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Structural Imaging in Parkinson’s Disease: New Developments

  • Movement Disorders (T. Simuni, Section Editor)
  • Published:
Current Neurology and Neuroscience Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

To review the advances in structural imaging for the diagnosis, prognosis, and treatment of Parkinson’s disease (PD) during the last 5 years.

Recent Findings

Structural imaging using high-field MRI (≥ 3 T) and new MR sequences sensitive to iron and nigral pigments have achieved to assess in vivo pathological surrogates useful for PD diagnosis (notably decreased nigral neuromelanin and loss of dorsal nigral hyperintensity, increased nigral iron content, diffusivity, and free-water), prodromal diagnosis (decreased neuromelanin signal in the locus coeruleus), and PD progression (with increasing nigral iron content (increasing R2* rate) and nigral damage (increasing free-water)). Additionally, evaluation of atrophy in small monoaminergic nuclei is useful for prognosis, including cholinergic basal forebrain nuclei atrophy for cognitive impairment.

Summary

New advances in multimodal structural imaging improve diagnosis, prognosis, and prediction of invasive treatment outcome in PD, and may further benefit from machine learning and large scale longitudinal studies to better identify prognostic subtypes.

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References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Lewy FH. Paralysis agitans. I. In: Lewandowsky M, Abelsdorff G, editors. Pathologische Anatomie. Berlin: Springer, Berlin; 1912.

    Google Scholar 

  2. Trétiakoff C. Contribution a l’etude de l’anatomie pathologique du Locus Niger de Soemmering avec quelques deduction relatives a la pathogenie des troubles du tonus musculaire et de la maladie de Parkinson. [Paris]: University of Paris; 1919.

  3. Berg D, Postuma RB, Bloem B, Chan P, Dubois B, Gasser T, et al. Time to redefine PD? Introductory statement of the MDS task force on the definition of Parkinson’s disease. Mov Disord. 2014;29:454–62.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Rizzo G, Copetti M, Arcuti S, Martino D, Fontana A, Logroscino G. Accuracy of clinical diagnosis of Parkinson disease. Neurology. 2016;86:566–76.

    Article  PubMed  Google Scholar 

  5. Postuma RB, Berg D, Stern M, Poewe W, Olanow CW, Oertel W, et al. MDS clinical diagnostic criteria for Parkinson’s disease. Mov Disord. 2015;30:1591–601.

    Article  PubMed  Google Scholar 

  6. Postuma RB, Poewe W, Litvan I, Lewis S, Lang AE, Halliday G, et al. Validation of the MDS clinical diagnostic criteria for Parkinson’s disease: validation of MDS criteria. Mov Disord. 2018;33:1601–8.

    Article  PubMed  CAS  Google Scholar 

  7. Thobois S, Prange S, Scheiber C, Broussolle E. What a neurologist should know about PET and SPECT functional imaging for parkinsonism: a practical perspective. Par kinsonism Relat Disord [Internet] 2018 [cited 2019 Feb 7];0. Available from: https://www.prd-journal.com/article/S1353-8020(18)30375-4/abstract.

  8. Lehericy S, Vaillancourt DE, Seppi K, Monchi O, Rektorova I, Antonini A, et al. The role of high-field magnetic resonance imaging in parkinsonian disorders: pushing the boundaries forward. Mov Disord. 2017;32:510–25.

    Article  PubMed  Google Scholar 

  9. Schwarz ST, Xing Y, Tomar P, Bajaj N, Auer DP. In vivo assessment of brainstem depigmentation in Parkinson disease: potential as a severity marker for multicenter studies. Radiology. 2017;283:789–98.

    Article  PubMed  Google Scholar 

  10. Taniguchi D, Hatano T, Kamagata K, Okuzumi A, Oji Y, Mori A, et al. Neuromelanin imaging and midbrain volumetry in progressive supranuclear palsy and Parkinson’s disease: neuromelanin-MRI and midbrain Volumetry. Mov Disord. 2018;33:1488–92.

    Article  PubMed  CAS  Google Scholar 

  11. Castellanos G, Fernández-Seara MA, Lorenzo-Betancor O, Ortega-Cubero S, Puigvert M, Uranga J, et al. Automated neuromelanin imaging as a diagnostic biomarker for Parkinson’s disease. Mov Disord. 2015;30:945–52.

    Article  PubMed  Google Scholar 

  12. Prasad S, Saini J, Yadav R, Pal PK. Motor asymmetry and neuromelanin imaging: concordance in Parkinson’s disease. Parkinsonism Relat Disord. 2018;53:28–32.

    Article  PubMed  Google Scholar 

  13. Xing Y, Sapuan A, Dineen RA, Auer DP. Life span pigmentation changes of the substantia nigra detected by neuromelanin-sensitive MRI: life span pigmentation changes detected by MRI. Mov Disord. 2018;33:1792–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Shibata E, Sasaki M, Tohyama K, Kanbara Y, Otsuka K, Ehara S, et al. Age-related changes in locus ceruleus on neuromelanin magnetic resonance imaging at 3 tesla. Magn Reson Med Sci. 2006;5:197–200.

    Article  PubMed  Google Scholar 

  15. Damier P, Hirsch EC, Agid Y, Graybiel AM. The substantia nigra of the human brainII. Patterns of loss of dopamine-containing neurons in Parkinson’s disease. Brain. 1999;122:1437–48.

