BACKGROUND: Stroke is a sudden interruption in the blood supply to a part of the brain, causing loss of neurological function. It is the third leading cause of death in Canada and affects mainly older people. In the acute setting, neuroimaging is integral to stroke evaluation and decision-making. The neuroimaging results guide patient selection for mechanical thrombectomy. Using automated image processing techniques facilitates efficient review of this information and communication between centres. We conducted a health technology assessment of automated CT perfusion imaging as a tool for selecting stroke patients with anterior circulation occlusion for mechanical thrombectomy. This assessment included an evaluation of clinical effectiveness, cost-effectiveness, and the budget impact of publicly funding automated CT perfusion imaging. METHODS: We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each study using QUADAS-2 or the Cochrane risk-of-bias tool, and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We performed a systematic economic literature search and approximated cost-effectiveness based on previous analyses. We also analyzed the budget impact of publicly funding automated CT perfusion imaging to evaluate people with acute ischemic stroke in Ontario. RESULTS: Automated CT perfusion imaging had a sensitivity of 84% for identifying the infarct core (dead tissue that does not recover despite restoring blood flow with mechanical thrombectomy), compared with diffusion-weighted MRI imaging at 24 hours. One study reported that 7% of patients were misclassified with respect to eligibility for mechanical thrombectomy (either erroneously classified as eligible or erroneously classified non-eligible). Two randomized controlled trials (DEFUSE 3 and DAWN) demonstrated the efficacy of mechanical thrombectomy up to 24 hours after stroke onset, with patient selection guided by automated CT perfusion imaging. These data showed that a significantly higher proportion of patients in the mechanical thrombectomy group achieved functional independence compared with the standard care group (DEFUSE 3: risk ratio: 2.67 [95% confidence interval 1.60-4.48]; DAWN: adjusted rate difference: 33% [95% credible interval 21%-44%]; GRADE: Moderate).A previous health technology assessment in stroke patients presenting at 0 to 6 hours after stroke symptom onset and the results from recent randomized controlled trials for patients presenting at 6 to 24 hours informed the evaluation of cost-effectiveness. Mechanical thrombectomy informed by automated CT perfusion imaging to assess eligibility is likely to be cost-effective for patients presenting at 6 to 24 hours after stroke symptom onset. The annual budget impact of publicly funding automated CT perfusion imaging in Ontario over the next 5 years would be $1.3 million in year 1 and $0.9 million each year thereafter. Some of the costs of automated CT perfusion imaging could be offset by avoiding unnecessary patient transfers between hospitals. CONCLUSIONS: Automated CT perfusion imaging has an acceptable sensitivity and specificity for detecting brain areas that have been affected by stroke. In patients selected for mechanical thrombectomy using automated CT perfusion imaging, there was significant improvement in functional independence. Mechanical thrombectomy informed by automated CT perfusion imaging is likely to be cost-effective. We estimate that publicly funding automated CT perfusion imaging in Ontario would result in additional costs of $1.3 million in year 1 and $0.9 million per year thereafter.
BACKGROUND: Stroke is a sudden interruption in the blood supply to a part of the brain, causing loss of neurological function. It is the third leading cause of death in Canada and affects mainly older people. In the acute setting, neuroimaging is integral to stroke evaluation and decision-making. The neuroimaging results guide patient selection for mechanical thrombectomy. Using automated image processing techniques facilitates efficient review of this information and communication between centres. We conducted a health technology assessment of automated CT perfusion imaging as a tool for selecting stroke patients with anterior circulation occlusion for mechanical thrombectomy. This assessment included an evaluation of clinical effectiveness, cost-effectiveness, and the budget impact of publicly funding automated CT perfusion imaging. METHODS: We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each study using QUADAS-2 or the Cochrane risk-of-bias tool, and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We performed a systematic economic literature search and approximated cost-effectiveness based on previous analyses. We also analyzed the budget impact of publicly funding automated CT perfusion imaging to evaluate people with acute ischemic stroke in Ontario. RESULTS: Automated CT perfusion imaging had a sensitivity of 84% for identifying the infarct core (dead tissue that does not recover despite restoring blood flow with mechanical thrombectomy), compared with diffusion-weighted MRI imaging at 24 hours. One study reported that 7% of patients were misclassified with respect to eligibility for mechanical thrombectomy (either erroneously classified as eligible or erroneously classified non-eligible). Two randomized controlled trials (DEFUSE 3 and DAWN) demonstrated the efficacy of mechanical thrombectomy up to 24 hours after stroke onset, with patient selection guided by automated CT perfusion imaging. These data showed that a significantly higher proportion of patients in the mechanical thrombectomy group achieved functional independence compared with the standard care group (DEFUSE 3: risk ratio: 2.67 [95% confidence interval 1.60-4.48]; DAWN: adjusted rate difference: 33% [95% credible interval 21%-44%]; GRADE: Moderate).A previous health technology assessment in stroke patients presenting at 0 to 6 hours after stroke symptom onset and the results from recent randomized controlled trials for patients presenting at 6 to 24 hours informed the evaluation of cost-effectiveness. Mechanical thrombectomy informed by automated CT perfusion imaging to assess eligibility is likely to be cost-effective for patients presenting at 6 to 24 hours after stroke symptom onset. The annual budget impact of publicly funding automated CT perfusion imaging in Ontario over the next 5 years would be $1.3 million in year 1 and $0.9 million each year thereafter. Some of the costs of automated CT perfusion imaging could be offset by avoiding unnecessary patient transfers between hospitals. CONCLUSIONS: Automated CT perfusion imaging has an acceptable sensitivity and specificity for detecting brain areas that have been affected by stroke. In patients selected for mechanical thrombectomy using automated CT perfusion imaging, there was significant improvement in functional independence. Mechanical thrombectomy informed by automated CT perfusion imaging is likely to be cost-effective. We estimate that publicly funding automated CT perfusion imaging in Ontario would result in additional costs of $1.3 million in year 1 and $0.9 million per year thereafter.
