Secondary Logo

Neuroimaging advances in Parkinson's disease

Rispoli, Vittorioa,b,*; Schreglmann, Sebastian R.a,*; Bhatia, Kailash P.a

Erratum

In the conflicts of interest of this article [1] , the statement for Sebastian R. Schreglmann (SRS) was incomplete. The complete statement for SRS should read, “SRS has received grant support by the Swiss Science Foundation, the Swiss Neurological Society, the European Academy of Neurology and EU Horizon 2020.”

Current Opinion in Neurology. 31(6):760, December 2018.

doi: 10.1097/WCO.0000000000000584
NEUROIMAGING: Edited by Massimo Filippi
Free
Erratum

Purpose of review Neuroimaging in Parkinson's disease is an evolving field, providing in-vivo insights into the structural and biochemical changes of the condition, although its diagnosis remains clinical. Here, we aim to summarize the most relevant recent advances in neuroimaging in Parkinson's disease to assess the underlying disease process, identify a biomarker of disease progression and guide or monitor therapeutic interventions.

Recent findings The clinical applications of imaging technology increasingly allow to quantify pigments (iron, neuromelanin) on MRI, proteins (tau), cell markers (phosphodiesterases, microglia) and neurotransmitter receptors (dopamine, serotonin, noradrenalin, cholin) via PET protocols, activity maps by resting-state and task-dependent functional MRI, as well as microstructural changes (free water) through diffusion-based assessments. Their application provides increasing insight on the temporal and spatial dynamics of dopaminergic and other neurotransmitter systems as well as anatomical structures and circuits in Parkinson's disease. An expanding list of PET tracers increases the yield of functional studies.

Summary This review summarizes the most recent, relevant advances in neuroimaging technology in Parkinson's disease. In particular, the combination of different imaging techniques seems promising to maximize the scope of future work, which should, among others, aim at identifying the best imaging marker of disease progression.

aSobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, UCL, London, UK

bDepartment of Neuroscience, University Hospital Arcispedale S. Anna, Ferrara, Italy

Correspondence to Kailash P. Bhatia, MD, FRCP, Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, UCL, 33 Queen Square, London WC1N 3BG, UK. Tel: +44 20 3448 4229; fax: +44 20 7676 2175; e-mail: k.bhatia@ucl.ac.uk

Back to Top | Article Outline

INTRODUCTION

Parkinson's disease is the second most common neurodegenerative disorder after Alzheimer‘s dementia [1,2]. Initially perceived as a condition affecting the motor system by α-synuclein-mediated loss of dopaminergic neurons in the substantia nigra [1], current knowledge about associated cognitive, neuropsychiatric and nonmotor symptoms has led to increased interest in cholinergic, serotoninergic, noradrenergic and other neurotransmitter systems [3,4]. For some time, advanced neuroimaging has been an invaluable tool to investigate in-vivo changes in Parkinson's disease [5]. But although voxel-based morphometry MRI has previously detected volume changes in cortical and subcortical areas [6], state of the art neuroimaging nowadays provides a window into the (micro-) structure and function of neuronal networks and surrounding glia [7,8▪].

The aim of this review therefore is to summarize the most relevant recent developments in both structural and functional neuroimaging in Parkinson's disease pertaining to certain aspects: the detection of underpinning neurobiological processes, the use of different neuroimaging techniques as biomarkers of disease progression and the application of imaging to guide and monitor therapeutic interventions.

Box 1

Box 1

Back to Top | Article Outline

DETECTION OF UNDERLYING NEUROBIOLOGICAL PROCESSES

Neuroimaging continues to be a powerful tool for the in-vivo study of disease-related pathophysiology and recent developments in Parkinson's disease corroborate this.

Back to Top | Article Outline

Neurotransmitter systems

It has been apparent for some time that the degeneration of neurons in Parkinson's disease is not limited to the Substantia nigra, but only recent developments of respective tracers allow the detailed in-vivo study of additional neurotransmitter systems (see Table 1).

Table 1

Table 1

Back to Top | Article Outline

Dopaminergic system

Although quantification of presynaptic dopaminergic function is part of daily clinical practice [9], the exact anatomical pattern and longitudinal dynamics of signal changes are increasingly described: a substantial meta-analysis of 142 studies using PET or single photon emission computed tomography (SPECT) to assess presynaptic dopaminergic function confirmed consistently larger decreases in binding in posterior > anterior putamen > caudate nucleus across ligands for aromatic L-amino-acid decarboxylase (AADC), dopamine transporter (DaT) and vesicular monoamine transporter 2 (VMAT2); overall, disease severity correlated closest with dopaminergic terminal loss in the caudate nucleus [10▪▪,11]. Focusing on the physiological equivalent of SPECT signalling, a large study reported postmortem numbers of nigral neurons in Parkinson's disease and atypical parkinsonian conditions not to correlate with [123I]FP-CIT or [123I]b-CIT tracer binding [12▪], which contrasts with previous observations [13]. This suggests that these tracers actually reflect striatal changes such as axonal dysfunction or reduced DaT expression, rather than the number of intact nigral neurons.

Similarly, the dynamics of changes among tracer targets are increasingly studied: a substantial meta-analysis reported a consistently smaller reduction in 6-[18F]fluoro-L-dopa measuring AADC in both caudate nucleus and putamen compared with DaT and VMAT2 levels, suggesting either less severe loss or even compensatory upregulation of AADC in Parkinson's disease [10▪▪]. An analysis of a large number (n = 210) of healthy control DaTSCANs indicated a relatively higher DaT concentration in women, as female striatal volumes are slightly lower, but DaT quantification similar between sexes [14].

