White matter fiber tracking in patients with space-occupying lesions of the brain: a new technique for neurosurgical planning?

doi:10.1016/j.neuroimage.2003.07.022

NeuroImage

Volume 20, Issue 3, November 2003, Pages 1601-1608

https://doi.org/10.1016/j.neuroimage.2003.07.022 Get rights and content

Abstract

The technique of fiber tracking based on diffusion tensor imaging offers the unique possibility of localizing the white matter pathways of the brain in vivo. In patients with cerebral tumors or space-occupying lesions of the brain, these pathways are often damaged or significantly displaced. Knowledge of the exact location of the lesion with respect to clinically eloquent white matter pathways is of great value to the neurosurgeon in planning the appropriate surgical strategy. We present here preliminary findings using the fiber tracking technique in four patients with space-occupying lesions and discuss the potential and limitations of the technique for lesion localization and neurosurgical planning.

Introduction

A significant proportion of brain tumors and space-occupying lesions originate within and propagate throughout the white matter of the brain. Magnetic resonance imaging (MRI) of the brain is the method of choice for characterization and determination of lesion anatomical location. Conventional MRI techniques typically used for radiological assessment and localization include T2-weighted, contrast-enhanced T1-weighted and FLAIR imaging (Gillespie and Jackson, 2000). This imaging information is then used to determine the appropriate course of therapy and is often used for neurosurgical planning if lesion resection is required.

A major disadvantage of current MRI methods is that they provide little information about the integrity and location of white matter tracts in the brain. Functional MRI or direct stimulation of the cortex can be used to localize important cortical areas for neurosurgical planning Mueller et al., 1996, Roux et al., 1999. However, these techniques provide limited information concerning the status of the white matter structures, particularly those in deep white matter. Knowledge of the structural integrity and location of white matter tracts is crucial, however, as damage to clinically eloquent pathways during surgery can have devastating consequences for the patient. Informed assessment of the structural integrity and orientation of white matter pathways that may be involved or affected by a lesion may facilitate their exclusion from the resection volume leading to improved outcomes.

Diffusion tensor imaging (DTI) is a magnetic resonance technique that is sensitive to the diffusion of water in brain tissue (Basser et al., 1994). Specifically, spatial characteristics of the diffusion displacements reveal the anisotropy and orientation of white matter tracts in the brain (Pierpaoli et al., 1996). This orientation information can then be used to delineate white matter pathways of the brain by employing so-called fiber tracking algorithms which compare local tensor field orientations from voxel to voxel Basser et al., 2000, Mori et al., 1999, Jones et al., 1999, Poupon et al., 2000, Conturo et al., 1999.

Fiber tracking using DTI has generated a great deal of interest because it offers the only method for tracking the white matter pathways of the brain in vivo. The technique has hitherto been largely restricted to studies of the healthy human brain and has provided demonstrations of white matter tract structures that compare favorably with long established atlases of brain anatomy (Catani et al., 2002).

Previous investigations in patients with space-occupying lesions have employed diffusion-weighted imaging to highlight cortico-spinal tract trajectory (Coenen et al., 2001), DTI to demonstrate local abnormalities in tract orientation Wieshmann et al., 2000, Witwer et al., 2002, and more recently fiber tracking to illustrate displacement of cortico-spinal tract, superior longitudinal fasciculus, and corona radiata Mori et al., 2002, Holodny et al., 2001.

In this study we have applied in vivo fiber tracking to investigate white matter tract orientation in four patients with space-occupying lesions of the brain. In so doing we have set out to investigate the potential of fiber tracking for neurosurgical planning. Distortion of frontal white matter, corpus callosum, and cortico-spinal tracts is demonstrated. It is also shown that coherent fiber tracking pathways can be produced within the lesion volume indicated on T2-weighted MRI, suggesting that diffusion tensor fiber tracking may also serve as a technique for detecting intact axonal pathways within the lesion volume which could potentially be resected in surgery. Current limitations of the technique and suggested directions for further developments are discussed.

