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Meesters S, Landers M, Rutten GJ, Florack L. Subject-Specific Automatic Reconstruction of White Matter Tracts. J Digit Imaging 2023; 36:2648-2661. [PMID: 37537513 PMCID: PMC10584769 DOI: 10.1007/s10278-023-00883-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 07/05/2023] [Accepted: 07/05/2023] [Indexed: 08/05/2023] Open
Abstract
MRI-based tractography is still underexploited and unsuited for routine use in brain tumor surgery due to heterogeneity of methods and functional-anatomical definitions and above all, the lack of a turn-key system. Standardization of methods is therefore desirable, whereby an objective and reliable approach is a prerequisite before the results of any automated procedure can subsequently be validated and used in neurosurgical practice. In this work, we evaluated these preliminary but necessary steps in healthy volunteers. Specifically, we evaluated the robustness and reliability (i.e., test-retest reproducibility) of tractography results of six clinically relevant white matter tracts by using healthy volunteer data (N = 136) from the Human Connectome Project consortium. A deep learning convolutional network-based approach was used for individualized segmentation of regions of interest, combined with an evidence-based tractography protocol and appropriate post-tractography filtering. Robustness was evaluated by estimating the consistency of tractography probability maps, i.e., averaged tractograms in normalized space, through the use of a hold-out cross-validation approach. No major outliers were found, indicating a high robustness of the tractography results. Reliability was evaluated at the individual level. First by examining the overlap of tractograms that resulted from repeatedly processed identical MRI scans (N = 10, 10 iterations) to establish an upper limit of reliability of the pipeline. Second, by examining the overlap for subjects that were scanned twice at different time points (N = 40). Both analyses indicated high reliability, with the second analysis showing a reliability near the upper limit. The robust and reliable subject-specific generation of white matter tracts in healthy subjects holds promise for future validation of our pipeline in a clinical population and subsequent implementation in brain tumor surgery.
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Affiliation(s)
- Stephan Meesters
- Department of Mathematics & Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands
- Department of Neurosurgery, Elisabeth-Tweesteden Hospital, Tilburg, The Netherlands
| | - Maud Landers
- Department of Neurosurgery, Elisabeth-Tweesteden Hospital, Tilburg, The Netherlands
| | - Geert-Jan Rutten
- Department of Neurosurgery, Elisabeth-Tweesteden Hospital, Tilburg, The Netherlands.
| | - Luc Florack
- Department of Mathematics & Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands
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Radwan AM, Sunaert S, Schilling K, Descoteaux M, Landman BA, Vandenbulcke M, Theys T, Dupont P, Emsell L. An atlas of white matter anatomy, its variability, and reproducibility based on constrained spherical deconvolution of diffusion MRI. Neuroimage 2022; 254:119029. [PMID: 35231632 DOI: 10.1016/j.neuroimage.2022.119029] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 01/19/2022] [Accepted: 02/21/2022] [Indexed: 11/17/2022] Open
Abstract
Virtual dissection of white matter (WM) using diffusion MRI tractography is confounded by its poor reproducibility. Despite the increased adoption of advanced reconstruction models, early region-of-interest driven protocols based on diffusion tensor imaging (DTI) remain the dominant reference for virtual dissection protocols. Here we bridge this gap by providing a comprehensive description of typical WM anatomy reconstructed using a reproducible automated subject-specific parcellation-based approach based on probabilistic constrained-spherical deconvolution (CSD) tractography. We complement this with a WM template in MNI space comprising 68 bundles, including all associated anatomical tract selection labels and associated automated workflows. Additionally, we demonstrate bundle inter- and intra-subject variability using 40 (20 test-retest) datasets from the human connectome project (HCP) and 5 sessions with varying b-values and number of b-shells from the single-subject Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation (MASSIVE) dataset. The most reliably reconstructed bundles were the whole pyramidal tracts, primary corticospinal tracts, whole superior longitudinal fasciculi, frontal, parietal and occipital segments of the corpus callosum and middle cerebellar peduncles. More variability was found in less dense bundles, e.g., the fornix, dentato-rubro-thalamic tract (DRTT), and premotor pyramidal tract. Using the DRTT as an example, we show that this variability can be reduced by using a higher number of seeding attempts. Overall inter-session similarity was high for HCP test-retest data (median weighted-dice = 0.963, stdev = 0.201 and IQR = 0.099). Compared to the HCP-template bundles there was a high level of agreement for the HCP test-retest data (median weighted-dice = 0.747, stdev = 0.220 and IQR = 0.277) and for the MASSIVE data (median weighted-dice = 0.767, stdev = 0.255 and IQR = 0.338). In summary, this WM atlas provides an overview of the capabilities and limitations of automated subject-specific probabilistic CSD tractography for mapping white matter fasciculi in healthy adults. It will be most useful in applications requiring a reproducible parcellation-based dissection protocol, and as an educational resource for applied neuroimaging and clinical professionals.
