Track and treat Parkinson’s disease using wearable sensors and MRI

The research projects described in this thesis investigated the role wearable sensors and MRI can play in tracking and treating Parkinsons’s disease. This research has shown that wearable sensors can especially play an important role in home monitoring systems. Such systems can measure Parkinson’s disease symptoms at home, and can therefore give the treating clinician a better view on the disease course. This may eventually lead to better treatment adaptation. The research in this thesis has also described the role that more detailed MRI images may play in tracking and treating Parkinson’s disease. For example, this research has shown that using more detailed MRI images led to a different placement of deep brain stimulation electrodes in the brain. Further, it describes the possible role more detailed MRI images may play in the diagnostic work-up of Parkinson’s disease

Comparison of Olfactory Tract Diffusion Measures Between Early Stage Parkinson's Disease Patients and Healthy Controls Using Ultra-High Field MRI

BACKGROUND: MRI is a valuable method to assist in the diagnostic work-up of Parkinson's disease (PD). The olfactory tract (OT) has been proposed as a potential MRI biomarker for distinguishing PD patients from healthy controls. OBJECTIVE: This study aims to further investigate whether diffusion measures of the OT differ between early stage PD patients and healthy controls. METHODS: Twenty hyposmic/anosmic PD patients, 65 normosmic PD patients, and 36 normosmic healthy controls were evaluated and a 7T diffusion weighted image scan was acquired. Manual seed regions of interest were drawn in the OT region. Tractography of the OT was performed using a deterministic streamlines algorithm. Diffusion measures (fractional anisotropy and mean- radial- and axial diffusivity) of the generated streamlines were compared between groups. RESULTS: Diffusion measures did not differ between PD patients compared to healthy controls and between hyposmic/anosmic PD patients, normosmic PD patients, and normosmic healthy controls. A positive correlation was found between age and mean- and axial diffusivity within the hyposmic/anosmic PD subgroup, but not in the normosmic groups. A positive correlation was found between MDS-UPDRSIII scores and fractional anisotropy. CONCLUSION: This study showed that fiber tracking of the OT was feasible in both early stage PD and healthy controls using 7T diffusion weighted imaging data. However, 7T MRI diffusion measures of the OT are not useful as an early clinical biomarker for PD. Future work is needed to clarify the role of other OT measurements as a biomarker for PD and its different subgroups

Mobile Health Daily Life Monitoring for Parkinson Disease:Development and Validation of Ecological Momentary Assessments

Background: Parkinson disease monitoring is currently transitioning from periodic clinical assessments to continuous daily life monitoring in free-living conditions. Traditional Parkinson disease monitoring methods lack intraday fluctuation detection. Electronic diaries (eDiaries) hold the potential to collect subjective experiences on the severity and burden of motor and nonmotor symptoms in free-living conditions. Objective: This study aimed to develop a Parkinson disease-specific eDiary based on ecological momentary assessments (EMAs) and to explore its validation. Methods: An observational cohort of 20 patients with Parkinson disease used the smartphone-based EMA eDiary for 14 consecutive days without adjusting free-living routines. The eDiary app presented an identical questionnaire consisting of questions regarding affect, context, motor and nonmotor symptoms, and motor performance 7 times daily at semirandomized moments. In addition, patients were asked to complete a morning and an evening questionnaire. Results: Mean affect correlated moderate-to-strong and moderate with motor performance (R=0.38 to 0.75; P Conclusions: We presented a Parkinson disease-specific EMA eDiary. Correlations between given answers support the internal validity of the eDiary and underline EMA's potential in free-living Parkinson disease monitoring. Careful patient selection and EMA design adjustment to this targeted population and their fluctuations are necessary to generate robust proof of EMA validation in future work. Combining clinical Parkinson disease knowledge with practical EMA experience is inevitable to design and perform studies, which will lead to the successful integration of eDiaries in free-living Parkinson disease monitoring

