Henrik Gensicke1,2, James W Evans3,4, Fahad S Al Ajlan3,5, Dar Dowlatshahi6, Mohamed Najm3, Ana L Calleja7, Josep Puig8, Sung-lI Sohn9, Seong H Ahn10, Alexandre Y Poppe11, Robert Mikulik12, Negar Asdaghi13, Thalia S Field14, Albert Jin15, Talip Asil16, Jean-Martin Boulanger17, Michael D Hill3, Mayank Goyal3, Andrew M Demchuk3, Bijoy K Menon3. 1. Calgary Stroke Program, Departments of Clinical Neurosciences, Radiology and Community Health Sciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada. henrik.gensicke@usb.ch. 2. Stroke Center and Department of Neurology, University Hospital Basel and University of Basel, Basel, Switzerland. henrik.gensicke@usb.ch. 3. Calgary Stroke Program, Departments of Clinical Neurosciences, Radiology and Community Health Sciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada. 4. Gosford Hospital, Gosford, Australia. 5. King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia. 6. University of Ottawa, Ottawa, Ontario, Canada. 7. Universidad de Valladolid, Valladolid, Spain. 8. Dr Josep Trueta University Hospital, Girona, Spain. 9. Department of Neurology, Brain Research Institute, Keimyung University School of Medicine, Daegu, Republic of Korea. 10. Department of Neurology, Chosun University School of Medicine, Gwangju, Republic of Korea. 11. Centre Hospitalier de l'Université de Montréal, University of Montréal, Montreal, Québec, Canada. 12. International Clinical Research Center, Department of Neurology, St Ann's University Hospital, Masaryk University, Brno, Czech Republic. 13. Miller School of Medicine, University of Miami, Miami, Florida, USA. 14. University of British Columbia, Vancouver, British Columbia, Canada. 15. Queen's University Kingston, Ontario, Canada. 16. Bezmialem Vakif Univesitesi Noroloji, Istanbul, Turkey. 17. Charles LeMoyne Hospital, University of Sherbrooke, Greenfield Park, Canada.
Abstract
PURPOSE: To compare the association of different measures of intracranial thrombus permeability on non-contrast computerized tomography (NCCT) and computed tomography angiography (CTA) with recanalization with or without intravenous alteplase. METHODS: Patients with anterior circulation occlusion from the INTERRSeCT study were included. Thrombus permeability was measured on non-contrast CT and CTA using the following methods: [1] automated method, mean attenuation increase on co-registered thin (< 2.5 mm) CTA/NCCT; [2] semi-automated method, maximum attenuation increase on non-registered CTA/NCCT (ΔHUmax); [3] manual method, maximum attenuation on CTA (HUmax); and [4] visual method, residual flow grade. Primary outcome was recanalization with intravenous alteplase on the revised AOL scale (2b/3). Regression models were compared using C-statistic, Akaike (AIC), and Bayesian information criterion (BIC). RESULTS: Four hundred eighty patients were included in this analysis. Statistical models using methods 2, 3, and 4 were similar in their ability to discriminate recanalizers from non-recanalizers (C-statistic 0.667, 0.683, and 0.634, respectively); method 3 had the least information loss (AIC = 483.8; BIC = 492.2). A HUmax ≥ 89 measured with method 3 provided optimal sensitivity and specificity in discriminating recanalizers from non-recanalizers [recanalization 55.4% (95%CI 46.2-64.6) when HUmax > 89 vs. 16.8% (95%CI 13.0-20.6) when HUmax ≤ 89]. In sensitivity analyses restricted to patients with co-registered CTA/NCCT (n = 88), methods 1-4 predicted recanalization similarly (C-statistic 0.641, 0.688, 0.640, 0.648, respectively) with Method 2 having the least information loss (AIC 104.8, BIC 109.8). CONCLUSION: Simple methods that measure thrombus permeability are as reliable as complex image processing methods in discriminating recanalizers from non-recanalizers.
PURPOSE: To compare the association of different measures of intracranial thrombus permeability on non-contrast computerized tomography (NCCT) and computed tomography angiography (CTA) with recanalization with or without intravenous alteplase. METHODS:Patients with anterior circulation occlusion from the INTERRSeCT study were included. Thrombus permeability was measured on non-contrast CT and CTA using the following methods: [1] automated method, mean attenuation increase on co-registered thin (< 2.5 mm) CTA/NCCT; [2] semi-automated method, maximum attenuation increase on non-registered CTA/NCCT (ΔHUmax); [3] manual method, maximum attenuation on CTA (HUmax); and [4] visual method, residual flow grade. Primary outcome was recanalization with intravenous alteplase on the revised AOL scale (2b/3). Regression models were compared using C-statistic, Akaike (AIC), and Bayesian information criterion (BIC). RESULTS: Four hundred eighty patients were included in this analysis. Statistical models using methods 2, 3, and 4 were similar in their ability to discriminate recanalizers from non-recanalizers (C-statistic 0.667, 0.683, and 0.634, respectively); method 3 had the least information loss (AIC = 483.8; BIC = 492.2). A HUmax ≥ 89 measured with method 3 provided optimal sensitivity and specificity in discriminating recanalizers from non-recanalizers [recanalization 55.4% (95%CI 46.2-64.6) when HUmax > 89 vs. 16.8% (95%CI 13.0-20.6) when HUmax ≤ 89]. In sensitivity analyses restricted to patients with co-registered CTA/NCCT (n = 88), methods 1-4 predicted recanalization similarly (C-statistic 0.641, 0.688, 0.640, 0.648, respectively) with Method 2 having the least information loss (AIC 104.8, BIC 109.8). CONCLUSION: Simple methods that measure thrombus permeability are as reliable as complex image processing methods in discriminating recanalizers from non-recanalizers.
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