Nigro-striatal dopaminergic loss, as quantified by DaT, has also been used to study pathophysiological changes only accessible to advanced imaging techniques by means of correlation analysis: one study on the basis of diffusion tensor imaging (DTI) reported a negative correlation between fractional anisotropy of the substantia nigra and putaminal dopamine transporter signal over time [15▪], while another cross-sectional study described that on neuromelanin-sensitive sequences, substantia nigra volume correlated best with nigro-striatal innervation loss [16]. Both studies detected microstructural changes based on correlations with established DaT quantification. Similarly, the severity of dopaminergic degeneration correlated with changes in diffusion measurements in the striatum in a primate MPTP model [17].

Today, the in-vivo study of dopaminergic degeneration is able to detect the temporal and spatial dynamics of tracer changes and serves as a basis for the explorative study of novel imaging approaches.

Back to Top | Article Outline

Serotoninergic system

Although serotoninergic dysfunction is known to occur in Parkinson's disease, in-vivo quantification has been achieved only recently. [123I]FP-CIT exhibits nonspecific, extrastriatal binding for presynaptic serotonergic transporters [18,19▪] and hence has been used to assess its involvement in the pathogenesis of nonmotor symptoms. One study found significant differences in hypothalamic binding between Parkinson's disease and atypical parkinsonism, suggesting a different pattern of serotonergic presynaptic receptor involvement between these conditions [20]. More specifically, the same team reported a negative association of levels of anxiety with low [123I]FP-CIT binding in the thalamus in a large sample of de-novo Parkinson's disease patients [19▪]. A similar negative correlation between right caudate nucleus [123I]FP-CIT SPECT tracer binding and anxiety has been reported in a large, controlled cohort of de-novo Parkinson's disease patients [21], confirming an earlier observation [22].

Although the above-mentioned results are in line with the hypothesis of anxiety mainly being linked to a serotoninergic dysfunction in earlier and a dopaminergic dysfunction in later disease stages [20], this remains to be proven in larger, and ideally longitudinal samples.

Back to Top | Article Outline

Noradrenergic system

Noradrenergic projections almost exclusively originate from the locus coeruleus, playing a role in cognitive attention, sleep cycle regulation and autonomic function. The application of neuromelanin-sensitive MRI sequences to identify pigmented cells of the locus coeruleus [23▪] and [11C]MeNER PET to characterize noradrenalin transporters [24] allowed a study comparing Parkinson's disease patients with and without rapid eye movement sleep behaviour disorder (RBD) and controls, revealing most pronounced reductions for both signals in the PD+RBD group [23▪], supporting an earlier neuromelanin-based study [25] (see Fig. 1). In terms of dynamics, first evidence indicates that the reduction in neuromelanin-content might be greater in the locus coeruleus than substantia nigra [16], possibly reflecting the progression of neuropathology according to the Braak hypothesis [26]. Although of minuscule anatomical size, the noradrenergic system and the implications of changes to it, is now accessible to state-of the art imaging.

FIGURE 1

FIGURE 1

Back to Top | Article Outline

Cholinergic system

There has been a debate over the anatomical and functional cause of cognitive symptoms in Parkinson's disease, which present most frequently as executive, and in later stages more widespread dysfunction including memory impairment [27]. A noticeable PET-based contribution is the finding that it might be the interaction between caudate nucleus dopaminergic and cortical cholinergic denervation to explain Parkinson's disease cognitive decline and dementia [28,29]. The data seem to suggest a possible compensatory overactivity of the cortical cholinergic system for caudate nucleus dopaminergic degeneration in early disease stages, before cognitive symptoms become apparent with cholinergic decline. This challenges the previously proposed dual syndrome hypothesis, which distinguishes dopaminergically mediated fronto-striatal executive impairments and cholinergically mediated memory symptoms [27].

Back to Top | Article Outline

Protein aggregates

Parkinson's disease neuropathology is dominated by the presence of α-synuclein deposits, although β-amyloid and tau have been implicated in cognitive impairment in Parkinson's disease [30,31▪]. Recent publications seem to support a role for both tau and β-amyloid only in advanced stages of cognitive impairment [30,31▪,32], most noticeably in dementia with lewy bodies [30]. Anatomically, precuneus and inferior temporal gyrus tau tracer uptake has been reported to be associated with this [33], adding to our understanding of mixed pathology in Parkinson's disease.

Back to Top | Article Outline

White matter involvement

Overt white matter lesions have been implicated with the development of both cognitive symptoms and gait disorder in Parkinson's disease. The reported observation of an association between white matter lesions and neurogenic orthostatic hypotension [34] supports the notion that extreme blood pressure changes might contribute to the development of cognitive symptoms through white matter lesions [35]. Small vessel involvement, defined as lacunes or white matter hyperintensities, have equally been linked to cortical thinning and cognitive impairment [36]. Overall, greater white matter lesion load is reported among patients presenting with postural instability and gait difficulty compared with a tremor-dominant phenotype [37,38].

Computational and theoretical advances allow for a more comprehensive assessment of microstructural changes and network disruptions: a meta-analysis of 39 DTI studies comparing data from 1087 PD patients and 768 healthy controls identified consistent changes within subcortical (substantia nigra) and cortical areas (cingulate and temporal cortices) as well as white matter fibre tracts (corpus callosum and corticospinal tract) [39]. In a cohort of treatment-naive patients, prospective high-resolution 3-Tesla DTI imaging and graph theory detected reduced connectivity in mesolimbic–striatal pathways, within the basal ganglia, the sensorimotor circuits and also the limbic system [40]. Another study suggested more prominent white matter lesions along the cerebello-thalamo-cortical pathway in tremor-dominant Parkinson's disease patients [41]. A large study of advanced Parkinson's disease patients also identified DTI changes in diffuse basal ganglia and fronto-parietal networks among Parkinson's disease patients with mild cognitive impairment [42]. Taken together, these findings point towards early, progressive and widespread damage to white matter connections, initially evident only at a microstructural level [43].

