Neuroimaging in stroke

Stroke remains one of the leading causes of death and long-term disability worldwide, posing a substantial burden on healthcare systems and societies. Over the past three decades, neuroimaging has transformed every stage of stroke care, from hyperacute triage and treatment selection to the longitudinal assessment of recovery and secondary prevention. Computed tomography (CT), magnetic resonance imaging (MRI), and advanced perfusion and vascular techniques now allow clinicians to visualize the ischemic core, the salvageable penumbra, hemorrhagic transformation, and microstructural tissue injury with unprecedented spatial and temporal resolution. In parallel, the integration of artificial intelligence (AI), and multimodal imaging biomarkers is reshaping how we characterize cerebrovascular pathophysiology, predict clinical outcomes, and personalize therapeutic strategies. Despite these remarkable advances, important gaps persist in our understanding of tissue fate, collateral dynamics, neurovascular uncoupling, post-stroke plasticity, and the imaging signatures of small vessel disease and hemorrhagic stroke subtypes.This Research Topic aims to consolidate cutting-edge contributions that advance the application of neuroimaging in stroke. We welcome original research, systematic reviews, meta-analyses, methodological papers, and clinical perspectives that bridge basic neurovascular science, translational imaging research, and clinical implementation. Submissions leveraging novel acquisition protocols, quantitative analytic pipelines, machine learning frameworks, or multicenter datasets are particularly encouraged. We invite submissions covering, but not limited to, the following themes:Hyperacute imaging and treatment selection: advances in non-contrast CT, CT angiography, CT perfusion, and rapid MRI protocols for thrombolysis and endovascular thrombectomy decision-making, including extended and unknown-onset time windows.Penumbra and collateral imaging: quantitative perfusion mismatch paradigms, multiphase CTA, arterial spin labeling, and dynamic assessment of leptomeningeal collaterals.Hemorrhagic stroke: imaging predictors of hematoma expansion, perihematomal edema, and outcome in intracerebral hemorrhage; vasospasm and delayed cerebral ischemia in subarachnoid hemorrhage.Cerebral small vessel disease: white matter hyperintensities, lacunes, microbleeds, enlarged perivascular spaces, and cortical superficial siderosis as biomarkers of vascular cognitive impairment.Advanced MRI techniques: diffusion tensor and diffusion kurtosis imaging, susceptibility-weighted imaging, quantitative susceptibility mapping, vessel wall imaging, and 7T applications in cerebrovascular disease.Functional and connectomic imaging: task-based and resting-state fMRI, EEG–fMRI, and graph-theoretical analyses of post-stroke network reorganization and recovery.Artificial intelligence and radiomics: deep learning for lesion segmentation, large vessel occlusion detection, ASPECTS scoring, hemorrhage classification, and outcome prediction.Multimodal biomarkers: integration of neuroimaging with fluid biomarkers, genomics, and clinical data for precision stroke medicine.Recovery and rehabilitation: longitudinal imaging of neuroplasticity, corticospinal tract integrity, and response to neuromodulation or rehabilitative interventions.Implementation science: mobile stroke units, telestroke imaging workflows, and strategies to harmonize and democratize advanced neuroimaging globally. Topic editors: Nasser Kashou, Bella B.B. ZHANG Source: https://www.frontiersin.org/research-topics/81400/neuroimaging-in-stroke