Evidence map›Paper›PMID 25698353›Full record

Observational studyEuropean radiology2015

Evaluation of Kinetic Entropy of Breast Masses Initially Found on MRI using Whole-lesion Curve Distribution Data: Comparison with the Standard Kinetic Analysis.

Akiko Shimauchi, Hiroyuki Abe, David V Schacht, Jian Yulei, Federico D Pineda, Sanaz A Jansen, Rajiv Ganesh, Gillian M Newstead

Abstract readComparative StudyObservational Study
PubMed Publisher
In one paragraph

Observational study in European radiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Correlation Between Enhancement Intensity in Contrast Enhancement Spectral Mammography and Types of Kinetic Curves in Magnetic Resonance Imaging.Medical science monitor : international medical journal of experimental and clinical research · 2020
    Article
  7. Article
  8. Article
  9. 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

8 authors.

Akiko ShimauchiDepartment of Radiology, University of Chicago, 5841 South Maryland Ave, MC 2026, Chicago, IL, 60637, USA, akikoshima@gmail.com.
Hiroyuki Abe
David V Schacht
Jian Yulei
Federico D Pineda
Sanaz A Jansen
Rajiv Ganesh
Gillian M Newstead

Funding

Computer-Aided Diagnosis of Breast Lesions in MammogramsR01CA092361 · NCI · UNIVERSITY OF CHICAGO · PI JIANG, YULEI · 2002 to 2013
$3.0M
Computer-Aided Diagnosis of Breast Lesions in MammogramsR56CA092361 · NCI · UNIVERSITY OF CHICAGO · PI JIANG, YULEI · 2008 to 2008
$303k
NCI NIH HHS CA092361
6 · The paper itself

Abstract

objectivesTo quantify kinetic heterogeneity of breast masses that were initially detected with dynamic contrast-enhanced MRI, using whole-lesion kinetic distribution data obtained from computer-aided evaluation (CAE), and to compare that with standard kinetic curve analysis.

methodsClinical MR images from 2006 to 2011 with breast masses initially detected with MRI were evaluated with CAE. The relative frequencies of six kinetic patterns (medium-persistent, medium-plateau, medium-washout, rapid-persistent, rapid-plateau, rapid-washout) within the entire lesion were used to calculate kinetic entropy (KE), a quantitative measure of enhancement pattern heterogeneity. Initial uptake (IU) and signal enhancement ratio (SER) were obtained from the most-suspicious kinetic curve. Mann-Whitney U test and ROC analysis were conducted for differentiation of malignant and benign masses.

resultsForty benign and 37 malignant masses comprised the case set. IU and SER were not significantly different between malignant and benign masses, whereas KE was significantly greater for malignant than benign masses (p = 0.748, p = 0.083, and p < 0.0001, respectively). Areas under ROC curve for IU, SER, and KE were 0.479, 0.615, and 0.662, respectively.

conclusionQuantification of kinetic heterogeneity of whole-lesion time-curve data with KE has the potential to improve differentiation of malignant from benign breast masses on breast MRI. KEY POINTS: • Kinetic heterogeneity can be quantified by computer-aided evaluation of breast MRI • Kinetic entropy was greater in malignant masses than benign masses • Kinetic entropy has the potential to improve differentiation of breast masses.

Indexed as

Breast NeoplasmsContrast MediaEntropyFemaleHumansImage Interpretation, Computer-AssistedKineticsMagnetic Resonance ImagingMiddle AgedRetrospective StudiesROC CurveStatistics, NonparametricContrast Media

Identifiers

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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.