    Article  PubMed  Google Scholar 

  16. Lehéricy S, Bardinet E, Poupon C, Vidailhet M, François C. 7 tesla magnetic resonance imaging: a closer look at substantia nigra anatomy in Parkinson’s disease. Mov Disord. 2014;29:1574–81.

    Article  PubMed  CAS  Google Scholar 

  17. Schwarz ST, Afzal M, Morgan PS, Bajaj N, Gowland PA, Auer DP. The ‘swallow tail’ appearance of the healthy nigrosome – a new accurate test of Parkinson’s disease: a case-control and retrospective cross-sectional MRI study at 3T. PLoS One. 2014;9:e93814.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Schmidt MA, Engelhorn T, Marxreiter F, Winkler J, Lang S, Kloska S, et al. Ultra high-field SWI of the substantia nigra at 7T: reliability and consistency of the swallow-tail sign. BMC Neurol. 2017;17:194.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Blazejewska AI, Schwarz ST, Pitiot A, Stephenson MC, Lowe J, Bajaj N, et al. Visualization of nigrosome 1 and its loss in PD. Neurology. 2013;81:534–40.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Mahlknecht P, Krismer F, Poewe W, Seppi K. Meta-analysis of dorsolateral nigral hyperintensity on magnetic resonance imaging as a marker for Parkinson’s disease. Mov Disord. 2017;32:619–23.

    Article  PubMed  CAS  Google Scholar 

  21. Shams S, Fällmar D, Schwarz S, Wahlund L-O, van WD, Hansson O, et al. MRI of the swallow tail sign: a useful marker in the diagnosis of Lewy body dementia? Am J Neuroradiol. 2017;38:1737–41.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  22. Yousaf T, Dervenoulas G, Valkimadi P-E, Politis M. Neuroimaging in Lewy body dementia. J Neurol. 2019;266:1–26.

    Article  PubMed  Google Scholar 

  23. Rizzo G, De Blasi R, Capozzo R, Tortelli R, Barulli MR, Liguori R, et al. Loss of swallow tail sign on susceptibility-weighted imaging in dementia with Lewy bodies. J Alzheimers Dis. 2019;67:61–5.

    Article  PubMed  Google Scholar 

  24. Bae YJ, Kim J-M, Kim KJ, Kim E, Park HS, Kang SY, et al. Loss of substantia nigra hyperintensity at 3.0-T MR imaging in idiopathic REM sleep behavior disorder: comparison with 123I-FP-CIT SPECT. Radiology. 2017:162486.

  25. Schwarz ST, Mougin O, Xing Y, Blazejewska A, Bajaj N, Auer DP, et al. Parkinson’s disease related signal change in the nigrosomes 1–5 and the substantia nigra using T2* weighted 7T MRI. NeuroImage Clin. 2018;19:683–9.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Massey L, Miranda M, Al-Helli O, Parkes H, Thornton J, So P-W, et al. 9.4T MR microscopy of the substantia nigra with pathological validation in controls and disease. NeuroImage Clin. 2017;13:154–63.

    Article  PubMed  CAS  Google Scholar 

  27. Gramsch C, Reuter I, Kraff O, Quick HH, Tanislav C, Roessler F, et al. Nigrosome 1 visibility at susceptibility weighted 7T MRI—A dependable diagnostic marker for Parkinson’s disease or merely an inconsistent, age-dependent imaging finding? PLoS One. 2017;12:e0185489.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Kau T, Hametner S, Endmayr V, Deistung A, Prihoda M, Haimburger E, et al. Microvessels may confound the “swallow tail sign” in normal aged midbrains: a postmortem 7 T SW-MRI study. J Neuroimaging. 2019;29:65–9.

    Article  PubMed  Google Scholar 

  29. Martin-Bastida A, Lao-Kaim NP, Loane C, Politis M, Roussakis AA, Valle-Guzman N, et al. Motor associations of iron accumulation in deep grey matter nuclei in Parkinson’s disease: a cross-sectional study of iron-related magnetic resonance imaging susceptibility. Eur J Neurol. 2017;24:357–65.

    Article  PubMed  CAS  Google Scholar 

  30. Martin WRW, Wieler M, Gee M. Midbrain iron content in early Parkinson disease: a potential biomarker of disease status. Neurology. 2008;70:1411–7.

    Article  PubMed  CAS  Google Scholar 

  31. Ulla M, Bonny JM, Ouchchane L, Rieu I, Claise B, Durif F. Is R2* a new MRI biomarker for the progression of Parkinson’s disease? A longitudinal follow-up. PLoS One. 2013;8:e57904.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Lewis MM, Du G, Baccon J, Snyder AM, Murie B, Cooper F, et al. Susceptibility MRI captures nigral pathology in patients with parkinsonian syndromes: R2* and QSM reflect pathology in parkinsonism. Mov Disord. 2018;33:1432–9.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  33. Du G, Liu T, Lewis MM, Kong L, Wang Y, Connor J, et al. Quantitative susceptibility mapping of the midbrain in Parkinson’s disease. Mov Disord. 2016;31:317–24.

    Article  PubMed  Google Scholar 

  34. Sun H, Walsh AJ, Lebel RM, Blevins G, Catz I, Lu J-Q, et al. Validation of quantitative susceptibility mapping with Perls’ iron staining for subcortical gray matter. NeuroImage. 2015;105:486–92.

