Pulse-echo quantitative ultrasound (QUS) is a well-established research field. Studies have demonstrated the diagnostic values of QUS features in a wide range of clinical and preclinical applications. In the past ten years, major medical ultrasound companies have introduced commercial implementations of QUS features motivated by their potential as indicators of fatty liver disease.
Despite the increasing interest in QUS, important challenges remain, most importantly the need to compensate for the effects of intervening tissues between the transducer and the tissue of interest. To address these challenges, novel QUS methods have been investigated to improve the compensation for total attenuation along the acoustic path and to reduce the effects of aberration through estimation of the speed of sound.
Numerous algorithms and methods exist, and the time has come to compare and evaluate them in a rigorous matter. The proposed challenge will provide (i) a wide platform to bring together research efforts from laboratories across the globe and (ii) a framework to compare the QUS algorithms developed by these laboratories in a uniform and standardized manner. Based on ultrasound data generated from realistic simulations and acquired from phantoms with known acoustical properties, participants will compete to develop the most accurate and precise methods (in terms of bias and variance) and with the best lesion detectability.
OBJECTIVES
Overall Goal: Provide a uniform framework to compare the performance of different attenuation and speed of sound estimation algorithms over a wide range of expected values.
- Specific objective 1: Identify the algorithms that provide the most accurate and precise estimates of the attenuation coefficient and speed of sound over a wide range of conditions using radio-frequency (RF) data from computational and experimental phantoms.
- Specific objective 2: Identify the algorithms that provide the best lesion detectability, i.e., able to detect the smallest spatial variation of attenuation or speed of sound.
- Specific objective 3: Identify the algorithms that provide the most robust estimates of attenuation and speed of sound to the presence of near-field aberration.
Organizers
Assistant Professor, Departments of Medical Physics and Radiology, University of Wisconsin-Madison
Instructor of Biomedical Engineering, Department of Radiology, Weill Cornell Medicine
Assistant Professor, Department of Biomedical Engineering and Mechanics, Virginia Tech
Professor of Electrical Engineering, Department of Radiology, Weill Cornell Medicine
REGISTRATION (Coming soon)
ACCESS TO DATA (Coming soon)
SPONSORS
AIUM / QMIC – Pulse Echo Quantitative Ultrasound Biomarker Committee