Choroid plexus volume in multiple sclerosis can be estimated on structural MRI avoiding contrast injection.

Choroid plexus Gadolinium-based contrast media Image segmentation Magnetic resonance imaging Multiple sclerosis

Journal

European radiology experimental
ISSN: 2509-9280
Titre abrégé: Eur Radiol Exp
Pays: England
ID NLM: 101721752

Informations de publication

Date de publication:
27 Feb 2024
Historique:
received: 25 09 2023
accepted: 11 12 2023
medline: 27 2 2024
pubmed: 27 2 2024
entrez: 27 2 2024
Statut: epublish

Résumé

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.

Identifiants

pubmed: 38409562
doi: 10.1186/s41747-024-00421-9
pii: 10.1186/s41747-024-00421-9
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

33

Informations de copyright

© 2024. The Author(s).

Références

Damkier HH, Brown PD, Praetorius J (2013) Cerebrospinal fluid secretion by the choroid plexus. Physiol Rev 93:1847–1892. https://doi.org/10.1152/physrev.00004.2013
doi: 10.1152/physrev.00004.2013 pubmed: 24137023
Balusu S, Brkic M, Libert C, Vandenbroucke RE (2016) The choroid plexus-cerebrospinal fluid interface in Alzheimer’s disease: more than just a barrier. Neural Regen Res 11:534–537. https://doi.org/10.4103/1673-5374.180372
doi: 10.4103/1673-5374.180372 pubmed: 27212900 pmcid: 4870896
Spector R, Keep RF, Robert Snodgrass S, Smith QR, Johanson CE (2015) A balanced view of choroid plexus structure and function: focus on adult humans. Exp Neurol 267:78–86. https://doi.org/10.1016/j.expneurol.2015.02.032
doi: 10.1016/j.expneurol.2015.02.032 pubmed: 25747036
Jessen NA, Munk ASF, Lundgaard I, Nedergaard M (2015) The glymphatic system: a beginner’s guide. Neurochem Res 40:2583–2599. https://doi.org/10.1007/s11064-015-1581-6
doi: 10.1007/s11064-015-1581-6 pubmed: 25947369 pmcid: 4636982
Monaco S, Nicholas R, Reynolds R, Magliozzi R (2020) Intrathecal inflammation in progressive multiple sclerosis. Int J Mol Sci 21:8217. https://doi.org/10.3390/ijms21218217
doi: 10.3390/ijms21218217 pubmed: 33153042 pmcid: 7663229
Engelhardt B, Wolburg-Buchholz K, Wolburg H (2001) Involvement of the choroid plexus in central nervous system inflammation. Microsc Res Tech 52:112–129. https://doi.org/10.1002/1097-0029(20010101)52:1<112::AID-JEMT13>3.0.CO;2-5
doi: 10.1002/1097-0029(20010101)52:1<112::AID-JEMT13>3.0.CO;2-5 pubmed: 11135454
Ricigliano VAG, Morena E, Colombi A et al (2021) Choroid plexus enlargement in inflammatory multiple sclerosis: 3.0-T MRI and translocator protein PET evaluation. Radiology 301:166–177. https://doi.org/10.1148/radiol.2021204426
doi: 10.1148/radiol.2021204426 pubmed: 34254858
Vercellino M, Votta B, Condello C et al (2008) Involvement of the choroid plexus in multiple sclerosis autoimmune inflammation: a neuropathological study. J Neuroimmunol 199:133–141. https://doi.org/10.1016/j.jneuroim.2008.04.035
doi: 10.1016/j.jneuroim.2008.04.035 pubmed: 18539342
Lassmann H (2018) Pathogenic mechanisms associated with different clinical courses of multiple sclerosis. Front Immunol 9:3116. https://doi.org/10.3389/fimmu.2018.03116
doi: 10.3389/fimmu.2018.03116 pubmed: 30687321
