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Increased echogenicity of the substantia nigra (SN), as determined by transcranial sonography (TCS), is characteristic of idiopathic Parkinson's disease (iPD). The results of initial retrospective studies indicate that this ultrasound sign is specific for iPD and can help to differentiate it from atypical parkinsonian syndromes (aPS); however, these early studies were done in patients with later disease stages and known clinical diagnosis. We aimed to determine the diagnostic value of TCS in the early stages of parkinsonian syndromes, when the clinical symptoms often do not enable a definite diagnosis to be made. 60 patients who presented with the first, but still unclear, clinical symptoms of parkinsonism had TCS in this prospective blinded study. Investigators were blinded to the results of the clinical investigations, the ultrasound findings, and the diagnosis at time of investigation. The patients were followed-up every 3 months for 1 year to assess and re-evaluate the clinical symptoms. The patients in whom a clinical diagnosis could not be made with certainty were investigated with raclopride PET or dopamine transporter single-photon emission computed tomography (SPECT), or both. A clinical diagnosis of parkinsonism could not be established at baseline in 38 patients. At 12 months, 39 patients were clinically categorised as having iPD. Compared with endpoint diagnosis, the sensitivity of TCS at baseline was 90%7% and the specificity was 82·4%; the positive predictive value of TCS for iPD was 92·9% and the classification accuracy was 88·3%. TCS is an easy to implement, non-invasive, and inexpensive technique that could help in the early differential diagnosis of parkinsonian syndromes. The routine use of TCS in the clinic could enable disease-specific therapy to be started earlier. Michael J Fox Foundation for Parkinson's Research.

Background Cognitive dysfunction is increasingly recognized in multiple system atrophy (MSA). Locus coeruleus (LC) integrity is associated with cognitive performance both in healthy controls (HC) and neurodegenerative conditions such as Parkinson’s disease (PD). Furthermore, cortical glucose hypometabolism is associated with impaired cognitive performance in MSA. However, knowledge about LC sub-regional degeneration and its association with cognitive dysfunction and cortical glucose metabolism is lacking. Objective To investigate LC sub-regional involvement and its association with cognitive impairment and brain metabolism in MSA. Methods Eleven MSA, eighteen PD, and eighteen HC participants were included in the study. Neuromelanin-sensitive MRI was used to determine rostral, middle and caudal LC neuromelanin signals. Brain glucose metabolism was investigated with [ 18 F]Fluorodeoxyglucose PET (FDG-PET). The Montreal Cognitive Assessment (MoCA) was used as a measure of global cognition. Results Middle LC neuromelanin signal was significantly reduced in MSA [ t (43) = 3.70, corrected- p  = 0.004] and PD [ t (43) = 2.63, corrected- p  = 0.041] compared to HC, while caudal LC was only reduced in MSA [ t (43) = 2.82, corrected- p  = 0.030]. In MSA, decreased rostral LC neuromelanin was associated with lower MoCA scores ( ρ  = 0.760, p  = 0.006) which, in turn, were associated with lower frontal cortex glucose metabolism. An association between rostral LC neuromelanin signal and frontal cortex glucose metabolism was found in exploratory analyses. Conclusion Loss of LC neuromelanin signal was found in MSA, the middle and caudal parts being targeted. Rostral LC neuromelanin signal loss was associated with both frontal cortex hypometabolism and lower MoCA scores. This pathophysiological link should be further investigated as the noradrenergic system transmission is amenable to pharmacological manipulation.

Many efforts have been tried to evaluate multiple system atrophy (MSA)-related cognitive impairment, however, there is still lacking of effective approach. In this study, for the first time, we developed the individual metabolic radiomics networks (IMRN) using [18F]FDG PET imaging to investigate brain metabolic connectivity patterns of MSA and validated the usefulness of IMRN-based predictive model for MSA-related cognitive impairment. In this retrospective study, we recruited 115 MSA patients with [18F]FDG PET/CT scans. IMRN was constructed by extracting non-redundant radiomics features from each brain region and computing pairwise Pearson correlation coefficients among these features. The validation of IMRN included assessments of small-world properties, test-retest reliability, and metabolic-genetic correlations. Connectome-based predictive modeling (CPM) was implemented to predict Mini Mental State Examination (MMSE) scores, while network-based statistics (NBS) were compared between MSA patients with cognitive impairment (MSA-CI, n = 58; MMSE < 27) and those with normal cognition (MSA-NC, n = 57; MMSE ≥ 27). A support vector machine (SVM) classifier for detecting MSA-CI was developed using discriminative IMRN edges. IMRN showed small-world properties (σ > 1), high reliability (average edge ICC = 0.754), and a significant correlation with gene expression (r = 0.44, P < 0.001). CPM significantly predicted cognitive scores through IMRN edges (positive network: r = 0.27, P = 0.03; negative network: r = 0.28, P = 0.02). NBS revealed decreased cerebellar-cortical connectivity (73 edges) and increased intra-cerebellar/limbic connectivity (24 edges) in MSA-CI compared to MSA-NC. The IMRN-based SVM outperformed SUVR-based SVM in classifying MSA-CI (accuracy: 73.91% vs 62.61%; AUC: 0.80 vs 0.69). This study established a novel approach of IMRN for assessing whole brain metabolic connectivity, uncovering distinct cerebellar connectivity patterns in MSA-CI, which held promise for facilitating personalized cognitive evaluations in MSA.

