| Literature DB >> 32988673 |
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.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