Ultrasound RF time series for tissue typing: first in vivo clinical results

Mehdi Moradi; S. Sara Mahdavi; Guy Nir; Edward C. Jones; S. Larry Goldenberg; Septimiu E. Salcudean

doi:10.1117/12.2007672

18 March 2013 Ultrasound RF time series for tissue typing: first in vivo clinical results

Mehdi Moradi, S. Sara Mahdavi, Guy Nir, Edward C. Jones, S. Larry Goldenberg, Septimiu E. Salcudean

Author Affiliations +

Proceedings Volume 8670, Medical Imaging 2013: Computer-Aided Diagnosis; 86701I (2013) https://doi.org/10.1117/12.2007672
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

The low diagnostic value of ultrasound in prostate cancer imaging has resulted in an effort to enhance the tumor contrast using ultrasound-based technologies that go beyond traditional B-mode imaging. Ultrasound RF time series, formed by echo samples originating from the same location over a few seconds of imaging, has been proposed and experimentally used for tissue typing with the goal of cancer detection. In this work, for the first time we report the preliminary results of in vivo clinical use of spectral parameters extracted from RF time series in prostate cancer detection. An image processing pipeline is designed to register the ultrasound data to wholemount histopathology references acquired from prostate specimens that are removed in radical prostatectomy after imaging. Support vector machine classification is used to detect cancer in 524 regions of interest of size 5×5 mm, each forming a feature vector of spectral RF time series parameters. Preliminary ROC curves acquired based on RF time series analysis for individual cases, with leave-one-patient-out cross validation, are presented and compared with B-mode texture analysis.

Citation Download Citation

Mehdi Moradi, S. Sara Mahdavi, Guy Nir, Edward C. Jones, S. Larry Goldenberg, and Septimiu E. Salcudean "Ultrasound RF time series for tissue typing: first in vivo clinical results", Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86701I (18 March 2013); https://doi.org/10.1117/12.2007672

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