Differential response to pallidal deep brain stimulation among monogenic dystonias: systematic review and meta-analysis.

OBJECTIVE: Genetic subtypes of dystonia may respond differentially to deep brain stimulation of the globus pallidus pars interna (GPi DBS). We sought to compare GPi DBS outcomes among the most common monogenic dystonias. METHODS: This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses and Meta-analysis of Observational Studies in Epidemiology guidelines. We searched PubMed for studies on genetically confirmed monogenic dystonia treated with GPi DBS documenting pre-surgical and post-surgical assessments using the Burke-Fahn-Marsden Dystonia Rating Scale Motor Score (BFMMS) and Burke-Fahn-Marsden Disability Score (BFMDS). We performed (i) meta-analysis for each gene mutation; (ii) weighted ordinary linear regression analyses to compare BFMMS and BFMDS outcomes between DYT-TOR1A and other monogenic dystonias, adjusting for age and disease duration and (iii) weighted linear regression analysis to estimate the effect of age, sex and disease duration on GPi DBS outcomes. Results were summarised with mean change and 95% CI. RESULTS: DYT-TOR1A (68%, 38.4 points; p<0.001), DYT-THAP1 (37% 14.5 points; p<0.001) and NBIA/DYT-PANK2 (27%, 21.4 points; p<0.001) improved in BFMMS; only DYT-TOR1A improved in BFMDS (69%, 9.7 points; p<0.001). Improvement in DYT-TOR1A was significantly greater than in DYT-THAP1 (BFMMS -31%), NBIA/DYT-PANK2 (BFMMS -35%; BFMDS -53%) and CHOR/DYT-ADCY5 (BFMMS -36%; BFMDS -42%). Worse motor outcomes were associated with longer dystonia duration and older age at dystonia onset in DYT-TOR1A, longer dystonia duration in DYT/PARK-TAF1 and younger age at dystonia onset in DYT-SGCE. CONCLUSIONS: GPi DBS outcomes vary across monogenic dystonias. These data serve to inform patient selection and prognostic counselling.

Appropriateness, safety, and effectiveness of "drip and ship" teleconsultation model in Southeastern Tuscany: a feasibility study.

PURPOSE: Teleconsultation is a consultation between two or more physicians about the diagnostic work-up and therapeutic strategy in the treatment of an individual case by means of modern telematics. 'Drip-and-ship' teleconsultation model consists of the transfer of patients, through telematics stroke networks, with large arteries occlusions from primary to comprehensive stroke centers equipped for endovascular therapy. We retrospectively investigated appropriateness, safety, and effectiveness of 'drip-and-ship' teleconsultation model in a rural area of Tuscany. METHODS: Outcome measures were: door-to-ship time (including door-to-needle time), ratio of number treated/total sent patients, adverse events/mortality during transfer, and mortality and modified Rankin scale at 90 days. Analysis of non-treated patients was also done. RESULTS: Seventy-eight patients were included; 16/78 patients were sent for endovascular therapy alone, and 62/78 for "drip-and-ship"; 12 patients were not treated. Door-to-ship, and door-to-needle times (mean ± SD) were 105 ± 29.8 and 62.5 ± 37.5 min, respectively. The ratio number of treated/total sent patients was 0.85. At 90 days, the global mortality rate was 21%, and 40% of patients showed favorable outcome. The main cause of non-treatment was spontaneous recanalization. CONCLUSIONS: The high value for treated/total sent patients' ratio underlines that "drip-and-ship" teleconsultation model is appropriate and effective, with a few untreated patients. The model is safe, without adverse events during transfer. Taken together, our outcomes are in line with the previous reports. "Drip-and-ship" teleconsultation model is safe and effective in rural areas, allowing good selections and rapid treatments for stroke patients, based on the transfer from the primary to the comprehensive stroke center.

Exploring white matter microstructural alterations in mild cognitive impairment: a multimodal diffusion MRI investigation utilizing diffusion kurtosis and free-water imaging.

