Dataset Information

Tractostorm: The what, why, and how of tractography dissection reproducibility.

ABSTRACT: Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called "virtual dissection." Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC-ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real-life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and "virtual dissection" across various laboratories and hospitals. Intra-rater agreement (Dice score) was approximately 0.77, while inter-rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science.

SUBMITTER: Rheault F

PROVIDER: S-EPMC7267902 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Tractostorm: The what, why, and how of tractography dissection reproducibility.

Rheault Francois F De Benedictis Alessandro A Daducci Alessandro A Maffei Chiara C Tax Chantal M W CMW Romascano David D Caverzasi Eduardo E Morency Felix C FC Corrivetti Francesco F Pestilli Franco F Girard Gabriel G Theaud Guillaume G Zemmoura Ilyess I Hau Janice J Glavin Kelly K Jordan Kesshi M KM Pomiecko Kristofer K Chamberland Maxime M Barakovic Muhamed M Goyette Nil N Poulin Philippe P Chenot Quentin Q Panesar Sandip S SS Sarubbo Silvio S Petit Laurent L Descoteaux Maxime M

Human brain mapping 20200110 7

Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called "virtual dissection." Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations ...[more]

PMID: 31925871

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Project description:The segmentation of brain structures is a key component of many neuroimaging studies. Consistent anatomical definitions are crucial to ensure consensus on the position and shape of brain structures, but segmentations are prone to variation in their interpretation and execution. White-matter (WM) pathways are global structures of the brain defined by local landmarks, which leads to anatomical definitions being difficult to convey, learn, or teach. Moreover, the complex shape of WM pathways and their representation using tractography (streamlines) make the design and evaluation of dissection protocols difficult and time-consuming. The first iteration of Tractostorm quantified the variability of a pyramidal tract dissection protocol and compared results between experts in neuroanatomy and nonexperts. Despite virtual dissection being used for decades, in-depth investigations of how learning or practicing such protocols impact dissection results are nonexistent. To begin to fill the gap, we evaluate an online educational tractography course and investigate the impact learning and practicing a dissection protocol has on interrater (groupwise) reproducibility. To generate the required data to quantify reproducibility across raters and time, 20 independent raters performed dissections of three bundles of interest on five Human Connectome Project subjects, each with four timepoints. Our investigation shows that the dissection protocol in conjunction with an online course achieves a high level of reproducibility (between 0.85 and 0.90 for the voxel-based Dice score) for the three bundles of interest and remains stable over time (repetition of the protocol). Suggesting that once raters are familiar with the software and tasks at hand, their interpretation and execution at the group level do not drastically vary. When compared to previous work that used a different method of communication for the protocol, our results show that incorporating a virtual educational session increased reproducibility. Insights from this work may be used to improve the future design of WM pathway dissection protocols and to further inform neuroanatomical definitions.

Project description:BackgroundDiffusion tensor imaging (DTI) has been applied in the lumbar and sacral nerves in vivo, but information about the reproducibility of this method is needed before DTI can be used reliably in clinical practice across centers.PurposeIn this multicenter study the reproducibility of DTI of the lumbosacral nerves in healthy volunteers was investigated.Study typeProspective control series.SubjectsTwenty healthy subjects.Field strength/sequence3T MRI. 3D turbo spin echo, and 3.0 mm isotropic DTI scan.AssessmentThe DTI scan was performed three times (twice in the same session, intrascan reproducibility, and once after an hour, interscan reproducibility). At site 2, 1 week later, the protocol was repeated (interweek reproducibility). Fiber tractography (FT) of the lumbar and sacral nerves (L3-S2) was performed to obtain values for fractional anisotropy, mean, axial, and radial diffusivity.Statistical testsReproducibility was determined using the intraclass correlation coefficient (ICC), and power calculations were performed.ResultsFT was successful and reproducible in all datasets. ICCs for all diffusion parameters were high for intrascan (ranging from 0.70-0.85), intermediate for interscan (ranging from 0.61-0.73), and interweek reliability (ranging from 0.58-0.62). There were small but significant differences between the interweek diffusivity values (P < 0.0005). Depending on the effect size, nerve location, and parameter of interest, power calculations showed that sample sizes between 10 and 232 subjects are needed for cross-sectional studies.Data conclusionWe found that DTI and FT of the lumbosacral nerves have intermediate to high reproducibility within and between scans. Based on these results, 10-58 subjects are needed to find a 10% change in parameters in cross-sectional studies of the lumbar and sacral nerves. The small significant differences of the interweek comparison suggest that results from longitudinal studies need to be interpreted carefully, since small differences may also be caused by factors other than disease progression or therapeutic effects.Level of evidence1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:951-963.

Project description:Introduction: Tractography analysis in group-based studies across large populations has been difficult to implement. We propose Selective Automated Group Integrated Tractography (SAGIT), an automated group tractography software platform that incorporates multiple diffusion magnetic resonance imaging (dMRI) practices which will allow great accessibility to group-wise dMRI. We use a merged tractography approach that permits evaluation of tractography datasets at the group level. We also introduce an image normalized overlap score (NOS) that measures the quality of the group tractography results. We deploy SAGIT to evaluate deterministic and probabilistic constrained spherical deconvolution (CST det , CST prob ) tractography, eXtended Streamline Tractography (XST), and diffusion tensor tractography (DTT) in their ability to delineate different neuroanatomy, as well as validating NOS across these different brain regions. Materials and methods: Magnetic resonance sequences were acquired from 42 healthy adults. Anatomical and group registrations were performed using Automated Normalization Tools. Cortical segmentation was performed using FreeSurfer. Four tractography algorithms were used to delineate six sets of neuroanatomy: fornix, facial/vestibular-cochlear cranial nerve complex, vagus nerve, rubral-cerebellar decussation, optic radiation, and auditory radiation. The tracts were generated both with and without region of interest filters. The generated visual reports were then evaluated by five neuroscientists. Results: At a group level, merged tractography demonstrated that different methods have different fiber distribution characteristics. CST prob is prone to false-positives, and thereby suitable in anatomy with strong priors. CST det and XST are more conservative, but have greater difficulty resolving hemispherical decussation and distant crossing projections. DTT consistently shows the worst reproducibility across the anatomies. Linear regression of rater scores against NOS shows significant (p < 0.05) correlation of the two sets of scores in filtered tractography. However, correlations are not significant (p > 0.05) for unfiltered tractography. Conclusion: The tractography results demonstrated reliable and consistent performance of SAGIT across multiple subjects and techniques. Through SAGIT, we quantifiably demonstrated that different algorithms showed different strengths and weaknesses at a group level. While no single algorithm seems to be suitable for all anatomical tasks, it is useful to consider the use of a mix of algorithms for different anatomical segments. SAGIT appears to be a promising group-wise tractography analysis approach for this purpose.

Dataset Information

Tractostorm: The what, why, and how of tractography dissection reproducibility.

Publications

Tractostorm: The what, why, and how of tractography dissection reproducibility.

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