    Article  PubMed  Google Scholar 

  35. Azuma M, Hirai T, Yamada K, Yamashita S, Ando Y, Tateishi M, et al. Lateral asymmetry and spatial difference of iron deposition in the substantia nigra of patients with Parkinson disease measured with quantitative susceptibility mapping. Am J Neuroradiol. 2016;37:782–8.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  36. Langkammer C, Pirpamer L, Seiler S, Deistung A, Schweser F, Franthal S, et al. Quantitative susceptibility mapping in Parkinson’s disease. PLoS One. 2016;11:e0162460.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Li G, Zhai G, Zhao X, An H, Spincemaille P, Gillen KM, et al. 3D texture analyses within the substantia nigra of Parkinson’s disease patients on quantitative susceptibility maps and R2∗ maps. NeuroImage. 2019;188:465–72.

    Article  PubMed  Google Scholar 

  38. Du G, Lewis MM, Sica C, He L, Connor JR, Kong L, et al. Distinct progression pattern of susceptibility MRI in the substantia nigra of Parkinson’s patients: longitudinal R2* and QSM progression in PD. Mov Disord. 2018;33:1423–31.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Vaillancourt DE, Spraker MB, Prodoehl J, Abraham I, Corcos DM, Zhou XJ, et al. High-resolution diffusion tensor imaging in the substantia nigra of de novo Parkinson disease. Neurology. 2009;72:1378–84.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Atkinson-Clement C, Pinto S, Eusebio A, Coulon O. Diffusion tensor imaging in Parkinson’s disease: review and meta-analysis. NeuroImage Clin. 2017;16:98–110.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Deng X-Y, Wang L, Yang T-T, Li R, Yu G. A meta-analysis of diffusion tensor imaging of substantia nigra in patients with Parkinson’s disease. Sci Rep. 2018;8:2941.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Ofori E, Pasternak O, Planetta PJ, Li H, Burciu RG, Snyder AF, et al. Longitudinal changes in free-water within the substantia nigra of Parkinson’s disease. Brain. 2015;138:2322–31.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Planetta PJ, Ofori E, Pasternak O, Burciu RG, Shukla P, DeSimone JC, et al. Free-water imaging in Parkinson’s disease and atypical parkinsonism. Brain. 2016;139:495–508.

    Article  PubMed  Google Scholar 

  44. •• Burciu RG, Ofori E, Archer DB, Wu SS, Pasternak O, McFarland NR, et al. Progression marker of Parkinson’s disease: a 4-year multi-site imaging study. Brain. 2017;140:2183–92 Multicenter validation study of nigral damage using a bi-tensor diffusion model (increased free-water) as a progression marker over 4 years.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Yang J, Archer DB, Burciu RG, Müller MLTM, Roy A, Ofori E, Bohnen NI, Albin RL, Vaillancourt DE Multimodal dopaminergic and free-water imaging in Parkinson’s disease. Parkinsonism Relat Disord [Internet]. 2019 [cited 2019 Jan 11]; Available from: http://www.sciencedirect.com/science/article/pii/S1353802019300070.

  46. Tao A, Chen G, Deng Y, Xu R. Accuracy of transcranial sonography of the substantia Nigra for detection of Parkinson’s disease: a systematic review and meta-analysis. Ultrasound Med Biol [Internet] 2019 [cited 2019 Jan 8]; Available from: http://www.sciencedirect.com/science/article/pii/S0301562918305210, 45, 628, 641.

    Article  Google Scholar 

  47. Weise D, Lorenz R, Schliesser M, Schirbel A, Reiners K, Classen J. Substantia nigra echogenicity: a structural correlate of functional impairment of the dopaminergic striatal projection in Parkinson’s disease. Mov Disord. 2009;24:1669–75.

    Article  PubMed  Google Scholar 

  48. Behnke S, Runkel A, Kassar HA-S, Ortmann M, Guidez D, Dillmann U, et al. Long-term course of substantia nigra hyperechogenicity in Parkinson’s disease. Mov Disord. 2013;28:455–9.

    Article  PubMed  Google Scholar 

  49. Berg D, Seppi K, Behnke S, Liepelt I, Schweitzer K, Stockner H, et al. Enlarged substantia nigra hyperechogenicity and risk for Parkinson disease: a 37-month 3-center study of 1847 older persons. Arch Neurol. 2011;68:932–7.

    Article  PubMed  Google Scholar 

  50. • Du G, Lewis MM, Sica C, Kong L, Huang X. Magnetic resonance T1w/T2w ratio: a parsimonious marker for Parkinson disease: midbrain T1w/T2w ratio in PD. Ann Neurol. 2019;85:96–104 MRI study identifying the midbrain T1/T2 ratio using conventional MRI as a promising, simple diagnostic marker.

    Article  PubMed  Google Scholar 

  51. Li X, Xing Y, Martin-Bastida A, Piccini P, Auer DP. Patterns of grey matter loss associated with motor subscores in early Parkinson’s disease. NeuroImage Clin. 2018;17:498–504.

    Article  PubMed  Google Scholar 

  52. Sterling NW, Du G, Lewis MM, Dimaio C, Kong L, Eslinger PJ, et al. Striatal shape in Parkinson’s disease. Neurobiol Aging. 2013;34:2510–6.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Lee HM, Kwon K-Y, Kim M-J, Jang J-W, Suh S, Koh S-B, et al. Subcortical grey matter changes in untreated, early stage Parkinson’s disease without dementia. Parkinsonism Relat Disord. 2014;20:622–6.