Background: Mild Cognitive Impairment (MCI) is a transitional stage from normal aging to dementia, characterized by noticeable changes in cognitive function that do not significantly impact daily life. Diffusion MRI (dMRI) plays a crucial role in understanding MCI by assessing white matter integrity and revealing early signs of axonal degeneration and myelin breakdown before cognitive symptoms appear. Methods: This study utilized the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to compare white matter microstructure in individuals with MCI to cognitively normal (CN) individuals, employing advanced dMRI techniques such as diffusion kurtosis imaging (DKI), mean signal diffusion kurtosis imaging (MSDKI), and free water imaging (FWI). Results: Analyzing data from 55 CN subjects and 46 individuals with MCI, this study found significant differences in white matter integrity, particularly in free water levels and kurtosis values, suggesting neuroinflammatory responses and microstructural integrity disruption in MCI. Moreover, negative correlations between Mini-Mental State Examination (MMSE) scores and free water levels in the brain within the MCI group point to the potential of these measures as early biomarkers for cognitive impairment. Conclusion: In conclusion, this study demonstrates how a multimodal advanced diffusion imaging approach can uncover early microstructural changes in MCI, offering insights into the neurobiological mechanisms behind cognitive decline.

Optimization and validation of multi-echo, multi-contrast SAGE acquisition in fMRI.

The purpose of this study was to optimize and validate a multi-contrast, multi-echo fMRI method using a combined spin- and gradient-echo (SAGE) acquisition. It was hypothesized that SAGE-based blood oxygen level-dependent (BOLD) functional MRI (fMRI) will improve sensitivity and spatial specificity while reducing signal dropout. SAGE-fMRI data were acquired with five echoes (2 gradient-echoes, 2 asymmetric spin-echoes, and 1 spin-echo) across 12 protocols with varying acceleration factors, and temporal SNR (tSNR) was assessed. The optimized protocol was then implemented in working memory and vision tasks in 15 healthy subjects. Task-based analysis was performed using individual echoes, quantitative dynamic relaxation times T2 * and T2, and echo time-dependent weighted combinations of dynamic signals. These methods were compared to determine the optimal analysis method for SAGE-fMRI. Implementation of a multiband factor of 2 and sensitivity encoding (SENSE) factor of 2.5 yielded adequate spatiotemporal resolution while minimizing artifacts and loss in tSNR. Higher BOLD contrast-to-noise ratio (CNR) and tSNR were observed for SAGE-fMRI relative to single-echo fMRI, especially in regions with large susceptibility effects and for T2-dominant analyses. Using a working memory task, the extent of activation was highest with T2 *-weighting, while smaller clusters were observed with quantitative T2 * and T2. SAGE-fMRI couples the high BOLD sensitivity from multi-gradient-echo acquisitions with improved spatial localization from spin-echo acquisitions, providing two contrasts for analysis. SAGE-fMRI provides substantial advantages, including improving CNR and tSNR for more accurate analysis.

Rapid simultaneous estimation of relaxation rates using multi-echo, multi-contrast MRI.

PURPOSE: Multi-echo, multi-contrast methods are increasingly used in dynamic imaging studies to simultaneously quantify R2∗ and R2. To overcome the computational challenges associated with nonlinear least squares (NLSQ) fitting, we propose a generalized linear least squares (LLSQ) solution to rapidly fit R2∗ and R2. METHODS: Spin- and gradient-echo (SAGE) data were simulated across T2∗ and T2 values at high (200) and low (20) SNR. Full (four-parameter) and reduced (three-parameter) parameter fits were implemented and compared with both LLSQ and NLSQ fitting. Fit data were compared to ground truth using concordance correlation coefficient (CCC) and coefficient of variation (CV). In vivo SAGE perfusion data were acquired in 20 subjects with relapsing-remitting multiple sclerosis. LLSQ R2∗ and R2, as well as cerebral blood volume (CBV), were compared with the standard NLSQ approach. RESULTS: Across all fitting methods, T2∗ was well-fit at high (CCC = 1, CV = 0) and low (CCC ≥ 0.87, CV ≤ 0.08) SNR. Except for short T2∗ values (5-15 ms), T2 was well-fit at high (CCC = 1, CV = 0) and low (CCC ≥ 0.99, CV ≤ 0.03) SNR. In vivo, LLSQ R2∗ and R2 estimates were similar to NLSQ, and there were no differences in R2∗ across fitting methods at high SNR. However, there were some differences at low SNR and for R2 at high and low SNR. In vivo NLSQ and LLSQ three parameter fits performed similarly, as did NLSQ and LLSQ four-parameter fits. LLSQ CBV nearly matched the standard NLSQ method for R2∗- (0.97 ratio) and R2-CBV (0.98 ratio). Voxel-wise whole-brain fitting was faster for LLSQ (3-4 min) than NLSQ (16-18 h). CONCLUSIONS: LLSQ reliably fit for R2∗ and R2 in simulated and in vivo data. Use of LLSQ methods reduced the computational demand, enabling rapid estimation of R2∗ and R2.

