Parkinson’s disease (PD) is a chronic progressive neurodegenerative disorder characterized by tremors, rigidity, and bradykinesia. This is primarily attributed to loss of nigrostriatal dopaminergic neurons to varying degrees. Many conditions that present similar classic motor symptoms of PD, known as atypical parkinsonian syndromes (APS), have also been identified. These encompass multiple system atrophy (MSA), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), and corticobasal degeneration (CBD). On the other hand, causes of non-neurodegenerative parkinsonism include vascular parkinsonism, drug-induced parkinsonism, and essential tremors. Neuroimaging plays a significant role in discriminating PD from its mimics which may represent a significant challenge in clinical practice. This article aims to review recent developments in imaging technologies, particularly magnetic resonance imaging (MRI) and nuclear medicine imaging techniques, that have the potential to unravel characteristic morphological and metabolic changes in the brain and would aid in the early diagnosis of PD and its differentiation from its potential mimickers.
Learning objectives
To identify the peculiar structural imaging features of atypical parkinsonian syndromes and recognize the role of the current state-of-the-art neuroimaging modalities (particularly MRI and nuclear medicine techniques) in discriminating Parkinson’s disease from its mimics.
WirdefeldtKAdamiH-OColeP, et al.Epidemiology and etiology of Parkinson’s disease: a review of the evidence. Eur J Epidemiol2011; 26: 1–58.
2.
PostumaRBBergDSternM, et al.MDS clinical diagnostic criteria for Parkinson's disease. Mov Disord2015; 30: 1591–1601.
3.
HirtzDThurmanDJGwinn-HardyK, et al.How common are the “common” neurologic disorders?Neurology2007; 68: 326–337.
4.
TitovaNPadmakumarCLewisSJ, et al.Parkinson’s: a syndrome rather than a disease?J Neural Transm2017; 124: 907–914.
5.
MarkMH. Lumping and splitting the Parkinson plus syndromes: dementia with Lewy bodies, multiple system atrophy, progressive supranuclear palsy, and cortical-basal ganglionic degeneration. Neurol Clin2001; 19: 607–627.
6.
HughesAJDanielSEKilfordL, et al.Accuracy of clinical diagnosis of idiopathic Parkinson's disease: a clinico-pathological study of 100 cases. J Neurol Neurosurg Psychiatr1992; 55: 181–184.
BaeYJKimJ-MSohnC-H, et al.Imaging the substantia nigra in Parkinson disease and other Parkinsonian syndromes. Radiology2021; 300: 260–278.
9.
DamierPHirschEAgidY, et al.The substantia nigra of the human brain: II. Patterns of loss of dopamine-containing neurons in Parkinson's disease. Brain1999; 122: 1437–1448.
10.
FearnleyJMLeesAJ. Ageing and Parkinson's disease: substantia nigra regional selectivity. Brain1991; 114: 2283–2301.
11.
ZuccaFACapucciatiABelleiC, et al.Neuromelanins in brain aging and Parkinson's disease: synthesis, structure, neuroinflammatory, and neurodegenerative role. IUBMB Life2023; 75: 55–65.
12.
MitraRPremrajLKhooTK. Neuromelanin: its role in the pathogenesis of idiopathic Parkinson's disease and potential as a therapeutic target. Parkinsonism Relat Disorders2023; 112: 105448.
13.
DicksonDW. Neuropathology of Parkinson disease. Parkinsonism Relat Disorders2018; 46: S30–S33.
14.
BraakHRubUJansen SteurE, et al.Cognitive status correlates with neuropathologic stage in Parkinson disease. Neurology2005; 64: 1404–1410.
15.
SavoiardoM. Differential diagnosis of Parkinson's disease and atypical parkinsonian disorders by magnetic resonance imaging. Neurol Sci2003; 24: s35–s37.
16.
GhaderyCStrafellaAP. New imaging markers for movement disorders. Curr Neurol Neurosci Rep2018; 18: 1–11.
17.
