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Stridor is a rare but important non-motor symptom that can support the diagnosis and prediction of worse prognosis in multiple system atrophy. Recording sounds generated during sleep by video-polysomnography is recommended for detecting stridor, but the analysis is labor intensive and time consuming. A method for automatic stridor detection should be developed using technologies such as artificial intelligence (AI) or machine learning. However, the rarity of stridor hinders the collection of sufficient data from diverse patients. Therefore, an AI method with high diagnostic performance should be devised to address this limitation. We propose an AI method for detecting patients with stridor by combining audio splitting and reintegration with few-shot learning for diagnosis. We used video-polysomnography data from patients with stridor (19 patients with multiple system atrophy) and without stridor (28 patients with parkinsonism and 18 patients with sleep disorders). To the best of our knowledge, this is the first study to propose a method for stridor detection and attempt the validation of few-shot learning to process medical audio signals. Even with a small training set, a substantial improvement was achieved for stridor detection, confirming the clinical utility of our method compared with similar developments. The proposed method achieved a detection accuracy above 96% using data from only eight patients with stridor for training. Performance improvements of 4%–13% were achieved compared with a state-of-the-art AI baseline. Moreover, our method determined whether a patient had stridor and performed real-time localization of the corresponding audio patches, thus providing physicians with support for interpreting and efficiently employing the results of this method. [ABSTRACT FROM AUTHOR]

Background and objective: Sex differences in gastrointestinal dysfunction have not been systematically analyzed in patients with Parkinson's disease (PD). This study was aimed to investigate the sex differences in gastrointestinal dysfunctions among the patients with PD using a multicenter trial dataset. Methods: We analyzed the baseline data of prospectively enrolled set of patients with gastrointestinal dysfunctions. Possible sex differences in gastrointestinal symptoms assessed on the Nepean Dyspepsia Index-Korean Version (NDI-K), gastrointestinal symptom diary, and Bristol stool scale were analyzed in association with clinical PD severity and antiparkinsonian drug dosages by multiple linear regression models. We also performed post hoc analysis of the dyspepsia symptom sub-items, adjusting for multiple comparisons. Results: Sixty-six of the 144 participants were female (45.8%). There were no differences in age, PD duration, Hoehn and Yahr stage, and daily dopaminergic medication dosages between sexes. NDI-K symptom and dyspepsia scores were correlated with the activity of daily living in females but not in males. In the multiple regression analysis controlling for all possible variables, female patients were shown to have worse gastrointestinal symptoms than males. When we performed post hoc analysis of the dyspepsia symptoms, inability to finish a regular meal and nausea were significantly worse in female patients. Gastrointestinal symptom diary supported that female patients more frequently complained of early fullness and bloating in the upper abdomen after meals than males, and burning pain in upper abdomen was more severe in female patients. Conclusion: Gastrointestinal dysfunctions may differentially affect female and male PD patients. [ABSTRACT FROM AUTHOR]

The effect of transcranial direct current stimulation (tDCS) for cerebellar-dominant multiple-system atrophy (MSA-C) is not well elucidated, yet. This study aimed to investigate the effect of tDCS on the primary motor cortex (M1) and cerebellum in patients with MSA-C. We recruited probable MSA-C patients and performed three single sessions of tDCS at each visit in random order (M1, cerebellum or sham). Cerebellar ataxia was evaluated with the International Cooperative Ataxia Rating Scale (ICARS) and objective gait and static balance analyses both before and after each stimulation session. Additionally, we also evaluated the factors related with objective improvement from each stimulation. Sixteen participants were enrolled, and one dropped out after 2 sessions of stimulation due to consent withdrawal. The gait velocity, step time and single support time all significantly improved after the M1 and cerebellar tDCS treatment compared with the sham stimulation while there was no difference in the improvement of ICARS and posturography results among 3 stimulations. In terms of the related factors with improvement of gait velocity, the disease duration, baseline gait speed and single support times were correlated after M1 stimulation, while a higher ICARS score and baseline gait speed in cerebellar stimulation. There were no adverse effects reported after the tDCS sessions. Our results demonstrated that both M1 and cerebellar tDCS demonstrated benefits for MSA-C patients without significant complications. Considering the different related factors with improvement at each stimulation, the mechanism would be different between M1 and cerebellar stimulations. [ABSTRACT FROM AUTHOR]

