ArticleNeuroradiology2021
Use of quantitative angiographic methods with a data-driven model to evaluate reperfusion status (mTICI) during thrombectomy.
Article in Neuroradiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 19 citations in OpenAlex.
- Enhancing cerebral vasculature analysis with pathlength-corrected 2D angiographic parametric imaging: A feasibility study.Medical physics · 2024Article
- Angiographic velocimetry analysis using contrast dilution gradient method with a 1000 frames per second photon-counting detector.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- Identification of infarct core and ischemic penumbra using computed tomography perfusion and deep learning.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- Hemodynamic Changes in Patients with Chronic Internal Carotid Artery Occlusion After Recanalization.Neuropsychiatric disease and treatment · 2023Article
- The age factor influencing long-term physical functionality in stroke patients undergoing intra-arterial thrombectomy treatment.Medicine · 2022Article
- Identification of successful cerebral reperfusions (mTICI ≥2b) using an artificial intelligence strategy.Neuroradiology · 2022Article
- Article
- Use of biplane quantitative angiographic imaging with ensemble neural networks to assess reperfusion status during mechanical thrombectomy.Proceedings of SPIE--the International Society for Optical Engineering · 2021Article
- Initial investigation of predicting hematoma expansion for intracerebral hemorrhage using imaging biomarkers and machine learning.Proceedings of SPIE--the International Society for Optical EngineeringArticle
- Prognosis of ischemia recurrence in patients with moderate intracranial atherosclerotic disease using quantitative MRA measurements.Proceedings of SPIE--the International Society for Optical EngineeringArticle
- Recovery of complete time density curves from incomplete angiographic data using recurrent neural networks.Proceedings of SPIE--the International Society for Optical EngineeringArticle
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
Abstract
purposeIntra-procedural assessment of reperfusion during mechanical thrombectomy (MT) for emergent large vessel occlusion (LVO) stroke is traditionally based on subjective evaluation of digital subtraction angiography (DSA). However, semi-quantitative diagnostic tools which encode hemodynamic properties in DSAs, such as angiographic parametric imaging (API), exist and may be used for evaluation of reperfusion during MT. The objective of this study was to use data-driven approaches, such as convolutional neural networks (CNNs) with API maps, to automatically assess reperfusion in the neuro-vasculature during MT procedures based on the modified thrombolysis in cerebral infarction (mTICI) scale.
methodsDSAs from patients undergoing MTs of anterior circulation LVOs were collected, temporally cropped to isolate late arterial and capillary phases, and quantified using API peak height (PH) maps. PH maps were normalized to reduce injection variability. A CNN was developed, trained, and tested to classify PH maps into 2 outcomes (mTICI 0,1,2a/mTICI 2b,2c,3) or 3 outcomes (mTICI 0,1,2a/mTICI 2b/mTICI 2c,3), respectively. Ensembled networks were used to combine information from multiple views (anteroposterior and lateral).
resultsThe study included 383 DSAs. For the 2-outcome classification, average accuracy was 81.0% (95% CI, 79.0-82.9%), and the area under the receiver operating characteristic curve (AUROC) was 0.86 (0.84-0.88). For the 3-outcome classification, average accuracy was 64.0% (62.0-66.0), and AUROC values were 0.85 (0.83-0.87), 0.74 (0.71-0.77), and 0.78 (0.76-0.81) for the mTICI 0,1,2a, mTICI 2b, and mTICI 2c,3 classes, respectively.
conclusionThis study demonstrated the feasibility of using hemodynamic information in API maps with data-driven models to autonomously assess intra-procedural reperfusion during MT.
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