{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:44:15Z","timestamp":1760147055902,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,1,2]],"date-time":"2023-01-02T00:00:00Z","timestamp":1672617600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research Project of Healthcare for Cadres of Sichuan province","award":["2021-229","2022NSFSC1473"],"award-info":[{"award-number":["2021-229","2022NSFSC1473"]}]},{"name":"Sichuan Provincial Natural Science Foundation (Youth Project)","award":["2021-229","2022NSFSC1473"],"award-info":[{"award-number":["2021-229","2022NSFSC1473"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>(1) Background: Follow-up infarct volume (FIV) may have implications for prognostication in acute ischemic stroke patients. Factors predicting the discrepancy between FIV and 90-day outcomes are poorly understood. We aimed to develop a comprehensive predictive model of FIV and explore factors associated with the discrepancy. (2) Methods: Patients with acute anterior circulation large vessel occlusion were included. Baseline clinical and CT features were extracted and analyzed, including the CTP-based hypoperfusion index (HI) and the NCCT-based e-ASPECT, measured by automated software. FIV was assessed on follow-up NCCT at 3\u20137 days. Multiple linear regression was used to construct the predictive model. Subgroup analysis was performed to explore factors associated with poor outcomes (90-mRS scores 3\u20136) in small FIV (&lt;70 mL). (3) Results: There were 170 patients included. Baseline e-ASPECT, infarct core volume, hypoperfusion volume, HI, baseline international normalized ratio, and successful recanalization were associated with FIV and included in constructing the predictive model. Baseline NIHSS, baseline hypertension, stroke history, and current tobacco use were associated with poor outcomes in small FIV. (4) Conclusions: A comprehensive predictive model (including HI) of FIV was constructed. We also emphasized the importance of hypertension and smoking status at baseline for the functional outcomes in patients with a small FIV.<\/jats:p>","DOI":"10.3390\/diagnostics13010152","type":"journal-article","created":{"date-parts":[[2023,1,3]],"date-time":"2023-01-03T02:05:53Z","timestamp":1672711553000},"page":"152","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Follow-Up Infarct Volume Prediction by CTP-Based Hypoperfusion Index, and the Discrepancy between Small Follow-Up Infarct Volume and Poor Functional Outcome\u2014A Multicenter Study"],"prefix":"10.3390","volume":"13","author":[{"given":"Pengyu","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Radiology, Sichuan Provincial People\u2019s Hospital, University of Electronic Science and Technology of China, Chengdu 610056, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8236-5956","authenticated-orcid":false,"given":"Ran","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiology, Sichuan Provincial People\u2019s Hospital, University of Electronic Science and Technology of China, Chengdu 610056, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siyun","family":"Liu","sequence":"additional","affiliation":[{"name":"GE Healthcare, Beijing 100176, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jincheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lixiang","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Radiology, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin 300071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Song","sequence":"additional","affiliation":[{"name":"Minhang Hospital, Fudan University, Shanghai 200437, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoqiang","family":"Tang","sequence":"additional","affiliation":[{"name":"The Affiliated Changzhou No. 2 People\u2019s Hospital of Nanjing Medical University, Changzhou 213003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Boyu","family":"Chen","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital, China Medical University, Shenyang 110122, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiting","family":"Yang","sequence":"additional","affiliation":[{"name":"Lanzhou University Second Hospital, Lanzhou 730030, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengcheng","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Washington, Seattle, WA 98101, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ajay","family":"Malhotra","sequence":"additional","affiliation":[{"name":"Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06501, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1443-2643","authenticated-orcid":false,"given":"Yuting","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiology, Sichuan Provincial People\u2019s Hospital, University of Electronic Science and Technology of China, Chengdu 610056, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1056\/NEJMoa1411587","article-title":"A Randomized Trial of Intraarterial Treatment for Acute Ischemic Stroke","volume":"372","author":"Berkhemer","year":"2015","journal-title":"N. Engl. J. Med."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2296","DOI":"10.1056\/NEJMoa1503780","article-title":"Thrombectomy within 8 Hours after Symptom Onset in Ischemic Stroke","volume":"372","author":"Jovin","year":"2015","journal-title":"N. Engl. J. Med."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2213","DOI":"10.1007\/s00415-021-10410-2","article-title":"Relationship between the degree of recanalization and functional outcome in acute ischemic stroke is mediated by penumbra salvage volume","volume":"268","author":"Broocks","year":"2021","journal-title":"J. Neurol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"e14773","DOI":"10.1111\/ijcp.14773","article-title":"Infarct volume and outcome of cerebral ischaemia, a systematic review and meta-analysis","volume":"75","author":"Meng","year":"2021","journal-title":"Int. J. Clin. Pract."