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Medical Physics Seminar – Monday, November 11, 2013

Emerging Quantitative Ultrasound Applications for Medical Diagnostics: From Assessing Liver Disease to Diagnosing Cancer to Monitoring of Therapy

Michael L. Oelze, PhD.(guest of Dr. Tim Hall)
Associate Professor, Department of Electrical & Computer Engineering, Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL

Conventional imaging techniques, e.g. MRI, X-Ray CT, ultrasound, etc., may be sensitive to the detection of anomalous tissue features, but the ability to classify these tissue features often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. In order to improve specificity of image findings, it is necessary to employ quantitative imaging techniques. Quantitative ultrasound (QUS) imaging techniques can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging can encompass a wide variety of techniques including spectral-based parameterization, elastography, flow estimation and envelope statistics. Furthermore, a goal of QUS imaging techniques is to provide system- and operator-independent parameters related to tissue properties. QUS imaging techniques have been employed to improve diagnostic ultrasound and monitoring of therapy. Specifically, spectral-based techniques and envelope statistics at clinical frequencies and at high ultrasonic frequencies (> 15 MHz) have been examined for their abilities to improve diagnostic ultrasound and monitor therapy. Spectral-based techniques include the estimation of the backscatter coefficient, estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer size and the concentration of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and implementation of QUS on clinical devices. Successful applications demonstrating the ability of QUS to improve medical diagnostics include cancer detection and classification of solid tumors and lymph nodes, detection and quantification of fatty liver disease, and monitoring and assessment of therapy in solid tumors.

Location: 1345 (HSLC) Health Sciences Learning Center, 750 Highland Avenue, Madison, WI

Time: 4:00pm-5:00pm



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