ArticleFrontiers in neuroscience2020
Prediction of Malignant Acute Middle Cerebral Artery Infarction via Computed Tomography Radiomics.
Article in Frontiers in neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 31 citations in OpenAlex.
- Radiomics model based on dual-energy CTA reconstructed images of infarcted brain tissue to predict malignant cerebral edema in stroke patients.Neuroradiology · 2026Article
- Quantitative Imaging of the Heterogeneity of Brain Potassium Depletion in Experimental Focal Ischemia.bioRxiv : the preprint server for biology · 2026Article
- Predicting malignant cerebral edema after acute ischemic stroke: a machine-learning model with multi-region radiomics.Quantitative imaging in medicine and surgery · 2025Article
- A clinical-radiomics nomogram to predict early neurological deterioration in patients with stroke undergoing intravenous thrombolysis.Journal of the Chinese Medical Association : JCMA · 2025Article
- Diffusion-Weighted Imaging-Based Radiomics Features and Machine Learning Method to Predict the 90-Day Prognosis in Patients With Acute Ischemic Stroke.The neurologist · 2025Article
- Development of a multimodal model combining radiomics and deep learning to predict malignant cerebral edema after endovascular thrombectomy.Frontiers in neurology · 2025Article
- An integrated nomogram combining clinical and radiomic features of hyperattenuated imaging markers to predict malignant cerebral edema following endovascular thrombectomy.Quantitative imaging in medicine and surgery · 2024Article
- A comprehensive review for artificial intelligence on neuroimaging in rehabilitation of ischemic stroke.Frontiers in neurology · 2024Review
- Prediction of hemorrhagic transformation via pre-treatment CT radiomics in acute ischemic stroke patients receiving endovascular therapy.The British journal of radiology · 2023Article
- Predicting prostate cancer in men with PSA levels of 4-10 ng/mL: MRI-based radiomics can help junior radiologists improve the diagnostic performance.Scientific reports · 2023Article
- MRI Radiomics and Predictive Models in Assessing Ischemic Stroke Outcome-A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
- Texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic stroke.Frontiers in neurology · 2023Article
- Clinical features and FLAIR radiomics nomogram for predicting functional outcomes after thrombolysis in ischaemic stroke.Frontiers in neuroscience · 2023Article
- OEDL: an optimized ensemble deep learning method for the prediction of acute ischemic stroke prognoses using union features.Frontiers in neurology · 2023Article
- Understanding Acquired Brain Injury: A Review.Biomedicines · 2022Review
- Optimized Deconvolutional Algorithm-based CT Perfusion Imaging in Diagnosis of Acute Cerebral Infarction.Contrast media & molecular imaging · 2022Article
- DCE-MRI radiomics models predicting the expression of radioresistant-related factors of LRP-1 and survivin in locally advanced rectal cancer.Frontiers in oncology · 2022Article
- Nomograms predict prognosis and hospitalization time using non-contrast CT and CT perfusion in patients with ischemic stroke.Frontiers in neuroscience · 2022Article
- Review
- Developing a model for estimating infarction onset time based on computed tomography radiomics in patients with acute middle cerebral artery occlusion.BMC medical imaging · 2021Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Malignant middle cerebral artery infarction (mMCAi) is a serious complication of cerebral infarction usually associated with poor patient prognosis. In this retrospective study, we analyzed clinical information as well as non-contrast computed tomography (NCCT) and computed tomography angiography (CTA) data from patients with cerebral infarction in the middle cerebral artery (MCA) territory acquired within 24 h from symptoms onset. Then, we aimed to develop a model based on the radiomics signature to predict the development of mMCAi in cerebral infarction patients. Patients were divided randomly into training (
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.