Clinical utility of plasma Aß42/40 ratio by LC-MS/MS in Alzheimer's disease assessment.

Introduction: Plasma Aß42/40 ratio can help predict amyloid PET status, but its clinical utility in Alzheimer's disease (AD) assessment is unclear. Methods: Aß42/40 ratio was measured by LC-MS/MS for 250 specimens with associated amyloid PET imaging, diagnosis, and demographic data, and for 6,192 consecutive clinical specimens submitted for Aß42/40 testing. Results: High diagnostic sensitivity and negative predictive value (NPV) for Aß-PET positivity were observed, consistent with the clinical performance of other plasma LC-MS/MS assays, but with greater separation between Aß42/40 values for individuals with positive vs. negative Aß-PET results. Assuming a moderate prevalence of Aß-PET positivity, a cutpoint was identified with 99% NPV, which could help predict that AD is likely not the cause of patients' cognitive impairment and help reduce PET evaluation by about 40%. Conclusion: High-throughput plasma Aß42/40 LC-MS/MS assays can help identify patients with low likelihood of AD pathology, which can reduce PET evaluations, allowing for cost savings.

Longitudinal Free-Water Changes in Dementia with Lewy Bodies.

BACKGROUND: Diffusion-weighted magnetic resonance imaging (dMRI) examines tissue microstructure integrity in vivo. Prior dementia with Lewy bodies (DLB) diffusion tensor imaging studies yielded mixed results. OBJECTIVE: We employed free-water (FW) imaging to assess DLB progression and correlate with clinical decline in DLB. METHODS: Baseline and follow-up MRIs were obtained at 12 and/or 24 months for 27 individuals with DLB or mild cognitive impairment with Lewy bodies (MCI-LB). FW was analyzed using the Mayo Clinic Adult Lifespan Template. Primary outcomes were FW differences between baseline and 12 or 24 months. To compare FW change longitudinally, we included 20 cognitively unimpaired individuals from the Alzheimer's Disease Neuroimaging Initiative. RESULTS: We followed 23 participants to 12 months and 16 participants to 24 months. Both groups had worsening in Montreal Cognitive Assessment (MoCA) and Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores. We found significant FW increases at both time points compared to baseline in the insula, amygdala, posterior cingulum, parahippocampal, entorhinal, supramarginal, fusiform, retrosplenial, and Rolandic operculum regions. At 24 months, we found more widespread microstructural changes in regions implicated in visuospatial processing, motor, and cholinergic functions. Between-group analyses (DLB vs. controls) confirmed significant FW changes over 24 months in most of these regions. FW changes were associated with longitudinal worsening of MDS-UPDRS and MoCA scores. CONCLUSIONS: FW increased in gray and white matter regions in DLB, likely due to neurodegenerative pathology associated with disease progression. FW change was associated with clinical decline. The findings support dMRI as a promising tool to track disease progression in DLB. © 2024 International Parkinson and Movement Disorder Society.

Diffusion MRI relates to plasma Aß42/40 in PET negative participants without dementia.

INTRODUCTION: Magnetic resonance imaging (MRI) biomarkers are needed for indexing early biological stages of Alzheimer's disease (AD), such as plasma amyloid-ß (Aß42/40) positivity in Aß positron emission tomography (PET) negative individuals. METHODS: Diffusion free-water (FW) MRI was acquired in individuals with normal cognition (NC) and mild cognitive impairment (MCI) with Aß plasma-/PET- (NC = 22, MCI = 60), plasma+/PET- (NC = 5, MCI = 20), and plasma+/PET+ (AD dementia = 21) biomarker status. Gray and white matter FW and fractional anisotropy (FAt) were compared cross-sectionally and the relationships between imaging, plasma and PET biomarkers were assessed. RESULTS: Plasma+/PET- demonstrated increased FW (24 regions) and decreased FAt (66 regions) compared to plasma-/PET-. FW (16 regions) and FAt (51 regions) were increased in plasma+/PET+ compared to plasma+/PET-. Composite brain FW correlated with plasma Aß42/40 and p-tau181. DISCUSSION: FW imaging changes distinguish plasma Aß42/40 positive and negative groups, independent of group differences in cognitive status, Aß PET status, and other plasma biomarkers (i.e., t-tau, p-tau181, glial fibrillary acidic protein, neurofilament light). HIGHLIGHTS: Plasma Aß42/40 positivity is associated with brain microstructure decline. Plasma+/PET- demonstrated increased FW in 24 total GM and WM regions. Plasma+/PET- demonstrated decreased FAt in 66 total GM and WM regions. Whole-brain FW correlated with plasma Aß42/40 and p-tau181 measures. Plasma+/PET- demonstrated decreased cortical volume and thickness.

