PET imaging of synaptic density in Parkinsonian disorders.

Synaptic dysfunction and altered synaptic pruning are present in people with Parkinsonian disorders. Dopamine loss and alpha-synuclein accumulation, two hallmarks of Parkinson's disease (PD) pathology, contribute to synaptic dysfunction and reduced synaptic density in PD. Atypical Parkinsonian disorders are likely to have unique spatiotemporal patterns of synaptic density, differentiating them from PD. Therefore, quantification of synaptic density has the potential to support diagnoses, monitor disease progression, and treatment efficacy. Novel radiotracers for positron emission tomography which target the presynaptic vesicle protein SV2A have been developed to quantify presynaptic density. The radiotracers have successfully investigated synaptic density in preclinical models of PD and people with Parkinsonian disorders. Therefore, this review will summarize the preclinical and clinical utilization of SV2A radiotracers in people with Parkinsonian disorders. We will evaluate how SV2A abundance is associated with other imaging modalities and the considerations for interpreting SV2A in Parkinsonian pathology.

Cerebral Small Vessel Disease Progression Increases Risk of Incident Parkinsonism.

OBJECTIVE: Cerebral small vessel disease (SVD) is associated with motor impairments and parkinsonian signs cross-sectionally, however, there are little longitudinal data on whether SVD increases risk of incident parkinsonism itself. We investigated the relation between baseline SVD severity as well as SVD progression, and incident parkinsonism over a follow-up of 14 years. METHODS: This study included 503 participants with SVD, and without parkinsonism at baseline, from the RUN DMC prospective cohort study. Baseline inclusion was performed in 2006 and follow-up took place in 2011, 2015, and 2020, including magnetic resonance imaging (MRI) and motor assessments. Parkinsonism was diagnosed according to the UK Brain Bank criteria, and stratified into vascular parkinsonism (VaP) and idiopathic Parkinson's disease (IPD). Linear mixed-effect models were constructed to estimate individual rate changes of MRI-characteristics. RESULTS: Follow-up for incident parkinsonism was near-complete (99%). In total, 51 (10.2%) participants developed parkinsonism (33 VaP, 17 IPD, and 1 progressive supranuclear palsy). Patients with incident VaP had higher SVD burden compared with patients with IPD. Higher baseline white matter hyperintensities (hazard ratio [HR] = 1.46 per 1-SD increase, 95% confidence interval [CI] = 1.21-1.78), peak width of skeletonized mean diffusivity (HR = 1.66 per 1-SD increase, 95% CI = 1.34-2.05), and presence of lacunes (HR = 1.84, 95% CI = 0.99-3.42) were associated with increased risk of all-cause parkinsonism. Incident lacunes were associated with incident VaP (HR = 4.64, 95% CI = 1.32-16.32). INTERPRETATION: Both baseline SVD severity and SVD progression are independently associated with long-term parkinsonism. Our findings indicate a causal role of SVD in parkinsonism. Future studies are needed to examine the underlying pathophysiology of this relation. ANN NEUROL 2023;93:1130-1141.

International consensus on clinical use of presynaptic dopaminergic positron emission tomography imaging in parkinsonism.

PURPOSE: Presynaptic dopaminergic positron emission tomography (PET) imaging serves as an essential tool in diagnosing and differentiating patients with suspected parkinsonism, including idiopathic Parkinson's disease (PD) and other neurodegenerative and non-neurodegenerative diseases. The PET tracers most commonly used at the present time mainly target dopamine transporters (DAT), aromatic amino acid decarboxylase (AADC), and vesicular monoamine type 2 (VMAT2). However, established standards for the imaging procedure and interpretation of presynaptic dopaminergic PET imaging are still lacking. The goal of this international consensus is to help nuclear medicine practitioners procedurally perform presynaptic dopaminergic PET imaging. METHOD: A multidisciplinary task group formed by experts from various countries discussed and approved the consensus for presynaptic dopaminergic PET imaging in parkinsonism, focusing on standardized recommendations, procedures, interpretation, and reporting. CONCLUSION: This international consensus and practice guideline will help to promote the standardized use of presynaptic dopaminergic PET imaging in parkinsonism. It will become an international standard for this purpose in clinical practice.

