ArticleNeurosurgery2016
Individualized Map of White Matter Pathways: Connectivity-Based Paradigm for Neurosurgical Planning.
Article in Neurosurgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed.
- Modified Target Delineation and Moderately Hypofractionated Radiotherapy for High-Grade Glioma: A Randomized Clinical Trial.JAMA network open · 2025Trial
- 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
- Diffusion MRI with Machine Learning.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Subject-Specific Automatic Reconstruction of White Matter Tracts.Journal of digital imaging · 2023Article
- Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellation.NeuroImage · 2023Article
- Brain network mapping and glioma pathophysiology.Brain communications · 2023Review
- Tumor location-based classification of surgery-related language impairments in patients with glioma.Journal of neuro-oncology · 2021Article
- From Neurosurgical Planning to Histopathological Brain Tumor Characterization: Potentialities of Arcuate Fasciculus Along-Tract Diffusion Tensor Imaging Tractography Measures.Frontiers in neurology · 2021Article
- Deep white matter analysis (DeepWMA): Fast and consistent tractography segmentation.Medical image analysis · 2020Article
- Tractography and the connectome in neurosurgical treatment of gliomas: the premise, the progress, and the potential.Neurosurgical focus · 2020Review
- The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview.Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries. BrainLes (Workshop) · 2020Article
- Article
- Deep white matter analysis: fast, consistent tractography segmentation across populations and dMRI acquisitions.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2019Article
- Article
- Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma.Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries. BrainLes (Workshop) · 2018Article
- Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.Journal of medical imaging (Bellingham, Wash.) · 2018Article
- Automated white matter fiber tract identification in patients with brain tumors.NeuroImage. Clinical · 2017Article
- White matter tractography for neurosurgical planning: A topography-based review of the current state of the art.NeuroImage. Clinical · 2017Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundAdvances in white matter tractography enhance neurosurgical planning and glioma resection, but white matter tractography is limited by biological variables such as edema, mass effect, and tract infiltration or selection biases related to regions of interest or fractional anisotropy values.
objectiveTo provide an automated tract identification paradigm that corrects for artifacts created by tumor edema and infiltration and provides a consistent, accurate method of fiber bundle identification.
methodsAn automated tract identification paradigm was developed and evaluated for glioma surgery. A fiber bundle atlas was generated from 6 healthy participants. Fibers of a test set (including 3 healthy participants and 10 patients with brain tumors) were clustered adaptively with this atlas. Reliability of the identified tracts in both groups was assessed by comparison with 2 experts with the Cohen κ used to quantify concurrence. We evaluated 6 major fiber bundles: cingulum bundle, fornix, uncinate fasciculus, arcuate fasciculus, inferior fronto-occipital fasciculus, and inferior longitudinal fasciculus, the last 3 tracts mediating language function.
resultsThe automated paradigm demonstrated a reliable and practical method to identify white mater tracts, despite mass effect, edema, and tract infiltration. When the tumor demonstrated significant mass effect or shift, the automated approach was useful for providing an initialization to guide the expert with identification of the specific tract of interest.
conclusionWe report a reliable paradigm for the automated identification of white matter pathways in patients with gliomas. This approach should enhance the neurosurgical objective of maximal safe resections. ABBREVIATIONS: AF, arcuate fasciculusDTI, diffusion tensor imagingIFOF, inferior fronto-occipital fasciculusILF, inferior longitudinal fasciculusROI, region of interestWM, white matter.
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Registered trials
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.