Back to Top | Article Outline

Neuroinflammation

A number of findings suggest a role of the immune system in Parkinson's disease pathoaetiology [1]. Activation of microglia may be evaluated through novel PET radioligands, such as [18F]FEPPA, although first, moderately sized studies in Parkinson's disease were not able to show signal differences in comparison to healthy controls [44,45]. [11C]PBR28 imaging, however, revealed a reduction in microglia activation after treatment with a selective myeloperoxidase inhibitor in Parkinson's disease, although this study included no controls for comparison [46]. Indirect indications of inflammation have also been detected by signs of blood– brain barrier breakdown, evident as microbleeds and gadolinium leakage [47].

Back to Top | Article Outline

Phosphodiesterases

Phosphodiesterases are enzymes highly expressed on striatal medium spiny neurons, metabolizing cAMP and cGMP, the second messengers of dopamine receptors. First studies employing specific radioligands, such as [11C]IMA107 binding to phosphodiesterase 10A [48], showed lower binding activity in the basal ganglia of Parkinson's disease patients compared with controls, and a negative correlation with disease duration and severity [49]. The same group adopted [11C]rolipram, assessing phosphodiesterase 4 levels, and reported lower binding in caudate, putamen, hypothalamus and cortex to correlate with spatial working memory deterioration [50▪▪]. Positing phosphodiesterase expression as a marker of striatal dopaminergic terminal loss, it would be interesting to study its decline longitudinally and compare its dynamics with DaT and other markers of dopaminergic degeneration in the future.

Back to Top | Article Outline

Functional MRI

The application of functional MRI (fMRI) studies in Parkinson's disease is still an evolving field, with a considerable heterogeneity of paradigms and patient subgroups being studied. Nevertheless, a methodologically sound, recent meta-analysis of resting state fMRI studies indicated reproducible, increased functional connectivity in the left postcentral gyrus [51]. Although this might highlight this area to be explored further, the conclusive interpretation of results of task-dependent fMRI studies [52] remains challenging, still.

Back to Top | Article Outline

IMAGING MODALITIES AS A BIOMARKER OF DISEASE PROGRESSION

Monitoring disease progression is a prime aim in Parkinson's disease imaging research, but although there have been some developments, it remains to be seen which modality might emerge as the most suitable measure.

Back to Top | Article Outline

Iron-content

Brain tissue physiologically contains iron, more than 90% of which is stored in the form of ferritin, and the basal ganglia (Globus Pallidus > Putamen > Caudate) are particularly rich in iron. Imaging studies have shown that ferritin accumulates throughout the basal ganglia in a linear fashion as a function of age [53]. Iron-sensitive MRI sequences, including SWI, 3D FLAIR, T2*, R2 and R2* relaxation, as well as quantitative susceptibility mapping (QSM) or adiabatic T1rho have been increasingly applied to study iron-content and iron metabolism in Parkinson's disease [54]. Overall, QSM has been suggested to be more sensitive than R2* to detect deep cerebral nuclei iron quantity [54,55], allowing the visualization of the dorsolateral nigral hyperintesity or nigrosome-1 within the substantia nigra. A meta-analysis of 16 studies suggested this assessment to be the most sensitive and specific imaging protocol to date to differentiate Parkinson's disease patients from controls and possibly suitable to differentiate degenerative from nondegenerative parkinsonism [56▪]. Nigral hyperintensity has also been correlated with disease progression and not only reported to predict DaTSCAN measures in Parkinson's disease [57,58] but also idiopathic RBD [59].

Disease severity, as measured by clinical characteristics ranging from UPDRS-III, H&Y stage, depression and anxiety to levodopa equivalent daily dose, has been reported to correlate with iron load in Parkinson's disease on SWI [60▪], R2* sequences [61] and QSM [54,62]. Iron load, especially in the caudal region of the substantia nigra (R2*), has been reported to be particularly higher in patients with freezing of gait in both cross-sectional [55] and longitudinal samples [61]. Taken together, as an epiphenomenon of the underpinning neuropathological process, iron accumulation seems to be a good candidate to follow disease progression in Parkinson's disease.

Regarding extranigral tissue in Parkinson's disease in comparison to controls, iron load was found increased in GP and putamen on SWI-weighted sequences [60▪], and red nucleus, GP and thalamus on QSM quantification [54]. A QSM-based study described iron signal changes only in SNc in early disease stages, whereas more prominent involvement of red nucleus and GP were apparent in more advanced patients [63]. Only one study reported whole brain iron level assessments; using a cross-sectional protocol, it reported higher QSM values in dorsal pons and a number of cortical areas, arguably following the topographical progression of α-synuclein deposition [64].

Iron content therefore seems to emerge as a powerful imaging tool with high diagnostic accuracy (nigral hyperintensity), good correlation with clinical characteristics and good spatial as well as longitudinal temporal resolution.

Back to Top | Article Outline

Neuromelanin

Neuromelanin is an insoluble pigment and by-product of catecholamine-synthesis. Its production is Fe3+-mediated and appears to be governed by cytosolic content of dopamine or other catecholamines and is therefore predominantly located in substantia nigra and locus coeruleus. Quantification of neuromelanin to follow disease progression has been investigated widely. The histologically known pattern of substantia nigra neuronal changes affecting postero-lateral aspects of SNc earlier/more than anterior-medial ones has been replicated with neuromelanin imaging [65–67]. Similarly, the progressive loss of SWI-hyperintensity from nigrosome-1 to nigrosome-4 seems to follow disease progression [68]. Neuromelanin loss has also been correlated with UPDRS [65,66] and MDS-UPDRS scores [67], H&Y stages [67] and disease duration [69].