Ménière's Disease: Insights from an Italian Nationwide Survey.

The aim of the present study was to obtain data from a large community sample of patients with Ménière's disease (MD) in Italy through a web-based nationwide survey. Demographic, clinical, and epidemiological features of MD among members of the Italian Association of Ménière's Disease (AMMI) were collected through a web-based survey. The questionnaire was posted on the AMMI website between 01/SEP/2021 and 31/OCT/2021. A total of 520 patients (374 F, 146 M) with MD were included. The age at interview (average ± standard deviation, SD) was 51.4 ± 10.9 years, with a disease duration of 9.9 ± 9.8 years. Eighty percent of cases were unilateral. No patients reported neurocognitive disorders or Parkinson's disease. A positive family history of MD was reported in 13% of participants, while a history of allergic diseases was reported in 33%. Comorbid thyroid disorders were present in 25% of participants, and 28% used betahistine as the main treatment. To our knowledge, this is the first study that has investigated the epidemiology and current patterns of care of MD in Italy, using an anonymous survey directly sent to patients, thus implying their active participation. We hope that future studies will support the utilization of web-based surveys to address the unmet needs in the management of patients with MD.

Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal study.

Introduction: Parkinson's disease (PD) is an idiopathic disease of the central nervous system characterized by both motor and non-motor symptoms. It is the second most common neurodegenerative disease. Magnetic resonance imaging (MRI) can reveal underlying brain changes associated with PD. Objective: In this study, structural connectivity and white matter networks were analyzed by diffusion MRI and graph theory in a cohort of patients with PD and a cohort of healthy controls (HC) obtained from the Parkinson's Progression Markers Initiative (PPMI) database in a cross-sectional analysis. Furthermore, we investigated longitudinal changes in the PD cohort over 36 months. Result: Compared with the control group, participants with PD showed lower structural connectivity in several brain areas, including the corpus callosum, fornix, and uncinate fasciculus, which were also confirmed by a large effect-size. Additionally, altered connectivity between baseline and after 36 months was found in different network paths inside the white matter with a medium effect-size. Network analysis showed trends toward lower network density in PD compared with HC at baseline and after 36 months, though not significant after correction. Significant differences were observed in nodal degree and strength in several nodes. Conclusion: In conclusion, altered structural and network metrics in several brain regions, such as corpus callosum, fornix, and cingulum were found in PD, compared to HC. We also report altered connectivity in the PD group after 36 months, reflecting the impact of both PD pathology and aging processes. These results indicate that structural and network metrics might yield insight into network reorganization that occurs in PD.

Functional Movement Disorders and Deep Brain Stimulation: A Multi-Center Study.

Background: Functional movement disorders (FMD) are a commonly under-recognized diagnosis in patients with underlying neurodegenerative diseases. FMD have been observed in patients undergoing deep brain stimulation (DBS) for Parkinson's disease (PD) and other movement disorders. The prevalence of coexisting FMD among movement disorder-related DBS patients is unknown, and it may occur more often than previously recognized. Methods: We retrospectively assessed the relative prevalence and clinical characteristics of FMD occurring post-DBS, in PD and dystonia patients (FMD+, n = 29). We compared this cohort with age at surgery-, sex-, and diagnosis-matched subjects without FMD post-DBS (FMD-, n = 29). Results: Both the FMD prevalence (0.2%-2.1%) and the number of cases/DBS procedures/year varied across centers (0.15-3.65). A total of nine of 29 FMD+ cases reported worse outcomes following DBS. Although FMD+ and FMD- manifested similar features, FMD+ showed higher psychiatric comorbidity. Conclusions: DBS may be complicated by the development of FMD in a subset of patients, particularly those with pre-morbid psychiatric conditions.

Resolving 'vascular parkinsonism' -COL22A1 as a genetic adult-onset leukoencephalopathy.

We describe an elderly woman meeting criteria for vascular parkinsonism/dementia associated with a likely pathogenic variant in the COL22A1 gene, supported by functional experiments in a zebrafish model. We suggest that white matter hyperintensities may not represent small-vessel ischemic disease and that, if confirmed by further observations, COL22A1 may be included among the adult-onset leukoencephalopathies mislabeled as "vascular parkinsonism."

Sex Differences in Alzheimer's Disease Revealed by Free-Water Diffusion Tensor Imaging and Voxel-Based Morphometry.