Contribution of MRI for the Early Diagnosis of Parkinsonism in Patients with Diagnostic Uncertainty.

BACKGROUND: International clinical criteria are the reference for the diagnosis of degenerative parkinsonism in clinical research, but they may lack sensitivity and specificity in the early stages. OBJECTIVES: To determine whether magnetic resonance imaging (MRI) analysis, through visual reading or machine-learning approaches, improves diagnostic accuracy compared with clinical diagnosis at an early stage in patients referred for suspected degenerative parkinsonism. MATERIALS: Patients with initial diagnostic uncertainty between Parkinson's disease (PD), progressive supranuclear palsy (PSP), and multisystem atrophy (MSA), with brain MRI performed at the initial visit (V1) and available 2-year follow-up (V2), were included. We evaluated the accuracy of the diagnosis established based on: (1) the international clinical diagnostic criteria for PD, PSP, and MSA at V1 ("Clin1"); (2) MRI visual reading blinded to the clinical diagnosis ("MRI"); (3) both MRI visual reading and clinical criteria at V1 ("MRI and Clin1"), and (4) a machine-learning algorithm ("Algorithm"). The gold standard diagnosis was established by expert consensus after a 2-year follow-up. RESULTS: We recruited 113 patients (53 with PD, 31 with PSP, and 29 with MSA). Considering the whole population, compared with clinical criteria at the initial visit ("Clin1": balanced accuracy, 66.2%), MRI visual reading showed a diagnostic gain of 14.3% ("MRI": 80.5%; P = 0.01), increasing to 19.2% when combined with the clinical diagnosis at the initial visit ("MRI and Clin1": 85.4%; P < 0.0001). The algorithm achieved a diagnostic gain of 9.9% ("Algorithm": 76.1%; P = 0.08). CONCLUSION: Our study shows the use of MRI analysis, whether by visual reading or machine-learning methods, for early differentiation of parkinsonism. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Practical Overview of 123I-Ioflupane Imaging in Parkinsonian Syndromes.

Parkinsonian syndromes are a heterogeneous group of progressive neurodegenerative disorders involving the nigrostriatal dopaminergic pathway and are characterized by a wide spectrum of motor and nonmotor symptoms. These syndromes are quite common and can profoundly impact the lives of patients and their families. In addition to classic Parkinson disease, parkinsonian syndromes include multiple additional disorders known collectively as Parkinson-plus syndromes or atypical parkinsonism. These are characterized by the classic parkinsonian motor symptoms with additional distinguishing clinical features. Dopamine transporter SPECT has been developed as a diagnostic tool to assess the levels of dopamine transporters in the striatum. This imaging assessment, which uses iodine 123 (123I) ioflupane, can be useful to differentiate parkinsonian syndromes caused by nigrostriatal degeneration from other clinical mimics such as essential tremor or psychogenic tremor. Dopamine transporter imaging plays a crucial role in diagnosing parkinsonian syndromes, particularly in patients who do not clearly fulfill the clinical criteria for diagnosis. Diagnostic clarification can allow early treatment in appropriate patients and avoid misdiagnosis. At present, only the qualitative interpretation of dopamine transporter SPECT is approved by the U.S. Food and Drug Administration, but quantitative interpretation is often used to supplement qualitative interpretation. The authors provide an overview of patient preparation, common imaging findings, and potential pitfalls that radiologists and nuclear medicine physicians should know when performing and interpreting dopamine transporter examinations. Alternatives to 123I-ioflupane imaging for the evaluation of nigrostriatal degeneration are also briefly discussed. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Intenzo and Colarossi in this issue.

Resting-State Functional MRI Approaches to Parkinsonisms and Related Dementia.

