Rationale and Objectives
Periventricular and deep white matter hyperintensities (WMHs) in the elderly have
been reported with distinctive roles in the progression of cognitive decline and dementia.
However, the definition of these two subregions of WMHs is arbitrary and varies across
studies. Here, we evaluate three partition methods for WMH subregions, including two
widely used conventional methods (CV & D10) and one novel method based on bilateral
distance (BD).
Materials and Methods
The three partition methods were assessed on the MRI scans of 60 subjects, with 20
normal control, 20 mild cognitive impairment, and 20 Alzheimer's disease (AD). Resulting
WMH subregional volumes were (1) compared among different partition methods and subject
groups, and (2) tested for clinical associations with cognition and dementia. Inter-rater,
intrarater, and interscan reproducibility of WMHs volumes were tested on 12 randomly
selected subjects from the 60.
Results
For all three partition methods, increased periventricular WMHs were found for AD
subjects over normal control. For BD and D10, but not CV method, increased Periventricular
WMHs were found for AD subjects over mild cognitive impairment. Significant correlations
were found between PVWMHs and Mini-Mental State Examination, Montreal Cognitive Assessment,
and Clinical Dementia Rating scores. Furthermore, PVWMHs under BD partition showed
higher correlations than D10 and CV. High intrarater and interscan reproducibility
(ICCA = 0.998 and 0.992 correspondingly) and substantial inter-rater reproducibility
(ICCA = 0.886) were detected.
Conclusion
Different WMH partition methods showed comparable diagnostic abilities. The proposed
BD method showed advantages in quantifying PVWMH over conventional CV and D10 methods,
in terms of higher consistency, larger contrast, and higher diagnosis accuracy. Furthermore,
the PVWMH under BD partition showed stronger clinical correlations than conventional
methods.
Keywords
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Article info
Publication history
Published online: October 27, 2020
Accepted:
July 27,
2020
Received in revised form:
July 26,
2020
Received:
May 25,
2020
Footnotes
Declarations of interest: None.
Identification
Copyright
© 2020 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
