Acoustomotive diffuse correlation spectroscopy for sensing mechanical stiffness in tissue-mimicking phantoms

Area of Science:

• Biomedical Optics
• Medical Physics
• Tissue Mechanics

Background:

• Disease-induced alterations in tissue mechanical stiffness are common indicators for conditions like inflammation, dropsy, and tumors.
• Current clinical stiffness assessment relies on ultrasound, while optical methods offer potential for microcirculatory and strain analysis.
• Diffuse correlation spectroscopy (DCS) detects enhanced scatterer motion from acoustic radiation force (ARF), theoretically linked to tissue stiffness.

Purpose of the Study:

• To develop and validate a novel optical technique combining ARF and DCS for qualitative evaluation of tissue stiffness changes.
• To assess the accuracy and feasibility of the acoustomotive DCS (AM-DCS) technique in homogeneous and heterogeneous phantoms.
• To explore AM-DCS's potential in differentiating between fluid-filled lesions and homogeneous tissues.

Main Methods:

• A light coherent technique integrating acoustic radiation force (ARF) with diffuse correlation spectroscopy (DCS) was developed.
• The technique, termed acoustomotive DCS (AM-DCS), measures enhanced scatterer motion induced by ARF to infer stiffness.
• Experimental validation involved homogeneous phantoms compared against ultrasound methods and heterogeneous phantoms for lesion differentiation.

Main Results:

• The accuracy and feasibility of AM-DCS for probing stiffness in homogeneous phantoms were experimentally demonstrated.
• Comparison with independent ultrasound methods confirmed the technique's reliability.
• Heterogeneous phantom experiments showed potential for distinguishing fluid-filled lesions from normal tissue.

Conclusions:

• The developed acoustomotive DCS (AM-DCS) technique provides a novel optical method for measuring particle-motion related stiffness.
• AM-DCS offers a promising alternative for assessing tissue mechanical properties, complementing existing diagnostic tools.
• This technique has potential applications in disease diagnosis and treatment monitoring by evaluating tissue physiopathology.