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15 March 2019 Correlation of ultrasound tomography to MRI and pathology for the detection of prostate cancer
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Abstract
Purpose: This study aims to investigate correlation of speed of sound (SoS) map with T2-weighted (T2w) MRI and pathology in an ex vivo human prostate tissue with cancer, as an early proof of concept towards cost effective augmented ultrasound diagnosis of prostate cancer. Method: A commercial breast full angle ultrasound tomography scanner was used to generate US tomography images. Prostate-specific Echolucent mold was fabricated to allow MRI and UST to be spatially correlated. Similarly, a 3D printed mold was developed to align the histology slices with the UST and MRI. The resulting slices of prostate tissue were H and E stained. A radiologist with 10 years of experience in using multi parametric MRI for prostate cancer diagnosis labeled and contoured the suspicious ROIs in both MRI and UST. For all tissue blocks (N=10 slices with 6 mm thickness), H and E slides were prepared and labeled by an expert pathologist. Results: The radiologist found two slices with prominent cancer in each modality (i.e. MR and UST) in the peripheral zone. These two pairs of slices correlated with each other and with slices #5 and #7 in pathology. The cancer ROIs were found at similar locations in all modalities, although MR and UST underestimated the size of lesions (Sørensen–Dice coefficients, with respect to pathology, for T2w and UST were 0.11 and 0.20 respectively for first ROI, and 0.33 and 0.27 for second ROI). The SoS was 1580.4±17.7 m/s and 1571.4±9.2 m/s for normal and cancer tissues in first ROI, and 1577.7±17.7 m/s and 1574.5±10.1 m/s for second ROI. Conclusions: SoS map can correlate with MRI and pathology findings in prostate cancer. Further ex vivo validation with fresh prostate tissue is warranted.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Reza Seifabadi, Alexis Cheng, Bilal Malik, Shun Kishimoto, James Wiskin, Jeeva Munasinghe, Ayele H. Negussie, Ivane Bakhutashvili, Murali C. Krishna, Peter Choyke, Peter Pinto, Arman Rahmim, Emad M. Boctor, Maria Merino, Mark Lenox, Baris Turkbey, and Bradford J. Wood "Correlation of ultrasound tomography to MRI and pathology for the detection of prostate cancer", Proc. SPIE 10955, Medical Imaging 2019: Ultrasonic Imaging and Tomography, 109550C (15 March 2019); https://doi.org/10.1117/12.2512001
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