Tech Exchange with VisualSonics

The first Tech Exchange in 2025 - with our Industry Board member FUJIFILM VisualSonics!

Jithin Jose, Global Market Leader Photoacoustics, will talk about "Recent Advances in Hybrid Ultrasound and Photoacoustic Imaging: Progress, Challenges, and Future Directions".

Non-invasive, longitudinal assessment of tumor progression is essential for monitoring dynamic changes in tissue composition under therapeutic conditions. Current hybrid imaging modalities, combining micro-ultrasound (US) and photoacoustic (PA) imaging, offer a powerful platform for extracting anatomical, functional, and molecular information from tumors. Conventionally, this platform enables the visualization and quantification of key parameters such as vascularity, perfusion, hemodynamics, and volumetrics. These multimodal capabilities provide invaluable insights into tumor progression and therapy response. However, the inclusion of mechanical property assessment, with its critical implication in drug delivery, can significantly enhance the ability not only to evaluate but also predict therapeutic outcomes.

Shear wave elastography (SWE) is an established clinical technique for assessing the mechanical properties of tissues by measuring stiffness. In clinical settings, SWE typically employs low-frequency ultrasound (<10 MHz) and is predominantly utilized to evaluate liver stiffness for fibrosis assessment and tumor detection. Despite its clinical utility, the application of high-quality SWE in pre-clinical research remains limited due to the lack of suitable platforms capable of combining ultrafast plane wave SWE acquisition with high spatial resolution.

Here, we introduce a novel hybrid US-PA imaging platform that integrates high-frequency SWE specifically designed for pre-clinical research applications. This platform is particularly advantageous for small animal imaging as it enables non-invasive, real time, and high-resolution imaging of tissue properties such as tissue stiffness and Young's modulus. By combining these mechanical insights with functional and molecular data, this approach bridges critical gaps in the assessment of tumor progression and translation of therapeutic efficacy to the clinic.

To complete the full non-invasive assessment of tumor properties, we present the development and integration of an AI-assisted algorithm to enhance the automated analysis of spectral photoacoustic imaging data. This advanced algorithm facilitates the extraction of tissue chromophores, enabling precise quantification of molecular markers within the tumor, including but not limited to pancreas, prostate, breast, liver, ovarian skin, and brain tumors. The synergy of high-frequency SWE and AI-assisted automated spectral photoacoustic imaging represents a significant advancement in non-invasive imaging, providing a comprehensive toolset for the detailed characterization of tumor progression and the user independent evaluation of therapeutic responses in pre-clinical research models.