Evidence map›Paper›PMID 38773660›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2024

Applying dynamic contrast-enhanced MRI tracer kinetic models to differentiate benign and malignant soft tissue tumors.

Aixin Gao, Hexiang Wang, Xiuyun Zhang, Tongyu Wang, Liuyang Chen, Jingwei Hao, Ruizhi Zhou, Zhitao Yang, Bin Yue, Dapeng Hao

Abstract read
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

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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

4 citing papers in PubMed.

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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.

Aixin Gao *Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China.
Hexiang Wang *Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China.
Xiuyun ZhangDepartment of Clinic Lab, Qingdao Cancer Hospital, Qingdao, Shandong, China.
Tongyu WangDepartment of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China.
Liuyang ChenFisca Healthcare (nanjing) Co., Ltd, Nanjing, Jiangsu, China.
Jingwei HaoDepartment of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China.
Ruizhi ZhouDepartment of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China.
Zhitao YangDepartment of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China.
Bin YueDepartment of Bone Oncology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China. bonetumoryb@qdu.edu.cn.
Dapeng HaoDepartment of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China. haodp2021@qdu.edu.cn.ORCID http://orcid.org/0000-0003-3499-4106

Funding

National Natural Science Foundation of China 82172035Natural Science Foundation of Shandong Province ZR2020MH286Natural Science Foundation of Shandong Province ZR2021MH159
6 · The paper itself

Abstract

backgroundTo explore the potential of different quantitative dynamic contrast-enhanced (qDCE)-MRI tracer kinetic (TK) models and qDCE parameters in discriminating benign from malignant soft tissue tumors (STTs).

methodsThis research included 92 patients (41females, 51 males; age range 16-86 years, mean age 51.24 years) with STTs. The qDCE parameters (K

resultsTOFTS-K

conclusionsVarious TK models successfully distinguish benign from malignant STTs. The comprehensive model is a noninvasive approach incorporating morphological imaging aspects and qDCE parameters, and shows significant potential for further development.

Indexed as

Contrast MediaMagnetic Resonance ImagingSoft Tissue NeoplasmsAdolescentAdultAgedAged, 80 and overDiagnosis, DifferentialFemaleHumansKineticsMaleMiddle AgedYoung AdultContrast MediaDiagnosisDynamic contrast-enhanced MRISoft tissue tumors

Identifiers

PMID38773660
PMCPMC11107050

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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.