Authors: William J Powers; Alejandro A Rabinstein; Teri Ackerson; Opeolu M Adeoye; Nicholas C Bambakidis; Kyra Becker; José Biller; Michael Brown; Bart M Demaerschalk; Brian Hoh; Edward C Jauch; Chelsea S Kidwell; Thabele M Leslie-Mazwi; Bruce Ovbiagele; Phillip A Scott; Kevin N Sheth; Andrew M Southerland; Deborah V Summers; David L Tirschwell Journal: Stroke Date: 2018-01-24 Impact factor: 7.914
Authors: Olvert A Berkhemer; Puck S S Fransen; Debbie Beumer; Lucie A van den Berg; Hester F Lingsma; Albert J Yoo; Wouter J Schonewille; Jan Albert Vos; Paul J Nederkoorn; Marieke J H Wermer; Marianne A A van Walderveen; Julie Staals; Jeannette Hofmeijer; Jacques A van Oostayen; Geert J Lycklama à Nijeholt; Jelis Boiten; Patrick A Brouwer; Bart J Emmer; Sebastiaan F de Bruijn; Lukas C van Dijk; L Jaap Kappelle; Rob H Lo; Ewoud J van Dijk; Joost de Vries; Paul L M de Kort; Willem Jan J van Rooij; Jan S P van den Berg; Boudewijn A A M van Hasselt; Leo A M Aerden; René J Dallinga; Marieke C Visser; Joseph C J Bot; Patrick C Vroomen; Omid Eshghi; Tobien H C M L Schreuder; Roel J J Heijboer; Koos Keizer; Alexander V Tielbeek; Heleen M den Hertog; Dick G Gerrits; Renske M van den Berg-Vos; Giorgos B Karas; Ewout W Steyerberg; H Zwenneke Flach; Henk A Marquering; Marieke E S Sprengers; Sjoerd F M Jenniskens; Ludo F M Beenen; René van den Berg; Peter J Koudstaal; Wim H van Zwam; Yvo B W E M Roos; Aad van der Lugt; Robert J van Oostenbrugge; Charles B L M Majoie; Diederik W J Dippel Journal: N Engl J Med Date: 2014-12-17 Impact factor: 91.245
Authors: Nicole Mittmann; Soo Jin Seung; Michael D Hill; Stephen J Phillips; Vladimir Hachinski; Robert Coté; Brian H Buck; Ariane Mackey; David J Gladstone; David C Howse; Ashfaq Shuaib; Mike Sharma Journal: Can J Neurol Sci Date: 2012-11 Impact factor: 2.104
Authors: Julian P T Higgins; Douglas G Altman; Peter C Gøtzsche; Peter Jüni; David Moher; Andrew D Oxman; Jelena Savovic; Kenneth F Schulz; Laura Weeks; Jonathan A C Sterne Journal: BMJ Date: 2011-10-18
Authors: Aquilla S Turk; Jordan Asher Magarick; Don Frei; Kyle Michael Fargen; Imran Chaudry; Christine A Holmstedt; Joyce Nicholas; J Mocco; Raymond D Turner; Daniel Huddle; David Loy; Richard Bellon; Gwendolyn Dooley; Robert Adams; Michelle Whaley; Chris Fanale; Edward Jauch Journal: J Neurointerv Surg Date: 2012-11-26 Impact factor: 5.836
Authors: Ralph R E G Geuskens; Jordi Borst; Marit Lucas; A M Merel Boers; Olvert A Berkhemer; Yvo B W E M Roos; Marianne A A van Walderveen; Sjoerd F M Jenniskens; Wim H van Zwam; Diederik W J Dippel; Charles B L M Majoie; Henk A Marquering Journal: PLoS One Date: 2015-11-04 Impact factor: 3.240
Authors: Keith W Muir; Gary A Ford; Claudia-Martina Messow; Ian Ford; Alicia Murray; Andrew Clifton; Martin M Brown; Jeremy Madigan; Rob Lenthall; Fergus Robertson; Anand Dixit; Geoffrey C Cloud; Joanna Wardlaw; Janet Freeman; Philip White Journal: J Neurol Neurosurg Psychiatry Date: 2016-10-18 Impact factor: 10.154