Hence, neuromelanin appears to be a promising imaging biomarker for Parkinson's disease progression, if confirmed prospectively.

Back to Top | Article Outline

Substantia nigra free water

Free water measurements are an advanced diffusion-based modelling approach, measuring the fractional volume of unconstrained diffusion. The recent development of a bitensor modelling technique allows to acquire the fractional signal of water from a single voxel. The detection of posterior substantia nigra free water was able to distinguish Parkinson's disease patients from controls [70,71▪▪] and in a multisite study showed to correlate with H&Y stages, MDS-UPDRS part III and cognitive performance [72]. This appeared to be independent of acute dopaminergic medication [73]. First longitudinal data indicated that posterior substantia nigra free water increases over time and can predict bradykinesia severity and MOCA scores [74], which was validated in a larger, international study [71▪▪] (see Fig. 2). By and large, all of the above suggest that substantia nigra free water might become a valuable tool to monitor Parkinson's disease progression.

FIGURE 2

FIGURE 2

Back to Top | Article Outline

DaTSCAN

It is generally accepted that DaT measurements correlate with the degree of dopaminergic cell loss; however, its exact dynamics across disease stages has not been clear. A recent study implied different velocities of midbrain neuromelanin-signal loss measured via [18F]AV-1451 PET [75▪], versus striatal dopaminergic loss ([123I]FP-CIT SPECT) in early Parkinson's disease [76]. Together with further evidence [77▪], this has been interpreted to indicate that in humans nigral cell loss and striatal tracer uptake in vivo correlate closely only up to a nigral cell loss of 50%. Beyond this, the dynamics of neurodegeneration and tracer uptake seem to follow a more lose correlation, as also observed in MPTP-treated monkeys [78]. Accordingly, the majority of longitudinal PET studies [10▪▪] point to a negative exponential dopaminergic loss in Parkinson's disease, consistent with the nonlinear pattern previously described for the progression of motor symptoms, with faster progression in the first symptomatic disease phase [10▪▪]. This is in keeping with the ‘dying back’ concept, describing axonal and terminal degeneration in the striatum before neuronal cell loss in substantia nigra [79].

Back to Top | Article Outline

GUIDING AND MONITORING THERAPEUTIC INTERVENTIONS

We have noted some developments in the application of imaging used for therapeutic interventions in Parkinson's disease.

Back to Top | Article Outline

Functional neurosurgery

Both deep brain stimulating and advanced lesioning [80] rely on the correct presurgical identification of target structures. One report proposed STN visualization to benefit from using QSM over T2*-weighted images [81] (see Fig. 3). Similarly, advanced high angular resolution diffusion-based imaging has been proposed to improve VIM nucleus targeting in tremor patients [82▪]. Probably, the most innovative addition to functional stereotactic neurosurgery has been the development of the publicly available ‘DBS Intrinsic Template Atlas’ [83▪▪] – this combination of subcortical brain manual segmentation, automatic multimodal probabilistic maps, coregistration with histology as well as STN and GP internus functional subsegmentation according to structural connectivity, offers potential advantages for future functional neurosurgical trials [83▪▪].

FIGURE 3

FIGURE 3

Another set of studies investigated the effect of both anatomical and functional connectivity after STN-DBS and validated the findings in a second, independent data set [84▪▪]: apart from replicating that STN-DBS has an effect on supplementary motor area and medial prefrontal cortex activity, authors reported that both types of connectivity explained 26.2% of clinical variance in intervention outcome. They concluded that their findings support the idea of focusing surgical treatment not only on specific brain regions but also on network nodes [84▪▪].

Finally, of more practical relevance, the development of a new coil system able to reduce DBS lead absorption might alleviate safety concerns for post-DBS MRI monitoring [85].

Back to Top | Article Outline

Levodopa/carbidopa intestinal gel

Continuous delivery of levodopa via levodopa/carbidopa intestinal gel (LCIG) provides more stable levodopa levels in blood with respective clinical advantages over pulsatile oral intake, which is advantageous in advanced Parkinson's disease cases. A small pilot study documented a sustained significant reduction in striatal [11C]raclopride binding, suggesting sustained higher dopamine levels during LCIG infusion [86].

Back to Top | Article Outline

Apomorphine

One study examined the effect of apomorphine infusions as add-on therapy using resting state PET over a 6-month period: induced changes in this relatively small sample (n = 12) were documented throughout motor, cognitive and limbic networks and appear compatible with the notion that metabolic changes in Parkinson's disease could be reversed by continuous dopaminergic treatment [87].

Back to Top | Article Outline

Rehabilitation

A randomized trial of cognitive rehabilitative approaches documented improved executive function, visual memory and functional but no structural changes on functional MRI after 3 months of integrative cognitive rehabilitation [88▪], persisting at 18 months [89].

Back to Top | Article Outline

Summary

In this review, we provide an update on current applications of state-of-the-art neuroimaging in Parkinson's disease. The expansion of the current in-vivo imaging armamentarium increasingly allows the comparison and cross-validation of different imaging modalities. It seems that the increasing number of radionuclide-based protocols assessing microglia activation, protein accumulation and receptor density as well as the combination of established and novel approaches drive developments in this field of movement disorder research. Providing distinct and complementary information, in particular the combination of these techniques will most likely advance our understanding of the pathophysiology of Parkinson's disease processes in the future. Among others, future work should focus on identifying the ideal marker to monitor disease progression.

Back to Top | Article Outline

Acknowledgements

None.

Back to Top | Article Outline

Financial support and sponsorship

This work has received no dedicated support.

