2.1.

Flow System

The flow system (Fig. 1) enables fluids to be circulated within a vessel-mimicking tube embedded in a tissue-mimicking agar phantom placed in the chamber of a photoacoustic imaging system. Online (and offline) spectrometry and ${\mathrm{pO}}_2$ detection provide independent validation of the spectral measurements made by the imaging system. Details of the tissue-mimicking phantom, the photoacoustic imaging system, the spectrometric validation, the ${\mathrm{pO}}_2$ detection, and the spectral analysis are described in the following sections.

Fig. 1

Overview of the flow system. (1) Injection site for introducing oxygenated blood (or other fluids) into the flow system, and for subsequently deoxygenating the blood using sodium hydrosulfite delivered via the syringe driver (MKCB2159V, Harvard); (2) online spectra are recorded using a light source (Avalight-HAL-S-Mini, Avantes) and spectrometer (AvaSpec-ULS2048-USB2-VA-50, Avantes) as the blood passes through a flow cell (170700-0.5-40, Hellma Analytics); (3) needle probes (NX-BF/O/E, Oxford Optronix) measure the temperature and partial pressure of oxygen (${\mathrm{pO}}_2$) before (3a) and after (3b) the blood passes through an agar phantom immersed in the photoacoustic imaging system (MSOT inVision 256-TF, iThera Medical) (4); (5) a touch-screen monitor (OxyLite Pro, Oxford Optronix) displays temperature and oxygen data; (6) these data are downloaded via an Arduino UNO and read in MATLAB on a laptop, which also records the spectrometer readings via AvaSoft software; (7) a peristaltic pump (CTP100, Fisher Scientific) provides blood circulation.

2.2.

Flow System Characterization

2.3.

Blood Oxygenation Measurements

Mouse blood, predominantly made up of strains B6 and 129SvEv, was collected post mortem from the animal facility at the Cancer Research UK Cambridge Institute, complying with the UK Animals (Scientific Procedures) Act 1986. Each mouse contributed about 1 mL to a pool of $\sim 5\mathrm{mL}$ blood required for the flow circuit. Chemicals were added to preserve, oxygenate, and deoxygenate the blood. Prior to the experiment, ethylenediaminetetraacetic acid anticoagulant (9002-07-7, Sigma-Aldrich) was added to the fresh blood, which was kept in a refrigerator under 4°C for no more than 72 hours. During the experiment, the blood was returned to room temperature, and the oxygenation was controlled chemically by adding 0.2% v/v hydrogen peroxide, ${\mathrm{H}}_2{\mathrm{O}}_2$ (7722-84-1, Sigma-Aldrich), for oxygenation³² and sodium hydrosulfite (7775-14-6, ACROS Organics) for deoxygenation.³³ The sodium hydrosulfite was dissolved in phosphate-buffered saline (PBS) $\sim 0.03\%\mathrm{w}/\mathrm{v}$ for injection into the flow circuit.

2.4.

Spectral and Statistical Analysis

PAT contrast is provided by optical absorbers within the field of illumination and detection. In general, PAT does not have sufficient resolution to visualize individual molecules and therefore each image pixel (or voxel) corresponds to more than one optical absorber, and a “spectral unmixing” approach is required in order to extract the individual spectral components. The linear mixture model³⁴ assumes that the measured spectrum is a linear combination of distinct spectra:

To correct for the spectrally varying fluence (spectral coloring) when using optically absorbing phantoms, the image intensities in the tube region were divided by the nigrosin absorption spectrum. Specifically, the nigrosin absorption spectrum was normalized to the known absorption coefficient (at the 564-nm absorption maximum) and resampled at the 17-experimental wavelengths; the multispectral PA data were then divided by a wavelength-specific factor calculated from exponential decay over the 8.5 mm distance from the outer edge of the phantom (the background agar material impregnated with absorbing nigrosin) to the tube wall. All data and source code used in this publication are available at https://doi.org/10.17863/CAM.40365 and in a GitHub repository at https://github.com/9xg/flow-phantom.

3.1.

Flow System Characterization

Eleven different tubes were assessed for their photoacoustic imaging suitability (Fig. 2). Tubes made from PMMA (I.D./O.D. 375/500, 432/865, 667/1000) showed the lowest signal-to-background (SBR) ratios ranging from 0.15 to 0.37. The other tubes materials show a clear trend of increasing SBR with larger inner diameters. Silicone tubes present high SBRs, even for low I.D./O.D. ratios (300/600, 630/1190, and 1570/2410). Three tubes showed very similar performance (I.D./O.D. 1500/2100, 1570/2410, and 2660/2800). The PVC tube with 1500/2100 presented a uniform, circular appearance in images with high SBR; it was therefore selected for the remaining experiments. Note also that regions of interest (ROIs) indicated in Fig. 2(a) exclude an outer boundary, but the dimensions of the image suggest that this boundary is likely to be due to the low frequency response of the detectors rather than absorption by the tube wall itself.

