Literature DB >> 32988673

Multiparametric Ultrasound for Targeting Prostate Cancer: Combining ARFI, SWEI, QUS and B-Mode.

D Cody Morris1, Derek Y Chan2, Theresa H Lye3, Hong Chen3, Mark L Palmeri2, Thomas J Polascik4, Wen-Chi Foo5, Jiaoti Huang5, Jonathan Mamou3, Kathryn R Nightingale2.   

Abstract

Diagnosing prostate cancer through standard transrectal ultrasound (TRUS)-guided biopsy is challenging because of the sensitivity and specificity limitations of B-mode imaging. We used a linear support vector machine (SVM) to combine standard TRUS imaging data with acoustic radiation force impulse (ARFI) imaging data, shear wave elasticity imaging (SWEI) data and quantitative ultrasound (QUS) midband fit data to enhance lesion contrast into a synthesized multiparametric ultrasound volume. This SVM was trained and validated using a subset of 20 patients and tested on a second subset of 10 patients. Multiparametric US led to a statistically significant improvements in contrast, contrast-to-noise ratio (CNR) and generalized CNR (gCNR) when compared with standard TRUS B-mode and SWEI; in contrast and CNR when compared with MF; and in CNR when compared with ARFI. ARFI, MF and SWEI also outperformed TRUS B-mode in contrast, with MF outperforming B-mode in CNR and gCNR as well. ARFI, although only yielding statistically significant differences in contrast compared with TRUS B-mode, captured critical qualitative features for lesion identification. Multiparametric US enhanced lesion visibility metrics and is a promising technique for targeted TRUS-guided prostate biopsy in the future.
Copyright © 2020 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Acoustic radiation force impulse imaging; Elasticity imaging; Midband fit; Multiparametric ultrasound; Prostate cancer; Shear wave elasticity imaging

Year:  2020        PMID: 32988673      PMCID: PMC7606559          DOI: 10.1016/j.ultrasmedbio.2020.08.022

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  3 in total

1.  Prostate Cancer Detection Using 3-D Shear Wave Elasticity Imaging.

Authors:  D Cody Morris; Derek Y Chan; Mark L Palmeri; Thomas J Polascik; Wen-Chi Foo; Kathryn R Nightingale
Journal:  Ultrasound Med Biol       Date:  2021-04-06       Impact factor: 3.694

2.  Machine learning prediction of prostate cancer from transrectal ultrasound video clips.

Authors:  Kai Wang; Peizhe Chen; Bojian Feng; Jing Tu; Zhengbiao Hu; Maoliang Zhang; Jie Yang; Ying Zhan; Jincao Yao; Dong Xu
Journal:  Front Oncol       Date:  2022-08-26       Impact factor: 5.738

3.  Clinically significant prostate cancer (csPCa) detection with various prostate sampling schemes based on different csPCa definitions.

Authors:  Fei Wang; Tong Chen; Meng Wang; Hanbing Chen; Caishan Wang; Peiqing Liu; Songtao Liu; Jing Luo; Qi Ma; Lijun Xu
Journal:  BMC Urol       Date:  2021-12-23       Impact factor: 2.264

  3 in total

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