Differentiating the parkinsonian variant of multiple system atrophy (MSA‐P) from idiopathic Parkinson's disease (IPD) is challenging, especially in the early stages. This study aimed to investigate differences and similarities in the brain functional connectomes of IPD and MSA‐P patients and use machine learning methods to explore the diagnostic utility of these features. Resting‐state fMRI data were acquired from 88 healthy controls, 76 MSA‐P patients, and 53 IPD patients using a 3.0 T scanner. The whole‐brain functional connectome was constructed by thresholding the Pearson correlation matrices of 116 regions, and topological properties were evaluated through graph theory approaches. Connectome measurements were used as features in machine learning models (random forest [RF]/logistic regression [LR]/support vector machine) to distinguish IPD and MSA‐P patients. Regarding graph metrics, early IPD and MSA‐P patients shared network topological properties. Both patient groups showed functional connectivity disruptions within the cerebellum‐basal ganglia‐cortical network, but these disconnections were mainly in the cortico‐thalamo‐cerebellar circuits in MSA‐P patients and the basal ganglia‐thalamo‐cortical circuits in IPD patients. Among the connectome parameters, t tests combined with the RF method identified 15 features, from which the LR classifier achieved the best diagnostic performance on the validation set (accuracy = 92.31%, sensitivity = 90.91%, specificity = 93.33%, area under the receiver operating characteristic curve = 0.89). MSA‐P and IPD patients show similar whole‐brain network topological alterations. MSA‐P primarily affects cerebellar nodes, and IPD primarily affects basal ganglia nodes; both conditions disrupt the cerebellum‐basal ganglia‐cortical network. Moreover, functional connectome parameters showed outstanding value in the differential diagnosis of early MSA‐P and IPD. We investigated brain functional connectome abnormalities in patients with idiopathic Parkinson's disease (IPD) and parkinsonian variant of multiple system atrophy (MSA‐P) using resting‐state functional magnetic resonance imaging, demonstrating that “disconnection” within the cortico‐basal ganglia‐cerebellar network serve as the cornerstone of a differential diagnosis. IPD patients have decreased functional connectivity (FC) in the basal ganglia‐cortical circuit, whereas early‐stage MSA‐P patients have reduced FC in the cerebellum‐cortical circuit.

BackgroundThe purpose of this study was to clarify the usefulness of the ‘hot cross bun’ sign (HCBS) as a diagnostic imaging marker in a large cohort of patients with multiple system atrophy (MSA) and spinocerebellar ataxia (SCA).MethodsThis multicentre study included 97 patients with neuropathologically confirmed MSA, and 105 patients with genetically confirmed SCA. Neuroimaging features, including HCBS and middle cerebellar peduncle (MCP) hyperintensities, were assessed. HCBS was graded from 0 to 2: 0, none; 1, only a vertical hyperintense line; and 2, a cruciform hyperintense line. The neuropathological correlates of HCBS were evaluated in 15 patients with MSA with ≤3 months between MRI and autopsy.ResultsIn patients with a disease duration <3 years, grade 1 or 2 HCBS was detected in 100% patients with MSA with predominant cerebellar ataxia (MSA-C) and 39.0% with SCA; whereas grade 2 HCBS was observed in 50% with MSA-C and 2.4% with SCA. Moreover, the coexistence of grade 2 HCBS and MCP hyperintensities exhibited a specificity of 100%. A neuropathological assessment revealed myelin loss, alpha-synuclein aggregates and astrocytic reaction in the MCP, transverse fibres, central zone between longitudinal fasciculi and raphe nucleus, with relative preservation in the longitudinal fasciculi and medial lemniscus in patients with MSA and grade 2 HCBS.ConclusionsGrade 1 or 2 HCBS is a highly sensitive finding in patients with MSA-C, and the observation of grade 2 HCBS within 3 years of motor symptom onset has excellent specificity for discriminating MSA-C from SCA, especially when accompanied by MCP hyperintensities.

