ArticleClinical neuroradiology2017
Clinical Application of Fiber Visualization with LIC Maps Using Multidirectional Anisotropic Glyph Samples (A-Glyph LIC).
Article in Clinical neuroradiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Fiber visualization for preoperative glioma assessment: Tractography versus local connectivity mapping.PloS one · 2019Article
- Improvement in White Matter Tract Reconstruction with Constrained Spherical Deconvolution and Track Density Mapping in Low Angular Resolution Data: A Pediatric Study and Literature Review.Frontiers in pediatrics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recently, a fiber visualization method for high-angular resolution diffusion-weighted magnetic resonance imaging (MRI) data was proposed using a multiple-kernel line integral convolution (LIC) algorithm and an anisotropic spot pattern. This processing routine leads to high contrast color-coded LIC maps that are capable of visualizing local anisotropy information and regional fiber architecture. In this paper, we evaluate and validate this method by applying it to simulated datasets and to in vivo diffusion MRI data of children and adults with different disease conditions and healthy volunteers. Compared to routine clinical fiber visualization (color-coded fractional anisotropy, FA maps, and fiber tractography), it has the advantage of visualizing complex local fiber architecture in a fully automated way. The results indicate that this method is capable of reliably delineating normal fiber architecture and fibers infiltrated, displaced, or disrupted by lesions and is therefore a promising tool in the clinical context.
Indexed as
Identifiers
What OpenQuestion holds
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.