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Affiliation(s)
- Ahmed M Radwan
- KU Leuven, Department of Imaging and pathology, Translational MRI, Leuven, Belgium; KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium.
| | - Stefan Sunaert
- KU Leuven, Department of Imaging and pathology, Translational MRI, Leuven, Belgium; KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium; UZ Leuven, Department of Radiology, Leuven, Belgium
| | - Kurt Schilling
- Vanderbilt University Medical Center, Department of Radiology and Radiological Sciences, Nashville, TN, USA
| | | | - Bennett A Landman
- Vanderbilt University, Department of Electrical Engineering and Computer Engineering, Nashville, TN, USA
| | - Mathieu Vandenbulcke
- KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium; KU Leuven, Department of Neurosciences, Neuropsychiatry, Leuven, Belgium; KU Leuven, Department of Geriatric Psychiatry, University Psychiatric Center (UPC), Leuven, Belgium
| | - Tom Theys
- KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium; KU Leuven, Department of Neurosciences, Research Group Experimental Neurosurgery and Neuroanatomy, Leuven, Belgium; UZ Leuven, Department of Neurosurgery, Leuven, Belgium
| | - Patrick Dupont
- KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium; KU Leuven, Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven, Belgium
| | - Louise Emsell
- KU Leuven, Department of Imaging and pathology, Translational MRI, Leuven, Belgium; KU Leuven, Leuven Brain Institute (LBI), Department of Neurosciences, Leuven, Belgium; KU Leuven, Department of Neurosciences, Neuropsychiatry, Leuven, Belgium; KU Leuven, Department of Geriatric Psychiatry, University Psychiatric Center (UPC), Leuven, Belgium
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Reid LB, Martínez‐Heras E, Manjón JV, Jeffree RL, Alexander H, Trinder J, Solana E, Llufriu S, Rose S, Prior M, Fripp J. Fully automated delineation of the optic radiation for surgical planning using clinically feasible sequences. Hum Brain Mapp 2021; 42:5911-5926. [PMID: 34547147 PMCID: PMC8596983 DOI: 10.1002/hbm.25658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 07/21/2021] [Accepted: 08/23/2021] [Indexed: 11/30/2022] Open
Abstract
Quadrantanopia caused by inadvertent severing of Meyer's Loop of the optic radiation is a well-recognised complication of temporal lobectomy for conditions such as epilepsy. Dissection studies indicate that the anterior extent of Meyer's Loop varies considerably between individuals. Quantifying this for individual patients is thus an important step to improve the safety profile of temporal lobectomies. Previous attempts to delineate Meyer's Loop using diffusion MRI tractography have had difficulty estimating its full anterior extent, required manual ROI placement, and/or relied on advanced diffusion sequences that cannot be acquired routinely in most clinics. Here we present CONSULT: a pipeline that can delineate the optic radiation from raw DICOM data in a completely automated way via a combination of robust pre-processing, segmentation, and alignment stages, plus simple improvements that bolster the efficiency and reliability of standard tractography. We tested CONSULT on 696 scans of predominantly healthy participants (539 unique brains), including both advanced acquisitions and simpler acquisitions that could be acquired in clinically acceptable timeframes. Delineations completed without error in 99.4% of the scans. The distance between Meyer's Loop and the temporal pole closely matched both averages and ranges reported in dissection studies for all tested sequences. Median scan-rescan error of this distance was 1 mm. When tested on two participants with considerable pathology, delineations were successful and realistic. Through this, we demonstrate not only how to identify Meyer's Loop with clinically feasible sequences, but also that this can be achieved without fundamental changes to tractography algorithms or complex post-processing methods.
