Longitudinal Changes in Neuromelanin MRI Signal in Parkinson's Disease: A Progression Marker

The new era of artificial intelligence in neuroradiology: current research and promising tools

Radiology has a number of characteristics that make it an especially suitable medical discipline for early artificial intelligence (AI) adoption. These include having a well-established digital workflow, standardized protocols for image storage, and numerous well-defined interpretive activities. The more than 200 commercial radiologic AI-based products recently approved by the Food and Drug Administration (FDA) to assist radiologists in a number of narrow image-analysis tasks such as image enhancement, workflow triage, and quantification, corroborate this observation. However, in order to leverage AI to boost efficacy and efficiency, and to overcome substantial obstacles to widespread successful clinical use of these products, radiologists should become familiarized with the emerging applications in their particular areas of expertise. In light of this, in this article we survey the existing literature on the application of AI-based techniques in neuroradiology, focusing on conditions such as vascular diseases, epilepsy, and demyelinating and neurodegenerative conditions. We also introduce some of the algorithms behind the applications, briefly discuss a few of the challenges of generalization in the use of AI models in neuroradiology, and skate over the most relevant commercially available solutions adopted in clinical practice. If well designed, AI algorithms have the potential to radically improve radiology, strengthening image analysis, enhancing the value of quantitative imaging techniques, and mitigating diagnostic errors.

An automated hybrid approach via deep learning and radiomics focused on the midbrain and substantia nigra to detect early-stage Parkinson's disease

Objectives

The altered neuromelanin in substantia nigra pars compacta (SNpc) is a valuable biomarker in the detection of early-stage Parkinson's disease (EPD). Diagnosis via visual inspection or single radiomics based method is challenging. Thus, we proposed a novel hybrid model that integrates radiomics and deep learning methodologies to automatically detect EPD based on neuromelanin-sensitive MRI, namely short-echo-time Magnitude (setMag) reconstructed from quantitative susceptibility mapping (QSM).

Methods

In our study, we collected QSM images including 73 EPD patients and 65 healthy controls, which were stratified into training-validation and independent test sets with an 8:2 ratio. Twenty-four participants from another center were included as the external validation set. Our framework began with the detection of the brainstem utilizing YOLO-v5. Subsequently, a modified LeNet was applied to obtain deep learning features. Meanwhile, 1781 radiomics features were extracted, and 10 features were retained after filtering. Finally, the classified models based on radiomics features, deep learning features, and the hybrid of both were established through machine learning algorithms, respectively. The performance was mainly evaluated using accuracy, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). The saliency map was used to visualize the model.

Results

The hybrid feature-based support vector machine (SVM) model showed the best performance, achieving ACC of 96.3 and 95.8% in the independent test set and external validation set, respectively. The model established by hybrid features outperformed the one radiomics feature-based (NRI: 0.245, IDI: 0.112). Furthermore, the saliency map showed that the bilateral "swallow tail" sign region was significant for classification.

Conclusion

The integration of deep learning and radiomic features presents a potent strategy for the computer-aided diagnosis of EPD. This study not only validates the accuracy of our proposed model but also underscores its interpretability, evidenced by differential significance across various anatomical sites.

Regional nigral neuromelanin degeneration in asymptomatic leucine-rich repeat kinase 2 gene carrier using MRI

Asymptomatic Leucine-Rich Repeat Kinase 2 Gene (LRRK2) carriers are at risk for developing Parkinson's disease (PD). We studied presymptomatic substantia nigra pars compacta (SNc) regional neurodegeneration in asymptomatic LRRK2 carriers compared to idiopathic PD patients using neuromelanin-sensitive MRI technique (NM-MRI). Fifteen asymptomatic LRRK2 carriers, 22 idiopathic PD patients, and 30 healthy controls (HCs) were scanned using NM-MRI. We computed volume and contrast-to-noise ratio (CNR) derived from the whole SNc and the sensorimotor, associative, and limbic SNc regions. An analysis of covariance was performed to explore the differences of whole and regional NM-MRI values among the groups while controlling the effect of age and sex. In whole SNc, LRRK2 had significantly lower CNR than HCs but non-significantly higher volume and CNR than PD patients, and PD patients significantly lower volume and CNR compared to HCs. Inside SNc regions, there were significant group effects for CNR in all regions and for volumes in the associative region, with a trend in the sensorimotor region but no significant changes in the limbic region. PD had reduced volume and CNR in all regions compared to HCs. Asymptomatic LRRK2 carriers showed globally decreased SNc volume and CNR suggesting early nigral neurodegeneration in these subjects at risk of developing PD.

Neuromelanin-sensitive magnetic resonance imaging: Possibilities and promises as an imaging biomarker for Parkinson's disease

Parkinson's disease (PD) is an age-related progressive neurodegenerative disorder characterized by both motor and non-motor symptoms resulting from the death of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and noradrenergic neurons in the locus coeruleus (LC). The current diagnosis of PD primarily relies on motor symptoms, often leading to diagnoses in advanced stages, where a significant portion of SNpc dopamine neurons has already succumbed. Therefore, the identification of imaging biomarkers for early-stage PD diagnosis and disease progression monitoring is imperative. Recent studies propose that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) holds promise as an imaging biomarker. In this review, we summarize the latest findings concerning NM-MRI characteristics at various stages in patients with PD and those with atypical parkinsonism. In conclusion, alterations in neuromelanin within the LC are associated with non-motor symptoms and prove to be a reliable imaging biomarker in the prodromal phase of PD. Furthermore, NM-MRI demonstrates efficacy in differentiating progressive supranuclear palsy (PSP) from PD and multiple system atrophy with predominant parkinsonism. The spatial patterns of changes in the SNpc can be indicative of PD progression and aid in distinguishing between PSP and synucleinopathies. We recommend that patients with PD and individuals at risk for PD undergo regular NM-MRI examinations. This technology holds the potential for widespread use in PD diagnosis.

PENCIL imaging: A novel approach for neuromelanin sensitive MRI in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is associated with the loss of neuromelanin (NM) and increased iron in the substantia nigra (SN). Magnetization transfer contrast (MTC) is widely used for NM visualization but has limitations in brain coverage and scan time. This study aimed to develop a new approach called Proton-density Enhanced Neuromelanin Contrast in Low flip angle gradient echo (PENCIL) imaging to visualize NM in the SN.

METHODS

This study included 30 PD subjects and 50 healthy controls (HCs) scanned at 3T. PENCIL and MTC images were acquired. NM volume in the SN pars compacta (SNpc), normalized image contrast (Cnorm), and contrast-to-noise ratio (CNR) were calculated. The change of NM volume in the SNpc with age was analyzed using the HC data. A group analysis compared differences between PD subjects and HCs. Receiver operating characteristic (ROC) analysis and area under the curve (AUC) calculations were used to evaluate the diagnostic performance of NM volume and CNR in the SNpc.

RESULTS

PENCIL provided similar visualization and structural information of NM compared to MTC. In HCs, PENCIL showed higher NM volume in the SNpc than MTC, but this difference was not observed in PD subjects. PENCIL had higher CNR, while MTC had higher Cnorm. Both methods revealed a similar pattern of NM volume in SNpc changes with age. There were no significant differences in AUCs between NM volume in SNpc measured by PENCIL and MTC. Both methods exhibited comparable diagnostic performance in this regard.

CONCLUSIONS

PENCIL imaging provided improved CNR compared to MTC and showed similar diagnostic performance for differentiating PD subjects from HCs. The major advantage is PENCIL has rapid whole-brain coverage and, when using STAGE imaging, offers a one-stop quantitative assessment of tissue properties.

Large-scale functional network connectivity mediates the association between nigral neuromelanin hypopigmentation and motor impairment in Parkinson's disease

Neuromelanin hypopigmentation within substantia nigra pars compacta (SNc) reflects the loss of pigmented neurons, which in turn contributes to the dysfunction of the nigrostriatal and striato-cortical pathways in Parkinson's disease (PD). Our study aims to investigate the relationships between SN degeneration manifested by neuromelanin reduction, functional connectivity (FC) among large-scale brain networks, and motor impairment in PD. This study included 68 idiopathic PD patients and 32 age-, sex- and education level-matched healthy controls who underwent neuromelanin-sensitive magnetic resonance imaging (MRI), functional MRI, and motor assessments. SN integrity was measured using the subregional contrast-to-noise ratio calculated from neuromelanin-sensitive MRI. Resting-state FC maps were obtained based on the independent component analysis. Subsequently, we performed partial correlation and mediation analyses in SN degeneration, network disruption, and motor impairment for PD patients. We found significantly decreased neuromelanin within SN and widely altered inter-network FCs, mainly involved in the basal ganglia (BG), sensorimotor and frontoparietal networks in PD. In addition, decreased neuromelanin content was negatively correlated with the dorsal sensorimotor network (dSMN)-medial visual network connection (P = 0.012) and dSMN-BG connection (P = 0.004). Importantly, the effect of SN neuromelanin hypopigmentation on motor symptom severity in PD is partially mediated by the increased connectivity strength between BG and dSMN (indirect effect =  - 1.358, 95% CI: - 2.997, - 0.147). Our results advanced our understanding of the interactions between neuromelanin hypopigmentation in SN and altered FCs of functional networks in PD and suggested the potential of multimodal metrics for early diagnosis and monitoring the response to therapies.

