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Abstract
We compared choroid plexus (ChP) manual segmentation on non-contrast-enhanced (non-CE) sequences and reference standard CE T1- weighted (T1w) sequences in 61 multiple sclerosis patients prospectively included. ChP was separately segmented on T1w, T2-weighted (T2w) fluid-attenuated inversion-recovery (FLAIR), and CE-T1w sequences. Inter-rater variability assessed on 10 subjects showed high reproducibility between sequences measured by intraclass correlation coefficient (T1w 0.93, FLAIR 0.93, CE-T1w 0.99). CE-T1w showed higher signal-to-noise ratio and contrast-to-noise ratio (CE-T1w 23.77 and 18.49, T1w 13.73 and 7.44, FLAIR 13.09 and 10.77, respectively). Manual segmentation of ChP resulted 3.073 ± 0.563 mL (mean ± standard deviation) on T1w, 3.787 ± 0.679 mL on FLAIR, and 2.984 ± 0.506 mL on CE-T1w images, with an error of 28.02 ± 19.02% for FLAIR and 3.52 ± 12.61% for T1w. FLAIR overestimated ChP volume compared to CE-T1w (p < 0.001). The Dice similarity coefficient of CE-T1w versus T1w and FLAIR was 0.67 ± 0.05 and 0.68 ± 0.05, respectively. Spatial error distribution per slice was calculated after nonlinear coregistration to the standard MNI152 space and showed a heterogeneous profile along the ChP especially near the fornix and the hippocampus. Quantitative analyses suggest T1w as a surrogate of CE-T1w to estimate ChP volume. Relevance statement To estimate the ChP volume, CE-T1w can be replaced by non-CE T1w sequences because the error is acceptable, while FLAIR overestimates the ChP volume. This encourages the development of automatic tools for ChP segmentation, also improving the understanding of the role of the ChP volume in multiple sclerosis, promoting longitudinal studies. Key points • CE-T1w sequences are considered the reference standard for ChP manual segmentation. • FLAIR sequences showed a higher CNR than T1w sequences but overestimated the ChP volume. • Non-CE T1w sequences can be a surrogate of CE-T1w sequences for manual segmentation of ChP.
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1 University of Padova, Department of Information Engineering, Padova, Italy (GRID:grid.5608.b) (ISNI:0000 0004 1757 3470)
2 University of Verona, Department of Engineering for Innovation Medicine, Verona, Italy (GRID:grid.5611.3) (ISNI:0000 0004 1763 1124)
3 University of Verona, Department of Diagnostic and Public Health, Verona, Italy (GRID:grid.5611.3) (ISNI:0000 0004 1763 1124)
4 University of Verona, Department of Neurosciences, Biomedicine and Movement Sciences, Verona, Italy (GRID:grid.5611.3) (ISNI:0000 0004 1763 1124)
5 University Hospital of Padova, Neuroradiology Unit, Padova, Italy (GRID:grid.144189.1) (ISNI:0000 0004 1756 8209)
6 University of Padova, Department of Information Engineering, Padova, Italy (GRID:grid.5608.b) (ISNI:0000 0004 1757 3470); University of Padova, Padova Neuroscience Center, Padova, Italy (GRID:grid.5608.b) (ISNI:0000 0004 1757 3470)