Evidence map›Paper›PMID 38386084›Full record

ArticleEJNMMI physics2024

Kinetic

Tao Wang, Yinglei Deng, Sidan Wang, Jianfeng He, Shaobo Wang

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

Article in EJNMMI physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Discriminating inflammation from malignancy with short-dynamic patlak parametric 18 F-FDG PET/CT.European journal of nuclear medicine and molecular imaging · 2026
    Article
  2. Article
  3. 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

5 authors at 1 institution in 1 country.

Tao WangFaculty of Information Engineering and Automation, Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming, 650500, Yunnan, China.
Yinglei DengPET/CT Center, Affiliated Hospital of Kunming University of Science and Technology, First People's Hospital of Yunnan, Kunming, 650031, China.
Sidan WangPET/CT Center, Affiliated Hospital of Kunming University of Science and Technology, First People's Hospital of Yunnan, Kunming, 650031, China.
Jianfeng HeFaculty of Information Engineering and Automation, Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming, 650500, Yunnan, China. jfenghe@foxmail.com.
Shaobo WangPET/CT Center, Affiliated Hospital of Kunming University of Science and Technology, First People's Hospital of Yunnan, Kunming, 650031, China. wshbo_98@126.com.ORCID http://orcid.org/0000-0001-8878-9496
Kunming University of Science and Technology · CN

Funding

National Natural Science Foundation of China No. 81760306National Natural Science Foundation of China No. 82160347National Natural Science Foundation of China No. 82260355the Basic Research on Application of Joint Special Funding of Science and Technology Department of Yunnan Province-Kunming Medical University No. 2018FE001(-291)the High-level Talent Project of Health in Yunnan Province No. D-2018011the Ten Thousand People Plan in Yunnan Province No. YNWR-QNBJ-2018-243Yunnan Key Laboratory of Smart City in Cyberspace Security No. 202105AG070010
6 · The paper itself

Abstract

backgroundThe endoplasmic reticulum plays an important role in glucose metabolism and has not been explored in the kinetic estimation of hepatocellular carcinoma (HCC) via 18F-fluoro-2-deoxy-D-glucose PET/CT.

methodsA dual-input four-compartment (4C) model, regarding endoplasmic reticulum was preliminarily used for kinetic estimation to differentiate 28 tumours from background liver tissue from 24 patients with HCC. Moreover, parameter images of the 4C model were generated from one patient with negative findings on conventional metabolic PET/CT.

resultsCompared to the dual-input three-compartment (3C) model, the 4C model has better fitting quality, a close transport rate constant (K

conclusionsThe 4C model with the endoplasmic reticulum performed better than the 3C model and produced additional useful parameters in kinetic estimation for differentiating HCC from background liver tissue.

Indexed as

Dual-input four-compartmentHepatocellular carcinomaKinetic modelPET/CT

Identifiers

PMID38386084
PMCPMC10884391
OpenAlexW4392052831

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.