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Lesion filling effect in regional brain volume estimations: a study in multiple sclerosis patients with low lesion load

  • Diagnostic Neuroradiology
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Abstract

Introduction

Regional brain volume estimation in multiple sclerosis (MS) patients is prone to error due to white matter lesions being erroneously segmented as grey matter. The Lesion Segmentation Toolbox (LST) is an automatic tool that estimates a lesion mask based on 3D T2-FLAIR images and then uses this mask to fill the structural MRI image. The goal of this study was (1) to test the LST for estimating white matter lesion volume in a cohort of MS patients using 2D T2-FLAIR images, and (2) to evaluate the performance of the optimized LST on image segmentation and the impact on the calculated grey matter fraction (GMF).

Methods

The study included 110 patients with a clinically isolated syndrome and 42 with a relapsing-remitting MS scanned on a 3.0-T MRI system. In a subset of consecutively selected patients, the lesion mask was semi-manually delineated over T2-FLAIR images. After establishing the optimized LST parameters, the corresponding regional fractions were calculated for the original, filled, and masked images.

Results

A high agreement (intraclass correlation coefficient (ICC) = 0.955) was found between the (optimized) LST and the semi-manual lesion volume estimations. The GMF was significantly smaller when lesions were masked (mean difference −0.603, p < 0.001) or when the LST filling technique was used (mean difference −0.598, p < 0.001), compared to the GMF obtained from the original image.

Conclusion

LST lesion volume calculation seems reliable. GMFs are significantly reduced when a method to correct the contribution of MS lesions is used, and it may have an impact in assessing GMF differences between clinical cohorts.

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Abbreviations

ANOVA:

One-way analysis of variance

CIS:

Clinically isolated syndromes

DC:

Dice coefficient

EDSS:

Expanded disability status scale

GM:

Grey matter

GMF:

Grey matter fraction

GT:

Ground truth

ICC:

Intraclass correlation coefficient

LST:

Lesion Segmentation Toolbox

LV:

Lesion volume

MNI:

Montreal Neurological Institute

MRI:

Magnetic resonance imaging

MS:

Multiple sclerosis

RRMS:

Relapsing-remitting multiple sclerosis

SPM:

Statistical Parametric Mapping

VBM:

Voxel-based morphometry

WM:

White matter

WMF:

White matter fraction

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Acknowledgments

We thank the Red Española de Esclerosis Múltiple (REEM) (RD07/0060; RD12/0032), which is sponsored by the Fondo de Investigación Sanitaria (FIS), Instituto de Salud Carlos III, Ministry of Economy and Competitiveness in Spain, and the Ajuts per donar Suport als Grups de Recerca de Catalunya (2009 SGR 0793), which is sponsored by the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) of the Catalonian regional government (Generalitat de Catalunya) in Spain.

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Authors and Affiliations

  1. Unitat de Ressonància Magnètica (Servei de Radiologia, IDI), Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Psg. Vall d’Hebron 119-129, 08035, Barcelona, Spain

    D Pareto, F X Aymerich, C Auger & A Rovira

  2. Servei de Neurologia / Neuroimmunologia, Multiple Sclerosis Centre of Catalonia (Cemcat), Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain

    J Sastre-Garriga, M Tintoré & X Montalban

  3. Departament D’Enginyeria de Sistemes, Automàtica i Informàtica Industrial (ESAII), Universitat Politècnica de Catalunya (UPC), Barcelona, Spain

    F X Aymerich

Authors
  1. D Pareto
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  2. J Sastre-Garriga
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  3. F X Aymerich
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  4. C Auger
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  5. M Tintoré
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  6. X Montalban
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  7. A Rovira
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Corresponding author

Correspondence to D Pareto.

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We declare that this manuscript does not contain clinical studies or patient data.

Conflict of interest

DP has received speaking honoraria from Novartis and Genzyme. JSG has received compensation for consulting services and speaking honoraria from Merck-Serono, Biogen, Teva, Genzyme, Almirall, Novartis and Excemed. CA has received speaking honoraria from Novartis and Genzyme. MT has received compensation for consulting services and speaking honoraria from Almirall, Bayer, Biogen, Genzyme, Merck, Novartis, Roche, Sanofi-Aventis and Teva, and has been on advisory boards of Biogen, Genzyme and Teva; grants paid to the institution by Biogen and Novartis. XM has received speaking honoraria and travel expenses for scientific meetings, has been a steering committee member of clinical trials, or participated in advisory boards of clinical trials in the past with Actelion, Almirall, Bayer-Schering, Biogen, F. Hoffman - La Roche, Merck-Serono, Genentech, Genzyme, Novartis, Receptos, Sanofi and Teva; grants paid to the institution from Octopharma and Thropos. AR serves on scientific advisory boards and/or has received speaker honoraria from Biogen, Novartis, Genzyme, OLEA Medical, Bayer, Bracco, Merck-Serono, Teva and Stendhal.

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Pareto, D., Sastre-Garriga, J., Aymerich, F.X. et al. Lesion filling effect in regional brain volume estimations: a study in multiple sclerosis patients with low lesion load. Neuroradiology 58, 467–474 (2016). https://doi.org/10.1007/s00234-016-1654-5

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  • DOI: https://doi.org/10.1007/s00234-016-1654-5

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