Imaging selection in ischemic stroke: feasibility of automated CT-perfusion analysis

Background: Advanced imaging may refine patient selection for ischemic stroke treatment but delays to acquire and process the imaging have limited implementation.

Aims: We examined the feasibility of imaging selection in clinical practice using fully automated software in the EXTEND trial program.

Methods: CTP and perfusion-diffusion MRI data were processed using fully-automated software to generate a yes/no 'mismatch' classification that determined eligibility for trial therapies. The technical failure/mismatch classification error rate and time to image and treat with CT vs. MR-based selection were examined.

Results: In a consecutive series of 776 patients from five sites over six-months the technical failure rate of CTP acquisition/processing (uninterpretable maps) was 3·4% (26/776, 95%CI 2·2-4·9%). Mismatch classification was overruled by expert review in an additional 9·0% (70/776, 95%CI 7·1-11·3%) due to artifactual 'perfusion lesion'. In 154 consecutive patients at one site, median additional time to acquire CTP after non-contrast CT was 6·5 min. Subsequent RAPID processing time varied from 3-10 min across 20 trial centers (median 5 min 20 s). In the EXTEND trial, door-to-needle times in patients randomized on the basis of CTP (n = 47) were median 78 min shorter than MRI-selected (n = 16) patients (P < 0·001).

Conclusions: Automated CTP-based mismatch selection is rapid, robust in clinical practice, and associated with faster treatment decisions than MRI. This technological advance has the potential to improve the standardization and reproducibility of interpretation of advanced imaging and extend use to practice settings beyond highly specialized academic centers.