•MSA and PD patients showed iron accumulation and demyelination in subcortical nuclei.•Reduced oxygen metabolism of DGM nuclei were observed in MSA patients.•Susceptibility-derived metrics provide valuable differential diagnosis of these two synucleinopathies. Substantial evidence emphasizes the dysregulation of iron homeostasis, demyelination and oxidative stress in the neurodegenerative process of multiple system atrophy (MSA) and Parkinson’s disease (PD), although its clinical implications remain unclear. Recent MRI post-processing techniques leveraging magnetic susceptibility properties provide a noninvasive means to characterize iron, myelin content and oxygen metabolism alterations. This study aims to investigate subcortical alterations of susceptibility-derived metrics in these two synucleinopathies. A cohort comprising 180 patients (122 with PD and 58 with MSA) and 77 healthy controls (HCs) underwent clinical evaluation and multi-echo gradient echo MRI scans. Susceptibility source separation, susceptibility-based oxygen extraction fraction (OEF) mapping and semiautomatic subcortical nuclei segmentation were utilized to derive parametric values of deep gray matter in all subjects. MSA patients showed markedly elevated paramagnetic susceptibility values in the putamen, globus pallidus (GP) and thalamus; increased diamagnetic susceptibility values in the putamen and dentate nucleus; and reduced OEF values across all nuclei compared with PD patients and HCs. Whereas PD exhibited increased positive susceptibility values in the substantia nigra and enhancing negative values in the GP, similar to MSA. Notably, age-related reductions in OEF were evident in HCs, which was altered by the MSA pathology. Paramagnetic susceptibility was correlated with disease severity. Moreover, the susceptibility-derived metrics of striatum and midbrain nuclei proved to be effective predictors to distinguish PD from MSA (AUC = 0.833). Susceptibility-derived metrics could detect pathological involvement distinct to each disease, offering significant potential for differentiating between MSA and PD in clinical settings.

Multiple system atrophy (MSA), corticobasal degeneration (CBD) and progressive supranuclear palsy (PSP) are the most common atypical parkinsonisms. These adult-onset and lethal neurodegenerative disorders of unknown etiology are clinically characterized by varying combinations of autonomic, levodopa-poorly responsive parkinsonsm, motor, non-motor, cerebellar syndromes, behavioral, cognitive and other neuropsychiatric disorders. Although their pathological hallmarks are different—MSA α-synucleinopathy, CBD and PSP 4-repeat (4R) tauopathies—their neuropsychiatric disturbances include anxiety, depression, agitations, attention-executive dysfunctions, less often compulsive and REM sleep behavior disorders (RBD), which may contribute to disease progression and reduced quality of life (QoL) of patients and caregivers. The present paper reviews the prevalence and type of neuropsychiatric profile in these atypical parkinsonian syndromes, their neuroimaging, and pathogenic backgrounds based on extensive literature research. MSA patients show anxiety, apathy (depression), initial RBD, attentional and executive dysfunction; PSP patients present with apathy, depression, disinhibition, and to a lesser extent, anxiety and agitation; CBD patients are featured by executive and visuospatial dysfunctions, irritability, alien limb phenomena, sleep and language disorders. Neuropsychiatric disorders in these syndromes are often similar, due to disruption of prefronto-subcortical (limbic) and striato-thalamo-cortical circuitries or default mode and attention network disorder. This supports the concept that they are brain network disorders due to complex pathogenic mechanisms related to the basic proteinopathies that are still poorly understood. Psychotic symptoms, hallucinations and delusions are rare. Neuropsychiatric changes in these disorders are often premature and anticipate motor dysfunctions; their assessment and further elucidation of their pathogenesis are warranted as a basis for early diagnosis and adequate treatment of these debilitating comorbidities.

