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He Y, Hong Y, Wu Y. Spherical-deconvolution informed filtering of tractograms changes laterality of structural connectome. Neuroimage 2024; 303:120904. [PMID: 39476882 DOI: 10.1016/j.neuroimage.2024.120904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2024] [Revised: 10/22/2024] [Accepted: 10/23/2024] [Indexed: 11/15/2024] Open
Abstract
Diffusion MRI-driven tractography, a non-invasive technique that reveals how the brain is connected, is widely used in brain lateralization studies. To improve the accuracy of tractography in showing the underlying anatomy of the brain, various tractography filtering methods were applied to reduce false positives. Based on different algorithms, tractography filtering methods are able to identify the fibers most consistent with the original diffusion data while removing fibers that do not align with the original signals, ensuring the tractograms are as biologically accurate as possible. However, the impact of tractography filtering on the lateralization of the brain connectome remains unclear. This study aims to investigate the relationship between fiber filtering and laterality changes in brain structural connectivity. Three typical tracking algorithms were used to construct the raw tractography, and two popular fiber filtering methods(SIFT and SIFT2) were employed to filter the tractography across a range of parameters. Laterality indices were computed for six popular biological features, including four microstructural measures (AD, FA, RD, and T1/T2 ratio) and two structural features (fiber length and connectivity) for each brain region. The results revealed that tractography filtering may cause significant laterality changes in more than 10% of connections, up to 25% for probabilistic tracking, and deterministic tracking exhibited minimal laterality changes compared to probabilistic tracking, experiencing only about 6%. Except for tracking algorithms, different fiber filtering methods, along with the various biological features themselves, displayed more variable patterns of laterality change. In conclusion, this study provides valuable insights into the intricate relationship between fiber filtering and laterality changes in brain structural connectivity. These findings can be used to develop improved tractography filtering methods, ultimately leading to more robust and reliable measurements of brain asymmetry in lateralization studies.
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Affiliation(s)
- Yifei He
- School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China
| | - Yoonmi Hong
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, USA.
| | - Ye Wu
- School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China.
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Koga SF, Hodges WB, Adamyan H, Hayes T, Fecci PE, Tsvankin V, Pradilla G, Hoang KB, Lee IY, Sankey EW, Codd PJ, Huie D, Zacharia BE, Verma R, Baboyan VG. Preoperative validation of edema-corrected tractography in neurosurgical practice: translating surgeon insights into novel software implementation. Front Neurol 2024; 14:1322815. [PMID: 38259649 PMCID: PMC10801029 DOI: 10.3389/fneur.2023.1322815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 12/19/2023] [Indexed: 01/24/2024] Open
Abstract
Background Peritumoral edema alters diffusion anisotropy, resulting in false negatives in tractography reconstructions negatively impacting surgical decision-making. With supratotal resections tied to survival benefit in glioma patients, advanced diffusion modeling is critical to visualize fibers within the peritumoral zone to prevent eloquent fiber transection thereafter. A preoperative assessment paradigm is therefore warranted to systematically evaluate multi-subject tractograms along clinically meaningful parameters. We propose a novel noninvasive surgically-focused survey to evaluate the benefits of a tractography algorithm for preoperative planning, subsequently applied to Synaptive Medical's free-water correction algorithm developed for clinically feasible single-shell DTI data. Methods Ten neurosurgeons participated in the study and were presented with patient datasets containing histological lesions of varying degrees of edema. They were asked to compare standard (uncorrected) tractography reconstructions overlaid onto anatomical images with enhanced (corrected) reconstructions. The raters assessed the datasets in terms of overall data quality, tract alteration patterns, and the impact of the correction on lesion definition, brain-tumor interface, and optimal surgical pathway. Inter-rater reliability coefficients were calculated, and statistical comparisons were made. Results Standard tractography was perceived as problematic in areas proximal to the lesion, presenting with significant tract reduction that challenged assessment of the brain-tumor interface and of tract infiltration. With correction applied, significant reduction in false negatives were reported along with additional insight into tract infiltration. Significant positive correlations were shown between favorable responses to the correction algorithm and the lesion-to-edema ratio, such that the correction offered further clarification in increasingly edematous and malignant lesions. Lastly, the correction was perceived to introduce false tracts in CSF spaces and - to a lesser degree - the grey-white matter interface, highlighting the need for noise mitigation. As a result, the algorithm was modified by free-water-parameterizing the tractography dataset and introducing a novel adaptive thresholding tool for customizable correction guided by the surgeon's discretion. Conclusion Here we translate surgeon insights into a clinically deployable software implementation capable of recovering peritumoral tracts in edematous zones while mitigating artifacts through the introduction of a novel and adaptive case-specific correction tool. Together, these advances maximize tractography's clinical potential to personalize surgical decisions when faced with complex pathologies.
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Affiliation(s)
- Sebastian F Koga
- Franciscan Missionaries of Our Lady Health System, Baton Rouge, LA, United States
| | | | | | - Tim Hayes
- Synaptive Medical Inc., Toronto, ON, Canada
| | - Peter E Fecci
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States
| | - Vadim Tsvankin
- Colorado Brain and Spine Institute, Englewood, CO, United States
| | - Gustavo Pradilla
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, United States
| | - Kimberly B Hoang
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, United States
| | - Ian Y Lee
- Department of Neurosurgery, Henry Ford Health System, Detroit, MI, United States
| | - Eric W Sankey
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States
| | - Patrick J Codd
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States
| | - David Huie
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States
| | - Brad E Zacharia
- Department of Neurosurgery, Penn State Hershey Medical Center, Hershey, PA, United States
| | - Ragini Verma
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
- Cohen Veterans Bioscience, New York, NY, United States
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