Evidence map›Paper›PMID 31592734›Full record

ReviewRadiology2019

Diffusion-weighted MRI for Unenhanced Breast Cancer Screening.

Nita Amornsiripanitch, Sebastian Bickelhaupt, Hee Jung Shin, Madeline Dang, Habib Rahbar, Katja Pinker, Savannah C Partridge

Registry-linked trialOpen access · greenAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07598084 (Artificial Intelligence Solution for Simplifying the Diagnostic Workflow of Breast MRI), which is not on this map. Cited by 82 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 3 pooled it
11.4field-weighted citation impact, top 1% 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.

NCT07598084 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Artificial Intelligence Solution for Simplifying the Diagnostic Workflow of Breast MRI: Development and Clinical Validation of a Diffusion-Weighted Imaging-Based Synthetic Contrast-Enhanced MRI System for Non-Contrast Breast Cancer Diagnosis and Risk Stratification

TypeobservationalSponsorPeking University People's HospitalRan2026 to 2027Enrolled12,000ConditionsBreast Neoplasms, Artificial Intelligence (AI), Magnetic Resonance Imaging (MRI), Diffusion Magnetic Resonance ImagingArmsNon-contrast breast MRI diagnostic model
3 · Its place in the literature

Who cites it

82 citing papers in PubMed, 3 syntheses or guidelines pooled it, 152 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Applications of TFrontiers in oncology · 2022
    Pooled it
  4. Article
  5. Article
  6. Article
  7. Time-dependent diffusion MRI as in vivo histology: microstructural biomarkers for breast cancer diagnosis and prognostic stratification.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    Article
  8. Article
  9. Article
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  11. Article
  12. Review
  13. Article
  14. Utility of Echo-planar Imaging with Compressed Sensitivity Encoding (EPICS) in the Evaluation of Small Breast Cancers Using Diffusion-weighted Imaging with Background Suppression (DWIBS).Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    Article
  15. Article
  16. Breast Diffusion-weighted MR Imaging: Current Applications, Insights from Screening, and Future Directions.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    Review
  17. Breast MRI to Screen Women With Extremely Dense Breasts.Journal of magnetic resonance imaging : JMRI · 2025
    Review
  18. Article
  19. Article
  20. Article

22 more citing papers are in PubMed but not listed here.

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

7 authors at 4 institutions in 4 countries.

Nita AmornsiripanitchFrom the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology-Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.).ORCID 0000-0003-3851-8537
Sebastian BickelhauptFrom the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology-Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.).ORCID 0000-0003-1043-4462
Hee Jung ShinFrom the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology-Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.).ORCID 0000-0002-3398-1074
Madeline DangFrom the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology-Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.).ORCID 0000-0003-0507-9822
Habib RahbarFrom the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology-Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.).ORCID 0000-0003-4835-1478
Katja PinkerFrom the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology-Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.).ORCID 0000-0002-2722-7331
Savannah C PartridgeFrom the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology-Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.).ORCID 0000-0001-6370-9111
University of Washington · USHeidelberg University · DEGerman Cancer Research Center · DEMemorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
Validation and Standardization of the Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker in Breast CancerR01CA207290 · NCI · UNIVERSITY OF WASHINGTON · PI PARTRIDGE, SAVANNAH CORRINA · 2017 to 2022
$2.2M
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA207290
6 · The paper itself

Abstract

Diffusion-weighted (DW) MRI is a rapid technique that measures the mobility of water molecules within tissue, reflecting the cellular microenvironment. At DW MRI, breast cancers typically exhibit reduced diffusivity and appear hyperintense to surrounding tissues. On the basis of this characteristic, DW MRI may offer an unenhanced method to detect breast cancer without the costs and safety concerns associated with dynamic contrast material-enhanced MRI, the current reference standard in the setting of high-risk screening. This application of DW MRI has not been widely explored but is particularly timely given the growing health concerns related to the long-term use of gadolinium-based contrast material. Moreover, increasing breast density notification legislation across the United States is raising awareness of the limitations of mammography in women with dense breasts, emphasizing the need for additional cost-effective supplemental screening examinations. Preliminary studies suggest unenhanced MRI with DW MRI may provide higher sensitivity than screening mammography for the detection of breast malignancies. Larger prospective multicenter trials are needed to validate single-center findings and assess the performance of DW MRI for generalized breast cancer screening. Standardization of DW MRI acquisition and interpretation is essential to ensure reliable sensitivity and specificity, and an optimal approach for screening using readily available techniques is proposed here.

Indexed as

Breast NeoplasmsDiffusion Magnetic Resonance ImagingEarly Detection of CancerFemaleHumans

Identifiers

PMID31592734
PMCPMC6884069
OpenAlexW2979521875

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.