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1212\/WNL.0000000000002860","article-title":"Early CT changes in patients admitted for thrombectomy: Intrarater and interrater agreement","volume":"87","author":"Farzin","year":"2016","journal-title":"Neurology"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1161\/STROKEAHA.114.006564","article-title":"Alberta stroke program early computed tomographic scoring performance in a series of patients undergoing computed tomography and MRI: Reader agreement, modality agreement, and outcome prediction","volume":"46","author":"McTaggart","year":"2015","journal-title":"Stroke"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Wang, T., Xing, H., Li, Y., Wang, S., Liu, L., Li, F., and Jing, H. (2022). Deep learning-based automated segmentation of eight brain anatomical regions using head CT images in PET\/CT. BMC Med. Imaging, 22.","DOI":"10.1186\/s12880-022-00807-4"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1177\/02841851221075789","article-title":"Automated ASPECTS in acute ischemic stroke: Comparison of the overall scores and Hounsfield unit values of two software packages and radiologists with different levels of experience","volume":"64","author":"Li","year":"2022","journal-title":"Acta Radiol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.1007\/s00415-020-09798-0","article-title":"Prediction contribution of the cranial collateral circulation to the clinical and radiological outcome of ischemic stroke","volume":"267","author":"Conrad","year":"2020","journal-title":"J. Neurol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"e941","DOI":"10.1016\/j.wneu.2018.08.008","article-title":"Final Infarct Volume of <10 cm(3) is a Strong Predictor of Return to Home in Nonagenarians Un-dergoing Mechanical Thrombectomy","volume":"119","author":"Tonetti","year":"2018","journal-title":"World Neurosurg."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1136\/neurintsurg-2020-017184","article-title":"Endovascular reperfusion outcomes in patients with a stroke and low ASPECTS is highly dependent on baseline infarct volumes","volume":"14","author":"Bouslama","year":"2021","journal-title":"J. NeuroInterventional Surg."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3021","DOI":"10.1093\/eurheartj\/ehy339","article-title":"2018 ESC\/ESH Guidelines for the management of arterial hypertension: The Task Force for the management of arterial hypertension of the European Society of Cardiology (ESC) and the European Society of Hypertension (ESH)","volume":"39","author":"Williams","year":"2018","journal-title":"Eur. Heart J."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"American Diabetes Association Professional Practice Committee (2022). 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2022. Diabetes Care, 45, S17\u2013S38.","DOI":"10.2337\/dc22-S002"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2650","DOI":"10.1161\/STROKEAHA.113.001972","article-title":"Recommendations on angiographic revascularization grading standards for acute ischemic stroke: A consensus statement","volume":"44","author":"Zaidat","year":"2013","journal-title":"Stroke"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2104","DOI":"10.1212\/WNL.0b013e3181aa5329","article-title":"ABC\/2 for rapid clinical estimate of infarct, perfusion, and mismatch volumes","volume":"72","author":"Sims","year":"2009","journal-title":"Neurology"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1002\/ana.24543","article-title":"Ischemic core and hypoperfusion volumes predict infarct size in SWIFT PRIME","volume":"79","author":"Albers","year":"2015","journal-title":"Ann. Neurol."},{"key":"ref_17","first-page":"695","article-title":"Early prediction of final infarct volume with material decomposition images of dual-energy CT after mechanical thrombectomy","volume":"63","author":"Anraths","year":"2020","journal-title":"Neuroradiology"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2683","DOI":"10.1161\/STROKEAHA.114.006163","article-title":"Computed Tomographic Angiography and Cerebral Blood Volume Can Predict Final Infarct Volume and Outcome After Recanalization","volume":"45","author":"Lum","year":"2014","journal-title":"Stroke"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"932","DOI":"10.1161\/STROKEAHA.116.015472","article-title":"Predictive Value of RAPID Assessed Perfusion Thresholds on Final Infarct Volume in SWIFT PRIME (Solitaire with the Intention for Thrombectomy as Primary Endovascular Treatment)","volume":"48","author":"Mokin","year":"2017","journal-title":"Stroke"},{"key":"ref_20","first-page":"198","article-title":"Baseline ASPECTS and e-ASPECTS Correlation with Infarct Volume and Functional Outcome in Patients Undergoing Mechanical Thrombectomy","volume":"29","author":"Martins","year":"2018","journal-title":"J. Neuroimaging"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"101589","DOI":"10.1016\/j.media.2019.101589","article-title":"Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning","volume":"59","author":"Robben","year":"2019","journal-title":"Med. Image Anal."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2786","DOI":"10.1161\/STROKEAHA.115.010710","article-title":"Relationships Between Imaging Assessments and Outcomes in Solitaire with the Intention for Thrombectomy as Primary Endovascular Treatment for Acute Ischemic Stroke","volume":"46","author":"Albers","year":"2015","journal-title":"Stroke"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1136\/neurintsurg-2017-013724","article-title":"Association of follow-up infarct volume with functional outcome in acute ischemic stroke: A pooled analysis of seven randomized trials","volume":"10","author":"Boers","year":"2018","journal-title":"J. NeuroInterventional Surg."