Towards validation of diffusion MRI tractography: bridging the resolution gap with 3D Polarized Light Imaging

International audienceThree-dimensional Polarized Light Imaging (3D-PLI) is an optical approach presented as a good candidate for validation of diffusion Magnetic Resonance Imaging (dMRI) results such as orientation estimates (fiber Orientation Distribution Functions) and tractography. We developed an anlytical approach to reconstruct fiber ODFs from 3D-PLI datasets. From these fODFs, here we compute brain fiber tracts via dMRI-based probabilistic tractography algorithm. Reconstructed fODFs at different scales proves the ability to bridge the resolution gap between 3D-PLI and dMRI, demonstrating, therefore, a great promise to validate diffusion MRI tractography thanks to multi-scale fiber tracking based on 3D-PLI

Quantitative assessment of multi-scale tractography: bridging the resolution gap with 3D-PLI

International audienceThe in vivo validation of diffusion MRI (dMRI)-based tractography has beenshown to be a challenging task [Maier-hein et al.]. Therefore, we have been investigating how 3D Polarized Light Imaging (3D-PLI) could be used as a validation tool for dMRI-based fiber orientation estimation and tractography. PLI is an optical imaging technique that provides us with high-resolution fiber orientation measurements at micrometer scale. For this reason, it has been presented as a good candidate for the afore mentioned validation tasks [Axer et al,2011, Alimi et al, 2019 submitted]. In some previous works [alimi2017,18isbi,18ismrm,19,19submitted] we introduced an approach to close the resolution gap between dMRI and 3D-PLI. The study of the brain network from the topological point of view has seen an increasing interest in the last years [Sizemore et al, 2018, Chung et al, 2017]. In this work, we show how tractograms obtained at different spatial scales using 3D-PLI human brain datasets can bein spected using homology theory to perform a quantitative comparison between them. In particular, we investigate the persistence of the number of connected components in brain networks estimated from data at different resolutions

Regularizing the ODF estimate with the Laplace-Beltrami operator in 3D Polarized Light Imaging

International audience3D-Polarized Light Imaging (3D-PLI) is an optical approach that utilizes the birefringence in postmortem organs (brain/ heart) to map their spatial fiber structure at a submillimeter resolution. Recently, Axer et al. proposed a strategy to bridge it to relatively low diffusion MRI spatial resolution by introducing an estimate of the fiber orientation distribution functions (pliODF) from high-resolution 3D-PLI vector data. However, this method introduces angular errors by discretizing the directional histogram (DH), which limits the spherical harmonics (SH) expansion order. In this work, we propose to improve the angular resolution by making use of the Laplace-Beltrami (LB) operator to regularize the SH coefficients which define the fiber ODF at higher orders

Spherical convolutional neural network for diffusion MRI analysis

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An Analytical Fiber ODF Reconstruction in 3D Polarized Light Imaging

International audienceThree dimensional polarized light imaging (3D-PLI) utilizes the birefringence in postmortem tissue to map its spatial fiber structure at a submillimeter resolution. We propose an analytical method to compute the fiber orientation distribution function (ODF) from high-resolution vector data provided by 3D-PLI. This strategy enables the bridging of high resolution 3D-PLI to diffusion magnetic resonance imaging with relatively low spatial resolution. First, the fiber ODF is modeled as a sum of K orientations on the unit sphere and expanded with a high order spherical harmonics series. Then, the coefficients of the spherical harmonics are derived directly with the spherical Fourier transform. We quantitatively validate the accuracy of the reconstruction against synthetic data and show that we can recover complex fiber configurations in the human heart at different scales

Analytical Fiber ODF Reconstruction in 3D Polarized Light Imaging: Performance Assessment

International audienceThree dimensional Polarized Light Imaging (3D-PLI) allows to map the spatial fiber structure of postmortem tissue at a sub-millimeter resolution, thanks to its birefringence property. Different methods have been recently proposed to reconstruct the fiber orientation distribution function (fODF) from high-resolution vector data provided by 3D-PLI. Here, we focus on the analytical fODF computation approach, which uses the spherical harmonics to represent the fODF and analytically computes the spherical harmonics coefficients via the spherical Fourier transform. This work deals with the assessment of the performance of this approach on rich synthetic data which simulates the geometry of the neuronal fibers and on human brain dataset. A computational complexity and robustness to noise analysis demonstrate the interest and great potential of the approach