Tadayon E, Moret B, Sprugnoli G et al (2020) Improving choroid plexus segmentation in the healthy and diseased brain: relevance for tau-PET imaging in dementia. J Alzheimers Dis 74:1057–1068. https://doi.org/10.3233/JAD-190706
doi: 10.3233/JAD-190706 pubmed: 32144979 pmcid: 9094634
Tadayon E, Pascual-Leone A, Press D, Santarnecchi E, Alzheimer’s Disease Neuroimaging Initiative (2020) Choroid plexus volume is associated with levels of CSF proteins: relevance for Alzheimer’s and Parkinson’s disease. Neurobiol Aging 89:108–117. https://doi.org/10.1016/j.neurobiolaging.2020.01.005
doi: 10.1016/j.neurobiolaging.2020.01.005 pubmed: 32107064 pmcid: 9094632
Althubaity N, Schubert J, Martins D et al (2022) Choroid plexus enlargement is associated with neuroinflammation and reduction of blood brain barrier permeability in depression. NeuroImage Clin 33:102926. https://doi.org/10.1016/j.nicl.2021.102926
doi: 10.1016/j.nicl.2021.102926 pubmed: 34972034
Lizano P, Lutz O, Ling G et al (2019) Association of choroid plexus enlargement with cognitive, inflammatory, and structural phenotypes across the psychosis spectrum. Am J Psychiatry 176:564–572. https://doi.org/10.1176/appi.ajp.2019.18070825
doi: 10.1176/appi.ajp.2019.18070825 pubmed: 31164007 pmcid: 6676480
Zhou YF, Huang JC, Zhang P et al (2020) Choroid plexus enlargement and allostatic load in schizophrenia. Schizophr Bull 46:722–731. https://doi.org/10.1093/schbul/sbz100
doi: 10.1093/schbul/sbz100 pubmed: 31603232
Maekawa T, Hori M, Murata K et al (2019) Choroid plexus cysts analyzed using diffusion-weighted imaging with short diffusion-time. Magn Reson Imaging 57:323–327. https://doi.org/10.1016/j.mri.2018.12.010
doi: 10.1016/j.mri.2018.12.010 pubmed: 30605722
Zhao L, Taso M, Dai W, Press DZ, Alsop DC (2020) Non-invasive measurement of choroid plexus apparent blood flow with arterial spin labeling. Fluids Barriers CNS 17:58. https://doi.org/10.1186/s12987-020-00218-z
doi: 10.1186/s12987-020-00218-z pubmed: 32962708 pmcid: 7510126
Schubert JJ, Veronese M, Marchitelli L et al (2019) Dynamic 11C-PiB PET shows cerebrospinal fluid flow alterations in Alzheimer disease and multiple sclerosis. J Nucl Med 60:1452–1460. https://doi.org/10.2967/jnumed.118.223834
doi: 10.2967/jnumed.118.223834 pubmed: 30850505 pmcid: 6785797
Fleischer V, Gonzalez-Escamilla G, Ciolac D et al (2021) Translational value of choroid plexus imaging for tracking neuroinflammation in mice and humans. Proc Natl Acad Sci U S A 118:e2025000118. https://doi.org/10.1073/pnas.2025000118
doi: 10.1073/pnas.2025000118 pubmed: 34479997 pmcid: 8433504
Manouchehri N, Stüve O (2021) Choroid plexus volumetrics and brain inflammation in multiple sclerosis. Proc Natl Acad Sci U S A 118:e2115221118. https://doi.org/10.1073/pnas.2115221118
doi: 10.1073/pnas.2115221118 pubmed: 34583997 pmcid: 8501877
Hubert V, Chauveau F, Dumot C et al (2019) Clinical imaging of choroid plexus in health and in brain disorders: a mini-review. Front Mol Neurosci 12:34. https://doi.org/10.3389/fnmol.2019.00034
doi: 10.3389/fnmol.2019.00034 pubmed: 30809124 pmcid: 6379459
Yazdan-Panah A, Schmidt-Mengin M, Ricigliano VAG et al (2023) Automatic segmentation of the choroid plexuses: Method and validation in controls and patients with multiple sclerosis. Neuroimage Clin 38:103368. https://doi.org/10.1016/j.nicl.2023.103368
