Reproducible segmentation of white matter hyperintensities using a new statistical definition

Soheil Damangir*, Eric Westman, Andrew Simmons, Hugo Vrenken, Lars Olof Wahlund, Gabriela Spulber

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Objectives: We present a method based on a proposed statistical definition of white matter hyperintensities (WMH), which can work with any combination of conventional magnetic resonance (MR) sequences without depending on manually delineated samples. Materials and methods: T1-weighted, T2-weighted, FLAIR, and PD sequences acquired at 1.5 Tesla from 119 subjects from the Kings Health Partners-Dementia Case Register (healthy controls, mild cognitive impairment, Alzheimer’s disease) were used. The segmentation was performed using a proposed definition for WMH based on the one-tailed Kolmogorov–Smirnov test. Results: The presented method was verified, given all possible combinations of input sequences, against manual segmentations and a high similarity (Dice 0.85–0.91) was observed. Comparing segmentations with different input sequences to one another also yielded a high similarity (Dice 0.83–0.94) that exceeded intra-rater similarity (Dice 0.75–0.91). We compared the results with those of other available methods and showed that the segmentation based on the proposed definition has better accuracy and reproducibility in the test dataset used. Conclusion: Overall, the presented definition is shown to produce accurate results with higher reproducibility than manual delineation. This approach can be an alternative to other manual or automatic methods not only because of its accuracy, but also due to its good reproducibility.

Original languageEnglish
Pages (from-to)227-237
Number of pages11
JournalMagnetic Resonance Materials in Physics, Biology and Medicine
Volume30
Issue number3
DOIs
Publication statusPublished - 1 Jun 2017

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