PyatigorskayaNGalleaCGarcia-LorenzoD, et al.A review of the use of magnetic resonance imaging in Parkinson’s disease. Therapeutic advances in neurological disorders2014; 7: 206–220.
18.
BrooksDJ. Morphological and functional imaging studies on the diagnosis and progression of Parkinson’s disease. J Neurol2000; 247: II11–II18.
19.
OsbornA. Toxic, metabolic, degenerative, and CSF disorders. In: Osborn's brain: imaging, pathology, and anatomy. 2nd ed.Elsevier, 2018, p. 1100.
20.
Nagano-SaitoAWashimiYArahataY, et al.Cerebral atrophy and its relation to cognitive impairment in Parkinson disease. Neurology2005; 64: 224–229.
21.
LeeEAChoHIKimSS, et al.Comparison of magnetic resonance imaging in subtypes of multiple system atrophy. Parkinsonism Relat Disorders2004; 10: 363–368.
22.
WenningGKStankovicIVignatelliL, et al.The movement disorder society criteria for the diagnosis of multiple system atrophy. Mov Disord2022; 37: 1131–1148.
23.
LeeW-HLeeC-CShyuW-C, et al.Hyperintense putaminal rim sign is not a hallmark of multiple system atrophy at 3T. Am J Neuroradiol2005; 26: 2238–2242.
24.
GröschelKKastrupALitvanI, et al.Penguins and hummingbirds: midbrain atrophy in progressive supranuclear palsy. Neurology2006; 66: 949–950.
25.
AdachiMKawanamiTOhshimaH, et al.Morning glory sign: a particular MR finding in progressive supranuclear palsy. Magn Reson Med Sci2004; 3: 125–132.
LongoniGAgostaFKostićVS, et al.MRI measurements of brainstem structures in patients with Richardson's syndrome, progressive supranuclear palsy‐parkinsonism, and Parkinson's disease. Mov Disord2011; 26: 247–255.
28.
KoyamaMYagishitaANakataY, et al.Imaging of corticobasal degeneration syndrome. Neuroradiology2007; 49: 905–912.
29.
McKeithIGDicksonDWLoweJ, et al.Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology2005; 65: 1863–1872.
30.
GompertsSN. Lewy body dementias: dementia with Lewy bodies and Parkinson disease dementia. Continuum: Lifelong Learning in Neurology2016; 22: 435–463.
31.
ShimizuSKanetakaHHiraoK, et al.Neuroimaging for diagnosing dementia with Lewy bodies: what is the best neuroimaging technique in discriminating dementia with Lewy bodies from Alzheimer's disease?Geriatr Gerontol Int2017; 17: 819–824.
32.
HeimBKrismerFDe MarziR, et al.Magnetic resonance imaging for the diagnosis of Parkinson’s disease. J Neural Transm2017; 124: 915–964.
VitaliPPanMIPalesiF, et al.Substantia nigra volumetry with 3-T MRI in de novo and advanced Parkinson disease. Radiology2020; 296: 401–410.
35.
VasconcellosLFPereiraJSAdachiM, et al.Volumetric brain analysis as a predictor of a worse cognitive outcome in Parkinson's disease. J Psychiatr Res2018; 102: 254–260.
36.
WhitwellJLHöglingerGUAntoniniA, et al.Radiological biomarkers for diagnosis in PSP: where are we and where do we need to be?Mov Disord2017; 32: 955–971.
37.
MorelliMArabiaGSalsoneM, et al.Accuracy of magnetic resonance parkinsonism index for differentiation of progressive supranuclear palsy from probable or possible Parkinson disease. Mov Disord2011; 26: 527–533.
38.
NigroSArabiaGAntoniniA, et al.Magnetic Resonance Parkinsonism Index: diagnostic accuracy of a fully automated algorithm in comparison with the manual measurement in a large Italian multicentre study in patients with progressive supranuclear palsy. Eur Radiol2017; 27: 2665–2675.
39.