BACKGROUND: Imaging biomarkers are increasingly used in Alzheimer's disease (AD), and the identification of sex differences using neuroimaging may provide insight into disease heterogeneity, progression, and therapeutic targets. OBJECTIVE: The purpose of this study was to investigate differences in grey matter (GM) volume and white matter (WM) microstructural disorganization between males and females with AD using voxel-based morphometry (VBM) and free-water-corrected diffusion tensor imaging (FW-DTI). METHODS: Data were downloaded from the OASIS-3 database, including 158 healthy control (HC; 86 females) and 46 mild AD subjects (24 females). VBM and FW-DTI metrics (fractional anisotropy (FA), axial and radial diffusivities (AxD and RD, respectively), and FW index) were compared using effect size for the main effects of group, sex, and their interaction. RESULTS: Significant group and sex differences were observed, with no significant interaction. Post-hoc comparisons showed that AD is associated with reduced GM volume, reduced FW-FA, and higher FW-RD/FW-index, consistent with neurodegeneration. Females in both groups exhibited higher GM volume than males, while FW-DTI metrics showed sex differences only in the AD group. Lower FW, lower FW-FA and higher FW-RD were observed in females relative to males in the AD group. CONCLUSION: The combination of VBM and DTI may reveal complementary sex-specific changes in GM and WM associated with AD and aging. Sex differences in GM volume were observed for both groups, while FW-DTI metrics only showed significant sex differences in the AD group, suggesting that WM tract disorganization may play a differential role in AD pathophysiology between females and males.

Systematic Assessment of the Impact of DTI Methodology on Fractional Anisotropy Measures in Alzheimer's Disease.

White matter microstructural changes in Alzheimer's disease (AD) are often assessed using fractional anisotropy (FA) obtained from diffusion tensor imaging (DTI). FA depends on the acquisition and analysis methods, including the fitting algorithm. In this study, we compared FA maps from different acquisitions and fitting algorithms in AD, mild cognitive impairment (MCI), and healthy controls (HCs) using the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Three acquisitions from two vendors were compared (Siemens 30, GE 48, and Siemens 54 directions). DTI data were fit using nine fitting algorithms (four linear least squares (LLS), two weighted LLS (WLLS), and three non-linear LLS (NLLS) from four software tools (FSL, DSI-Studio, CAMINO, and AFNI). Different cluster volumes and effect-sizes were observed across acquisitions and fits, but higher consistency was observed as the number of diffusion directions increased. Significant differences were observed between HC and AD groups for all acquisitions, while significant differences between HC and MCI groups were only observed for GE48 and SI54. Using the intraclass correlation coefficient, AFNI-LLS and CAMINO-RESTORE were the least consistent with the other algorithms. By combining data across all three acquisitions and nine fits, differences between AD and HC/MCI groups were observed in the fornix and corpus callosum, indicating FA differences in these regions may be robust DTI-based biomarkers. This study demonstrates that comparisons of FA across aging populations could be confounded by variability in acquisitions and fit methodologies and that identifying the most robust DTI methodology is critical to provide more reliable DTI-based neuroimaging biomarkers for assessing microstructural changes in AD.

When does postural instability appear in monogenic parkinsonisms? An individual-patient meta-analysis.

BACKGROUND: Postural instability is a disease milestone signaling advanced disease. OBJECTIVES: To estimate the onset of postural instability in monogenic parkinsonisms. METHODS: We systematically reviewed studies (PubMed 1996-2017) in SNCA, PRKN, PINK1, DJ-1, LRRK2, ATP13A2, FBXO7, VPS35, DNAJC6, or SYNJ1-related monogenic parkinsonisms, with documented postural instability. Genes with ≥ 15 patients were included in an individual-patient meta-analysis and compared with a retrospectively collected sporadic Parkinson's disease cohort from our center. The primary outcome measure was the progression-free survival from postural instability using Kaplan-Meier survival curves. Cox proportional hazards analyses were summarized using hazards ratio (HR). RESULTS: Of 2085 eligible studies, 124 met full criteria (636 patients) for the systematic review, whereas a total of 871 subjects (270 from sporadic cohort, 601 monogenic parkinsonisms) were included in the individual-patient meta-analysis. Postural instability was reported in 80% of DJ-1, 40% of PRKN, 39% of PINK1, 34% of ATP13A2, 31% of LRRK2, and 29% of SNCA patients. Progression-free survival from postural instability at 10 years after disease onset was longest in ATP13A2 (97%) and shortest in SNCA (50%). Halfway between these two extremes were PRKN (88%), PINK1 (87%), and LRRK2 (81%), similar to sporadic Parkinson's disease (72%). Higher risk of postural instability was observed in SNCA (HR = 3.2, p = 0.007) and DJ-1 (HR = 3.96, p = 0.001) compared to sporadic Parkinson's disease. Young age at onset in PINK1 and female sex in LRRK2 were associated with a decreased risk of postural instability. CONCLUSIONS: Monogenic parkinsonisms exhibit differential timelines to postural instability, informing prognostic counseling and interpretation of future genotype-specific treatment trials.

