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Breast cancer is one of the most common diseases among women and is one of the major contributors to the mortality of the world. Early and efficient detection of breast cancer has the potential to reduce this mortality. Due to several limitations, the existing imaging modalities do not perform reasonably well as far as efficient breast cancer detection is concerned. There is a need for a new imaging modality which can potentially detect breast cancer using functional information extracted from soft tissue. Photoacoustic Imaging is an emerging hybrid imaging modality that has the potential for efficient detection of breast cancer. Photoacoustic imaging is based on the optical properties of tissues and it provides optical absorption based contrast and also it won’t suffer from the problem of poor resolution as we probe deep inside the soft tissue. Photoacoustic Imaging can find out functional information in terms of optical properties of tissue, as it uses laser light in the near-infrared region to probe the tissue. These optical properties change with the change of distribution of blood vessels as well as other light absorbing chromophores inside the tissue. Based on the experimental evidence from the clinical studies on human patients, it is observed that the tumors located up to a depth of 30 mm in the breast tissue are successfully visualized using photoacoustic imaging without involving any exogenous contrast agents. Our objective is to identify efficient contrast agents which can detect breast tumors beyond the depth of 30mm. In this study, we have performed a detailed simulation of photoacoustic imaging to detect tumors located up to a depth of 40mm with the help of efficient exogenous contrast agents especially with the help of NIR dyes. Simulation of photoacoustic imaging has been performed using a 3-D Monte Carlo simulation for light propagation through breast tissue to generate absorption profile of the breast tissue. This absorption profile of the breast tissue has been given as an input to the k-wave toolbox, a toolbox for time-domain simulation of acoustic-wave fields. Using this toolbox, photoacoustic wave fields are generated, propagated and detected using ultrasound detectors. The detected photoacoustic waves are reconstructed with the help of time-reversal reconstruction algorithm. The simulation study has been performed with endogenous as well as exogenous contrast agents. With endogenous contrast agents, the study was performed at four wavelengths 850 nm, 800 nm 750 nm and 700 nm to detect tumors of spherical shape in the breast tissue at different depths in the range of 10-40 mm at regular intervals of 5mm. Photoacoustic Imaging performance was measured in terms of contrast (tumor to background region average intensity ratio) at various depths of the tumor. Further, the simulation study has been performed with exogenous contrast agents by involving NIR dyes such as ICG, Methylene Blue, IRdye800CW, IRDye750, IRDye700, Alexa Fluor790, Alexa Fluor750 and Alexa Fluor700 as exogenous contrast agents to improve the performance of photoacoustic imaging. Comparative analysis of contrast versus depth for different endogenous and exogenous contrast agents has been done to identify the efficient photoacoustic contrast agents for deep tissue imaging of breast cancer. Performance of endogenous contrast agents is compared with the exogenous contrast agents corresponding to the identical peak absorption wavelengths. Alexa Fluor 700 and IRDye700 are showing better performance in terms of improved contrast beyond the depth of 30mm as compared to other contrast agents.
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