Atlas-guided tract reconstruction for automated and comprehensive examination of the white matter anatomy
Open accessAbstract
Tractography based on diffusion tensor imaging (DTI) is widely used to quantitatively analyze the status of the white matter anatomy in a tract-specific manner in many types of diseases. This approach, however, involves subjective judgment in the tract-editing process to extract only the tracts of interest. This process, usually performed by manual delineation of regions of interest, is also time-consuming, and certain tracts, especially the short cortico-cortical association fibers, are difficult to reconstruct. In this paper, we propose an automated approach for reconstruction of a large number of white matter tracts. In this approach, existing anatomical knowledge about tract trajectories (called the Template ROI Set or TRS) were stored in our DTI-based brain atlas with 130 three-dimensional anatomical segmentations, which were warped non-linearly to individual DTI data. We examined the degree of matching with manual results for selected fibers. We established 30 TRSs to reconstruct 30 prominent and previously well-described fibers. In addition, TRSs were developed to delineate 29 short association fibers that were found in all normal subjects examined in this paper (N=20). Probabilistic maps of the 59 tract trajectories were created from the normal subjects and were incorporated into our image analysis tool for automated tract-specific quantification.
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Projections to the parietal lobe are systematically excluded using the method of Zhang et al. (2010) and are likely to be missed using the method of Catani and Thiebaut de Schotten (2008), as was the case in Sarubbo et al. (2013).
“As shown Figure 8, projections to the parietal lobe are systematically excluded using the method of Zhang et al. (2010) and are likely to be missed using the method of Catani and Thiebaut de Schotten (2008) that use ROIs delineated around the frontal and occipital lobes, as was the case in Sarubbo et al. (2013).”
From Cortical Terminations of the Inferior Fronto-Occipital and Uncinate Fasciculi: Anatomical Stem-Based Virtual Dissection (2016) · cites this paper as Zhang et al. (2010)
The Results section (Comparison between the automated and manual methods; page not provided) says Zhang et al.’s automated method reconstructed superior longitudinal fasciculus projections to the parietal lobe. It was the manual comparison method, not Zhang et al.’s automated method, that lacked a posterior parietal–temporal segment. The paper does not establish the claim about the other named methods. (LLM, conf=0.90)
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Experimental — accuracy not yet measuredSome studies describe a fifth division of the SLF comprised of a distinct fasciculus that connects the superior temporal gyrus to the superior parietal.
“Indeed, some studies even describe a fifth division of the SLF comprised of a distinct fasciculus (61–63) that would connect the superior temporal gyrus to the superior parietal.”
From Superior Longitudinal Fasciculus: A Review of the Anatomical Descriptions With Functional Correlates (2022) · cites this paper as [63]
The Results (Comparison between the automated and manual methods; page unavailable) describe a separately reconstructed SLF segment connecting the parietal and temporal lobes. They do not call it a fifth division or identify its endpoints as the superior temporal gyrus and superior parietal region; the parietal regions specified are the angular and supramarginal gyri. (LLM, conf=0.85)
Experimental — accuracy not yet measuredCurrent tract segmentation approaches rely heavily on a priori knowledge, using set-of-ROIs strategies that place ROIs around known terminal areas or areas of passage.
“While current tract segmentation approaches rely heavily on a priori knowledge, using set-of-ROIs strategies that place the ROIs around their known terminal areas or areas of passage (Catani and Thiebaut de Schotten, 2008; Zhang et al., 2010)”
From Cortical Terminations of the Inferior Fronto-Occipital and Uncinate Fasciculi: Anatomical Stem-Based Virtual Dissection (2016) · cites this paper as Zhang et al., 2010
The stem-based virtual dissection results in more extensive IFOFs and UFs than current set-of-ROIs methods.
“our stem-based virtual dissection results in more extensive IFOFs and UFs.”
From Cortical Terminations of the Inferior Fronto-Occipital and Uncinate Fasciculi: Anatomical Stem-Based Virtual Dissection (2016) · cites this paper as Zhang et al., 2010
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- Authors
- Zhang, Y., Zhang, J., Oishi, K., Faria, A. V., Jiang, H., Li, X., Akhter, K., Rosa-Neto, P., Pike, G. B., Evans, A., Toga, A. W., Woods, R., Mazziotta, J. C., Miller, M. I., van Zijl, P. C. M., & Mori, S.
- Affiliations
- Johns Hopkins University (US)
- Kennedy Krieger Institute (US)
- Montreal Neurological Institute and Hospital (CA)
- University of California, Los Angeles (US)
- Corresponding author
- Mori, Susumu
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-10
- Volume
- 52
- Issue
- 4
- Pages
- 1289-1301
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2910162
- OpenAlex
- W2033793704
- Cited by
- 297
- References
- 3
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 12 · 2023: 17 · 2022: 24 · 2021: 17 · 2020: 24 · 2019: 19 · 2018: 18 · 2017: 27 · 2016: 21 · 2015: 24 · 2014: 22 · 2013: 28 · 2012: 22
- FWCI
- 16.38
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (R01AG020012, R21AG033774, R01-AG20012, P50AG005146, P50AG05146)
- National Institute of Neurological Disorders and Stroke (R01NS058299)
- National Institute of Biomedical Imaging and Bioengineering (P41EB015909, P01EB001955, R01EB000975)
- National Center for Research Resources (P41RR015241)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD065955)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- tractography, diffusion tensor imaging, white matter anatomy, brain atlas, probability maps, nonlinear registration
- MeSH terms
- Adult, Algorithms, Computer Simulation, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Male, Models, Anatomic, Models, Neurological, Nerve Fibers, Myelinated, Neural Pathways, Sensitivity and Specificity, Reproducibility of Results, Diffusion Tensor Imaging
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