Purpose: Biomarkers related to hemodynamics can be quantified using angiographic parametric imaging (API), which is a quantitative imaging method that uses digital subtraction angiography (DSA). We aimed to assess the accuracy of API in locating infarct core within large vessel occlusion (LVO) acute ischemic stroke (AIS) patients. Approach: Data were retrospectively collected for 25 LVO AIS patients who achieved successful recanalization. DSA data from lateral and anteroposterior (AP) views were loaded into API software to generate hemodynamic parameter maps. Relative differences in hemispherical regions for each API parameter were calculated. Ground truth infarct core locations were obtained using 24-h follow-up fluid-attenuation inversion recovery (FLAIR) MRI imaging. FLAIR MRI infarct locations were registered with DSA images to determine infarct regions in API parameter maps. Relative differences across hemispheres for each API parameter were plotted against each other. A support vector machine was used to determine the optimal hyperplane for classifying regions as infarct or healthy tissue. Results: For the lateral and AP views, respectively, the most accurate classification of infarct regions came from plotting mean transit time (MTT) versus peak height (PH) [accuracy = 0.8125 ± 0.0012 (95%)], the area under the receiver operator characteristic curve ( AUROC ) = 0.8946 ± 0.0000 (95%), and plotting MTT versus the area under the curve (AUC) [accuracy = 0.7957 ± 0.0011 (95%), AUROC = 0.8759 ± 0.0000 (95%)]. Conclusions: API provides accurate assessment of locating ischemic core in AIS LVO patients and has the potential for clinical benefit by determining infarct core location and growth in real time for intraoperative decision making. |
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CITATIONS
Cited by 12 scholarly publications and 1 patent.
Tissues
Angiography
Magnetic resonance imaging
Targeting Task Performance metric
Image registration
Arteries
Artificial intelligence