Share Email Print

Proceedings Paper

Characterization of aggressive prostate cancer using ultrasound RF time series
Author(s): Amir Khojaste; Farhad Imani; Mehdi Moradi; David Berman; D. Robert Siemens; Eric E. Sauerberi; Alexander H. Boag; Purang Abolmaesumi; Parvin Mousavi
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Prostate cancer is the most prevalently diagnosed and the second cause of cancer-related death in North American men. Several approaches have been proposed to augment detection of prostate cancer using different imaging modalities. Due to advantages of ultrasound imaging, these approaches have been the subject of several recent studies. This paper presents the results of a feasibility study on differentiating between lower and higher grade prostate cancer using ultrasound RF time series data. We also propose new spectral features of RF time series to highlight aggressive prostate cancer in small ROIs of size 1 mm × 1 mm in a cohort of 19 ex vivo specimens of human prostate tissue. In leave-one-patient-out cross-validation strategy, an area under accumulated ROC curve of 0.8 has been achieved with overall sensitivity and specificity of 81% and 80%, respectively. The current method shows promising results on differentiating between lower and higher grade of prostate cancer using ultrasound RF time series.

Paper Details

Date Published: 20 March 2015
PDF: 8 pages
Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 94141A (20 March 2015); doi: 10.1117/12.2082663
Show Author Affiliations
Amir Khojaste, Queen's Univ. (Canada)
Farhad Imani, Queen's Univ. (Canada)
Mehdi Moradi, The Univ. of British Columbia (Canada)
David Berman, Kingston General Hospital (Canada)
D. Robert Siemens, Kingston General Hospital (Canada)
Eric E. Sauerberi, Kingston General Hospital (Canada)
Alexander H. Boag, Kingston General Hospital (Canada)
Purang Abolmaesumi, The Univ. of British Columbia (Canada)
Parvin Mousavi, Queen's Univ. (Canada)

Published in SPIE Proceedings Vol. 9414:
Medical Imaging 2015: Computer-Aided Diagnosis
Lubomir M. Hadjiiski; Georgia D. Tourassi, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?