PURPOSE OF THE REVIEW: In this review, we attempt to summarize the most updated studies that applied resting-state functional magnetic resonance imaging (rs-fMRI) in the field of Parkinsonisms and related dementia. RECENT FINDINGS: Over the past decades, increasing interest has emerged on investigating the presence and pathophysiology of cognitive symptoms in Parkinsonisms and their possible role as predictive biomarkers of neurodegenerative brain processes. In recent years, evidence has been provided, applying mainly three methodological approaches (i.e. seed-based, network-based and graph-analysis) on rs-fMRI data, with promising results. Neural correlates of cognitive impairment and dementia have been detected in patients with Parkinsonisms along the diseases course. Interestingly, early functional connectivity signatures were proposed to track and predict future progression of neurodegenerative processes. However, longitudinal studies are still sparce and further investigations are needed to overcome this knowledge gap.

Progression of atypical parkinsonian syndromes: PROSPECT-M-UK study implications for clinical trials.

The advent of clinical trials of disease-modifying agents for neurodegenerative disease highlights the need for evidence-based end point selection. Here we report the longitudinal PROSPECT-M-UK study of progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), multiple system atrophy (MSA) and related disorders, to compare candidate clinical trial end points. In this multicentre UK study, participants were assessed with serial questionnaires, motor examination, neuropsychiatric and MRI assessments at baseline, 6 and 12 months. Participants were classified by diagnosis at baseline and study end, into Richardson syndrome, PSP-subcortical (PSP-parkinsonism and progressive gait freezing subtypes), PSP-cortical (PSP-frontal, PSP-speech and language and PSP-CBS subtypes), MSA-parkinsonism, MSA-cerebellar, CBS with and without evidence of Alzheimer's disease pathology and indeterminate syndromes. We calculated annual rate of change, with linear mixed modelling and sample sizes for clinical trials of disease-modifying agents, according to group and assessment type. Two hundred forty-three people were recruited [117 PSP, 68 CBS, 42 MSA and 16 indeterminate; 138 (56.8%) male; age at recruitment 68.7 ± 8.61 years]. One hundred and fifty-nine completed the 6-month assessment (82 PSP, 27 CBS, 40 MSA and 10 indeterminate) and 153 completed the 12-month assessment (80 PSP, 29 CBS, 35 MSA and nine indeterminate). Questionnaire, motor examination, neuropsychiatric and neuroimaging measures declined in all groups, with differences in longitudinal change between groups. Neuroimaging metrics would enable lower sample sizes to achieve equivalent power for clinical trials than cognitive and functional measures, often achieving N < 100 required for 1-year two-arm trials (with 80% power to detect 50% slowing). However, optimal outcome measures were disease-specific. In conclusion, phenotypic variance within PSP, CBS and MSA is a major challenge to clinical trial design. Our findings provide an evidence base for selection of clinical trial end points, from potential functional, cognitive, clinical or neuroimaging measures of disease progression.

Progressive gray matter atrophy in parkinsonian variant of multiple system atrophy assessed by using causal structural covariance network.

INTRODUCTION: Multiple system atrophy (MSA), a rare neurodegenerative disease, is usually accompanied by brain morphological alterations. However, the causal relationships between progressive gray matter atrophy in MSA parkinsonian (MSA-P) subtype remain unknown. METHODS: In total, thirty-five MSA-P patients and thirty-five healthy controls (HC) underwent three-dimensional high-resolution T1-weighted structural imaging and voxel-based morphometry analysis. The causal structural covariance network (CaSCN) of gray matter was assessed to explore the causal relationships in MSA-P. RESULTS: With greater illness duration, the reduction of gray matter was originated from right cerebellum and progressed to bilateral cerebellum, fusiform gyrus, insula, putamen, caudate nucleus, frontal lobe, right angular gyrus, right precuneus, left middle occipital lobe and left inferior temporal lobe, then expanded to midbrain, bilateral para-hippocampus, thalamus, temporal lobe, inferior parietal lobule (IPL), precentral gyrus, postcentral gyrus and middle cingulate cortex. The right cerebellum was revealed to be the core node of the directional network and projected positive causal effects to bilateral cerebellum, caudate nucleus and left IPL. CONCLUSION: MSA-P patients showed progression of gray matter atrophy over time, with the right cerebellum probably as a primary hub. Furthermore, the early structural vulnerability of cerebellum in MSA-P may play a pivotal role in the modulation of motor and non-motor circuits at the structural level.

