Feature extraction of ultrasound radiofrequency data for the classification of the peripheral zone of human prostate

Teja Pathour; Ling Ma; Douglas W. Strand; Jeffrey Gahan; Brett A. Johnson; Shashank R. Sirsi; Baowei Fei

doi:10.1117/12.3008643

1 April 2024 Feature extraction of ultrasound radiofrequency data for the classification of the peripheral zone of human prostate

Teja Pathour, Ling Ma, Douglas W. Strand, Jeffrey Gahan, Brett A. Johnson, Shashank R. Sirsi, Baowei Fei

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Proceedings Volume 12932, Medical Imaging 2024: Ultrasonic Imaging and Tomography; 129321F (2024) https://doi.org/10.1117/12.3008643
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

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Abstract

Prostate cancer ranks among the most prevalent types of cancer in males, prompting a demand for early detection and non-invasive diagnostic techniques. This paper explores the potential of ultrasound radiofrequency (RF) data to study different anatomic zones of the prostate. The study leverages RF data's capacity to capture nuanced acoustic information from clinical transducers. The research focuses on the peripheral zone due to its high susceptibility to cancer. The feasibility of utilizing RF data for classification is evaluated using ex-vivo whole prostate specimens from human patients. Ultrasound data, acquired using a phased array transducer, is processed, and correlated with B-mode images. A range filter is applied to highlight the peripheral zone's distinct features, observed in both RF data and 3D plots. Radiomic features were extracted from RF data to enhance tissue characterization and segmentation. The study demonstrated RF data's ability to differentiate tissue structures and emphasizes its potential for prostate tissue classification, addressing the current limitations of ultrasound imaging for prostate management. These findings advocate for the integration of RF data into ultrasound diagnostics, potentially transforming prostate cancer diagnosis and management in the future.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Teja Pathour, Ling Ma, Douglas W. Strand, Jeffrey Gahan, Brett A. Johnson, Shashank R. Sirsi, and Baowei Fei "Feature extraction of ultrasound radiofrequency data for the classification of the peripheral zone of human prostate", Proc. SPIE 12932, Medical Imaging 2024: Ultrasonic Imaging and Tomography, 129321F (1 April 2024); https://doi.org/10.1117/12.3008643

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