ArticleNeuroImage. Clinical2017
Automated white matter fiber tract identification in patients with brain tumors.
Article in NeuroImage. Clinical, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 1 of them a synthesis that pooled it.
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Who cites it
76 citing papers in PubMed, 1 synthesis or guideline pooled it, 130 citations in OpenAlex.
- A systematic review of automated methods to perform white matter tract segmentation.Frontiers in neuroscience · 2024Pooled it
- The role of white matter microstructure in the association between childhood maltreatment and adult post-traumatic symptoms.Molecular psychiatry · 2026Article
- CNNT-Net: a novel deep learning-based framework for estimating high-quality fiber orientation distributions from single-shell dMRI.Physical and engineering sciences in medicine · 2026Article
- Cross-population white matter atlas creation for concurrent mapping of brain connections in neonates and adults with diffusion MRI tractography.Fundamental research · 2026Article
- Study of sex differences in the whole brain white matter using diffusion MRI tractography and suprathreshold fiber cluster statistics.NeuroImage. Clinical · 2026Article
- Study of Sex Differences in the Whole Brain White Matter Using Diffusion MRI Tractography and Suprathreshold Fiber Cluster Statistics.bioRxiv : the preprint server for biology · 2025Article
- Atlas-based templates vs. subject-specific tractography: resolving the debate.Brain structure & function · 2025Review
- Quality and efficiency of a semi-automatic anatomy-based method for tractography of associative white matter fascicles in brain tumor patients, a case series.Neurosurgical review · 2025Article
- Artificial intelligence in corticospinal tract segmentation using constrained spherical deconvolution.Surgical neurology international · 2025Article
- Functional anatomy and topographical organization of the frontotemporal arcuate fasciculus.Communications biology · 2024Article
- Identification and Connectomic Profiling of Concussion Using Bayesian Machine Learning.Journal of neurotrauma · 2024Article
- A diffusion MRI tractography atlas for concurrent white matter mapping across Eastern and Western populations.Scientific data · 2024Article
- Fibre orientation atlas guided rapid segmentation of white matter tracts.Human brain mapping · 2024Article
- Prediction of cognitive outcome after mild traumatic brain injury from acute measures of communication within brain networks.Cortex; a journal devoted to the study of the nervous system and behavior · 2024Article
- Multimodal Neuroimaging Computing: Basics and Applications in Neurosurgery.Advances in experimental medicine and biology · 2024Review
- Phybers: a package for brain tractography analysis.Frontiers in neuroscience · 2024Article
- Subject-Specific Automatic Reconstruction of White Matter Tracts.Journal of digital imaging · 2023Article
- Improved prediction of glioma-related aphasia by diffusion MRI metrics, machine learning, and automated fiber bundle segmentation.Human brain mapping · 2023Article
- Assessing informative tract segmentation and nTMS for pre-operative planning.Journal of neuroscience methods · 2023Article
- The decoupling of structural and functional connectivity of auditory networks in individuals at clinical high-risk for psychosis.The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry · 2023Article
16 more citing papers are in PubMed but not listed here.
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Authors and funding
16 authors at 2 institutions in 4 countries.
Funding
Abstract
We propose a method for the automated identification of key white matter fiber tracts for neurosurgical planning, and we apply the method in a retrospective study of 18 consecutive neurosurgical patients with brain tumors. Our method is designed to be relatively robust to challenges in neurosurgical tractography, which include peritumoral edema, displacement, and mass effect caused by mass lesions. The proposed method has two parts. First, we learn a data-driven white matter parcellation or fiber cluster atlas using groupwise registration and spectral clustering of multi-fiber tractography from healthy controls. Key fiber tract clusters are identified in the atlas. Next, patient-specific fiber tracts are automatically identified using tractography-based registration to the atlas and spectral embedding of patient tractography. Results indicate good generalization of the data-driven atlas to patients: 80% of the 800 fiber clusters were identified in all 18 patients, and 94% of the 800 fiber clusters were found in 16 or more of the 18 patients. Automated subject-specific tract identification was evaluated by quantitative comparison to subject-specific motor and language functional MRI, focusing on the arcuate fasciculus (language) and corticospinal tracts (motor), which were identified in all patients. Results indicate good colocalization: 89 of 95, or 94%, of patient-specific language and motor activations were intersected by the corresponding identified tract. All patient-specific activations were within 3mm of the corresponding language or motor tract. Overall, our results indicate the potential of an automated method for identifying fiber tracts of interest for neurosurgical planning, even in patients with mass lesions.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.