Rapidly progressive multiple system atrophy in a patient carrying LRRK2 G2019S mutation.

BACKGROUND: Multiple system atrophy (MSA) is considered a primarily sporadic neurodegenerative disease, but the role of genetic is poorly understood. CASE: We present a female patient of Moroccan origin who developed a rapidly progressive non-levodopa responsive parkinsonism, gait and balance problems, and dysautonomia including severe bulbar symptoms. She was diagnosed with MSA Parkinsonian-type (MSA-P) and suddenly died at night at 58 years of age. Reduced striatal DAT-SPECT, putaminal hyperintensity on T2-MRI, and hypometabolism with FDG-PET were present. Genetic testing documented a G2019S mutation in the LRRK2 gene. A skin biopsy was obtained and used to perform alpha-synuclein RT-QuIC, which was negative, and immunohistochemical analysis, which demonstrated abnormal alpha-synuclein deposits in cutaneous nerves. Elevated blood neurofilament light chain levels were also documented. CONCLUSIONS: LRRK2 mutations are the most common cause of monogenic Parkinson's disease (PD) and G2019S is the most frequent variant. Our patient presented with biological, clinical, and radiological features of MSA, but genetic testing revealed a G2019S LRRK2 mutation, which has been previously reported only in one other case of pathologically proven MSA but with mild progression. In our patient, post-mortem confirmation could not be performed, but RT-QuIC and immunohistochemical findings on skin biopsy support the diagnosis of MSA. G2019S LRRK2 may be linked to an increased risk of MSA. Cases of atypical parkinsonism with rapid disease course should be screened for PD-related genes especially in populations with a high prevalence of mutations in known genes.

Clinical features, disease progression, and nuclear imaging in ATXN2-related parkinsonism in a longitudinal cohort.

BACKGROUND: Spinocerebellar ataxia 2 (SCA2) with a low range of CAG repeat expansion of ATXN2 gene can present with predominant or isolated parkinsonism that closely resembles Parkinson's disease (PD). This study is aimed at comparing clinical features, disease progression, and nuclear imaging between ATXN2-related parkinsonism (ATXN2-P) and PD. METHODS: Three hundred and seventy-seven clinically diagnosed PD with family history were screened by multiplex ligation-dependent probe amplification, whole-exome sequencing or target sequencing, and dynamic mutation testing of 10 SCA subtypes. The baseline and longitudinal clinical features as well as the dual-tracer positron emission tomography (PET) imaging were compared between ATXN2-P and genetically undefined familial PD (GU-fPD). RESULTS: Fifteen ATXN2-P patients from 7 families and 50 randomly selected GU-fPD patients were evaluated. Significantly less resting tremor and more symmetric signs were observed in ATXN2-P than GU-fPD. No significant difference was found in motor progression and duration from onset to occurrence of fluctuation, dyskinesia, and recurrent falls between the two groups. Cognitive impairment and rapid-eye-movement sleep behavior disorder were more common in ATXN2-P. During follow-up, olfaction was relatively spared, and no obvious progression of cognition dysfunction evaluated by Mini-Mental State Examination scores was found in ATXN2-P. PET results of ATXN2-P demonstrated a symmetric, diffuse, and homogenous dopamine transporter loss of bilateral striatum and a glucose metabolism pattern inconsistent with that in PD. CONCLUSIONS: Symmetric motor signs and unique nuclear imaging might be the clues to distinguish ATXN2-P from GU-fPD.

No impact of attenuation and scatter correction on the interpretation of dopamine transporter SPECT in patients with clinically uncertain parkinsonian syndrome.

