3-D Multi-parametric Contrast-Enhanced Ultrasound for the Prediction of Prostate Cancer.
3-D
Contrast ultrasound dispersion imaging
Dynamic contrast-enhanced ultrasound
Machine learning
Prostate cancer
Systematic biopsy
Journal
Ultrasound in medicine & biology
ISSN: 1879-291X
Titre abrégé: Ultrasound Med Biol
Pays: England
ID NLM: 0410553
Informations de publication
Date de publication:
10 2019
10 2019
Historique:
received:
30
01
2019
revised:
23
04
2019
accepted:
16
05
2019
pubmed:
14
7
2019
medline:
13
5
2020
entrez:
14
7
2019
Statut:
ppublish
Résumé
Trans-rectal ultrasound-guided 12-core systematic biopsy (SBx) is the standard diagnostic pathway for prostate cancer (PCa) because of a lack of sufficiently accurate imaging. Quantification of 3-D dynamic contrast-enhanced ultrasound (US) might open the way for a targeted procedure in which biopsies are directed at lesions suspicious on imaging. This work describes the expansion of contrast US dispersion imaging algorithms to 3-D and compares its performance against malignant and benign disease. Furthermore, we examined the feasibility of a multi-parametric approach to predict SBx-core outcomes using machine learning. An area under the receiver operating characteristic (ROC) curve of 0.76 and 0.81 was obtained for all PCa and significant PCa, respectively, an improvement over previous US methods. We found that prostatitis, in particular, was a source of false-positive readings.
Identifiants
pubmed: 31300222
pii: S0301-5629(19)30225-X
doi: 10.1016/j.ultrasmedbio.2019.05.017
pii:
doi:
Substances chimiques
Contrast Media
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2713-2724Informations de copyright
Copyright © 2019 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.