Segmentation of fiber tracts based on an accuracy analysis on diffusion tensor software phantoms

Barbieri, Sebastiano; Bauer, Mathias; Klein, Jan; Nimsky, Christopher; Hahn, Horst K.

doi:10.1016/j.neuroimage.2010.12.069

Cited by 14 publications

(7 citation statements)

References 39 publications

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“…The precision and reliability of tractography results are largely influenced by image quality, parameter settings and even choice of tracking algorithms (Barbieri et al 2011; Feigl et al 2014). Together with the low SNR, this implies that many false positives and false negatives might occur in the tracking process (Jbabdi and Johansen-Berg 2011).…”

Section: Introductionmentioning

confidence: 99%

Dentatorubrothalamic tract localization with postmortem MR diffusion tractography compared to histological 3D reconstruction

et al. 2015

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Diffusion-weighted imaging (DWI) tractography is a technique with great potential to characterize the in vivo anatomical position and integrity of white matter tracts. Tractography, however, remains an estimation of white matter tracts, and false-positive and false-negative rates are not available. The goal of the present study was to compare postmortem tractography of the dentatorubrothalamic tract (DRTT) by its 3D histological reconstruction, to estimate the reliability of the tractography algorithm in this specific tract. Recent studies have shown that the cerebellum is involved in cognitive, language and emotional functions besides its role in motor control. However, the exact working mechanism of the cerebellum is still to be elucidated. As the DRTT is the main output tract it is of special interest for the neuroscience and clinical community. A postmortem human brain specimen was scanned on a 7T MRI scanner using a diffusion-weighted steady-state free precession sequence. Tractography was performed with PROBTRACKX. The specimen was subsequently serially sectioned and stained for myelin using a modified Heidenhain–Woelke staining. Image registration permitted the 3D reconstruction of the histological sections and comparison with MRI. The spatial concordance between the two modalities was evaluated using ROC analysis and a similarity index (SI). ROC curves showed a high sensitivity and specificity in general. Highest measures were observed in the superior cerebellar peduncle with an SI of 0.72. Less overlap was found in the decussation of the DRTT at the level of the mesencephalon. The study demonstrates high spatial accuracy of postmortem probabilistic tractography of the DRTT when compared to a 3D histological reconstruction. This gives hopeful prospect for studying structure–function correlations in patients with cerebellar disorders using tractography of the DRTT.Electronic supplementary materialThe online version of this article (doi:10.1007/s00429-015-1115-7) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Dentatorubrothalamic tract localization with postmortem MR diffusion tractography compared to histological 3D reconstruction

et al. 2015

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“…x(i) is the mixed noise vector reconstructed by combining the original sample o(i) and the noise vector v(i) with probability p v . To evaluate the results, the commonly used objective measures, [16][17][18] such as mean absolute error (MAE) and mean square error (MSE) are utilized to measure closeness between two vector fields. The MAE and MSE are defined as follows:…”

Section: Resultsmentioning

confidence: 99%

A Mixed Gauss and Directional Distance Filter for Fiber Direction Tracking

Yuan

Wang

2014

Int. J. Image Grap.

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Fiber directional tracking through diffusion tensor magnetic resonance imaging (DT-MRI) is a promising research field in visualization and computer graphics and is widely applied in the reconstruction of fiber orientation and the structure of biological tissues. The filter technique used to blur noise in data is of critical importance for fiber directional tracking, particularly because existing tracking methods are very sensitive to impulsive noise. In this paper, a mixed filter of the 3D Gauss and directional distance filter (GDDF) is proposed to suppress noises in corrupted vector fields. Simulation results and objective evaluation of vector datasets demonstrate that GDDF not only possesses the capability of noise attenuation but also preserves vector directions. By validating the simulated vector data against experimental heart data, it is also shown that the GDDF is an effective and stable preprocessing method that accurately reconstructs fiber orientation.

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“…DTI continues to inspire new analyses, developments, refinements and extensions (Caruyer et al, 2013; Hutchinson et al, 2012; Koay, 2009; Koay, 2014; Koay et al, 2011; Koay et al, 2009a; Koay et al, 2012; Koay et al, 2009b; Wu et al, 2004). Uncertainty quantification (Anderson, 2001; Behrens et al, 2003; Beltrachini et al, 2013; Chang et al, 2007; Jeong and Anderson, 2008; Jones, 2003; Jones and Pierpaoli, 2005; Koay et al, 2007; Koay et al, 2008; Lazar and Alexander, 2003, 2005; Lazar et al, 2005; Poonawalla and Zhou, 2004) in DTI is another important area of research with wide-ranging implications to tractography (Barbieri et al, 2011; Basser et al, 2000; Conturo et al, 1999; Mori et al, 1999; Pajevic et al, 2002; Poupon et al, 2000; Poupon et al, 2001) and data analyses (longitudinal, single-subject, group or graph-theoretic, e.g., (Rubinov and Sporns, 2010)).…”

Section: Introductionmentioning

confidence: 99%

Tract Orientation and Angular Dispersion Deviation Indicator (TOADDI): A framework for single-subject analysis in diffusion tensor imaging

et al. 2016

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The purpose of this work is to develop a framework for single-subject analysis of diffusion tensor imaging (DTI) data. This framework is termed Tract Orientation and Angular Dispersion Deviation Indicator (TOADDI) because it is capable of testing whether an individual tract as represented by the major eigenvector of the diffusion tensor and its corresponding angular dispersion are significantly different from a group of tracts on a voxel-by-voxel basis. This work develops two complementary statistical tests based on the elliptical cone of uncertainty, which is a model of uncertainty or dispersion of the major eigenvector of the diffusion tensor. The orientation deviation test examines whether the major eigenvector from a single subject is within the average elliptical cone of uncertainty formed by a collection of elliptical cones of uncertainty. The shape deviation test is based on the two-tailed Wilcoxon-Mann-Whitney two-sample test between the normalized shape measures (area and circumference) of the elliptical cones of uncertainty of the single subject against a group of controls. The False Discovery Rate (FDR) and False Non-discovery Rate (FNR) were incorporated in the orientation deviation test. The shape deviation test uses FDR only. TOADDI was found to be numerically accurate and statistically effective. Clinical data from two Traumatic Brain Injury (TBI) patients and one non-TBI subject were tested against the data obtained from a group of 45 non-TBI controls to illustrate the application of the proposed framework in single-subject analysis. The frontal portion of the superior longitudinal fasciculus seemed to be implicated in both tests (orientation and shape) as significantly different from that of the control group. The TBI patients and the single non-TBI subject were well separated under the shape deviation test at the chosen FDR level of 0.0005. TOADDI is a simple but novel geometrically based statistical framework for analyzing DTI data. TOADDI may be found useful in single-subject, graph-theoretic and group analyses of DTI data or DTI-based tractography techniques.

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Segmentation of fiber tracts based on an accuracy analysis on diffusion tensor software phantoms

Cited by 14 publications

References 39 publications

Dentatorubrothalamic tract localization with postmortem MR diffusion tractography compared to histological 3D reconstruction

Dentatorubrothalamic tract localization with postmortem MR diffusion tractography compared to histological 3D reconstruction

A Mixed Gauss and Directional Distance Filter for Fiber Direction Tracking

Tract Orientation and Angular Dispersion Deviation Indicator (TOADDI): A framework for single-subject analysis in diffusion tensor imaging

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