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Multimodal magnetic resonance imaging to identify stroke onset within 6 h in patients with large vessel occlusions

Wouters, Anke; Dupont, Patrick; Christensen, Soren; Norrving, Bo LU ; Laage, Rico; Thomalla, Götz; Kemp, Stephanie; Lansberg, Maarten; Thijs, Vincent and Albers, Gregory W., et al. (2018) In European Stroke Journal 3(2). p.185-192
Abstract

Introduction: Mechanical thrombectomy within 6 h after stroke onset improves the outcome in patients with large vessel occlusions. The aim of our study was to establish a model based on diffusion weighted and perfusion weighted imaging to provide an accurate prediction for the 6 h time-window in patients with unknown time of stroke onset. Patients and methods: A predictive model was designed based on data from the DEFUSE 2 study and validated in a subgroup of patients with large vessel occlusions from the AXIS 2 trial. Results: We constructed the model in 91 patients from DEFUSE 2. The following parameters were independently associated with <6 h time-window and included in the model: interquartile range and median relative diffusion... (More)

Introduction: Mechanical thrombectomy within 6 h after stroke onset improves the outcome in patients with large vessel occlusions. The aim of our study was to establish a model based on diffusion weighted and perfusion weighted imaging to provide an accurate prediction for the 6 h time-window in patients with unknown time of stroke onset. Patients and methods: A predictive model was designed based on data from the DEFUSE 2 study and validated in a subgroup of patients with large vessel occlusions from the AXIS 2 trial. Results: We constructed the model in 91 patients from DEFUSE 2. The following parameters were independently associated with <6 h time-window and included in the model: interquartile range and median relative diffusion weighted imaging, hypoperfusion intensity ratio, core volume and the interaction between median relative diffusion weighted imaging and hypoperfusion intensity ratio as predictors of the 6 h time-window. The area under the curve was 0.80 with a positive predictive value of 0.90 (95%CI 0.79–0.96). In the validation cohort (N = 90), the area under the curve was 0.73 (P for difference = 0.4) with a positive predictive value of 0.85 (95%CI 0.69–0.95). Discussion: After validation in a larger independent dataset the model can be considered to select patients for endovascular treatment in whom stroke onset is unknown. Conclusion: In patients with large vessel occlusion and unknown time of stroke onset an automated multivariate imaging model is able to select patients who are likely within the 6 h time-window.

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publication status
published
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keywords
Acute stroke therapy, cerebral infarction, ischaemic stroke, magnetic resonance imaging, stroke, thrombectomy, treatment, unknown onset
in
European Stroke Journal
volume
3
issue
2
pages
8 pages
publisher
SAGE Publications Inc.
external identifiers
  • scopus:85060504705
ISSN
2396-9873
DOI
10.1177/2396987317753486
language
English
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yes
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8b48dcd0-19df-4d8b-a649-bb5b48c88781
date added to LUP
2019-02-08 12:45:57
date last changed
2019-02-27 05:12:57
@article{8b48dcd0-19df-4d8b-a649-bb5b48c88781,
  abstract     = {<p>Introduction: Mechanical thrombectomy within 6 h after stroke onset improves the outcome in patients with large vessel occlusions. The aim of our study was to establish a model based on diffusion weighted and perfusion weighted imaging to provide an accurate prediction for the 6 h time-window in patients with unknown time of stroke onset. Patients and methods: A predictive model was designed based on data from the DEFUSE 2 study and validated in a subgroup of patients with large vessel occlusions from the AXIS 2 trial. Results: We constructed the model in 91 patients from DEFUSE 2. The following parameters were independently associated with &lt;6 h time-window and included in the model: interquartile range and median relative diffusion weighted imaging, hypoperfusion intensity ratio, core volume and the interaction between median relative diffusion weighted imaging and hypoperfusion intensity ratio as predictors of the 6 h time-window. The area under the curve was 0.80 with a positive predictive value of 0.90 (95%CI 0.79–0.96). In the validation cohort (N = 90), the area under the curve was 0.73 (P for difference = 0.4) with a positive predictive value of 0.85 (95%CI 0.69–0.95). Discussion: After validation in a larger independent dataset the model can be considered to select patients for endovascular treatment in whom stroke onset is unknown. Conclusion: In patients with large vessel occlusion and unknown time of stroke onset an automated multivariate imaging model is able to select patients who are likely within the 6 h time-window.</p>},
  author       = {Wouters, Anke and Dupont, Patrick and Christensen, Soren and Norrving, Bo and Laage, Rico and Thomalla, Götz and Kemp, Stephanie and Lansberg, Maarten and Thijs, Vincent and Albers, Gregory W. and Lemmens, Robin},
  issn         = {2396-9873},
  keyword      = {Acute stroke therapy,cerebral infarction,ischaemic stroke,magnetic resonance imaging,stroke,thrombectomy,treatment,unknown onset},
  language     = {eng},
  number       = {2},
  pages        = {185--192},
  publisher    = {SAGE Publications Inc.},
  series       = {European Stroke Journal},
  title        = {Multimodal magnetic resonance imaging to identify stroke onset within 6 h in patients with large vessel occlusions},
  url          = {http://dx.doi.org/10.1177/2396987317753486},
  volume       = {3},
  year         = {2018},
}