Monitoring Parkinson's disease symptoms during daily life:a feasibility study

Parkinson's disease symptoms are most often charted using the MDS-UPDRS. Limitations of this approach include the subjective character of the assessments and a discrepant performance in the clinic compared to the home situation. Continuous monitoring using wearable devices is believed to eventually replace this golden standard, but measurements often lack a parallel ground truth or are only tested in lab settings. To overcome these limitations, this study explores the feasibility of a newly developed Parkinson's disease monitoring system, which aims to measure Parkinson's disease symptoms during daily life by combining wearable sensors with an experience sampling method application. Twenty patients with idiopathic Parkinson's disease participated in this study. During a period of two consecutive weeks, participants had to wear three wearable sensors and had to complete questionnaires at seven semi-random moments per day on their mobile phone. Wearable sensors collected objective movement data, and the questionnaires containing questions about amongst others Parkinson's disease symptoms served as parallel ground truth. Results showed that participants wore the wearable sensors during 94% of the instructed timeframe and even beyond. Furthermore, questionnaire completion rates were high (79,1%) and participants evaluated the monitoring system positively. A preliminary analysis showed that sensor data could reliably predict subjectively reported OFF moments. These results show that our Parkinson's disease monitoring system is a feasible method to use in a diverse Parkinson's disease population for at least a period of two weeks. For longer use, the monitoring system may be too intense and wearing comfort needs to be optimized.</p

Mobile Health Daily Life Monitoring for Parkinson Disease: Development and Validation of Ecological Momentary Assessments

Background: Parkinson disease monitoring is currently transitioning from periodic clinical assessments to continuous daily life monitoring in free-living conditions. Traditional Parkinson disease monitoring methods lack intraday fluctuation detection. Electronic diaries (eDiaries) hold the potential to collect subjective experiences on the severity and burden of motor and nonmotor symptoms in free-living conditions. Objective: This study aimed to develop a Parkinson disease-specific eDiary based on ecological momentary assessments (EMAs) and to explore its validation. Methods: An observational cohort of 20 patients with Parkinson disease used the smartphone-based EMA eDiary for 14 consecutive days without adjusting free-living routines. The eDiary app presented an identical questionnaire consisting of questions regarding affect, context, motor and nonmotor symptoms, and motor performance 7 times daily at semirandomized moments. In addition, patients were asked to complete a morning and an evening questionnaire. Results: Mean affect correlated moderate-to-strong and moderate with motor performance (R=0.38 to 0.75; P Conclusions: We presented a Parkinson disease-specific EMA eDiary. Correlations between given answers support the internal validity of the eDiary and underline EMA's potential in free-living Parkinson disease monitoring. Careful patient selection and EMA design adjustment to this targeted population and their fluctuations are necessary to generate robust proof of EMA validation in future work. Combining clinical Parkinson disease knowledge with practical EMA experience is inevitable to design and perform studies, which will lead to the successful integration of eDiaries in free-living Parkinson disease monitoring

Neuromelanin related ultra-high field signal intensity of the locus coeruleus differs between Parkinson’s disease and controls

Introduction: Neuromelanin related signal changes in catecholaminergic nuclei are considered as a promising MRI biomarker in Parkinson’s disease (PD). Until now, most studies have investigated the substantia nigra (SN), while signal changes might be more prominent in the locus coeruleus (LC). Ultra-high field MRI improves the visualisation of these small brainstem regions and might support the development of imaging biomarkers in PD. Objectives: To compare signal intensity of the SN and LC on Magnetization Transfer MRI between PD patients and healthy controls (HC) and to explore its association with cognitive performance in PD. Methods: This study was conducted using data from the TRACK-PD study, a longitudinal 7T MRI study. A total of 78 early-stage PD patients and 36 HC were included. A mask for the SN and LC was automatically segmented and manually corrected. Neuromelanin related signal intensity of the SN and LC was compared between PD and HC. Results: PD participants showed a lower contrast-to-noise ratio (CNR) in the right SN (p = 0.029) and left LC (p = 0.027). After adding age as a confounder, the CNR of the right SN did not significantly differ anymore between PD and HC (p = 0.055). Additionally, a significant positive correlation was found between the SN CNR and memory function. Discussion: This study confirms that neuromelanin related signal intensity of the LC differs between early-stage PD patients and HC. No significant difference was found in the SN. This supports the theory of bottom-up disease progression in PD. Furthermore, loss of SN integrity might influence working memory or learning capabilities in PD patients