ArticleEuropean radiology2021
The role of CT texture analysis in predicting the clinical outcomes of acute ischemic stroke patients undergoing mechanical thrombectomy.
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 18 citations in OpenAlex.
- Evaluating the predictive efficacy of multi-parameter MRI based radiomic models on clinical symptom progression in perforator artery cerebral infarction.BMC medical imaging · 2026Article
- Comparable efficacy and safety of bridging therapy versus direct mechanical thrombectomy in anterior circulation large vessel occlusion stroke.American journal of translational research · 2026Article
- A predictive clinical-radiomics nomogram for early diagnosis of mesenteric arterial embolism based on non-contrast CT and biomarkers.Abdominal radiology (New York) · 2025Article
- Optimizing acute ischemic stroke outcome prediction by integrating radiomics features of DSC-PWI and perfusion parameter maps.Frontiers in neurology · 2025Article
- A CT texture-based nomogram for predicting futile reperfusion in patients with intraparenchymal hyperdensity after endovascular thrombectomy for acute anterior circulation large vessel occlusion.Frontiers in neurology · 2024Article
- Textural Analysis of the Hyperdense Artery Sign in Patients with Acute Ischemic Stroke Predicts the Outcome of Thrombectomy.Journal of cardiovascular development and disease · 2023Article
- Texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic stroke.Frontiers in neurology · 2023Article
- Applying a CT texture analysis model trained with deep-learning reconstruction images to iterative reconstruction images in pulmonary nodule diagnosis.Journal of applied clinical medical physics · 2022Article
- MRI whole-lesion texture analysis on ADC maps for the prognostic assessment of ischemic stroke.BMC medical imaging · 2022Article
- Plasma Lipid Mediators Associate With Clinical Outcome After Successful Endovascular Thrombectomy in Patients With Acute Ischemic Stroke.Frontiers in immunology · 2022Article
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Authors and funding
6 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
objectivesTo evaluate the performance of CT-based texture analysis (TA) for predicting clinical outcomes of mechanical thrombectomy (MT) in acute ischemic stroke (AIS).
methodsThis single-center, retrospective study contained 64 consecutive patients with AIS who underwent MT for large anterior circulation occlusion between December 2016 and January 2020. Patients were divided into 2 groups according to the modified Rankin scale (mRS) scores at 3 months as good outcome (mRS ≤ 2) and bad outcome (mRS > 2). Two observers examined the early ischemic changes for TA on baseline non-contrast CT images independently. Demographic, clinical, periprocedural, and texture variables were compared between the groups and ROC curves were made. Logistic regression analysis was used and a model was created to determine the independent predictors of a bad outcome.
resultsSixty-four patients (32 female, 32 male; mean age 63.03 ± 14.42) were included in the study. Fourteen texture parameters were significantly different between patients with good and bad outcomes. The long-run high gray-level emphasis (LRHGE), which is a gray-level run-length matrix (GLRLM) feature, showed the highest sensitivity (80%) and specificity (70%) rates to predict disability. The GLRLM_LRHGE value of > 4885.0 and the time from onset to puncture of > 237.5 mi were found as independent predictors of the bad outcome. The diagnostic rate was 80.0% when using the combination of the GLRLM_LRHGE and the time from onset to puncture cutoff values.
conclusionCT-based TA might be a promising modality to predict clinical outcome after MT in patients with AIS. KEY POINTS: • The gray-level run-length matrix parameters displayed higher diagnostic performance among the texture features. • The long-run high gray-level emphasis showed the highest sensitivity and specificity rates for predicting a bad outcome in stroke patients undergoing mechanical thrombectomy. • The gray-level run-length matrix_long-run high gray-level emphasis value of > 4885.0 (OR = 11.06; 95% CI = 2.51 - 48.77; p = 0.001) and the time from onset to puncture of > 237.5 min (OR = 8.55; 95% CI = 1.96 - 37.21; p = 0.004) were found as independent predictors of the bad outcome.
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