How Lifetime Evolution of Parkinson's Disease Could Shape Clinical Trial Design: A Shared Patient-Clinician Viewpoint

Parkinson's disease (PD) has a long, heterogeneous, pre-diagnostic phase, during which pathology insidiously accumulates. Increasing evidence suggests that environmental and lifestyle factors in early life contribute to disease risk and progression. Thanks to the extensive study of this pre-diagnostic phase, the first prevention trials of PD are being designed. However, the highly heterogenous evolution of the disease across the life course is not yet sufficiently taken into account. This could hamper clinical trial success in the advent of biological disease definitions. In an interdisciplinary patient-clinician study group, we discussed how an approach that incorporates the lifetime evolution of PD may benefit the design of disease-modifying trials by impacting population, target and outcome selection. We argue that the timepoint of exposure to risk and protective factors plays a critical role in PD subtypes, influencing population selection. In addition, recent developments in differential disease mechanisms, aided by biological disease definitions, could impact optimal treatment targets. Finally, multimodal biomarker panels using this lifetime approach will likely be most sensitive as progression markers for more personalized trials. We believe that the lifetime evolution of PD should be considered in the design of clinical trials, and that such initiatives could benefit from more patient-clinician partnerships.

Neuromelanin-sensitive magnetic resonance imaging in the study of mental disorder: A systematic review

Dopamine and norepinephrine are implicated in the pathophysiology of mental disorders, but non-invasive study of their neuronal function remains challenging. Recent research suggests that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) techniques may overcome this limitation by enabling the non-invasive imaging of the substantia nigra (SN)/ ventral tegmental area (VTA) dopaminergic and locus coeruleus (LC) noradrenergic systems. A review of 19 studies that met the criteria for NM-MRI application in mental disorders found that despite the use of heterogeneous sequence parameters and metrics, nearly all studies reported differences in contrast ratio (CNR) of LC or SN/VTA between patients with mental disorders and healthy controls. These findings suggest that NM-MRI is a valuable tool in psychiatry, but the differences in sequence parameters across studies hinder comparability, and a standardized analysis pipeline is needed to improve the reliability of results. Further research using standardized methods is needed to better understand the role of dopamine and norepinephrine in mental disorders.

Cinpanemab in Early Parkinson Disease: Evaluation of Biomarker Results From the Phase 2 SPARK Clinical Trial

BACKGROUND AND OBJECTIVES

Sensitive, reliable, and scalable biomarkers are needed to accelerate the development of therapies for Parkinson disease (PD). In this study, we evaluate the biomarkers of early PD diagnosis, disease progression, and treatment effect collected in the SPARK.

METHODS

Cinpanemab is a human-derived monoclonal antibody binding preferentially to aggregated forms of extracellular α-synuclein. SPARK was a randomized, double-blind, placebo-controlled, phase 2 multicenter trial evaluating 3 cinpanemab doses administered intravenously every 4 weeks for 52 weeks with an active treatment dose-blind extension period for up to 112 weeks. SPARK enrolled 357 participants diagnosed with PD within 3 years, aged 40-80 years, ≤2.5 on the modified Hoehn and Yahr scale, and with evidence of striatal dopaminergic deficit. The primary outcome was change from baseline in the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale total score. Secondary and exploratory biomarker outcomes evaluated change from baseline at week 52 relative to placebo. Dopamine transporter SPECT and MRI were used to quantify changes in the nigrostriatal dopamine pathway and regional atrophy. CSF and plasma samples were used to assess change in total α-synuclein levels, α-synuclein seeding, and neurofilament light chain levels. SPARK was conducted from January 2018 to April 2021 and terminated due to lack of efficacy.

RESULTS

Approximately 3.8% (15/398) of SPECT-imaged participants did not have evidence of dopaminergic deficit and were screen-failed. Binary classification of α-synuclein seeding designated 93% (110/118) of the enrolled CSF subgroup as positive for α-synuclein seeds at baseline. Clinical disease progression was observed, with no statistically significant difference in cinpanemab groups compared with that in placebo. Ninety-nine percent of participants with positive α-synuclein seeding remained positive through week 52. No statistically significant changes from baseline were observed between treatment groups and placebo across biomarker measures. Broadly, there was minimal annual change with high interindividual variability across biomarkers-with striatal binding ratios of the ipsilateral putamen showing the greatest mean change/SD over time.

DISCUSSION

Biomarker results indicated enrollment of the intended population with early PD, but there was no significant correlation with disease progression or clear evidence of a cinpanemab treatment effect on biomarker measures. Suitable biomarkers for evaluating disease severity and progression in early PD trials are still needed.

TRIAL REGISTRATION INFORMATION

NCT03318523 (clinicaltrials.gov/ct2/show/NCT03318523); Submitted October 24, 2017; First patient enrolled January 2018.

Neuromelanin-sensitive MRI as a promising biomarker of catecholamine function

Disruptions to dopamine and noradrenergic neurotransmission are noted in several neurodegenerative and psychiatric disorders. Neuromelanin-sensitive (NM)-MRI offers a non-invasive approach to visualize and quantify the structural and functional integrity of the substantia nigra and locus coeruleus. This method may aid in the diagnosis and quantification of longitudinal changes of disease and could provide a stratification tool for predicting treatment success of pharmacological interventions targeting the dopaminergic and noradrenergic systems. Given the growing clinical interest in NM-MRI, understanding the contrast mechanisms that generate this signal is crucial for appropriate interpretation of NM-MRI outcomes and for the continued development of quantitative MRI biomarkers that assess disease severity and progression. To date, most studies associate NM-MRI measurements to the content of the neuromelanin pigment and/or density of neuromelanin-containing neurons, while recent studies suggest that the main source of the NM-MRI contrast is not the presence of neuromelanin but the high-water content in the dopaminergic and noradrenergic neurons. In this review, we consider the biological and physical basis for the NM-MRI contrast and discuss a wide range of interpretations of NM-MRI. We describe different acquisition and image processing approaches and discuss how these methods could be improved and standardized to facilitate large-scale multisite studies and translation into clinical use. We review the potential clinical applications in neurological and psychiatric disorders and the promise of NM-MRI as a biomarker of disease, and finally, we discuss the current limitations of NM-MRI that need to be addressed before this technique can be utilized as a biomarker and translated into clinical practice and offer suggestions for future research.

Diagnostic utility of 7T neuromelanin imaging of the substantia nigra in Parkinson's disease

Parkinson's disease (PD) is a prevalent neurodegenerative disorder that presents a diagnostic challenge due to symptom overlap with other disorders. Neuromelanin (NM) imaging is a promising biomarker for PD, but adoption has been limited, in part due to subpar performance at standard MRI field strengths. We aimed to evaluate the diagnostic utility of ultra-high field 7T NM-sensitive imaging in the diagnosis of PD versus controls and essential tremor (ET), as well as NM differences among PD subtypes. A retrospective case-control study was conducted including PD patients, ET patients, and controls. 7T NM-sensitive 3D-GRE was acquired, and substantia nigra pars compacta (SNpc) volumes, contrast ratios, and asymmetry indices were calculated. Statistical analyses, including general linear models and ROC curves, were employed. Twenty-one PD patients, 13 ET patients, and 18 controls were assessed. PD patients exhibited significantly lower SNpc volumes compared to non-PD subjects. SNpc total volume showed 100% sensitivity and 96.8% specificity (AUC = 0.998) for differentiating PD from non-PD and 100% sensitivity and 95.2% specificity (AUC = 0.996) in differentiating PD from ET. Contrast ratio was not significantly different between PD and non-PD groups (p = 0.07). There was also significantly higher asymmetry index in SNpc volume in PD compared to non-PD cohorts (p < 0.001). NM signal loss in PD predominantly involved the inferior, posterior, and lateral aspects of SNpc. Akinetic-rigid subtype showed more significant NM signal loss compared to tremor dominant subtype (p < 0.001). 7T NM imaging demonstrates potential as a diagnostic tool for PD, including potential distinction between subtypes, allowing improved understanding of disease progression and subtype-related characteristics.

Progressive Cerebrovascular Reactivity Reduction Occurs in Parkinson's Disease: A Longitudinal Study

BACKGROUND

The change of microvascular function over the course of Parkinson's disease (PD) remains unclear.

OBJECTIVE

We aimed to ascertain regional cerebrovascular reactivity (CVR) changes in the patients with PD at baseline (V0) and during a 2-year follow-up period (V1). We further investigated whether alterations in CVR were linked to cognitive decline and brain functional connectivity (FC).

METHODS

We recruited 90 PD patients and 51 matched healthy controls (HCs). PD patients underwent clinical evaluations, neuropsychological assessments, and magnetic resonance (MR) scanning at V0 and V1, whereas HCs completed neuropsychological assessments and MR at baseline. The analysis included evaluating CVR and FC maps derived from resting-state functional magnetic resonance imaging and investigating CVR measurement reproducibility.

RESULTS

Compared with HCs, CVR reduction in left inferior occipital gyrus and right superior temporal cortex at V0 persisted at V1, with larger clusters. Longitudinal reduction in CVR of the left posterior cingulate cortex correlated with decline in Trail Making Test B performance within PD patients. Reproducibility validation further confirmed these findings. In addition, the results also showed that there was a tendency for FC to be weakened from posterior to anterior with the progression of the disease.

CONCLUSIONS

Microvascular dysfunction might be involved in disease progression, subsequently weaken brain FC, and partly contribute to executive function deficits in early PD. © 2023 International Parkinson and Movement Disorder Society.

Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here?

Parkinsonian disorders are a heterogeneous group of incurable neurodegenerative diseases that significantly reduce quality of life and constitute a substantial economic burden. Nuclear imaging (NI) and magnetic resonance imaging (MRI) have played and continue to play a key role in research aimed at understanding and monitoring these disorders. MRI is cheaper, more accessible, nonirradiating, and better at measuring biological structures and hemodynamics than NI. NI, on the other hand, can track molecular processes, which may be crucial for the development of efficient diseasemodifying therapies. Given the strengths and weaknesses of NI and MRI, how can they best be applied to Parkinsonism research going forward? This review aims to examine the effectiveness of NI and MRI in three areas of Parkinsonism research (differential diagnosis, prodromal disease identification, and disease monitoring) to highlight where they can be most impactful. Based on the available literature, MRI can assist with differential diagnosis, prodromal disease identification, and disease monitoring as well as NI. However, more work is needed, to confirm the value of MRI for monitoring prodromal disease and predicting phenoconversion. Although NI can complement or be a substitute for MRI in all the areas covered in this review, we believe that its most meaningful impact will emerge once reliable Parkinsonian proteinopathy tracers become available. Future work in tracer development and high-field imaging will continue to influence the landscape for NI and MRI.

Comparison of automated and manual quantification methods for neuromelanin-sensitive MRI in Parkinson's disease

Neuromelanin-sensitive magnetic resonance imaging quantitative analysis methods have provided promising biomarkers that can noninvasively quantify degeneration of the substantia nigra in patients with Parkinson's disease. However, there is a need to systematically evaluate the performance of manual and automated quantification approaches. We evaluate whether spatial, signal-intensity, or subject specific abnormality measures using either atlas based or manually traced identification of the substantia nigra better differentiate patients with Parkinson's disease from healthy controls using logistic regression models and receiver operating characteristics. Inference was performed using bootstrap analyses to calculate 95% confidence interval bounds. Pairwise comparisons were performed by generating 10,000 permutations, refitting the models, and calculating a paired difference between metrics. Thirty-one patients with Parkinson's disease and 22 healthy controls were included in the analyses. Signal intensity measures significantly outperformed spatial and subject specific abnormality measures, with the top performers exhibiting excellent ability to differentiate patients with Parkinson's disease and healthy controls (balanced accuracy = 0.89; area under the curve = 0.81; sensitivity =0.86; and specificity = 0.83). Atlas identified substantia nigra metrics performed significantly better than manual tracing metrics. These results provide clear support for the use of automated signal intensity metrics and additional recommendations. Future work is necessary to evaluate whether the same metrics can best differentiate atypical parkinsonism, perform similarly in de novo and mid-stage cohorts, and serve as longitudinal monitoring biomarkers.

How should we be using biomarkers in trials of disease modification in Parkinson's disease?

The recent validation of the α-synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson's disease has formed the backbone for a proposed staging system for incorporation in Parkinson's disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson's disease patients into trials (as distinct from patients with non-Parkinson's disease parkinsonism or non-Parkinson's disease tremors). There remain, however, further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson's disease, namely: optimizing the distinction between different α-synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; a sensitive means of confirming target engagement; and the early prediction of longer-term clinical benefit. For example, levels of CSF proteins such as the lysosomal enzyme β-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer's disease-like pathology (detectable through CSF levels of amyloid-β42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline in Parkinson's disease even in its later stages. The exploitation of additional biomarkers to the α-synuclein seed amplification assay will, therefore, greatly add to our ability to plan trials and assess the disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson's disease. However, correlation with clinical progression does not necessarily equate to causation, and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson's disease.

Predicting longitudinal brain atrophy in Parkinson's disease using a Susceptible-Infected-Removed agent-based model

Parkinson's disease is a progressive neurodegenerative disorder characterized by accumulation of abnormal isoforms of alpha-synuclein. Alpha-synuclein is proposed to act as a prion in Parkinson's disease: In its misfolded pathologic state, it favors the misfolding of normal alpha-synuclein molecules, spreads trans-neuronally, and causes neuronal damage as it accumulates. This theory remains controversial. We have previously developed a Susceptible-Infected-Removed (SIR) computational model that simulates the templating, propagation, and toxicity of alpha-synuclein molecules in the brain. In this study, we test this model with longitudinal MRI collected over 4 years from the Parkinson's Progression Markers Initiative (1,068 T1 MRI scans, 790 Parkinson's disease scans, and 278 matched control scans). We find that brain deformation progresses in subcortical and cortical regions. The SIR model recapitulates the spatiotemporal distribution of brain atrophy observed in Parkinson's disease. We show that connectome topology and geometry significantly contribute to model fit. We also show that the spatial expression of two genes implicated in alpha-synuclein synthesis and clearance, SNCA and GBA, also influences the atrophy pattern. We conclude that the progression of atrophy in Parkinson's disease is consistent with the prion-like hypothesis and that the SIR model is a promising tool to investigate multifactorial neurodegenerative diseases over time.

The integrity of dopaminergic and noradrenergic brain regions is associated with different aspects of late-life memory performance

Changes in dopaminergic neuromodulation play a key role in adult memory decline. Recent research has also implicated noradrenaline in shaping late-life memory. However, it is unclear whether these two neuromodulators have distinct roles in age-related cognitive changes. Here, combining longitudinal MRI of the dopaminergic substantia nigra-ventral tegmental area (SN-VTA) and noradrenergic locus coeruleus (LC) in younger (n = 69) and older (n = 251) adults, we found that dopaminergic and noradrenergic integrity are differentially associated with memory performance. While LC integrity was related to better episodic memory across several tasks, SN-VTA integrity was linked to working memory. Longitudinally, we found that older age was associated with more negative change in SN-VTA and LC integrity. Notably, changes in LC integrity reliably predicted future episodic memory. These differential associations of dopaminergic and noradrenergic nuclei with late-life cognitive decline have potential clinical utility, given their degeneration in several age-associated diseases.

Nigral Pathology Contributes to Microstructural Integrity of Striatal and Frontal Tracts in Parkinson's Disease

BACKGROUND

Motor and cognitive impairment in Parkinson's disease (PD) is associated with dopaminergic dysfunction that stems from substantia nigra (SN) degeneration and concomitant α-synuclein accumulation. Diffusion magnetic resonance imaging (MRI) can detect microstructural alterations of the SN and its tracts to (sub)cortical regions, but their pathological sensitivity is still poorly understood.

OBJECTIVE

To unravel the pathological substrate(s) underlying microstructural alterations of SN, and its tracts to the dorsal striatum and dorsolateral prefrontal cortex (DLPFC) in PD.

METHODS

Combining post-mortem in situ MRI and histopathology, T1-weighted and diffusion MRI, and neuropathological samples of nine PD, six PD with dementia (PDD), five dementia with Lewy bodies (DLB), and 10 control donors were collected. From diffusion MRI, mean diffusivity (MD) and fractional anisotropy (FA) were derived from the SN, and tracts between the SN and caudate nucleus, putamen, and DLPFC. Phosphorylated-Ser129-α-synuclein and tyrosine hydroxylase immunohistochemistry was included to quantify nigral Lewy pathology and dopaminergic degeneration, respectively.

RESULTS

Compared to controls, PD and PDD/DLB showed increased MD of the SN and SN-DLPFC tract, as well as increased FA of the SN-caudate nucleus tract. Both PD and PDD/DLB showed nigral Lewy pathology and dopaminergic loss compared to controls. Increased MD of the SN and FA of SN-caudate nucleus tract were associated with SN dopaminergic loss. Whereas increased MD of the SN-DLPFC tract was associated with increased SN Lewy neurite load.

CONCLUSIONS

In PD and PDD/DLB, diffusion MRI captures microstructural alterations of the SN and tracts to the dorsal striatum and DLPFC, which differentially associates with SN dopaminergic degeneration and Lewy neurite pathology. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Imaging Markers in Genetic Forms of Parkinson's Disease

Parkinson's disease (PD) is a complex neurodegenerative disorder characterized by motor symptoms such as bradykinesia, rigidity, and resting tremor. While the majority of PD cases are sporadic, approximately 15-20% of cases have a genetic component. Advances in neuroimaging techniques have provided valuable insights into the pathophysiology of PD, including the different genetic forms of the disease. This literature review aims to summarize the current state of knowledge regarding neuroimaging findings in genetic PD, focusing on the most prevalent known genetic forms: mutations in the GBA1, LRRK2, and Parkin genes. In this review, we will highlight the contributions of various neuroimaging modalities, including positron emission tomography (PET), single-photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI), in elucidating the underlying pathophysiological mechanisms and potentially identifying candidate biomarkers for genetic forms of PD.

Iron homeostasis imbalance and ferroptosis in brain diseases

Brain iron homeostasis is maintained through the normal function of blood-brain barrier and iron regulation at the systemic and cellular levels, which is fundamental to normal brain function. Excess iron can catalyze the generation of free radicals through Fenton reactions due to its dual redox state, thus causing oxidative stress. Numerous evidence has indicated brain diseases, especially stroke and neurodegenerative diseases, are closely related to the mechanism of iron homeostasis imbalance in the brain. For one thing, brain diseases promote brain iron accumulation. For another, iron accumulation amplifies damage to the nervous system and exacerbates patients' outcomes. In addition, iron accumulation triggers ferroptosis, a newly discovered iron-dependent type of programmed cell death, which is closely related to neurodegeneration and has received wide attention in recent years. In this context, we outline the mechanism of a normal brain iron metabolism and focus on the current mechanism of the iron homeostasis imbalance in stroke, Alzheimer's disease, and Parkinson's disease. Meanwhile, we also discuss the mechanism of ferroptosis and simultaneously enumerate the newly discovered drugs for iron chelators and ferroptosis inhibitors.