    Article  PubMed  Google Scholar 

  54. Garg A, Appel-Cresswell S, Popuri K, McKeown MJ, Beg MF. Morphological alterations in the caudate, putamen, pallidum, and thalamus in Parkinson’s disease. Front Neurosci. 2015;9:101.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Surova Y, Nilsson M, Lampinen B, Lätt J, Hall S, Widner H, et al. Alteration of putaminal fractional anisotropy in Parkinson’s disease: a longitudinal diffusion kurtosis imaging study. Neuroradiology. 2018;60:247–54.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Pozorski V, Oh JM, Adluru N, Merluzzi AP, Theisen F, Okonkwo O, et al. Longitudinal white matter microstructural change in Parkinson’s disease. Hum Brain Mapp. 2018;39:4150–61.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Albrecht F, Ballarini T, Neumann J, Schroeter ML. FDG-PET hypometabolism is more sensitive than MRI atrophy in Parkinson’s disease: a whole-brain multimodal imaging meta-analysis. NeuroImage Clin. 2019;21:101594.

    Article  PubMed  Google Scholar 

  58. Sampedro F, Marín-Lahoz J, Martínez-Horta S, Pagonabarraga J, Kulisevsky J. Dopaminergic degeneration induces early posterior cortical thinning in Parkinson’s disease. Neurobiol Dis. 2019;124:29–35.

    Article  PubMed  CAS  Google Scholar 

  59. Sterling NW, Du G, Lewis MM, Swavely S, Kong L, Styner M, et al. Cortical gray and subcortical white matter associations in Parkinson’s disease. Neurobiol Aging. 2017;49:100–8.

    Article  PubMed  Google Scholar 

  60. Zeighami Y, Ulla M, Iturria-Medina Y, Dadar M, Zhang Y, KM-H L, et al. Network structure of brain atrophy in de novo Parkinson’s disease. eLife. 2015;4:e08440.

    Article  PubMed Central  Google Scholar 

  61. de Schipper LJ, van der Grond J, Marinus J, Henselmans JML, van Hilten JJ. Loss of integrity and atrophy in cingulate structural covariance networks in Parkinson’s disease. NeuroImage Clin. 2017;15:587–93.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Wu Q, Gao Y, Liu A-S, Xie L-Z, Qian L, Yang X-G. Large-scale cortical volume correlation networks reveal disrupted small world patterns in Parkinson’s disease. Neurosci Lett. 2018;662:374–80.

    Article  PubMed  CAS  Google Scholar 

  63. Ji G-J, Ren C, Li Y, Sun J, Liu T, Gao Y, Xue D, Shen L, Cheng W, Zhu C, Tian Y, Hu P, Chen X, Wang K Regional and network properties of white matter function in Parkinson’s disease. Hum Brain Mapp [Internet] 2018 [cited 2019 Jan 11]; Available from: https://doi.org/10.1002/hbm.24444, 40, 1253, 1263

    Article  PubMed  PubMed Central  Google Scholar 

  64. Luo CY, Guo XY, Song W, Chen Q, Cao B, Yang J, et al. Functional connectome assessed using graph theory in drug-naive Parkinson’s disease. J Neurol. 2015;262:1557–67.

    Article  PubMed  CAS  Google Scholar 

  65. Sreenivasan K, Mishra V, Bird C, Zhuang X, Yang Z, Cordes D, Walsh RR Altered functional network topology correlates with clinical measures in very early-stage, drug-naïve Parkinson’s disease. Parkinsonism Relat Disord [Internet]. 2019 [cited 2019 Feb 15]; Available from: http://www.sciencedirect.com/science/article/pii/S135380201930032X.

  66. Yau Y, Zeighami Y, Baker TE, Larcher K, Vainik U, Dadar M, Fonov VS, Hagmann P, Griffa A, Mišić B, Collins DL, Dagher A Network connectivity determines cortical thinning in early Parkinson’s disease progression. Nat Commun 2018;9:12. Multimodal MRI study suggesting that disease propagation subserving cortical atrophy follows neuronal connectivity to a PD ‘disease reservoir’.

  67. Theisen F, Leda R, Pozorski V, Oh JM, Adluru N, Wong R, et al. Evaluation of striatonigral connectivity using probabilistic tractography in Parkinson’s disease. NeuroImage Clin. 2017;16:557–63.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Schrag A, Horsfall L, Walters K, Noyce A, Petersen I. Prediagnostic presentations of Parkinson’s disease in primary care: a case-control study. Lancet Neurol. 2015;14:57–64.

    Article  PubMed  Google Scholar 

  69. Berg D, Postuma RB, Adler CH, Bloem BR, Chan P, Dubois B, et al. MDS research criteria for prodromal Parkinson’s disease. Mov Disord. 2015;30:1600–11.

    Article  PubMed  Google Scholar 

  70. Fereshtehnejad S-M, Montplaisir JY, Pelletier A, Gagnon J-F, Berg D, Postuma RB. Validation of the MDS research criteria for prodromal Parkinson’s disease: longitudinal assessment in a REM sleep behavior disorder (RBD) cohort. Mov Disord. 2017;32:865–73.

