BundleSeg: A versatile, reliable and reproducible approach to white matter bundle segmentation

This work presents BundleSeg, a reliable, reproducible, and fast method for extracting white matter pathways. The proposed method combines an iterative registration procedure with a recently developed precise streamline search algorithm that enables efficient segmentation of streamlines without the need for tractogram clustering or simplifying assumptions. We show that BundleSeg achieves improved repeatability and reproducibility than state-of-the-art segmentation methods, with significant speed improvements. The enhanced precision and reduced variability in extracting white matter connections offer a valuable tool for neuroinformatic studies, increasing the sensitivity and specificity of tractography-based studies of white matter pathways

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process

Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging

Subtle changes in white matter (WM) microstructure have been associated with normal aging and neurodegeneration. To study these associations in more detail, it is highly important that the WM tracts can be accurately and reproducibly characterized from brain diffusion MRI. In addition, to enable analysis of WM tracts in large datasets and in clinical practice it is essential to have methodology that is fast and easy to apply. This work therefore presents a new approach for WM tract segmentation: Neuro4Neuro, that is capable of direct extraction of WM tracts from diffusion tensor images using convolutional neural network (CNN). This 3D end-to-end method is trained to segment 25 WM tracts in aging individuals from a large population-based study (N=9752, 1.5T MRI). The proposed method showed good segmentation performance and high reproducibility, i.e., a high spatial agreement (Cohen's kappa, k = 0.72 ~ 0.83) and a low scan-rescan error in tract-specific diffusion measures (e.g., fractional anisotropy: error = 1% ~ 5%). The reproducibility of the proposed method was higher than that of a tractography-based segmentation algorithm, while being orders of magnitude faster (0.5s to segment one tract). In addition, we showed that the method successfully generalizes to diffusion scans from an external dementia dataset (N=58, 3T MRI). In two proof-of-principle experiments, we associated WM microstructure obtained using the proposed method with age in a normal elderly population, and with disease subtypes in a dementia cohort. In concordance with the literature, results showed a widespread reduction of microstructural organization with aging and substantial group-wise microstructure differences between dementia subtypes. In conclusion, we presented a highly reproducible and fast method for WM tract segmentation that has the potential of being used in large-scale studies and clinical practice.Comment: Preprint to be published in NeuroImag

Analyse et reconstruction de faisceaux de la matière blanche

L'imagerie par résonance magnétique de diffusion (IRMd) est une modalité d'acquisition permettant de sonder les tissus biologiques et d'en extraire une variété d'informations sur le mouvement microscopique des molécules d'eau. Plus spécifiquement à l'imagerie médicale, l'IRMd permet l'investigation des structures fibreuses de nombreux organes et facilite la compréhension des processus cognitifs ou au diagnostic. Dans le domaine des neurosciences, l'IRMd est cruciale à l'exploration de la connectivité structurelle de la matière blanche. Cette thèse s'intéresse plus particulièrement à la reconstruction de faisceaux de la matière blanche ainsi qu'à leur analyse. Toute la complexité du traitement des données commençant au scanneur jusqu'à la création d'un tractogramme est extrêmement importante. Par contre, l'application spécifique de reconstruction des faisceaux anatomiques plausibles est ultimement le véritable défi de l'IRMd. L'optimisation des paramètres de la tractographie, le processus de segmentation manuelle ou automatique ainsi que l'interprétation des résultats liée à ces faisceaux sont toutes des étapes du processus avec leurs lots de difficultés

Tractographic and Microstructural Analysis of the Dentato-Rubro-Thalamo-Cortical Tracts in Children Using Diffusion MRI

The dentato-rubro-thalamo-cortical tract (DRTC) is the main outflow pathway of the cerebellum, contributing to a finely balanced corticocerebellar loop involved in cognitive and sensorimotor functions. Damage to the DRTC has been implicated in cerebellar mutism syndrome seen in up to 25% of children after cerebellar tumor resection. Multi-shell diffusion MRI (dMRI) combined with quantitative constrained spherical deconvolution tractography and multi-compartment spherical mean technique modeling was used to explore the frontocerebellar connections and microstructural signature of the DRTC in 30 healthy children. The highest density of DRTC connections were to the precentral (M1) and superior frontal gyri (F1), and from cerebellar lobules I-IV and IX. The first evidence of a topographic organization of anterograde projections to the frontal cortex at the level of the superior cerebellar peduncle (SCP) is demonstrated, with streamlines terminating in F1 lying dorsomedially in the SCP compared to those terminating in M1. The orientation dispersion entropy of DRTC regions appears to exhibit greater contrast than that shown by fractional anisotropy. Analysis of a separate reproducibility cohort demonstrates good consistency in the dMRI metrics described. These novel anatomical insights into this well-studied pathway may prove to be of clinical relevance in the surgical resection of cerebellar tumors