Genetic parkinsonisms and cancer: a systematic review and meta-analysis.

Genes associated with parkinsonism may also be implicated in carcinogenesis, but their interplay remains unclear. We systematically reviewed studies (PubMed 1967-2019) reporting gene variants associated with both parkinsonism and cancer. Somatic variants were examined in cancer samples, whereas germline variants were examined in cancer patients with both symptomatic and asymptomatic (carriers) genetic parkinsonisms. Pooled proportions were calculated with random-effects meta-analyses. Out of 9,967 eligible articles, 60 were included. Of the 28 genetic variants associated with parkinsonism, six were also associated with cancer. In cancer samples, SNCA was predominantly associated with gastrointestinal cancers, UCHL1 with breast cancer, and PRKN with head-and-neck cancers. In asymptomatic carriers, LRRK2 was predominantly associated with gastrointestinal and prostate cancers, PRKN with prostate and genitourinary tract cancers, GBA with sarcoma, and 22q11.2 deletion with leukemia. In symptomatic genetic parkinsonism, LRRK2 was associated with nonmelanoma skin cancers and breast cancers, and PRKN with head-and-neck cancers. Cancer was more often manifested in genetic parkinsonisms compared to asymptomatic carriers. These results suggest that intraindividual genetic contributions may modify the co-occurrence of cancer and neurodegeneration.

Assessing White Matter Pathology in Early-Stage Parkinson Disease Using Diffusion MRI: A Systematic Review.

Structural brain white matter (WM) changes such as axonal caliber, density, myelination, and orientation, along with WM-dependent structural connectivity, may be impacted early in Parkinson disease (PD). Diffusion magnetic resonance imaging (dMRI) has been used extensively to understand such pathological WM changes, and the focus of this systematic review is to understand both the methods utilized and their corresponding results in the context of early-stage PD. Diffusion tensor imaging (DTI) is the most commonly utilized method to probe WM pathological changes. Previous studies have suggested that DTI metrics are sensitive in capturing early disease-associated WM changes in preclinical symptomatic regions such as olfactory regions and the substantia nigra, which is considered to be a hallmark of PD pathology and progression. Postprocessing analytic approaches include region of interest-based analysis, voxel-based analysis, skeletonized approaches, and connectome analysis, each with unique advantages and challenges. While DTI has been used extensively to study WM disorganization in early-stage PD, it has several limitations, including an inability to resolve multiple fiber orientations within each voxel and sensitivity to partial volume effects. Given the subtle changes associated with early-stage PD, these limitations result in inaccuracies that severely impact the reliability of DTI-based metrics as potential biomarkers. To overcome these limitations, advanced dMRI acquisition and analysis methods have been employed, including diffusion kurtosis imaging and q-space diffeomorphic reconstruction. The combination of improved acquisition and analysis in DTI may yield novel and accurate information related to WM-associated changes in early-stage PD. In the current article, we present a systematic and critical review of dMRI studies in early-stage PD, with a focus on recent advances in DTI methodology. Yielding novel metrics, these advanced methods have been shown to detect diffuse WM changes in early-stage PD. These findings support the notion of early axonal damage in PD and suggest that WM pathology may go unrecognized until symptoms appear. Finally, the advantages and disadvantages of different dMRI techniques, analysis methods, and software employed are discussed in the context of PD-related pathology.

Skin Cancer May Delay Onset but Not Progression of Parkinson's Disease: A Nested Case-Control Study.