QuattroneAMorelliMNigroS, et al.A new MR imaging index for differentiation of progressive supranuclear palsy-parkinsonism from Parkinson's disease. Parkinsonism Relat Disorders2018; 54: 3–8.
40.
QuattroneAAntoniniAVaillancourtDE, et al.A new MRI measure to early differentiate progressive supranuclear palsy from de novo Parkinson's disease in clinical practice: an international study. Mov Disord2021; 36: 681–689.
41.
ObaHYagishitaATeradaH, et al.New and reliable MRI diagnosis for progressive supranuclear palsy. Neurology2005; 64: 2050–2055.
42.
QuattroneANicolettiGMessinaD, et al.MR imaging index for differentiation of progressive supranuclear palsy from Parkinson disease and the Parkinson variant of multiple system atrophy. Radiology2008; 246: 214–221.
43.
LeeW. Conventional magnetic resonance imaging in the diagnosis of Parkinsonian disorders: a meta‐analysis. Mov Disord Clin Pract2021; 8: 217–223.
44.
TsuboiYSlowinskiJJosephsK, et al.Atrophy of superior cerebellar peduncle in progressive supranuclear palsy. Neurology2003; 60: 1766–1769.
45.
ConstantinidesVCParaskevasGPStamboulisE, et al.Simple linear brainstem MRI measurements in the differential diagnosis of progressive supranuclear palsy from the parkinsonian variant of multiple system atrophy. Neurol Sci2018; 39: 359–364.
46.
NigroSAntoniniAVaillancourtDE, et al.Automated MRI classification in progressive supranuclear palsy: a large international cohort study. Mov Disord2020; 35: 976–983.
47.
StephenCDVangelMGuptaAS, et al.Rates of change of pons and middle cerebellar peduncle diameters are diagnostic of multiple system atrophy of the cerebellar type. Brain Communications2024; 6: fcae019.
48.
NicolettiGFeraFCondinoF, et al.MR imaging of middle cerebellar peduncle width: differentiation of multiple system atrophy from Parkinson disease. Radiology2006; 239: 825–830.
49.
MangesiusSHusslAKrismerF, et al.MR planimetry in neurodegenerative parkinsonism yields high diagnostic accuracy for PSP. Parkinsonism Relat Disorders2018; 46: 47–55.
50.
SchulzJBSkalejMWedekindD, et al.Magnetic resonance imaging–based volumetry differentiates idiopathic Parkinson's syndrome from multiple system atrophy and progressive supranuclear palsy. Ann Neurol: Official Journal of the American Neurological Association and the Child Neurology Society1999; 45: 65–74.
51.
ReginoldWLangAEMarrasC, et al.Longitudinal quantitative MRI in multiple system atrophy and progressive supranuclear palsy. Parkinsonism Relat Disorders2014; 20: 222–225.
52.
DamierPHirschEAgidY, et al.The substantia nigra of the human brain: I. Nigrosomes and the nigral matrix, a compartmental organization based on calbindin D28K immunohistochemistry. Brain1999; 122: 1421–1436.
BlazejewskaAISchwarzSTPitiotA, et al.Visualization of nigrosome 1 and its loss in PD: pathoanatomical correlation and in vivo 7 T MRI. Neurology2013; 81: 534–540.
55.
ChoZHOhSHKimJM, et al.Direct visualization of Parkinson's disease by in vivo human brain imaging using 7.0 T magnetic resonance imaging. Mov Disord2011; 26: 713–718.
56.
LehericySVaillancourtDESeppiK, et al.The role of high‐field magnetic resonance imaging in parkinsonian disorders: pushing the boundaries forward. Mov Disord2017; 32: 510–525.
57.
MahlknechtPKrismerFPoeweW, et al.Meta‐analysis of dorsolateral nigral hyperintensity on magnetic resonance imaging as a marker for Parkinson's disease. Mov Disord2017; 32: 619–623.
58.
XingYNaiduSMartín-BastidaA, et al.Diagnostic value of swallow tail sign at brain MRI in patients with clinically uncertain parkinsonian syndrome. Radiology2025; 316: e240680.
