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Characteristics of perivascular space dilatation in normal aging
- Title
- Characteristics of perivascular space dilatation in normal aging
- Authors
- Park C.-H.; Shin N.-Y.; Nam Y.; Yoon U.; Ahn K.; Lee S.-K.
- Ewha Authors
- 박창현
- SCOPUS Author ID
- 박창현
- Issue Date
- 2023
- Journal Title
- Human Brain Mapping
- ISSN
- 1065-9471
- Citation
- Human Brain Mapping vol. 44, no. 8, pp. 3232 - 3240
- Keywords
- age estimation; machine learning; normal aging; perivascular space
- Publisher
- John Wiley and Sons Inc
- Indexed
- SCIE; SCOPUS
- Document Type
- Article
- Abstract
- The increased incidence of dilated perivascular spaces (dPVSs) visible on MRI has been observed with advancing age, but the relevance of PVS dilatation to normal aging across the lifespan has yet to be fully clarified. In the current study, we sought to find out the age dependence of dPVSs by exploring changes in different characteristics of PVS dilatation across a wide range of age. For 1220 healthy subjects aged between 18 and 100 years, PVSs were automatically segmented and characteristics of PVS dilatation were assessed in terms of the burden, location, and morphology of PVSs in the white matter (WM) and basal ganglia (BG). A machine learning model using the random forests method was constructed to estimate the subjects’ age by employing the PVS features. The constructed machine learning model was able to estimate the age of the subjects with an error of 9.53 years on average (correlation = 0.875). The importance of the PVS features indicated the primary contribution of the burden of PVSs in the BG and the additional contribution of locational and morphological changes of PVSs, specifically peripheral extension and reduced linearity, in the WM to age estimation. Indeed, adding the PVS location or morphology features to the PVS burden features provided an improvement to the performance of age estimation. The age dependence of dPVSs in terms of such various characteristics of PVS dilatation in healthy subjects could provide a more comprehensive reference for detecting brain disease-related PVS dilatation. © 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
- DOI
- 10.1002/hbm.26277
- Appears in Collections:
- 연구기관 > 뇌융합과학연구원 > Journal papers
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