Evidence map›Paper›PMID 37864025›Full record

ArticleScientific reports2023

Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status.

Xiaojun Li, Zhichang Fan, Hongnan Jiang, Jinliang Niu, Wenjin Bian, Chen Wang, Ying Wang, Runmei Zhang, Hui Zhang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
4.6field-weighted citation impact, top 5% 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

19 citing papers in PubMed, 20 citations in OpenAlex.

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  18. Quantitative MR Imaging of the Breast.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
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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

9 authors at 2 institutions in 1 country.

Xiaojun Li *Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi, China.
Zhichang Fan *Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi, China.
Hongnan JiangDepartment of Breast Surgery, Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, Shenzhen, China.
Jinliang NiuDepartment of Radiology, The 2nd Affiliated Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Wenjin BianDepartment of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi, China.
Chen WangDepartment of Pathology, The 2nd Affiliated Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Ying WangDepartment of Pathology, The 2nd Affiliated Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Runmei ZhangDepartment of Radiology, The 2nd Affiliated Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Hui ZhangDepartment of Radiology, First Hospital of Shanxi Medical University, No. 85, South Jiefang Road, Yingze District, Taiyuan, 030001, Shanxi, China. zhang_hui@sxmu.edu.cn.
Shanxi Medical University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and SyMRI before surgery in our hospital. DCE-MRI was used to assess the lesions, and then regions of interest (ROIs) were outlined on SyMRI (before and after enhancement), and apparent diffusion coefficient (ADC) maps to obtain quantitative values. After being grouped according to benign and malignant status, the malignant lesions were divided into high and low expression groups according to the expression status of IHC markers. Logistic regression was used to analyse the differences in independent variables between groups. The performance of the modalities in classification and prediction was evaluated by receiver operating characteristic (ROC) curves. In total, 57 of 121 lesions were benign, the other 64 were malignant, and 56 malignant lesions performed immunohistochemical staining. Quantitative values from proton density-weighted imaging prior to an injection of the contrast agent (PD-Pre) and T2-weighted imaging (T2WI) after the injection (T2-Gd), as well as its standard deviation (SD of T2-Gd), were valuable SyMRI parameters for the classification of benign and malignant breast lesions, but the performance of SyMRI (area under the curve, AUC = 0.716) was not as good as that of ADC values (AUC = 0.853). However, ADC values could not predict the expression status of breast cancer markers, for which SyMRI had excellent performance. The AUCs of androgen receptor (AR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), p53 and Ki-67 were 0.687, 0.890, 0.852, 0.746, 0.813 and 0.774, respectively. SyMRI had certain value in distinguishing between benign and malignant breast lesions, and ADC values were still the ideal method. However, to predict the expression status of IHC markers, SyMRI had an incomparable value compared with ADC values.

Indexed as

Breast NeoplasmsBreastContrast MediaDiagnosis, DifferentialDiffusion Magnetic Resonance ImagingFemaleHumansMagnetic Resonance ImagingRetrospective StudiesROC CurveSensitivity and SpecificityContrast Media

Identifiers

PMID37864025
PMCPMC10589282
OpenAlexW4387804849

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LicenceCC BY
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Registered trials

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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.