Different aspects of failing to recover from proactive semantic interference predicts rate of progression from amnestic mild cognitive impairment to dementia.

Introduction: This study investigated the role of proactive semantic interference (frPSI) in predicting the progression of amnestic Mild Cognitive Impairment (aMCI) to dementia, taking into account various cognitive and biological factors. Methods: The research involved 89 older adults with aMCI who underwent baseline assessments, including amyloid PET and MRI scans, and were followed longitudinally over a period ranging from 12 to 55 months (average 26.05 months). Results: The findings revealed that more than 30% of the participants diagnosed with aMCI progressed to dementia during the observation period. Using Cox Proportional Hazards modeling and adjusting for demographic factors, global cognitive function, hippocampal volume, and amyloid positivity, two distinct aspects of frPSI were identified as significant predictors of a faster decline to dementia. These aspects were fewer correct responses on a frPSI trial and a higher number of semantic intrusion errors on the same trial, with 29.5% and 31.6 % increases in the likelihood of more rapid progression to dementia, respectively. Discussion: These findings after adjustment for demographic and biological markers of Alzheimer's Disease, suggest that assessing frPSI may offer valuable insights into the risk of dementia progression in individuals with aMCI.

Cortico-basal ganglia white matter microstructure is linked to restricted repetitive behavior in autism spectrum disorder.

BACKGROUND: Restricted repetitive behavior (RRB) is one of two behavioral domains required for the diagnosis of autism spectrum disorder (ASD). Neuroimaging is widely used to study brain alterations associated with ASD and the domain of social and communication deficits, but there has been less work regarding brain alterations linked to RRB. METHODS: We utilized neuroimaging data from the National Institute of Mental Health Data Archive to assess basal ganglia and cerebellum structure in a cohort of children and adolescents with ASD compared to typically developing (TD) controls. We evaluated regional gray matter volumes from T1-weighted anatomical scans and assessed diffusion-weighted scans to quantify white matter microstructure with free-water imaging. We also investigated the interaction of biological sex and ASD diagnosis on these measures, and their correlation with clinical scales of RRB. RESULTS: Individuals with ASD had significantly lower free-water corrected fractional anisotropy (FAT) and higher free-water (FW) in cortico-basal ganglia white matter tracts. These microstructural differences did not interact with biological sex. Moreover, both FAT and FW in basal ganglia white matter tracts significantly correlated with measures of RRB. In contrast, we found no significant difference in basal ganglia or cerebellar gray matter volumes. LIMITATIONS: The basal ganglia and cerebellar regions in this study were selected due to their hypothesized relevance to RRB. Differences between ASD and TD individuals that may occur outside the basal ganglia and cerebellum, and their potential relationship to RRB, were not evaluated. CONCLUSIONS: These new findings demonstrate that cortico-basal ganglia white matter microstructure is altered in ASD and linked to RRB. FW in cortico-basal ganglia and intra-basal ganglia white matter was more sensitive to group differences in ASD, whereas cortico-basal ganglia FAT was more closely linked to RRB. In contrast, basal ganglia and cerebellar volumes did not differ in ASD. There was no interaction between ASD diagnosis and sex-related differences in brain structure. Future diffusion imaging investigations in ASD may benefit from free-water estimation and correction in order to better understand how white matter is affected in ASD, and how such measures are linked to RRB.

Plasma Alzheimer's biomarkers and brain amyloid in Hispanic and non-Hispanic older adults.

