Characterization of aggressive prostate cancer using ultrasound RF time series

Amir Khojaste; Farhad Imani; Mehdi Moradi; David Berman; D. Robert Siemens; Eric E. Sauerberi; Alexander H. Boag; Purang Abolmaesumi; Parvin Mousavi

doi:10.1117/12.2082663

Characterization of aggressive prostate cancer using ultrasound RF time series

Amir Khojaste, Farhad Imani, Mehdi Moradi, David Berman, D. Robert Siemens, Eric E. Sauerberi, Alexander H. Boag, Purang Abolmaesumi, Parvin Mousavi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

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.

Original language	English (US)
Title of host publication	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Publisher	SPIE
Volume	9414
ISBN (Print)	9781628415049
DOIs	https://doi.org/10.1117/12.2082663
State	Published - 2015
Externally published	Yes
Event	SPIE Medical Imaging Symposium 2015: Computer-Aided Diagnosis - Orlando, United States Duration: Feb 22 2015 → Feb 25 2015

Other

Other	SPIE Medical Imaging Symposium 2015: Computer-Aided Diagnosis
Country/Territory	United States
City	Orlando
Period	2/22/15 → 2/25/15

Keywords

Prostate cancer
RF time series
Tissue classification
Ultrasound RF data

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics
Electronic, Optical and Magnetic Materials
Biomaterials
Radiology Nuclear Medicine and imaging

Access to Document

10.1117/12.2082663

Cite this

Khojaste, A, Imani, F, Moradi, M, Berman, D, Siemens, DR, Sauerberi, EE, Boag, AH, Abolmaesumi, P & Mousavi, P 2015, Characterization of aggressive prostate cancer using ultrasound RF time series. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 9414, 94141A, SPIE, SPIE Medical Imaging Symposium 2015: Computer-Aided Diagnosis, Orlando, United States, 2/22/15. https://doi.org/10.1117/12.2082663

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title = "Characterization of aggressive prostate cancer using ultrasound RF time series",

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.",

keywords = "Prostate cancer, RF time series, Tissue classification, Ultrasound RF data",

author = "Amir Khojaste and Farhad Imani and Mehdi Moradi and David Berman and Siemens, {D. Robert} and Sauerberi, {Eric E.} and Boag, {Alexander H.} and Purang Abolmaesumi and Parvin Mousavi",

year = "2015",

doi = "10.1117/12.2082663",

language = "English (US)",

isbn = "9781628415049",

volume = "9414",

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note = "SPIE Medical Imaging Symposium 2015: Computer-Aided Diagnosis ; Conference date: 22-02-2015 Through 25-02-2015",

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AU - Khojaste, Amir

AU - Imani, Farhad

AU - Moradi, Mehdi

AU - Berman, David

AU - Siemens, D. Robert

AU - Sauerberi, Eric E.

AU - Boag, Alexander H.

AU - Abolmaesumi, Purang

AU - Mousavi, Parvin

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - Prostate cancer

KW - RF time series

KW - Tissue classification

KW - Ultrasound RF data

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DO - 10.1117/12.2082663

M3 - Conference contribution

AN - SCOPUS:84948808621

SN - 9781628415049

VL - 9414

BT - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

PB - SPIE

T2 - SPIE Medical Imaging Symposium 2015: Computer-Aided Diagnosis

Y2 - 22 February 2015 through 25 February 2015

ER -

Characterization of aggressive prostate cancer using ultrasound RF time series

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Keywords

ASJC Scopus subject areas

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