{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T04:31:07Z","timestamp":1786336267314,"version":"build-2736575974"},"reference-count":40,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T00:00:00Z","timestamp":1786320000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurol."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To develop and validate an integrated nomogram combining MRI radiomics features with clinical variables for predicting 30-day progression risk in patients with acute ischemic stroke (AIS), and to deploy a web-based visualization tool for clinical application.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective two-center study included 254 AIS patients. Radiomics features were extracted from DWI using MaZda, and key features were selected by LASSO logistic regression to build a radiomics signature. Clinical predictors were identified using logistic regression. Radiomics, clinical, and combined models were developed and evaluated using area under the curve (AUC), net reclassification index (NRI), and integrated discrimination improvement (IDI), calibration analysis, and decision curve analysis (DCA). Optimal cutoffs were determined in the training cohort using the Youden index and then directly applied to the external validation cohort without re-optimization. The corresponding training-derived thresholds were \u22121.2023 for the clinical model, \u22121.0368 for the radiomics model, and \u22122.3639 for the combined model. Bootstrap resampling (1,000 repetitions) was used for internal validation of the combined model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Eight optimal radiomics features were selected from 300 extracted features. Multivariate analysis identified four independent predictors: Radiomics score (Radscore) (OR\u202f=\u202f2.23, 95% CI: 1.28\u20135.11), National Institutes of Health Stroke Scale (NIHSS) score (OR\u202f=\u202f1.57, 95% CI: 1.25\u20132.14), type 2 diabetes mellitus (OR\u202f=\u202f9.28, 95% CI: 2.02\u201356.03), and monocytes (MO) (OR\u202f=\u202f1.08, 95% CI: 1.02\u20131.16). The combined model showed favorable discriminative performance with AUCs of 0.945 (95%CI: 0.903\u20130.987) and 0.904 (95%\n                      <jats:italic>CI:<\/jats:italic>\n                      0.854\u20130.954) in the training and validation cohorts, respectively. When the training-derived cutoff of \u22122.3639 was applied to the validation cohort, the combined model achieved 93.75% sensitivity, 73.95% specificity, and 83.85% balanced accuracy. Bootstrap internal validation yielded an optimism-corrected C-index of 0.912 and a corrected calibration slope of 0.769. The combined model outperformed the clinical-only and radiomics-only models, although the external validation should still be interpreted as an initial cross-center assessment.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The integrated radiomics-clinical nomogram incorporating Radscore, NIHSS score, type 2 diabetes mellitus (T2DM), and MO showed potential for predicting 30-day progression risk in patients with AIS. This web-based tool may support early risk stratification, but further large-scale prospective validation is required before routine clinical application.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fneur.2026.1774830","type":"journal-article","created":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T04:23:13Z","timestamp":1786335793000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A web-based radiomics nomogram combining MRI features and clinical data for predicting 30-day progression of acute ischemic stroke: a two-center study"],"prefix":"10.3389","volume":"17","author":[{"given":"Xiaohua","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Radiology, The Affiliated Hospital of Xuzhou Medical University","place":["Xuzhou, Jiangsu, China"]},{"name":"First School of Clinical Medicine, Xuzhou Medical University","place":["Xuzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pugang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Neurology, The 334 Affiliated Hospital of Nanchang University","place":["Nanchang, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huashuo","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Public Health, Xuzhou Medical University","place":["Xuzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wanruo","family":"Zhang","sequence":"additional","affiliation":[{"name":"First School of Clinical Medicine, Xuzhou Medical University","place":["Xuzhou, Jiangsu, China"]},{"name":"Department of Neurology, The Affiliated Hospital of Xuzhou Medical University","place":["Xuzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Radiology, The Affiliated Hospital of Xuzhou Medical University","place":["Xuzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaodong","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiology, The Affiliated Hospital of Xuzhou Medical University","place":["Xuzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Radiology, The Affiliated Hospital of Xuzhou Medical University","place":["Xuzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liguo","family":"Dong","sequence":"additional","affiliation":[{"name":"First School of Clinical Medicine, Xuzhou Medical University","place":["Xuzhou, Jiangsu, China"]},{"name":"Department of Neurology, The Affiliated Hospital of Xuzhou Medical