Evidence map›Paper›PMID 27008431›Full record

ArticleJournal of magnetic resonance imaging : JMRI2016

Variability and bias assessment in breast ADC measurement across multiple systems.

Kathryn E Keenan, Adele P Peskin, Lisa J Wilmes, Sheye O Aliu, Ella F Jones, Wen Li, John Kornak, David C Newitt, Nola M Hylton

Abstract readComparative StudyEvaluation Study
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

16 citing papers in PubMed, 33 citations in OpenAlex.

  1. Additive value of diffusion-weighted MRI in the I-SPY 2 TRIAL.Journal of magnetic resonance imaging : JMRI · 2019
    Trial
  2. Article
  3. Article
  4. Quantitative MR Imaging of the Breast.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    Review
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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

9 authors at 3 institutions in 1 country.

Kathryn E KeenanPhysical Measurement Laboratory, National Institute of Standards and Technology, Boulder, Colorado, USA. kathryn.keenan@nist.gov.
Adele P PeskinPhysical Measurement Laboratory, National Institute of Standards and Technology, Boulder, Colorado, USA.
Lisa J WilmesDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
Sheye O AliuDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
Ella F JonesDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
Wen LiDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
John KornakDepartment of Epidemiology and Biostatistics, University of California, San Francisco, California, USA.
David C NewittDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
Nola M HyltonDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
University of California, San Francisco · USUniversity of California System · USPhysical Measurement Laboratory · US

Funding

Quantitative Imaging for Assessing Breast Cancer Response to TreatmentU01CA151235 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HYLTON-WATSON, NOLA M. · 2011 to 2015
$2.8M
NCI NIH HHS U01 CA151235
6 · The paper itself

Abstract

purposeTo assess the ability of a recent, anatomically designed breast phantom incorporating T1 and diffusion elements to serve as a quality control device for quantitative comparison of apparent diffusion coefficient (ADC) measurements calculated from diffusion-weighted MRI (DWI) within and across MRI systems. MATERIALS AND

methodsA bilateral breast phantom incorporating multiple T1 and diffusion tissue mimics and a geometric distortion array was imaged with DWI on 1.5 Tesla (T) and 3.0T scanners from two different manufacturers, using three different breast coils (three configurations total). Multiple measurements were acquired to assess the bias and variability of different diffusion weighted single-shot echo-planar imaging sequences on the scanner-coil systems.

resultsThe repeatability of ADC measurements was mixed: the standard deviation relative to baseline across scanner-coil-sequences ranged from low variability (0.47, 95% confidence interval [CI]: 0.22-1.00) to high variability (1.69, 95% CI: 0.17-17.26), depending on material, with the lowest and highest variability from the same scanner-coil-sequence. Assessment of image distortion showed that right/left measurements of the geometric distortion array were 1 to 16% larger on the left coil side compared with the right coil side independent of scanner-coil systems, diffusion weighting, and phase-encoding direction.

conclusionThis breast phantom can be used to measure scanner-coil-sequence bias and variability for DWI. When establishing a multisystem study, this breast phantom may be used to minimize protocol differences (e.g., due to available sequences or shimming technique), to correct for bias that cannot be minimized, and to weigh results from each system depending on respective variability. J. Magn. Reson. Imaging 2016. J. MAGN. RESON. IMAGING 2016;44:846-855.

Indexed as

ArtifactsPhantoms, ImagingEquipment DesignEquipment Failure AnalysisFemaleHumansImage Interpretation, Computer-AssistedMagnetic Resonance ImagingReproducibility of ResultsSensitivity and Specificityapparent diffusion coefficientbreast MRIEPIphantomsquality controltissue mimic

Identifiers

PMID27008431
PMCPMC5098898
OpenAlexW2305582452

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.