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Article

Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study

1
Department of Nuclear Medicine, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium
2
Center for Microscopy and Molecular Imaging (CMMI), Université Libre de Bruxelles, Rue Adrienne Bolland 8, 6041 Charleroi, Belgium
3
Laboratory of Image Synthesis and Analysis (LISA), École Polytechnique de Bruxelles, Université Libre de Bruxelles, Avenue Franklin Roosevelt 50, 1050 Brussels, Belgium
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Department of Pathology, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium
5
Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
These authors contributed equally to this work.
Academic Editor: Emilio Quaia
Tomography 2021, 7(4), 650-674; https://doi.org/10.3390/tomography7040055
Received: 6 September 2021 / Revised: 22 October 2021 / Accepted: 25 October 2021 / Published: 29 October 2021
Reaction-diffusion models have been proposed for decades to capture the growth of gliomas. Nevertheless, these models require an initial condition: the tumor cell density distribution over the whole brain at diagnosis time. Several works have proposed to relate this distribution to abnormalities visible on magnetic resonance imaging (MRI). In this work, we verify these hypotheses by stereotactic histological analysis of a non-operated brain with glioblastoma using a 3D-printed slicer. Cell density maps are computed from histological slides using a deep learning approach. The density maps are then registered to a postmortem MR image and related to an MR-derived geodesic distance map to the tumor core. The relation between the edema outlines visible on T2-FLAIR MRI and the distance to the core is also investigated. Our results suggest that (i) the previously proposed exponential decrease of the tumor cell density with the distance to the core is reasonable but (ii) the edema outlines would not correspond to a cell density iso-contour and (iii) the suggested tumor cell density at these outlines is likely overestimated. These findings highlight the limitations of conventional MRI to derive glioma cell density maps and the need for other initialization methods for reaction-diffusion models to be used in clinical practice. View Full-Text
Keywords: cellularity; digital pathology; glioma; histology; magnetic resonance imaging; reaction-diffusion model; registration; tumor growth modeling; 3D printing cellularity; digital pathology; glioma; histology; magnetic resonance imaging; reaction-diffusion model; registration; tumor growth modeling; 3D printing
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MDPI and ACS Style

Martens, C.; Lebrun, L.; Decaestecker, C.; Vandamme, T.; Van Eycke, Y.-R.; Rovai, A.; Metens, T.; Debeir, O.; Goldman, S.; Salmon, I.; Van Simaeys, G. Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study. Tomography 2021, 7, 650-674. https://doi.org/10.3390/tomography7040055

AMA Style

Martens C, Lebrun L, Decaestecker C, Vandamme T, Van Eycke Y-R, Rovai A, Metens T, Debeir O, Goldman S, Salmon I, Van Simaeys G. Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study. Tomography. 2021; 7(4):650-674. https://doi.org/10.3390/tomography7040055

Chicago/Turabian Style

Martens, Corentin, Laetitia Lebrun, Christine Decaestecker, Thomas Vandamme, Yves-Rémi Van Eycke, Antonin Rovai, Thierry Metens, Olivier Debeir, Serge Goldman, Isabelle Salmon, and Gaetan Van Simaeys. 2021. "Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study" Tomography 7, no. 4: 650-674. https://doi.org/10.3390/tomography7040055

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