Evidence map›Paper›PMID 28894997›Full record

ArticleMagma (New York, N.Y.)2018

A novel framework for evaluating the image accuracy of dynamic MRI and the application on accelerated breast DCE MRI.

Yuan Le, Marcel Dominik Nickel, Stephan Kannengiesser, Berthold Kiefer, Bruce Spottiswoode, Brian Dale, Victor Soon, Chen Lin

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Article in Magma (New York, N.Y.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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.

Yuan LeDepartment of Radiology and Imaging Science, Indiana University School of Medicine, 950 West Walnut St. R2 E124, Indianapolis, IN, 46202, USA.
Marcel Dominik NickelSiemens Healthcare, Erlangen, Germany.
Stephan KannengiesserSiemens Healthcare, Erlangen, Germany.
Berthold KieferSiemens Healthcare, Erlangen, Germany.
Bruce SpottiswoodeSiemens Medical Solutions USA Inc, Malven, PA, USA.
Brian DaleSiemens Medical Solutions USA Inc, Malven, PA, USA.
Victor SoonDepartment of Radiology and Imaging Science, Indiana University School of Medicine, 950 West Walnut St. R2 E124, Indianapolis, IN, 46202, USA.
Chen LinDepartment of Radiology and Imaging Science, Indiana University School of Medicine, 950 West Walnut St. R2 E124, Indianapolis, IN, 46202, USA. clin1@iupui.edu.ORCID http://orcid.org/0000-0002-6146-7347

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop a novel framework for evaluating the accuracy of quantitative analysis on dynamic contrast-enhanced (DCE) MRI with a specific combination of imaging technique, scanning parameters, and scanner and software performance and to test this framework with breast DCE MRI with Time-resolved angiography WIth Stochastic Trajectories (TWIST). MATERIALS AND

methodsRealistic breast tumor phantoms were 3D printed as cavities and filled with solutions of MR contrast agent. Full k-space raw data of individual tumor phantoms and a uniform background phantom were acquired. DCE raw data were simulated by sorting the raw data according to TWIST view order and scaling the raw data according to the enhancement based on pharmaco-kinetic (PK) models. The measured spatial and temporal characteristics from the images reconstructed using the scanner software were compared with the original PK model (ground truth).

resultsImages could be reconstructed using the manufacturer's platform with the modified 'raw data.' Compared with the 'ground truth,' the RMS error in all images was <10% in most cases. With increasing view-sharing acceleration, the error of the initial uptake slope decreased while the error of peak enhancement increased. Deviations of PK parameters varied with the type of enhancement.

conclusionA new framework has been developed and tested to more realistically evaluate the quantitative measurement errors caused by a combination of the imaging technique, parameters and scanner and software performance in DCE-MRI.

Indexed as

Magnetic Resonance ImagingAccelerationAlgorithmsBreastBreast NeoplasmsComputer SimulationContrast MediaFemaleHumansImage EnhancementImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedModels, StatisticalParticle SizePhantoms, ImagingReproducibility of ResultsContrast MediaBreast imagingDCE-MRISimulationTumor modelView-sharing acceleration

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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.