INTRODUCTION: Alzheimer's disease studies often lack ethnic diversity. METHODS: We evaluated associations between plasma biomarkers commonly studied in Alzheimer's (p-tau181, GFAP, and NfL), clinical diagnosis (clinically normal, amnestic MCI, amnestic dementia, or non-amnestic MCI/dementia), and Aß-PET in Hispanic and non-Hispanic older adults. Hispanics were predominantly of Cuban or South American ancestry. RESULTS: Three-hundred seventy nine participants underwent blood draw (71.9 ± 7.8 years old, 60.2% female, 57% Hispanic of which 88% were Cuban or South American) and 240 completed Aß-PET. P-tau181 was higher in amnestic MCI (p = 0.004, d = 0.53) and dementia (p < 0.001, d = 0.97) than in clinically normal participants and discriminated Aß-PET[+] and Aß-PET[-] (AUC = 0.86). P-tau181 outperformed GFAP and NfL. There were no significant interactions with ethnicity. Among amnestic MCI, Hispanics had lower odds of elevated p-tau181 than non-Hispanic (OR = 0.41, p = 0.006). DISCUSSION: Plasma p-tau181 informs etiological diagnosis of cognitively impaired Hispanic and non-Hispanic older adults. Hispanic ethnicity may relate to greater likelihood of non-Alzheimer's contributions to memory loss. HIGHLIGHTS: Alzheimer's biomarkers were measured in Hispanic and non-Hispanic older adults. Plasma p-tau181 related to amnestic cognitive decline and brain amyloid burden. AD biomarker associations did not differ between Hispanic and non-Hispanic ethnicity. Hispanic individuals may be more likely to have non-Alzheimer causes of memory loss.

Free-water imaging reveals unique brain microstructural deficits in hispanic individuals with Dementia.

Prior evidence suggests that Hispanic and non-Hispanic individuals differ in potential risk factors for the development of dementia. Here we determine whether specific brain regions are associated with cognitive performance for either ethnicity along various stages of Alzheimer's disease. For this cross-sectional study, we examined 108 participants (61 Hispanic vs. 47 Non-Hispanic individuals) from the 1Florida Alzheimer's Disease Research Center (1Florida ADRC), who were evaluated at baseline with diffusion-weighted and T1-weighted imaging, and positron emission tomography (PET) amyloid imaging. We used FreeSurfer to segment 34 cortical regions of interest. Baseline Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used as measures of cognitive performance. Group analyses assessed free-water measures (FW) and volume. Statistically significant FW regions based on ethnicity x group interactions were used in a stepwise regression function to predict total MMSE and MoCA scores. Random forest models were used to identify the most predictive brain-based measures of a dementia diagnosis separately for Hispanic and non-Hispanic groups. Results indicated elevated FW values for the left inferior temporal gyrus, left middle temporal gyrus, left banks of the superior temporal sulcus, left supramarginal gyrus, right amygdala, and right entorhinal cortex in Hispanic AD subjects compared to non-Hispanic AD subjects. These alterations occurred in the absence of different volumes of these regions in the two AD groups. FW may be useful in detecting individual differences potentially reflective of varying etiology that can influence cognitive decline and identify MRI predictors of cognitive performance, particularly among Hispanics.

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

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

Semantic intrusion errors are associated with plasma Ptau-181 among persons with amnestic mild cognitive impairment who are amyloid positive.

Introduction: Semantic intrusion errors (SI) have distinguished between those with amnestic Mild Cognitive Impairment (aMCI) who are amyloid positive (A+) versus negative (A-) on positron emission tomography (PET). Method: This study examines the association between SI and plasma - based biomarkers. One hundred and twenty-eight participants received SiMoA derived measures of plasma pTau-181, ratio of two amyloid-ß peptide fragments (Aß42/Aß40), Neurofilament Light protein (NfL), Glial Fibrillary Acidic Protein (GFAP), ApoE genotyping, and amyloid PET imaging. Results: The aMCI A+ (n = 42) group had a higher percentage of ApoE ɛ4 carriers, and greater levels of pTau-181 and SI, than Cognitively Unimpaired (CU) A- participants (n = 25). CU controls did not differ from aMCI A- (n = 61) on plasma biomarkers or ApoE genotype. Logistic regression indicated that ApoE ɛ4 positivity, pTau-181, and SI were independent differentiating predictors (Correct classification = 82.0%; Sensitivity = 71.4%; Specificity = 90.2%) in identifying A+ from A- aMCI cases. Discussion: A combination of plasma biomarkers, ApoE positivity and SI had high specificity in identifying A+ from A- aMCI cases.