Screening and Targeting Risk Factors for Prodromal Synucleinopathy: Taking Steps toward a Prescriptive Multi-modal Framework

As the prevalence of Parkinson's disease (PD) grows, so too does the population at-risk of developing PD, those in the so-called prodromal period. This period can span from those experiencing subtle motor deficits yet not meeting full diagnostic criteria or those with physiologic markers of disease alone. Several disease-modifying therapies have failed to show a neuroprotective effect. A common criticism is that neurodegeneration, even in the early motor stages, has advanced too far for neuro-restoration-based interventions to be effective. Therefore, identifying this early population is essential. Once identified, these patients could then potentially benefit from sweeping lifestyle modifications to alter their disease trajectory. Herein, we review the literature on risk factors for, and prodromal symptoms of, PD with an emphasis on ones which may be modifiable in the earliest possible stages. We propose a process for identifying this population and speculate on some strategies which may modulate disease trajectory. Ultimately, this proposal warrants prospective studies.

Neuromelanin related ultra-high field signal intensity of the locus coeruleus differs between Parkinson's disease and controls

INTRODUCTION

Neuromelanin related signal changes in catecholaminergic nuclei are considered as a promising MRI biomarker in Parkinson's disease (PD). Until now, most studies have investigated the substantia nigra (SN), while signal changes might be more prominent in the locus coeruleus (LC). Ultra-high field MRI improves the visualisation of these small brainstem regions and might support the development of imaging biomarkers in PD.

OBJECTIVES

To compare signal intensity of the SN and LC on Magnetization Transfer MRI between PD patients and healthy controls (HC) and to explore its association with cognitive performance in PD.

METHODS

This study was conducted using data from the TRACK-PD study, a longitudinal 7T MRI study. A total of 78 early-stage PD patients and 36 HC were included. A mask for the SN and LC was automatically segmented and manually corrected. Neuromelanin related signal intensity of the SN and LC was compared between PD and HC.

RESULTS

PD participants showed a lower contrast-to-noise ratio (CNR) in the right SN (p = 0.029) and left LC (p = 0.027). After adding age as a confounder, the CNR of the right SN did not significantly differ anymore between PD and HC (p = 0.055). Additionally, a significant positive correlation was found between the SN CNR and memory function.

DISCUSSION

This study confirms that neuromelanin related signal intensity of the LC differs between early-stage PD patients and HC. No significant difference was found in the SN. This supports the theory of bottom-up disease progression in PD. Furthermore, loss of SN integrity might influence working memory or learning capabilities in PD patients.

Neuromelanin-Sensitive Magnetic Resonance Imaging as a Measure for Differential Diagnosis of Essential Tremor and Parkinson's Disease

We sought to evaluate whether the neuromelanin-sensitive magnetic resonance imaging (NM-MRI) features of the substantia nigra (SN) have utility in the differential diagnosis of Parkinson's disease (PD) and essential tremor (ET). This study enrolled 23 patients with PD, 20 patients with ET, and 18 healthy participants. All subjects underwent clinical examination, motor and cognitive assessments, and NM-MRI scans. The area and contrast-to-noise ratio (CNR) values of SN were defined according to NM-MRI images. Then, receiver operating characteristic (ROC) analysis was conducted to characterize the diagnostic power of the SN area and CNR values of SN. Compared with ET and control groups, the PD group showed a significant reduction of the area of SN (P = 0.003, PD vs. ET; P = 0.001, PD vs. control) and in the SN to midbrain area ratio in the same layer (P = 0.006, PD vs. ET; P = 0.005, PD vs. control). The SN area had a sensitivity of 65% and a specificity of 87% for distinguishing ET from PD, with an area under the curve (AUC) of 0.7630 and a Youden index of 0.5200, whereas the ratio of the SN area to midbrain area in the same layer had a sensitivity of 60% and a specificity of 87% for distinguishing ET from PD, with an AUC of 0.7478 and a Youden index of 0.4700. Compared with the ET group, the mean CNR value of the SN and the respective CNR values of the three subregions were all weakened in the PD group, and only the CNR in the middle part was significantly different from the control group (P = 0.006). The sensitivity of the CNR value of the middle part of the SN for differentiating ET from PD was 65%, the specificity was 87%, the AUC was 0.7500, and the Youden index was 0.5200.Based on our findings, we conclude that NM-MRI can improve diagnostic accuracy in PD and can be used as a specific and sensitive potential diagnostic biomarker for PD.

Chaudhuri's Dashboard of Vitals in Parkinson's syndrome: an unmet need underpinned by real life clinical tests

We have recently published the notion of the "vitals" of Parkinson's, a conglomeration of signs and symptoms, largely nonmotor, that must not be missed and yet often not considered in neurological consultations, with considerable societal and personal detrimental consequences. This "dashboard," termed the Chaudhuri's vitals of Parkinson's, are summarized as 5 key vital symptoms or signs and comprise of (a) motor, (b) nonmotor, (c) visual, gut, and oral health, (d) bone health and falls, and finally (e) comorbidities, comedication, and dopamine agonist side effects, such as impulse control disorders. Additionally, not addressing the vitals also may reflect inadequate management strategies, leading to worsening quality of life and diminished wellness, a new concept for people with Parkinson's. In this paper, we discuss possible, simple to use, and clinically relevant tests that can be used to monitor the status of these vitals, so that these can be incorporated into clinical practice. We also use the term Parkinson's syndrome to describe Parkinson's disease, as the term "disease" is now abandoned in many countries, such as the U.K., reflecting the heterogeneity of Parkinson's, which is now considered by many as a syndrome.

Brainstem neuromelanin and iron MRI reveals a precise signature for idiopathic and LRRK2 Parkinson's disease

Neuromelanin (NM) loss in substantia nigra pars compacta (SNc) and locus coeruleus (LC) reflects neuronal death in Parkinson's disease (PD). Since genetically-determined PD shows varied clinical expressivity, we wanted to accurately quantify and locate brainstem NM and iron, to discover whether specific MRI patterns are linked to Leucine-rich repeat kinase 2 G2019S PD (LRRK2-PD) or idiopathic Parkinson's disease (iPD). A 3D automated MRI atlas-based segmentation pipeline (3D-ABSP) for NM/iron-sensitive MRI images topographically characterized the SNc, LC, and red nucleus (RN) neuronal loss and calculated NM/iron contrast ratio (CR) and normalized volume (nVol). Left-side NM nVol was larger in all groups. PD had lower NM CR and nVol in ventral-caudal SNc, whereas iron increased in lateral, medial-rostral, and caudal SNc. The SNc NM CR reduction was associated with psychiatric symptoms. LC CR and nVol discriminated better among subgroups: LRRK2-PD had similar LC NM CR and nVol as that of controls, and larger LC NM nVol and RN iron CR than iPD. PD showed higher iron SNc nVol than controls, especially among LRRK2-PD. ROC analyses showed an AUC > 0.92 for most pairwise subgroup comparisons, with SNc NM being the best discriminator between HC and PD. NM measures maintained their discriminator power considering the subgroup of PD patients with less than 5 years of disease duration. The SNc iron CR and nVol increase was associated with longer disease duration in PD patients. The 3D-ABSP sensitively identified NM and iron MRI patterns strongly correlated with phenotypic PD features.

Diagnosing Parkinson's disease by combining neuromelanin and iron imaging features using an automated midbrain template approach

BACKGROUND AND PURPOSE

Early diagnosis of Parkinson's disease (PD) is still a clinical challenge. Most previous studies using manual or semi-automated methods for segmenting the substantia nigra (SN) are time-consuming and, despite raters being well-trained, individual variation can be significant. In this study, we used a template-based, automatic, SN subregion segmentation pipeline to detect the neuromelanin (NM) and iron features in the SN and SN pars compacta (SNpc) derived from a single 3D magnetization transfer contrast (MTC) gradient echo (GRE) sequence in an attempt to develop a comprehensive imaging biomarker that could be used to diagnose PD.

MATERIALS AND METHODS

A total of 100 PD patients and 100 age- and sex-matched healthy controls (HCs) were imaged on a 3T scanner. NM-based SN (SN_NM) boundaries and iron-based SN (SN_QSM) boundaries and their overlap region (representing the SNpc) were delineated automatically using a template-based SN subregion segmentation approach based on quantitative susceptibility mapping (QSM) and NM images derived from the same MTC-GRE sequence. All PD and HC subjects were evaluated for the nigrosome-1 (N1) sign by two raters independently. Receiver Operating Characteristic (ROC) analyses were performed to evaluate the utility of SN_NM volume, SN_QSM volume, SNpc volume and iron content with a variety of thresholds as well as the N1 sign in diagnosing PD. Correlation analyses were performed to study the relationship between these imaging measures and the clinical scales in PD.

