Longitudinal segmentation of age-related white matter hyperintensities

•A longitudinal WMH segmentation algorithm is proposed.•Time points segmentation are constrained by an average data model.•It is shown to be unbiased to time point ordering.•A longitudinal lesion simulator is developed for validation.•The longitudinal solution is more robust compared to cross-sectio...

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Bibliographic Details
Published in:Medical image analysis 2017-05, Vol.38, p.50-64
Main Authors: Sudre, Carole H., Cardoso, M. Jorge, Ourselin, Sebastien
Format: Article
Language:English
Subjects:
Aged
Aging - pathology
Algorithms
Alzheimer Disease - diagnostic imaging
Alzheimer Disease - genetics
Apolipoproteins E - genetics
Bias
Computer simulation
Cross-Sectional Studies
Female
Humans
Longitudinal
Longitudinal Studies
Magnetic Resonance Imaging
Male
Medical imaging
Nervous system
NMR
Nuclear magnetic resonance
Reproducibility of Results
Segmentation
Substantia alba
White Matter - diagnostic imaging
White Matter - pathology
White matter hyperintensities
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Summary:•A longitudinal WMH segmentation algorithm is proposed.•Time points segmentation are constrained by an average data model.•It is shown to be unbiased to time point ordering.•A longitudinal lesion simulator is developed for validation.•The longitudinal solution is more robust compared to cross-sectional methods. [Display omitted] Although white matter hyperintensities evolve in the course of ageing, few solutions exist to consider the lesion segmentation problem longitudinally. Based on an existing automatic lesion segmentation algorithm, a longitudinal extension is proposed. For evaluation purposes, a longitudinal lesion simulator is created allowing for the comparison between the longitudinal and the cross-sectional version in various situations of lesion load progression. Finally, applied to clinical data, the proposed framework demonstrates an increased robustness compared to available cross-sectional methods and findings are aligned with previously reported clinical patterns.
ISSN:1361-8415
1361-8423
DOI:10.1016/j.media.2017.02.007