Multiparametric dynamic contrast-enhanced ultrasound imaging of prostate cancer.
Objectives: The 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 Methods: Thirteen different parameters related to either perfusion or dispersion were extracted pi...
| Published in: | European Radiology Vol. 27; no. 8; pp. 3226 - 3235 |
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| Main Authors: | , , , , , , , , |
| Format: | diagnostic images research tables/charts Journal Article |
| Published: |
Springer Nature
Aug2017
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=123837866&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 123837866 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Aug2017 vid: 27 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 123837866 123837866 144094781 NLM28004162 123837866 10.1007/s00330-016-4693-8 NLM28004162 123837866 ppf: 3226 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Multiparametric dynamic contrast-enhanced ultrasound imaging of prostate cancer. aug: au: Wildeboer, Rogier Postema, Arnoud Demi, Libertario Kuenen, Maarten Wijkstra, Hessel Mischi, Massimo Wildeboer, Rogier R Postema, Arnoud W Kuenen, Maarten P J affil: Laboratory of Biomedical Diagnostics, Department of Electrical Engineering , Eindhoven University of Technology , 5600 MB Eindhoven The Netherlands sug: subj: Prostatic Neoplasms Ultrasonography Methods Image Interpretation, Computer Assisted Methods Contrast Media Administration and Dosage Male Algorithms Middle Age Retrospective Design Prostatectomy Prostatic Neoplasms Pathology Early Detection of Cancer Methods Predictive Value of Tests Aged Sensitivity and Specificity Human Middle Aged: 45-64 years Aged: 65+ years Male ab: Objectives: The 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 Methods: Thirteen 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.Results: The 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.Conclusions: Our 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. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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