Tractography in the presence of multiple sclerosis lesions

Lipp, Ilona; Parker, Greg D.; Tallantyre, Emma; Goodall, Alex; Grama, Steluta; Patitucci, Eleonora; Heveron, Phoebe; Tomassini, Valentina; Jones, Derek K.

doi:10.1016/j.neuroimage.2019.116471

Cited by 43 publications

(32 citation statements)

References 69 publications

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“…Moreover, as MS lesions may affect the tractography-derived reconstruction of WM fibers, they need to be taken better into account. While traditional DTI-based fiber tracking may underestimate the effect of MS lesions on WM tracts, novel methods such as constrained spherical deconvolution–based fiber tracking ( 120 , 121 ) and convex optimization modeling for microstructure informed tractography ( 122 ) were able to perform a more adequate WM fiber tracts reconstruction in the MS lesional brain ( 121 , 122 ), thus providing a more reliable assessment of SC ( 122 ). Finally, data-driven methods for extracting structural networks, such as ICA and NMF, have rarely been used in the MS field.…”

Section: Future Directionsmentioning

confidence: 99%

Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis

et al. 2021

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Cognitive impairment (CI) occurs in 43 to 70% of multiple sclerosis (MS) patients at both early and later disease stages. Cognitive domains typically involved in MS include attention, information processing speed, memory, and executive control. The growing use of advanced magnetic resonance imaging (MRI) techniques is furthering our understanding on the altered structural connectivity (SC) and functional connectivity (FC) substrates of CI in MS. Regarding SC, different diffusion tensor imaging (DTI) measures (e.g., fractional anisotropy, diffusivities) along tractography-derived white matter (WM) tracts showed relevance toward CI. Novel diffusion MRI techniques, including diffusion kurtosis imaging, diffusion spectrum imaging, high angular resolution diffusion imaging, and neurite orientation dispersion and density imaging, showed more pathological specificity compared to the traditional DTI but require longer scan time and mathematical complexities for their interpretation. As for FC, task-based functional MRI (fMRI) has been traditionally used in MS to brain mapping the neural activity during various cognitive tasks. Analysis methods of resting fMRI (seed-based, independent component analysis, graph analysis) have been applied to uncover the functional substrates of CI in MS by revealing adaptive or maladaptive mechanisms of functional reorganization. The relevance for CI in MS of SC–FC relationships, reflecting common pathogenic mechanisms in WM and gray matter, has been recently explored by novel MRI analysis methods. This review summarizes recent advances on MRI techniques of SC and FC and their potential to provide a deeper understanding of the pathological substrates of CI in MS.

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Section: Future Directionsmentioning

confidence: 99%

Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis

et al. 2021

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“…If only diffusion‐weighted magnetic resonance imaging data are available, it is reasonable to assume that the intra‐axonal diffusion signal is constant along the tract and COMMIT uses any predefined microstructural model to estimate it. Similarly to what was recently found in Lipp et al (), using the recently introduced multishell multitissue spherical deconvolution (Jeurissen et al, ) and the probabilistic algorithm (Tournier et al, ) to generate streamlines, we were able to propagate the tracking also inside MS lesions to build the input tractograms. We then applied COMMIT to decide if a streamline passing through a lesion is essential to explain the signal or not and consequently keeps or discards it to construct the final tractogram.…”

Section: Discussionmentioning

confidence: 81%

Sensory‐motor network topology in multiple sclerosis: Structural connectivity analysis accounting for intrinsic density discrepancy

