Photoacoustic microscopy (PAM) utilizes short laser pulses to deposit energy into light absorbers and sensitively detects the ultrasonic waves the absorbers generate in response. PAM directly renders a three-dimensional spatial distribution of sub-surface optical absorbers. Unlike other optical imaging technologies, PAM features label-free optical absorption contrast and excellent imaging depths. Standard dental imaging instruments are limited to X-ray and CCD cameras. Subsurface optical dental imaging is difficult due to the highly-scattering enamel and dentin tissue. Thus, very few imaging methods can detect dental decay or diagnose dental pulp, which is the innermost part of the tooth, containing the nerves, blood vessels, and other cells. Here, we conducted a feasibility study on imaging dental decay and dental pulp with PAM. Our results showed that PAM is sensitive to the color change associated with dental decay. Although the relative PA signal distribution may be affected by surface contours and subsurface reflections from deeper dental tissue, monitoring changes in the PA signals (at the same site) over time is necessary to identify the progress of dental decay. Our results also showed that deep-imaging, near-infrared (NIR) PAM can sensitively image blood in the dental pulp of an in vitro tooth. In conclusion, PAM is a promising tool for imaging both dental decay and dental pulp. © 2011 SPIE.

Lipids play crucial roles in many biological processes. Mapping spatial distributions and examining the metabolic dynamics of different lipid subtypes in cells and tissues are critical to better understanding their roles in aging and diseases. Commonly used imaging methods (such as mass spectrometry-based, fluorescence labeling, conventional optical imaging) can disrupt the native environment of cells/tissues, have limited spatial or spectral resolution, or cannot distinguish different lipid subtypes. Here we present a hyperspectral imaging platform that integrates a Penalized Reference Matching algorithm with Stimulated Raman Scattering (PRM-SRS) microscopy. Using this platform, we visualize and identify high density lipoprotein particles in human kidney, a high cholesterol to phosphatidylethanolamine ratio inside granule cells of mouse hippocampus, and subcellular distributions of sphingosine and cardiolipin in human brain. Our PRM-SRS displays unique advantages of enhanced chemical specificity, subcellular resolution, and fast data processing in distinguishing lipid subtypes in different organs and species.