Opto-acoustic imaging involves using light to produce sound waves for visualizing blood in biological tissue. By using multiple optical wavelengths, diagnostic images of blood oxygen saturation and total hemoglobin are generated using endogenous optical contrast, without injection of any external contrast agent and without using any ionizing radiation. The technology has been used in recent clinical studies for diagnosis of breast cancer to help distinguish benign from malignant lesions, potentially reducing the need for biopsy through improved diagnostic imaging accuracy. To enable this application, techniques for mapping oxygen saturation differences within tissue are necessary. Using biologically relevant opto-acoustic phantoms, we analyze the ability of an opto-acoustic imaging system to display colorized parametric maps that are generated using a statistical mapping approach. To mimic breast tissue, a material with closely matching properties for optical absorption, optical scattering, acoustic attenuation, and speed of sound is used. The phantoms include two vessels filled with whole blood at oxygen saturation levels determined using a sensor-based approach. A flow system with gas-mixer and membrane oxygenator adjusts the oxygen saturation of each vessel independently. Datasets are collected with an investigational Imagio^® breast imaging system. We examine the ability to distinguish vessels as the oxygen saturation level and imaging depth are varied. At depth of 15 mm and hematocrit of 42%, a sufficient level of contrast to distinguish between two 1.6-mm diameter vessels was measured for an oxygen saturation difference of ∼4.6  %  . In addition, an oxygenated vessel was visible at a depth of 48 mm using an optical wavelength of 1064 nm, and a deoxygenated vessel was visible to a depth of 42 mm with 757 nm. The results provide insight toward using color mapped opto-acoustic images for diagnosing breast cancer.

Solid tumors are typically supplied nutrients by a network of irregular blood vessels. By targeting these vascular networks, it might be possible to hinder cancer growth and metastasis. Vascular disrupting agents induce intertumoral hemorrhaging, making photoacoustic (PA) imaging well positioned to detect bleeding due to its sensitivity to hemoglobin and its various states. We introduce a fractal-based numerical model of intertumoral hemorrhaging to simulate the PA signals from disrupted tumor blood vessels. The fractal model uses bifurcated cylinders to represent vascular trees. To mimic bleeding from blood vessels, hemoglobin diffusion from microvessels was simulated. In the simulations, the PA signals were detected by a linear array transducer (30 MHz center frequency) of four different vascular trees. The power spectrum of each beamformed PA signal was computed and fitted to a straight line within the −6-dB bandwidth of the receiving transducer. The spectral slope and midband fit (MBF) based on the fit decreased by 0.11  dB  /  MHz and 2.12 dB, respectively, 1 h post bleeding, while the y-intercept increased by 1.21 dB. The results suggest that spectral PA analysis can be used to measure changes in the concentration and spatial distribution of hemoglobin in tissue without the need to resolve individual vessels. The simulations support the feasibility of using PA imaging and spectral analysis in cancer treatment monitoring by detecting microvessel disruption.

We have developed a photoacoustic (PA) sensor using a low-power, continuous- wave laser and a kHz-range microphone. The sensor is simple, flexible, cost-effective, and compatible with commercial optical microscopes. The sensor enables noncontact PA measurements through air, whereas most current existing PA techniques require an acoustic coupling liquid for detection. The PA sensor has three main components: one is the chamber that holds the sample, the second is a resonator column used to amplify the weak PA signals generated within the sample chamber, and the third is a microphone at the end of the resonator column to detect the amplified signals. The chamber size was designed to be 8  mm  ×  3  mm as the thermal diffusion length and viscous-thermal damping of air at room pressure and temperature are 2 and 1 mm, respectively. We numerically and experimentally examined the effect of the resonator column size on the frequency response of the PA sensor. The quality factor decreased significantly when the sample chamber size was reduced from 4  mm  ×  3  mm to 2  mm  ×  3  mm due to thermos-viscous damping of the air. The quality factor decreased by 27%, demonstrating the need for optimal design for the sample chamber and resonator column size. The system exhibited noise equivalent molecular sensitivity (NEM) per unit bandwidth (NEM  /    √  Δf) of ∼19,966  Hz^−  1/2 or 33  ×  10^−  21  mol or 33 zeptomol, which is an improvement of 2.2 times compared to the previous system design. This PA sensor has the potential for noncontact high-resolution PA imaging of materials without the need for coupling fluids.

While the nucleus-to-cytoplasmic (N:C) ratio has traditionally been used for assessing cell malignancy, most N:C measurement techniques are time-consuming and performed on thin histological sections, which prohibit assessment of three-dimensional cell structure. A combined ultrahigh frequency ultrasound (US) and photoacoustic (PA) technique was used to assess the size and N:C ratio of cultured cancer cells in three dimensions (3D). The diameters of the cells and their stained nuclei were obtained by fitting the power spectrum of backscattered US pulses and emitted PA waves, respectively, to well-established theoretical models. For comparison, an imaging flow cytometer (IFC) was also used to determine the two-dimensional cell and nucleus sizes from large cell populations using brightfield and fluorescence images, respectively. An N:C ratio was calculated for each cell using the quotient of the measured nucleus diameter and the total cell diameter. The mean N:C ratios calculated using the sound-based approach were 0.68, 0.66, and 0.54 for MCF-7, PC-3, and MDA-MB-231 cells, respectively, and were in good agreement with the corresponding values of 0.68, 0.67, and 0.68 obtained using the IFC. The combined US and PA technique, which assesses cellular N:C ratio in 3D, has potential applications in the detection of circulating tumor cells in liquid biopsies.