Tissue characterization based on photoacoustic physio-chemical analysis


Conventional gold standard histopathologic diagnosis requires information of both high resolution structural and chemical changes in tissue.  Taking advantage of the multi-physics nature of photoacoustic (PA) measurements, high-sensitivity and highly accurate tissue characterization can be achieved noninvasively in the authentic in vivo environment. A two-dimensional (2D) physio-chemical spectrogram (PCS) integrating micrometer to centimeter morphology and chemical composition simultaneously can be generated by 1) performing PA scans of a tissue over a broad optical spectrum covering the absorption peaks of specific relevant chemical components, 2) transforming the PA signals into the spatial frequency domain, and 3) arranging the spatial frequency power spectra side-by-side in the order of the wavelengths.  By systematically integrating the “optical absorption signature” and the “spatial frequencies of the optical absorbers” in one 2D spectrogram, the PCS presents a unique “physio-chemical signature” for any specific type of tissue.  Comprehensive analysis of PCS, termed PA physio-chemical analysis (PAPCA), can lead to rich diagnostic information, including the contents of all relevant molecular and chemical components along with their corresponding histological microfeatures, comparable to those accessible by conventional histology.   Ex vivo and in situ studies on mouse models of nonalcoholic fatty liver disease (NAFLD) conditions have demonstrated that, by quantifying the PCS at the optical absorption peaks of major chromophores in liver tissue, including hemoglobin, lipid and collagen, PAPCA can non-invasively characterize the pathological changes correlated to liver steatosis and liver fibrosis.

 Example results:



Physio-chemical spectrogram (PCS) spectrograms of (a) normal, (b) steatosis, and (c) fibrotic livers. The fingerprints of hemoglobin, lipid, collagen and water are marked by the magenta, green, blue and black contours, respectively. (d) The multi-spectral photoacoustic (PA) measurements of normal, steatosis, and fibrotic livers, which are produced by summing the pixels in the PCS maps in normal scale along each column. (e) The relative optical absorption spectra of the major optically absorbing chemical components in liver tissue.  The red dashed lines indicate the matching between the absorption peaks of the chemical components and the fingerprints in the PCS.






Non-invasive ultrasound (US) and photoacoustic (PA) imaging and PA spectral analysis (PASA) of normal, steatosis, and fibrotic mouse livers in situ. The unit of the image dimensions is mm. (a) Normal liver vs. steatotic liver at 1220 nm optical wavelength.  In comparison with the normal control, the steatotic liver shows higher intercept, higher midband-fit and higher slope values.  (b) Normal liver vs. fibrotic liver at 1370 nm optical wavelength.  In comparison with the normal control, the fibrotic liver shows higher intercept, higher midband-fit, and higher slope values.  PASA parameter images show better differentiation of liver steatosis and liver fibrosis from normal control.



Statistics of the experiment data from the progressive NAFLD mice, demonstrating that photoacoustic physio-chemical analysis (PAPCA) can characterize various liver conditions.  Each data group consists of 12 data points.  The mean and the standard deviation of the spectral parameters including slopes and midband-fits within each liver condition group (i.e. normal, steatosis, and fibrosis) at three different optical wavelengths (700 nm, 1220 nm, and 1370 nm) are compared.