Photoacoustic (PA) field calculations using a Green’s function approach is presented. The method has been applied to predict PA spectra generated by normal (discocyte) and pathological (stomatocyte) red blood cells (RBCs). The contours of normal and pathological RBCs were generated by employing a popular parametric model and accordingly, fitted with the Legendre polynomial expansions for surface parametrization. The first frequency minimum of theoretical PA spectrum approximately appears at 607 MHz for a discocyte and 410 MHz for a stomatocyte when computed from the direction of symmetry axis. The same feature occurs nearly at 247 and 331 MHz, respectively, for those particles when measured along the perpendicular direction. The average experimental spectrum for normal RBCs is found to be flat over a bandwidth of 150-500 MHz when measured along the direction of symmetry axis. For spherical RBCs, both the theoretical and experimental spectra demonstrate negative slope over a bandwidth of 250-500 MHz. Using the Green’s function method discussed, it may be possible to rapidly characterize cellular morphology from single-particle PA spectra.
A methodology for simulating photoacoustic (PA) images of samples with solid spherical absorbers acquired using linear array transducer is described. Two types of numerical phantoms (i.e., polystyrene beads suspended in agar medium) of two different size regimes were imaged with a 40 MHz linear array transducer utilizing this approach. The frequency domain features and statistics of the simulated signals were quantified for tissue characterization. The midband fit at 40 MHz was found to be about 35 dB higher for the sample with larger beads (radius ~7.36 μm) than that of the sample with smaller particles (radius ~ 1.77 μm). The scale parameter of the generalized gamma distribution function was found to be nearly 51 times greater for the former sample compared to the latter sample. The method developed here shows potential to be used a s a fast simulation tool for the PA imaging of collection of absorbers mimicking biological tissue.
Photoacoustic (PA) measurements on confined and unconfined hemoglobin molecules are presented. In vitro experiments were performed with porcine red blood cells (RBCs) at 532 and 1064 nm at various laser fluences. Fluence was gradually changed from 8 to 21 mJ/cm2/pulse for 532 nm and 353 to 643 mJ/cm2/pulse for 1064 nm. PA signals from suspended RBCs (SRBCs) and hemolyzed RBCs (HRBCs) were measured using a needle hydrophone at hematocrits ranging from 10 to 60%. PA amplitude was found to be varied linearly with the laser fluence for each type of samples at the above two optical radiations. At 532 nm, PA signals from SRBCs and HRBCs were measured to be nearly equal, whereas, at 1064 nm, signal amplitude for SRBCs was approximately 2 times higher than that of HRBCs. The results suggest that it may be feasible to detect hemolysis with PAs.
The simultaneous photoacoustic assessment of oxygen saturation and red blood cell aggregation is presented.
Aggregation was induced on porcine red blood cells using Dextran-70 at multiple hematocrit levels. Samples were
exposed to 750 nm and 1064 nm for each hematocrit and aggregate size in order to compute the oxygen saturation. As
the size of the aggregate increased, the photoacoustic signal amplitude increased monotonically. The same trend was
observed for increasing hematocrit at each aggregation level. The oxygen saturation of aggregated samples was 30%
higher than non-aggregated samples at each hematocrit level. This suggests that the presence of red blood cell aggregates
impairs the release of oxygen to the surrounding environment. Such a result has important implications for detecting red
blood cell aggregation non-invasively and making clinical decisions based on the simulatenous assessment of oxygen
Red blood cell (RBC) aggregation and oxygenation are important markers for a variety of blood disorders. No current technique is capable of simultaneously measuring aggregation/oxygenation levels noninvasively. We propose using photoacoustic ultrasound spectroscopy (PAUS) for assessing both phenomena. This technique relies on frequency-domain analysis of the PA signals by extracting parameters such as the ultrasound spectral slope and the midband fit. To investigate the effect of hematocrit, aggregation, and oxygenation levels on PAUS parameters, a Monte Carlo-based theoretical model and an experimental protocol using porcine RBCs were developed. The samples were illuminated at 750 and 1064 nm and changes in the PAUS parameters were compared to the oxygen-dependent optical absorption coefficients to assess the oxygenation level. Good agreement between the theoretical and experimental spectral parameters was obtained for the spectral slope of the nonaggregated spectra (∼0.3 dB/MHz). The experimental midband fit increased by ∼5 dB for the largest aggregate size. Based on the analysis of the PA signals, the oxygen saturation level of the most aggregated sample was >20% greater than the nonaggregated sample. The results provide a framework for using PA signals' spectroscopic parameters for monitoring the aggregation and oxygenation levels of RBCs.
