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Review
. 2023 Dec 15;12(24):7706.
doi: 10.3390/jcm12247706.

Diagnostic and Therapeutic Issues in Glioma Using Imaging Data: The Challenge of Numerical Twinning

Rémy Guillevin  1   2   3 , Mathieu Naudin  1   2   3 , Pierre Fayolle  1   2   3 , Clément Giraud  1   2   3 , Xavier Le Guillou  2   3   4 , Clément Thomas  1   2   3 , Guillaume Herpe  1   2   3 , Alain Miranville  2   3 , Christine Fernandez-Maloigne  2   5 , Luc Pellerin  6 , Carole Guillevin  1   2   3
Affiliations
Review

Diagnostic and Therapeutic Issues in Glioma Using Imaging Data: The Challenge of Numerical Twinning

Rémy Guillevin et al. J Clin Med. .

Abstract

Glial tumors represent the leading etiology of primary brain tumors. Their particularities lie in (i) their location in a highly functional organ that is difficult to access surgically, including for biopsy, and (ii) their rapid, anisotropic mode of extension, notably via the fiber bundles of the white matter, which further limits the possibilities of resection. The use of mathematical tools enables the development of numerical models representative of the oncotype, genotype, evolution, and therapeutic response of lesions. The significant development of digital technologies linked to high-resolution NMR exploration, coupled with the possibilities offered by AI, means that we can envisage the creation of digital twins of tumors and their host organs, thus reducing the use of physical sampling.

Keywords: connectome; functional MRI; metabolic MRI; numerical twin; virtual biopsy.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
(A) schematic comparison between physical (needle) biopsy: focal and partial and virtual, global biopsy (grid superimposed in successive slices). (B) Different fields of knowledge required in a team for achieving numerical twinning for an organ in the course of its pathological process.
Figure 2
Figure 2
Fast-slow system. Rapid variations of [Lac] (vertical lines) around a medium value (green cross) on asymptotic trajectory, in accordance with in vivo spectroscopic quantifications.
Figure 3
Figure 3
Two examples of the evolution of local lactate concentration (red dots: patient data; black curve: model simulation) in a WHO IV glioma [57]. In vivo measurements fit in silico predictions.
Figure 4
Figure 4
Constructing a functional map from resting fMRI data. The connectivity matrix provides temporal correlations between each possible pairs of times series. The functional network is then identified after clustering both matrix and graph representation.
Figure 5
Figure 5
Comparison between dynamics fluctuations of metabolites ratios and volumetric measurements on LGG under TMZ treatment: stronger variations within a short time delay allowing better monitoring. (A) axial image FLAIR of low-grade glioma at 8 months (inflexion point ★) with associated spectrum showing a ratio Cho/NAA at 0.48, (B) axial image FLAIR of low-grade glioma at 9 month (circle represent the relapse) and the spectrum with a ratio Cho/NAA at 0.61. we can observe a volume augmentation of 2% and 22% for the ratio cho/NAA in one month [94].
See this image and copyright information in PMC

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