Section snippets

MRI data acquisition

Preoperative imaging was performed on a 1.5-T General Electric Signa MRI system with a maximum field gradient strength of 22 mT m⁻¹. A quadrature head coil was used for transmission and reception of the NMR signal. DTI data were obtained using a single-shot echo planar imaging (EPI) sequence with diffusion sensitizing gradients positioned either side of the 180° refocusing pulse. The degree of diffusion weighting (b value) was set to 1000 s mm⁻². Following an acquisition without diffusion

Patient 1

The fiber tracking results indicated disruption of the superior longitudinal fasciculus (SLF) by the suspected glioma. Tracking of the SLF was generated from a single seed ROI defined from a coronal FA map. The FA threshold was set to 0.01, angular threshold to 18°, and vector step length to 0.7 mm. The tracking results are illustrated in Fig. 1. The tracking indicates that the SLF is displaced superiorly and is disrupted in the tumor region. Tracking also revealed that disruption of the SLF

Discussion

This study demonstrates that fiber tracking techniques can be used to reveal the trajectories of white matter pathways in patients with space-occupying lesions. The results described here complement those of Mori et al. (2002), who used the FACT fiber tracking algorithm (Mori et al., 1999) in two patients with anaplastic astrocytoma. In one of the cases studied, displacement of the corona radiata and SLF was demonstrated.

In the present study fiber tracking indicated a disruption and

References (30)

P.J. Basser et al.
Microstructural and physiological features of tissues elucidated by quantitative diffusion tensor MRI
J. Magn. Reson. Ser. B.
(1996)
M. Catani et al.
Virtual in vivo interactive dissection of white matter fasciculi in the human brain
NeuroImage
(2002)
C. Gossl et al.
Fiber tracking from DTI using linear state space modelsdetectability of the pyramidal tract
NeuroImage
(2002)
C. Poupon et al.
Regularization of diffusion based direction maps for the tracking of brain white matter fascicles
NeuroImage
(2000)
D.C. Alexander et al.
Detection and modelling of non-gaussian apparent diffusion coefficient profiles in human brain data
Magn. Reson. Med.
(2002)
D.C. Alexander et al.
Spatial transformations of diffusion tensor magnetic resonance images
IEEE Trans. Med. Imag.
(2001)
Barrick T.R, Clark C.A., 2002. Resolving fibre crossing using the diffusion tensor model. The International Society of...
P.J. Basser et al.
Estimation of the effective self-diffusion tensor from the NMR spin echo
J. Magn. Reson. Ser. B.
(1994)
P.J. Basser et al.
In vivo fiber tractography using DT-MRI data
Magn. Reson. Med.
(2000)
V.A. Coenen et al.
Three-dimensional visualization of the pyramidal tract in a neuronavigation system during brain tumor surgeryfirst experiences and technical note
Neurosurgery
(2001)

T.E. Conturo et al.

Tracking neuronal fiber pathways in the living human brain

Proc. Natl. Acad. Sci. USA

(1999)

L.R. Frank

Characterisation of anisotropy in high angular resolution diffusion-weighted MRI

Magn. Reson. Med.

(2002)

Gillespie, J.E., Jackson, A., 2000. MRI and CT of the Brain, Arnold,...

J.C. Haselgrove et al.

Correction for distortion of echo-planar images used to calculate the apparent diffusion coefficient

Magn. Reson. Med.

(1996)

A.I. Holodny et al.

Identification of the cortico-spinal tracts achieved using blood-oxygen-level-dependent and diffusion functional MR imaging in patients with brain tumours

Am. J. Neuroradiol.

(2001)