    Article  PubMed  Google Scholar 

  71. Iranzo A, Fernández-Arcos A, Tolosa E, Serradell M, Molinuevo JL, Valldeoriola F, et al. Neurodegenerative disorder risk in idiopathic REM sleep behavior disorder: study in 174 patients. PLoS One. 2014;9:e89741.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  72. Postuma RB, Iranzo A, Hu M, Högl B, Boeve BF, Manni R, et al. Risk and predictors of dementia and parkinsonism in idiopathic REM sleep behaviour disorder: a multicentre study. Brain. 2019;142:744–59.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Ehrminger M, Latimier A, Pyatigorskaya N, Garcia-Lorenzo D, Leu-Semenescu S, Vidailhet M, Lehericy S, Arnulf I The coeruleus/subcoeruleus complex in idiopathic rapid eye movement sleep behaviour disorder. Brain. 2016;139:1180–1188. Neuromelanin-sensitive MRI study identifying that decreased neuromelanin signal in the locus coeruleus represents an early marker of non-dopaminergic alpha-synucleinopathy that can be detected on an individual basis.

    Article  PubMed  Google Scholar 

  74. Knudsen K, Fedorova TD, Hansen AK, Sommerauer M, Otto M, Svendsen KB, Nahimi A, Stokholm MG, Pavese N, Beier CP, Brooks DJ, Borghammer P In-vivo staging of pathology in REM sleep behaviour disorder: a multimodality imaging case-control study. Lancet Neurol 2018;17:618–628. Multimodal imaging study evidencing a continuum in the pattern of peripheral and central pathology in RBD and PD patients.

    Article  PubMed  Google Scholar 

  75. Braak H, Tredici KD, Rüb U, de Vos RAI, Jansen Steur ENH, Braak E. Staging of brain pathology related to sporadic Parkinson’s disease. Neurobiol Aging. 2003;24:197–211.

    Article  PubMed  Google Scholar 

  76. Surmeier DJ, Obeso JA, Halliday GM. Selective neuronal vulnerability in Parkinson disease. Nat Rev Neurosci. 2017;18:101–13.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  77. Iranzo A, Lomeña F, Stockner H, Valldeoriola F, Vilaseca I, Salamero M, et al. Decreased striatal dopamine transporter uptake and substantia nigra hyperechogenicity as risk markers of synucleinopathy in patients with idiopathic rapid-eye-movement sleep behaviour disorder: a prospective study. Lancet Neurol. 2010;9:1070–7.

    Article  PubMed  CAS  Google Scholar 

  78. Mueller C, Hussl A, Krismer F, Heim B, Mahlknecht P, Nocker M, et al. The diagnostic accuracy of the hummingbird and morning glory sign in patients with neurodegenerative parkinsonism. Parkinsonism Relat Disord. 2018;54:90–4.

    Article  PubMed  Google Scholar 

  79. Quattrone A, Nicoletti G, Messina D, Fera F, Condino F, Pugliese P, et al. MR imaging index for differentiation of progressive supranuclear palsy from Parkinson disease and the Parkinson variant of multiple system atrophy. Radiology. 2008;246:214–21.

    Article  PubMed  Google Scholar 

  80. Quattrone A, Morelli M, Williams DR, Vescio B, Arabia G, Nigro S, et al. MR parkinsonism index predicts vertical supranuclear gaze palsy in patients with PSP–parkinsonism. Neurology. 2016;87:1266–73.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Longoni G, Agosta F, Kostić VS, Stojković T, Pagani E, Stošić-Opinćal T, et al. MRI measurements of brainstem structures in patients with Richardson’s syndrome, progressive supranuclear palsy-parkinsonism, and Parkinson’s disease. Mov Disord. 2011;26:247–55.

    Article  PubMed  Google Scholar 

  82. Quattrone A, Morelli M, Nigro S, Quattrone A, Vescio B, Arabia G, et al. A new MR imaging index for differentiation of progressive supranuclear palsy-parkinsonism from Parkinson’s disease. Parkinsonism Relat Disord. 2018;54:3–8.

    Article  PubMed  Google Scholar 

  83. Quattrone A, Morelli M, Vescio B, Nigro S, Le Piane E, Sabatini U, et al. Refining initial diagnosis of Parkinson’s disease after follow-up: a 4-year prospective clinical and magnetic resonance imaging study. Mov Disord [Internet]. 2019 [cited 2019 Feb 21]; Available from: https://doi.org/10.1002/mds.27621

    Article  PubMed  PubMed Central  Google Scholar 

  84. Gupta D, Saini J, Kesavadas C, Sarma PS, Kishore A. Utility of susceptibility-weighted MRI in differentiating Parkinson’s disease and atypical parkinsonism. Neuroradiology. 2010;52:1087–94.

    Article  PubMed  Google Scholar 

  85. Schrag A, Kingsley D, Phatouros C, Mathias CJ, Lees AJ, Daniel SE, et al. Clinical usefulness of magnetic resonance imaging in multiple system atrophy. J Neurol Neurosurg Psychiatry. 1998;65:65–71.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  86. Ramli N, Nair SR, Ramli NM, Lim SY. Differentiating multiple-system atrophy from Parkinson’s disease. Clin Radiol. 2015;70:555–64.

    Article  PubMed  CAS  Google Scholar 

  87. Zanigni S, Evangelisti S, Testa C, Manners DN, Calandra-Buonaura G, Guarino M, et al. White matter and cortical changes in atypical parkinsonisms: a multimodal quantitative MR study. Parkinsonism Relat Disord. 2017;39:44–51.

    Article  PubMed  Google Scholar 

  88. Lee EA, Cho HI, Kim SS, Lee WY. Comparison of magnetic resonance imaging in subtypes of multiple system atrophy. Parkinsonism Relat Disord. 2004;10:363–8.

