ArticleJournal of visualized experiments : JoVE2018
A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage.
Article in Journal of visualized experiments : JoVE, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Incidence and Factors in Delayed Neurological Deficits after Subarachnoid Hemorrhage in Mice.Brain hemorrhages · 2024Article
- Automated Grading of Cerebral Vasospasm to Standardize Computed Tomography Angiography Examinations After Subarachnoid Hemorrhage.Frontiers in neurology · 2020Article
- Volumetric analysis of intracranial vessels: a novel tool for evaluation of cerebral vasospasm.International journal of computer assisted radiology and surgery · 2019Article
- Large Vessel Vasospasm Is Not Associated with Cerebral Cortical Hypoperfusion in a Murine Model of Subarachnoid Hemorrhage.Translational stroke research · 2018Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Subarachnoid hemorrhage (SAH) is a subtype of hemorrhagic stroke. Cerebral vasospasm that occurs in the aftermath of the bleeding is an important factor determining patient outcome and is therefore frequently taken as a study endpoint. However, in small animal studies on SAH, quantification of cerebral vasospasm is a major challenge. Here, an ex vivo method is presented that allows quantification of volumes of entire vessel segments, which can be used as an objective measure to quantify cerebral vasospasm. In a first step, endovascular casting of the cerebral vasculature is performed using a radiopaque casting agent. Then, cross-sectional imaging data are acquired by micro computed tomography. The final step involves 3-dimensional reconstruction of the virtual vascular tree, followed by an algorithm to calculate center lines and volumes of the selected vessel segments. The method resulted in a highly accurate virtual reconstruction of the cerebrovascular tree shown by a diameter-based comparison of anatomical samples with their virtual reconstructions. Compared with vessel diameters alone, the vessel volumes highlight the differences between vasospastic and non-vasospastic vessels shown in a series of SAH and sham-operated mice.
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Registered trials
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