Evidence map›Paper›PMID 30811717›Full record

ArticleJournal of magnetic resonance imaging : JMRI2019

Diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping as a quantitative imaging biomarker for prediction of immunohistochemical receptor status, proliferation rate, and molecular subtypes of breast cancer.

Joao V Horvat, Blanca Bernard-Davila, Thomas H Helbich, Michelle Zhang, Elizabeth A Morris, Sunitha B Thakur, R Elena Ochoa-Albiztegui, Doris Leithner, Maria A Marino, Pascal A Baltzer and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 1 pooled it
8.5field-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

59 citing papers in PubMed, 1 synthesis or guideline pooled it, 99 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Monitoring Pharmacological Treatment of Breast Cancer with MRI.Current issues in molecular biology · 2025
    Review
  15. Article
  16. Article
  17. 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
  18. Article
  19. Article
  20. Article
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

14 authors at 2 institutions in 2 countries.

Joao V HorvatDepartment of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Blanca Bernard-DavilaDepartment of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Thomas H HelbichDepartment of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Austria.
Michelle ZhangDepartment of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Elizabeth A MorrisDepartment of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Sunitha B ThakurDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.ORCID 0000-0001-8090-3696
R Elena Ochoa-AlbizteguiDepartment of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Doris LeithnerDepartment of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Maria A MarinoDepartment of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.ORCID 0000-0002-5614-2660
Pascal A BaltzerDepartment of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Austria.ORCID 0000-0002-3755-5398
Paola ClauserDepartment of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Austria.
Panagiotis KapetasDepartment of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Austria.
Zsuzsanna Bago-HorvathDepartment of Pathology, Medical University of Vienna, Austria.
Katja PinkerDepartment of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.ORCID 0000-0002-2722-7331
Memorial Sloan Kettering Cancer Center · USMedical University of Vienna · AT

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
2020 - Research and Innovation Framework Programme PHC-11-2015 Nr. 667211-2Austrian Nationalbank 'Jubiläumsfond' Project Nr. 16219Breast Cancer Research FoundationGuerbet, FranceNCI NIH HHS P30 CA008748NovomedSiemens, AustriaSusan G. Komen
6 · The paper itself

Abstract

backgroundDiffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping is one of the most useful additional MRI parameters to improve diagnostic accuracy and is now often used in a multiparameric imaging setting for breast tumor detection and characterization. PURPOSE: To evaluate whether different ADC metrics can also be used for prediction of receptor status, proliferation rate, and molecular subtype in invasive breast cancer. STUDY TYPE: Retrospective. SUBJECTS: In all, 107 patients with invasive breast cancer met the inclusion criteria (mean age 57 years, range 32-87) and underwent multiparametric breast MRI. FIELD STRENGTH/SEQUENCE: 3 T, readout-segmented echo planar imaging (rsEPI) with IR fat suppression, dynamic contrast-enhanced (DCE) T ASSESSMENT: Two readers independently drew a region of interest on ADC maps on the whole tumor (WTu), and on its darkest part (DpTu). Minimum, mean, and maximum ADC values of both WTu and DpTu were compared for receptor status, proliferation rate, and molecular subtypes. STATISTICAL TESTS: Wilcoxon rank sum, Mann-Whitney U-tests for associations between radiologic features and histopathology; histogram and q-q plots, Shapiro-Wilk's test to assess normality, concordance correlation coefficient for precision and accuracy; receiver operating characteristics curve analysis.

resultsEstrogen receptor (ER) and progesterone receptor (PR) status had significantly different ADC values for both readers. Maximum WTu (P = 0.0004 and 0.0005) and mean WTu (P = 0.0101 and 0.0136) were significantly lower for ER-positive tumors, while PR-positive tumors had significantly lower maximum WTu values (P = 0.0089 and 0.0047). Maximum WTu ADC was the only metric that was significantly different for molecular subtypes for both readers (P = 0.0100 and 0.0132) and enabled differentiation of luminal tumors from nonluminal (P = 0.0068 and 0.0069) with an area under the curve of 0.685 for both readers. DATA

conclusionMaximum WTu ADC values may be used to differentiate luminal from other molecular subtypes of breast cancer. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:836-846.

Indexed as

AdultAgedAged, 80 and overBiomarkersBreastBreast NeoplasmsCell ProliferationContrast MediaDiffusion Magnetic Resonance ImagingEcho-Planar ImagingFemaleHumansImage EnhancementImage Interpretation, Computer-AssistedMiddle AgedReceptors, EstrogenBiomarkersContrast MediaReceptors, EstrogenReceptors, Progesteroneapparent diffusion coefficient: magnetic resonance imagingbreast cancerdiffusion weighted imagingimmunohistochemistrymolecular subtypes

Identifiers

PMID30811717
PMCPMC6767396
OpenAlexW2919850878

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.