Evidence map›Paper›PMID 38512492›Full record

SynthesisEuropean radiology2024

The diagnostic performance of ultrafast MRI to differentiate benign from malignant breast lesions: a systematic review and meta-analysis.

Yoav Amitai, Vivianne A R Freitas, Orit Golan, Rivka Kessner, Tamar Shalmon, Rina Neeman, Michal Mauda-Havakuk, Diego Mercer, Miri Sklair-Levy, Tehillah S Menes

Open access · hybridAbstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in European radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
8.9field-weighted citation impact, top 2% 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

14 citing papers in PubMed, 22 citations in OpenAlex.

  1. Imaging the hallmarks of cancer.Nature reviews. Cancer · 2026
    Review
  2. Article
  3. Ultrafast MRI in BI-RADS 4 Masses: The Fast Lane to Clarity.The Indian journal of radiology & imaging · 2026
    Article
  4. Article
  5. Magnetic resonance imaging in breast cancer management: current applications, limitations, and future directions.Translational breast cancer research : a journal focusing on translational research in breast cancer · 2026
    Review
  6. Article
  7. Article
  8. Review
  9. Institutional Variability in Ultrafast Breast MR Imaging: Comparing Compressed Sensing and View Sharing Techniques with Different Patient Populations and Contrast Injection Protocols.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    Article
  10. Article
  11. Abbreviated and Ultrafast Dynamic Contrast-enhanced (DCE) MR Imaging.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    Review
  12. Review
  13. Ultrafast Breast MRI: A Narrative Review.Journal of personalized medicine · 2025
    Review
  14. Advances in Risk Management and Screening for Women at Increased Risk of Breast Cancer: The Role of MR Imaging and Personalised Approaches.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 2 countries.

Yoav AmitaiDepartment of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel. yoavslava@yahoo.com.ORCID http://orcid.org/0000-0002-8847-0490
Vivianne A R FreitasJoint Department of Medical Imaging - University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, 610 University Avenue - M5G 2M9, Toronto, Ontario, Canada.
Orit GolanDepartment of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel.
Rivka KessnerDepartment of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel.
Tamar ShalmonDepartment of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel.
Rina NeemanDepartment of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel.
Michal Mauda-HavakukDepartment of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel.
Diego MercerDepartment of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel.
Miri Sklair-LevyDepartment of Medical Imaging, Sackler School of Medicine, Chaim Sheba Medical Center, Tel Aviv University, Tel Hashomer, Derech Shiba 2, 52621, Ramat-Gan, Israel.
Tehillah S MenesDepartment of Surgery, Sackler School of Medicine, Chaim Sheba Medical Center, Tel Aviv University, Tel Hashomer, Derech Shiba 2, 52621, Ramat-Gan, Israel.
Tel Aviv University · ILUniversity Health Network · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess the diagnostic performance of ultrafast magnetic resonance imaging (UF-DCE MRI) in differentiating benign from malignant breast lesions. MATERIALS AND

methodsA comprehensive search was conducted until September 1, 2023, in Medline, Embase, and Cochrane databases. Clinical studies evaluating the diagnostic performance of UF-DCE MRI in breast lesion stratification were screened and included in the meta-analysis. Pooled summary estimates for sensitivity, specificity, diagnostic odds ratio (DOR), and hierarchic summary operating characteristics (SROC) curves were pooled under the random-effects model. Publication bias and heterogeneity between studies were calculated.

resultsA final set of 16 studies analyzing 2090 lesions met the inclusion criteria and were incorporated into the meta-analysis. Using UF-DCE MRI kinetic parameters, the pooled sensitivity, specificity, DOR, and area under the curve (AUC) for differentiating benign from malignant breast lesions were 83% (95% CI 79-88%), 77% (95% CI 72-83%), 18.9 (95% CI 13.7-26.2), and 0.876 (95% CI 0.83-0.887), respectively. We found no significant difference in diagnostic accuracy between the two main UF-DCE MRI kinetic parameters, maximum slope (MS) and time to enhancement (TTE). DOR and SROC exhibited low heterogeneity across the included studies. No evidence of publication bias was identified (p = 0.585).

conclusionsUF-DCE MRI as a stand-alone technique has high accuracy in discriminating benign from malignant breast lesions. CLINICAL RELEVANCE STATEMENT: UF-DCE MRI has the potential to obtain kinetic information and stratify breast lesions accurately while decreasing scan times, which may offer significant benefit to patients. KEY POINTS: • Ultrafast breast MRI is a novel technique which captures kinetic information with very high temporal resolution. • The kinetic parameters of ultrafast breast MRI demonstrate a high level of accuracy in distinguishing between benign and malignant breast lesions. • There is no significant difference in accuracy between maximum slope and time to enhancement kinetic parameters.

Indexed as

Breast NeoplasmsMagnetic Resonance ImagingBreastDiagnosis, DifferentialFemaleHumansSensitivity and SpecificityArtificial intelligenceBreast cancerKineticsMagnetic resonance imagingUltrafast

Identifiers

PMID38512492
PMCPMC11399157
OpenAlexW4393043512

What OpenQuestion holds

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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.