Evidence map›Paper›PMID 34722246›Full record

ArticleFrontiers in oncology2021

Multiparameter MRI Model With DCE-MRI, DWI, and Synthetic MRI Improves the Diagnostic Performance of BI-RADS 4 Lesions.

Shi Yun Sun, Yingying Ding, Zhuolin Li, Lisha Nie, Chengde Liao, Yifan Liu, Jia Zhang, Dongxue Zhang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

17 citing papers in PubMed, 21 citations in OpenAlex.

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  7. 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

8 authors at 3 institutions in 1 country.

Shi Yun SunDepartment of Radiology, Yunnan Cancer Center, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China.
Yingying DingDepartment of Radiology, Yunnan Cancer Center, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China.
Zhuolin LiDepartment of Radiology, Yunnan Cancer Center, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China.
Lisha NieMagnetic Resonance Imaging Research, General Electric Healthcare (China), Beijing, China.
Chengde LiaoDepartment of Radiology, Yunnan Cancer Center, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China.
Yifan LiuDepartment of Radiology, Yunnan Cancer Center, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China.
Jia ZhangDepartment of Radiology, Third People's Hospital of Yunnan Province, Kunming, China.
Dongxue ZhangDepartment of Radiology, Yunnan Cancer Center, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China.
Kunming Medical University · CNThird People's Hospital of Yunnan Province · CNUnited Imaging Healthcare (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo evaluate the value of synthetic magnetic resonance imaging (syMRI), diffusion-weighted imaging (DWI), DCE-MRI, and clinical features in breast imaging-reporting and data system (BI-RADS) 4 lesions, and develop an efficient method to help patients avoid unnecessary biopsy.

methodsA total of 75 patients with breast diseases classified as BI-RADS 4 (45 with malignant lesions and 30 with benign lesions) were prospectively enrolled in this study. T1-weighted imaging (T1WI), T2WI, DWI, and syMRI were performed at 3.0 T. Relaxation time (T1 and T2), apparent diffusion coefficient (ADC), conventional MRI features, and clinical features were assessed. "T" represents the relaxation time value of the region of interest pre-contrast scanning, and "T+" represents the value post-contrast scanning. The rate of change in the T value between pre- and post-contrast scanning was represented by ΔT%.

resultsΔT1%, T2, ADC, age, body mass index (BMI), menopause, irregular margins, and heterogeneous internal enhancement pattern were significantly associated with a breast cancer diagnosis in the multivariable logistic regression analysis. Based on the above parameters, four models were established: model 1 (BI-RADS model, including all conventional MRI features recommended by BI-RADS lexicon), model 2 (relaxation time model, including ΔT1% and T2), model 3 [multi-parameter (mp)MRI model, including ΔT1%, T2, ADC, margin, and internal enhancement pattern], and model 4 (combined image and clinical model, including ΔT1%, T2, ADC, margin, internal enhancement pattern, age, BMI, and menopausal state). Among these, model 4 has the best diagnostic performance, followed by models 3, 2, and 1.

conclusionsThe mpMRI model with DCE-MRI, DWI, and syMRI is a robust tool for evaluating the malignancies in BI-RADS 4 lesions. The clinical features could further improve the diagnostic performance of the model.

Indexed as

breast cancermappingquantitative imagingrelaxation timesynthetic magnetic resonance imaging (syMRI)

Identifiers

PMID34722246
PMCPMC8554332
OpenAlexW3206222485

What OpenQuestion holds

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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.