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. 2021 Nov 4;11(11):2038.
doi: 10.3390/diagnostics11112038.

Impact of Pretreatment Ischemic Location on Functional Outcome after Thrombectomy

Affiliations

Impact of Pretreatment Ischemic Location on Functional Outcome after Thrombectomy

Yu Xie et al. Diagnostics (Basel). .

Abstract

Pretreatment ischemic location may be an important determinant for functional outcome prediction in acute ischemic stroke. In total, 143 anterior circulation ischemic stroke patients in the THRACE study were included. Ischemic lesions were semi-automatically segmented on pretreatment diffusion-weighted imaging and registered on brain atlases. The percentage of ischemic tissue in each atlas-segmented region was calculated. Statistical models with logistic regression and support vector machine were built to analyze the predictors of functional outcome. The investigated parameters included: age, baseline National Institutes of Health Stroke Scale score, and lesional volume (three-parameter model), together with the ischemic percentage in each atlas-segmented region (four-parameter model). The support vector machine with radial basis functions outperformed logistic regression in prediction accuracy. The support vector machine three-parameter model demonstrated an area under the curve of 0.77, while the four-parameter model achieved a higher area under the curve (0.82). Regions with marked impacts on outcome prediction were the uncinate fasciculus, postcentral gyrus, putamen, middle occipital gyrus, supramarginal gyrus, and posterior corona radiata in the left hemisphere; and the uncinate fasciculus, paracentral lobule, temporal pole, hippocampus, inferior occipital gyrus, middle temporal gyrus, pallidum, and anterior limb of the internal capsule in the right hemisphere. In conclusion, pretreatment ischemic location provided significant prognostic information for functional outcome in ischemic stroke.

Keywords: ischemia; outcome; stroke; thrombectomy.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Workflow of lesion location determination: (1) Ischemic lesions were segmented semi-automatically. (2) The generated lesion masks were then normalized to standard Montreal Neurological Institute space using SPM12. (3) The regional ischemic location was determined according to Automated Anatomical Labeling Atlas and the Johns Hopkins University White Matter Labels (1 mm) Atlas. Abbreviations: MNI = Montreal Neurological Institute; AAL = Automated Anatomical Labeling Atlas; JHU-WM = Johns Hopkins University White Matter Labels (1 mm) Atlas.
Figure 2
Figure 2
Patient selection flowchart. Abbreviations: IVT = intravenous thrombolysis; IVTMT = intravenous thrombolysis plus mechanical thrombectomy; DWI = diffusion-weighted imaging; mRS = modified Rankin Scale.
Figure 3
Figure 3
F1 accessed on 30 October 2019 score obtained on the average training (red dotted line) and validation (blue line) sets during cross-validation performed by SVM after adding different features. The model reached the highest performance on the validation set when using 16 features (green dotted line). Abbreviation: SVM = support vector machine.

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