Evidence map›Paper›PMID 36335166›Full record

ArticleScientific reports2022

Generative adversarial network-created brain SPECTs of cerebral ischemia are indistinguishable to scans from real patients.

Rudolf A Werner, Takahiro Higuchi, Naoko Nose, Fujio Toriumi, Yohji Matsusaka, Ichiei Kuji, Koshino Kazuhiro

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 17% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 6 institutions in 3 countries.

Rudolf A WernerDepartment of Nuclear Medicine, University Hospital Würzburg, Oberdürrbacher Str. 6, 97080, Würzburg, Germany.
Takahiro HiguchiDepartment of Nuclear Medicine, University Hospital Würzburg, Oberdürrbacher Str. 6, 97080, Würzburg, Germany. thiguchi@me.com.
Naoko NoseGraduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.
Fujio ToriumiDepartment of Systems Innovation, Graduate School of Engineering, The University of Tokyo, Bunkyo-Ku, Japan.
Yohji MatsusakaDepartment of Nuclear Medicine, University Hospital Würzburg, Oberdürrbacher Str. 6, 97080, Würzburg, Germany.
Ichiei KujiDepartment of Nuclear Medicine, Saitama Medical University International Medical Center, Saitama, Japan.
Koshino KazuhiroDepartment of Systems and Informatics, Hokkaido Information University, Ebetsu, Japan.
Saitama Medical University · JPHokkaido Information University · JPJohns Hopkins University · USOkayama University · JPThe University of Tokyo · JPUniversitätsklinikum Würzburg · DE

Funding

Deutsche Forschungsgemeinschaft 453989101Japan Society for the Promotion of Science 22H03027
6 · The paper itself

Abstract

Deep convolutional generative adversarial networks (GAN) allow for creating images from existing databases. We applied a modified light-weight GAN (FastGAN) algorithm to cerebral blood flow SPECTs and aimed to evaluate whether this technology can generate created images close to real patients. Investigating three anatomical levels (cerebellum, CER; basal ganglia, BG; cortex, COR), 551 normal (248 CER, 174 BG, 129 COR) and 387 pathological brain SPECTs using N-isopropyl p-I-123-iodoamphetamine (

Indexed as

Brain IschemiaTomography, Emission-Computed, Single-PhotonBrainCerebral InfarctionCerebrovascular CirculationHumansImage Processing, Computer-AssistedIodine RadioisotopesIofetamineIodine-123Iodine RadioisotopesIofetamine

Identifiers

PMID36335166
PMCPMC9637159
OpenAlexW4308305932

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.