We will develop a new treatment modality for Parkinson’s disease, neurofeedback with functional magnetic resonance imaging (fMRI) signals, that emulates the effects of deep brain stimulation (DBS) on brain networks. New neuromodulation treatments are needed for in the field of neurodegenerative disorders (as recognised by this call for proposals) - current invasive neuromodulation protocols with DBS provide good symptomatic relief for motor symptoms of Parkinson’s disease (PD) but have inconsistent effects on the often equally disabling non-motor symptoms, whereas the clinical effects of non-invasive brain stimulation techniques have been generally limited so far. In order to emulate the success of DBS on motor symptoms non-invasively we need to measure its effects directly with fMRI and target these fMRI signal patterns with neurofeedback. Similarly, for better relief of non-motor symptoms we need to map the relevant network both functionally and anatomically and identify the relevant neurofeedback targets. Finally we need to show that patients with PD can indeed self-regulate activation in these networks through neurofeedback training. This project will thus include simultaneous DBS-fMRI studies and anatomical connectivity mapping of the cortico-subcortical networks supporting symptom relief, classification analysis of therapeutic activation patterns, and proof of concept of the feasibility of neurofeedback with these signals. In WP (work package) 1 we will scan PD patients during DBS of the subthalamic nucleus (STN) and compare “on” (with motor symptom improvement) and “off” states with classification analysis of functional connectivity patterns. We will also use online fMRI during DBS in patients who show improvement of non-motor symptoms and combine this information with the knowledge of anatomical connectivity of the non-motor portion of the STN. We will then demonstrate proof-of-concept of neurofeedback training targeting these signals in PD patients with a focus on motor symptoms and the non-motor symptoms depression and anxiety (WP2-3). This work will lay the foundation for clinical trials of this promising non-invasive neuromodulation strategy that can be used both in patients without implanted DBS electrodes and as an add-on to DBS.

Measuring and quantifying how a patient feels or functions during treatment is an important endpoint in cancer clinical trials. It is generally accepted that the collection of PRO data in cancer clinical trials allows the inclusion of the patient’s voice in the risk-benefit assessment of therapies. However, no standards exist on how to analyse, interpret or report health-related quality of life (HRQOL) and other patient-reported outcomes (PROs). This initiative wants to pursue efforts in addressing the urgent need for standardization, by setting clear and validated standards that are tailored to and endorsed by all relevant stakeholders. With a strong international and multi-stakeholder Consortium, the initiative aims at finding consensus on suitable methods to analyse valid PRO objectives in cancer randomized clinical trials (RCTs) and ways to communicate these PRO findings in a standardized way that is understandable to all. To achieve this aim, SISAQOL-IMI will identify valid PRO research objectives and match these with appropriate statistical methods for PRO analysis in cancer RCTs. Translation to the estimands framework will be provided. Furthermore, the possibility of extending these recommendations to single-arm trial designs will be explored. Recommendations on clinically meaningful change for PRO instruments, as well as design considerations and ways for assessing quality of collected PRO data will be developed, and tools and templates for presentation and visualization of PRO findings freely made available. Strong emphasis is put on continuous collaboration with patient advocacy representatives throughout the project. Increased interpretability, adoption and full use of PRO outcomes for all stakeholders is expected by providing consensus-based and validated recommendations and communication tools for PRO data, ultimately resulting in better communication and shared decision making, improved outcomes, treatment satisfaction and care.