PURPOSE: The benefit from attenuation and scatter correction (ASC) of dopamine transporter (DAT)-SPECT for the detection of nigrostriatal degeneration in clinical routine is still a matter of debate. The current study evaluated the impact of ASC on visual interpretation and semi-quantitative analysis of DAT-SPECT in a large patient sample. METHODS: One thousand seven hundred forty consecutive DAT-SPECT with 123I-FP-CIT from clinical routine were included retrospectively. SPECT images were reconstructed iteratively without and with ASC. Attenuation correction was based on uniform attenuation maps, scatter correction on simulation. All SPECT images were categorized with respect to the presence versus the absence of Parkinson-typical reduction of striatal 123I-FP-CIT uptake by three independent readers. Image reading was performed twice to assess intra-reader variability. The specific 123I-FP-CIT binding ratio (SBR) was used for automatic categorization, separately with and without ASC. RESULTS: The mean proportion of cases with discrepant categorization by the same reader between the two reading sessions was practically the same without and with ASC, about 2.2%. The proportion of DAT-SPECT with discrepant categorization without versus with ASC by the same reader was 1.66% ± 0.50% (1.09-1.95%), not exceeding the benchmark of 2.2% from intra-reader variability. This also applied to automatic categorization of the DAT-SPECT images based on the putamen SBR (1.78% discrepant cases between without versus with ASC). CONCLUSION: Given the large sample size, the current findings provide strong evidence against a relevant impact of ASC with uniform attenuation and simulation-based scatter correction on the clinical utility of DAT-SPECT to detect nigrostriatal degeneration in patients with clinically uncertain parkinsonian syndrome.

Magnetic Susceptibility in Progressive Supranuclear Palsy Variants, Parkinson's Disease, and Corticobasal Syndrome.

BACKGROUND: Previous studies have shown that magnetic susceptibility is increased in several subcortical regions in progressive supranuclear palsy (PSP). However, it is still unclear how subcortical and cortical susceptibilities vary across different PSP variants, Parkinson's disease (PD), and corticobasal syndrome (CBS). OBJECTIVE: This study aims to clarify the susceptibility profiles in the subcortical and cortical regions in different PSP variants, PD, and CBS. METHODS: Sixty-four patients, 20 PSP-Richardson syndrome (PSP-RS), 9 PSP-parkinsonism (PSP-P), 7 PSP-progressive gait freezing, 4 PSP-postural instability, 11 PD, and 13 CBS, and 20 cognitively normal control subjects underwent a 3-Tesla magnetic resonance imaging scan to reconstruct quantitative susceptibility maps. Region-of-interest analysis was performed to obtain susceptibility in several subcortical and cortical regions. Bayesian linear mixed effect models were used to estimate susceptibility within group and differences between groups. RESULTS: In the subcortical regions, patients with PSP-RS and PSP-P showed greater susceptibility than control subjects in the pallidum, substantia nigra, red nucleus, and cerebellar dentate (P < 0.05). Patients with PSP-RS also showed greater susceptibility than patients with PSP-progressive gait freezing, PD, and CBS in the red nucleus and cerebellar dentate, and patients with PSP-P showed greater susceptibility than PD in the red nucleus. Patients with PSP-postural instability and CBS showed greater susceptibility than control subjects in the pallidum and substantia nigra. No significant differences were observed in any cortical region. CONCLUSIONS: The PSP variants and CBS had different patterns of magnetic susceptibility in the subcortical regions. The findings will contribute to our understanding about iron profiles and pathophysiology of PSP and may provide a potential biomarker to differentiate PSP variants, PD, and CBS. © 2023 International Parkinson and Movement Disorder Society.

Slowing of Frontal ß Oscillations in Atypical Parkinsonism.

BACKGROUND: Diagnosis of atypical parkinsonian syndromes (APS) mostly relies on clinical presentation as well as structural and molecular brain imaging. Whether parkinsonian syndromes are distinguishable based on neuronal oscillations has not been investigated so far. OBJECTIVE: The aim was to identify spectral properties specific to atypical parkinsonism. METHODS: We measured resting-state magnetoencephalography in 14 patients with corticobasal syndrome (CBS), 16 patients with progressive supranuclear palsy (PSP), 33 patients with idiopathic Parkinson's disease, and 24 healthy controls. We compared spectral power as well as amplitude and frequency of power peaks between groups. RESULTS: Atypical parkinsonism was associated with spectral slowing, distinguishing both CBS and PSP from Parkinson's disease (PD) and age-matched healthy controls. Patients with atypical parkinsonism showed a shift in ß peaks (13-30 Hz) toward lower frequencies in frontal areas bilaterally. A concomitant increase in θ/α power relative to controls was observed in both APS and PD. CONCLUSION: Spectral slowing occurs in atypical parkinsonism, affecting frontal ß oscillations in particular. Spectral slowing with a different topography has previously been observed in other neurodegenerative disorders, such as Alzheimer's disease, suggesting that spectral slowing might be an electrophysiological marker of neurodegeneration. As such, it might support differential diagnosis of parkinsonian syndromes in the future. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Plasma Biomarkers and Positron Emission Tomography Tau Pathology in Progressive Supranuclear Palsy.

