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This study develops and internally validates a multimodal nomogram that integrates clinical, imaging, and laboratory variables to predict MBE following reperfusion in anterior-circulation large-vessel occlusion. A LASSO-selected multivariable logistic model is assessed using discrimination, calibration, and decision-analytic 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nomogram integrating clinical, imaging, and laboratory data to predict malignant brain edema after reperfusion in acute ischemic stroke  \nWenhao Gong1\\#, Haotian Xia2\\#, Shuguang Chu2, Jianhua Zhang2  \n1Department of Radiology, Shanghai Seventh People’s Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China; 2Department of Radiology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China  \nContributions: (I) Conception and design: W Gong, H Xia, J Zhang; (II) Administrative support: J Zhang; (III) Provision of study materials or patients: S Chu; (IV) Collection and assembly of data: W Gong, H Xia; (V) Data analysis and interpretation: All authors; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.  \n\\#These authors contributed equally to this work as co-first authors.  \nCorrespondence to: Jianhua Zhang, PhD. Department of Radiology, Shanghai East Hospital, Tongji University School of Medicine, No. 150 Jimo  \nRoad, Pudong New Area, Shanghai 200120, China. Email: [zhangjianhua7228@sina.com](zhangjianhua7228@sina.com).  \nBackground: Malignant brain edema (MBE) is a life-threatening complication of acute ischemic stroke (AIS) after reperfusion therapy, often leading to fatal herniation or severe disability. Early identification of patients at high risk for MBE is critical but remains challenging due to limited predictive tools. In this study, we aimed to develop and internally validate a multimodal nomogram integrating clinical, imaging, and laboratory variables to predict MBE after reperfusion in anterior-circulation large vessel occlusion (LVO)  \nstroke.  \nMethods: We retrospectively enrolled 214 consecutive AIS patients who underwent mechanical thrombectomy between 2018 and 2023. After standardizing candidate variables, we performed least absolute shrinkage and selection operator (LASSO)-logistic regression with the one-standard-error rule and stratified five-fold cross-validation for variable selection and collinearity handling. Selected variables were entered into a multivariable logistic model to construct the nomogram. Model discrimination [area under the curve (AUC)] and Brier score were evaluated using stratified five-fold out-of-fold predictions. Calibration was assessed by bootstrap resampling (B=1,000) with reporting of calibration slope, intercept, and the Hosmer-Lemeshow test P value. Clinical utility was examined using decision curve analysis (DCA) and a clinical impact curve  \n(CIC) .  \nResults: MBE occurred in 62 patients (29%) . The final model included seven predictors: relative cerebral blood flow (rCBF) \u003C40% volume, delay time (DT) >6.0 s volume, infarct growth rate (IGR), diastolic blood pressure (DBP), neutrophil count (N), collateral circulation score (CCS), and lactate dehydrogenase (LDH) .  \nApparent AUC in the modeling cohort was 0.87 [95% confidence interval (CI): 0.82–0.93]; five-fold out-offold AUC was 0.860. After 1,000-bootstrap optimism correction, AUC was 0.85 (95% CI: 0.80–0.91) with a Brier score of 0.13. The calibration slope was ~0.86, the intercept was near 0, and Hosmer-Lemeshow P=0.173 . DCA showed net benefit across probability thresholds of 0.10–0.70, and the CIC indicated good  \nidentification of high-risk individuals.  \nConclusions: A LASSO-selected, internally validated nomogram enables early risk stratification and decision support for MBE after reperfusion in AIS. Prospective external validation in independent cohorts is  \nrequired before clinical adoption to confirm reliability and generalizability.  \n© AME Publishing Company. Quant Imaging Med Surg 2026;16(1):16 | [https://dx.doi.org/10.21037/qims-2025-1153](https://dx.doi.org/10.21037/qims-2025-1153)  \nPage 2 of 13 Gong et al. Clinical-imaging-lab nomogram for brain edema prediction  \nKeywords: Malignant brain edema (MBE); acute ischemic stroke (AIS); mechanical thro","cbCaisHh9KpFJduo","https://ap.wps.com/l/cbCaisHh9KpFJduo","pdf",1500542,13,"English","# Introduction\n# Methods\n# Results\n# Conclusions","[{\"question\":\"What was the primary goal of developing the multimodal nomogram?\",\"answer\":\"To predict malignant brain edema after reperfusion in patients with acute ischemic stroke by integrating clinical, imaging, and laboratory variables.\"},{\"question\":\"How were predictors selected and the model validated internally?\",\"answer\":\"Variables were selected using LASSO-logistic regression with the one-standard-error rule and stratified five-fold cross-validation, then assessed with out-of-fold discrimination and bootstrap calibration.\"},{\"question\":\"What performance and calibration results did the nomogram achieve?\",\"answer\":\"The model showed strong discrimination (AUC about 0.87 apparent and 0.85 after bootstrap correction), with calibration slope near 0.86 and Hosmer-Lemeshow P=0.173.\"}]","Development and internal validation of a multimodal nomogram integrating clinical, imaging, and laboratory data to predict malignant brain edema after reperfusion in acute ischemic stroke | PDF",1790748837,33,[147,151],{"page_no":22,"url":148,"width":149,"height":150},"https://res-academy.cache.wpscdn.com/upload/kdocshare/2026-11-08/f76f5b8c2b0c81c72acc616e8878d7d1.webp",983,1287,{"page_no":26,"url":152,"width":153,"height":154},"https://res-academy.cache.wpscdn.com/upload/kdocshare/2026-11-08/f60f2790b62fea2bd3f48cd53af4f8af.webp",982,1286]