Evidence map›Paper›PMID 28004162›Full record

ArticleEuropean radiology2017

Multiparametric dynamic contrast-enhanced ultrasound imaging of prostate cancer.

Rogier R Wildeboer, Arnoud W Postema, Libertario Demi, Maarten P J Kuenen, Hessel Wijkstra, Massimo Mischi

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Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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  9. Interpretable Machine Learning for Characterization of Focal Liver Lesions by Contrast-Enhanced Ultrasound.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2022
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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

6 authors.

Rogier R WildeboerLaboratory of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, PO-Box 513, 5600 MB, Eindhoven, The Netherlands. r.r.wildeboer@tue.nl.
Arnoud W PostemaDepartment of Urology, Academic Medical Center University Hospital, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
Libertario DemiLaboratory of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, PO-Box 513, 5600 MB, Eindhoven, The Netherlands.
Maarten P J KuenenPhilips Research, Philips, Eindhoven, The Netherlands.
Hessel WijkstraLaboratory of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, PO-Box 513, 5600 MB, Eindhoven, The Netherlands.
Massimo MischiLaboratory of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, PO-Box 513, 5600 MB, Eindhoven, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe aim of this study is to improve the accuracy of dynamic contrast-enhanced ultrasound (DCE-US) for prostate cancer (PCa) localization by means of a multiparametric approach. MATERIALS AND

methodsThirteen different parameters related to either perfusion or dispersion were extracted pixel-by-pixel from 45 DCE-US recordings in 19 patients referred for radical prostatectomy. Multiparametric maps were retrospectively produced using a Gaussian mixture model algorithm. These were subsequently evaluated on their pixel-wise performance in classifying 43 benign and 42 malignant histopathologically confirmed regions of interest, using a prostate-based leave-one-out procedure.

resultsThe combination of the spatiotemporal correlation (r), mean transit time (μ), curve skewness (κ), and peak time (PT) yielded an accuracy of 81% ± 11%, which was higher than the best performing single parameters: r (73%), μ (72%), and wash-in time (72%). The negative predictive value increased to 83% ± 16% from 70%, 69% and 67%, respectively. Pixel inclusion based on the confidence level boosted these measures to 90% with half of the pixels excluded, but without disregarding any prostate or region.

conclusionsOur results suggest multiparametric DCE-US analysis might be a useful diagnostic tool for PCa, possibly supporting future targeting of biopsies or therapy. Application in other types of cancer can also be foreseen. KEY POINTS: • DCE-US can be used to extract both perfusion and dispersion-related parameters. • Multiparametric DCE-US performs better in detecting PCa than single-parametric DCE-US. • Multiparametric DCE-US might become a useful tool for PCa localization.

Indexed as

Contrast MediaAgedAlgorithmsEarly Detection of CancerHumansImage Interpretation, Computer-AssistedMaleMiddle AgedPredictive Value of TestsProstatectomyProstatic NeoplasmsRetrospective StudiesSensitivity and SpecificityUltrasonographyContrast MediaClassificationContrast agentsMultiparametric imagingProstate cancerUltrasound

Identifiers

PMID28004162
PMCPMC5491563

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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.