Mapping the subcortical connectome using in vivo diffusion MRI: Feasibility and reliability

Tractography combined with regions of interest (ROIs) has been used to non-invasively study the structural connectivity of the cortex as well as to assess the reliability of these connections. However, the subcortical connectome (subcortex to subcortex) has not been comprehensively examined, in part due to the difficulty of performing tractography in this complex and compact region. In this study, we performed an in vivo investigation using tractography to assess the feasibility and reliability of mapping known connections between structures of the subcortex using the test-retest dataset from the Human Connectome Project (HCP). We further validated our observations using a separate unrelated subjects dataset from the HCP. Quantitative assessment was performed by computing tract densities and spatial overlap of identified connections between subcortical ROIs. Further, known connections between structures of the basal ganglia and thalamus were identified and visually inspected, comparing tractography reconstructed trajectories with descriptions from tract-tracing studies. Our observations demonstrate both the feasibility and reliability of using a data-driven tractography-based approach to map the subcortical connectome in vivo

Reproducible protocol to obtain and measure first-order relay human thalamic white-matter tracts

Available online 13 August 2022The “primary ”or “first-order relay ”nuclei of the thalamus feed the cerebral cortex with information about on- going activity in the environment or the subcortical motor systems. Because of the small size of these nuclei and the high specificity of their input and output pathways, new imaging protocols are required to investigate thala- mocortical interactions in human perception, cognition and language. The goal of the present study was twofold: I) to develop a reconstruction protocol based on in vivo diffusion MRI to extract and measure the axonal fiber tracts that originate or terminate specifically in individual first-order relay nuclei; and, II) to test the reliability of this reconstruction protocol. In left and right hemispheres, we investigated the thalamocortical/corticothalamic axon bundles linking each of the first-order relay nuclei and their main cortical target areas, namely, the lateral geniculate nucleus (optic radiation), the medial geniculate nucleus (acoustic radiation), the ventral posterior nu- cleus (somatosensory radiation) and the ventral lateral nucleus (motor radiation). In addition, we examined the main subcortical input pathway to the ventral lateral posterior nucleus, which originates in the dentate nucleus of the cerebellum. Our protocol comprised three components: defining regions-of-interest; preprocessing diffu- sion data; and modeling white-matter tracts and tractometry. We then used computation and test-retest methods to check whether our protocol could reliably reconstruct these tracts of interest and their profiles. Our results demonstrated that the protocol had nearly perfect computational reproducibility and good-to-excellent test-retest reproducibility. This new protocol may be of interest for both basic human brain neuroscience and clinical studies and has been made publicly available to the scientific community.This work was supported by grants from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie (grant agreement No. 713673 ), and from “la Caixa ”Foundation (grant No. 11660016 ) to M.L.; grants from the Span- ish Ministerio de Ciencia e Innovación ( IJC2020-042887-I ; PID2021- 123577NA-I00 ) to G.L.-U.; grants from the European Union ’s Horizon 2020 Research and Innovation Program, European Commission (grant agreement No. 945539 - HBP SGA3 ) and from the Ministerio de Ciencia e Innovación FLAG-ERA grant NeuronsReunited ( MICINN-AEI PCI2019-111900-2 ) to F.C.; and grants from the Ministerio de Ciencia e Innovación ( PGC2018-093408-B-I00 ; PID2021-123574NB-I00 ), Neuro- science projects from the Fundación Tatiana Pérez de Guzmán el Bueno , Basque Government ( PIBA-2021-1-0003 ), and a grant from “la Caixa ”Banking Foundation under the project code LCF/PR/HR19/52160002 to P.M.P.-A. BCBL acknowledges support by the Basque Government through the BERC 2022-2025 program and by the S panish State Re- search Agency through BCBL Severo Ochoa excellence accreditation CEX2020-001010-S