Photoacoustic spectral analysis is a novel tool for studying various parameters affecting signals in Photoacoustic microscopy. But only observing frequency components of photoacoustic signals doesn't make enough data for a desirable analysis. Thus a hybrid time-domain and frequency-domain analysis scheme has been proposed to investigate effects of various parameters like depth of microscopy, laser focal spot size and contrast agent concentration on Photoacoustic signals.
hotoacoustic Imaging (PAI) is a nonionizing hybrid medical imaging modality based on photoacoustic effect which was described by Alexander Graham Bell at 1880 for the first time [1].
Briefly, in pulsed-mode PAI, a pulsed laser beam illuminates the tissue, then the absorption of photons, reaching the tissue Region Of Interest (ROI), leads to a slight localized heating of the tissue causing thermoelastic expansion and generating pressure waves, which can be detected by ultrasound transducer(s) as Photoacoustic (PA) signals. PAI simultaneously benefits from optical contrast and ultrasound resolution and this means more depth resolution than pure optical imaging modalities and more contrast rather than ultrasound imaging techniques, though the origins of contrast are completely different in PAI rather than imaging with ultrasound echoes in B-mode imaging. PAI, like many medical imaging modalities, utilizes agents for contrast enhancement of different targeted ROIs. These contrast agents are either endogenous or exogenous. Hemoglobin, melanin, lipid, collagen, elastin and water are some endogenous agents. Also, a variety of exogenous agents, e.g. Indocyanine Green (ICG), Evans Blue (EB), IRDye800, quantum dots and copper sulfide nanoparticles, have been used in various biomedical applications [2][3][4][5][6][7][8].
During the last decade, PAI has found many clinical applications in fields like urology, dermatology, gynecology, hematology, ophthalmology and neuroscience studies for neuroimaging and brain mapping [9][10].
The capability of this modality for both anatomical and functional imaging has made it an opportune method for small animal brain imaging. Also, it can connect micro structural studies of brain with macro scale observations. Studies on the brain of small animals like mouse and rat have proposed methods for measuring quantities like Cerebral Metabolic Rate of Oxygen (CMRO 2 ) and Saturation of Oxygen (SO 2 ) either with or without the use of exogenous agents [11][12].
Various systems have been utilized in the literature, amongst them; Photoacoustic Microscopy (PAM) and Photoacoustic Tomography (PAT) have found major applications. Focused spherical, ring-shaped transducers, rotational multi-element transducers or novel linear array transducers have been used in PAT. Sensors detect signals of various ROIs in biological tissues and then the reconstruction of acquired PA signals forms tomographic images [13].
PAM systems are confocal microscopes which are based on their instrumentation and can be divided into two sub-systems; Optical-Resolution Photoacoustic Microscopy (OR-PAM) and Acoustic-Resolution Photoacoustic Microscopy (AR-PAM). Briefly, the focus of pulsed laser beam in OR-PAM is narrow and a broadband transducer is used for the detection of broadband ultrasound waves. In contrast, AR-PAM utilizes narrower bandwidth transducers and the focal spot of laser light is broader at the focal zone of microscopy. Broader light illumination can be achieved by the utilization of mirrors for diffusing photons [14][15][16][17].
ICG is one of the most efficient contrast agents for photoacoustic brain imaging. It is a non-toxic agent with a suitable clearance which can be transmitted across the Blood-Brain Barrier (BBB) and has an optical absorption peak at a laser wavelength of 800 nm. Wavelengths in the range of 700-1064 nm are in Near Infrared (NIR) region of optical spectrum in which light penetration achieves its maximum level, that is why almost all exogenous contrast agents are fabricated with the optical absorption peaks of wavelengths in NIR region [4,[6][7].
A majority of previous studies on PAI were focused on instrumentation, different imaging techniques e.g. PAM or PAT and the implementation of novel reconstruction algorithms etc. Recently, a new technique termed Photoacoustic Spectral Analysis (PASA) has been developed. The major purpose of PASA is the quantification of different characteristics of tissues and biological microstructures by analyzing PA signal spectrums [18][19].
Earlier studies like “spectral analysis of PAI data from prostate adenocarcinoma tumors in a murine model “have focused on morphological characterization of biological tissues only by implementing analysis in frequency-domain data [20][21].
In this work, a simulation study is presented, for the first time to the best of our knowledge, both time-domain and frequency-domain analysis of PA signals generated from different concentrations of ICG. Then, PA signals from ICG have been compared with signals generated by hemoglobin in mouse brain vasculature using narrowband curved array transducers. In addition, the analysis of PA signals from different imaging depths and different sizes of illuminated optical absorbers or chromophores augment our study. Despite using AR-PAM, which is similar to our simulation setup, PASA has not been reported so far. Beside considered studies, a novel technique for the analysis of effe
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