    Article  PubMed  Google Scholar 

  89. Wang N, Zhang L, Yang H, Liu H, Luo X, Fan G. Similarities and differences in cerebellar grey matter volume and disrupted functional connectivity in idiopathic Parkinson’s disease and multiple system atrophy. Neuropsychologia. 2019;124:125–32.

    Article  PubMed  Google Scholar 

  90. Shao N, Yang J, Shang H. Voxelwise meta-analysis of gray matter anomalies in Parkinson variant of multiple system atrophy and Parkinson’s disease using anatomic likelihood estimation. Neurosci Lett. 2015;587:79–86.

    Article  PubMed  CAS  Google Scholar 

  91. Baudrexel S, Seifried C, Penndorf B, Klein JC, Middendorp M, Steinmetz H, et al. The value of putaminal diffusion imaging versus 18-fluorodeoxyglucose positron emission tomography for the differential diagnosis of the Parkinson variant of multiple system atrophy. Mov Disord. 2014;29:380–7.

    Article  PubMed  CAS  Google Scholar 

  92. Bajaj S, Krismer F, Palma J-A, Wenning GK, Kaufmann H, Poewe W, et al. Diffusion-weighted MRI distinguishes Parkinson disease from the parkinsonian variant of multiple system atrophy: a systematic review and meta-analysis. PLoS One. 2017;12:e0189897.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  93. Oppedal K, Ferreira D, Cavallin L, Lemstra AW, ten KM, Padovani A, et al. A signature pattern of cortical atrophy in dementia with Lewy bodies: a study on 333 patients from the European DLB consortium. Alzheimers Dement J Alzheimers Assoc. 2019;15:400–9.

    Article  Google Scholar 

  94. Watson R, Blamire AM, Colloby SJ, Wood JS, Barber R, He J, et al. Characterizing dementia with Lewy bodies by means of diffusion tensor imaging. Neurology. 2012;79:906–14.

    Article  PubMed  PubMed Central  Google Scholar 

  95. Whitwell JL, Jack CR, Boeve BF, Parisi JE, Ahlskog JE, Drubach DA, et al. Imaging correlates of pathology in corticobasal syndrome. Neurology. 2010;75:1879–87.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  96. Albrecht F, Bisenius S, Schaack RM, Neumann J, Schroeter ML. Disentangling the neural correlates of corticobasal syndrome and corticobasal degeneration with systematic and quantitative ALE meta-analyses. Npj Park Dis. 2017;3:12.

    Article  Google Scholar 

  97. Prange S, Danaila T, Laurencin C, Caire C, Metereau E, Merle H, et al. Age and time course of long-term motor and nonmotor complications in Parkinson disease. Neurology. 2019;92:e148–60.

    Article  PubMed  Google Scholar 

  98. Nutt JG. Motor subtype in Parkinson’s disease: different disorders or different stages of disease? Mov Disord. 2016;31:957–61.

    Article  PubMed  Google Scholar 

  99. Selikhova M, Williams DR, Kempster PA, Holton JL, Revesz T, Lees AJ. A clinico-pathological study of subtypes in Parkinson’s disease. Brain. 2009;132:2947–57.

    Article  PubMed  CAS  Google Scholar 

  100. Fereshtehnejad S-M, Zeighami Y, Dagher A, Postuma RB. Clinical criteria for subtyping Parkinson’s disease: biomarkers and longitudinal progression. Brain. 2017;140:1959–76.

    Article  PubMed  Google Scholar 

  101. Rosenberg-Katz K, Herman T, Jacob Y, Giladi N, Hendler T, Hausdorff JM. Gray matter atrophy distinguishes between Parkinson disease motor subtypes. Neurology. 2013;80:1476–84.

    Article  PubMed  PubMed Central  Google Scholar 

  102. Rosenberg-Katz K, Herman T, Jacob Y, Kliper E, Giladi N, Hausdorff JM. Subcortical volumes differ in Parkinson’s disease motor subtypes: new insights into the pathophysiology of disparate symptoms. Front Hum Neurosci. 2016;10:356.

    Article  PubMed  PubMed Central  Google Scholar 

  103. Nyberg EM, Tanabe J, Honce JM, Krmpotich T, Shelton E, Hedeman J, et al. Morphologic changes in the mesolimbic pathway in Parkinson’s disease motor subtypes. Parkinsonism Relat Disord. 2015;21:536–40.

    Article  PubMed  PubMed Central  Google Scholar 

  104. Fereshtehnejad S-M, Romenets SR, Anang JBM, Latreille V, Gagnon J-F, Postuma RB. New clinical subtypes of Parkinson disease and their longitudinal progression: a prospective cohort comparison with other phenotypes. JAMA Neurol. 2015;72:863–73.

    Article  PubMed  Google Scholar 

  105. Aarsland D, Creese B, Politis M, Chaudhuri KR, Ffytche DH, Weintraub D, et al. Cognitive decline in Parkinson disease. Nat Rev Neurol. 2017;13:217–31.

    Article  PubMed  PubMed Central  Google Scholar 

  106. Mak E, Su L, Williams GB, Firbank MJ, Lawson RA, Yarnall AJ, et al. Baseline and longitudinal grey matter changes in newly diagnosed Parkinson’s disease: ICICLE-PD study. Brain. 2015;138:2974–86.

