Data and methods Accepted project proposals Clinical outcomes of young stroke patients predicted from multivariate lesion-behaviour and lesion network mapping.

Author: Anil Tuladhar
Affiliation(s): Donders Center of Medical Neurosciences, Radboud university medical centre        
Research question(s): 
Can we identify the strategic lesion locations and the lesion-associated networks that are linked to clinical outcomes (such as cognitive impairments, depression and apathy) and develop a method for more accurate risk stratification for post-stroke deficits?
Link: OSF Preregistration

Abstract:
Ischaemic stroke is a major health concern, with over two million young adults experiencing this condition annually. Despite typically being associated with older adults, approximately 10% to 20% of ischaemic stroke cases occur in individuals aged 18 to 50 years. Furthermore, recent data have shown a growing incidence of ischaemic stroke among young adults worldwide, highlighting the attention to the stroke in young adults. The socioeconomic impact of stroke in young adults is substantial, including high healthcare costs, loss of labour productivity and long-term consequences, such as cognitive impairments, vascular dementia, apathy, and depression.
Despite its importance, the underlying mechanisms of post-stroke outcomes in young adults are still largely unknown. One potential factor is lesion location, which refers to the specific location and size of brain damage resulting from stroke. Prior studies in older stroke patients have employed voxel-based lesion symptom mapping (VLSM), a technique that investigates the relationship between lesion location and behavioral measurements, to identify the strategic regions for post-stroke consequences. However, there is still a lack of evidence on how lesion location influences post-stroke outcomes in young adults.
In addition to the lesion location, brain network disruption is another potential factor that may impact post-stroke outcomes in young adults. Brain networks comprise interconnected brain regions that work together to perform normal neuropsychological functions. Stroke can damage not only a single region but also its connections with other regions, resulting in network dysfunction. To investigate this effect, researchers have employed functional or structural lesion network mapping (LNM) approach, which use data from healthy individuals to infer how stroke lesions affect brain networks. This approach has been applied to uncover the mechanism of post-stroke depression and predict short-term cognitive decline in older stroke patients. However, further studies are needed to examine the association between damaged networks and clinical outcomes in young stroke patients.