Neuromelanin and T2*-MRI for the assessment of genetically at-risk, prodromal, and symptomatic Parkinson's disease.

MRI was suggested as a promising method for the diagnosis and assessment of Parkinson's Disease (PD). We aimed to assess the sensitivity of neuromelanin-MRI and T2* with radiomics analysis for detecting PD, identifying individuals at risk, and evaluating genotype-related differences. Patients with PD and non-manifesting (NM) participants [NM-carriers (NMC) and NM-non-carriers (NMNC)], underwent MRI and DAT-SPECT. Imaging-based metrics included 48 neuromelanin and T2* radiomics features and DAT-SPECT specific-binding-ratios (SBR), were extracted from several brain regions. Imaging values were assessed for their correlations with age, differences between groups, and correlations with the MDS-likelihood-ratio (LR) score. Several machine learning classifiers were evaluated for group classification. A total of 127 participants were included: 46 patients with PD (62.3 ± 10.0 years) [15:LRRK2-PD, 16:GBA-PD, and 15:idiopathic-PD (iPD)], 47 NMC (51.5 ± 8.3 years) [24:LRRK2-NMC and 23:GBA-NMC], and 34 NMNC (53.5 ± 10.6 years). No significant correlations were detected between imaging parameters and age. Thirteen MRI-based parameters and radiomics features demonstrated significant differences between PD and NMNC groups. Support-Vector-Machine (SVM) classifier achieved the highest performance (AUC = 0.77). Significant correlations were detected between LR scores and two radiomic features. The classifier successfully identified two out of three NMC who converted to PD. Genotype-related differences were detected based on radiomic features. SBR values showed high sensitivity in all analyses. In conclusion, neuromelanin and T2* MRI demonstrated differences between groups and can be used for the assessment of individuals at-risk in cases when DAT-SPECT can't be performed. Combining neuromelanin and T2*-MRI provides insights into the pathophysiology underlying PD, and suggests that iron accumulation precedes neuromelanin depletion during the prodromal phase.

Connecting real-world digital mobility assessment to clinical outcomes for regulatory and clinical endorsement-the Mobilise-D study protocol.

BACKGROUND: The development of optimal strategies to treat impaired mobility related to ageing and chronic disease requires better ways to detect and measure it. Digital health technology, including body worn sensors, has the potential to directly and accurately capture real-world mobility. Mobilise-D consists of 34 partners from 13 countries who are working together to jointly develop and implement a digital mobility assessment solution to demonstrate that real-world digital mobility outcomes have the potential to provide a better, safer, and quicker way to assess, monitor, and predict the efficacy of new interventions on impaired mobility. The overarching objective of the study is to establish the clinical validity of digital outcomes in patient populations impacted by mobility challenges, and to support engagement with regulatory and health technology agencies towards acceptance of digital mobility assessment in regulatory and health technology assessment decisions. METHODS/DESIGN: The Mobilise-D clinical validation study is a longitudinal observational cohort study that will recruit 2400 participants from four clinical cohorts. The populations of the Innovative Medicine Initiative-Joint Undertaking represent neurodegenerative conditions (Parkinson's Disease), respiratory disease (Chronic Obstructive Pulmonary Disease), neuro-inflammatory disorder (Multiple Sclerosis), fall-related injuries, osteoporosis, sarcopenia, and frailty (Proximal Femoral Fracture). In total, 17 clinical sites in ten countries will recruit participants who will be evaluated every six months over a period of two years. A wide range of core and cohort specific outcome measures will be collected, spanning patient-reported, observer-reported, and clinician-reported outcomes as well as performance-based outcomes (physical measures and cognitive/mental measures). Daily-living mobility and physical capacity will be assessed directly using a wearable device. These four clinical cohorts were chosen to obtain generalizable clinical findings, including diverse clinical, cultural, geographical, and age representation. The disease cohorts include a broad and heterogeneous range of subject characteristics with varying chronic care needs, and represent different trajectories of mobility disability. DISCUSSION: The results of Mobilise-D will provide longitudinal data on the use of digital mobility outcomes to identify, stratify, and monitor disability. This will support the development of widespread, cost-effective access to optimal clinical mobility management through personalised healthcare. Further, Mobilise-D will provide evidence-based, direct measures which can be endorsed by regulatory agencies and health technology assessment bodies to quantify the impact of disease-modifying interventions on mobility. TRIAL REGISTRATION: ISRCTN12051706.

Outcome Assessment in Parkinson Disease Prevention Trials: Utility of Clinical and Digital Measures.

BACKGROUND AND OBJECTIVES: The prodromal phase of Parkinson disease (PD) is accompanied by subtle clinical signs that are not sufficient for diagnosis but could potentially be measured in the context of clinical trials of therapies intended to delay or prevent more definitive clinical features. The objective of this study was to review the available literature on the presence and time course of subtle motor features in prodromal PD in the context of planning for possible clinical trials. METHODS: We reviewed the available literature based on expert opinion. We considered a range of outcomes including measurement of clinical features, patient-reported outcomes, digital markers, and clinical diagnosis. RESULTS: We considered these features and measures in the context of patient stratification, intermediate outcomes, and clinically relevant end points, including phenoconversion. DISCUSSION: Substantial progress has been made in understanding how motor features evolve in the period immediately before a PD diagnosis. Digital measures hold substantial progress for measurement precision and may be additionally relevant because they can be used in naturalistic environments outside the clinic. Future studies should focus on advancing digital sensor technology and analysis and developing methods to implement available methods, particularly determination of a clinical diagnosis of PD, in a clinical trial context.

