Literature DB >> 31026623

Quantitative assessment of the intracranial vasculature in an older adult population using iCafe.

Li Chen1, Jie Sun2, Daniel S Hippe2, Niranjan Balu2, Quan Yuan3, Isabelle Yuan4, Xihai Zhao5, Rui Li5, Le He5, Thomas S Hatsukami6, Jenq-Neng Hwang1, Chun Yuan7.   

Abstract

Comprehensive quantification of intracranial artery features may help us assess and understand variations of blood supply during brain development and aging. We analyzed vasculature features of 163 participants (age 56-85 years, mean of 71) from a community study to investigate if any of the features varied with age. Three-dimensional time-of-flight magnetic resonance angiography images of these participants were processed in IntraCranial artery feature extraction technique (a recently developed technique to obtain quantitative features of arteries) to divide intracranial vasculatures into anatomical segments and generate 8 morphometry and intensity features for each segment. Overall, increase in age was found negatively associated with number of branches and average order of intracranial arteries while positively associated with tortuosity, which remained after adjusting for cardiovascular risk factors. The associations with number of branches and average order were consistently found between 3 main intracranial artery regions, whereas the association with tortuosity appeared to be present only in middle cerebral artery/distal arteries. The combination of time-of-flight magnetic resonance angiography and IntraCranial artery feature extraction technique may provide an effective way to study vascular conditions and changes in the aging brain.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Aging; Feature extraction; Intracranial artery; Vascular biomarker; Vascular change; iCafe

Mesh:

Year:  2019        PMID: 31026623      PMCID: PMC6591051          DOI: 10.1016/j.neurobiolaging.2019.02.027

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


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