Rezan Ashayeri Ahmadabad, Kim H Tran, Yiran Zhang, Mahesh P Kate, Sachin Mishra, Brian H Buck, Khurshid A Khan, Jeremy Rempel, Gregory W Albers, Ashfaq Shuaib
Background: Early diagnosis of large vessel occlusion (LVO) in acute stroke often requires CT angiography (CTA). Automated CT perfusion (CTP) software, which identifies blood flow abnormalities, enhances LVO diagnosis and patient selection for endovascular thrombectomy (EVT). This study evaluates the sensitivity of automated CTP images in detecting perfusion abnormalities in patients with acute ischemic stroke (AIS) and LVO or medium vessel occlusion (MeVO), compared to CTA.
Methods: We screened acute ischemic stroke patients presenting within 24 h who underwent CT, CTA, and CTP as per institutional protocol. RAPID AI software processed CTP images, while neuroradiologists reviewed CTA for intracranial arterial occlusions. Sensitivity, specificity, and accuracy of automated CTP maps in detecting occlusions were assessed.
Results: Of 790 screened patients, 31 were excluded due to lack of RAPID CTP data or poor-quality scans, leaving 759 for analysis. The median age was 71 years (IQR: 61-81), with 47% female. Among them, 678 had AIS, and 81 had AIS ruled out. CTA identified arterial occlusion in 562 patients (74%), with corresponding CTP abnormalities in 537 patients (Tmax > 6 sec). In the 197 without occlusion, CTP was negative in 161. Automated CTP maps had a sensitivity of 95.55% (CI 95: 93.50-97.10%), specificity of 81.73% (CI 95: 75.61-86.86%), negative predictive value of 98.22% (CI 95: 97.39-98.79%), positive predictive value of 63.54% (CI 95: 56.46-70.09%), and overall accuracy of 85.18% (CI 95: 82.45-87.64%).
Conclusions: Automated CTP maps demonstrated high sensitivity and negative predictive value for LVOs and MeVOs, suggesting their usefulness as a rapid diagnostic tool, especially in settings without expert neuroradiologists.
{"title":"Utility of automated CT perfusion software in acute ischemic stroke with large and medium vessel occlusion.","authors":"Rezan Ashayeri Ahmadabad, Kim H Tran, Yiran Zhang, Mahesh P Kate, Sachin Mishra, Brian H Buck, Khurshid A Khan, Jeremy Rempel, Gregory W Albers, Ashfaq Shuaib","doi":"10.1002/acn3.52207","DOIUrl":"https://doi.org/10.1002/acn3.52207","url":null,"abstract":"<p><strong>Background: </strong>Early diagnosis of large vessel occlusion (LVO) in acute stroke often requires CT angiography (CTA). Automated CT perfusion (CTP) software, which identifies blood flow abnormalities, enhances LVO diagnosis and patient selection for endovascular thrombectomy (EVT). This study evaluates the sensitivity of automated CTP images in detecting perfusion abnormalities in patients with acute ischemic stroke (AIS) and LVO or medium vessel occlusion (MeVO), compared to CTA.</p><p><strong>Methods: </strong>We screened acute ischemic stroke patients presenting within 24 h who underwent CT, CTA, and CTP as per institutional protocol. RAPID AI software processed CTP images, while neuroradiologists reviewed CTA for intracranial arterial occlusions. Sensitivity, specificity, and accuracy of automated CTP maps in detecting occlusions were assessed.</p><p><strong>Results: </strong>Of 790 screened patients, 31 were excluded due to lack of RAPID CTP data or poor-quality scans, leaving 759 for analysis. The median age was 71 years (IQR: 61-81), with 47% female. Among them, 678 had AIS, and 81 had AIS ruled out. CTA identified arterial occlusion in 562 patients (74%), with corresponding CTP abnormalities in 537 patients (Tmax > 6 sec). In the 197 without occlusion, CTP was negative in 161. Automated CTP maps had a sensitivity of 95.55% (CI 95: 93.50-97.10%), specificity of 81.73% (CI 95: 75.61-86.86%), negative predictive value of 98.22% (CI 95: 97.39-98.79%), positive predictive value of 63.54% (CI 95: 56.46-70.09%), and overall accuracy of 85.18% (CI 95: 82.45-87.64%).</p><p><strong>Conclusions: </strong>Automated CTP maps demonstrated high sensitivity and negative predictive value for LVOs and MeVOs, suggesting their usefulness as a rapid diagnostic tool, especially in settings without expert neuroradiologists.</p>","PeriodicalId":126,"journal":{"name":"Annals of Clinical and Translational Neurology","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142386585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Correction to Impact of paramagnetic rim lesions on disability and race in multiple sclerosis: mediation analysis.","authors":"","doi":"10.1002/acn3.52223","DOIUrl":"https://doi.org/10.1002/acn3.52223","url":null,"abstract":"","PeriodicalId":126,"journal":{"name":"Annals of Clinical and Translational Neurology","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142379636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Saeed Jahromi, Margherita A.G. Matarrese, Lorenzo Fabbri, Eleonora Tamilia, M. Scott Perry, Joseph R. Madsen, Jeffrey Bolton, Scellig S.D. Stone, Phillip L. Pearl, Christos Papadelis