Novel Estimation of Penumbra Zone Based on Infarct Growth Using Machine Learning Techniques in Acute Ischemic Stroke

Figures

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  Figure A1. Comparison of time-to-maximum (Tmax) and relative time to peak (rTTP) lesion volumes. (A) Perfusion lesion volumes measured by Tmax and rTTP. (B) Severe ischemic lesion volumes measured by Tmax and rTTP.

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  Figure 1. Schematics of two approaches for the estimation of final infarct volume and functional outcome. (A) Traditional approach of penumbra zone estimation. (B) Machine learning (ML)-based infarct prediction.

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  Figure 2. Sample external validation cases of SR- and UR-based infarct predictions. (A) A case of large infarct growth in a UR patient (intravenous thrombolysis, modified treatment in cerebral infarction (mTICI) = 0, and 90-day modified Rankin Scale (mRS) = 5). (B) A case of small infarct growth in an SR patient (endovascular therapy, mTICI = 2b, and 90-day mRS = 0). (C) A case of small infarct growth in a UR patient (endovascular therapy, mTICI = 1, and 90-day mRS = 2). (D) A case of large infarct growth in an SR patient (endovascular therapy, mTICI = 2b, and 90-day mRS = 5). Predicted infarct masks, shown in red, are overlaid on pre-treatment DWI images for UR and SR model predictions. All four patients had target mismatch presence but showed various degrees of infarct growth. The yellow numbers indicate the following volumes: (from left to right) baseline DWI lesion volume, baseline PWI lesion volume, UR-predicted infarct volume, SR-predicted infarct volume, and day-7 infarct volume.

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  Figure 3. Correlation plots of (A) the UR-predicted infarct volume and (B) the SR-predicted infarct volume on the external validation UR and SR cohorts, respectively. The manual infarct volume measurement on day-7 DWI served as the reference.

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  Figure 4. Infarct growth distribution in the external validation SR patients (n = 27). (A) Target mismatch classification. (B) SR-predicted infarct growth classification. In (A), the mismatch absence group shows a heterogeneous distribution of actual infarct growth. In (B), the high group (SR-predicted infarct growth ≥ 35 mL) shows a heterogeneous distribution of actual infarct growth, and the low group (SR-predicted infarct growth < 15 mL) shows the narrowest distribution of the actual infarct growth.

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  Figure 5. Distribution of modified Rankin Scale (mRS) scores at day-90 by target mismatch (top) and ML-predicted infarct growth (bottom). In both (A) SR and (B) UR patients, a lower ML-predicted infarct growth was related to a lower mRS score at day 90.