ArticleThe pharmacogenomics journal2013
Gray matter textural heterogeneity as a potential in-vivo biomarker of fine structural abnormalities in Asperger syndrome.
Article in The pharmacogenomics journal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 18 citations in OpenAlex.
- Identification of voxel-based texture abnormalities as new biomarkers for schizophrenia and major depressive patients using layer-wise relevance propagation on deep learning decisions.Psychiatry research. Neuroimaging · 2021Article
- Article
- CT texture analysis of renal masses: pilot study using random forest classification for prediction of pathology.Academic radiology · 2014Article
- Abnormalities in fronto-striatal connectivity within language networks relate to differences in grey-matter heterogeneity in Asperger syndrome.NeuroImage. Clinical · 2013Article
- Sex differences and autism: brain function during verbal fluency and mental rotation.PloS one · 2012Article
- Behavioral, Cognitive and Neural Markers of Asperger Syndrome.Basic and clinical neuroscienceReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 6 institutions in 4 countries.
Funding
Abstract
Brain imaging studies contribute to the neurobiological understanding of Autism Spectrum Conditions (ASC). Herein, we tested the prediction that distributed neurodevelopmental abnormalities in brain development impact on the homogeneity of brain tissue measured using texture analysis (TA; a morphological method for surface pattern characterization). TA was applied to structural magnetic resonance brain scans of 54 adult participants (24 with Asperger syndrome (AS) and 30 controls). Measures of mean gray-level intensity, entropy and uniformity were extracted from gray matter images at fine, medium and coarse textures. Comparisons between AS and controls identified higher entropy and lower uniformity across textures in the AS group. Data reduction of texture parameters revealed three orthogonal principal components. These were used as regressors-of-interest in a voxel-based morphometry analysis that explored the relationship between surface texture variations and regional gray matter volume. Across the AS but not control group, measures of entropy and uniformity were related to the volume of the caudate nuclei, whereas mean gray-level was related to the size of the cerebellar vermis. Similar to neuropathological studies, our study provides evidence for distributed abnormalities in the structural integrity of gray matter in adults with ASC, in particular within corticostriatal and corticocerebellar networks. Additionally, this in-vivo technique may be more sensitive to fine microstructural organization than other more traditional magnetic resonance approaches and serves as a future testable biomarker in AS and other neurodevelopmental disorders.
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.