ArticleNeuroscience bulletin2018
An Automatic Method for Generating an Unbiased Intensity Normalizing Factor in Positron Emission Tomography Image Analysis After Stroke.
Article in Neuroscience bulletin, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Article
- White matter microstructural alterations and brain metabolism distributions in Parkinson's disease.Brain imaging and behavior · 2025Article
- Association between gene expression and functional-metabolic architecture in Parkinson's disease.Human brain mapping · 2023Article
- Article
- Severity-dependent functional connectome and the association with glucose metabolism in the sensorimotor cortex of Parkinson's disease.Frontiers in neuroscience · 2023Article
- Feature-based Quality Assessment of Middle Cerebral Artery Occlusion Using 18F-Fluorodeoxyglucose Positron Emission Tomography.Neuroscience bulletin · 2022Article
- Modulation effect of substantia nigra iron deposition and functional connectivity on putamen glucose metabolism in Parkinson's disease.Human brain mapping · 2022Article
- Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization.Frontiers in medicine · 2021Article
- Abnormal Metabolic Connectivity in Rats at the Acute Stage of Ischemic Stroke.Neuroscience bulletin · 2018Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Positron emission tomography (PET) imaging of functional metabolism has been widely used to investigate functional recovery and to evaluate therapeutic efficacy after stroke. The voxel intensity of a PET image is the most important indicator of cellular activity, but is affected by other factors such as the basal metabolic ratio of each subject. In order to locate dysfunctional regions accurately, intensity normalization by a scale factor is a prerequisite in the data analysis, for which the global mean value is most widely used. However, this is unsuitable for stroke studies. Alternatively, a specified scale factor calculated from a reference region is also used, comprising neither hyper- nor hypo-metabolic voxels. But there is no such recognized reference region for stroke studies. Therefore, we proposed a totally data-driven automatic method for unbiased scale factor generation. This factor was generated iteratively until the residual deviation of two adjacent scale factors was reduced by < 5%. Moreover, both simulated and real stroke data were used for evaluation, and these suggested that our proposed unbiased scale factor has better sensitivity and accuracy for stroke studies.
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.