Saini V, Guada L, Yavagal DR (2021) Global epidemiology of stroke and access to acute ischemic stroke interventions. Neurology 97:S6–S16. https://doi.org/10.1212/WNL.0000000000012781

Article  PubMed  Google Scholar 

Feigin VL, Brainin M, Norrving B et al (2022) World Stroke Organization (WSO): global stroke fact sheet 2022. Int J Stroke 17:18–29. https://doi.org/10.1177/17474930211065917

Article  PubMed  Google Scholar 

Tsivgoulis G, Saqqur M, Sharma VK et al (2020) Timing of recanalization and functional recovery in acute ischemic stroke. J Stroke 22:130–140. https://doi.org/10.5853/jos.2019.01648

Article  PubMed  PubMed Central  Google Scholar 

Nogueira Raul G, Jadhav Ashutosh P, Haussen Diogo C et al (2018) Thrombectomy 6 to 24 h after stroke with a mismatch between deficit and infarct. N Engl J Med 378:11–21. https://doi.org/10.1056/NEJMoa1706442

Article  CAS  PubMed  Google Scholar 

Albers GW, Marks MP, Kemp S et al (2018) Thrombectomy for stroke at 6 to 16 h with selection by perfusion imaging. N Engl J Med 378:708–718. https://doi.org/10.1056/NEJMoa1713973

Article  PubMed  PubMed Central  Google Scholar 

Briganti G, Le Moine O (2020) Artificial intelligence in medicine: today and tomorrow. Front Med. https://doi.org/10.3389/fmed.2020.00027

Adamou A, Beltsios ET, Bania A et al (2023) Artificial intelligence-driven ASPECTS for the detection of early stroke changes in non-contrast CT: a systematic review and meta-analysis. J Neurointerv Surg 15:e298–e304. https://doi.org/10.1136/jnis-2022-019447

Article  PubMed  Google Scholar 

Zebrowitz E, Dadoo S, Brabant P et al (2024) The impact of artificial intelligence on large vessel occlusion stroke detection and management: a systematic review meta-analysis. Intell-Based Med 10:100161. https://doi.org/10.1016/j.ibmed.2024.100161

Article  Google Scholar 

Zhao K, Zhao Q, Zhou P et al (2022) Can artificial intelligence be applied to diagnose intracerebral hemorrhage under the background of the fourth industrial revolution? A novel systemic review and meta-analysis. Int J Clin Pract 2022:9430097. https://doi.org/10.1155/2022/9430097

Article  PubMed  PubMed Central  Google Scholar 

Konstas AA, Goldmakher GV, Lee T-Y, Lev MH (2009) Theoretic basis and technical implementations of CT perfusion in acute ischemic stroke, Part 1: Theoretic basis. AJNR Am J Neuroradiol 30:662–668. https://doi.org/10.3174/ajnr.A1487

Article  CAS  PubMed  PubMed Central  Google Scholar 

Konstas AA, Goldmakher GV, Lee T-Y, Lev MH (2009) Theoretic basis and technical implementations of CT perfusion in acute ischemic stroke, Part 2: Technical implementations. AJNR Am J Neuroradiol 30:885–892. https://doi.org/10.3174/ajnr.A1492

Article  CAS  PubMed  PubMed Central  Google Scholar 

Vagal A, Wintermark M, Nael K et al (2019) Automated CT perfusion imaging for acute ischemic stroke. Neurology 93:888–898. https://doi.org/10.1212/WNL.0000000000008481

Article  PubMed  Google Scholar 

Yedavalli VS, Tong E, Martin D et al (2021) Artificial intelligence in stroke imaging: current and future perspectives. Clin Imaging 69:246–254. https://doi.org/10.1016/j.clinimag.2020.09.005

Article  PubMed  Google Scholar 

Turc G, Bhogal P, Fischer U et al (2019) European Stroke Organisation (ESO)—European Society for Minimally Invasive Neurological Therapy (ESMINT) guidelines on mechanical thrombectomy in acute ischaemic stroke endorsed by Stroke Alliance for Europe (SAFE). Eur Stroke J 4:6–12. https://doi.org/10.1177/2396987319832140

Article  PubMed  PubMed Central  Google Scholar 

Cereda CW, Christensen S, Campbell BC et al (2016) A benchmarking tool to evaluate computer tomography perfusion infarct core predictions against a DWI standard. J Cereb Blood Flow Metab 36:1780–1789. https://doi.org/10.1177/0271678X15610586

Article  PubMed  Google Scholar 

Fainardi E, Busto G, Morotti A (2023) Automated advanced imaging in acute ischemic stroke. Certainties and uncertainties. Eur J Radiol Open. https://doi.org/10.1016/j.ejro.2023.100524

Ladumor H, Vilanilam GK, Ameli S et al (2024) CT perfusion in stroke: comparing conventional and RAPID automated software. Curr Probl Diagn Radiol 53:201–207. https://doi.org/10.1067/j.cpradiol.2023.10.011

Article  PubMed  Google Scholar 

Albers GW (2018) Use of imaging to select patients for late window endovascular therapy. Stroke. https://www.ahajournals.org/doi/10.1161/STROKEAHA.118.021011