BACKGROUND: Development of disease-modifying therapeutic trials of progressive supranuclear palsy (PSP) urges the need for sensitive fluid biomarkers. OBJECTIVES: The objectives of this study were to explore the utility of plasma biomarkers in the diagnosis, differential diagnosis, and assessment of disease severity, brain atrophy, and tau deposition in PSP. METHODS: Plasma biomarkers were measured using a single-molecule array in a cohort composed of patients with PSP, Parkinson's disease (PD), multiple system atrophy with predominant parkinsonism (MSA-P), and healthy controls (HCs). RESULTS: Plasma neurofilament light chain (NfL) outperformed other plasma makers (ie, glial fibrillary acidic protein [GFAP], phosphorylated-tau 181 [p-tau181], amyloid-ß 1-40, amyloid-ß 1-42) in identifying PSP from HC (area under the curve [AUC] = 0.904) and from MSA-P (AUC = 0.711). Plasma GFAP aided in distinguishing PSP from HC (AUC = 0.774) and from MSA-P (AUC = 0.832). It correlated with brainstem atrophy and higher regional tau accumulation. However, plasma p-tau181 neither helped in diagnosis nor was it associated with clinical or neuroimaging measures. CONCLUSIONS: Plasma NfL and GFAP showed different values in differentiating PSP from HC or controls with other forms of neurodegenerative parkinsonism and detecting disease severity, brain atrophy, or tau deposition in PSP. © 2023 International Parkinson and Movement Disorder Society.

Correlations between cerebrospinal fluid homovanillic acid and dopamine transporter SPECT in degenerative parkinsonian syndromes.

Both cerebrospinal fluid (CSF) homovanillic acid (HVA) and striatal dopamine transporter (DAT) binding on single-photon emission computed tomography (SPECT) reflect nigrostriatal dopaminergic function, but studies on the relationship between the two have been limited. It is also unknown whether the reported variance in striatal DAT binding among diseases reflects the pathophysiology or characteristics of the subjects. We included 70 patients with Parkinson's disease (PD), 12 with progressive supranuclear palsy (PSP), 12 with multiple system atrophy, six with corticobasal syndrome, and nine with Alzheimer's disease as disease control, who underwent both CSF analysis and 123I-N-ω-fluoropropyl-2ß-carbomethoxy-3ß-(4-iodophenyl)nortropane (123I-ioflupane) SPECT. We evaluated the correlation between CSF HVA concentration and the specific binding ratio (SBR) of striatal DAT binding. We also compared the SBR for each diagnosis, controlling for CSF HVA concentration. The correlations between the two were significant in patients with PD (r = 0.34, p = 0.004) and PSP (r = 0.77, p = 0.004). The mean SBR value was the lowest in patients with PSP and was significantly lower in patients with PSP than in those with PD (p = 0.037) after adjusting for CSF HVA concentration. Our study demonstrates that striatal DAT binding correlates with CSF HVA concentration in both PD and PSP, and striatal DAT reduction would be more advanced in PSP than in PD at an equivalent dopamine level. Striatal DAT binding may correlate with dopamine levels in the brain. The pathophysiology of each diagnosis may explain this difference.

Comparative analysis of freezing of gait in distinct Parkinsonism types by diffusion tensor imaging method and cognitive profiles.

