Differences in Gaussian diffusion tensor imaging and non-Gaussian diffusion kurtosis imaging model-based estimates of diffusion tensor invariants in the human brain

Lanzafame, Simona; Giannelli, Marco; Garaci, Francesco; Floris, Roberto; Duggento, Andrea; Guerrisi, Maria; Toschi, Nicola

doi:10.1118/1.4946819

Cited by 33 publications

(19 citation statements)

References 64 publications

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“…However, many of these interesting advances including both MRI acquisition and tractography approaches have not yet entered clinical routine. Nonetheless, recent technical innovations such as the use of optimized b -values and kurtosis tensor strategies (Marrale et al, 2015, Lanzafame et al, 2016) may further improve the future value of diffusion imaging in routine diagnostics. Furthermore, the improving processor power of modern computers will, in time, enable probabilistic DTI tractography to be fast enough for routine clinical use in preoperative tumour diagnostics.…”

Section: Discussionmentioning

confidence: 99%

Functional MRI vs. navigated TMS to optimize M1 seed volume delineation for DTI tractography. A prospective study in patients with brain tumours adjacent to the corticospinal tract

Lucas

Tursunova

Neuschmelting

et al. 2017

NeuroImage: Clinical

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BackgroundDTI-based tractography is an increasingly important tool for planning brain surgery in patients suffering from brain tumours. However, there is an ongoing debate which tracking approaches yield the most valid results. Especially the use of functional localizer data such as navigated transcranial magnetic stimulation (nTMS) or functional magnetic resonance imaging (fMRI) seem to improve fibre tracking data in conditions where anatomical landmarks are less informative due to tumour-induced distortions of the gyral anatomy. We here compared which of the two localizer techniques yields more plausible results with respect to mapping different functional portions of the corticospinal tract (CST) in brain tumour patients.MethodsThe CSTs of 18 patients with intracranial tumours in the vicinity of the primary motor area (M1) were investigated by means of deterministic DTI. The core zone of the tumour-adjacent hand, foot and/or tongue M1 representation served as cortical regions of interest (ROIs). M1 core zones were defined by both the nTMS hot-spots and the fMRI local activation maxima. In addition, for all patients, a subcortical ROI at the level of the inferior anterior pons was implemented into the tracking algorithm in order to improve the anatomical specificity of CST reconstructions. As intra-individual control, we additionally tracked the CST of the hand motor region of the unaffected, i.e., non-lesional hemisphere, again comparing fMRI and nTMS M1 seeds. The plausibility of the fMRI-ROI- vs. nTMS-ROI-based fibre trajectories was assessed by a-priori defined anatomical criteria. Moreover, the anatomical relationship of different fibre courses was compared regarding their distribution in the anterior-posterior direction as well as their location within the posterior limb of the internal capsule (PLIC).ResultsOverall, higher plausibility rates were observed for the use of nTMS- as compared to fMRI-defined cortical ROIs (p < 0.05) in tumour vicinity. On the non-lesional hemisphere, however, equally good plausibility rates (100%) were observed for both localizer techniques. fMRI-originated fibres generally followed a more posterior course relative to the nTMS-based tracts (p < 0.01) in both the lesional and non-lesional hemisphere.ConclusionNTMS achieved better tracking results than fMRI in conditions when the cortical tract origin (M1) was located in close vicinity to a brain tumour, probably influencing neurovascular coupling. Hence, especially in situations with altered BOLD signal physiology, nTMS seems to be the method of choice in order to identify seed regions for CST mapping in patients.

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Section: Discussionmentioning

confidence: 99%

Functional MRI vs. navigated TMS to optimize M1 seed volume delineation for DTI tractography. A prospective study in patients with brain tumours adjacent to the corticospinal tract

Lucas

Tursunova

Neuschmelting

et al. 2017

NeuroImage: Clinical

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“…Conceptually, DKI quantifies the deviation from Gaussianity of the self-diffusion probability profile of water molecules in brain tissue. In a complex cytoarchitectonic environment such as white or grey matter, because such deviations are strongly influenced by the underlying microstructure, DKI indices are able to provide complementary information about microstructural alterations as compared with DTI alone [ 25 ]. In this context, a small number of previous studies investigated DKI alterations in glaucoma patients using a region-of interest (ROI)-based approach [ 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