Analytical and fast Fiber Orientation Distribution reconstruction in 3D-Polarized Light Imaging

International audienceThree dimensional Polarized Light Imaging (3D-PLI) is an optical technique which allows mapping the spatial fiber architecture of fibrous postmortem tissues, at sub-millimeter resolutions. Here, we propose an analytical and fast approach to compute the fiber orientation distribution (FOD) from high-resolution vector data provided by 3D-PLI. The FOD is modeled as a sum of K orientations/Diracs on the unit sphere, described on a spherical harmonics basis and analytically computed using the spherical Fourier transform. Experiments are performed on rich synthetic data which simulate the geometry of the neuronal fibers and on human brain data. Results indicate the analytical FOD is computationally efficient and very fast, and has high angular precision and angular resolution. Furthermore, investigations on the right occipital lobe illustrate that our strategy of FOD computation enables the bridging of spatial scales from microscopic 3D-PLI information to macro-or mesoscopic dimensions of diffusion Magnetic Resonance Imaging (MRI), while being a means to evaluate prospective resolution limits for diffusion MRI to reconstruct regionspecific white matter tracts. These results demonstrate the interest and great potential of our analytical approach

Imagerie Tridimensionnelle en Lumière Polarisée: vers une Analyse Multi-échelle et Multimodale avec l'Imagerie par Résonance Magnétique pondérée en Diffusion

Diffusion Magnetic Resonance Imaging (dMRI) is the only non-invasive and in-vivo imaging modality able to provide human brain structural connectivity information. This is done via an estimation of the fiber orientation distribution (FOD) of white matter and dMRI tractography. In this thesis, three-dimensional Polarized Light Imaging (3D-PLI) is in- vestigated and, thanks to its high spatial resolution, is presented as a complementary and potential technique for validation and guidance of dMRI fiber orientation estimates and tracking. The main goal of this work is, thus, to propose a strategy to close the resolution gap between dMRI and 3D-PLI and to investigate metrics for their quantitative comparison and, henceforth, to pave the way for multiscale and multimodal image analysis. Contributions in this thesis are manifold. First, we study the 3D-PLI fiber orientation and propose a method to disentangle the sign ambiguity of its inclination angle for an accurate determination of the 3D orientation. Second, we introduce an analytical and fast technique to compute the FOD from microscopic 3D-PLI orientation estimates to the meso- or macroscopic dimensions of dMRI. Third, we perform tractography at multiple scales from 3D-PLI human brain data to demonstrate the preservation of the fiber tracts architecture regardless of the decrease in resolution. Finally, we investigate how these obtained tractograms can be inspected using homology theory for a quantitative evaluation between them. Overall, we develop original and efficient dMRI and 3D-PLI methods, validate on both synthetic and human data and lay the foundations for multiscale and multimodal studies between dMRI and 3D-PLI.L’Imagerie par Résonance Magnétique pondérée en diffusion (IRMd) est la seule modalité in-vivo et non invasive offrant des informations sur la connectivité structurelle du cerveau humain. Cela est effectué via l’estimation de la distribution des orientations de fibres (FOD) de la matière blanche et leur suivi ou tractographie. Dans cette thèse, l’Imagerie tridimensionnelle en Lumière Polarisée (3D-PLI) est, grâce à sa haute résolution, considérée comme une potentielle technique complémentaire et de validation de l’estimation et du suivi des orientations de fibres par l’IRMd. Ainsi, notre travail a pour but principal de combler l’écart de résolution et d’étudier des critères de comparaison quantitative entre l’IRMd et la 3D-PLI pour ainsi ouvrir la voie à une analyse multi-modale et multi-échelle. Nos contributions sont multiples. D’abord, nous étudions l’orientation des fibres produites par 3D-PLI et proposons une méthode pour lever l’ambigüité du signe de l’inclinaison pour une estimation plus précise. Puis, nous développons une méthode analytique de calcul de la FOD des mesures microscopiques de 3D-PLI à la résolution meso- ou macroscopique de l’IRMd. Ensuite, à partir des données PLI du cerveau, nous effectuons la tractographie à diverses échelles et montrons la conservation de l’architecture structurelle des fibres malgré la baisse de résolution. Enfin, nous nous intéressons à la théorie de l’homologie en vue d’évaluation quantitative des résultats de tractographie. En somme, nous développons des méthodes en IRMd et 3D-PLI, et les validons sur des données synthétiques et réelles tout en établissant les bases d’études multi-échelles et multi-modales entre IRMd et 3D-PLI