RESULTS

In this study, we verified the value of the fully automatic template based midbrain deep gray matter mapping approach in differentiating PD patients from HCs. The automatic segmentation of the SN in PD patients led to satisfactory DICE similarity coefficients and volume ratio (VR) values of 0.81 and 1.17 for the SN_NM, and 0.87 and 1.05 for the SN_QSM, respectively. For the HC group, the average DICE similarity coefficients and VR values were 0.85 and 0.94 for the SN_NM, and 0.87 and 0.96 for the SN_QSM, respectively. The SN_QSM volume tended to decrease with age for both the PD and HC groups but was more severe for the PD group. For diagnosing PD, the N1 sign performed reasonably well by itself (Area Under the Curve (AUC) = 0.783). However, combining the N1 sign with the other quantitative measures (SN_NM volume, SN_QSM volume, SNpc volume and iron content) resulted in an improved diagnosis of PD with an AUC as high as 0.947 (using an SN threshold of 50ppb and an NM threshold of 0.15). Finally, the SN_QSM volume showed a negative correlation with the MDS-UPDRS III (R² = 0.1, p = 0.036) and the Hoehn and Yahr scale (R² = 0.04, p = 0.013) in PD patients.

CONCLUSION

In summary, this fully automatic template based deep gray matter mapping approach performs well in the segmentation of the SN and its subregions for not only HCs but also PD patients with SN degeneration. The combination of the N1 sign with other quantitative measures (SN_NM volume, SN_QSM volume, SNpc volume and iron content) resulted in an AUC of 0.947 and provided a comprehensive set of imaging biomarkers that, potentially, could be used to diagnose PD clinically.

Imaging in Movement Disorders

OBJECTIVE

This article reviews commonly used imaging modalities in movement disorders, particularly parkinsonism. The review includes the diagnostic utility, role in differential diagnosis, reflection of pathophysiology, and limitations of neuroimaging in the setting of movement disorders. It also introduces promising new imaging modalities and describes the current status of research.

LATEST DEVELOPMENTS

Iron-sensitive MRI sequences and neuromelanin-sensitive MRI can be used to directly assess the integrity of nigral dopaminergic neurons and thus may reflect disease pathology and progression throughout the full range of severity in Parkinson disease (PD). The striatal uptake of presynaptic radiotracers in their terminal axons as currently assessed using clinically approved positron emission tomography (PET) or single-photon emission computed tomography (SPECT) imaging correlates with nigral pathology and disease severity only in early PD. Cholinergic PET, using radiotracers that target the presynaptic vesicular acetylcholine transporter, constitutes a substantial advance and may provide crucial insights into the pathophysiology of clinical symptoms such as dementia, freezing, and falls.

ESSENTIAL POINTS

In the absence of valid, direct, objective biomarkers of intracellular misfolded α-synuclein, PD remains a clinical diagnosis. The clinical utility of PET- or SPECT-based striatal measures is currently limited given their lack of specificity and inability to reflect nigral pathology in moderate to severe PD. These scans may be more sensitive than clinical examination to detect nigrostriatal deficiency that occurs in multiple parkinsonian syndromes and may still be recommended for clinical use in the future to identify prodromal PD if and when disease-modifying treatments become available. Multimodal imaging to evaluate underlying nigral pathology and its functional consequences may hold the key to future advances.

How should future clinical trials be designed in the search for disease-modifying therapies for Parkinson's disease?

INTRODUCTION

Although there has been substantial progress in research and innovations in symptomatic treatments, similar success has not been achieved in disease-modifying therapy (DMT) for Parkinson's disease (PD). Considering the enormous motor, psychosocial and financial burden associated with PD, safe and effective DMT is of paramount importance.

AREAS COVERED

One of the reasons for the lack of progress in DMT for PD is poor or inappropriate design of clinical trials. In the first part of the article, the authors focus on the plausible reasons why the previous trials have failed and in the latter part, they provide their perspectives on future DMT trials.

EXPERT OPINION

There are several potential reasons why previous trials have failed, including broad clinical and etiopathogenic heterogeneity of PD, poor definition and documentation of target engagement, lack of appropriate biomarkers and outcome measures, and short duration of follow-up. To address these deficiencies, future trials may consider- (i) a more customized approach to select the most suitable participants and therapeutic approaches, (ii) explore combination therapies that would target multiple pathogenetic mechanisms, and (iii) moving beyond targeting only motor symptoms to also assessing non-motor features of PD in well-designed longitudinal studies.

Regional age-related changes of neuromelanin and iron in the substantia nigra based on neuromelanin accumulation and iron deposition

OBJECTIVES

To investigate age-related neuromelanin signal variation and iron content changes in the subregions of substantia nigra (SN) using magnetization transfer contrast neuromelanin-sensitive multi-echo fast field echo sequence in a normal population.

METHODS

In this prospective study, 115 healthy volunteers between 20 and 86 years of age were recruited and scanned using 3.0-T MRI. We manually delineated neuromelanin accumulation and iron deposition regions in neuromelanin image and quantitative susceptibility mapping, respectively. We calculated the overlap region using the two measurements mentioned above. Partial correlation analysis was used to evaluate the correlations between volume, contrast ratio (CR), susceptibility of three subregions of SN, and age. Curve estimation models were used to find the best regression model.

RESULTS

CR increased with age (r = 0.379, p < 0.001; r = 0.371, p < 0.001), while volume showed an age-related decline (r =  -0.559, p < 0.001; r =  -0.410, p < 0.001) in the neuromelanin accumulation and overlap regions. Cubic polynomial regression analysis found a small increase in neuromelanin accumulation volume with age until 34, followed by a significant decrease until the 80 s (R² = 0.358, p < 0.001). No significant correlations were found between susceptibility and age in any subregion. No correlation was found between CR and susceptibility in the overlap region.

CONCLUSIONS

Our results indicated that CR increased with age, while volume showed an age-related decline in the overlap region. We further found that the neuromelanin accumulation region volume increased until the 30 s and decreased into the 80 s. This study may provide a reference for future neurodegenerative elucidations of substantia nigra.

KEY POINTS

• Our results define the regional changes in neuromelanin and iron in the substantia nigra with age in the normal population, especially in the overlap region. • The contrast ratio increased with age in the neuromelanin accumulation and overlap regions, and volume showed an age-related decline, while contrast ratio and volume do not affect each other indirectly. • The contrast ratio of hyperintense neuromelanin in the overlap region was unaffected by iron content.

Advances in the neuroimaging of motor disorders

Neuroimaging is a valuable adjunct to the history and examination in the evaluation of motor system disorders. Conventional imaging with computed tomography or magnetic resonance imaging depicts important anatomic information and helps to identify imaging patterns which may support diagnosis of a specific motor disorder. Advanced imaging techniques can provide further detail regarding volume, functional, or metabolic changes occurring in nervous system pathology. This chapter is an overview of the advances in neuroimaging with particular emphasis on both standard and less well-known advanced imaging techniques and findings, such as diffusion tensor imaging or volumetric studies, and their application to specific motor disorders. In addition, it provides reference to emerging imaging biomarkers in motor system disorders such as Parkinson disease, amyotrophic lateral sclerosis, and Huntington disease, and briefly reviews the neuroimaging findings in different causes of myelopathy and peripheral nerve disorders.

Magnetic resonance imaging modalities aid in the differential diagnosis of atypical parkinsonian syndromes

Accurate and timely diagnosis of atypical parkinsonian syndromes (APS) remains a challenge. Especially early in the disease course, the clinical manifestations of the APS overlap with each other and with those of idiopathic Parkinson's disease (PD). Recent advances in magnetic resonance imaging (MRI) technology have introduced promising imaging modalities to aid in the diagnosis of APS. Some of these MRI modalities are also included in the updated diagnostic criteria of APS. Importantly, MRI is safe for repeated use and more affordable and accessible compared to nuclear imaging. These advantages make MRI tools more appealing for diagnostic purposes. As the MRI field continues to advance, the diagnostic use of these techniques in APS, alone or in combination, are expected to become commonplace in clinical practice.

Corticospinal Suppression Underlying Intact Movement Preparation Fades in Parkinson's Disease

BACKGROUND

In Parkinson's disease (PD), neurophysiological abnormalities within the primary motor cortex (M1) have been shown to contribute to bradykinesia, but exact modalities are still uncertain. We propose that such motor slowness could involve alterations in mechanisms underlying movement preparation, especially the suppression of corticospinal excitability-called "preparatory suppression"-which is considered to propel movement execution by increasing motor neural gain in healthy individuals.

METHODS

On two consecutive days, 29 PD patients (on and off medication) and 29 matched healthy controls (HCs) underwent transcranial magnetic stimulation over M1, eliciting motor-evoked potentials (MEPs) in targeted hand muscles, while they were either at rest or preparing a left- or right-hand response in an instructed-delay choice reaction time task. Preparatory suppression was assessed by expressing MEP amplitudes during movement preparation relative to rest.

RESULTS

Contrary to HCs, PD patients showed a lack of preparatory suppression when the side of the responding hand was analyzed, especially when the latter was the most affected one. This deficit, which did not depend on dopamine medication, increased with disease duration and also tended to correlate with motor impairment, as measured by the Movement Disorder Society Unified Parkinson's Disease Rating Scale, Part III (both total and bradykinesia scores).

CONCLUSIONS

Our novel findings indicate that preparatory suppression fades in PD, in parallel with worsening motor symptoms, including bradykinesia. Such results suggest that an alteration in this marker of intact movement preparation could indeed cause motor slowness and support its use in future studies on the relation between M1 alterations and motor impairment in PD. © 2022 International Parkinson and Movement Disorder Society.