Combining transcranial direct current stimulation with a motor-cognitive task: the impact on dual-task walking costs in older adults.

BACKGROUND: The performance of a secondary task while walking increases motor-cognitive interference and exacerbates fall risk in older adults. Previous studies have demonstrated that transcranial direct current stimulation (tDCS) may improve certain types of dual-task performance, and, that tDCS delivered during the performance of a task may augment the benefits of stimulation, potentially reducing motor-cognitive interference. However, it is not yet known if combining multi-target tDCS with the simultaneous performance of a task related to the tDCS targets reduces or increases dual-task walking costs among older adults. The objectives of the present work were (1) To examine whether tDCS applied during the performance of a task that putatively utilizes the brain networks targeted by the neuro-stimulation reduces dual-task costs, and (2) to compare the immediate after-effects of tDCS applied during walking, during seated-rest, and during sham stimulation while walking, on dual-task walking costs in older adults. We also explored the impact on postural sway and other measures of cognitive function. METHODS: A double-blind, 'within-subject' cross-over pilot study evaluated the effects of 20 min of anodal tDCS targeting both the primary motor cortex (M1) and the left dorsolateral prefrontal cortex (lDLPFC) in 25 healthy older adults (73.9 ± 5.2 years). Three stimulation conditions were assessed in three separate sessions: (1) tDCS while walking in a complex environment (tDCS + walking), (2) tDCS while seated (tDCS + seated), and (3) walking in a complex environment with sham tDCS (sham + walking). The complex walking condition utilized virtual reality to tax motor and cognitive abilities. During each session, usual-walking, dual-task walking, quiet standing sway, and cognitive function (e.g., Stroop test) were assessed before and immediately after stimulation. Dual-task costs to gait speed and other measures were computed. RESULTS: The dual-task cost to gait speed was reduced after tDCS + walking (p = 0.004) as compared to baseline values. Neither tDCS + seated (p = 0.173) nor sham + walking (p = 0.826) influenced this outcome. Similar results were seen for other gait measures and for Stroop performance. Sway was not affected by tDCS. CONCLUSIONS: tDCS delivered during the performance of challenging walking decreased the dual-task cost to walking in older adults when they were tested just after stimulation. These results support the existence of a state-dependent impact of neuro-modulation that may set the stage for a more optimal neuro-rehabilitation. TRIAL REGISTRATION: Clinical Trials Gov Registrations Number: NCT02954328.

Sensor-Based and Patient-Based Assessment of Daily-Living Physical Activity in People with Parkinson's Disease: Do Motor Subtypes Play a Role?

The benefits of daily-living physical activity are clear. Nonetheless, the relationship between physical activity levels and motor subtypes of Parkinson's disease (PD), i.e., tremor dominant (TD) and postural instability gait difficulty (PIGD), have not been well-studied. It is also unclear if patient perspectives and motor symptom severity are related to objective, sensor-based assessment of daily-living activity in those subtypes. To address these questions, total daily-living physical activity was quantified in 73 patients with PD and 29 healthy controls using a 3D-accelerometer worn on the lower back for at least three days. We found that individuals with the PIGD subtype were significantly less active than healthy older adults (p = 0.007), unlike individuals with the TD subtype. Among the PIGD subtype, higher daily physical activity was negatively associated with more severe ON bradykinesia (rS = -0.499, p = 0.002), motor symptoms (higher ON MDS-UPDRS (Unified Parkinson's Disease Rating Scale motor examination)-III scores), gait difficulties (rS = -0.502, p = 0.002), motor complications (rS = 0.466, p = 0.004), and balance (rS = 0.519, p = 0.001). In contrast, among the TD subtype, disease-related characteristics were not related to daily-living physical activity. Intriguingly, physical activity was not related to self-report of ADL difficulties (scores of the MDS-UPDRS Parts I or II) in both motor subtypes. These findings highlight the importance of objective daily-living physical activity monitoring and suggest that self-report does not necessarily reflect objective physical activity levels. Furthermore, the results point to important differences in factors related to physical activity in PD motor subtypes, setting the stage for personalized treatment programs.

Long-term unsupervised mobility assessment in movement disorders.

Mobile health technologies (wearable, portable, body-fixed sensors, or domestic-integrated devices) that quantify mobility in unsupervised, daily living environments are emerging as complementary clinical assessments. Data collected in these ecologically valid, patient-relevant settings can overcome limitations of conventional clinical assessments, as they capture fluctuating and rare events. These data could support clinical decision making and could also serve as outcomes in clinical trials. However, studies that directly compared assessments made in unsupervised and supervised (eg, in the laboratory or hospital) settings point to large disparities, even in the same parameters of mobility. These differences appear to be affected by psychological, physiological, cognitive, environmental, and technical factors, and by the types of mobilities and diagnoses assessed. To facilitate the successful adaptation of the unsupervised assessment of mobility into clinical practice and clinical trials, clinicians and researchers should consider these disparities and the multiple factors that contribute to them.