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Affiliation(s)
- Lee B. Reid
- The Australian e‐Health Research CentreCSIROBrisbaneQueenslandAustralia
| | - Eloy Martínez‐Heras
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic BarcelonaInstitut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS) and Universitat de BarcelonaBarcelonaSpain
| | - Jose V. Manjón
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de ValènciaValenciaSpain
| | - Rosalind L. Jeffree
- Royal Brisbane and Women's HospitalMetro NorthQueenslandAustralia
- School of Clinical MedicineUniversity of QueenslandHerstonQueenslandAustralia
| | - Hamish Alexander
- Royal Brisbane and Women's HospitalMetro NorthQueenslandAustralia
| | - Julie Trinder
- The Australian e‐Health Research CentreCSIROBrisbaneQueenslandAustralia
| | - Elisabeth Solana
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic BarcelonaInstitut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS) and Universitat de BarcelonaBarcelonaSpain
| | - Sara Llufriu
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic BarcelonaInstitut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS) and Universitat de BarcelonaBarcelonaSpain
| | - Stephen Rose
- The Australian e‐Health Research CentreCSIROBrisbaneQueenslandAustralia
| | - Marita Prior
- Royal Brisbane and Women's HospitalMetro NorthQueenslandAustralia
| | - Jurgen Fripp
- The Australian e‐Health Research CentreCSIROBrisbaneQueenslandAustralia
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Fourier Transform on the Homogeneous Space of 3D Positions and Orientations for Exact Solutions to Linear PDEs. ENTROPY 2019; 21:e21010038. [PMID: 33266754 PMCID: PMC7514144 DOI: 10.3390/e21010038] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 12/10/2018] [Accepted: 12/18/2018] [Indexed: 11/16/2022]
Abstract
Fokker–Planck PDEs (including diffusions) for stable Lévy processes (including Wiener processes) on the joint space of positions and orientations play a major role in mechanics, robotics, image analysis, directional statistics and probability theory. Exact analytic designs and solutions are known in the 2D case, where they have been obtained using Fourier transform on SE(2). Here, we extend these approaches to 3D using Fourier transform on the Lie group SE(3) of rigid body motions. More precisely, we define the homogeneous space of 3D positions and orientations R3⋊S2:=SE(3)/({0}×SO(2)) as the quotient in SE(3). In our construction, two group elements are equivalent if they are equal up to a rotation around the reference axis. On this quotient, we design a specific Fourier transform. We apply this Fourier transform to derive new exact solutions to Fokker–Planck PDEs of α-stable Lévy processes on R3⋊S2. This reduces classical analysis computations and provides an explicit algebraic spectral decomposition of the solutions. We compare the exact probability kernel for α=1 (the diffusion kernel) to the kernel for α=12 (the Poisson kernel). We set up stochastic differential equations (SDEs) for the Lévy processes on the quotient and derive corresponding Monte-Carlo methods. We verified that the exact probability kernels arise as the limit of the Monte-Carlo approximations.
