Dataset Information

Three variations in rabbit angiographic stroke models.

ABSTRACT:

Purpose

To develop angiographic models of embolic stroke in the rabbit using pre-formed clot or microspheres to model clinical situations ranging from transient ischemic events to severe ischemic stroke.

Materials and methods

New Zealand White rabbits (N=151) received angiographic access to the internal carotid artery (ICA) from a femoral approach. Variations of emboli type and quantity of emboli were tested by injection into the ICA. These included fresh clots (1.0-mm length, 3-6h), larger aged clots (4.0-mm length, 3 days), and 2 or 3 insoluble microspheres (700-900 ?m). Neurological assessment scores (NAS) were based on motor, sensory, balance, and reflex measures. Rabbits were euthanized at 4, 7, or 24h after embolization, and infarct volume was measured as a percent of total brain volume using 2,3,5-triphenyltetrazolium chloride (TTC).

Results

Infarct volume percent at 24 h after stroke was lower for rabbits embolized with fresh clot (0.45±0.14%), compared with aged clot (3.52±1.31%) and insoluble microspheres (3.39±1.04%). Overall NAS (including posterior vessel occlusions) were positively correlated to infarct volume percent measurements in the fresh clot (r=0.50), aged clot (r=0.65) and microsphere (r=0.62) models (p<0.001).

Conclusion

The three basic angiographic stroke models may be similar to human transient ischemic attacks (TIA) (fresh clot), major strokes that can be thrombolysed (aged clot), or major strokes with insoluble emboli such as atheromata (microspheres). Model selection can be tailored to specific research needs.

SUBMITTER: Culp WC

PROVIDER: S-EPMC3563856 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Publications

Three variations in rabbit angiographic stroke models.

Culp William C WC Woods Sean D SD Brown Aliza T AT Lowery John D JD Hennings Leah J LJ Skinner Robert D RD Borrelli Michael J MJ Roberson Paula K PK

Journal of neuroscience methods 20121108 2

<h4>Purpose</h4>To develop angiographic models of embolic stroke in the rabbit using pre-formed clot or microspheres to model clinical situations ranging from transient ischemic events to severe ischemic stroke.<h4>Materials and methods</h4>New Zealand White rabbits (N=151) received angiographic access to the internal carotid artery (ICA) from a femoral approach. Variations of emboli type and quantity of emboli were tested by injection into the ICA. These included fresh clots (1.0-mm length, 3-6 ...[more]

PMID: 23142182

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Project description:Background and purposeAs "time is brain" in acute stroke triage, the need for automated prognostication tools continues to increase, particularly in rapidly expanding tele-stroke settings. We aimed to create an automated prognostication tool for anterior circulation large vessel occlusion (LVO) stroke based on admission CTA radiomics.MethodsWe automatically extracted 1116 radiomics features from the anterior circulation territory on admission CTAs of 829 acute LVO stroke patients who underwent mechanical thrombectomy in two academic centers. We trained, optimized, validated, and compared different machine-learning models to predict favorable outcome (modified Rankin Scale ≤ 2) at discharge and 3-month follow-up using four different input sets: "Radiomics", "Radiomics + Treatment" (radiomics, post-thrombectomy reperfusion grade, and intravenous thrombolysis), "Clinical + Treatment" (baseline clinical variables and treatment), and "Combined" (radiomics, treatment, and baseline clinical variables).ResultsFor discharge outcome prediction, models were optimized/trained on n = 494 and tested on an independent cohort of n = 100 patients from Yale. Receiver operating characteristic analysis of the independent cohort showed no significant difference between best-performing Combined input models (area under the curve, AUC = 0.77) versus Radiomics + Treatment (AUC = 0.78, p = 0.78), Radiomics (AUC = 0.78, p = 0.55), or Clinical + Treatment (AUC = 0.77, p = 0.87) models. For 3-month outcome prediction, models were optimized/trained on n = 373 and tested on an independent cohort from Yale (n = 72), and an external cohort from Geisinger Medical Center (n = 232). In the independent cohort, there was no significant difference between Combined input models (AUC = 0.76) versus Radiomics + Treatment (AUC = 0.72, p = 0.39), Radiomics (AUC = 0.72, p = 0.39), or Clinical + Treatment (AUC = 76, p = 0.90) models; however, in the external cohort, the Combined model (AUC = 0.74) outperformed Radiomics + Treatment (AUC = 0.66, p < 0.001) and Radiomics (AUC = 0.68, p = 0.005) models for 3-month prediction.ConclusionMachine-learning signatures of admission CTA radiomics can provide prognostic information in acute LVO stroke candidates for mechanical thrombectomy. Such objective and time-sensitive risk stratification can guide treatment decisions and facilitate tele-stroke assessment of patients. Particularly in the absence of reliable clinical information at the time of admission, models solely using radiomics features can provide a useful prognostication tool.

Dataset Information

Three variations in rabbit angiographic stroke models.

Purpose

Materials and methods

Results

Conclusion

Publications

Three variations in rabbit angiographic stroke models.

Similar Datasets

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