A theoretical model investigating the dependence of optoacoustic (OA) signal on blood oxygen saturation (SO2) is discussed. The derivations for the nonbandlimited and bandlimited OA signals from many red blood cells (RBCs) are presented. The OA field generated by many RBCs was obtained by summing the OA field emitted by each RBC approximated as a fluid sphere. A Monte Carlo technique was employed generating the spatial organizations of RBCs in two-dimensional. The RBCs were assumed to have the same SO2 level in a simulated configuration. The fractional number of oxyhemoglobin molecules, confined in a cell, determined the cellular SO2 and also defined the blood SO2. For the nonbandlimited case, the OA signal amplitude decreased and increased linearly with blood SO2 when illuminated by 700 and 1000 nm radiations, respectively. The power spectra exhibited similar trends over the entire frequency range (MHz to GHz). For the bandlimited case, three acoustic receivers with 2, 10, and 50 MHz as the center frequencies were considered. The linear variations of the OA amplitude with blood SO2 were also observed for each receiver at those laser sources. The good agreement between simulated and published experimental results validates the model qualitatively.
Red blood cells (RBCs) aggregate in the presence of increased plasma fibrinogen and low shear forces during blood
flow. RBC aggregation has been observed in deep vein thrombosis, sepsis and diabetes. We propose using
photoacoustics (PA) as a non-invasive imaging modality to detect RBC aggregation. The theoretical and experimental
feasibility of PA for detecting and characterizing aggregation was assessed. A simulation study was performed to
generate PA signals from non-aggregated and aggregated RBCs using a frequency domain approach and to study the PA
signals' dependence on hematocrit and aggregate size. The effect of the finite bandwidth nature of transducers on the PA
power spectra was also investigated. Experimental confirmation of theoretical results was conducted using porcine RBC
samples exposed to 1064 nm optical wavelength using the Imagio Small Animal PA imaging system (Seno Medical
Instruments, Inc., San Antonio, TX). Aggregation was induced with Dextran-70 (Sigma-Aldrich, St. Louis, MO) and the
effect of hematocrit and aggregation level was investigated. The theoretical and experimental PA signal amplitude
increased linearly with increasing hematocrit. The theoretical dominant frequency content of PA signals shifted towards
lower frequencies (<30 MHz) and 9 dB enhancements in spectral power were observed as the size of aggregates
increased compared to non-aggregating RBCs. Calibration of the PA spectra with the transducer response obtained from
a 200 nm gold film was performed to remove system dependencies. Analysis of the spectral parameters from the
calibrated spectra suggested that PA can assess the degree of aggregation at multiple hematocrit and aggregation levels.
In this paper we examine the potential of using photoacoustic (PA) spectroscopy for the monitoring of red blood cell
(RBC) aggregation phenomena. The process of RBC aggregation has been shown to occur during periods of increased
plasma fibrinogen concentration and periods of decreased blood flow (leading to diminished shear forces on the
aggregates). Current techniques used to monitor RBC aggregation are invasive and do not provide an accurate
assessment of the aggregation process in-vivo. We present a theoretical model for investigating the potential of PA
spectroscopy for detecting and characterizing the aggregation phenomenon. We show that the signal strength increases
with RBC aggregation. Experimental confirmation of the theoretical predictions is provided. Our theoretical and
experimental results suggest the PA spectroscopy is capable of monitoring RBC aggregation and providing important
information about changes that occur during the aggregation process as it pertains to the dynamics of aggregate
A theoretical model examining the effects of erythrocyte oxygenation on optoacoustic (OA) signals is presented. Each erythrocyte is considered as a fluid sphere and its optical absorption is defined by its oxygen saturation state. The OA field generated by a cell is computed by solving the wave equation in the frequency domain with appropriate boundary conditions. The resultant field from many cells is simulated by summing the pressure waves emitted by individual cells. A Monte Carlo algorithm generates 2-D spatially random distributions of oxygenated and deoxygenated erythrocytes. Oxygen saturation levels of oxygenated cells a assumed to be 100% and 0% for deoxygenated cells. The OA signal amplitude decreases monotonically for the 700-nm laser source and increases monotonically for 1000 nm optical radiation when blood oxygen saturation varies from 0 to 100%. An approximately sixfold decrease and fivefold increase of the OA signal amplitude were computed at those wavelengths, respectively. The OA spectral power in the low-frequency range (<10 MHz) and in the very high-frequency range (>100 MHz) decreases for 700 nm and increases for 1000 nm with increasing blood oxygen saturation. This model provides a theoretical framework to study the erythrocyte oxygenation-dependent OA signals.