doi: 10.1016/j.nicl.2023.103368 pubmed: 36913908 pmcid: 10011049
Wattjes MP, Ciccarelli O, Reich DS et al (2021) 2021 MAGNIMS–CMSC–NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol 20:653–670. https://doi.org/10.1016/S1474-4422(21)00095-8
doi: 10.1016/S1474-4422(21)00095-8 pubmed: 34139157
Senay O, Seethaler M, Makris N et al (2023) A preliminary choroid plexus volumetric study in individuals with psychosis. Hum Brain Mapp 44:2465–2478. https://doi.org/10.1002/hbm.26224
doi: 10.1002/hbm.26224 pubmed: 36744628 pmcid: 10028672
Yushkevich PA, Piven J, Hazlett HC et al (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 31:1116–1128. https://doi.org/10.1016/j.neuroimage.2006.01.015
doi: 10.1016/j.neuroimage.2006.01.015 pubmed: 16545965
Fischl B (2012) FreeSurfer. Neuroimage 62:774–781. https://doi.org/10.1016/j.neuroimage.2012.01.021
doi: 10.1016/j.neuroimage.2012.01.021 pubmed: 22248573
Avants BB, Tustison NJ, Song G, Cook PA, Klein A, Gee JC (2011) A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage 54:2033–2044. https://doi.org/10.1016/j.neuroimage.2010.09.025
doi: 10.1016/j.neuroimage.2010.09.025 pubmed: 20851191
Fonov V, Evans A, McKinstry R, Almli CR, Collins DL (2009) Unbiased nonlinear average age-appropriate brain templates from birth to adulthood. Neuroimage 47:S102. https://doi.org/10.1016/S1053-8119(09)70884-5
doi: 10.1016/S1053-8119(09)70884-5
Gulani V, Calamante F, Shellock FG, Kanal E, Reeder SB, International Society for Magnetic Resonance in Medicine (2017) Gadolinium deposition in the brain: summary of evidence and recommendations. Lancet Neurol 16:564–570. https://doi.org/10.1016/S1474-4422(17)30158-8
doi: 10.1016/S1474-4422(17)30158-8 pubmed: 28653648
Schieda N, van der Pol CB, Walker D et al (2020) Adverse events to the gadolinium-based contrast agent gadoxetic acid: systematic review and meta-analysis. Radiology 297:565–572. https://doi.org/10.1148/radiol.2020200073
doi: 10.1148/radiol.2020200073 pubmed: 32452732
Rudie JD, Mattay RR, Schindler M et al (2019) An initiative to reduce unnecessary gadolinium-based contrast in multiple sclerosis patients. J Am Coll Radiol 16:1158–1164. https://doi.org/10.1016/j.jacr.2019.04.005
doi: 10.1016/j.jacr.2019.04.005 pubmed: 31092348 pmcid: 6732018

Auteurs

Valentina Visani (V)

Department of Information Engineering, University of Padova, Padova, Italy.

Francesca B Pizzini (FB)

Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy.

Valerio Natale (V)

Department of Diagnostic and Public Health, University of Verona, Verona, Italy.

Agnese Tamanti (A)

Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.

Mariagiulia Anglani (M)

Neuroradiology Unit, University Hospital of Padova, Padova, Italy.

Alessandra Bertoldo (A)

Department of Information Engineering, University of Padova, Padova, Italy.
Padova Neuroscience Center, University of Padova, Padova, Italy.

Massimiliano Calabrese (M)

Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.

Marco Castellaro (M)

Department of Information Engineering, University of Padova, Padova, Italy. marco.castellaro@unipd.it.

Classifications MeSH