Three-dimensional polarized light imaging : towards multiscale and multimodal analysis with diffusion magnetic resonance imaging

L’Imagerie par Résonance Magnétique pondérée en diffusion (IRMd) est la seule modalité in-vivo et non invasive offrant des informations sur la connectivité structurelle du cerveau humain. Cela est effectué via l’estimation de la distribution des orientations de fibres (FOD) de la matière blanche et leur suivi ou tractographie. Dans cette thèse, l’Imagerie tridimensionnelle en Lumière Polarisée (3D-PLI) est, grâce à sa haute résolution, considérée comme une potentielle technique complémentaire et de validation de l’estimation et du suivi des orientations de fibres par l’IRMd. Ainsi, notre travail a pour but principal de combler l’écart de résolution et d’étudier des critères de comparaison quantitative entre l’IRMd et la 3D-PLI pour ainsi ouvrir la voie à une analyse multi-modale et multi-échelle.Nos contributions sont multiples. D’abord, nous étudions l’orientation des fibres produites par 3D-PLI et proposons une méthode pour lever l’ambiguıẗ é du signe de l’inclinaison pour une estimation plus précise. Puis, nous développons une méthode analytique de calcul de la FOD des mesures microscopiques de 3D-PLI à la résolution meso- ou macroscopique de l’IRMd. Ensuite, à partir des données PLI du cerveau, nous effectuons la tractographie à diverses échelles et montrons la conservation de l’architecture structurelle des fibres malgré la baisse de résolution. Enfin, nous nous intéressons à la théorie de l’homologie en vue d’évaluation quantitative des résultats de tractographie. En somme, nous développons des méthodes en IRMd et 3D-PLI, et les validons sur des données synthétiques et réelles tout en établissant les bases d’études multi-échelles et multi-modales entre IRMd et 3D-PLI.Diffusion Magnetic Resonance Imaging (dMRI) is the only non-invasive and invivo imaging modality able to provide human brain structural connectivity information. This is done via an estimation of the fiber orientation distribution (FOD) of white matter and dMRI tractography. In this thesis, three-dimensional Polarized Light Imaging (3D-PLI) is investigated and, thanks to its high spatial resolution, is presented as a complementary and potential technique for validation and guidance of dMRI fiber orientation estimates and tracking. The main goal of this work is, thus, to propose a strategy to close the resolution gap between dMRI and 3D-PLI and to investigate metrics for their quantitative comparison and, henceforth, to pave the way for multiscale and multimodal image analysis.Contributions in this thesis are manifold. First, we study the 3D-PLI fiber orientation and propose a method to disentangle the sign ambiguity of its inclination angle for an accurate determination of the 3D orientation. Second, we introduce an analytical and fast technique to compute the FOD from microscopic 3D-PLI orientation estimates to the meso- or macroscopic dimensions of dMRI. Third, we perform tractography at multiple scales from 3D-PLI human brain data to demonstrate the preservation of the fiber tracts architecture regardless of the decrease in resolution. Finally, we investigate how these obtained tractograms can be inspected using homology theory for a quantitative evaluation between them. Overall, we develop original and efficient dMRI and 3D-PLI methods, validate on both synthetic and human data and lay the foundations for multiscale and multimodal studies between dMRI and 3D-PLI

Towards validation of diffusion MRI tractography: bridging the resolution gap with 3D Polarized Light Imaging

International audienceSynopsis Three-dimensional Polarized Light Imaging (3D-PLI) is an optical approach presented as a good candidate for validation of diffusion Magnetic Resonance Imaging (dMRI) results such as orientation estimates (fiber Orientation Distribution Functions) and tractography. We developed an anlytical approach to reconstruct fiber ODFs from 3D-PLI datasets. From these fODFs, here we compute brain fiber tracts via dMRI-based probabilistic tractography algorithm. Reconstructed fODFs at different scales proves the ability to bridge the resolution gap between 3D-PLI and dMRI, demonstrating, therefore, a great promise to validate diffusion MRI tractography thanks to multi-scale fiber tracking based on 3D-PLI