    Article  PubMed  PubMed Central  Google Scholar 

  107. Lee JE, Cho KH, Song SK, Kim HJ, Lee HS, Sohn YH, et al. Exploratory analysis of neuropsychological and neuroanatomical correlates of progressive mild cognitive impairment in Parkinson’s disease. J Neurol Neurosurg Psychiatry. 2014;85:7–16.

    Article  PubMed  Google Scholar 

  108. Dadar M, Zeighami Y, Yau Y, Fereshtehnejad S-M, Maranzano J, Postuma RB, et al. White matter hyperintensities are linked to future cognitive decline in de novo Parkinson’s disease patients. NeuroImage Clin. 2018;20:892–900.

    Article  PubMed  PubMed Central  Google Scholar 

  109. Minett T, Su L, Mak E, Williams G, Firbank M, Lawson RA, et al. Longitudinal diffusion tensor imaging changes in early Parkinson’s disease: ICICLE-PD study. J Neurol. 2018;265:1528–39.

    Article  PubMed  Google Scholar 

  110. Ray NJ, Bradburn S, Murgatroyd C, Toseeb U, Mir P, Kountouriotis GK, et al. In vivo cholinergic basal forebrain atrophy predicts cognitive decline in de novo Parkinson’s disease. Brain. 2018;141:165–76 MRI study demonstrating that demonstrating that atrophy in basal forebrain cholinergic nuclei may predict cognitive impairment in PD.

    Article  PubMed Central  Google Scholar 

  111. Schulz J, Pagano G, Fernández Bonfante JA, Wilson H, Politis M. Nucleus basalis of Meynert degeneration precedes and predicts cognitive impairment in Parkinson’s disease. Brain. 2018;141:1501–16 MRI study demonstrating demonstrating that atrophy in basal forebrain cholinergic nuclei may predict cognitive impairment in PD.

    Article  PubMed  PubMed Central  Google Scholar 

  112. Gargouri F, Gallea C, Mongin M, Pyatigorskaya N, Valabregue R, Ewenczyk C, Sarazin M, Yahia-Cherif L, Vidailhet M, Lehéricy S Multimodal magnetic resonance imaging investigation of basal forebrain damage and cognitive deficits in Parkinson’s disease. Mov Disord [Internet] 2018 [cited 2018 Dec 17]; Available from: https://doi.org/10.1002/mds.27561.

  113. Liu G, Locascio JJ, Corvol J-C, Boot B, Liao Z, Page K, et al. Prediction of cognition in Parkinson’s disease with a clinical–genetic score: a longitudinal analysis of nine cohorts. Lancet Neurol. 2017;16:620–9.

    Article  PubMed  PubMed Central  Google Scholar 

  114. Schrag A, Siddiqui UF, Anastasiou Z, Weintraub D, Schott JM. Clinical variables and biomarkers in prediction of cognitive impairment in patients with newly diagnosed Parkinson’s disease: a cohort study. Lancet Neurol. 2017;16:66–75.

    Article  PubMed  CAS  Google Scholar 

  115. Caspell-Garcia C, Simuni T, Tosun-Turgut D, Wu I-W, Zhang Y, Nalls M, et al. Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease. PLoS One. 2017;12:e0175674.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  116. Mollenhauer B, Zimmermann J, Sixel-Döring F, Focke NK, Wicke T, Ebentheuer J, Schaumburg M, Lang E, Friede T, Trenkwalder C, on behalf of the DeNoPa Study Group Baseline predictors for progression 4 years after Parkinson’s disease diagnosis in the De novo Parkinson cohort (DeNoPa). Mov Disord [Internet]. [cited 2019 Jan 15];0. Available from: https://doi.org/10.1002/mds.27492, 67, 77

    Article  PubMed  Google Scholar 

  117. Sampedro F, Marín-Lahoz J, Martínez-Horta S, Pagonabarraga J, Kulisevsky J. Reduced gray matter volume in cognitively preserved COMT 158Val/Val Parkinson’s disease patients and its association with cognitive decline. Brain Imaging Behav [Internet] 2019 [cited 2019 Jan 8]; Available from: https://doi.org/10.1007/s11682-018-0022-y.

  118. Pyatigorskaya N, Sharman M, Corvol J-C, Valabregue R, Yahia-Cherif L, Poupon F, et al. High nigral iron deposition in LRRK2 and Parkin mutation carriers using R2* relaxometry. Mov Disord. 2015;30:1077–84.

    Article  PubMed  CAS  Google Scholar 

  119. Saunders-Pullman R, Mirelman A, Alcalay RN, Wang C, Ortega RA, Raymond D, et al. Progression in the LRRK2-associated Parkinson disease population. JAMA Neurol. 2018;75:312–9.

    Article  PubMed  PubMed Central  Google Scholar 

  120. Wile DJ, Agarwal PA, Schulzer M, Mak E, Dinelle K, Shahinfard E, et al. Serotonin and dopamine transporter PET changes in the premotor phase of LRRK2 parkinsonism: cross-sectional studies. Lancet Neurol. 2017;16:351–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  121. Risacher SL, Anderson WH, Charil A, Castelluccio PF, Shcherbinin S, Saykin AJ, et al. Alzheimer disease brain atrophy subtypes are associated with cognition and rate of decline. Neurology. 2017;89:2176–86.