Campbell BC, Christensen S, Levi CR et al (2011) Cerebral blood flow is the optimal CT perfusion parameter for assessing infarct core. Stroke. https://www.ahajournals.org/doi/full/10.1161/strokeaha.111.618355

Ballout AA, Oh SY, Huang B et al (2023) Ghost infarct core: a systematic review of the frequency, magnitude, and variables of CT perfusion overestimation. J Neuroimaging 33:716–724. https://doi.org/10.1111/jon.13127

Article  PubMed  Google Scholar 

Boned S, Padroni M, Rubiera M et al (2017) Admission CT perfusion may overestimate initial infarct core: the ghost infarct core concept. J NeuroInterv Surg 9:66–69. https://doi.org/10.1136/neurintsurg-2016-012494

Article  PubMed  Google Scholar 

Sarraj A, Campbell BCV, Christensen S et al (2022) Accuracy of CT perfusion–based core estimation of follow-up infarction. Neurology 98:e2084–e2096. https://doi.org/10.1212/WNL.0000000000200269

Article  CAS  PubMed  PubMed Central  Google Scholar 

Abrams K, Dabus G (2022) Perfusion scotoma: a potential core underestimation in CT perfusion in the delayed time window in patients with acute ischemic stroke. AJNR Am J Neuroradiol 43:813–816. https://doi.org/10.3174/ajnr.A7524

Article  CAS  PubMed  PubMed Central  Google Scholar 

Nagar VA, McKinney AM, Karagulle AT, Truwit CL (2009) Reperfusion phenomenon masking acute and subacute infarcts at dynamic perfusion CT: confirmation by fusion of CT and diffusion-weighted MR images. AJR Am J Roentgenol 193:1629–1638. https://doi.org/10.2214/AJR.09.2664

Article  PubMed  Google Scholar 

Peerlings D, Bennink E, Dankbaar JW et al (2023) Standardizing the estimation of ischemic regions can harmonize CT perfusion stroke imaging. Eur Radiol 34:797–807. https://doi.org/10.1007/s00330-023-10035-1

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chung CY, Hu R, Peterson RB, Allen JW (2021) Automated processing of head CT perfusion imaging for ischemic stroke triage: a practical guide to quality assurance and interpretation. AJR Am J Roentgenol 217:1401–1416. https://doi.org/10.2214/AJR.21.26139

Article  PubMed  Google Scholar 

Austein F, Riedel C, Kerby T et al (2016) Comparison of perfusion CT software to predict the final infarct volume after thrombectomy. Stroke. https://www.ahajournals.org/doi/full/10.1161/STROKEAHA.116.013147

Xiong Y, Huang CC, Fisher M et al (2019) Comparison of automated CT perfusion softwares in evaluation of acute ischemic stroke. J Stroke Cerebrovasc Dis. https://doi.org/10.1016/j.jstrokecerebrovasdis.2019.104392

Bivard A, Churilov L, Ma H et al (2022) Does variability in automated perfusion software outputs for acute ischemic stroke matter? Reanalysis of EXTEND perfusion imaging. CNS Neurosci Ther. https://onlinelibrary.wiley.com/doi/10.1111/cns.13756

Stanton RJ, Wang LL, Smith MS et al (2022) Differences in automated perfusion software: do they matter clinically? Stroke Vasc Interv Neurol. https://www.ahajournals.org/doi/10.1161/SVIN.122.000424

Zhou X, Nan Y, Ju J et al (2022) Comparison of two software packages for perfusion imaging: ischemic core and penumbra estimation and patient triage in acute ischemic stroke. Cells 11:2547. https://doi.org/10.3390/cells11162547

Article  PubMed  PubMed Central  Google Scholar 

Pisani L, Haussen DC, Mohammaden M et al (2023) Comparison of CT perfusion software packages for thrombectomy eligibility. Ann Neurol 94:848–855. https://doi.org/10.1002/ana.26748

Article  CAS  PubMed  Google Scholar 

Bushnaq S, Hassan AE, Delora A et al (2024) A comparison of CT perfusion output of Rapid.AI and Viz.ai software in the evaluation of acute ischemic stroke. AJNR Am J Neuroradiol. https://doi.org/10.3174/ajnr.A8196

Lin L, Bivard A, Levi CR, Parsons MW (2014) Comparison of computed tomographic and magnetic resonance perfusion measurements in acute ischemic stroke. Stroke 45:1727–1732. https://doi.org/10.1161/STROKEAHA.114.005419

Article  PubMed  Google Scholar 

Bivard A, Churilov L, Ma H et al (2022) Does variability in automated perfusion software outputs for acute ischemic stroke matter? Reanalysis of EXTEND perfusion imaging. CNS Neurosci Ther 28:139–144. https://doi.org/10.1111/cns.13756

Article  PubMed  Google Scholar 

Bendszus M, Fiehler J, Subtil F et al (2023) Endovascular thrombectomy for acute ischaemic stroke with established large infarct: multicentre, open-label, randomised trial. Lancet 402:1753–1763. https://doi.org/10.1016/S0140-6736(23)02032-9

Article