in bipolar patients. J Psychiatr Res. 2001; 35: 31322.CrossRefGoogle ScholarPubMed
30. Whitwell, JL, Crum, WR, Watt, HC, Fox, NC. Normalization of cerebral volumes by use of intracranial volume: implications for longitudinal quantitative MR imaging. AJNR Am J Neuroradiol. 2001; 22: 14839.Google ScholarPubMed
31. Wahlund, LO, Barkhof, F, Fazekas, F, Bronge, L, Augustin, M, Sjogren, M, et al. A new rating scale for age-related white matter changes applicable to MRI and CT. Stroke. 2001; 32: 131822.CrossRefGoogle ScholarPubMed
32. Zar, J. Comparing simple linear regression equations. In: Ryu, T, editor. Biostatistical analysis. Upper Saddle River: Prentice-Hall; 1999. p.3608.Google Scholar
33. Camicioli, R, Moore, MM, Kinney, A, Corbridge, E, Glassberg, K, Kaye, JA. Parkinson’s disease is associated with hippocampal atrophy. Mov Disord. 2003; 18: 78490.CrossRefGoogle ScholarPubMed
34. Camicioli, RM, Korzan, JR, Foster, SL, Fisher, NJ, Emery, DJ, Bastos, AC, et al. Posterior cingulate metabolic changes occur in Parkinson’s disease patients without dementia. Neurosci Lett. 2004; 354: 17780.CrossRefGoogle ScholarPubMed
35. Schneider, E, Fischer, PA, Jacobi, P, Becker, H, Beyer, M. Cerebral atrophy and long-term response to levodopa in Parkinson’s disease. J Neurol. 1979; 222: 3743.CrossRefGoogle ScholarPubMed
36. Becker, H, Schneider, E, Hacker, H, Fischer, PA. Cerebral atrophy in Parkinson’s disease--represented in CT. Arch Psychiatr Nervenkr. 1979; 227: 818.CrossRefGoogle ScholarPubMed
37. Drayer, BP. Imaging of the aging brain. Part I. Normal findings. Radiology. 1988; 166: 78596.CrossRefGoogle ScholarPubMed
38. Lewis, GN, Byblow, WD, Walt, SE. Stride length regulation in Parkinson’s disease: the use of extrinsic, visual cues. Brain. 2000; 123 (Pt 10): 207790.CrossRefGoogle ScholarPubMed
39. Sohn, YH, Kim, JS. The influence of white matter hyperintensities on the clinical features of Parkinson’s disease. Yonsei Med J. 1998; 39: 505.CrossRefGoogle ScholarPubMed
40. Jellinger, KA. Prevalence of cerebrovascular lesions in Parkinson’s disease. A postmortem study. Acta Neuropathol (Berl). 2003; 105: 41519.CrossRefGoogle ScholarPubMed
41. Guerini, F, Frisoni, GB, Bellwald, C, Rossi, R, Bellelli, G, Trabucchi, M. Subcortical vascular lesions predict functional recovery after rehabilitation in patients with L-dopa refractory parkinsonism. J Am Geriatr Soc. 2004; 52: 2526.CrossRefGoogle ScholarPubMed
42. Lang, AE, Obeso, JA. Challenges in Parkinson’s disease: restoration of the nigrostriatal dopamine system is not enough. The Lancet Neurology. 2004; 3: 309.CrossRefGoogle ScholarPubMed
43. Koller, W, O’Hara, R, Weiner, W, Lang, A, Nutt, J, Agid, Y, et al. Relationship of aging to Parkinson’s disease. Adv Neurol. 1987; 45: 31721.Google ScholarPubMed