Back to Top | Article Outline

Conflicts of interest

VR declares received travel grants from AbbVie, Boston Scientific and Italian Neurological Society. SRS has received grant support by the Swiss Science Foundation, the Swiss Neurological Society and the European Academy of Neurology. KPB has received grant support from welcome/MRC, NIHR, Parkinson's UK and EU horizon 2020. He has received royalties from publication of the Oxford Specialist Handbook Parkinson's Disease and Other Movement Disorders (Oxford University Press, 2008, 2016) and of Marsden's Book of Movement Disorders (Oxford University Press, 2013). He has received honoraria/personal compensation for participating as consultant/scientific board member from Ipsen, Allergan, Merz and honoraria for speaking at meetings and from Allergan, Ipsen, Merz, Sun Pharma, Teva, UCB Pharmaceuticals and from the American Academy of Neurology and movement disorders society.

Back to Top | Article Outline

REFERENCES AND RECOMMENDED READING

Papers of particular interest, published within the annual period of review, have been highlighted as:

  • ▪ of special interest
  • ▪▪ of outstanding interest
Back to Top | Article Outline

REFERENCES

1. Poewe W, Seppi K, Tanner CM, et al. Parkinson disease. Nat Rev Dis Prim 2017; 3:17013.
2. Hirtz D, Thurman DJ, Gwinn-Hardy K, et al. How common are the ‘common’ neurologic disorders? Neurology 2007; 68:326–337.
3. Titova N, Padmakumar C, Lewis SJG, Chaudhuri KR. Parkinson's: a syndrome rather than a disease? J Neural Transm 2017; 124:907–914.
4. Titova N, Qamar MA, Chaudhuri KR. Biomarkers of Parkinson's disease: an introduction. Int Rev Neurobiol 2017; 132:183–196.
5. Politis M. Neuroimaging in Parkinson disease: from research setting to clinical practice. Nat Rev Neurol 2014; 10:708–722.
6. Jia X, Liang P, Li Y, et al. Longitudinal study of gray matter changes in Parkinson disease. Am J Neuroradiol 2015; 36:2219–2226.
7. Saeed U, Compagnone J, Aviv RI, et al. Imaging biomarkers in Parkinson's disease and Parkinsonian syndromes: current and emerging concepts. Transl Neurodegener 2017; 6:8.
8▪. Strafella AP, Bohnen NI, Perlmutter JS, et al. Molecular imaging to track Parkinson's disease and atypical parkinsonisms: new imaging frontiers. Mov Disord 2017; 32:181–192.

It is an outstanding clear review on molecular imaging, especially focused on cognitive impairment and psychiatric complications in Parkinson's disease.

9. Kagi G, Bhatia KP, Tolosa E. The role of DAT-SPECT in movement disorders. J Neurol Neurosurg Psychiatry 2010; 81:5–12.
10▪▪. Kaasinen V, Vahlberg T. Striatal dopamine in Parkinson disease: a meta-analysis of imaging studies. Ann Neurol 2017; 82:873–882.

This is the first comprehensive meta-analysis on PET and SPECT studies analysing the dopaminergic denervation in Parkinson's disease. Importanly, it pointed out an exponenatial loss of nigral dopaminergic projections and the relation across AADC, VMAT2 and DAT tracer related findings.

11. Prashanth R, Dutta Roy S, Mandal PK, Ghosh S. High-accuracy classification of Parkinson's disease through shape analysis and surface fitting in 123I-Ioflupane SPECT imaging. IEEE J Biomed Heal Informatics 2017; 21:794–802.
12▪. Saari L, Kivinen K, Gardberg M, et al. Dopamine transporter imaging does not predict the number of nigral neurons in Parkinson disease. Neurology 2017; 88:1461–1467.

Despite the larger employment of SPECT to assess the presence of DaT degeneration, it is not clear whether the results of this test reflect neuropathological correlates of Parkinson's disease. This is the sole study to address this question in a small sample of Parkinson's disease patients.

13. Kraemmer J, Kovacs GG, Perju-Dumbrava L, et al. Correlation of striatal dopamine transporter imaging with post mortem substantia nigra cell counts. Mov Disord 2014; 29:1767–1773.
14. Tagare HD, DeLorenzo C, Chelikani S, et al. Voxel-based logistic analysis of PPMI control and Parkinson's disease DaTscans. Neuroimage 2017; 152:299–311.
15▪. Zhang Y, Wu I-W, Tosun D, et al. Progression of regional microstructural degeneration in Parkinson's disease: a multicenter diffusion tensor imaging study. PLoS One 2016; 11:e0165540.

This article described the substantia nigra microstructural alterations on a large cohort of Parkinson's disease patients and controls from the PPMI database. Apart from the DTI change annual rate, the authors correlated for the first time this parameter to DaTs, as measured by [123I]FP-CIT, and to CSF concentration of α-synuclein and tau protein.

16. Isaias IU, Trujillo P, Summers P, et al. Neuromelanin imaging and dopaminergic loss in Parkinson's disease. Front Aging Neurosci 2016; 8:1–12.
17. Météreau E, Beaudoin-Gobert M, Duperrier S, et al. Diffusion tensor imaging marks dopaminergic and serotonergic lesions in the Parkinsonian monkey. Mov Disord 2018; 33:298–309.
18. Jaakkola E, Joutsa J, Mäkinen E, et al. Ventral striatal dopaminergic defect is associated with hallucinations in Parkinson's disease. Eur J Neurol 2017; 24:1341–1347.
19▪. Joling M, van den Heuvel OA, Berendse HW, et al. Serotonin transporter binding and anxiety symptoms in Parkinson's disease. J Neurol Neurosurg Psychiatry 2018; 89:89–94.

The novelty of this article consists in pointing to a thalamic serotonergic transporter involvement in Parkinson's disease anxiety, as measured by the [123I]FP-CIT extrastrital binding.

