ABSTRACT Here we launch an international initiative to understand Parkinson’s disease dementia (PDD), using a novel tractometry approach for fine-scale mapping of the brain’s microstructure. Up to 80% of the 8.5 million people diagnosed with Parkinson’s disease (PD) worldwide will develop dementia within a decade of diagnosis, with devastating consequences for everyday functioning, caregiver burden, and heightened morbidity and mortality. In addition to the immense personal toll of dementia in PD, the economic burden of PD in North America will exceed $37 billion by 2037. Symptomatic treatments are available, but no disease modifying therapeutics exist, making PD a lifelong, incurable disorder. Recent innovations in imaging - by us and others - reveal early microstructural changes in brain white matter (WM); their progression is strongly associated with dementia onset and with mild cognitive impairment (MCI) in people living with PD. Even so, prior PDD studies are plagued by small sample sizes, low statistical power, poor replication, and findings whose generalizability and reliability is unknown. With so many studies assessing so few patients, there is a pressing need to integrate international data to achieve samples with the statistical power to detect prognostic markers in PDD. To address this, we launch a global initiative with unprecedented power to understand what leads to dementia in PD - what are the primary risk factors, and what processes in the brain are progressing in those who develop dementia in PD versus those who do not. Building on our pilot data that merged global data in an internationally coordinated analysis of diffusion tensor images from 1,654 individuals with PD and 885 controls from 17 sites in 9 countries, our work will reveal how WM microstructure deteriorates as dementia develops in PD, which WM pathways show changes associated with dementia, and which individuals diagnosed with PD are most likely to progress to dementia. We deploy - on a global scale - our novel tractometry method, Bundle Analytics (BUAN), to map fine-scale microstructural alterations in PD-related dementia, and its precursor, PD with MCI (N=3,539 participants scanned with MRI). Our Specific Aims are to: (1) Create an age-dependent statistical reference model for WM microstructure in the brain's fiber bundles throughout adult life; (2) Identify along-tract microstructural biomarkers of PDD; and (3) predict decline to dementia from PD with MCI, identifying which subjects will progress to dementia is crucial for personalized treatment planning. To boost predictive accuracy, we will merge global data on vascular disease assessed with FLAIR imaging, based on pilot work that revealed in patients with PD-MCI that WMH volume was associated with PD dementia conversion. Overall, we hypothesize that tractometry and FLAIR imaging will each add significant prognostic value relative to the baseline clinical data alone; by identifying which neuroimaging data predi...