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Photoacoustic tomography (PAT) is a noninvasive, high-resolution imaging modality, capable of providing functional and molecular information of various pathologies such as cancer. In most PAT systems, the effect of tissue heterogeneity (i.e. variations in acoustic properties such as speed of sound and acoustic attenuation) is neglected. This is due to the lack of information about acoustic properties of tissue and complexity of a model to compensate for these variations. We have been developing a full-ring PAT system consists of an omni-directional illumination and a ring-based acoustic detection. In this study, we investigate using a model-based method that employs light diffusion (Monte-carlo) and acoustic wave propagation (K-wave) to compensate for both optical and acoustic heterogeneity of the tissue and provide fully compensated (i.e. quantitative) PAT images for our full-ring PAT system. To demonstrate the feasibility of providing fully compensated PAT images, in silico studies were performed in which a heterogeneous breast-tissue-mimicking phantoms were computationally generated. The map includes optical (µa, µs, g) and acoustic properties (ρ, Cs) of the fatty, fibroglandular and breast lesions. The monte-carlo light diffusion model was first utilized to generate the fluence map and thus the initial photoacoustic pressure fields (P0) within the tissue. Following to the generation of P0, the propagation of acoustic waves through a heterogeneous medium was simulated using K-wave. Using a ring-geometry ultrasound transducers (N=256), the pressure waves were received and were utilized to reconstruct PAT images. Our results indicate the PAT improvement using acoustic and optical compensation and more importantly the feasibility of achieving “quantitative” PAT images upon compensating for tissue heterogeneity.
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