Does culture affect usability? A trans-European usability and user experience assessment of a falls-risk connected health system following a user-centred design methodology carried out in a single European country.

BACKGROUND: User-centred design (UCD) is a process whereby the end-user is placed at the centre of the design process. The WIISEL (Wireless Insole for Independent and Safe Elderly Living) system is designed to monitor fall risk and to detect falls, and consists of a pair of instrumented insoles and a smartphone app. The system was designed using a three-phase UCD process carried out in Ireland, which incorporated the input of Irish end-users and multidisciplinary experts throughout. OBJECTIVE: In this paper we report the results of a usability and user experience (UX) assessment of the WIISEL system in multiple countries and thus establish whether the UCD process carried out in Ireland produced positive usability and UX results outside of Ireland. METHODS: 15 older adults across three centres (Ireland, Italy and Israel) were recruited for a three-day trial of the system in their home. Usability and UX data were captured using observations, interviews and usability questionnaires. RESULTS: The system was satisfactory in terms of the usability and UX feedback from the participants in all three countries. There was no statistically significant difference in the usability scores for the three countries tested, with the exception of comfort. CONCLUSIONS: A connected health system designed using a UCD process in a single country resulted in positive usability and UX for users in other European countries.

DaT-SPECT assessment depicts dopamine depletion among asymptomatic G2019S LRRK2 mutation carriers.

Identification of early changes in Dopamine-Transporter (DaT) SPECT imaging expected in the prodromal phase of Parkinson's disease (PD), are usually overlooked. Carriers of the G2019S LRRK2 mutation are known to be at high risk for developing PD, compared to non-carriers. In this work we aimed to study early changes in Dopamine uptake in non-manifesting PD carriers (NMC) of the G2019S LRRK2 mutation using quantitative DaT-SPECT analysis and to examine the potential for early prediction of PD. Eighty Ashkenazi-Jewish subjects were included in this study: eighteen patients with PD; thirty-one NMC and thirty-one non-manifesting non-carriers (NMNC). All subjects underwent a through clinical assessment including evaluation of motor, olfactory, affective and non-motor symptoms and DaT-SPECT imaging. A population based DaT-SPECT template was created based on the NMNC cohort, and data driven volumes-of-interest (VOIs) were defined. Comparisons between groups were performed based on VOIs and voxel-wise analysis. The striatum area of all three cohorts was segmented into four VOIs, corresponding to the right/left dorsal and ventral striatum. Significant differences in clinical measures were found between patients with PD and non-manifesting subjects with no differences between NMC and NMNC. Significantly lower uptake (p<0.001) was detected in the right and left dorsal striatum in the PD group (2.2±0.3, 2.3±0.4) compared to the NMC (4.2±0.6, 4.3±0.5) and NMNC (4.5±0.6, 4.6±0.6), and significantly (p = 0.05) lower uptake in the right dorsal striatum in the NMC group compared to NMNC. Converging results were obtained using voxel-wise analysis. Two NMC participants, who later phenoconverted into PD, demonstrated reduced uptake mainly in the dorsal striatum. No significant correlations were found between the DaT-SPECT uptake in the different VOIs and clinical and behavioral assessments in the non-manifesting groups. This study shows the clinical value of quantitative assessment of DaT-SPECT imaging and the potential for predicting PD by detection of dopamine depletion, already at the pre-symptomatic stage. Clinical registration numbers: NCT01089270 and NCT01089283.

Virtual reality and motor imagery: promising tools for assessment and therapy in Parkinson's disease.

Motor imagery (MI) and virtual reality (VR) are two evolving therapeutic approaches that make use of cognitive function to study and enhance movement, in particular, balance and mobility of people with Parkinson's disease (PD). This review examines the literature on the use of VR and MI in the assessment of mobility and as a therapeutic intervention to improve balance and gait in patients with PD. A study was eligible for inclusion if MI or VR were used to assess motor or cognitive function to improve gait, balance, or mobility in patients with PD. Data were extracted on the following categories: participants; study design; intervention (type, duration, and frequency); and outcomes. Intervention studies were evaluated for quality using the Physiotherapy Evidence Database scale. Sixteen studies were identified; 4 articles used MI and 12 used VR for assessment and treatment of gait impairments in PD. The studies included small samples and were diverse in terms of methodology. Quality of the intervention trials varied from fair for VR to good for MI. The benefits of using MI and VR for assessment and treatment were noted. Encouraging findings on the potential benefits of using MI and VR in PD were found, although further good-quality research is still needed. Questions remain on the optimal use, content of interventions, and generalizability of findings across the different stages of the disease. The possible mechanisms underlying MI and VR and recommendations for future research and therapy are also presented.