Distinct cortical and subcortical predictors of Purdue Pegboard decline in Parkinson's disease and atypical parkinsonism.

Objective measures of disease progression are critically needed in research on Parkinson's disease (PD) and atypical Parkinsonism but may be hindered by both practicality and cost. The Purdue Pegboard Test (PPT) is objective, has high test-retest reliability, and has a low cost. The goals of this study were to determine: (1) longitudinal changes in PPT in a multisite cohort of patients with PD, atypical Parkinsonism, and healthy controls; (2) whether PPT performance reflects brain pathology revealed by neuroimaging; (3) quantify kinematic deficits shown by PD patients during PPT. Parkinsonian patients showed a decline in PPT performance that correlated with motor symptom progression, which was not seen in controls. Neuroimaging measures from basal ganglia were significant predictors of PPT performance in PD, whereas cortical, basal ganglia, and cerebellar regions were predictors for atypical Parkinsonism. Accelerometry in a subset of PD patients showed a diminished range of acceleration and irregular patterns of acceleration, which correlated with PPT scores.

Imaging features of small vessel disease in cerebral amyloid angiopathy among patients with Alzheimer's disease.

BACKGROUND AND PURPOSE: Cerebral small vessel disease biomarkers including white matter hyperintensities (WMH), lacunes, and enlarged perivascular spaces (ePVS) are under investigation to identify those specific to cerebral amyloid angiopathy (CAA). In subjects with Alzheimer's disease (AD), we assessed characteristic features and amounts of WMH, lacunes, and ePVS in four CAA categories (no, mild, moderate and severe CAA) and correlated these with Clinical Dementia Rating sum of boxes (CDRsb) score, ApoE genotype, and neuropathological changes at autopsy. METHODS: The study included patients with a clinical diagnosis of dementia due to AD and neuropathological confirmation of AD and CAA in the National Alzheimer's Coordinating Center (NACC) database. The WMH, lacunes, and ePVS were evaluated using semi-quantitative scales. Statistical analyses compared the WMH, lacunes, and ePVS values in the four CAA groups with vascular risk factors and AD severity treated as covariates, and to correlate the imaging features with CDRsb score, ApoE genotype, and neuropathological findings. RESULTS: The study consisted of 232 patients, of which 222 patients had FLAIR data available and 105 patients had T2-MRI. Occipital predominant WMH were significantly associated with the presence of CAA (p = 0.007). Among the CAA groups, occipital predominant WMH was associated with severe CAA (ß = 1.22, p = 0.0001) compared with no CAA. Occipital predominant WMH were not associated with the CDRsb score performed at baseline (p = 0.68) or at follow-up 2-4 years after the MRI (p = 0.92). There was no significant difference in high grade ePVS in the basal ganglia (p = 0.63) and centrum semiovale (p = 0.95) among the four CAA groups. The WMH and ePVS on imaging did not correlate with the number of ApoE ε4 alleles but the WMH (periventricular and deep) correlated with the presence of infarcts, lacunes and microinfarcts on neuropathology. CONCLUSION: Among patients with AD, occipital predominant WMH is more likely to be found in patients with severe CAA than in those without CAA. The high-grade ePVS in centrum semiovale were common in all AD patients regardless of CAA severity.

Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks.

Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in devising corrective neural stimulation before the onset of behavior. Recurrent Neural Networks (RNNs) are common models for sequence data. However, standard RNNs are not able to handle data with temporal distributional shifts to guarantee robust classification across time. To enable the network to utilize all temporal features of the neural input data, and to enhance the memory of an RNN, we propose a novel approach: RNNs with time-varying weights, here termed Time-Varying RNNs (TV-RNNs). These models are able to not only predict the class of the time-sequence correctly but also lead to accurate classification earlier in the sequence than standard RNNs. In this work, we focus on early sequential classification of brain-wide neural activity across time using TV-RNNs applied to a variety of neural data from mice and humans, as subjects perform motor tasks. Finally, we explore the contribution of different brain regions on behavior classification using SHapley Additive exPlanation (SHAP) value, and find that the somatosensory and premotor regions play a large role in behavioral classification.

