Evidence map›Paper›PMID 38223079›Full record

ArticleQuantitative imaging in medicine and surgery2024

Low

Lei Yan, Zhao Wang, Dacheng Li, Yangyang Wang, Guangjie Yang, Yujun Zhao, Yan Kong, Rui Wang, Runze Wu, Zhenguang Wang

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 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
0.9field-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, 4 citations in OpenAlex.

  1. EJNMMI research · 2025
    Article
  2. Review
  3. Review
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

10 authors at 3 institutions in 1 country.

Lei YanDepartment of Nuclear Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China.
Zhao WangDepartment of Nuclear Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China.
Dacheng LiDepartment of Nuclear Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China.
Yangyang WangDepartment of Nuclear Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China.
Guangjie YangDepartment of Nuclear Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China.
Yujun ZhaoDepartment of Nuclear Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China.
Yan KongDepartment of Nuclear Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China.
Rui WangDepartment of Nuclear Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China.
Runze WuCentral Research Institute, Beijing United Imaging Research Institute of Intelligent Imaging, Beijing, China.
Zhenguang WangDepartment of Nuclear Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China.
Affiliated Hospital of Qingdao University · CNQingdao University · CNUnited Imaging Healthcare (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients with lymphoma receive multiple positron emission tomography/computed tomography (PET/CT) exams for monitoring of the therapeutic response. With PET imaging, a reduced level of injected fluorine-18 fluorodeoxyglucose ([ Methods: This study retrospectively enrolled 62 patients who underwent [ Results: The visual image quality of the LD group was improved compared with the RD group. The DS was similar between the RD and LD group, and the negative (DS 1-3) and positive (DS 4-5) results remained unchanged. The correlation coefficients of SUV in the liver, mediastinum, and lesions were all >0.85. The mean differences of SUV Conclusions: The DL denoising technique enables accurate tumor assessment and quantification with LD [

Indexed as

deep learning (DL)image qualityLow doselymphomapositron emission tomography (PET)tumor staging

Identifiers

PMID38223079
PMCPMC10784027
OpenAlexW4390426657

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.