Emerging quantitative ultrasound applications: From diagnosing disease to monitoring of therapy

Abstract

Ultrasound has traditionally been considered an imaging modality characterized by high spatial resolution but low contrast. Conventional ultrasonic imaging may be sensitive to the detection of anomalous tissue features, but the ability to classify these tissue features often lacks specificity. However, recent advances in quantitative ultrasound (QUS) have emerged which can improve diagnostics by providing new sources of image contrast and specific numbers tied to tissue state. QUS imaging can encompass a wide variety of techniques including spectral-based parameterization, elastography, flow estimation, and envelope statistics. 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 acoustic 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. In this talk, successful applications of QUS will be discussed demonstrating the ability of spectral-based QUS and envelope statistics approaches to improve medical diagnostics including cancer detection and classification of solid tumors in the breast or thyroids, grading of fatty liver disease and monitoring and assessment of therapy in solid tumors.