ArticleAmerican journal of nuclear medicine and molecular imaging2019
Renal statistical map for positron emission tomography with [O-15] water.
Article in American journal of nuclear medicine and molecular imaging, 2019. 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, 2 citations in OpenAlex.
- Basic principles and new advances in kidney imaging.Kidney international · 2021Review
- Mapping COVID-19 with nuclear imaging: from infection to functional sequelae.American journal of nuclear medicine and molecular imaging · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Image statistics are frequently used for functional and molecular imaging research in which images from a patient group with a specific diagnosis are compared with images from a healthy control group who have been matched for demographic variables. The success of image statistics for brain imaging has encouraged us to develop a method for obtaining volumetrically normalized kidney to perform image statistics so that we can locally visualize the statistical significant difference comparing voxel by voxel between certain groups in terms kidney blood flow kinetic parameters. For the development of this evolutionary process, we first volumetrically normalized all subjects, which include healthy control (HC) and chronic renal failure (CRF) patients,
Indexed as
Identifiers
31516765PMC6737348W2982588322What 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.