20. Joling M, Vriend C, van den Heuvel OA, et al. Analysis of extrastriatal 123 I-FP-CIT binding contributes to the differential diagnosis of Parkinsonian diseases. J Nucl Med 2017; 58:1117–1123.
21. Picillo M, Santangelo G, Erro R, et al. Association between dopaminergic dysfunction and anxiety in de novo Parkinson's disease. Parkinsonism Relat Disord 2017; 37:106–110.
22. Erro R, Pappatà S, Amboni M, et al. Anxiety is associated with striatal dopamine transporter availability in newly diagnosed untreated Parkinson's disease patients. Parkinsonism Relat Disord 2012; 18:1034–1038.
23▪. Sommerauer M, Fedorova TD, Hansen AK, et al. Evaluation of the noradrenergic system in Parkinson's disease: an 11C-MeNER PET and neuromelanin MRI study. Brain 2018; 141:496–504.

Sommerauer et al. evaluated in vivo for the first time the noradrenegic degeneration in Parkinson's disease with the means of neuromelanin-sensitive MRI sequences and 11C-MeNER: they traced a link betweeen neuradrenergic loss (mainly in locus coeruleus) and three of the most common nonmotor symptoms (RBD, orthostatic hypotention and cognitive decline).

24. Nahimi A, Sommerauer M, Kinnerup MB, et al. Noradrenergic deficits in Parkinson disease imaged with 11 C-MeNER. J Nucl Med 2018; 59:659–664.
25. García-Lorenzo D, Longo-Dos Santos C, Ewenczyk C, et al. The coeruleus/subcoeruleus complex in rapid eye movement sleep behaviour disorders in Parkinson's disease. Brain 2013; 136:2120–2129.
26. Braak H, Rüb U, Gai WP, Del Tredici K. Idiopathic Parkinson's disease: possible routes by which vulnerable neuronal types may be subject to neuroinvasion by an unknown pathogen. J Neural Transm 2003; 110:517–536.
27. Kehagia AA, Barker RA, Robbins TW. Cognitive impairment in Parkinson's disease: the dual syndrome hypothesis. Neurodegener Dis 2013; 11:79–92.
28. Kim K, Bohnen NI, Müller MLTM, Lustig C. Compensatory dopaminergic-cholinergic interactions in conflict processing: evidence from patients with Parkinson's disease. Neuroimage 2018; [Epub ahead of print].
29. Bohnen NI, Albin RL, Müller MLTM, et al. Frequency of cholinergic and caudate nucleus dopaminergic deficits across the predemented cognitive spectrum of Parkinson disease and evidence of interaction effects. JAMA Neurol 2015; 72:194–200.
30. Petrou M, Dwamena BA, Foerster BR, et al. Amyloid deposition in Parkinson's disease and cognitive impairment: a systematic review. Mov Disord 2015; 30:928–935.
31▪. Winer JR, Maass A, Pressman P, et al. Associations between tau, β-amyloid, and cognition in Parkinson disease. JAMA Neurol 2018; 75:227–235.

It described the first combined approach consisting in Tau and β-amyloid binding tracers to study Parkinson's disease cognitive impairment: tau protein deposition seemed to be related to β-amyloid and age of patients, but not to cognitive performaces per se.

32. Akhtar RS, Xie SX, Chen YJ, et al. Regional brain amyloid-β accumulation associates with domain-specific cognitive performance in Parkinson disease without dementia. PLoS One 2017; 12:e0177924.
33. Gomperts SN, Locascio JJ, Makaretz SJ, et al. Tau positron emission tomographic imaging in the lewy body diseases. JAMA Neurol 2016; 73:1334–1341.
34. ten Harmsen BL, van Rumund A, Aerts MB, et al. Clinical correlates of cerebral white matter abnormalities in patients with Parkinson's disease. Parkinsonism Relat Disord 2018; 49:28–33.
35. Malek N, Lawton MA, Swallow DMA, et al. Vascular disease and vascular risk factors in relation to motor features and cognition in early Parkinson's disease. Mov Disord 2016; 31:1518–1526.
36. Foo H, Mak E, Yong TT, et al. Progression of small vessel disease correlates with cortical thinning in Parkinson's disease. Parkinsonism Relat Disord 2016; 31:34–40.
37. Wen M-C, Heng HSE, Lu Z, et al. Differential white matter regional alterations in motor subtypes of early drug-naive Parkinson's disease patients. Neurorehabil Neural Repair 2018; 32:129–141.
38. Al-Bachari S, Vidyasagar R, Emsley HC, Parkes LM. Structural and physiological neurovascular changes in idiopathic Parkinson's disease and its clinical phenotypes. J Cereb Blood Flow Metab 2017; 37:3409–3421.
39. 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.
40. Nigro S, Riccelli R, Passamonti L, et al. Characterizing structural neural networks in de novo Parkinson disease patients using diffusion tensor imaging. Hum Brain Mapp 2016; 37:4500–4510.
41. Luo C, Song W, Chen Q, et al. White matter microstructure damage in tremor-dominant Parkinson's disease patients. Neuroradiology 2017; 59:691–698.
42. Galantucci S, Agosta F, Stefanova E, et al. Structural brain connectome and cognitive impairment in Parkinson disease. Radiology 2017; 283:515–525.
43. Rektor I, Svátková A, Vojtíšek L, et al. White matter alterations in Parkinson's disease with normal cognition precede grey matter atrophy. PLoS One 2018; 13:e0187939.
44. Koshimori Y, Ko J-H, Mizrahi R, et al. Imaging striatal microglial activation in patients with Parkinson's disease. PLoS One 2015; 10:e0138721.
45. Ghadery C, Koshimori Y, Coakeley S, et al. Microglial activation in Parkinson's disease using [18F]-FEPPA. J Neuroinflammation 2017; 14:8.
46. Jucaite A, Svenningsson P, Rinne JO, et al. Effect of the myeloperoxidase inhibitor AZD3241 on microglia: a PET study in Parkinson's disease. Brain 2015; 138:2687–2700.
47. Sweeney MD, Sagare AP, Zlokovic BV. Blood-brain barrier breakdown in Alzheimer disease and other neurodegenerative disorders. Nat Rev Neurol 2018; 14:133–150.
48. Plisson C, Weinzimmer D, Jakobsen S, et al. Phosphodiesterase 10A PET radioligand development program: from pig to human. J Nucl Med 2014; 55:595–601.
49. Niccolini F, Foltynie T, Reis Marques T, et al. Loss of phosphodiesterase 10A expression is associated with progression and severity in Parkinson's disease. Brain 2015; 138:3003–3015.
50▪▪. Niccolini F, Wilson H, Pagano G, et al. Loss of phosphodiesterase 4 in Parkinson disease. Neurology 2017; 89:586–593.

