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Substantial advances in neuroscience and cerebrovascular research have shaped our understanding of brain health and disease. The convergence of artificial intelligence, increasingly sophisticated neuroimaging techniques, and evolving diagnostic frameworks is reshaping how cerebrovascular diseases are detected, characterized, and managed (1)(2)(3). These developments have had tangible clinical impact, contributing to improved outcomes in disorders that remain among the leading causes of death and longterm disability worldwide (4,5).Cerebrovascular disease encompasses a heterogeneous group of conditions that can be broadly categorised into pathologies aXecting large-and medium-sized cerebral arteries and those involving the small perforating vessels supplying cortical, subcortical, and deep grey matter structures (6). Large-vessel disease includes acute ischemic stroke due to major arterial occlusion, atherosclerosis (including stenosing and vulnerable plaques), dissections, and aneurysmal rupture, entities that have benefited from substantial advances in interventional neuroradiology and clinical management (5)(6)(7). This is exemplified by work from Zhang et al., who demonstrate how contemporary endovascular strategies for intracranial aneurysm treatment can achieve favourable safety and eXicacy profiles. Complementing these therapeutic advances, emerging imaging biomarkers such as aneurysm wall calcification patterns are improving rupture risk stratification and informing treatment decisions, underscoring ongoing progress in the interventional management of large-vessel cerebrovascular disease (8).In contrast, cerebral small vessel disease (CSVD) represents a process involving small arteries, arterioles, venules, and capillaries which can have diXerent underlying aetiologies, most commonly arteriolosclerosis and cerebral amyloid angiopathy, but also genetic and inflammatory or immunologically mediated forms (9). CSVD accounts for a substantial proportion of ischemic strokes and spontaneous intracerebral haemorrhages and is a major contributor to vascular cognitive impairment and dementia (6).Although large-and small-vessel disease are often discussed as distinct entities, growing evidence suggests that they are intertwined (10). Shared vascular risk factors -including hypertension, diabetes, hypercholesterolemia, smoking, and aging -drive pathological changes across the cerebrovascular tree (6,10). Yet the mechanisms linking macrovascular pathology to microvascular injury, and vice versa, remain incompletely understood, though emerging evidence points to shared pathways involving endothelial dysfunction, impaired vascular reactivity, and chronic inflammation (6,10,11). This is particularly consequential because, unlike large-vessel disease, CSVD remains largely inaccessible to surgical or endovascular intervention, relying instead on medical therapy, risk factor control, and lifestyle modification. Advancing diagnostic precision and mechanistic understanding is therefore essential for identifying new preventive and therapeutic strategies.Recent progress has been driven in large part by advances in neuroimaging. Modern MRI techniques now allow detailed assessment of the vessel wall, cerebral perfusion, vascular dynamics, and tissue microstructure, underscoring that cerebrovascular disease cannot be fully captured by static measures such as infarct volume or degree of stenosis. Instead, vascular pathology exerts its eXects through dynamic processes that influence peri-lesional tissue, white matter integrity, and distributed brain networks.Imaging biomarkers sensitive to these processes are now reshaping how vascular brain injury and recovery are conceptualized (2,12). These imaging advances are exemplified by the work of Jiang et al., who synthesize evidence demonstrating that neuroimaging can capture biologically meaningful markers of brain repair following ischemic stroke, particularly within peri-infarct regions and distributed functional networks. Their findings underscore the limitations of infarct volume as a surrogate endpoint and point toward white matter integrity, functional reorganization, and perfusion as more sensitive indicators of recovery.Taken together, these findings suggest that cerebrovascular disease involves disturbances in systems-level regulation in addition to focal injury (6,11). Vascular dysfunction is associated with disrupted neurovascular coupling, impaired metabolic eXiciency, and reduced neural plasticity. Functional and metabolic adaptations frequently extend beyond the primary site of injury, reflecting bilateral and network-level responses that shape long-term outcomes. Such observations are particularly relevant to CSVD, where diXuse microvascular injury accumulates over time and manifests clinically as cognitive decline, gait disturbance, and mood disorders rather than discrete neurological deficits (6,11).Quantifying CSVD burden remains challenging, and composite imaging scores, whether visually rated or computationally derived, have emerged as practical tools to capture its multifaceted nature (2,6,13). The meta-analysis by Silva et al. supports the reliability and construct validity of these scores, while also highlighting variability related to imaging protocols, rater characteristics, and population diXerences. This variability underscores the need to relate imaging phenotypes to underlying biological mechanisms, an eXort that may benefit from integrating imaging with systemic biomarkers and longitudinal clinical data.Mounting evidence suggests that cerebrovascular pathology reflects a close interplay between cerebral and systemic processes. Associations between peripheral inflammatory markers, white matter injury, and brain atrophy, as explored by Liu et al., support the concept that immune and inflammatory pathways actively modulate microvascular injury and tissue vulnerability. These findings align with a growing body of literature implicating chronic inflammation and endothelial dysfunction as drivers of both CSVD and vascular cognitive impairment (6). Together, these findings emphasize that vascular diseases of the brain are dynamic, multifactorial disorders that benefit from integrative approaches (6,10). Advances in artificial intelligence and machine learning oXer new avenues for handling the complexity of multimodal data, enabling automated detection of subtle imaging features, improved risk stratification, and outcome prediction. When coupled with standardized imaging pipelines and biologically informed models, these approaches hold promise for translating scientific insight into clinical impact (1)(2)(3)13).In summary, recent advances have significantly enhanced the understanding of cerebrovascular disease, particularly CSVD, while also revealing persistent gaps in knowledge and available therapies. Moving beyond lesion-centric paradigms toward systems-based models that integrate vascular biology, neuroimaging, and computational tools will be essential for addressing the burden of vascular brain disease and mitigating its contribution to cognitive decline. Critical challenges remain, including the need for standardized imaging protocols across centres, validation of imaging biomarkers in diverse populations, and development of therapeutic interventions that target the mechanisms identified through advanced imaging.Dr. Carole H. Sudre serves as a scientific advisor to BrainKey. This relationship did not influence the content of this editorial. All other authors declare no competing interests.