Automated segmentation and volumetry of brain magnetic resonance imaging (MRI) scans are essential for the diagnosis of Parkinson's disease (PD) and Parkinson's plus syndromes (P-plus). To enhance the diagnostic performance, we adopt deep learning (DL) models in brain MRI segmentation and compared their performance with the gold-standard non-DL method. We collected brain MRI scans of healthy controls ( n = 105 ) and patients with PD ( n = 105 ), multiple systemic atrophy ( n = 132 ), and progressive supranuclear palsy ( n = 69 ) at Samsung Medical Center from January 2017 to December 2020. Using the gold-standard non-DL model, FreeSurfer (FS), we segmented six brain structures: midbrain, pons, caudate, putamen, pallidum, and third ventricle, and considered them as annotated data for DL models, the representative convolutional neural network (CNN) and vision transformer (ViT)-based models. Dice scores and the area under the curve (AUC) for differentiating normal, PD, and P-plus cases were calculated to determine the measure to which FS performance can be reproduced as-is while increasing speed by the DL approaches. The segmentation times of CNN and ViT for the six brain structures per patient were 51.26 ± 2.50 and 1101.82 ± 22.31 s, respectively, being 14 to 300 times faster than FS (15,735 ± 1.07 s). Dice scores of both DL models were sufficiently high (> 0.85) so their AUCs for disease classification were not inferior to that of FS. For classification of normal vs. P-plus and PD vs. P-plus (except multiple systemic atrophy - Parkinsonian type) based on all brain parts, the DL models and FS showed AUCs above 0.8, demonstrating the clinical value of DL models in addition to FS. DL significantly reduces the analysis time without compromising the performance of brain segmentation and differential diagnosis. Our findings may contribute to the adoption of DL brain MRI segmentation in clinical settings and advance brain research. [ABSTRACT FROM AUTHOR]

Background: Although iron dyshomeostasis is associated with Parkinson's disease (PD) pathogenesis, the relationship between iron deposition and non-motor involvement in PD is not fully understood. In this study, we investigated basal ganglia and extra-basal ganglia system iron contents and their correlation with non-motor symptoms in drug-naïve, early-stage PD patients. Methods: We enrolled 14 drug-naïve, early-stage PD patients and 12 age/sex-matched normal controls. All participants underwent brain magnetic resonance imaging to obtain the effective transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM). Deep brain structures, including the nucleus accumbens, caudate nucleus, putamen, globus pallidus, thalamus, hippocampus, and amygdala, were delineated using the FSL-FIRST; the substantia nigra, red nucleus, and dentate nucleus were segmented manually. Inter-group differences in R2* and QSM values, as well as their association with clinical parameters of PD, were investigated. Results: Substantia nigra and putamen R2* values were significantly higher in PD patients than in normal controls, despite no significant difference in QSM values. Regarding the non-motor symptom scales, PD sleep scale score negatively correlated with R2* values in the red nucleus and right amygdala, Scales for Outcomes in Parkinson's disease-Autonomic scores were positively correlated with R2* values in the right amygdala and left hippocampus, and cardiovascular sub-score of Non-Motor Symptoms Scale for PD was positively associated with the QSM value in the left hippocampus. Conclusion: In this study, iron content in the extra-basal ganglia system was significantly correlated with non-motor symptoms, especially sleep problems and dysautonomia, even in early-stage PD. [ABSTRACT FROM AUTHOR]

Fatigue is a common and disabling non-motor symptom (NMS) of Parkinson's disease (PD); however, it has been poorly understood in patients with progressive supranuclear palsy (PSP). We investigated the association between fatigue, clinical features, and other NMS in patients with probable PSP. In 72 probable PSP patients, fatigue was investigated using the Parkinson Fatigue Scale (PFS). Further, all patients were evaluated using the PSP rating scale (PSPRS), Beck Depression Inventory (BDI), Mini-Mental State Examination (MMSE), Frontal Assessment Battery (FAB), PD Sleep Scale (PDSS), NMS scale (NMSS), PD Questionnaire-39 summary index (PDQ-39 SI), and Scale for outcomes in PD-Autonomic (SCOPA-AUT). The prevalence of fatigue assessed by PFS was 38.9% (28/72) in patients with PSP. The secondary fatigue was defined as fatigued patients with depression and/or sleep disturbances. We divided the patients into primary (n = 15), secondary (n = 13), and non-fatigue groups. There were no differences in age, sex, disease duration, and PSPRS, PDSS, MMSE, and FAB scores among the three groups. The primary fatigue group had higher scores in PDQ-39 SI compared to the non-fatigue group. The secondary fatigue group showed higher scores in NMSS, PDQ-39 SI, and SCOPA-AUT compared to the non-fatigue group. PFS was positively correlated with NMSS and PDQ-39 SI and SCOPA-AUT. Fatigue is common in patients with PSP and is associated with the NMS and the quality of life in these patients. The present study provides meaningful insight into fatigue in patients with PSP. [ABSTRACT FROM AUTHOR]