Freezing of gait (FOG) is an episodic gait pattern that is common in advanced Parkinson's disease (PD) and other atypical parkinsonism syndromes. Recently, disturbances in the pedunculopontine nucleus (PPN) and its connections have been suggested to play a critical role in the development of FOG. In this study, we aimed to demonstrate possible disturbances in PPN and its connections by performing the diffusion tensor imaging (DTI) technique. We included 18 patients of PD with FOG [PD-FOG], 13 patients of PD without FOG [PD-nFOG] and 12 healthy subjects as well as a group of patients with progressive supranuclear palsy (PSP), an atypical parkinsonism syndrome which is very often complicated with FOG [6 PSP-FOG, 5 PSP-nFOG]. To determine the specific cognitive parameters that can be related to FOG, deliberate neurophysiological evaluations of all the individuals were performed. The comparative analyses and correlation analyses were performed to reveal the neurophysiological and DTI correlates of FOG in either group. We have found disturbances in values reflecting microstructural integrity of the bilateral superior frontal gyrus (SFG), bilateral fastigial nucleus (FN), left pre-supplementary motor area (SMA) in the PD-FOG group relative to the PD-nFOG group. The analysis of the PSP group also demonstrated disturbance in left pre-SMA values in the PSP-FOG group likewise, while negative correlations were determined between right STN, left PPN values and FOG scores. In neurophysiological assessments, lower performances for visuospatial functions were demonstrated in FOG ( +) individuals for either patient group. The disturbances in the visuospatial abilities may be a critical step for the occurrence of FOG. Together with the results of DTI analyses, it might be suggested that impairment in the connectivity of disturbed frontal areas with disordered basal ganglia, maybe the key factor for the occurrence of FOG in the PD group, whereas left PPN which is a nondopaminergic nucleus may play a more prominent role in the process of FOG in PSP. Moreover, our results support the relationship between right STN, and FOG as mentioned before, as well as introduce the importance of FN as a new structure that may be involved in FOG pathogenesis.

Accurate measurement of magnetic resonance parkinsonism index by a fully automatic and deep learning quantification pipeline.

OBJECTIVES: This study aims at a fully automatic pipeline for measuring the magnetic resonance parkinsonism index (MRPI) using deep learning methods. METHODS: MRPI is defined as the product of the pons area to the midbrain area ratio and the middle cerebellar peduncle (MCP) width to the superior cerebellar peduncle (SCP) width ratio. In our proposed pipeline, we first used nnUNet to segment the brainstem and then employed HRNet to identify two key boundary points so as to sub-divide the whole brainstem into midbrain and pons. HRNet was also employed to predict the MCP endpoints for measuring the MCP width. Finally, we segmented the SCP on an oblique coronal plane and calculated its width. A total of 400 T1-weighted magnetic resonance images (MRIs) were used to train the nnUNet and HRNet models. Five-fold cross-validation was conducted to evaluate our proposed pipeline's performance on the training dataset. We also evaluated the performance of our proposed pipeline on three external datasets. Two of them had two raters manually measuring the MRPI values, providing insights into automatic accuracy versus inter-rater variability. RESULTS: We obtained average absolute percentage errors (APEs) of 17.21%, 18.17%, 20.83%, and 22.83% on the training dataset and the three external validation datasets, while the inter-rater average APE measured on the first two external validation datasets was 11.31%. Our proposed pipeline significantly improved the MRPI quantification accuracy over a representative state-of-the-art traditional approach (p < 0.001). CONCLUSION: The proposed automatic pipeline can accurately predict MRPI that is comparable with manual measurement. CLINICAL RELEVANCE STATEMENT: This study presents an automated magnetic resonance parkinsonism index measurement tool that can analyze large amounts of magnetic resonance images, enhance the efficiency of Parkinsonism-Plus syndrome diagnosis, reduce the workload of clinicians, and minimize the impact of human factors on diagnosis. KEY POINTS: • We propose an automatic pipeline for measuring the magnetic resonance parkinsonism index from magnetic resonance images. • The effectiveness of the proposed pipeline is successfully established on multiple datasets and comparisons with inter-rater measurements. • The proposed pipeline significantly outperforms a state-of-the-art quantification approach, being much closer to ground truth.

Structural and Molecular Imaging for Clinically Uncertain Parkinsonism.

