Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2025
Multivariate Pattern Analysis of Perfusion and Oxygenation Impairment in Asymptomatic Carotid Artery Stenosis.
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Kufer Jan, Preibisch Christine, Göttler Jens, Schmitzer Lena, Hoffmann Gabriel, Kallmayer Michael, Zimmer Claus, Hyder Fahmeed, Kaczmarz Stephan
Аннотация
BACKGROUND AND PURPOSE: Hemodynamic impairment may contribute to stroke risk and cognitive decline in asymptomatic internal carotid artery stenosis (ICAS). Therefore, multimodal MRI-based quantification of hemodynamic impairment could inform improved treatment decisions. While gross interhemispheric hemodynamic imbalances have been reported in ICAS, identifying more spatially resolved patterns of disease-related alterations may be promising to harness the full potential of hemodynamic MRI.
METHODS: In this feasibility study, we investigated the spatial topography of ICAS-related impairments by applying scaled subprofile model principal component analysis (SSM-PCA) to cerebral blood flow (CBF), relative oxygen extraction fraction (rOEF), and oxygen extraction capacity (OEFmax) data of 21 unilateral ICAS patients and 25 healthy controls (HC).
RESULTS: We found spatially extended, partly overlapping disease-related patterns for CBF and OEFmax, but not rOEF. CBF (area under the curve [AUC] = 0.95) but not OEFmax (AUC = 0.72) SSM-PCA scores distinguished ICAS patients and HC better than interhemispheric lateralizations (AUC = 0.75/0.73). SSM-PCA scores were only partly explained by interhemispheric lateralization (R2 = -0.27/0.38), indicating complementary information. Critically, ICAS patients with higher OEFmax SSM-PCA scores (z ≥ 1) demonstrated higher stenotic degrees and lower cognitive performance (p < 0.05) without differing in interhemispheric lateralization (p > 0.05).
CONCLUSIONS: We demonstrated the feasibility of SSM-PCA in ICAS and obtained novel insights into complex hemodynamic impairment patterns and their association with cognitive function.
METHODS: In this feasibility study, we investigated the spatial topography of ICAS-related impairments by applying scaled subprofile model principal component analysis (SSM-PCA) to cerebral blood flow (CBF), relative oxygen extraction fraction (rOEF), and oxygen extraction capacity (OEFmax) data of 21 unilateral ICAS patients and 25 healthy controls (HC).
RESULTS: We found spatially extended, partly overlapping disease-related patterns for CBF and OEFmax, but not rOEF. CBF (area under the curve [AUC] = 0.95) but not OEFmax (AUC = 0.72) SSM-PCA scores distinguished ICAS patients and HC better than interhemispheric lateralizations (AUC = 0.75/0.73). SSM-PCA scores were only partly explained by interhemispheric lateralization (R2 = -0.27/0.38), indicating complementary information. Critically, ICAS patients with higher OEFmax SSM-PCA scores (z ≥ 1) demonstrated higher stenotic degrees and lower cognitive performance (p < 0.05) without differing in interhemispheric lateralization (p > 0.05).
CONCLUSIONS: We demonstrated the feasibility of SSM-PCA in ICAS and obtained novel insights into complex hemodynamic impairment patterns and their association with cognitive function.