Mediation of Reduced Hippocampal Volume by Cerebral Amyloid Angiopathy in Pathologically Confirmed Patients with Alzheimer's Disease.

BACKGROUND: Hippocampal atrophy in cerebral amyloid angiopathy (CAA) has been reported to be similar to that in Alzheimer's disease (AD). OBJECTIVE: To evaluate if CAA pathology partly mediates reduced hippocampal volume in patients with AD. METHODS: Patients with a clinical diagnosis of AD and neuropathological confirmation of AD+/-CAA in the National Alzheimer's Coordinating Center database were included in the study. The volumes of temporal lobe structures were calculated on T1-weighted imaging (T1-MRI) using automated FreeSurfer software, from images acquired on average 5 years prior to death. Multivariate regression analysis was performed to compare brain volumes in four CAA groups. The hippocampal volume on T1-MRI was correlated with Clinical Dementia Rating sum of boxes (CDRsb) score, apolipoprotein E (APOE) genotype, and hippocampal atrophy at autopsy. RESULTS: The study included 231 patients with no (n = 45), mild (n = 70), moderate (n = 67), and severe (n = 49) CAA. Among the four CAA groups, patients with severe CAA had a smaller mean left hippocampal volume (p = 0.023) but this was not significant when adjusted for APOE ɛ4 (p = 0.07). The left hippocampal volume on MRI correlated significantly with the hippocampal atrophy grading on neuropathology (p = 0.0003). Among patients with severe CAA, the left hippocampal volume on T1-MRI: (a) decreased with an increase in the number of APOE ɛ4 alleles (p = 0.04); but (b) had no evidence of correlation with CDRsb score (p = 0.57). CONCLUSION: Severe CAA was associated with smaller left hippocampal volume on T1-MRI up to five years prior to death among patients with neuropathologically confirmed AD. This relationship was dependent on APOE ɛ4 genotype.

Association of longitudinal cognitive decline with diffusion MRI in Gray Matter, Amyloid, and Tau deposition.

Extracellular amyloid plaques in gray matter are the earliest pathological marker for Alzheimer's disease (AD), followed by abnormal tau protein accumulation. The link between diffusion changes in gray matter, amyloid and tau pathology, and cognitive decline is not well understood. We first performed cross-sectional analyses on T1-weighted imaging, diffusion MRI, and amyloid and tau PETs from the ADNI 2/3 database. We evaluated cortical volume, free-water, fractional anisotropy (FA), and amyloid and tau SUVRs in 171 cognitively normal, 103 MCI, and 44 AD individuals. When the 3 groups were combined, increasing amyloid burden was associated with reduced extracellular free-water in the entorhinal cortex and hippocampus in those with amyloid-negative status whereas increasing tau burden was associated with increased extracellular free-water regardless of amyloid status. Next, we found that for the MCI subjects, diffusion measures (free-water, FA) alone predicted MMSE score 2 years later with a high r-square value (87%), as compared to tau SUVRs (27%), T1 volume (36%), and amyloid SUVRs (75%). Diffusion measures represent a potent non-invasive marker for predicting cognitive decline.

Evaluation of an Adoptive Cellular Therapy-Based Vaccine in a Transgenic Mouse Model of α-synucleinopathy.

Aggregated α-synuclein, a major constituent of Lewy bodies plays a crucial role in the pathogenesis of α-synucleinopathies (SPs) such as Parkinson's disease (PD). PD is affected by the innate and adaptive arms of the immune system, and recently both active and passive immunotherapies targeted against α-synuclein are being trialed as potential novel treatment strategies. Specifically, dendritic cell-based vaccines have shown to be an effective treatment for SPs in animal models. Here, we report on the development of adoptive cellular therapy (ACT) for SP and demonstrate that adoptive transfer of pre-activated T-cells generated from immunized mice can improve survival and behavior, reduce brain microstructural impairment via magnetic resonance imaging (MRI), and decrease α-synuclein pathology burden in a peripherally induced preclinical SP model (M83) when administered prior to disease onset. This study provides preclinical evidence for ACT as a potential immunotherapy for LBD, PD and other related SPs, and future work will provide necessary understanding of the mechanisms of its action.

