Recent results in nonlinear strain and modulus imaging.

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Cancer Research

Background:

• Clinical ultrasound imaging is crucial for cancer diagnosis and treatment monitoring.
• Accurate quantification of in vivo tissue mechanical properties, especially nonlinear strain, is challenging but vital for improving diagnostic capabilities.

Purpose of the Study:

• To report recent developments and the current status of imaging and quantifying in vivo nonlinear strain and tissue mechanical properties.
• To focus on applications in cancer diagnosis and treatment using clinical ultrasound and quasi-static tissue deformations.

Main Methods:

• Developed and reviewed advanced displacement estimation techniques from ultrasound image sequences, including cross-correlation, regularized optimization, guided search, multiscale, and hybrid methods.
• Compared various strain estimators, highlighting the benefits of regularized optimization approaches.
• Discussed direct and iterative methods for reconstructing tissue mechanical property distributions from strain and displacement fields, considering formulation, discretization, and algorithmic aspects.

Main Results:

• Achieved high accuracy in both axial and lateral displacement estimations at several frames per second.
• Demonstrated quantitative determination of nonlinear elastic properties in phantoms and in vivo using 2D models and data.
• Successfully applied methods to breast disease diagnosis and tumor ablation monitoring.

Conclusions:

• Current methods enable accurate, real-time quantification of nonlinear tissue mechanics using clinical ultrasound.
• Future work will incorporate 3D data from 2D transducer arrays to create calibrated 3D quantitative maps of nonlinear elastic properties of breast tissues in vivo.