Sandwich spatial saturation for neuromelanin-sensitive MRI: Development and multi-center trial

Neuromelanin (NM)-sensitive MRI using a magnetization transfer (MT)-prepared T1-weighted sequence has been suggested as a tool to visualize NM contents in the brain. In this study, a new NM-sensitive imaging method, sandwichNM, is proposed by utilizing the incidental MT effects of spatial saturation RF pulses in order to generate consistent high-quality NM images using product sequences. The spatial saturation pulses are located both superior and inferior to the imaging volume, increasing MT weighting while avoiding asymmetric MT effects. When the parameters of the spatial saturation were optimized, sandwichNM reported a higher NM contrast ratio than those of conventional NM-sensitive imaging methods with matched parameters for comparability with sandwichNM (SandwichNM: 23.6 ± 5.4%; MT-prepared TSE: 20.6 ± 7.4%; MT-prepared GRE: 17.4 ± 6.0%). In a multi-vendor experiment, the sandwichNM images displayed higher means and lower standard deviations of the NM contrast ratio across subjects in all three vendors (SandwichNM vs. MT-prepared GRE; Vendor A: 28.4 ± 1.5% vs. 24.4 ± 2.8%; Vendor B: 27.2 ± 1.0% vs. 13.3 ± 1.3%; Vendor C: 27.3 ± 0.7% vs. 20.1 ± 0.9%). For each subject, the standard deviations of the NM contrast ratio across the vendors were substantially lower in SandwichNM (SandwichNM vs. MT-prepared GRE; subject 1: 1.5% vs. 8.1%, subject 2: 1.1 % vs. 5.1%, subject 3: 0.9% vs. 4.0%, subject 4: 1.1% vs. 5.3%), demonstrating consistent contrasts across the vendors. The proposed method utilizes product sequences, requiring no alteration of a sequence and, therefore, may have a wide practical utility in exploring the NM imaging.

Iron- and Neuromelanin-Weighted Neuroimaging to Study Mitochondrial Dysfunction in Patients with Parkinson's Disease

The underlying causes of Parkinson's disease are complex, and besides recent advances in elucidating relevant disease mechanisms, no disease-modifying treatments are currently available. One proposed pathophysiological hallmark is mitochondrial dysfunction, and a plethora of evidence points toward the interconnected nature of mitochondria in neuronal homeostasis. This also extends to iron and neuromelanin metabolism, two biochemical processes highly relevant to individual disease manifestation and progression. Modern neuroimaging methods help to gain in vivo insights into these intertwined pathways and may pave the road to individualized medicine in this debilitating disorder. In this narrative review, we will highlight the biological rationale for studying these pathways, how distinct neuroimaging methods can be applied in patients, their respective limitations, and which challenges need to be overcome for successful implementation in clinical studies.

Automated volumetric determination of high R2 * regions in substantia nigra: A feasibility study of quantifying substantia nigra atrophy in progressive supranuclear palsy

The establishment of an unbiased protocol for the automated volumetric measurement of iron-rich regions in the substantia nigra (SN) is clinically important for diagnosing neurodegenerative diseases exhibiting midbrain atrophy, such as progressive supranuclear palsy (PSP). This study aimed to automatically quantify the volume and surface properties of the iron-rich 3D regions in the SN using the quantitative MRI-R₂ ^* map. Three hundred and sixty-seven slices of R₂ ^* map and susceptibility-weighted imaging (SWI) at 3-T MRI from healthy control (HC) individuals and Parkinson's disease (PD) patients were used to train customized U-net++ convolutional neural network based on expert-segmented masks. Age- and sex-matched participants were selected from HC, PD, and PSP groups to automate the volumetric determination of iron-rich areas in the SN. Dice similarity coefficient values between expert-segmented and detected masks from the proposed network were 0.91 ± 0.07 for R₂ ^* maps and 0.89 ± 0.08 for SWI. Reductions in iron-rich SN volume from the R₂ ^* map (SWI) were observed in PSP with area under the receiver operating characteristic curve values of 0.96 (0.89) and 0.98 (0.92) compared with HC and PD, respectively. The mean curvature of the PSP showed SN deformation along the side closer to the red nucleus. We demonstrated the automated volumetric measurement of iron-rich regions in the SN using deep learning can quantify the SN atrophy in PSP compared with PD and HC.

NigraNet: An automatic framework to assess nigral neuromelanin content in early Parkinson's disease using convolutional neural network

BACKGROUND

Parkinson's disease (PD) demonstrates neurodegenerative changes in the substantia nigra pars compacta (SNc) using neuromelanin-sensitive (NM)-MRI. As SNc manual segmentation is prone to substantial inter-individual variability across raters, development of a robust automatic segmentation framework is necessary to facilitate nigral neuromelanin quantification. Artificial intelligence (AI) is gaining traction in the neuroimaging community for automated brain region segmentation tasks using MRI.

OBJECTIVE

Developing and validating AI-based NigraNet, a fully automatic SNc segmentation framework allowing nigral neuromelanin quantification in patients with PD using NM-MRI.

METHODS

We prospectively included 199 participants comprising 144 early-stage idiopathic PD patients (disease duration = 1.5 ± 1.0 years) and 55 healthy volunteers (HV) scanned using a 3 Tesla MRI including whole brain T1-weighted anatomical imaging and NM-MRI. The regions of interest (ROI) were delineated in all participants automatically using NigraNet, a modified U-net, and compared to manual segmentations performed by two experienced raters. The SNc volumes (Vol), volumes corrected by total intracranial volume (C_vol), normalized signal intensity (NSI) and contrast-to-noise ratio (CNR) were computed. One-way GLM-ANCOVA was performed while adjusting for age and sex as covariates. Diagnostic performance measurement was assessed using the receiver operating characteristic (ROC) analysis. Inter and intra-observer variability were estimated using Dice similarity coefficient (DSC). The agreements between methods were tested using intraclass correlation coefficient (ICC) based on a mean-rating, two-way, mixed-effects model estimates for absolute agreement. Cronbach's alpha and Bland-Altman plots were estimated to assess inter-method consistency.

RESULTS

Using both methods, Vol, C_vol, NSI and CNR measurements differed between PD and HV with an effect of sex for C_vol and CNR. ICC values between the methods demonstrated optimal agreement for C_vol and CNR (ICC > 0.9) and high reproducibility (DSC: 0.80) was also obtained. The SNc measurements also showed good to excellent consistency values (Cronbach's alpha > 0.87). Bland-Altman plots of agreement demonstrated no association of SNc ROI measurement differences between the methods and ROI average measurements while confirming that 95 % of the data points were ranging between the limits of mean difference (d ± 1.96xSD). Percentage changes between PD and HV were -27.4 % and -17.7 % for Vol, -30.0 % and -22.2 % for C_vol, -15.8 % and -14.4 % for NSI, -17.1 % and -16.0 % for CNR for automatic and manual measurements respectively. Using automatic method, in the entire dataset, we obtained the areas under the ROC curve (AUC) of 0.83 for Vol, 0.85 for C_vol, 0.79 for NSI and 0.77 for CNR whereas in the training dataset of 0.96 for Vol, 0.95 for C_vol, 0.85 for NSI and 0.85 for CNR. Disease duration correlated negatively with NSI of the patients for both the automatic and manual measurements.

CONCLUSIONS

We presented an AI-based NigraNet framework that utilizes a small MRI training dataset to fully automatize the SNc segmentation procedure with an increased precision and more reproducible results. Considering the consistency, accuracy and speed of our approach, this study could be a crucial step towards the implementation of a time-saving non-rater dependent fully automatic method for studying neuromelanin changes in clinical settings and large-scale neuroimaging studies.

Neuromelanin and T2*-MRI for the assessment of genetically at-risk, prodromal, and symptomatic Parkinson's disease

MRI was suggested as a promising method for the diagnosis and assessment of Parkinson's Disease (PD). We aimed to assess the sensitivity of neuromelanin-MRI and T₂* with radiomics analysis for detecting PD, identifying individuals at risk, and evaluating genotype-related differences. Patients with PD and non-manifesting (NM) participants [NM-carriers (NMC) and NM-non-carriers (NMNC)], underwent MRI and DAT-SPECT. Imaging-based metrics included 48 neuromelanin and T₂* radiomics features and DAT-SPECT specific-binding-ratios (SBR), were extracted from several brain regions. Imaging values were assessed for their correlations with age, differences between groups, and correlations with the MDS-likelihood-ratio (LR) score. Several machine learning classifiers were evaluated for group classification. A total of 127 participants were included: 46 patients with PD (62.3 ± 10.0 years) [15:LRRK2-PD, 16:GBA-PD, and 15:idiopathic-PD (iPD)], 47 NMC (51.5 ± 8.3 years) [24:LRRK2-NMC and 23:GBA-NMC], and 34 NMNC (53.5 ± 10.6 years). No significant correlations were detected between imaging parameters and age. Thirteen MRI-based parameters and radiomics features demonstrated significant differences between PD and NMNC groups. Support-Vector-Machine (SVM) classifier achieved the highest performance (AUC = 0.77). Significant correlations were detected between LR scores and two radiomic features. The classifier successfully identified two out of three NMC who converted to PD. Genotype-related differences were detected based on radiomic features. SBR values showed high sensitivity in all analyses. In conclusion, neuromelanin and T₂* MRI demonstrated differences between groups and can be used for the assessment of individuals at-risk in cases when DAT-SPECT can't be performed. Combining neuromelanin and T₂*-MRI provides insights into the pathophysiology underlying PD, and suggests that iron accumulation precedes neuromelanin depletion during the prodromal phase.

