Haryadi Prasetya1, Lucas A Ramos1, Thabiso Epema1, Kilian M Treurniet2, Bart J Emmer2, Ido R van den Wijngaard3,4, Guang Zhang2, Manon Kappelhof2, Olvert A Berkhemer2,5,6,7, Albert J Yoo8, Yvo Bewm Roos9, Robert J van Oostenbrugge10, Diederik Wj Dippel7, Wim H van Zwam5, Aad van der Lugt6, Bas Ajm de Mol11, Charles Blm Majoie2, Ed van Bavel1, Henk A Marquering1,2. 1. Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam, the Netherlands. 2. Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, the Netherlands. 3. Department of Neurology, Haaglanden Medical Center, the Hague, the Netherlands. 4. Department of Neurology, Leiden University Medical Centers, Leiden, the Netherlands. 5. Department of Radiology, Maastricht University Medical Center and Cardiovascular Research Institute, Maastricht, the Netherlands. 6. Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands. 7. Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands. 8. Division of Neurointervention, Texas Stroke Institute, Dallas, TX, USA. 9. Department of Neurology, Amsterdam University Medical Centers, Amsterdam, the Netherlands. 10. Department of Neurology, Maastricht University Medical Center and Cardiovascular Research Institute, Maastricht, the Netherlands. 11. Department of Cardiothoracic Surgery, Amsterdam University Medical Centers, Amsterdam, the Netherlands.
Abstract
BACKGROUND: The Thrombolysis in Cerebral Infarction (TICI) scale is an important outcome measure to evaluate the quality of endovascular stroke therapy. The TICI scale is ordinal and observer-dependent, which may result in suboptimal prediction of patient outcome and inconsistent reperfusion grading. AIMS: We present a semi-automated quantitative reperfusion measure (quantified TICI (qTICI)) using image processing techniques based on the TICI methodology. METHODS: We included patients with an intracranial proximal large vessel occlusion with complete, good quality runs of anteroposterior and lateral digital subtraction angiography from the MR CLEAN Registry. For each vessel occlusion, we identified the target downstream territory and automatically segmented the reperfused area in the target downstream territory on final digital subtraction angiography. qTICI was defined as the percentage of reperfused area in target downstream territory. The value of qTICI and extended TICI (eTICI) in predicting favorable functional outcome (modified Rankin Scale 0-2) was compared using area under receiver operating characteristics curve and binary logistic regression analysis unadjusted and adjusted for known prognostic factors. RESULTS: In total, 408 patients with M1 or internal carotid artery occlusion were included. The median qTICI was 78 (interquartile range 58-88) and 215 patients (53%) had an eTICI of 2C or higher. qTICI was comparable to eTICI in predicting favorable outcome with area under receiver operating characteristics curve of 0.63 vs. 0.62 (P = 0.8) and 0.87 vs. 0.86 (P = 0.87), for the unadjusted and adjusted analysis, respectively. In the adjusted regression analyses, both qTICI and eTICI were independently associated with functional outcome. CONCLUSION: qTICI provides a quantitative measure of reperfusion with similar prognostic value for functional outcome to eTICI score.
BACKGROUND: The Thrombolysis in Cerebral Infarction (TICI) scale is an important outcome measure to evaluate the quality of endovascular stroke therapy. The TICI scale is ordinal and observer-dependent, which may result in suboptimal prediction of patient outcome and inconsistent reperfusion grading. AIMS: We present a semi-automated quantitative reperfusion measure (quantified TICI (qTICI)) using image processing techniques based on the TICI methodology. METHODS: We included patients with an intracranial proximal large vessel occlusion with complete, good quality runs of anteroposterior and lateral digital subtraction angiography from the MR CLEAN Registry. For each vessel occlusion, we identified the target downstream territory and automatically segmented the reperfused area in the target downstream territory on final digital subtraction angiography. qTICI was defined as the percentage of reperfused area in target downstream territory. The value of qTICI and extended TICI (eTICI) in predicting favorable functional outcome (modified Rankin Scale 0-2) was compared using area under receiver operating characteristics curve and binary logistic regression analysis unadjusted and adjusted for known prognostic factors. RESULTS: In total, 408 patients with M1 or internal carotid artery occlusion were included. The median qTICI was 78 (interquartile range 58-88) and 215 patients (53%) had an eTICI of 2C or higher. qTICI was comparable to eTICI in predicting favorable outcome with area under receiver operating characteristics curve of 0.63 vs. 0.62 (P = 0.8) and 0.87 vs. 0.86 (P = 0.87), for the unadjusted and adjusted analysis, respectively. In the adjusted regression analyses, both qTICI and eTICI were independently associated with functional outcome. CONCLUSION: qTICI provides a quantitative measure of reperfusion with similar prognostic value for functional outcome to eTICI score.
Entities:
Keywords:
Digital subtraction angiography; endovascular therapy; ischemic stroke; reperfusion