ArticleNeurology and therapy2021
A Clinical-Radiomics Nomogram for Functional Outcome Predictions in Ischemic Stroke.
Article in Neurology and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 45 citations in OpenAlex.
- Feasibility of a Clinical-Radiomics Model to Predict the Outcomes of Acute Ischemic Stroke.Korean journal of radiology · 2022Trial
- Development of a recurrence risk prediction model for intracranial atherosclerotic stroke using HR-VWI combined with radiomics.Neuroradiology · 2026Article
- Identification of signal-based gait features and blood analytes associated with stroke status and walking speed in mild acute ischemic stroke.BMC neurology · 2026Article
- Evaluating the predictive efficacy of multi-parameter MRI based radiomic models on clinical symptom progression in perforator artery cerebral infarction.BMC medical imaging · 2026Article
- Integrating serum globulin into the ICF framework: a novel multidimensional predictive model for 1-year mRS outcomes in acute ischemic stroke.European journal of medical research · 2026Article
- Review
- Construction and Validation of a Risk Prediction Model Incorporating Temporal Muscle Thickness for Adverse Outcome in Acute Ischemic Stroke Patients.Journal of central nervous system disease · 2026Article
- Cerebrospinal fluid-based clinical-radiomics model for predicting treatment prognosis of acute ischemic stroke.Quantitative imaging in medicine and surgery · 2025Article
- Nomogram to predict 1-year cognitive decline after stent placement for unruptured intracranial aneurysms.iScience · 2025Article
- AI-driven integration of imaging and radiology language improves stroke mortality prediction.Frontiers in neurology · 2025Article
- The impracticality of radiomics research in acute ischemic stroke: from the perspective of primary healthcare institutions.Frontiers in neurology · 2025Review
- Prediction of prognosis in acute ischemic stroke after mechanical thrombectomy based on multimodal MRI radiomics and deep learning.Frontiers in neurology · 2025Article
- Serum Cystatin C and 90-Day Neurological Functional Prognosis in Acute Ischemic Stroke: Insights from a Prospective Cohort and Mendelian Randomization.International journal of general medicine · 2025Article
- Feasibility of a clinical-radiomics combined model to predict the occurrence of stroke-associated pneumonia.BMC neurology · 2024Article
- Machine learning-based nomogram: integrating MRI radiomics and clinical indicators for prognostic assessment in acute ischemic stroke.Frontiers in neurology · 2024Article
- Ischemic stroke outcome prediction with diversity features from whole brain tissue using deep learning network.Frontiers in neurology · 2024Article
- A CT-based machine learning model for using clinical-radiomics to predict malignant cerebral edema after stroke: a two-center study.Frontiers in neuroscience · 2024Article
- DWI-Based Radiomics Predicts the Functional Outcome of Endovascular Treatment in Acute Basilar Artery Occlusion.AJNR. American journal of neuroradiology · 2023Article
- MRI Radiomics and Predictive Models in Assessing Ischemic Stroke Outcome-A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
- Research on prognostic risk assessment model for acute ischemic stroke based on imaging and multidimensional data.Frontiers in neurology · 2023Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
introductionStroke remains a leading cause of death and disability worldwide. Effective and prompt prognostic evaluation is vital for determining the appropriate management strategy. Radiomics is an emerging noninvasive method used to identify the quantitative imaging indicators for predicting important clinical outcomes. This study was conducted to investigate and validate a radiomics nomogram for predicting ischemic stroke prognosis using the modified Rankin scale (mRS).
methodsA total of 598 consecutive patients with subacute infarction confirmed by diffusion-weighted imaging (DWI), from January 2018 to December 2019, were retrospectively assessed. They were assigned to the good (mRS ≤ 2) and poor (mRS > 2) functional outcome groups, respectively. Then, 399 patients examined by MR scanner 1 and 199 patients scanned by MR scanner 2 were assigned to the training and validation cohorts, respectively. Infarction lesions underwent manual segmentation on DWI, extracting 402 radiomic features. A radiomics nomogram encompassing patient characteristics and the radiomics signature was built using a multivariate logistic regression model. The performance of the nomogram was evaluated in the training and validation cohorts. Ultimately, decision curve analysis was implemented to assess the clinical value of the nomogram. The performance of infarction lesion volume was also evaluated using univariate analysis.
resultsStroke lesion volume showed moderate performance, with an area under the curve (AUC) of 0.678. The radiomics signature, including 11 radiomics features, exhibited good prediction performance. The radiomics nomogram, encompassing clinical characteristics (age, hemorrhage, and 24 h National Institutes of Health Stroke Scale score) and the radiomics signature, presented good discriminatory potential in the training cohort [AUC = 0.80; 95% confidence interval (CI) 0.75-0.86], which was validated in the validation cohort (AUC = 0.73; 95% CI 0.63-0.82). In addition, it demonstrated good calibration in the training (p = 0.55) and validation (p = 0.21) cohorts. Decision curve analysis confirmed the clinical value of this nomogram.
conclusionThis novel noninvasive clinical-radiomics nomogram shows good performance in predicting ischemic stroke prognosis.
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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.