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Diffusion MRI is a valuable tool for probing tissue microstructure in the brain noninvasively. Today, model-based techniques are widely available and used for white matter characterisation where their development is relatively mature. Conversely, tissue modelling in grey matter is more challenging, and no generally accepted models exist. With advances in measurement technology and modelling efforts, a clinically viable technique that reveals salient features of grey matter microstructure, such as the density of quasi-spherical cell bodies and quasi-cylindrical cell projections, is an exciting prospect. As a step towards capturing the microscopic architecture of grey matter in clinically feasible settings, this work uses a biophysical model that is designed to disentangle the diffusion signatures of spherical and cylindrical structures in the presence of orientation heterogeneity, and takes advantage of B-tensor encoding measurements, which provide additional sensitivity compared to standard single diffusion encoding sequences. For the fast and robust estimation of microstructural parameters, we leverage recent advances in machine learning and replace conventional fitting techniques with an artificial neural network that fits complex biophysical models within seconds. Our results demonstrate apparent markers of spherical and cylindrical geometries in healthy human subjects, and in particular an increased volume fraction of spherical compartments in grey matter compared to white matter. We evaluate the extent to which spherical and cylindrical geometries may be interpreted as correlates of neural soma and neural projections, respectively, and quantify parameter estimation errors in the presence of various departures from the modelling assumptions. While further work is necessary to translate the ideas presented in this work to the clinic, we suggest that biomarkers focussing on quasi-spherical cellular geometries may be valuable for the enhanced assessment of neurodevelopmental disorders and neurodegenerative diseases.
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Citation Excerpt :
The popular tractography or fiber-tracing algorithms include deterministic tractography (Descoteaux et al., 2009; Lazar et al., 2003; Lenglet et al., 2009; Mori and Zijl, 2002; Tournier et al., 2012), probabilistic tractography (Anwander et al., 2007; Behrens et al., 2003; Kaden et al., 2007; Koch et al., 2002) and global tractography (Jbabdi et al., 2007; Kreher et al., 2008). The above tractography methods have been used in the neuro-scientific investigations and clinical applications, such as the study of white matter connectivity (Anwander et al., 2007; Johansen-Berg and Rushworth, 2009; Kaden et al., 2007; Koch et al., 2002; Turken and Dronkers, 2011) and the research in the neurosurgery (Bello et al., 2008; Chen et al., 2009; Clark et al., 2003; Kinoshita et al., 2005; Reinges et al., 2004). Until now, diffusion tensor imaging (DTI) is a common dMRI method for fiber tracking, which is based on the Gaussian assumption and describes diffusion by a second-order tensor (Basser et al., 1994; Le Bihan et al., 2001; Mori and Zhang, 2006).
Diffusion magnetic resonance imaging (dMRI) is a popular non-invasive imaging technique applied for the study of nerve fibers in vivo, with diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI) as the commonly used dMRI methods. However, DTI cannot resolve complex fiber orientations in a local area and HARDI lacks a solid physical basis.
We introduce a diffusion coefficient orientation distribution function (DCODF). It has a clear physical meaning to represent the orientation distribution of diffusion coefficients for Gaussian and non-Gaussian diffusion. Based on DCODF, we then propose a new HARDI method, termed as diffusion coefficient orientation distribution transform (DCODT), to estimate the orientation distribution of nerve fibers in voxels.
The method is verified on the simulated data, ISMRM-2015-Tracto-challenge data, and HCP datasets. The results show the superior capability of DCODT in resolving the complex distribution of multiple fiber bundles effectively.
The method is compared to other common model-free HARDI estimators. In the numerical simulations, DCODT achieves a better trade-off between the resolution and accuracy than the counterparts for high b-values. In the comparisons based on the challenge data, the improvement of DCODT is significant in scoring. The results on the HCP datasets show that DCODT provides fewer spurious lobes in the glyphs, resulting in more coherent fiber orientations.
We conclude that DCODT may be a reliable method to extract accurate information about fiber orientations from dMRI data and promising for the study of neural architecture.
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We investigated the added value of combining information from direction-encoded color (DEC) maps with high-resolution structural magnetic resonance imaging scans (T1-weighted images [T1WIs]) to improve the identification of regions of interest (ROIs) for fiber tracking during preoperative planning for patients with brain tumors.
The dataset included 42 patients with gliomas and 10 healthy subjects from the Human Connectome Project. For identification of the ROIs, we combined the structural information from high-resolution T1WIs and the directional information from DEC maps. To test our hypothesis, we examined the interrater and intrarater agreement.
We identified specific ROIs to extract the main white matter bundles. The directional information from the DEC maps combined with the T1WIs (T1WI–DEC maps) had significantly facilitated ROI identification in patients with brain tumors, especially patients in whom the tracts had been displaced by the mass effect of the tumor. Fiber tracking using the combined T1WI–DEC maps showed significantly greater inter- and intrarater agreement compared with using either T1WI or DEC maps alone.
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It is commonly known that brain metastases usually have clear boundaries in magnetic resonance imaging. However, little is known regarding the trajectory of white matter fibers around the tumors, especially using the fiber dissection technique. Here, we focused on the anatomical interaction between white matter fibers and the tumor, using the fiber dissection in a postmortem brain with metastatic tumor and compared the findings with those of diffusion tensor imaging (DTI) tractography. One postmortem human brain hemisphere with metastatic adenocarcinoma in the Broca’s area was dissected using fiber dissection following the Klingler’s method. In order to compare the in vitro and in vivo results, additional brains from 15 patients with metastatic adenocarcinomas, the volumes of which were comparable to that of the adenocarcinoma in the brain used for fiber dissection, were analyzed using DTI tractographic reconstruction. Morphological findings of white matter bundles running around the tumor were compared between the two techniques. In the fiber dissection technique, the superior longitudinal fascicle, arcuate fascicle, and frontal aslant tract could be dissected, and the white matter bundles were curved and retracted to avoid the tumor. In all the cases analyzed, white matter fibers or streamlines surrounding the tumor avoided the lesion. Using the fiber dissection technique, this is the first direct evidence to elucidate the anatomy of white matter fibers affected by a metastatic brain. This suggests that brain metastatic adenocarcinoma is an intra-axial neoplasm with extra-axial white matter structures.
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Diffusion tensor imaging (DTI) based on echo-planar imaging (EPI) can suffer from geometric image distortions in comparison to conventional anatomical magnetic resonance imaging (MRI). Therefore, DTI-derived information, such as fiber tractography (FT) used for treatment planning of brain tumors, might be associated with spatial inaccuracies when linearly projected on anatomical MRI. Hence, a non-linear, semi-elastic image fusion shall be evaluated in this study that aims at correcting for image distortions in DTI.
In a sample of 27 patient datasets, 614 anatomical landmark pairs were retrospectively defined in DTI and T1- or T2-weighted three-dimensional (3D) MRI data. The datasets were processed by a commercial software package (Elements Image Fusion .0; Brainlab AG, Munich, Germany) providing rigid and semi-elastic fusion functionalities, such as DTI distortion correction. To quantify the displacement prior to and after semi-elastic fusion, the Euclidian distances of rigidly and elastically fused landmarks were evaluated by means of descriptive statistics and Bland-Altman plot.
For rigid and semi-elastic fusion mean target registration errors of 3.03 ± 2.29 mm and 2.04 ± 1.95 mm were found, respectively, with 91% of the evaluated landmarks moving closer to their position determined in T1- or T2-weighted 3D MRI data after distortion correction. Most efficient correction was achieved for non-superficial landmarks showing distortions up to 1 cm.
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Regular articleWhite matter fiber tracking in patients with space-occupying lesions of the brain: a new technique for neurosurgical planning?