Objective: To evaluate the extent to which cancer, a biological opposite to neurodegenerative disorders, may affect the onset and progression of Parkinson's disease (PD). Methods: A nested case-control design in consecutive PD patients with (cases) vs. without (controls) cancer was used to compare time to clinical diagnosis and time to Hoehn & Yahr (H&Y) staging score ≥ 3 as a measure of progression. Further, we compared PD onset and progression between cases with cancer diagnosis before (cancer before PD group) and after (cancer after PD group) PD onset. Independent variables were age at PD onset, motor subscale of the Movement Disorders Society-Unified Parkinson's Disease Rating Scale, sex, cognitive impairment, falls, depression, anxiety, dementia, and autonomic symptoms. Time to H&Y ≥ 3 was determined using Cox proportional hazards, with adjusted results summarized as hazards ratio (HR). Group differences were evaluated using unpaired t-test or Fisher's exact test. Results: The clinical PD onset was later in cases vs. controls (median 67.2 vs. 59.8 years; p < 0.001), but the adjusted time to H&Y ≥ 3 was similar between groups (HR = 0.67; p = 0.13). Skin cancers constituted 75% of all cancers in cases. Amongst skin cancers, compared to controls, cases had an older age at PD onset (67.8 vs. 59.8 years; p < 0.001). There was no difference in risk of progression in PD patients with skin cancer compared to controls (HR = 0.54, p = 0.09). Conclusions: Cancer, in particular of the skin, may delay the onset but not the progression of PD. Future prospective observational studies are warranted to elucidate the complex interactions between these biologically divergent disorders.

Phenotype-Agnostic Molecular Subtyping of Neurodegenerative Disorders: The Cincinnati Cohort Biomarker Program (CCBP).

Ongoing biomarker development programs have been designed to identify serologic or imaging signatures of clinico-pathologic entities, assuming distinct biological boundaries between them. Identified putative biomarkers have exhibited large variability and inconsistency between cohorts, and remain inadequate for selecting suitable recipients for potential disease-modifying interventions. We launched the Cincinnati Cohort Biomarker Program (CCBP) as a population-based, phenotype-agnostic longitudinal study. While patients affected by a wide range of neurodegenerative disorders will be deeply phenotyped using clinical, imaging, and mobile health technologies, analyses will not be anchored on phenotypic clusters but on bioassays of to-be-repurposed medications as well as on genomics, transcriptomics, proteomics, metabolomics, epigenomics, microbiomics, and pharmacogenomics analyses blinded to phenotypic data. Unique features of this cohort study include (1) a reverse biology-to-phenotype direction of biomarker development in which clinical, imaging, and mobile health technologies are subordinate to biological signals of interest; (2) hypothesis free, causally- and data driven-based analyses; (3) inclusive recruitment of patients with neurodegenerative disorders beyond clinical criteria-meeting patients with Parkinson's and Alzheimer's diseases, and (4) a large number of longitudinally followed participants. The parallel development of serum bioassays will be aimed at linking biologically suitable subjects to already available drugs with repurposing potential in future proof-of-concept adaptive clinical trials. Although many challenges are anticipated, including the unclear pathogenic relevance of identifiable biological signals and the possibility that some signals of importance may not yet be measurable with current technologies, this cohort study abandons the anchoring role of clinico-pathologic criteria in favor of biomarker-driven disease subtyping to facilitate future biosubtype-specific disease-modifying therapeutic efforts.

Paraneoplastic movement disorders: phenomenology, diagnosis, and treatment.

Paraneoplastic syndromes include, by definition, any symptomatic and non-metastatic condition associated with a neoplasm. Paraneoplastic movement disorders are a heterogeneous group of syndromes encompassing both hyperkinetic and hypokinetic conditions, characterized by acute/sub-acute onset, rapidly progressive evolution, and multifocal localizations with several overlapping features. These movement disorders are immune-mediated, as shown by the rapid onset and by the presence of antineuronal antibodies in biological samples of patients, fundamental for the diagnosis. Antineuronal antibodies could be targeted against intracellular or neuronal surface antigens. Paraneoplastic movement disorders associated with anti-neuronal surface antigens antibodies respond more frequently to immunotherapy. The underlying tumors may be different, according to the clinical presentation, age, and gender of patients. Our search considered articles involving human subjects indexed in PubMed. Abstracts were independently reviewed for eligibility criteria by one author and validated by at least one additional author. In this review, we sought to critically reappraise the clinical features and the pathophysiological mechanisms of paraneoplastic movement disorders, focusing on diagnostic and therapeutic strategies. Our main aim is to make clinicians aware of paraneoplastic movement disorders, and to provide assistance in the early diagnosis and management of these rare but life-threatening conditions.