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Innocenti GM, Dyrby TB, Girard G, St-Onge E, Thiran JP, Daducci A, Descoteaux M. Topological principles and developmental algorithms might refine diffusion tractography. Brain Struct Funct 2018; 224:1-8. [PMID: 30264235 PMCID: PMC6373358 DOI: 10.1007/s00429-018-1759-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Accepted: 09/20/2018] [Indexed: 01/09/2023]
Abstract
The identification and reconstruction of axonal pathways in the living brain or "ex-vivo" is promising a revolution in connectivity studies bridging the gap from animal to human neuroanatomy with extensions to brain structural-functional correlates. Unfortunately, the methods suffer from juvenile drawbacks. In this perspective paper we mention several computational and developmental principles, which might stimulate a new generation of algorithms and a discussion bridging the neuroimaging and neuroanatomy communities.
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Affiliation(s)
- Giorgio M Innocenti
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden. .,Brain and Mind Institute, Ecole Polytechnique Féderale de Lausanne EPFL, Lausanne, Switzerland. .,Signal Processing Laboratory (LT55) Ecole Polytechnique Féderale de Lausanne (EPFL-STI-IEL-LT55), Station 11, 1015, Lausanne, Switzerland.
| | - Tim B Dyrby
- Danish Research Centre for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.,Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens, Lyngby, Denmark
| | - Gabriel Girard
- Signal Processing Laboratory (LT55) Ecole Polytechnique Féderale de Lausanne (EPFL-STI-IEL-LT55), Station 11, 1015, Lausanne, Switzerland
| | - Etienne St-Onge
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Computer Science Department, Faculty of Science, Université de Sherbrooke, Quebec, Canada
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LT55) Ecole Polytechnique Féderale de Lausanne (EPFL-STI-IEL-LT55), Station 11, 1015, Lausanne, Switzerland.,Department of Radiology, University Hospital Center (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
| | | | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Computer Science Department, Faculty of Science, Université de Sherbrooke, Quebec, Canada.,Department of Nuclear Medicine and Radiobiology, Sherbrooke Molecular Imaging Center, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrook, Canada
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Chamberland M, Tax CMW, Jones DK. Meyer's loop tractography for image-guided surgery depends on imaging protocol and hardware. Neuroimage Clin 2018; 20:458-465. [PMID: 30128284 PMCID: PMC6096050 DOI: 10.1016/j.nicl.2018.08.021] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Revised: 07/31/2018] [Accepted: 08/10/2018] [Indexed: 12/19/2022]
Abstract
Introduction Surgical resection is an effective treatment for temporal lobe epilepsy but can result in visual field defects. This could be minimized if surgeons knew the exact location of the anterior part of the optic radiation (OR), the Meyer's loop. To this end, there is increasing prevalence of image-guided surgery using diffusion MRI tractography. Despite considerable effort in developing analysis methods, a wide discrepancy in Meyer's loop reconstructions is observed in the literature. Moreover, the impact of differences in image acquisition on Meyer's loop tractography remains unclear. Here, while employing the same state-of-the-art analysis protocol, we explored the extent to which variance in data acquisition leads to variance in OR reconstruction. Methods Diffusion MRI data were acquired for the same thirteen healthy subjects using standard and state-of-the-art protocols on three scanners with different maximum gradient amplitudes (MGA): Siemens Connectom (MGA = 300 mT/m); Siemens Prisma (MGA = 80 mT/m) and GE Excite-HD (MGA = 40 mT/m). Meyer's loop was reconstructed on all subjects and its distance to the temporal pole (ML-TP) was compared across protocols. Results A significant effect of data acquisition on the ML-TP distance was observed between protocols (p < .01 to 0.0001). The biggest inter-acquisition discrepancy for the same subject across different protocols was 16.5 mm (mean: 9.4 mm, range: 3.7-16.5 mm). Conclusion We showed that variance in data acquisition leads to substantive variance in OR tractography. This has direct implications for neurosurgical planning, where part of the OR is at risk due to an under-estimation of its location using conventional acquisition protocols.
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Affiliation(s)
- Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom; School of Psychology, Faculty of Health Sciences, Australian Catholic University, Victoria, Australia
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