•PD, MSA, and HC patients present distinctly different patterns of association across the clinical symptomatology - cortical excitability - neuroimaging network.•A wide range of associations centered around RMT were found in the HC group, which were disrupted in PD and MSA patient populations.•The joint metric involving ICF and the FC between the right M1 and left temporal middle gyrus can facilitate early differentiation of PD and MSA. Due to a high degree of symptom overlap in the early stages, with movement disorders predominating, Parkinson's disease (PD) and multiple system atrophy (MSA) may exhibit a similar decline in motor areas, yet they differ in their spread throughout the brain, ultimately resulting in two distinct diseases. Drawing upon neuroimaging analyses and altered motor cortex excitability, potential diffusion mechanisms were delved into, and comparisons of correlations across distinct disease groups were conducted in a bid to uncover significant pathological disparities. We recruited thirty-five PD, thirty-seven MSA, and twenty-eight matched controls to conduct clinical assessments, electromyographic recording, and magnetic resonance imaging scanning during the \"on medication\" state. Patients with neurodegeneration displayed a widespread decrease in electrophysiology in bilateral M1. Brain function in early PD was still in the self-compensatory phase and there was no significant change. MSA patients demonstrated an increase in intra-hemispheric function coupled with a decrease in diffusivity, indicating a reduction in the spread of neural signals. The level of resting motor threshold in healthy aged showed broad correlations with both clinical manifestations and brain circuits related to left M1, which was absent in disease states. Besides, ICF exhibited distinct correlations with functional connections between right M1 and left middle temporal gyrus in all groups. The present study identified subtle differences in the functioning of PD and MSA related to bilateral M1. By combining clinical information, cortical excitability, and neuroimaging intuitively, we attempt to bring light on the potential mechanisms that may underlie the development of neurodegenerative disease.

PurposeTo construct multivariate radiomics models using hybrid 18F-FDG PET/MRI for distinguishing between Parkinson’s disease (PD) and multiple system atrophy (MSA).MethodsNinety patients (60 with PD and 30 with MSA) were randomized to training and test sets in a 7:3 ratio. All patients underwent 18F-fluorodeoxyglucose (18F-FDG) PET/MRI to simultaneously obtain metabolic images (18F-FDG), structural MRI images (T1-weighted imaging (T1WI), T2-weighted imaging (T2WI) and T2-weighted fluid-attenuated inversion recovery (T2/FLAIR)) and functional MRI images (susceptibility-weighted imaging (SWI) and apparent diffusion coefficient). Using PET and five MRI sequences, we extracted 1172 radiomics features from the putamina and caudate nuclei. The radiomics signatures were constructed with the least absolute shrinkage and selection operator algorithm in the training set, with progressive optimization through single-sequence and double-sequence radiomics models. Multivariable logistic regression analysis was used to develop a clinical-radiomics model, combining the optimal multi-sequence radiomics signature with clinical characteristics and SUV values. The diagnostic performance of the models was assessed by receiver operating characteristic and decision curve analysis (DCA).ResultsThe radiomics signatures showed favourable diagnostic efficacy. The optimal model comprised structural (T1WI), functional (SWI) and metabolic (18F-FDG) sequences (RadscoreFDG_T1WI_SWI) with the area under curves (AUCs) of the training and test sets of 0.971 and 0.957, respectively. The integrated model, incorporating RadscoreFDG_T1WI_SWI, three clinical symptoms (disease duration, dysarthria and autonomic failure) and SUVmax, demonstrated satisfactory calibration and discrimination in the training and test sets (0.993 and 0.994, respectively). DCA indicated the highest clinical benefit of the clinical-radiomics integrated model.ConclusionsThe radiomics signature with metabolic, structural and functional information provided by hybrid 18F-FDG PET/MRI may achieve promising diagnostic efficacy for distinguishing between PD and MSA. The clinical-radiomics integrated model performed best.

The choroid plexus (CP), a component of the glymphatic system, is essential in homeostasis and producing cerebrospinal fluid. Role of CP in multiple system atrophy (MSA) remains unclear. This study aimed to investigate the implication of the CP in MSA. This retrospective cross-sectional study included 87 MSA patients who underwent the Unified MSA Rating Scale (UMSARS), brain MRI, and 18 F-fluorodeoxyglucose PET scan, along with 84 healthy controls (HCs). Multivariate linear regression analyses were performed to examine the associations between CP volume (CPV) and UMSARS scores, as well as the volumes and cerebral metabolism. Compared with HCs, MSA had significantly reduced CPV (1.00 ± 0.27 vs. 1.30 ± 0.26, P  < 0.001). CPV showed no association with UMSARS, however, it was positively correlated with regional cerebellar volumes. Reduced CPV was associated with lower cerebral glucose metabolism in MSA-susceptible regions, consistent with the positive association between CPV and regional cerebral glucose metabolism observed in multivariate analyses. Notably, CPV positively correlated with glucose metabolism in the brainstem (β = 0.110, P  = 0.003) and cerebellar white matter (β = 0.080, P  = 0.004). This study suggests that CPV is positively associated with disease burden in MSA, with CPV decreasing as disease severity increases. Further research is warranted to determine whether CPV could serve as a potential biomarker for MSA.