Evidence map›Paper›PMID 27766710›Full record

ArticleJournal of magnetic resonance imaging : JMRI2017

Separation of benign and malignant breast lesions using dynamic contrast enhanced MRI in a biopsy cohort.

Sungheon Gene Kim, Melanie Freed, Ana Paula Klautau Leite, Jin Zhang, Claudia Seuss, Linda Moy

Abstract read
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 11% 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, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Machine learning in breast MRI.Journal of magnetic resonance imaging : JMRI · 2020
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. 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

6 authors at 2 institutions in 1 country.

Sungheon Gene KimCenter for Advanced Imaging Innovation and Research (CAIR), New York, New York, USA.
Melanie FreedCenter for Advanced Imaging Innovation and Research (CAIR), New York, New York, USA.
Ana Paula Klautau LeiteCenter for Advanced Imaging Innovation and Research (CAIR), New York, New York, USA.
Jin ZhangCenter for Advanced Imaging Innovation and Research (CAIR), New York, New York, USA.
Claudia SeussCenter for Advanced Imaging Innovation and Research (CAIR), New York, New York, USA.
Linda MoyCenter for Advanced Imaging Innovation and Research (CAIR), New York, New York, USA.
Advanced Imaging Research (United States) · USNew York University · US

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Hersh Chandarana · 2014 to 2026
$19.3M
DCE MRI Study for Breast Cancer.R01CA160620 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI KIM, SUNGHEON GENE · 2012 to 2023
$5.4M
PET/MR study of Metastatic Lymph Nodes in Head and Neck CancerR21CA188217 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI KIM, SUNGHEON GENE · 2014 to 2015
$703k
NCI NIH HHS R01 CA160620NCI NIH HHS R21 CA188217NIBIB NIH HHS P41 EB017183
6 · The paper itself

Abstract

purposeTo assess the diagnostic utility of contrast kinetic analysis for breast lesions and background parenchyma of women undergoing MRI-guided biopsies, for whom standard clinical analysis had failed to separate benign and malignant lesions. MATERIALS AND

methodsThis study included 115 women who had indeterminate lesions based on routine diagnostic breast MRI exams and underwent an MRI (3 Tesla) -guided biopsy of one or more lesions suspicious for breast cancer. Breast dynamic contrast-enhanced (DCE)-MRI was performed using a radial stack-of-stars three-dimensional spoiled gradient echo pulse sequence and modified k-space weighted image contrast image reconstruction. Contrast kinetic model analysis was conducted to characterize the contrast enhancement patterns measured in lesions and background parenchyma (BP). The transfer rate (K

resultsThe patients with malignant lesions had significantly (P < 0.05) higher median lesion-K

conclusionOur results suggest that the contrast kinetic analysis of DCE-MRI data can be used to differentiate the malignant lesions from the benign and high-risk lesions among the indeterminate breast lesions recommended for MRI-guided biopsy exams. LEVEL OF EVIDENCE: 3 J. MAGN. RESON. IMAGING 2017;45:1385-1393.

Indexed as

Magnetic Resonance ImagingAdultAgedBiopsyBreastBreast NeoplasmsContrast MediaFemaleHumansImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedKineticsMiddle AgedRetrospective StudiesContrast Mediabiopsybreast cancerbreast compressioncontrast kinetic analysisdynamic contrast enhanced MRI

Identifiers

PMID27766710
PMCPMC5395340
OpenAlexW2532803838

What OpenQuestion holds

Textmetadata
LicenceTDM
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.