Intrasubject subcortical quantitative referencing to boost MRI sensitivity to Parkinson's disease

Several postmortem studies have shown iron accumulation in the substantia nigra of Parkinson's disease patients. Iron concentration can be estimated via MRI-R₂^∗ mapping. To assess the changes in R₂^∗ occurring in Parkinson's disease patients compared to controls, a multicentre transversal study was carried out on a large cohort of Parkinson's disease patients (n = 163) with matched controls (n = 82). In this study, 44 patients and 11 controls were removed due to motion artefacts, 21 patient and 6 controls to preserve matching. Thus, 98 patients and 65 age and sex-matched healthy subjects were selected with enough image quality. The study was conducted on patients with early to late stage Parkinson's disease. The images were acquired at 3Tesla in 12 clinical centres. R₂^∗ values were measured in subcortical regions of interest (substantia nigra, red nucleus, striatum, globus pallidus externus and globus pallidus internus) contralateral (dominant side) and ipsilateral (non dominant side) to the most clinically affected hemibody. As the observed inter-subject R₂^∗ variability was significantly higher than the disease effect, an original strategy (intrasubject subcortical quantitative referencing, ISQR) was developed using the measurement of R₂^∗ in the red nucleus as an intra-subject reference. R₂^∗ values significantly increased in Parkinson's disease patients when compared with controls; in the substantia nigra (SN) in the dominant side (D) and in the non dominant side (ND), respectively (P_{SN_D} and P_{SN_ND} < 0.0001). After stratification into four subgroups according to the disease duration, no significant R₂^∗ difference was found in all regions of interest when comparing Parkinson's disease subgroups. By applying our ISQR strategy, R_2(ISQR)^∗ values significantly increased in the substantia nigra (P_{SN_D} and P_{SN_ND} < 0.0001) when comparing all Parkinson's disease patients to controls. R_2(ISQR)^∗ values in the substantia nigra significantly increased with the disease duration (P_{SN_D} = 0.01; P_{SN_ND} = 0.03) as well as the severity of the disease (Hoehn & Yahr scale <2 and ≥ 2, P_{SN_D} = 0.02). Additionally, correlations between R_2(ISQR)^∗ and clinical features, mainly related to the severity of the disease, were found. Our results support the use of ISQR to reduce variations not directly related to Parkinson's disease, supporting the concept that ISQR strategy is useful for the evaluation of Parkinson's disease.

Relationship between Substantia Nigra Neuromelanin Imaging and Dual Alpha-Synuclein Labeling of Labial Minor in Salivary Glands in Isolated Rapid Eye Movement Sleep Behavior Disorder and Parkinson's Disease

We investigated the presence of misfolded alpha-Synuclein (α-Syn) in minor salivary gland biopsies in relation to substantia nigra pars compacta (SNc) damage measured using magnetic resonance imaging in patients with isolated rapid eye movement sleep behavior disorder (iRBD) and Parkinson's disease (PD) as compared to healthy controls. Sixty-one participants (27 PD, 16 iRBD, and 18 controls) underwent a minor salivary gland biopsy and were scanned using a 3 Tesla MRI. Deposits of α-Syn were found in 15 (55.6%) PD, 7 (43.8%) iRBD, and 7 (38.9%) controls using the anti-aggregated α-Syn clone 5G4 antibody and in 4 (14.8%) PD, 3 (18.8%) iRBD and no control using the purified mouse anti-α-Syn clone 42 antibody. The SNc damages obtained using neuromelanin-sensitive imaging did not differ between the participants with versus without α-Syn deposits (irrespective of the antibodies and the disease group). Our study indicated that the α-Syn detection in minor salivary gland biopsies lacks sensitivity and specificity and does not correlate with the SNc damage, suggesting that it cannot be used as a predictive or effective biomarker for PD.

New hope for Parkinson's disease treatment: Targeting gut microbiota

There might be more than 10 million confirmed cases of Parkinson's disease (PD) worldwide by 2040. However, the pathogenesis of PD is still unclear. Host health is closely related to gut microbiota, which are affected by factors such as age, diet, and exercise. Recent studies have found that gut microbiota may play key roles in the progression of a wide range of diseases, including PD. Changes in the abundance of gut bacteria, such as Helicobacter pylori, Enterococcus faecalis, and Desulfovibrio, might be involved in PD pathogenesis or interfere with PD therapy. Gut microbiota and the distal brain achieve action on each other through a gut‐brain axis composed of the nervous system, endocrine system, and immune system. Here, this review focused on the current understanding of the connection between Parkinson's disease and gut microbiota, to provide potential therapeutic targets for PD.

Altered Prefrontal Blood Flow Related With Mild Cognitive Impairment in Parkinson's Disease: A Longitudinal Study

Cognitive impairment is a common non-motor symptom in Parkinson's disease (PD), with executive dysfunction being an initial manifestation. We aimed to investigate whether and how longitudinal changes in the prefrontal perfusion correlate with mild cognitive impairment (MCI) in patients with PD. We recruited 49 patients with PD with normal cognition and 37 matched healthy control subjects (HCs). Patients with PD completed arterial spin labeling MRI (ASL–MRI) scans and a comprehensive battery of neuropsychological assessments at baseline (V0) and 2-year follow-up (V1). HCs completed similar ASL–MRI scans and neuropsychological assessments at baseline. At V1, 10 patients with PD progressed to MCI (converters) and 39 patients remained cognitively normal (non-converters). We examined differences in the cerebral blood flow (CBF) derived from ASL–MRI and neuropsychological measures (a) between patients with PD and HCs at V0 (effect of the disease), (b) between V1 and V0 in patients with PD (effect of the disease progression), and (c) between converters and non-converters (effect of the MCI progression) using t-tests or ANOVAs with false discovery rate correction. We further analyzed the relationship between longitudinal CBF and neuropsychological changes using multivariate regression models with false discovery rate correction, focusing on executive functions. At V0, no group difference was found in prefrontal CBF between patients with PD and HCs, although patients with PD showed worse performances on executive function. At V1, patients with PD showed significantly reduced CBF in multiple prefrontal regions, including the bilateral lateral orbitofrontal, medial orbitofrontal, middle frontal, inferior frontal, superior frontal, caudal anterior cingulate, and rostral anterior cingulate. More importantly, converters showed a more significant CBF reduction in the left lateral orbitofrontal cortex than non-converters. From V0 to V1, the prolonged completion time of Trail Making Test-B (TMT-B) negatively correlated with longitudinal CBF reduction in the right caudal anterior cingulate cortex. The decreased accuracy of the Stroop Color-Word Test positively correlated with longitudinal CBF reduction in the left medial orbitofrontal cortex. In addition, at V1, the completion time of TMT-B negatively correlated with CBF in the left caudal anterior cingulate cortex. Our findings suggest that longitudinal CBF reduction in the prefrontal cortex might impact cognitive functions (especially executive functions) at the early stages of PD.

Magnetic resonance and dopamine transporter imaging for the diagnosis of Parkinson´s disease: a narrative review

BACKGROUND

the diagnosis of Parkinson's disease (PD) can be challenging, especially in the early stages, albeit its updated and validated clinical criteria. Recent developments on neuroimaging in PD, altogether with its consolidated role of excluding secondary and other neurodegenerative causes of parkinsonism, provide more confidence in the diagnosis across the different stages of the disease. This review highlights current knowledge and major recent advances in magnetic resonance and dopamine transporter imaging in aiding PD diagnosis.

OBJECTIVE

This study aims to review current knowledge about the role of magnetic resonance imaging and neuroimaging of the dopamine transporter in diagnosing Parkinson's disease.

METHODS

We performed a non-systematic literature review through the PubMed database, using the keywords "Parkinson", "magnetic resonance imaging", "diffusion tensor", "diffusion-weighted", "neuromelanin", "nigrosome-1", "single-photon emission computed tomography", "dopamine transporter imaging". The search was restricted to articles written in English, published between January 2010 and February 2022.

RESULTS

The diagnosis of Parkinson's disease remains a clinical diagnosis. However, new neuroimaging biomarkers hold promise for increased diagnostic accuracy, especially in earlier stages of the disease.

CONCLUSION

Future validation of new imaging biomarkers bring the expectation of an increased neuroimaging role in the diagnosis of PD in the following years.

Regional Selectivity of Neuromelanin Changes in the Substantia Nigra in Atypical Parkinsonism

BACKGROUND

Neurodegeneration in the substantia nigra pars compacta (SNc) in parkinsonian syndromes may affect the nigral territories differently.

OBJECTIVE

The objective of this study was to investigate the regional selectivity of neurodegenerative changes in the SNc in patients with Parkinson's disease (PD) and atypical parkinsonism using neuromelanin-sensitive magnetic resonance imaging (MRI).

METHODS

A total of 22 healthy controls (HC), 38 patients with PD, 22 patients with progressive supranuclear palsy (PSP), 20 patients with multiple system atrophy (MSA, 13 with the parkinsonian variant, 7 with the cerebellar variant), 7 patients with dementia with Lewy body (DLB), and 4 patients with corticobasal syndrome were analyzed. volume and signal-to-noise ratio (SNR) values of the SNc were derived from neuromelanin-sensitive MRI in the whole SNc. Analysis of signal changes was performed in the sensorimotor, associative, and limbic territories of the SNc.