Recent advances in next-generation sequencing technologies have uncovered the genetic backgrounds of various diseases. Type 1 sialidosis (OMIM#256550) is a rare autosomal recessive lysosomal storage disease caused by a mutation in the NEU1 (OMIM * 608272) gene. In this study, we aimed to review the previous reports of type 1 sialidosis and compare those with the first case of type 1 sialidosis in Korea. A 36-year-old woman presented with progressive ataxia, myoclonus, and seizure since the age of 12. Whole-exome sequencing revealed a pathogenic missense variant c.928G > A (p.D310N) and novel c.15_16del (p.P6Qfs*21) of the NEU1 gene as final causal candidate as compound heterozygotes. We reviewed the literature and selected the clinical reports of genetically confirmed type 1 sialidosis patients. A total of 45 patients in 17 reports were identified. Cherry-red spot, myoclonus, ataxia, and seizure were reported in 51.2%, 100.0%, 87.8%, and 73.7% of patients, respectively. Abnormalities of cognitive function, EEG, and brain MRI and visual symptoms were reported in 22.2%, 40.7%, 66.7%, and 70.2% of patients, respectively. Overall, our patient showed similar clinical features to previous type 1 sialidosis patients, but she did not complain of visual symptoms despite having cherry-red spots. We summarize the clinical features of type 1 sialidosis and report the first case of type 1 sialidosis with novel deletion variant in the NEU1 gene in the Korean population. Our study suggests the importance of ophthalmologic examinations in patients with myoclonus, ataxia, and seizure who do not complain of visual symptoms. [ABSTRACT FROM AUTHOR]

These authors contributed equally: Joomee Song and Juyoung Hahm. Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-023-30381-w, published online 01 March 2023 The original online version of this Article was revised: In the original version of this Article, the Supplementary File, which was included with the initial submission, was omitted from the Supplementary Information section. [Extracted from the article]

To compare the effects of intravenous amantadine and placebo therapy on freezing of gait in patients with Parkinson’s disease, this randomized, double-blind, placebo-controlled, multicenter trial compared the efficacy of 5 days intravenous amantadine and placebo treatments on freezing of gait in 42 subjects randomly allocated 2:1 to amantadine or placebo groups. Changes in freezing of gait questionnaire (FOG-Q) scores and in unified Parkinson’s disease rating scale (UPDRS) scores, from baseline to immediately (V1) and 1 month (V2) after treatments, were assessed. Among the 42 patients (amantadine n = 29, placebo n = 13, a mean age 65.5 ± 9.4 years and a mean FOG-Q score 17.4 ± 3.2), 40 subjects completed treatment. There was no significant group difference on the primary outcome measure as total FOG-Q score changes at V1. However a significant beneficial effect of amantadine on freezing was seen at V2 in the UPDRS Part II freezing and FOG-Q item 3 scores, and there was significant improvement in the UPDRS Part IV total score and in the UPDRS Part II getting out of bed score in the amantadine group at both V1 and V2. There was no serious adverse event reported during the study. The intravenous amantadine therapy did not show a significant improvement on overall FOG-Q scores in patients with moderate-to-severe freezing; however, it might be beneficial by attenuating freezing severity and improving patients’ mobility. To prove this finding further studies with larger sample sizes are warranted in the future. [ABSTRACT FROM AUTHOR]

Clinically differentiating multiple system atrophy cerebellar (MSA-C) phenotype and spinocerebellar ataxias (SCAs) is challenging especially in the early stage. We assessed diagnostic value of brain magnetic resonance imaging (MRI) in differentiating MSA-C and SCAs based at different disease stages (<3, 3–7, and >7 years of disease duration). Overall, 186 patients with probable MSA-C and 117 with genetically confirmed SCAs were included. Hot cross bun (HCB) signs and middle cerebellar peduncle (MCP) hyperintensities were exclusively prevalent in MSA-C compared to SCAs at <3 years (HCB, 44.6% versus 0.9%; MCP hyperintensities, 38.3% versus 0.9%, respectively). Sensitivity, specificity, and positive predictive value (PPV) for HCB signs to differentiate MSA-C from SCAs were 45%, 99%, and 99% and those for MCP hyperintensities were 68%, 99%, and 99%, respectively; considering both HCB signs and MCP hyperintensities, specificity and PPV were 100%. However, the differential value of MRI signs decreased over time. MCP widths were smaller and showed more significant decrease in MSA-C than in SCAs. In conclusion, pontine and MCP changes were exclusively prominent in early stage MSA-C rather than in SCAs. Therefore, we should consider disease duration when interpreting pontine and MCP changes in brain MRIs, which will help better differentiate MSA-C and SCAs. [ABSTRACT FROM AUTHOR]