scholarly journals Structural connectome with high angular resolution diffusion imaging MRI: assessing the impact of diffusion weighting and sampling on graph-theoretic measures

2018 ◽  
Vol 60 (5) ◽  
pp. 497-504 ◽  
Author(s):  
Giuseppina Caiazzo ◽  
Michele Fratello ◽  
Federica Di Nardo ◽  
Francesca Trojsi ◽  
Gioacchino Tedeschi ◽  
...  
2017 ◽  
Vol 19 (5) ◽  
pp. 592-605 ◽  
Author(s):  
Joseph Yuan-Mou Yang ◽  
Richard Beare ◽  
Marc L. Seal ◽  
A. Simon Harvey ◽  
Vicki A. Anderson ◽  
...  

OBJECTIVECharacterization of intraoperative white matter tract (WMT) shift has the potential to compensate for neuronavigation inaccuracies using preoperative brain imaging. This study aimed to quantify and characterize intraoperative WMT shift from the global hemispheric to the regional tract-based scale and to investigate the impact of intraoperative factors (IOFs).METHODSHigh angular resolution diffusion imaging (HARDI) diffusion-weighted data were acquired over 5 consecutive perioperative time points (MR1 to MR5) in 16 epilepsy patients (8 male; mean age 9.8 years, range 3.8–15.8 years) using diagnostic and intraoperative 3-T MRI scanners. MR1 was the preoperative planning scan. MR2 was the first intraoperative scan acquired with the patient's head fixed in the surgical position. MR3 was the second intraoperative scan acquired following craniotomy and durotomy, prior to lesion resection. MR4 was the last intraoperative scan acquired following lesion resection, prior to wound closure. MR5 was a postoperative scan acquired at the 3-month follow-up visit. Ten association WMT/WMT segments and 1 projection WMT were generated via a probabilistic tractography algorithm from each MRI scan. Image registration was performed through pairwise MRI alignments using the skull segmentation. The MR1 and MR2 pairing represented the first surgical stage. The MR2 and MR3 pairing represented the second surgical stage. The MR3 and MR4 (or MR5) pairing represented the third surgical stage. The WMT shift was quantified by measuring displacements between a pair of WMT centerlines. Linear mixed-effects regression analyses were carried out for 6 IOFs: head rotation, craniotomy size, durotomy size, resected lesion volume, presence of brain edema, and CSF loss via ventricular penetration.RESULTSThe average WMT shift in the operative hemisphere was 2.37 mm (range 1.92–3.03 mm) during the first surgical stage, 2.19 mm (range 1.90–3.65 mm) during the second surgical stage, and 2.92 mm (range 2.19–4.32 mm) during the third surgical stage. Greater WMT shift occurred in the operative than the nonoperative hemisphere, in the WMTs adjacent to the surgical lesion rather than those remote to it, and in the superficial rather than the deep segment of the pyramidal tract. Durotomy size and resection size were significant, independent IOFs affecting WMT shift. The presence of brain edema was a marginally significant IOF. Craniotomy size, degree of head rotation, and ventricular penetration were not significant IOFs affecting WMT shift.CONCLUSIONSWMT shift occurs noticeably in tracts adjacent to the surgical lesions, and those motor tracts superficially placed in the operative hemisphere. Intraoperative probabilistic HARDI tractography following craniotomy, durotomy, and lesion resection may compensate for intraoperative WMT shift and improve neuronavigation accuracy.


2005 ◽  
Vol 54 (6) ◽  
pp. 1480-1489 ◽  
Author(s):  
Tim Hosey ◽  
Guy Williams ◽  
Richard Ansorge

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Adelino R. Ferreira da Silva

We present a new methodology based on directional data clustering to represent white matter fiber orientations in magnetic resonance analyses for high angular resolution diffusion imaging. A probabilistic methodology is proposed for estimating intravoxel principal fiber directions, based on clustering directional data arising from orientation distribution function (ODF) profiles. ODF reconstructions are used to estimate intravoxel fiber directions using mixtures of von Mises-Fisher distributions. The method focuses on clustering data on the unit sphere, where complexity arises from representing ODF profiles as directional data. The proposed method is validated on synthetic simulations, as well as on a real data experiment. Based on experiments, we show that by clustering profile data using mixtures of von Mises-Fisher distributions it is possible to estimate multiple fiber configurations in a more robust manner than currently used approaches, without recourse to regularization or sharpening procedures. The method holds promise to support robust tractographic methodologies and to build realistic models of white matter tracts in the human brain.


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