RESULTS

SNc volume and corrected volume were significantly reduced in PD, PSP, and MSA versus HC. Patients with PSP had lower volume, corrected volume, SNR, and contrast-to-noise ratio than HC and patients with PD and MSA. Patients with PSP had greater SNR reduction in the associative region than HC and patients with PD and MSA. Patients with PD had reduced SNR in the sensorimotor territory, unlike patients with PSP. Patients with MSA did not differ from patients with PD.

CONCLUSIONS

This study provides the first MRI comparison of the topography of neuromelanin changes in parkinsonism. The spatial pattern of changes differed between PSP and synucleinopathies. These nigral topographical differences are consistent with the topography of the extranigral involvement in parkinsonian syndromes. © 2022 International Parkinson and Movement Disorder Society.

Carving the senescent phenotype by the chemical reactivity of catecholamines: An integrative review

Macromolecules damaged by covalent modifications produced by chemically reactive metabolites accumulate in the slowly renewable components of living bodies and compromise their functions. Among such metabolites, catecholamines (CA) are unique, compared with the ubiquitous oxygen, ROS, glucose and methylglyoxal, in that their high chemical reactivity is confined to a limited set of cell types, including the dopaminergic and noradrenergic neurons and their direct targets, which suffer from CA propensities for autoxidation yielding toxic quinones, and for Pictet-Spengler reactions with carbonyl-containing compounds, which yield mitochondrial toxins. The functions progressively compromised because of that include motor performance, cognition, reward-driven behaviors, emotional tuning, and the neuroendocrine control of reproduction. The phenotypic manifestations of the resulting disorders culminate in such conditions as Parkinson's and Alzheimer's diseases, hypertension, sarcopenia, and menopause. The reasons to suspect that CA play some special role in aging accumulated since early 1970-ies. Published reviews address the role of CA hazardousness in the development of specific aging-associated diseases. The present integrative review explores how the bizarre discrepancy between CA hazardousness and biological importance could have emerged in evolution, how much does the chemical reactivity of CA contribute to the senescent phenotype in mammals, and what can be done with it.

Multimodal brain and retinal imaging of dopaminergic degeneration in Parkinson disease

Parkinson disease (PD) is a progressive disorder characterized by dopaminergic neurodegeneration in the brain. The development of parkinsonism is preceded by a long prodromal phase, and >50% of dopaminergic neurons can be lost from the substantia nigra by the time of the initial diagnosis. Therefore, validation of in vivo imaging biomarkers for early diagnosis and monitoring of disease progression is essential for future therapeutic developments. PET and single-photon emission CT targeting the presynaptic terminals of dopaminergic neurons can be used for early diagnosis by detecting axonal degeneration in the striatum. However, these techniques poorly differentiate atypical parkinsonian syndromes from PD, and their availability is limited in clinical settings. Advanced MRI in which pathological changes in the substantia nigra are visualized with diffusion, iron-sensitive susceptibility and neuromelanin-sensitive sequences potentially represents a more accessible imaging tool. Although these techniques can visualize the classic degenerative changes in PD, they might be insufficient for phenotyping or prognostication of heterogeneous aspects of PD resulting from extranigral pathologies. The retina is an emerging imaging target owing to its pathological involvement early in PD, which correlates with brain pathology. Retinal optical coherence tomography (OCT) is a non-invasive technique to visualize structural changes in the retina. Progressive parafoveal thinning and fovea avascular zone remodelling, as revealed by OCT, provide potential biomarkers for early diagnosis and prognostication in PD. As we discuss in this Review, multimodal imaging of the substantia nigra and retina is a promising tool to aid diagnosis and management of PD.

Neuromelanin-MRI to Quantify and Track Nigral Depigmentation in Parkinson's Disease: A Multicenter Longitudinal Study Using Template-Based Standardized Analysis

Background

Clinical diagnosis and monitoring of Parkinson's disease (PD) remain challenging because of the lack of an established biomarker. Neuromelanin‐magnetic resonance imaging (NM‐MRI) is an emerging biomarker of nigral depigmentation indexing the loss of melanized neurons but has unknown prospective diagnostic and tracking performance in multicenter settings.

Objectives

The aim was to investigate the diagnostic accuracy of NM‐MRI in early PD in a multiprotocol setting and to determine and compare serial NM‐MRI changes in PD and controls.

Methods

In this longitudinal case–control 3 T MRI study, 148 patients and 97 controls were included from six UK clinical centers, of whom 140 underwent a second scan after 1.5 to 3 years. An automated template‐based analysis was applied for subregional substantia nigra NM‐MRI contrast and volume assessment. A point estimate of the period of prediagnostic depigmentation was computed.

Results

All NM metrics performed well to discriminate patients from controls, with receiver operating characteristic showing 85% accuracy for ventral NM contrast and 83% for volume. Generalizability using a priori volume cutoff was good (79% accuracy). Serial MRI demonstrated accelerated NM loss in patients compared to controls. Ventral NM contrast loss was point estimated to start 5 to 6 years before clinical diagnosis. Ventral nigral depigmentation was greater in the most affected side, more severe cases, and nigral NM volume change correlated with change in motor severity.

Conclusions

We demonstrate that NM‐MRI provides clinically useful diagnostic information in early PD across protocols, platforms, and sites. It provides methods and estimated depigmentation rates that highlight the potential to detect preclinical PD and track progression for biomarker‐enabled clinical trials. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Dopamine Transporter Imaging, Current Status of a Potential Biomarker: A Comprehensive Review

A major goal of current clinical research in Parkinson's disease (PD) is the validation and standardization of biomarkers enabling early diagnosis, predicting outcomes, understanding PD pathophysiology, and demonstrating target engagement in clinical trials. Molecular imaging with specific dopamine-related tracers offers a practical indirect imaging biomarker of PD, serving as a powerful tool to assess the status of presynaptic nigrostriatal terminals. In this review we provide an update on the dopamine transporter (DAT) imaging in PD and translate recent findings to potentially valuable clinical practice applications. The role of DAT imaging as diagnostic, preclinical and predictive biomarker is discussed, especially in view of recent evidence questioning the incontrovertible correlation between striatal DAT binding and nigral cell or axon counts.

Emerging Neuroimaging Biomarkers Across Disease Stage in Parkinson Disease: A Review

Importance

Imaging biomarkers in Parkinson disease (PD) are increasingly important for monitoring progression in clinical trials and also have the potential to improve clinical care and management. This Review addresses a critical need to make clear the temporal relevance for diagnostic and progression imaging biomarkers to be used by clinicians and researchers over the clinical course of PD. Magnetic resonance imaging (diffusion imaging, neuromelanin-sensitive imaging, iron-sensitive imaging, T1-weighted imaging), positron emission tomography/single-photon emission computed tomography dopaminergic, serotonergic, and cholinergic imaging as well as metabolic and cerebral blood flow network neuroimaging biomarkers in the preclinical, prodromal, early, and moderate to late stages are characterized.

Observations

If a clinical trial is being carried out in the preclinical and prodromal stages, potentially useful disease-state biomarkers include dopaminergic imaging of the striatum; metabolic imaging; free-water, neuromelanin-sensitive, and iron-sensitive imaging in the substantia nigra; and T1-weighted structural magnetic resonance imaging. Disease-state biomarkers that can distinguish atypical parkinsonisms are metabolic imaging, free-water imaging, and T1-weighted imaging; dopaminergic imaging and other molecular imaging track progression in prodromal patients, whereas other established progression biomarkers need to be evaluated in prodromal cohorts. Progression in early-stage PD can be monitored using dopaminergic imaging in the striatum, metabolic imaging, and free-water and neuromelanin-sensitive imaging in the posterior substantia nigra. Progression in patients with moderate to late-stage PD can be monitored using free-water imaging in the anterior substantia nigra, R2* of substantia nigra, and metabolic imaging. Cortical thickness and gyrification might also be useful markers or predictors of progression. Dopaminergic imaging and free-water imaging detect progression over 1 year, whereas other modalities detect progression over 18 months or longer. The reliability of progression biomarkers varies with disease stage, whereas disease-state biomarkers are relatively consistent in individuals with preclinical, prodromal, early, and moderate to late-stage PD.

Conclusions and Relevance

Imaging biomarkers for various stages of PD are readily available to be used as outcome measures in clinical trials and are potentially useful in multimodal combination with routine clinical assessment. This Review provides a critically important template for considering disease stage when implementing diagnostic and progression biomarkers in both clinical trials and clinical care settings.

Update on neuroimaging for categorization of Parkinson's disease and atypical parkinsonism

PURPOSE OF REVIEW

Differential diagnosis of Parkinsonism may be difficult. The objective of this review is to present the work of the last three years in the field of imaging for diagnostic categorization of parkinsonian syndromes focusing on progressive supranuclear palsy (PSP) and multiple system atrophy (MSA).

RECENT FINDINGS

Two main complementary approaches are being pursued. The first seeks to develop and validate manual qualitative or semi-quantitative imaging markers that can be easily used in clinical practice. The second is based on quantitative measurements of magnetic resonance imaging abnormalities integrated in a multimodal approach and in automatic categorization machine learning tools.

SUMMARY

These two complementary approaches obtained high diagnostic around 90% and above in the classical Richardson form of PSP and probable MSA. Future work will determine if these techniques can improve diagnosis in other PSP variants and early forms of the diseases when all clinical criteria are not fully met.