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- W2897438580 abstract "Multiple mechanisms lead to the brain damage ending in vascular dementia. Refining the spatial specificity of each of these vulnerabilities has been difficult because many of these contributing pathologies lead to small, diffuse, and nonoverlapping lesions. Our lab overcame this problem with a new method, Convergence Analysis of Micro-Lesions (CAML), that uses convergence analysis to generate probabilistic maps (Rosen et al., Neuroimage Clinical, 2018). We applied this method to lesions from carotid revascularization (carotid endartorectomy or stenting). These procedures rapidly restore flow to the brain and prevent stroke in patients with severely occluded carotid arteries, but they also lead to small brain lesions easily identified by diffusion weighted magnetic resonance imaging (DWI). The mechanism underlying these lesions is believed to be embolization that travels to the distal vascular trees on the same side of the procedure. Our technique has yielded precise and highly consistent maps across two cohorts, one imaged at 1.5T and one at 3T. Here we present an additional finding. Two groups of patients, underwent diffusion weighted imaging (DWI) and structural MRI (T1) before and after carotid revascularization, one imaged at 1.5 T (N=126) and another imaged at 3 T (N=80). Postoperative MRI was collected within 48 hours after intervention. Apparent Diffusion Coefficient (ADC) maps were calculated based on these DW-images using the GE product software. Lesions were manually defined if they were new increases on DWI and decreases on ADC and analyzed using CAML. Of the 126 patients scanned at 1.5 T, 43 had lesions and for those scanned at 3 T, 46 had lesions. A conjunction analysis comparing the two groups found the posterior insula to be vulnerable to these lesions in both cohorts (Figure)." @default.
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- W2897438580 date "2018-07-01" @default.
- W2897438580 modified "2023-09-26" @default.
- W2897438580 title "P2‐383: CONVERGENCE ANALYSIS OF MICRO‐LESIONS (CAML) FOR DIFFUSE PATHOLOGIES" @default.
- W2897438580 doi "https://doi.org/10.1016/j.jalz.2018.06.1074" @default.
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