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Practice document outlines neuroimaging strategies for diagnosing and managing posterior circulation large vessel occlusions, suggesting improved outcomes.
BACKGROUND: Posterior circulation (PC) large vessel occlusions (PC-LVO) include occlusions of vertebral arteries, basilar artery and P1 segment of posterior cerebral artery, although the latter is variably classified as a medium vessel occlusion in some studies and clinical trials. PC-LVOs account for a substantial proportion of PC strokes. PC-LVO remains challenging to diagnose due to nonspecific symptoms and limited sensitivity of CT for posterior fossa ischemic changes. However, PC-LVO is associated with substantial disability and mortality, particularly with basilar artery occlusion (BAO). Recent randomized trials demonstrate a clear benefit of endovascular thrombectomy (EVT) for BAO up to 24 hours in selected patients, shifting treatment paradigms toward imaging-guided selection. METHODS: A working group comprising select members of the Executive Committee and other members of the American Society of Functional Neuroradiology convened to develop a clinical State-of-Practice document on neuroimaging in acute PC-LVO stroke. The aim of this document is to provide a concise, practical, and evidence-informed imaging framework for the diagnosis, triage, and prognostication of patients with PC-LVO stroke in everyday neuroradiology practice. KEY POINTS: A multimodal imaging approach is necessary for PC-LVO stroke detection. NCCT is relatively insensitive for ischemia detection but remains essential for excluding hemorrhage, while CTA serves as the diagnostic cornerstone for identifying PC-LVO. CT perfusion may provide additional information, although its sensitivity in the posterior fossa is limited. DWI-MRI remains the reference standard, despite the occurrence of early false negatives and the limited reliability of DWI–FLAIR mismatch in posterior circulation stroke. Imaging biomarkers, including PC-ASPECTS and brainstem infarct scores, are important for patient selection and outcome prediction.
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Sriwastwa et al. (2026) studied this question.
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