학술논문

Tract-based white matter hyperintensity patterns in patients with systemic lupus erythematosus using an unsupervised machine learning approach
Document Type
Source
Scientific Reports MultiPark: Multidisciplinary research focused on Parkinson´s disease EpiHealth: Epidemiology for Health eSSENCE: The e-Science Collaboration. 12:1-12
Subject
Naturvetenskap
Fysik
Annan fysik
Natural Sciences
Physical Sciences
Other Physics Topics
Medicin och hälsovetenskap
Klinisk medicin
Radiologi och bildbehandling
Medical and Health Sciences
Clinical Medicine
Radiology
Nuclear Medicine and Medical Imaging
Language
English
ISSN
2045-2322
Abstract
Currently, little is known about the spatial distribution of white matter hyperintensities (WMH) in the brain of patients with Systemic Lupus erythematosus (SLE). Previous lesion markers, such as number and volume, ignore the strategic location of WMH. The goal of this work was to develop a fully-automated method to identify predominant patterns of WMH across WM tracts based on cluster analysis. A total of 221 SLE patients with and without neuropsychiatric symptoms from two different sites were included in this study. WMH segmentations and lesion locations were acquired automatically. Cluster analysis was performed on the WMH distribution in 20 WM tracts. Our pipeline identified five distinct clusters with predominant involvement of the forceps major, forceps minor, as well as right and left anterior thalamic radiations and the right inferior fronto-occipital fasciculus. The patterns of the affected WM tracts were consistent over the SLE subtypes and sites. Our approach revealed distinct and robust tract-based WMH patterns within SLE patients. This method could provide a basis, to link the location of WMH with clinical symptoms. Furthermore, it could be used for other diseases characterized by presence of WMH to investigate both the clinical relevance of WMH and underlying pathomechanism in the brain.