Niccolini et al. [50▪▪], using for the first time [11C]rolipram to study phosphodiesterase 4 in vivo in Parkinson's disease, attributed spatial working memory scores to the expression of this enzyme in the striato-thalamo-cortical network.

51. Ji G-J, Hu P, Liu T-T, et al. Functional connectivity of the corticobasal ganglia-thalamocortical network in parkinson disease: a systematic review and meta-analysis with cross-validation. Radiology 2018; [Epub ahead of print].
52. Herz DM, Eickhoff SB, Løkkegaard A, Siebner HR. Functional neuroimaging of motor control in parkinson's disease: a meta-analysis. Hum Brain Mapp 2014; 35:3227–3237.
53. Bartzokis G, Tishler TA, Lu PH, et al. Brain ferritin iron may influence age- and gender-related risks of neurodegeneration. Neurobiol Aging 2007; 28:414–423.
54. Langkammer C, Pirpamer L, Seiler S, et al. Quantitative susceptibility mapping in Parkinson's disease. PLoS One 2016; 11:e0162460.
55. Naduthota RM, Honnedevasthana AA, Lenka A, et al. Association of freezing of gait with nigral iron accumulation in patients with Parkinson's disease. J Neurol Sci 2017; 382:61–65.
56▪. 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; 32:619–623.

With the mean of a meta-analysis approach, Mahlknecht et al. [56▪] confirmed the usefulness of nigral iron content, as measured by MRI, to differentiate Parkinson's disease from controls and other types of parkinsonism not related to neurodegenerations and its correlation with DaT analysis.

57. Oh SW, Shin N-Y, Lee JJ, et al. Correlation of 3D FLAIR and dopamine transporter imaging in patients with Parkinsonism. Am J Roentgenol 2016; 207:1089–1094.
58. Bae YJ, Kim JM, Kim E, et al. Loss of nigral hyperintensity on 3 Tesla MRI of Parkinsonism: comparison with 123I-FP-CIT SPECT. Mov Disord 2016; 31:684–692.
59. Bae YJ, Kim J-M, Kim KJ, et al. Loss of substantia nigra hyperintensity at 3.0-T MR imaging in idiopathic REM sleep behavior disorder: comparison with 123 I-FP-CIT SPECT. Radiology 2018; 287:285–293.
60▪. Martin-Bastida A, Lao-Kaim NP, Loane C, 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; 24:357–365.

The substantia nigra iron quantification by high-pass filtered phase of SWI RMI was suggested as a measure of Parkinson's disease progression, as it correlated with disease severity.

61. Wieler M, Gee M, Camicioli R, Martin WRW. Freezing of gait in early Parkinson's disease: nigral iron content estimated from magnetic resonance imaging. J Neurol Sci 2016; 361:87–91.
62. An H, Zeng X, Niu T, et al. Quantifying iron deposition within the substantia nigra of Parkinson's disease by quantitative susceptibility mapping. J Neurol Sci 2018; 386:46–52.
63. Guan X, Xuan M, Gu Q, et al. Regionally progressive accumulation of iron in Parkinson's disease as measured by quantitative susceptibility mapping. NMR Biomed 2017; 30:e3489.
64. Acosta-Cabronero J, Cardenas-Blanco A, Betts MJ, et al. The whole-brain pattern of magnetic susceptibility perturbations in Parkinson's disease. Brain 2017; 140:118–131.
65. Schwarz ST, Xing Y, Tomar P, et al. In vivo assessment of brainstem depigmentation in parkinson disease: potential as a severity marker for multicenter studies. Radiology 2017; 283:789–798.
66. Prasad S, Stezin A, Lenka A, et al. Three-dimensional neuromelanin-sensitive magnetic resonance imaging of the substantia nigra in Parkinson's disease. Eur J Neurol 2018; 12:3218–3221.
67. Fabbri M, Reimão S, Carvalho M, et al. Substantia nigra neuromelanin as an imaging biomarker of disease progression in Parkinson's disease. J Parkinsons Dis 2017; 7:491–501.
68. Sung YH, Lee J, Nam Y, et al. Differential involvement of nigral subregions in idiopathic parkinson's disease. Hum Brain Mapp 2018; 39:542–553.
69. Matsuura K, Maeda M, Tabei K, et al. A longitudinal study of neuromelanin-sensitive magnetic resonance imaging in Parkinson's disease. Neurosci Lett 2016; 633:112–117.
70. Ofori E, Pasternak O, Planetta PJ, et al. Increased free water in the substantia nigra of Parkinson's disease: a single-site and multisite study. Neurobiol Aging 2015; 36:1097–1104.
71▪▪. Burciu RG, Ofori E, Archer DB, et al. Progression marker of Parkinson's disease: a 4-year multisite imaging study. Brain 2017; 140:2183–2192.