    Article  PubMed  PubMed Central  Google Scholar 

  122. Uribe C, Segura B, Baggio HC, Abos A, Marti MJ, Valldeoriola F, et al. Patterns of cortical thinning in nondemented Parkinson’s disease patients. Mov Disord. 2016;31:699–708.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  123. Uribe C, Segura B, Baggio HC, Abos A, Garcia-Diaz AI, Campabadal A, et al. Cortical atrophy patterns in early Parkinson’s disease patients using hierarchical cluster analysis. Parkinsonism Relat Disord. 2018;50:3–9.

    Article  PubMed  Google Scholar 

  124. Horn A, Kühn AA. Lead-DBS: a toolbox for deep brain stimulation electrode localizations and visualizations. NeuroImage. 2015;107:127–35.

    Article  PubMed  Google Scholar 

  125. Horn A, Kühn AA, Merkl A, Shih L, Alterman R, Fox M. Probabilistic conversion of neurosurgical DBS electrode coordinates into MNI space. NeuroImage. 2017;150:395–404.

    Article  PubMed  Google Scholar 

  126. Horn A, Li N, Dembek TA, Kappel A, Boulay C, Ewert S, et al. Lead-DBS v2: towards a comprehensive pipeline for deep brain stimulation imaging. NeuroImage. 2019;184:293–316.

    Article  PubMed  Google Scholar 

  127. Horn A, Reich M, Vorwerk J, Li N, Wenzel G, Fang Q, et al. Connectivity predicts deep brain stimulation outcome in Parkinson disease. Ann Neurol. 2017;82:67–78.

    Article  PubMed  PubMed Central  Google Scholar 

  128. Vanegas-Arroyave N, Lauro PM, Huang L, Hallett M, Horovitz SG, Zaghloul KA, et al. Tractography patterns of subthalamic nucleus deep brain stimulation. Brain. 2016;139:1200–10.

    Article  PubMed  PubMed Central  Google Scholar 

  129. Riva-Posse P, Choi KS, Holtzheimer PE, Crowell AL, Garlow SJ, Rajendra JK, et al. A connectomic approach for subcallosal cingulate deep brain stimulation surgery: prospective targeting in treatment-resistant depression. Mol Psychiatry. 2018;23:843–9.

    Article  PubMed  CAS  Google Scholar 

  130. Gratwicke J, Zrinzo L, Kahan J, Peters A, Beigi M, Akram H, et al. Bilateral deep brain stimulation of the nucleus basalis of Meynert for Parkinson disease dementia: a randomized clinical trial. JAMA Neurol. 2018;75:169–78.

    Article  PubMed  Google Scholar 

  131. Goetz L, Bhattacharjee M, Ferraye MU, Fraix V, Maineri C, Nosko D, et al. Deep brain stimulation of the pedunculopontine nucleus area in Parkinson disease: MRI-based anatomoclinical correlations and optimal target. Neurosurgery. 2019;84:506–18.

    Article  PubMed  Google Scholar 

  132. Pyatigorskaya N, Magnin B, Mongin M, Yahia-Cherif L, Valabregue R, Arnaldi D, et al. Comparative study of MRI biomarkers in the substantia nigra to discriminate idiopathic Parkinson disease. Am J Neuroradiol. 2018;39:1460–7.

    PubMed  CAS  PubMed Central  Google Scholar 

  133. Jin L, Wang J, Wang C, Lian D, Zhou Y, Zhang Y, et al. Combined visualization of nigrosome-1 and neuromelanin in the substantia nigra using 3T MRI for the differential diagnosis of essential tremor and de novo Parkinson’s disease. Front Neurol [Internet. 2019 [cited 2019 Mar 11;10 Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6379476/.

  134. Salvatore C, Cerasa A, Castiglioni I, Gallivanone F, Augimeri A, Lopez M, et al. Machine learning on brain MRI data for differential diagnosis of Parkinson’s disease and Progressive Supranuclear Palsy. J Neurosci Methods. 2014;222:230–7.

    Article  PubMed  CAS  Google Scholar 

  135. Ballarini T, Mueller K, Albrecht F, Růžička F, Bezdicek O, Růžička E, et al. Regional gray matter changes and age predict individual treatment response in Parkinson’s disease. NeuroImage Clin. 2018:101636.

    Article  Google Scholar 

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Authors and Affiliations

  1. Institut des Sciences Cognitives Marc Jeannerod, Université de Lyon, CNRS, UMR 5229, F-69675, Bron, France

    Stéphane Prange, Elise Metereau & Stéphane Thobois

  2. Hôpital Neurologique Pierre Wertheimer, Service de Neurologie C, Centre Expert Parkinson, Hospices Civils de Lyon, F-69677, Bron, France

    Stéphane Prange, Elise Metereau & Stéphane Thobois

  3. Université Claude Bernard Lyon 1, Faculté de Médecine Lyon Sud Charles Mérieux, Université de Lyon, F-69921, Oullins, France

    Stéphane Thobois

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Stéphane Prange reports grants from Fondation pour la Recherche Médicale and from Association France Parkinson during the conduct of the study. Dr. Prange also reports non-financial support from Abbvie and TEVA, outside the submitted work. Stéphane Thobois reports grants from France Parkinson and Fondation pour la Recherche Médicale, personal fees from Aguettant, Boston, Medtronic, TEVA and Novartis, non-financial support from Abbvie, and Zambon, outside the submitted work. Elise Metereau declares no potential conflicts of interest.

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Prange, S., Metereau, E. & Thobois, S. Structural Imaging in Parkinson’s Disease: New Developments. Curr Neurol Neurosci Rep 19, 50 (2019). https://doi.org/10.1007/s11910-019-0964-5

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