59.
KimJ-MJeongH-JBaeYJ, et al.Loss of substantia nigra hyperintensity on 7 Tesla MRI of Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy. Parkinsonism Relat Disorders2016; 26: 47–54.
60.
BaeYJKimJMKimE, et al.Loss of nigral hyperintensity on 3 Tesla MRI of parkinsonism: comparison with 123I‐FP‐CIT SPECT. Mov Disord2016; 31: 684–692.
61.
ShamsSFällmarDSchwarzS, et al.MRI of the swallow tail sign: a useful marker in the diagnosis of Lewy body dementia?Am J Neuroradiol2017; 38: 1737–1741.
62.
LeeHBaekS-YChunSY, et al.Specific visualization of neuromelanin-iron complex and ferric iron in the human post-mortem substantia nigra using MR relaxometry at 7T. Neuroimage2018; 172: 874–885.
63.
BrammerlohMMorawskiMFriedrichI, et al.Measuring the iron content of dopaminergic neurons in substantia nigra with MRI relaxometry. Neuroimage2021; 239: 118255.
64.
BrammerlohMKirilinaEAlkemadeA, et al.Swallow tail sign: revisited. Radiology2022; 305: 674–677.
65.
HaradaTKudoKFujimaN, et al.Quantitative susceptibility mapping: basic methods and clinical applications. Radiographics2022; 42: 1161–1176.
66.
LiuZZhangYWangH, et al.Altered cerebral perfusion and microstructure in advanced Parkinson's disease and their associations with clinical features. Neurol Res2022; 44: 47–56.
67.
HaackeEMLiuSBuchS, et al.Quantitative susceptibility mapping: current status and future directions. Magn Reson Imaging2015; 33: 1–25.
68.
DeistungASchweserFReichenbachJR. Overview of quantitative susceptibility mapping. NMR Biomed2017; 30: e3569.
69.
LangkammerCPirpamerLSeilerS, et al.Quantitative susceptibility mapping in Parkinson's disease. PLoS One2016; 11: e0162460.
70.
KimEYSungYHShinH-G, et al.Diagnosis of early-stage idiopathic Parkinson'S disease using high-resolution quantitative susceptibility mapping combined with histogram analysis in the substantia nigra at 3 T. J Clin Neurol2018; 14: 90–97.
71.
GuanXXuanMGuQ, et al.Regionally progressive accumulation of iron in Parkinson's disease as measured by quantitative susceptibility mapping. NMR Biomed2017; 30: e3489.
72.
SjöströmHGranbergTWestmanE, et al.Quantitative susceptibility mapping differentiates between parkinsonian disorders. Parkinsonism Relat Disorders2017; 44: 51–57.
73.
HanY-HLeeJ-HKangB-M, et al.Topographical differences of brain iron deposition between progressive supranuclear palsy and parkinsonian variant multiple system atrophy. J Neurol Sci2013; 325: 29–35.
74.
AzumaMHiraiTYamadaK, 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 Neuroradiol2016; 37: 782–788.
75.
CassidyCMZuccaFAGirgisRR, et al.Neuromelanin-sensitive MRI as a noninvasive proxy measure of dopamine function in the human brain. Proc Natl Acad Sci2019; 116: 5108–5117.
76.
ZhangWPhillipsKWielgusAR, et al.Neuromelanin activates microglia and induces degeneration of dopaminergic neurons: implications for progression of Parkinson’s disease. Neurotox Res2011; 19: 63–72.
77.
TrujilloPAumannMAClaassenDO. Neuromelanin-sensitive MRI as a promising biomarker of catecholamine function. Brain2024; 147: 337–351.
78.
PriovoulosNvan BoxelSCJacobsHI, et al.Unraveling the contributions to the neuromelanin-MRI contrast. Brain Struct Funct2020; 225: 2757–2774.
79.
PaveseNTaiYF. Nigrosome imaging and neuromelanin sensitive MRI in diagnostic evaluation of Parkinsonism. Mov Disord Clin Pract2018; 5: 131–140.