It is the first (4-year) long-term longitudinal multicentre study to assess the substantia nigra free water as a surrogate biomarker of Parkinson's disease progression.

72. Ofori E, Krismer F, Burciu RG, et al. Free water improves detection of changes in the substantia nigra in parkinsonism: a multisite study. Mov Disord 2017; 32:1457–1464.
73. Chung JW, Burciu RG, Ofori E, et al. Parkinson's disease diffusion MRI is not affected by acute antiparkinsonian medication. NeuroImage Clin 2017; 14:417–421.
74. Ofori E, Pasternak O, Planetta PJ, et al. Longitudinal changes in free-water within the substantia nigra of Parkinson's disease. Brain 2015; 138:2322–2331.
75▪. Marquié M, Verwer EE, Meltzer AC, et al. Lessons learned about [F-18]-AV-1451 off-target binding from an autopsy-confirmed Parkinson's case. Acta Neuropathol Commun 2017; 5:75.

It is the first article descring the correlation between tau imaging and neuropathological underpinning in a autopsy-diagnosed Parkinson's disease patient.

76. Hansen AK, Knudsen K, Lillethorup TP, et al. In vivo imaging of neuromelanin in Parkinson's disease using 18 F-AV-1451 PET. Brain 2016; 139:2039–2049.
77▪. Kuya K, Shinohara Y, Miyoshi F, et al. Correlation between neuromelanin-sensitive MR imaging and 123I-FP-CIT SPECT in patients with parkinsonism. Neuroradiology 2016; 58:351–356.

For the first time, the authors of this article correlated the dopaminergic denervation, assessed by DaTSCAN, with the progressive decrease in neuromelanin signal MRI.

78. Karimi M, Tian L, Brown CA, et al. Validation of nigrostriatal positron emission tomography measures: critical limits. Ann Neurol 2013; 73:390–396.
79. Cheng H-C, Ulane CM, Burke RE. Clinical progression in Parkinson disease and the neurobiology of axons. Ann Neurol 2010; 67:715–725.
80. Schreglmann SR, Krauss JK, Chang JW, et al. Functional lesional neurosurgery for tremor: back to the future? J Neurol Neurosurg Psychiatry 2017; [Epub ahead of print].
81. Alkemade A, de Hollander G, Keuken MC, et al. Comparison of T2*-weighted and QSM contrasts in Parkinson's disease to visualize the STN with MRI. PLoS One 2017; 12:e0176130.
82▪. Akram H, Dayal V, Mahlknecht P, et al. Connectivity derived thalamic segmentation in deep brain stimulation for tremor. NeuroImage Clin 2018; 18:130–142.

A high angular resolution diffusion-based imaging technique was proposed in this article to support the VIM visualization for functional surgery.

83▪▪. Ewert S, Plettig P, Li N, et al. Toward defining deep brain stimulation targets in MNI space: a subcortical atlas based on multimodal MRI, histology and structural connectivity. Neuroimage 2018; 170:271–282.

This work provides a potential outstandingly valuable free tool to improve the precision of functional surgery targeting and its effettiveness in tailoring the treatment of advanced Parkinson's disease.

84▪▪. Horn A, Reich M, Vorwerk J, et al. Connectivity predicts deep brain stimulation outcome in Parkinson disease. Ann Neurol 2017; 82:67–78.

This study disclosed the role of connectivity behind the STN DBS effectiveness in PD: these authors also proposed to consider network nodes as possible future targets of neuromodulation.

85. Golestanirad L, Iacono MI, Keil B, et al. Construction and modeling of a reconfigurable MRI coil for lowering SAR in patients with deep brain stimulation implants. Neuroimage 2017; 147:577–588.
86. Politis M, Sauerbier A, Loane C, et al. Sustained striatal dopamine levels following intestinal levodopa infusions in Parkinson's disease patients. Mov Disord 2017; 32:235–240.
87. Auffret M, Le Jeune F, Maurus A, et al. Apomorphine pump in advanced Parkinson's disease: effects on motor and nonmotor symptoms with brain metabolism correlations. J Neurol Sci 2017; 372:279–287.
88▪. Díez-Cirarda M, Ojeda N, Peña J, et al. Increased brain connectivity and activation after cognitive rehabilitation in Parkinson's disease: a randomized controlled trial. Brain Imaging Behav 2017; 11:1640–1651.

This is the first study to report how the DTI changes after a 3-month cognitive rehabilitation.

89. Díez-Cirarda M, Ojeda N, Peña J, et al. Long-term effects of cognitive rehabilitation on brain, functional outcome and cognition in Parkinson's disease. Eur J Neurol 2018; 25:5–12.
90. Laruelle M, Wallace E, Seibyl JP, et al. Graphical, kinetic, and equilibrium analyses of in vivo [123 I]β-CIT binding to dopamine transporters in healthy human subjects. J Cereb Blood Flow Metab 1994; 14:982–994.
91. Abi-dargham A, Gandelman MS, Deerausquin GA, et al. SPECT imaging of dopamine transporters in human brain with iodine- 123-fluoroalkyl analogs of n-CIT. J Nucl Med 1996; 37:1129–1134.
92. Xia C-F, Arteaga J, Chen G, et al. [18F]T807, a novel tau positron emission tomography imaging agent for Alzheimer's disease. Alzheimer's Dement 2013; 9:666–676.

* Both Vittorio Rispoli and Sebastian R. Schreglmann contributed equally to this article.

Keywords:

imaging; MRI; Parkinson's disease; PET; single photon emission computed tomography

Copyright © 2018 Wolters Kluwer Health, Inc. All rights resereved.