Schiavi

Petracca

Battocchio

et al. 2020

Human Brain Mapping

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Graph theory and network modelling have been previously applied to characterize motor network structural topology in multiple sclerosis (MS). However, between‐group differences disclosed by graph analysis might be primarily driven by discrepancy in density, which is likely to be reduced in pathologic conditions as a consequence of macroscopic damage and fibre loss that may result in less streamlines properly traced. In this work, we employed the convex optimization modelling for microstructure informed tractography (COMMIT) framework, which, given a tractogram, estimates the actual contribution (or weight) of each streamline in order to optimally explain the diffusion magnetic resonance imaging signal, filtering out those that are implausible or not necessary. Then, we analysed the topology of this ‘COMMIT‐weighted sensory‐motor network’ in MS accounting for network density. By comparing with standard connectivity analysis, we also tested if abnormalities in network topology are still identifiable when focusing on more ‘quantitative’ network properties. We found that topology differences identified with standard tractography in MS seem to be mainly driven by density, which, in turn, is strongly influenced by the presence of lesions. We were able to identify a significant difference in density but also in network global and local properties when accounting for density discrepancy. Therefore, we believe that COMMIT may help characterize the structural organization in pathological conditions, allowing a fair comparison of connectomes which considers discrepancies in network density. Moreover, discrepancy‐corrected network properties are clinically meaningful and may help guide prognosis assessment and treatment choice.

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“…It is known that WM lesions can affect the tractography algorithm, track reconstruction and track-dissection ( Lipp et al, 2020 ). Strategies must be employed to avoid premature track termination, as both FA threshold and T1-based segmentations would result in “holes” were tracking would not be possible.…”

Section: Discussionmentioning

confidence: 99%

Modern Technology in Multi-Shell Diffusion MRI Reveals Diffuse White Matter Changes in Young Adults With Relapsing-Remitting Multiple Sclerosis

et al. 2021

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ObjectiveTo characterize microstructural white matter changes related to relapsing-remitting multiple sclerosis using advanced diffusion MRI modeling and tractography. The association between imaging data and patient’s cognitive performance, fatigue severity and depressive symptoms is also explored.MethodsIn this cross-sectional study, 24 relapsing-remitting multiple sclerosis patients and 11 healthy controls were compared using high angular resolution diffusion imaging (HARDI). The imaging method includes a multi-shell scheme, free water correction to obtain tissue-specific measurements, probabilistic tracking algorithm robust to crossing fibers and white matter lesions, automatic streamlines and bundle dissection and tract-profiling with tractometry. The neuropsychological evaluation included the Symbol Digit Modalities Test, Paced Auditory Serial Addition Test, Modified Fatigue Impact Scale and Beck Depression Inventory-II.ResultsBundle-wise analysis by tractometry revealed a difference between patients and controls for 11 of the 14 preselected white matter bundles. In patients, free water corrected fractional anisotropy was significantly reduced while radial and mean diffusivities were increased, consistent with diffuse demyelination. The fornix and left inferior fronto-occipital fasciculus exhibited a higher free water fraction. Eight bundles showed an increase in total apparent fiber density and four bundles had a higher number of fiber orientations, suggesting axonal swelling and increased organization complexity, respectively. In the association study, depressive symptoms were associated with diffusion abnormalities in the right superior longitudinal fasciculus.ConclusionTissue-specific diffusion measures showed abnormalities along multiple cerebral white matter bundles in patients with relapsing-remitting multiple sclerosis. The proposed methodology combines free-water imaging, advanced bundle dissection and tractometry, which is a novel approach to investigate cerebral pathology in multiple sclerosis. It opens a new window of use for HARDI-derived measures and free water corrected diffusion measures. Advanced diffusion MRI provides a better insight into cerebral white matter changes in relapsing-remitting multiple sclerosis, namely diffuse demyelination, edema and increased fiber density and complexity.

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Tractography in the presence of multiple sclerosis lesions

Cited by 43 publications

References 69 publications

Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis

Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis

Sensory‐motor network topology in multiple sclerosis: Structural connectivity analysis accounting for intrinsic density discrepancy

Modern Technology in Multi-Shell Diffusion MRI Reveals Diffuse White Matter Changes in Young Adults With Relapsing-Remitting Multiple Sclerosis

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