Neuroimaging is an important adjunct to the clinical assessment of Parkinson disease (PD). Parkinsonism can be challenging to differentiate, especially in early disease stages, when it mimics other movement disorders or when there is a poor response to dopaminergic therapies. There is also a discrepancy between the phenotypic presentation of degenerative parkinsonism and the pathological outcome. The emergence of more sophisticated and accessible neuroimaging can identify molecular mechanisms of PD, the variation between clinical phenotypes, and the compensatory mechanisms that occur with disease progression. Ultra-high-field imaging techniques have improved spatial resolution and contrast that can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. We highlight the imaging modalities that can be accessed in clinical practice and recommend an approach to the diagnosis of clinically uncertain parkinsonism.

Parkinsonism in spinocerebellar ataxia with axonal neuropathy caused by adult-onset COA7 variants: a case report.

BACKGROUND: Individuals with variants of cytochrome c oxidase assembly factor 7 (COA7), a mitochondrial functional-related gene, exhibit symptoms of spinocerebellar ataxia with axonal neuropathy before the age of 20. However, COA7 variants with parkinsonism or adult-onset type cases have not been described. CASE PRESENTATION: We report the case of a patient who developed cerebellar symptoms and slowly progressive sensory and motor neuropathy in the extremities, similar to Charcot-Marie-Tooth disease, at age 30, followed by parkinsonism at age 58. Exome analysis revealed COA7 missense mutation in homozygotes (NM_023077.2:c.17A > G, NP_075565.2: p.Asp6Gly). Dopamine transporter single-photon emission computed tomography using a 123I-Ioflupane revealed clear hypo-accumulation in the bilateral striatum. However, 123I-metaiodobenzylguanidine myocardial scintigraphy showed normal sympathetic nerve function. Levodopa administration improved parkinsonism in this patient. CONCLUSIONS: COA7 gene variants may have caused parkinsonism in this case because mitochondrial function-related genes, such as parkin and PINK1, are known causative genes in some familial Parkinson's diseases.

Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake.

PURPOSE: Nigrosome imaging using susceptibility-weighted imaging (SWI) and dopamine transporter imaging using 123I-2ß-carbomethoxy-3ß-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (123I-FP-CIT) single-photon emission computerized tomography (SPECT) can evaluate Parkinsonism. Nigral hyperintensity from nigrosome-1 and striatal dopamine transporter uptake are reduced in Parkinsonism; however, quantification is only possible with SPECT. Here, we aimed to develop a deep-learning-based regressor model that can predict striatal 123I-FP-CIT uptake on nigrosome magnetic resonance imaging (MRI) as a biomarker for Parkinsonism. METHODS: Between February 2017 and December 2018, participants who underwent 3 T brain MRI including SWI and 123I-FP-CIT SPECT based on suspected Parkinsonism were included. Two neuroradiologists evaluated the nigral hyperintensity and annotated the centroids of nigrosome-1 structures. We used a convolutional neural network-based regression model to predict striatal specific binding ratios (SBRs) measured via SPECT using the cropped nigrosome images. The correlation between measured and predicted SBRs was evaluated. RESULTS: We included 367 participants (203 women (55.3%); age, 69.0 ± 9.2 [range, 39-88] years). Random data from 293 participants (80%) were used for training. In the test set (74 participants [20%]), the measured and predicted 123I-FP-CIT SBRs were significantly lower with the loss of nigral hyperintensity (2.31 ± 0.85 vs. 2.44 ± 0.90) than with intact nigral hyperintensity (4.16 ± 1.24 vs. 4.21 ± 1.35, P < 0.01). The sorted measured 123I-FP-CIT SBRs and the corresponding predicted values were significantly and positively correlated (ρc = 0.7443; 95% confidence interval, 0.6216-0.8314; P < 0.01). CONCLUSION: A deep learning-based regressor model effectively predicted striatal 123I-FP-CIT SBRs based on nigrosome MRI with high correlation using manually-measured values, enabling nigrosome MRI as a biomarker for nigrostriatal dopaminergic degeneration in Parkinsonism.