80.
Martin-BastidaAPietracupaSPicciniP. Neuromelanin in parkinsonian disorders: an update. Int J Neurosci2017; 127: 1116–1123.
81.
LehéricySSharmanMASantosCLD, et al.Magnetic resonance imaging of the substantia nigra in Parkinson's disease. Mov Disord2012; 27: 822–830.
82.
OgisuKKudoKSasakiM, et al.3D neuromelanin-sensitive magnetic resonance imaging with semi-automated volume measurement of the substantia nigra pars compacta for diagnosis of Parkinson’s disease. Neuroradiology2013; 55: 719–724.
83.
KashiharaKShinyaTHigakiF. Neuromelanin magnetic resonance imaging of nigral volume loss in patients with Parkinson’s disease. J Clin Neurosci2011; 18: 1093–1096.
84.
BiondettiEGauravRYahia-CherifL, et al.Spatiotemporal changes in substantia nigra neuromelanin content in Parkinson’s disease. Brain2020; 143: 2757–2770.
85.
OhtsukaCSasakiMKonnoK, et al.Differentiation of early-stage parkinsonisms using neuromelanin-sensitive magnetic resonance imaging. Parkinsonism Relat Disorders2014; 20: 755–760.
86.
KitaoSMatsusueEFujiiS, et al.Correlation between pathology and neuromelanin MR imaging in Parkinson’s disease and dementia with Lewy bodies. Neuroradiology2013; 55: 947–953.
87.
HeNChenYLeWittPA, et al.Application of neuromelanin MR imaging in Parkinson disease. J Magn Reson Imag2023; 57: 337–352.
88.
ZhangYBurockMA. Diffusion tensor imaging in Parkinson's disease and parkinsonian syndrome: a systematic review. Front Neurol2020; 11: 531993.
89.
BasserPJJonesDK. Diffusion‐tensor MRI: theory, experimental design and data analysis–a technical review. NMR Biomed: An International Journal Devoted to the Development and Application of Magnetic Resonance In Vivo2002; 15: 456–467.
90.
VaillancourtDSprakerMProdoehlJ, et al.High-resolution diffusion tensor imaging in the substantia nigra of de novo Parkinson disease. Neurology2009; 72: 1378–1384.
91.
DuGLewisMMStynerM, et al.Combined R2* and diffusion tensor imaging changes in the substantia nigra in Parkinson's disease. Mov Disord2011; 26: 1627–1632.
92.
TanW-QYeohC-SRumpelH, et al.Deterministic tractography of the nigrostriatal-nigropallidal pathway in Parkinson’s disease. Sci Rep2015; 5: 17283.
93.
ProdoehlJLiHPlanettaPJ, et al.Diffusion tensor imaging of Parkinson's disease, atypical parkinsonism, and essential tremor. Mov Disord2013; 28: 1816–1822.
94.
BlainCBarkerGJaroszJ, et al.Measuring brain stem and cerebellar damage in parkinsonian syndromes using diffusion tensor MRI. Neurology2006; 67: 2199–2205.
95.
PyatigorskayaNYahia‐CherifLGauravR, et al.Multimodal magnetic resonance imaging quantification of brain changes in progressive supranuclear palsy. Mov Disord2020; 35: 161–170.
96.
SamsonENoseworthyMD. A review of diagnostic imaging approaches to assessing Parkinson's disease. Brain Disorders2022; 6: 100037.
97.
MercerMKRevelsJWBlacklockLC, et al.Practical overview of 123I-Ioflupane imaging in Parkinsonian syndromes. Radiographics2024; 44: e230133.
98.
MirpourSTurkbeyEBMarashdehW, et al.Impact of DAT-SPECT on management of patients suspected of parkinsonism. Clin Nucl Med2018; 43: 710–714.
99.
MorganSKempPBooijJ, et al.Differentiation of frontotemporal dementia from dementia with Lewy bodies using FP-CIT SPECT. J Neurol Neurosurg Psychiatr2012; 83: 1063–1070.
