Abstract
(1) Background: To test the accuracy of a fully automated stroke tissue estimation algorithm (FASTER) to predict final lesion volumes in an independent dataset in patients with acute stroke; (2) Methods: Tissue-at-risk prediction was performed in 31 stroke patients presenting with a proximal middle cerebral artery occlusion. FDA-cleared perfusion software using the AHA recommendation for the Tmax threshold delay was tested against a prediction algorithm trained on an independent perfusion software using artificial intelligence (FASTER). Following our endovascular strategy to consequently achieve TICI 3 outcome, we compared patients with complete reperfusion (TICI 3) vs. no reperfusion (TICI 0) after mechanical thrombectomy. Final infarct volume was determined on a routine follow-up MRI or CT at 90 days after the stroke; (3) Results: Compared to the reference standard (infarct volume after 90 days), the decision forest algorithm overestimated the final infarct volume in patients without reperfusion. Underestimation was observed if patients were completely reperfused. In cases where the FDA-cleared segmentation was not interpretable due to improper definitions of the arterial input function, the decision forest provided reliable results; (4) Conclusions: The prediction accuracy of automated tissue estimation depends on (i) success of reperfusion, (ii) infarct size, and (iii) software-related factors introduced by the training sample. A principal advantage of machine learning algorithms is their improved robustness to artifacts in comparison to solely threshold-based model-dependent software. Validation on independent datasets remains a crucial condition for clinical implementations of decision support systems in stroke imaging.
Highlights
Defining infarction core and penumbra is relevant to determine the management plan of patients with acute ischemic stroke
This is reflected in the current guidelines for stroke management by the American Stroke Association, as selected patients may be eligible for invasive stroke therapy in an extended time window (6–24 h from last seen normal)
Patients were included if imaging data were complete, including the raw perfusion data saved in the Picture archiving and communication system (PACS), and were not used to train the Patients were stratified according to thrombolysis in cerebral infarction (TICI) score [28]: (1) TICI score 3 vs. (2) TICI score 0
Summary
Defining infarction core and penumbra is relevant to determine the management plan of patients with acute ischemic stroke. Multiple factors influence the evolution and final extent of ischemic lesions, such as the location of the thrombus [1,2], preexisting vascular pathology [3], and the state of collateral circulation [4,5], as well as other patientrelated factors [6,7], which necessitate moving from a universal time window towards an individualized approach in management This is reflected in the current guidelines for stroke management by the American Stroke Association, as selected patients may be eligible for invasive stroke therapy in an extended time window (6–24 h from last seen normal). The dependency of the deconvolution method on the arterial input function (AIF) renders Tmax susceptible to even minor changes in the shape of AIF, making it one of the limitations of this perfusion parameter [21]
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