Molecular photoacoustic imaging of targeted agents in vivo can be a valuable tool for biopsy guidance, tumor detection and delineation. Recently, our group has developed a prototype clinical, side looking, photoacoustic and ultrasonic system based on capacitive micro-machined ultrasound transducers. The system was used for imaging both fresh ex vivo pancreatic cancer samples labeled with functionalized IRDye-800 as well as in vivo trans-rectal imaging of prostate cancer patients with and without Indocyanine green contrast agent.
Beamforming algorithms were used to provide real-time imaging albeit their low contrast to background ratio. To improve the quality images, presented here is a model-based acoustic reconstruction technique. The model is adapted to a sector scanning convention common in ultrasonography, compensates for the effects of non-ideal element directivity, impulse response and uneven responsivity as well as the ultrasound’s time dependent gain and the medium’s acoustic attenuation. Despite the low element count and the very limited viewing angle of the transducer, this technique was capable of reconstructing high-quality photoacoustic images both ex vivo and in vivo with a significant increase in contrast compared to the commonly used Universal back-projection algorithm. For ex vivo imaging, the results are also compared with fluorescence imaging showing a high degree of correlation.
This study demonstrates the feasibility and the potential of the model based reconstruction approach for real-time visualization of contrast agents in vivo deep within the tissue, either intraoperatively or in routine imaging. Thus, such approach opens avenues for better cancer detection, diagnosis, treatment and monitoring.
Idan Steinberg, David Huland, Willemieke Tummers, Sri Rajasekhar (Raj) Kothapalli, and Sanjiv Gambhir, "A model-based acoustic reconstruction algorithm for deep tissue clinical photoacoustic imaging of cancerous tissues labeled with contrast agents (Conference Presentation)," Proc. SPIE 10494, Photons Plus Ultrasound: Imaging and Sensing 2018, 104942G (Presented at SPIE BiOS: January 31, 2018; Published: 15 March 2018); https://doi.org/10.1117/12.2291081.5752219218001.
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