University","place":["Xuzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,10]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"759","DOI":"10.1161\/CIRCULATIONAHA.116.025250","article-title":"Prevalence, incidence, and mortality of stroke in China: results from a Nationwide population-based survey of 480\u202f687 adults","volume":"135","author":"Wang","year":"2017","journal-title":"Circulation"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"394","DOI":"10.1016\/S1474-4422(18)30500-3","article-title":"Stroke in China: advances and challenges in epidemiology, prevention, and management","volume":"18","author":"Wu","year":"2019","journal-title":"Lancet Neurol"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"846","DOI":"10.1016\/S1474-4422(15)00140-4","article-title":"Endovascular stent thrombectomy: the new standard of care for large vessel ischaemic stroke","volume":"14","author":"Campbell","year":"2015","journal-title":"Lancet Neurol"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"1012896","DOI":"10.3389\/fneur.2022.1012896","article-title":"Diffusion-weighted imaging-based radiomics for predicting 1-year ischemic stroke recurrence","volume":"13","author":"Wang","year":"2022","journal-title":"Front Neurol"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"e076406","DOI":"10.1136\/bmjopen-2023-076406","article-title":"Prediction of recurrent ischaemic stroke using radiomics data and machine learning methods in patients with acute ischaemic stroke: protocol for a multicentre, large sample, prospective observational cohort study in China","volume":"13","author":"Li","year":"2023","journal-title":"BMJ Open"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"858","DOI":"10.3390\/brainsci12070858","article-title":"Prediction model of hemorrhage transformation in patient with acute ischemic stroke based on multiparametric MRI radiomics and machine learning","volume":"12","author":"Meng","year":"2022","journal-title":"Brain Sci"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"107093","DOI":"10.1016\/j.cmpb.2022.107093","article-title":"Combining machine learning with radiomics features in predicting outcomes after mechanical thrombectomy in patients with acute ischemic stroke","volume":"225","author":"Li","year":"2022","journal-title":"Comput Methods Prog Biomed"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"2488","DOI":"10.1161\/STROKEAHA.120.030334","article-title":"Clot-based radiomics predict a mechanical thrombectomy strategy for successful recanalization in acute ischemic stroke","volume":"51","author":"Hofmeister","year":"2020","journal-title":"Stroke"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1136\/svn-2021-001333","article-title":"Functional status at 30 and 90 days after mild ischaemic 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depolarizations","volume":"125","author":"Eikermann-Haerter","year":"2012","journal-title":"Circulation"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"232","DOI":"10.1038\/nature09613","article-title":"Glial and neuronal control of brain blood flow","volume":"468","author":"Attwell","year":"2010","journal-title":"Nature"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"1615","DOI":"10.2337\/diabetes.54.6.1615","article-title":"The pathobiology of diabetic complications: a unifying mechanism","volume":"54","author":"Brownlee","year":"2005","journal-title":"Diabetes"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"2215","DOI":"10.1016\/S0140-6736(10)60484-9","article-title":"Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective 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J"},{"key":"ref35","volume-title":"Predicting Short-term (30-day) Mortality in Patients with Ischemic Stroke Using the Baseline Score of the National Institutes of Health Stroke Scale","author":"Fabjan","year":"2011"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1097\/JCN.0000000000000198","article-title":"Retrospective study on National Institutes of Health stroke scale as a predictor of patient recovery after stroke","volume":"31","author":"Jain","year":"2016","journal-title":"J Cardiovasc Nurs"},{"key":"ref37","doi-asserted-by":"publisher","first-page":"319","DOI":"10.3389\/fncel.2014.00319","article-title":"Post-ischemic inflammation regulates neural damage and protection","volume":"8","author":"Shichita","year":"2014","journal-title":"Front Cell Neurosci"},{"key":"ref38","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1007\/978-3-7091-9465-2_6","article-title":"Leukocytes, macrophages and secondary brain damage following cerebral ischemia","volume":"66","author":"Tomita","year":"1996","journal-title":"Acta Neurochir Suppl"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"3530","DOI":"10.7150\/thno.24475","article-title":"CCR2-dependent monocytes\/macrophages exacerbate acute brain injury but promote functional recovery after ischemic stroke in mice","volume":"8","author":"Fang","year":"2018","journal-title":"Theranostics"},{"key":"ref40","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.pjnns.2017.08.011","article-title":"Monocyte\/high-density lipoprotein ratio predicts the mortality in ischemic stroke patients","volume":"52","author":"Bolayir","year":"2017","journal-title":"Neurol Neurochir Pol"}],"container-title":["Frontiers in 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