Article

Reliability of two techniques for assessing cerebral iron deposits with structural magnetic resonance imaging

Citation

Valdés Hernández MC, Jeong TH, Murray C, Bastin ME, Chappell FM, Deary IJ & Wardlaw JM (2011) Reliability of two techniques for assessing cerebral iron deposits with structural magnetic resonance imaging. Journal of Magnetic Resonance Imaging, 33 (1), pp. 54-61. https://doi.org/10.1002/jmri.22361

Abstract
Purpose To test the reliability of two computational methods for segmenting cerebral iron deposits (IDs) in the aging brain, given that its measurement in magnetic resonance imaging (MRI) is challenging due to the similar effect produced by other minerals, especially calcium, on T2*-weighted sequences. Materials and Methods T1-, T2*-weighted, and fluid-attenuated inversion recovery (FLAIR) MR brain images obtained at 1.5T from 70 subjects in their early 70s who displayed a wide range of brain IDs were analyzed. The first segmentation method used a multispectral approach based on the fusion of two or more structural sequences registered and mapped in the red/green color space followed by Minimum Variance Quantization. The second method employed a combined thresholding, size and shape analysis using T2*-weighted images augmented with visual information from T1-weighted data. Results Both segmentation techniques had high intra- and interobserver agreement (95% confidence interval [CI] = +/- 57 voxels in a range from 0 to 1800), which decreased in subjects with significant microbleeds and/or IDs. However, the thresholding method was more observer dependent in identifying microbleeds and IDs boundaries than the multispectral approach. Conclusion Both techniques proved to be in agreement and have good intra- and interobserver reliability. However, they have limitations, specifically with regard to automation and observer independence, so further work is required to develop fully user-independent methods of identifying cerebral IDs.

Keywords
iron deposits; MRI; thresholding; multispectral segmentation; reliability;

Journal
Journal of Magnetic Resonance Imaging: Volume 33, Issue 1

StatusPublished
FundersBiotechnology and Biological Sciences Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council and Medical Research Council
Publication date31/01/2011
Publication date online22/12/2010
Date accepted by journal11/08/2010
URLhttp://hdl.handle.net/1893/27651
PublisherWiley
ISSN1053-1807