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      Evaluating Contextual Processing in Diffusion MRI: Application to Optic Radiation Reconstruction for Epilepsy Surgery

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          Abstract

          Diffusion MRI and tractography allow for investigation of the architectural configuration of white matter in vivo, offering new avenues for applications like presurgical planning. Despite the promising outlook, there are many pitfalls that complicate its use for (clinical) application. Amongst these are inaccuracies in the geometry of the diffusion profiles on which tractography is based, and poor alignment with neighboring profiles. Recently developed contextual processing techniques, including enhancement and well-posed geometric sharpening, have shown to result in sharper and better aligned diffusion profiles. However, the research that has been conducted up to now is mainly of theoretical nature, and so far these techniques have only been evaluated by visual inspection of the diffusion profiles. In this work, the method is evaluated in a clinically relevant application: the reconstruction of the optic radiation for epilepsy surgery. For this evaluation we have developed a framework in which we incorporate a novel scoring procedure for individual pathways. We demonstrate that, using enhancement and sharpening, the extraction of an anatomically plausible reconstruction of the optic radiation from a large amount of probabilistic pathways is greatly improved in three healthy controls, where currently used methods fail to do so. Furthermore, challenging reconstructions of the optic radiation in three epilepsy surgery candidates with extensive brain lesions demonstrate that it is beneficial to integrate these methods in surgical planning.

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          Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution.

          Diffusion-weighted (DW) MR images contain information about the orientation of brain white matter fibres that potentially can be used to study human brain connectivity in vivo using tractography techniques. Currently, the diffusion tensor model is widely used to extract fibre directions from DW-MRI data, but fails in regions containing multiple fibre orientations. The spherical deconvolution technique has recently been proposed to address this limitation. It provides an estimate of the fibre orientation distribution (FOD) by assuming the DW signal measured from any fibre bundle is adequately described by a single response function. However, the deconvolution is ill-conditioned and susceptible to noise contamination. This tends to introduce artefactual negative regions in the FOD, which are clearly physically impossible. In this study, the introduction of a constraint on such negative regions is proposed to improve the conditioning of the spherical deconvolution. This approach is shown to provide FOD estimates that are robust to noise whilst preserving angular resolution. The approach also permits the use of super-resolution, whereby more FOD parameters are estimated than were actually measured, improving the angular resolution of the results. The method provides much better defined fibre orientation estimates, and allows orientations to be resolved that are separated by smaller angles than previously possible. This should allow tractography algorithms to be designed that are able to track reliably through crossing fibre regions.
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            Probabilistic fiber tracking using the residual bootstrap with constrained spherical deconvolution.

            Constrained spherical deconvolution (CSD) is a new technique that, based on high-angular resolution diffusion imaging (HARDI) MR data, estimates the orientation of multiple intravoxel fiber populations within regions of complex white matter architecture, thereby overcoming the limitations of the widely used diffusion tensor imaging (DTI) technique. One of its main applications is fiber tractography. The noisy nature of diffusion-weighted (DW) images, however, affects the estimated orientations and the resulting fiber trajectories will be subject to uncertainty. The impact of noise can be large, especially for HARDI measurements, which employ relatively high b-values. To quantify the effects of noise on fiber trajectories, probabilistic tractography was introduced, which considers multiple possible pathways emanating from one seed point, taking into account the uncertainty of local fiber orientations. In this work, a probabilistic tractography algorithm is presented based on CSD and the residual bootstrap. CSD, which provides accurate and precise estimates of multiple fiber orientations, is used to extract the local fiber orientations. The residual bootstrap is used to estimate fiber tract probability within a clinical time frame, without prior assumptions about the form of uncertainty in the data. By means of Monte Carlo simulations, the performance of the CSD fiber pathway uncertainty estimator is measured in terms of accuracy and precision. In addition, the performance of the proposed method is compared to state-of-the-art DTI residual bootstrap tractography and to an existing probabilistic CSD tractography algorithm using clinical DW data. Copyright © 2010 Wiley-Liss, Inc.
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              Defining Meyer's loop–temporal lobe resections, visual field deficits and diffusion tensor tractography