Clinical utility of plasma Aß42/40 ratio by LC-MS/MS in Alzheimer's disease assessment.

INTRODUCTION: Plasma Aß42/40 ratio can be used to help predict amyloid PET status, but its clinical utility in Alzheimer's disease (AD) assessment is unclear. METHODS: Aß42/40 ratio was measured by LC-MS/MS in 250 specimens with associated amyloid PET imaging, diagnosis, and demographic data, and 6,192 consecutive clinical specimens submitted for Aß42/40 testing. RESULTS: High diagnostic sensitivity and negative predictive value (NPV) for Aß-PET positivity were observed, consistent with the clinical performance of other plasma LC-MS/MS assays, but with greater separation between Aß42/40 values for individuals with positive vs negative Aß-PET results. Assuming a moderate prevalence of Aß-PET positivity, a cutpoint was identified with 99% NPV, which could help predict that AD is likely not the cause of patients' cognitive impairment and help reduce PET evaluation by about 40%. DISCUSSION: Using high-throughput plasma Aß42/40 LC-MS/MS assays can help reduce PET evaluations in patients with low likelihood of AD pathology, allowing for cost savings.

A transfer learning approach based on gradient boosting machine for diagnosis of Alzheimer's disease.

Early detection of Alzheimer's disease (AD) during the Mild Cognitive Impairment (MCI) stage could enable effective intervention to slow down disease progression. Computer-aided diagnosis of AD relies on a sufficient amount of biomarker data. When this requirement is not fulfilled, transfer learning can be used to transfer knowledge from a source domain with more amount of labeled data than available in the desired target domain. In this study, an instance-based transfer learning framework is presented based on the gradient boosting machine (GBM). In GBM, a sequence of base learners is built, and each learner focuses on the errors (residuals) of the previous learner. In our transfer learning version of GBM (TrGB), a weighting mechanism based on the residuals of the base learners is defined for the source instances. Consequently, instances with different distribution than the target data will have a lower impact on the target learner. The proposed weighting scheme aims to transfer as much information as possible from the source domain while avoiding negative transfer. The target data in this study was obtained from the Mount Sinai dataset which is collected and processed in a collaborative 5-year project at the Mount Sinai Medical Center. The Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset was used as the source domain. The experimental results showed that the proposed TrGB algorithm could improve the classification accuracy by 1.5 and 4.5% for CN vs. MCI and multiclass classification, respectively, as compared to the conventional methods. Also, using the TrGB model and transferred knowledge from the CN vs. AD classification of the source domain, the average score of early MCI vs. late MCI classification improved by 5%.

Suppression of Axial Tremor by Deep Brain Stimulation in Patients with Essential Tremor: Effects on Gait and Balance Measures.

Background: Deep brain stimulation (DBS) of the ventralis intermedius (VIM) nucleus of the thalamus has been successful in mitigating upper limb tremor, but the effect on gait and balance performance is unclear. Here, we aim to examine the effectiveness of VIM DBS on stride length variability, sway path length, and task-relevant tremor of various body segments in essential tremor (ET). Methods: Seventeen ET individuals treated with DBS (ET DBS) and 17 age-and sex-matched healthy controls (HC) performed a postural balance and overground walking task. In separate and consecutive visits, ET DBS performed gait and balance tasks with DBS ON or OFF. The main outcome measures were sway path length, stride length variability, and tremor quantified from upper limb, lower limb, upper and lower trunk (axial) during the gait and balance tasks. Results: With DBS OFF, ET DBS exhibited significantly greater stride length variability, sway path length, and tremor during gait and balance task relative to HC. Relative to DBS OFF, DBS ON reduced stride length variability and sway path length in ET DBS. The DBS-induced reduction in stride length variability was associated with the reduction in both upper trunk tremor and upper limb tremor. The DBS-induced reduction in sway path length was associated with the reduction in upper trunk tremor. Discussion: The findings of this study revealed that VIM DBS was effective in improving gait and balance in ET DBS and that improvements in gait and postural balance were associated with a reduction of axial tremor during the tasks. Highlights: ET patients exhibit tremor in various body locations during gait and balance.DBS reduced stride length variability and sway path length.DBS-induced improvements in gait and balance were associated with reduction in axial tremor.

