Comparative study of lesion detection methods in complex scattering media using quantitative ultrasound

Classical ultrasound imaging often fails in media with significant multiple scattering, such as lung tissue, where air-filled alveoli strongly scatter the sound waves. As a result, there is a need for alternative approaches capable of detecting nodules within such complex scattering environments. However, ultrasound is particularly suited for surgical guidance due to its real time and non-ionizing characteristics. Several techniques in quantitative ultrasound have been developed to address this challenge, including the separation of single and multiple scattering components, comparison against the Quarter Circle Law (QCL), diffusion constant analysis, and entropy-based methods, among others. While each of these techniques offers distinct advantages, they also come with limitations. This study focuses on a comparative evaluation of these methods. We specifically study sensitivity to lung aeration, and the impact on scattering and the wave’s “memory” for the detection of deeper nodules. The goal is to better understand the strengths and weaknesses of each approach and, ultimately, to work toward a more reliable method that can guide real-time ultrasound monitoring of lung nodules during surgery.