Paper
17 March 2015 Parametric imaging of tumor perfusion and neovascular morphology using ultrasound
Kenneth Hoyt
Author Affiliations +
Abstract
A new image processing strategy is detailed for the simultaneous measurement of tumor perfusion and neovascular morphology parameters from a sequence of dynamic contrast-enhanced ultrasound (DCE-US) images. A technique for locally mapping tumor perfusion parameters using skeletonized neovascular data is also introduced. Simulated images were used to test the neovascular skeletonization technique and variance (error) of relevant parametric estimates. Preliminary DCE-US image datasets were collected in 6 female patients diagnosed with invasive breast cancer and using a Philips iU22 ultrasound system equipped with a L9-3 MHz transducer and Definity contrast agent. Simulation data demonstrates that neovascular morphology parametric estimation is reproducible albeit measurement error can occur at a lower signal-to-noise ratio (SNR). Experimental results indicate the feasibility of our approach to performing both tumor perfusion and neovascular morphology measurements from DCE-US images. Future work will expand on our initial clinical findings and also extent our image processing strategy to 3-dimensional space to allow whole tumor characterization.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kenneth Hoyt "Parametric imaging of tumor perfusion and neovascular morphology using ultrasound", Proc. SPIE 9419, Medical Imaging 2015: Ultrasonic Imaging and Tomography, 941911 (17 March 2015); https://doi.org/10.1117/12.2081541
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KEYWORDS
Tumors

Signal to noise ratio

Image processing

Ultrasonography

Image segmentation

Breast cancer

Error analysis

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