A Tensorized Multitask Deep Learning Network for Progression Prediction of Alzheimer's Disease.

With the advances in machine learning for the diagnosis of Alzheimer's disease (AD), most studies have focused on either identifying the subject's status through classification algorithms or on predicting their cognitive scores through regression methods, neglecting the potential association between these two tasks. Motivated by the need to enhance the prospects for early diagnosis along with the ability to predict future disease states, this study proposes a deep neural network based on modality fusion, kernelization, and tensorization that perform multiclass classification and longitudinal regression simultaneously within a unified multitask framework. This relationship between multiclass classification and longitudinal regression is found to boost the efficacy of the final model in dealing with both tasks. Different multimodality scenarios are investigated, and complementary aspects of the multimodal features are exploited to simultaneously delineate the subject's label and predict related cognitive scores at future timepoints using baseline data. The main intent in this multitask framework is to consolidate the highest accuracy possible in terms of precision, sensitivity, F1 score, and area under the curve (AUC) in the multiclass classification task while maintaining the highest similarity in the MMSE score as measured through the correlation coefficient and the RMSE for all time points under the prediction task, with both tasks, run simultaneously under the same set of hyperparameters. The overall accuracy for multiclass classification of the proposed KTMnet method is 66.85 ± 3.77. The prediction results show an average RMSE of 2.32 ± 0.52 and a correlation of 0.71 ± 5.98 for predicting MMSE throughout the time points. These results are compared to state-of-the-art techniques reported in the literature. A discovery from the multitasking of this consolidated machine learning framework is that a set of hyperparameters that optimize the prediction results may not necessarily be the same as those that would optimize the multiclass classification. In other words, there is a breakpoint beyond which enhancing further the results of one process could lead to the downgrading in accuracy for the other.

Advanced diffusion imaging to track progression in Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy.

Advanced diffusion imaging which accounts for complex tissue properties, such as crossing fibers and extracellular fluid, may detect longitudinal changes in widespread pathology in atypical Parkinsonian syndromes. We implemented fixel-based analysis, Neurite Orientation and Density Imaging (NODDI), and free-water imaging in Parkinson's disease (PD), multiple system atrophy (MSAp), progressive supranuclear palsy (PSP), and controls longitudinally over one year. Further, we used these three advanced diffusion imaging techniques to investigate longitudinal progression-related effects in key white matter tracts and gray matter regions in PD and two common atypical Parkinsonian disorders. Fixel-based analysis and free-water imaging revealed longitudinal declines in a greater number of descending sensorimotor tracts in MSAp and PSP compared to PD. In contrast, only the primary motor descending sensorimotor tract had progressive decline over one year, measured by fiber density (FD), in PD compared to that in controls. PSP was characterized by longitudinal impairment in multiple transcallosal tracts (primary motor, dorsal and ventral premotor, pre-supplementary motor, and supplementary motor area) as measured by FD, whereas there were no transcallosal tracts with longitudinal FD impairment in MSAp and PD. In addition, free-water (FW) and FW-corrected fractional anisotropy (FAt) in gray matter regions showed longitudinal changes over one year in regions that have previously shown cross-sectional impairment in MSAp (putamen) and PSP (substantia nigra, putamen, subthalamic nucleus, red nucleus, and pedunculopontine nucleus). NODDI did not detect any longitudinal white matter tract progression effects and there were few effects in gray matter regions across Parkinsonian disorders. All three imaging methods were associated with change in clinical disease severity across all three Parkinsonian syndromes. These results identify novel extra-nigral and extra-striatal longitudinal progression effects in atypical Parkinsonian disorders through the application of multiple diffusion methods that are related to clinical disease progression. Moreover, the findings suggest that fixel-based analysis and free-water imaging are both particularly sensitive to these longitudinal changes in atypical Parkinsonian disorders.