Laser photothermoacoustic heterodyned lock-in depth profilometry in turbid tissue phantoms.

Frequency-domain correlation and spectral analysis photothermoacoustic (FD-PTA) imaging is a promising new technique, which is being developed to detect tumor masses in turbid biological tissue. Unlike conventional biomedical photoacoustics which uses time-of-flight acoustic information induced by a pulsed laser to indicate the tumor size and location, in this research, a new FD-PTA instrument featuring frequency sweep (chirp) and heterodyne modulation and lock-in detection of a continuous-wave laser source at wavelength is constructed and tested for its depth profilometric capabilities with regard to turbid media imaging. Owing to the linear relationship between the depth of acoustic signal generation and the delay time of signal arrival to the transducer, information specific to a particular depth can be associated with a particular frequency in the chirp signal. Scanning laser-fluence modulation frequencies with a linear frequency sweep method preserves the depth-to-delay time linearity and recovers FD-PTA signals from a range of depths. Combining with the depth information carried by the back-propagated acoustic chirp signal at each scanning position, one could rapidly generate subsurface three-dimensional images of the scanning area at optimal signal-to-noise ratios and low laser fluences, a combination of tasks that is difficult or impossible by use of pulsed photoacoustic detection. In this paper, results of PTA scans performed on tissue mimicking control phantoms with various optical, acoustical, and geometrical properties are presented. A mathematical model is developed to study the laser-induced photothermoacoustic waves in turbid media. The model includes both the scattering and absorption properties of the turbid medium. A good agreement is obtained between the experimental and numerical results. It is concluded that frequency domain photothermoacoustics using a linear frequency sweep method and heterodyne lock-in detection has the potential to be a reliable tool for biomedical depth-profilometric imaging.