              Anterior temporal lobe resection is often complicated by superior quadrantic visual field deficits (VFDs). In some cases this can be severe enough to prohibit driving, even if a patient is free of seizures. These deficits are caused by damage to Meyer's loop of the optic radiation, which shows considerable heterogeneity in its anterior extent. This structure cannot be distinguished using clinical magnetic resonance imaging sequences. Diffusion tensor tractography is an advanced magnetic resonance imaging technique that enables the parcellation of white matter. Using seed voxels antero-lateral to the lateral geniculate nucleus, we applied this technique to 20 control subjects, and 21 postoperative patients. All patients had visual fields assessed with Goldmann perimetry at least three months after surgery. We measured the distance from the tip of Meyer's loop to the temporal pole and horn in all subjects. In addition, we measured the size of temporal lobe resection using postoperative T1-weighted images, and quantified VFDs. Nine patients suffered VFDs ranging from 22% to 87% of the contralateral superior quadrant. In patients, the range of distance from the tip of Meyer's loop to the temporal pole was 24–43 mm (mean 34 mm), and the range of distance from the tip of Meyer's loop to the temporal horn was −15 to +9 mm (mean 0 mm). In controls the range of distance from the tip of Meyer's loop to the temporal pole was 24–47 mm (mean 35 mm), and the range of distance from the tip of Meyer's loop to the temporal horn was −11 to +9 mm (mean 0 mm). Both quantitative and qualitative results were in accord with recent dissections of cadaveric brains, and analysis of postoperative VFDs and resection volumes. By applying a linear regression analysis we showed that both distance from the tip of Meyer's loop to the temporal pole and the size of resection were significant predictors of the postoperative VFDs. We conclude that there is considerable variation in the anterior extent of Meyer's loop. In view of this, diffusion tensor tractography of the optic radiation is a potentially useful method to assess an individual patient's risk of postoperative VFDs following anterior temporal lobe resection.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                31 July 2014
                : 9
                : 7
                : e101524
                Affiliations
                [1 ]Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
                [2 ]Department of Biomedical Engineering, Biomedical Image Analysis, Eindhoven University of Technology, Eindhoven, The Netherlands
                [3 ]Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands
                [4 ]Department of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
                [5 ]Department of Function and Medical Technology, Epilepsy Center Kempenhaeghe, Heeze, The Netherlands
                University of Minnesota, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: PO RD AV PH LW CT. Performed the experiments: PO CT. Analyzed the data: PO PH LW CT. Contributed reagents/materials/analysis tools: RD AV BR PH LW AL PO CT. Wrote the paper: CT. Included patients: PO PH LW. Provided funding: RD AL. Critically reviewed manuscript: RD AV BR PH LW AL PO.

                Article
                PONE-D-13-54780
                10.1371/journal.pone.0101524
                4117467
                25077946
                fadd10cb-c219-4c78-a292-731d2587adf7
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 6 January 2014
                : 9 June 2014
                Page count
                Pages: 19
                Funding
                Chantal Tax is supported by a grant (No. 612.001.104) from the Physical Sciences division of the Netherlands Organisation for Scientific Research (NWO). The research leading to the results of this article has received funding from the European Research Council under the European Community's 7th Framework Programme (FP7/2007–2014)/ERC grant agreement No. 335555. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Nervous System
                Neuroanatomy
                Neuroscience
                Neuroimaging
                Engineering and Technology
                Signal Processing
                Image Processing
                Medicine and Health Sciences
                Medical Physics
                Surgical and Invasive Medical Procedures
                Nervous System Procedures
                Neurosurgery
                Physical Sciences
                Mathematics
                Applied Mathematics
                Physics

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