Abstract

Introduction

Section snippets

MRI data acquisition

Patient 1

Discussion

J. Magn. Reson. Ser. B.

NeuroImage

NeuroImage

NeuroImage

Detection and modelling of non-gaussian apparent diffusion coefficient profiles in human brain data

Magn. Reson. Med.

Spatial transformations of diffusion tensor magnetic resonance images

IEEE Trans. Med. Imag.

Estimation of the effective self-diffusion tensor from the NMR spin echo

J. Magn. Reson. Ser. B.

In vivo fiber tractography using DT-MRI data

Magn. Reson. Med.

Three-dimensional visualization of the pyramidal tract in a neuronavigation system during brain tumor surgeryfirst experiences and technical note

Neurosurgery

Tracking neuronal fiber pathways in the living human brain

Proc. Natl. Acad. Sci. USA

Characterisation of anisotropy in high angular resolution diffusion-weighted MRI

Magn. Reson. Med.

Correction for distortion of echo-planar images used to calculate the apparent diffusion coefficient

Magn. Reson. Med.

Identification of the cortico-spinal tracts achieved using blood-oxygen-level-dependent and diffusion functional MR imaging in patients with brain tumours

Am. J. Neuroradiol.

Regular article
White matter fiber tracking in patients with space-occupying lesions of the brain: a new technique for neurosurgical planning?