100.
AkdemirÜÖHatBAtayLÖ. Dopamine transporter spect imaging in Parkinson's disease and parkinsoniandisorders. Turk J Med Sci2021; 51: 400–410.
101.
MeyerPTFringsLRückerG, et al.18F-FDG PET in parkinsonism: differential diagnosis and evaluation of cognitive impairment. J Nucl Med2017; 58: 1888–1898.
102.
TripathiMDhawanVPengS, et al.Differential diagnosis of parkinsonian syndromes using F-18 fluorodeoxyglucose positron emission tomography. Neuroradiology2013; 55: 483–492.
103.
BrownRKBohnenNIWongKK, et al.Brain PET in suspected dementia: patterns of altered FDG metabolism. Radiographics2014; 34: 684–701.
104.
WalkerZGandolfoFOriniS, et al.Clinical utility of FDG PET in Parkinson’s disease and atypical parkinsonism associated with dementia. Eur J Nucl Med Mol Imag2018; 45: 1534–1545.
105.
ShangSLiDTianY, et al.Hybrid PET-MRI for early detection of dopaminergic dysfunction and microstructural degradation involved in Parkinson’s disease. Commun Biol2021; 4(1): 1162.
106.
DepierreuxFParmentierEMackelsL, et al.Parkinson’s disease multimodal imaging: F-DOPA PET, neuromelanin-sensitive and quantitative iron-sensitive MRI. Npj Parkinson's Disease2021; 7: 57.
107.
HuXSunXHuF, et al.Multivariate radiomics models based on 18F-FDG hybrid PET/MRI for distinguishing between Parkinson’s disease and multiple system atrophy. Eur J Nucl Med Mol Imag2021; 48: 3469–3481.
108.
SmithRCapotostiFSchainM, et al.The α-synuclein PET tracer [18F] ACI-12589 distinguishes multiple system atrophy from other neurodegenerative diseases. Nat Commun 14: 6750 1. Shahnawaz M et al (2020) Discriminating α-synuclein strains in Parkinson’s disease and multiple system atrophy. Nature2023; 578: 273–277.
109.
LiCHuiDWuF, et al.Automatic diagnosis of Parkinson’s disease using artificial intelligence base on routine T1-weighted MRI. Front Med2024; 10: 1303501.
110.
ShinDHHeoHSongS, et al.Automated assessment of the substantia nigra on susceptibility map-weighted imaging using deep convolutional neural networks for diagnosis of Idiopathic Parkinson's disease. Parkinsonism Relat Disorders2021; 85: 84–90.
111.
WangCHeNZhangY, et al.Enhancing Nigrosome‐1 sign identification via interpretable AI using true susceptibility weighted imaging. J Magn Reson Imag2024; 60: 1904–1915.
112.
BaeYJChoiBSKimJ-M, et al.Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake. Neuroradiology2023; 65: 1101–1109.
113.
WuPZhaoYWuJ, et al.Differential diagnosis of parkinsonism based on deep metabolic imaging indices. J Nucl Med2022; 63: 1741–1747.
114.
QuattroneAZappiaMQuattroneA. Simple biomarkers to distinguish Parkinson’s disease from its mimics in clinical practice: a comprehensive review and future directions. Front Neurol2024; 15: 1460576.
RymanSGPostonKL. MRI biomarkers of motor and non-motor symptoms in Parkinson's disease. Parkinsonism Relat Disorders2020; 73: 85–93.
117.
BiswasDBanerjeeRSarkarS, et al.Nigrosome and neuromelanin imaging as tools to differentiate Parkinson's Disease and parkinsonism. Ann Indian Acad Neurol2022; 25: 1029–1035.
118.
WangLZhangQLiH, et al.SPECT molecular imaging in Parkinson′ s disease. BioMed Res Int2012; 2012: 412486.
119.
CaravellaCPalestroCTomasM, et al.Is SPECT/CT beneficial to the interpretation of DaT scans?Society of Nuclear Medicine2022.
