Ultrasound tomosynthesis: A new paradigm for quantitative imaging of the prostate

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Abstract

Biopsy under B-mode transrectal ultrasound (TRUS) is the gold standard for prostate cancer diagnosis. However,B-mode US shows only the boundary of the prostate,therefore biopsy is performed in a blind fashion,resulting in many false negatives. Although MRI or TRUS-MRI fusion is more sensitive and specific,it may not be readily available across a broad population,and may be cost prohibitive. In this paper,a limited-angle transmission US methodology is proposed,here called US tomosynthesis (USTS),for prostate imaging. This enables quantitative imaging of the prostate,such as generation of a speed of sound (SOS) map,which theoretically may improve detection,localization,or characterization of cancerous prostate tissue. Prostate USTS can be enabled by adding an abdominal probe aligned with the transrectal probe by utilizing a robotic arm. In this paper,we elaborate proposed methodology; then develop a setup and a technique to enable ex vivo USTS imaging of human prostate immediately after prostatectomy. Custom hardware and software were developed and implemented. Mock ex vivo prostate and lesions were made by filling a mold cavity with water,and adding a plastisol lesion. The time of flights were picked using a proposed center of mass method and corrected manually. The SOS map with a difference expectation-maximization reconstruction performed most accurately,with 2.69 %,0.23 %,0.06 % bias in estimating the SOS of plastisol,water,and mold respectively. Although USTS methodology requires further ex vivo validation,USTS has the potential to open up a new window in quantitative low-cost US imaging of the prostate which may meet a public health need.

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Aalamifar, F., Seifabadi, R., Bernardo, M., Negussie, A. H., Turkbey, B., Merino, M., … Boctor, E. M. (2016). Ultrasound tomosynthesis: A new paradigm for quantitative imaging of the prostate. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9900 LNCS, pp. 577–584). Springer Verlag. https://doi.org/10.1007/978-3-319-46720-7_67

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