Diffusional Kurtosis Imaging of White Matter Degeneration in Glaucoma

Nucci

Garaci

Altobelli

et al. 2020

JCM

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Glaucoma is an optic neuropathy characterized by death of retinal ganglion cells and loss of their axons, progressively leading to blindness. Recently, glaucoma has been conceptualized as a more diffuse neurodegenerative disorder involving the optic nerve and also the entire brain. Consistently, previous studies have used a variety of magnetic resonance imaging (MRI) techniques and described widespread changes in the grey and white matter of patients. Diffusion kurtosis imaging (DKI) provides additional information as compared with diffusion tensor imaging (DTI), and consistently provides higher sensitivity to early microstructural white matter modification. In this study, we employ DKI to evaluate differences among healthy controls and a mixed population of primary open angle glaucoma patients ranging from stage I to V according to Hodapp–Parrish–Anderson visual field impairment classification. To this end, a cohort of patients affected by primary open angle glaucoma (n = 23) and a group of healthy volunteers (n = 15) were prospectively enrolled and underwent an ophthalmological evaluation followed by magnetic resonance imaging (MRI) using a 3T MR scanner. After estimating both DTI indices, whole-brain, voxel-wise statistical comparisons were performed in white matter using Tract-Based Spatial Statistics (TBSS). We found widespread differences in several white matter tracts in patients with glaucoma relative to controls in several metrics (mean kurtosis, kurtosis anisotropy, radial kurtosis, and fractional anisotropy) which involved localization well beyond the visual pathways, and involved cognitive, motor, face recognition, and orientation functions amongst others. Our findings lend further support to a causal brain involvement in glaucoma and offer alternative explanations for a number of multidomain impairments often observed in glaucoma patients.

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“…An in-house implementation of the kurtosis model that integrates important constraints for robustness to noise (Groeschel et al, 2016 ) was found to improve the fit and the derived parameter maps. Since DT derived metrics from the DT model and the kurtosis model, however, are not directly comparable (Lanzafame et al, 2016 ), those parameters should be reported for both models. To further extend the comparison of DT model parameters obtained from CS-DSI and 3-shell HARDI, future work could convert CS-DSI and 3-shell HARDI data to corresponding single-shell HARDI data (Yeh and Verstynen, 2016 ).…”

Section: Discussionmentioning

confidence: 99%

Compressed Sensing Diffusion Spectrum Imaging for Accelerated Diffusion Microstructure MRI in Long-Term Population Imaging

et al. 2018

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Mapping non-invasively the complex microstructural architecture of the living human brain, diffusion magnetic resonance imaging (dMRI) is one of the core imaging modalities in current population studies. For the application in longitudinal population imaging, the dMRI protocol should deliver reliable data with maximum potential for future analysis. With the recent introduction of novel MRI hardware, advanced dMRI acquisition strategies can be applied within reasonable scan time. In this work we conducted a pilot study based on the requirements for high resolution dMRI in a long-term and high throughput population study. The key question was: can diffusion spectrum imaging accelerated by compressed sensing theory (CS-DSI) be used as an advanced imaging protocol for microstructure dMRI in a long-term population imaging study? As a minimum requirement we expected a high level of agreement of several diffusion metrics derived from both CS-DSI and a 3-shell high angular resolution diffusion imaging (HARDI) acquisition, an established imaging strategy used in other population studies. A wide spectrum of state-of-the-art diffusion processing and analysis techniques was applied to the pilot study data including quantitative diffusion and microstructural parameter mapping, fiber orientation estimation and white matter fiber tracking. When considering diffusion weighted images up to the same maximum diffusion weighting for both protocols, group analysis across 20 subjects indicates that CS-DSI performs comparable to 3-shell HARDI in the estimation of diffusion and microstructural parameters. Further, both protocols provide similar results in the estimation of fiber orientations and for local fiber tracking. CS-DSI provides high radial resolution while maintaining high angular resolution and it is well-suited for analysis strategies that require high b-value acquisitions, such as CHARMED modeling and biomarkers from the diffusion propagator.

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Differences in Gaussian diffusion tensor imaging and non-Gaussian diffusion kurtosis imaging model-based estimates of diffusion tensor invariants in the human brain

Cited by 33 publications

References 64 publications

Functional MRI vs. navigated TMS to optimize M1 seed volume delineation for DTI tractography. A prospective study in patients with brain tumours adjacent to the corticospinal tract

Functional MRI vs. navigated TMS to optimize M1 seed volume delineation for DTI tractography. A prospective study in patients with brain tumours adjacent to the corticospinal tract

Diffusional Kurtosis Imaging of White Matter Degeneration in Glaucoma

Compressed Sensing Diffusion Spectrum Imaging for Accelerated Diffusion Microstructure MRI in Long-Term Population Imaging

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