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1161\/STROKEAHA.116.015156","article-title":"Associations of Ischemic Lesion Volume with Functional Outcome in Patients with Acute Ischemic Stroke: 24-Hour Versus 1-Week Imaging","volume":"48","author":"Bucker","year":"2017","journal-title":"Stroke"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1148\/radiol.2015151586","article-title":"Evolution of Volume and Signal Intensity on Fluid-attenuated Inversion Recovery MR Images after Endovascular Stroke Therapy","volume":"280","author":"Federau","year":"2016","journal-title":"Radiology"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1002\/ana.25320","article-title":"Hypoperfusion ratio predicts infarct growth during transfer for thrombectomy","volume":"84","author":"Guenego","year":"2018","journal-title":"Ann. Neurol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1161\/STROKEAHA.121.034444","article-title":"Prediction of Stroke Infarct Growth Rates by Baseline Perfusion Imaging","volume":"53","author":"Wouters","year":"2022","journal-title":"Stroke"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1018","DOI":"10.1161\/STROKEAHA.113.003857","article-title":"Hypoperfusion Intensity Ratio Predicts Infarct Progression and Functional Outcome in the DEFUSE 2 Cohort","volume":"45","author":"Olivot","year":"2014","journal-title":"Stroke"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1253\/circj.CJ-16-0707","article-title":"Relationship Between Infarct Volume and Prothrombin Time-International Normalized Ratio in Ischemic Stroke Patients with Nonvalvular Atrial Fibrillation","volume":"81","author":"Matsumoto","year":"2017","journal-title":"Circ. J."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"106630","DOI":"10.1016\/j.cmpb.2022.106630","article-title":"ISP-Net: Fusing features to predict ischemic stroke infarct core on CT perfusion maps","volume":"215","author":"Zhu","year":"2022","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1578","DOI":"10.1161\/STROKEAHA.118.022649","article-title":"Artificial Neural Network Computer Tomography Perfusion Prediction of Ischemic Core","volume":"50","author":"Kasasbeh","year":"2019","journal-title":"Stroke"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"e748","DOI":"10.1016\/j.wneu.2020.04.139","article-title":"Large Infarct Volume Post Thrombectomy: Characteristics, Outcomes, and Predictors","volume":"139","author":"Tonetti","year":"2020","journal-title":"World Neurosurg."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1389","DOI":"10.1161\/STROKEAHA.115.012364","article-title":"Acute Stroke Imaging Research Roadmap III Imaging Selection and Outcomes in Acute Stroke Reperfusion Clinical Trials: Consensus Recommendations and Further Research Priorities","volume":"47","author":"Warach","year":"2016","journal-title":"Stroke"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1161\/STROKEAHA.118.023392","article-title":"Persistent Target Mismatch Profile >24 Hours After Stroke Onset in DEFUSE 3","volume":"50","author":"Christensen","year":"2019","journal-title":"Stroke"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"e2132376","DOI":"10.1001\/jamanetworkopen.2021.32376","article-title":"Assessment of Discrepancies Between Follow-up Infarct Volume and 90-Day Outcomes Among Pa-tients With Ischemic Stroke Who Received Endovascular Therapy","volume":"4","author":"Ganesh","year":"2021","journal-title":"JAMA Netw. Open"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2","DOI":"10.3174\/ajnr.A6883","article-title":"Artificial Intelligence and Acute Stroke Imaging","volume":"42","author":"Soun","year":"2020","journal-title":"Am. J. Neuroradiol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1148\/radiol.2021203964","article-title":"A Detailed Analysis of Infarct Patterns and Volumes at 24-hour Noncontrast CT and Diffu-sion-weighted MRI in Acute Ischemic Stroke Due to Large Vessel Occlusion: Results from the ESCAPE-NA1 Trial","volume":"300","author":"Ospel","year":"2021","journal-title":"Radiology"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"105567","DOI":"10.1016\/j.jstrokecerebrovasdis.2020.105567","article-title":"White Matter Acute Infarct Volume After Thrombectomy for Anterior Circulation Large Vessel Occlusion Stroke is Associated with Long Term Outcomes","volume":"30","author":"Regenhardt","year":"2020","journal-title":"J. Stroke Cerebrovasc. Dis."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2426","DOI":"10.1161\/STROKEAHA.117.017513","article-title":"Association of Computed Tomography Ischemic Lesion Location with Functional Outcome in Acute Large Vessel Occlusion Ischemic Stroke","volume":"48","author":"Ernst","year":"2017","journal-title":"Stroke"}],"container-title":["Diagnostics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4418\/13\/1\/152\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T17:56:37Z","timestamp":1760118997000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4418\/13\/1\/152"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,2]]},"references-count":39,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["diagnostics13010152"],"URL":"https:\/\/doi.org\/10.3390\/diagnostics13010152","relation":{},"ISSN":["2075-4418"],"issn-type":[{"type":"electronic","value":"2075-4418"}],"subject":[],"published":{"date-parts":[[2023,1,2]]}}}