Profilometry: A new statistical framework for the characterization of white matter pathways, with application to multiple sclerosis

Dayan, Michael; Monohan, Elizabeth; Pandya, Sneha; Kuceyeski, Amy; Nguyen, Thanh D.; Raj, Ashish; Gauthier, Susan A.

doi:10.1002/hbm.23082

Cited by 40 publications

(36 citation statements)

References 67 publications

(91 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…52 In its simplest and most widely used form, tractography-defined ROI analysis, metrics are averaged across all voxels covered by a specific tract, [53][54][55][56][57] but more advanced techniques such as profilometry study metrics as a function of arc length along tract-specific exemplar tracks. [58][59][60] 4 | FIBER-TRACKING ALGORITHMS Since its introduction in 1998, 61,62 a multitude of papers introducing new tracking algorithms have been published. It is beyond the scope of this paper to review every published technique.…”

Section: Virtual Dissectionmentioning

confidence: 99%

Diffusion MRI fiber tractography of the brain

et al. 2017

View full text Add to dashboard Cite

The ability of fiber tractography to delineate non-invasively the white matter fiber pathways of the brain raises possibilities for clinical applications and offers enormous potential for neuroscience. In the last decade, fiber tracking has become the method of choice to investigate quantitative MRI parameters in specific bundles of white matter. For neurosurgeons, it is quickly becoming an invaluable tool for the planning of surgery, allowing for visualization and localization of important white matter pathways before and even during surgery. Fiber tracking has also claimed a central role in the field of "connectomics," a technique that builds and studies comprehensive maps of the complex network of connections within the brain, and to which significant resources have been allocated worldwide. Despite its unique abilities and exciting applications, fiber tracking is not without controversy, in particular when it comes to its interpretation. As neuroscientists are eager to study the brain's connectivity, the quantification of tractography-derived "connection strengths" between distant brain regions is becoming increasingly popular. However, this practice is often frowned upon by fiber-tracking experts. In light of this controversy, this paper provides an overview of the key concepts of tractography, the technical considerations at play, and the different types of tractography algorithm, as well as the common misconceptions and mistakes that surround them. We also highlight the ongoing challenges related to fiber tracking. While recent methodological developments have vastly increased the biological accuracy of fiber tractograms, one should be aware that, even with state-of-the-art techniques, many issues that severely bias the resulting structural "connectomes" remain unresolved.

show abstract

Section: Virtual Dissectionmentioning

confidence: 99%

Diffusion MRI fiber tractography of the brain

et al. 2017

View full text Add to dashboard Cite

show abstract

“…It is common to report asymmetry or group difference in bundle volume (Catani et al, 2007;Chenot et al, 2019;Song et al, 2014), diffusion values within the bundle of interest (average fractional anisotropy, mean diffusivity, etc.) (De Erausquin & Alba-Ferrara, 2013;Kimura-Ohba et al, 2016;Ling et al, 2012;Mole et al, 2016) or values along the bundle (called profilometry and tractometry) (Cousineau et al, 2017;Dayan et al, 2016;Yeatman, Dougherty, Myall, Wandell, & Feldman, 2012;Yeatman, Richie-Halford, Smith, Keshavan, & Rokem, 2018). Spatial distribution of cortical terminations of streamlines can help to identify cortical regions with underlying WM connections affected by a condition (Behrens et al, 2003;Donahue et al, 2016;Johansen-Berg et al, 2004;Mars et al, 2011;Rushworth, Behrens, & Johansen-Berg, 2005).…”

Section: Bundle Segmentationmentioning

confidence: 99%

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

Rheault

Benedictis

Daducci

et al. 2020

Human Brain Mapping

View full text Add to dashboard Cite

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.

show abstract

“…Both frameworks have the advantage of providing higher sensitivity to microstructural features of fibre pathways by mapping a set of MR-derived measures over white matter bundles. Recently, along-tract profiling has been successfully applied to study normal brain development (Geeraert et al, 2018) and to characterise areas of the brain with 40 abnormal properties in various brain conditions (Dayan et al, 2016;Cousineau et al, 2017;Groeschel et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Dimensionality Reduction of Diffusion MRI Measures for Improved Tractometry of the Human Brain

Chamberland

Raven

Genc

et al. 2019

Preprint

View full text Add to dashboard Cite

Various diffusion MRI measures have been proposed for characterising tissue microstructure over the last 15 years.Despite the growing number of experiments using different diffusion measures in assessments of white matter, there has been limited work on: 1) examining their covariance along specific pathways; and on 2) combining these different measures to study tissue microstructure. In this work, we first demonstrate redundancies in the amount of information captured by 10 diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI) measures.Using a data-reduction approach, we identified two biologically-interpretable components that capture 80% of the variance in commonly-used DTI and HARDI measures profiled along 22 brain pathways extracted from typically developing children aged 8 -18 years (n = 36). The first derived component captures properties related to hindrance and restriction in tissue microstructure, while the second component reflects characteristics related to tissue complexity and orientational dispersion. We demonstrate that the components generated by this approach preserve the biological relevance of the original measurements by showing age-related effects across developmentally sensitive pathways. Our results also suggest that HARDI measures are more sensitive at detecting age-related changes in tissue microstructure than DTI measures.

show abstract

Profilometry: A new statistical framework for the characterization of white matter pathways, with application to multiple sclerosis

Cited by 40 publications

References 67 publications

Diffusion MRI fiber tractography of the brain

Diffusion MRI fiber tractography of the brain

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

Dimensionality Reduction of Diffusion MRI Measures for Improved Tractometry of the Human Brain

Contact Info

Product

Resources

About