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Detection and grading of prostate cancer using temporal enhanced ultrasound: combining deep neural networks and tissue mimicking simulations. Int J Comput Assist Radiol Surg 2017 Aug;12(8):1293-1305

Date

06/22/2017

Pubmed ID

28634789

DOI

10.1007/s11548-017-1627-0

Scopus ID

2-s2.0-85021150139   12 Citations

Abstract

PURPOSE  : Temporal Enhanced Ultrasound (TeUS) has been proposed as a new paradigm for tissue characterization based on a sequence of ultrasound radio frequency (RF) data. We previously used TeUS to successfully address the problem of prostate cancer detection in the fusion biopsies. METHODS  : In this paper, we use TeUS to address the problem of grading prostate cancer in a clinical study of 197 biopsy cores from 132 patients. Our method involves capturing high-level latent features of TeUS with a deep learning approach followed by distribution learning to cluster aggressive cancer in a biopsy core. In this hypothesis-generating study, we utilize deep learning based feature visualization as a means to obtain insight into the physical phenomenon governing the interaction of temporal ultrasound with tissue. RESULTS  : Based on the evidence derived from our feature visualization, and the structure of tissue from digital pathology, we build a simulation framework for studying the physical phenomenon underlying TeUS-based tissue characterization. CONCLUSION  : Results from simulation and feature visualization corroborated with the hypothesis that micro-vibrations of tissue microstructure, captured by low-frequency spectral features of TeUS, can be used for detection of prostate cancer.

Author List

Azizi S, Bayat S, Yan P, Tahmasebi A, Nir G, Kwak JT, Xu S, Wilson S, Iczkowski KA, Lucia MS, Goldenberg L, Salcudean SE, Pinto PA, Wood B, Abolmaesumi P, Mousavi P

Author

Kenneth A. Iczkowski MD Professor in the Pathology department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Humans
Image-Guided Biopsy
Imaging, Three-Dimensional
Magnetic Resonance Imaging
Male
Neoplasm Staging
Neural Networks (Computer)
Prostatic Neoplasms
Sensitivity and Specificity
Ultrasonography, Interventional
jenkins-FCD Prod-411 e00897e83867fcfa48419861683711f8d99adb75