Stability metrics for optic radiation tractography: Towards damage prediction after resective surgery

Meesters, Stephan; Ossenblok, Pauly; Wagner, Louis; Schijns, Olaf; Boon, Paul; Florack, Luc; Vilanova, Anna; Duits, Remco

doi:10.1016/j.jneumeth.2017.05.029

Cited by 15 publications

(17 citation statements)

References 51 publications

(66 reference statements)

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“…Second. Aberrant streamlines, whose trajectory deviates from the bulk of a given projection are eliminated by inspection or by algorithms which tend to preserve the bundling of axons (Côté et al 2015 ; Prieto et al 2016 ; Meesters et al 2017 ). These algorithms also achieve economy of connections.…”

Section: Introductionmentioning

confidence: 99%

Topological principles and developmental algorithms might refine diffusion tractography

et al. 2018

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The identification and reconstruction of axonal pathways in the living brain or “ex-vivo” is promising a revolution in connectivity studies bridging the gap from animal to human neuroanatomy with extensions to brain structural–functional correlates. Unfortunately, the methods suffer from juvenile drawbacks. In this perspective paper we mention several computational and developmental principles, which might stimulate a new generation of algorithms and a discussion bridging the neuroimaging and neuroanatomy communities. Electronic supplementary material The online version of this article (10.1007/s00429-018-1759-1) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Topological principles and developmental algorithms might refine diffusion tractography

et al. 2018

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“…Tractography is an invaluable tool for surgical planning, being the only tool available for neurosurgeons to visualize fibre pathways prior to surgery ( Essayed et al, 2017 ; Nimsky et al, 2016 ) by super-imposing them onto surgical navigation scans. Multiple groups have attempted to model the OR using tractography for surgical planning ( Borius et al, 2014 ; Chen et al, 2009 ; Lilja et al, 2015 ; Meesters et al, 2017 ; Nilsson et al, 2007 ; Nowell et al, 2015 ; Yogarajah et al, 2009 ), suggesting a direct link between the ML-TP distance and VFDs ( Chen et al, 2009 ). A more recent clinical study revealed that patients with VFDs had their Meyer's loop estimates located anterior to the resection margins, whereas in patients without VFDs, the Meyer's loop reconstruction did not reach as far as the resection area ( Winston et al, 2012 ).…”

Section: Discussionmentioning

confidence: 99%

Meyer's loop tractography for image-guided surgery depends on imaging protocol and hardware

Chamberland

Tax

Jones

2018

NeuroImage: Clinical

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IntroductionSurgical resection is an effective treatment for temporal lobe epilepsy but can result in visual field defects. This could be minimized if surgeons knew the exact location of the anterior part of the optic radiation (OR), the Meyer's loop. To this end, there is increasing prevalence of image-guided surgery using diffusion MRI tractography. Despite considerable effort in developing analysis methods, a wide discrepancy in Meyer's loop reconstructions is observed in the literature. Moreover, the impact of differences in image acquisition on Meyer's loop tractography remains unclear. Here, while employing the same state-of-the-art analysis protocol, we explored the extent to which variance in data acquisition leads to variance in OR reconstruction.MethodsDiffusion MRI data were acquired for the same thirteen healthy subjects using standard and state-of-the-art protocols on three scanners with different maximum gradient amplitudes (MGA): Siemens Connectom (MGA = 300 mT/m); Siemens Prisma (MGA = 80 mT/m) and GE Excite-HD (MGA = 40 mT/m). Meyer's loop was reconstructed on all subjects and its distance to the temporal pole (ML-TP) was compared across protocols.ResultsA significant effect of data acquisition on the ML-TP distance was observed between protocols (p < .01 to 0.0001). The biggest inter-acquisition discrepancy for the same subject across different protocols was 16.5 mm (mean: 9.4 mm, range: 3.7–16.5 mm).ConclusionWe showed that variance in data acquisition leads to substantive variance in OR tractography. This has direct implications for neurosurgical planning, where part of the OR is at risk due to an under-estimation of its location using conventional acquisition protocols.

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“…A high diffusivity in particular orientation correlates to biological fibers structure, in brain white matter, along that same direction. Crossing-preserving enhancement of FODF fields U : M → R + helps to better identify structural pathways in brain white matter, which is relevant for surgery planning, see for example [26,28].…”

Section: Tvf and Mcf On R 3 S 2 For Denoising Fodfs In Dw-mrimentioning

confidence: 99%

Total Variation and Mean Curvature PDEs on the Space of Positions and Orientations

Duits

St-Onge²,

Portegies

et al. 2019

Lecture Notes in Computer Science

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Total variation regularization and total variation flows (TVF) have been widely applied for image enhancement and denoising. To include a generic preservation of crossing curvilinear structures in TVF we lift images to the homogeneous space M = R d S d−1 of positions and orientations as a Lie group quotient in SE(d). For d = 2 this is called 'total roto-translation variation' by Chambolle & Pock. We extend this to d = 3, by a PDE-approach with a limiting procedure for which we prove convergence. We also include a Mean Curvature Flow (MCF) in our PDE model on M. This was first proposed for d = 2 by Citti et al. and we extend this to d = 3. Furthermore, for d = 2 we take advantage of locally optimal differential frames in invertible orientation scores (OS). We apply our TVF and MCF in the denoising/enhancement of crossing fiber bundles in DW-MRI. In comparison to data-driven diffusions, we see a better preservation of bundle boundaries and angular sharpness in fiber orientation densities at crossings. We support this by error comparisons on a noisy DW-MRI phantom. We also apply our TVF and MCF in enhancement of crossing elongated structures in 2D images via OS, and compare the results to nonlinear diffusions (CED-OS) via OS.

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Stability metrics for optic radiation tractography: Towards damage prediction after resective surgery

Cited by 15 publications

References 51 publications

Topological principles and developmental algorithms might refine diffusion tractography

Topological principles and developmental algorithms might refine diffusion tractography

Meyer's loop tractography for image-guided surgery depends on imaging protocol and hardware

Total Variation and Mean Curvature PDEs on the Space of Positions and Orientations

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