Diffusion tensor imaging and optimized fiber tracking in glioma patients: Histopathologic evaluation of tumor-invaded white matter structures

Stadlbauer, Andreas; Nimsky, Christopher; Buslei, Rolf; Salomonowitz, Erich; Hammen, T.; Buchfelder, Michael; Moser, Ewald; Ernst-Stecken, Antje; Ganslandt, Oliver

doi:10.1016/j.neuroimage.2006.08.051

Cited by 110 publications

(65 citation statements)

References 37 publications

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“…We could not control for sampling error associated with histologic sampling; with the exception of a few studies that performed stereotactic biopsies, it is possible that some lesions were inappropriately classified. 22 Case reports were excluded. FA and MD values were tabulated as mean values and SDs.…”

Section: Methodsmentioning

confidence: 99%

Meta-Analysis of Diffusion Metrics for the Prediction of Tumor Grade in Gliomas

Miloushev

Chow

Filippi

2014

AJNR Am J Neuroradiol

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Section: Methodsmentioning

confidence: 99%

Meta-Analysis of Diffusion Metrics for the Prediction of Tumor Grade in Gliomas

Miloushev

Chow

Filippi

2014

AJNR Am J Neuroradiol

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“…In a recent work, it was shown that the distance of the reconstructed fiber bundles to the pathological signal change increases with higher FA threshold. 33 We chose a low FA threshold to be sure to reconstruct the fibers also in cases of tumor infiltration and edema. However, in these regions the propagation directions are relatively Fig.…”

Section: Accuracy and Reliability Of Dti Fiber Trackingmentioning

confidence: 99%

“…26,27 Standard thresholds may be too high to enable tracking into areas within or around lesions characterized by a low FA. 3,23,33 Recently, probabilistic fiber tracking algorithms have been introduced that take into account the uncertainty in the diffusion data and quantify tract probabilities over Quantifying accuracy and precision of diffusion MR tractography of the corticospinal tract in brain tumors the distribution of possible orientations. 2,31 Probability density functions (PDFs) are constructed on local fiber trajectories by voxel-wise diffusion modeling that accounts for noise and signal ambiguity.…”

mentioning

confidence: 99%

Quantifying accuracy and precision of diffusion MR tractography of the corticospinal tract in brain tumors

Mandelli¹,

Berger

Bucci³

et al. 2014

JNS

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Object. The aim of this paper was to validate the diffusion tensor imaging (DTI) model for delineation of the corticospinal tract using cortical and subcortical white matter electrical stimulation for the location of functional motor pathways.Methods. The authors compare probabilistic versus deterministic DTI fiber tracking by reconstructing the pyramidal fiber tracts on preoperatively acquired DTI in patients with brain tumors. They determined the accuracy and precision of these 2 methods using subcortical stimulation points and the sensitivity using cortical stimulation points. The authors further explored the reliability of these methods by estimation of the potential that the found connections were due to a random chance using a novel neighborhood permutation method.Results. The probabilistic tracking method delineated tracts that were significantly closer to the stimulation points and was more sensitive than deterministic DTI fiber tracking to define the tracts directed to the motor sites. However, both techniques demonstrated poor sensitivity to finding lateral motor regions.Conclusions. This study highlights the importance of the validation and quantification of preoperative fiber tracking with the aid of electrophysiological data during the surgery. The poor sensitivity of DTI to delineate lateral motor pathways reported herein suggests that DTI fiber tracking must be used with caution and only as adjunctive data to established methods for motor mapping. (http://thejns.org/doi/abs/10.3171/2014.4.JNS131160) key Words • diffusion tensor imaging • tractography • corticospinal tract • intraoperative stimulation • brain tumor • oncologyAbbreviations used in this paper: ANNull = architectural neighborhood null; dMRI = diffusion MRI; DTI = diffusion tensor imaging; FA = fractional anisotropy; FSE = fast spin echo; IES = intraoperative electrical stimulation; PDF = probability density function; ROI = region of interest; SNR = signal-to-noise ratio; SPGR = spoiled gradient recalled.

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“…15, [73][74][75]105,106 However, the reconstruction of subcortical fiber tracts from diffusion tensor vectors is a purely anatomical imaging analysis that does not include true electrophysiological functional data.…”

Section: Technical Detailsmentioning

confidence: 99%

Functional preoperative and intraoperative mapping and monitoring: increasing safety and efficacy in glioma surgery

Ottenhausen¹,

Krieg²,

Meyer³

et al. 2015

FOC

124

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Greater extent of resection (EOR) of low-grade gliomas is associated with improved survival. Proximity to eloquent cortical regions often limits resectability and elevates the risk of surgery-related deficits. Therefore, functional localization of eloquent cortex or subcortical fiber tracts can enhance the EOR and functional outcome. Imaging techniques such as functional MRI and diffusion tensor imaging fiber tracking, and neurophysiological methods like navigated transcranial magnetic stimulation and magnetoencephalography, make it possible to identify eloquent areas prior to resective surgery and to tailor indication and surgical approach but also to assess the surgical risk. Intraoperative monitoring with direct cortical stimulation and subcortical stimulation enables surgeons to preserve essential functional tissue during surgery. Through tailored pre- and intraoperative mapping and monitoring the EOR can be maximized, with reduced rates of surgery-related deficits.

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Diffusion tensor imaging and optimized fiber tracking in glioma patients: Histopathologic evaluation of tumor-invaded white matter structures

Cited by 110 publications

References 37 publications

Meta-Analysis of Diffusion Metrics for the Prediction of Tumor Grade in Gliomas

Meta-Analysis of Diffusion Metrics for the Prediction of Tumor Grade in Gliomas

Quantifying accuracy and precision of diffusion MR tractography of the corticospinal tract in brain tumors

Functional preoperative and intraoperative mapping and monitoring: increasing safety and efficacy in glioma surgery

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