Fig. 2

Assessment of the effect of tube type on the quality of photoacoustic images. (a) PAT images (at 775 nm) of four tubes with inner and outer diameters (I.D.-O.D.) in $\mu \mathrm{m}$ of 630 to 1190 (silicone), 667 to 1000 (PMMA), 1500 to 2100 (PVC), and 1570 to 2410 (silicone), filled with a solution of ICG and embedded within a scattering agar cylinder (not shown). (b) Mean photoacoustic signal intensity inside the tube relative to the signal outside (SBR) for 11 different tubes. The tube with I.D.-O.D. 1500 to $2100\mu \mathrm{m}$ was selected due to its high SBR, flexibility, and low cost. The four tubes illustrated in (a) are marked with symbols.

Dilutions of MB and ICG were tested inside the flow phantom under closed conditions, i.e., with a steady concentration flowing in the circuit. By calculating the mean PA signal intensities over a manually segmented tube cross-sectional ROI for 17 different wavelengths, it was possible to compare the PA spectra with those acquired during online flow spectrometry [Figs. 3(a)–3(d)]. Unexpectedly, the two independent spectral measurements show poor agreement in terms of relative intensities and spectral shape for the different dye concentrations. In particular, it is notable that the PA signal intensities [Fig. 3(b)] show a more pronounced shift in spectral peak with increasing ICG concentration compared with the online spectrometer data [Fig. 3(d)]; this may be a result of spectral coloring where light attenuation at the 800-nm peak suppresses the PA signal intensity deeper within the tube, leading to an overall reduction in mean PA intensity at this wavelength. Long fluorescent lifetimes and formation of aggregates are additional factors that may influence the inversion of the PA spectrum, although they do not explain the absence of an equivalent spectral shift in the spectrometer data. For MB, the discrepancies are difficult to discern seeing as the prominent spectral features occur below the PA imaging range. However, it is interesting that the relative PA intensities are about half those for ICG suggesting that MB has poorer PA signal generation efficiency; this may be related to the long-lived triplet states of MB, which tend to suppress PA emission and can in fact be exploited in pump-probe techniques to enhance the PA signal.^36,37 Overall, these spectral inconsistencies raise a question about which are the most suitable endmember spectra for unmixing PAT images of MB and ICG.

Fig. 3

Comparison of dye spectra measured using PAT and online flow spectrometry under closed conditions. (a), (b) PA signal intensities (with smoothed spline) and (c), (d) online flow spectrometer absorbance values measured for different concentrations of MB [panels (a) and (c)] and ICG [panels (b) and (d)]. Gray box indicates wavelengths outside the PAT spectral range.

The spectra measured with the online spectrometer and offline in the plate reader were used to perform concentration-specific unmixing of the mean ROI intensities recorded at all 17 wavelengths, and these unmixed intensities were compared with those calculated using the literature spectra incorporated within the PA analysis software. These literature spectra are shown in Figs. 4(a)–4(b) along with online and offline spectra for example concentrations [Figs. 4(c)–4(f)].

Fig. 4

Comparison of endmember spectra used for spectral unmixing. (a), (b) Literature spectra, spectra acquired using (c), (d) the online flow spectrometer and (e), (f) the offline flow spectrometer for MB [panels (a), (c), and (e)] and ICG [panels (b), (d), and (f)].

Figures 5(a) and 5(b) show a linear relationship between dye concentration and spectrally unmixed PA intensities up to $100\mu \mathrm{M}$ for MB and $40\mu \mathrm{M}$ for ICG, respectively. Divergence between the two types of unmixing is likely due to concentration-dependent changes in the spectra of these dyes; these changes are particularly prominent for ICG and indeed the online spectra [Fig. 3(d)] slightly deviate from a linear relationship with increasing concentration.

Fig. 5

Spectrally unmixed PA signal intensities for a range of dye concentrations. (a) MB and (b) ICG concentrations obtained by unmixing with literature spectra and those measured using the online and offline spectrometers. The LM was used to calculate concentrations of (c) MB and (d) ICG during evolution of dye concentrations within the flow circuit due to continual dye injection. The starting points were forced to zero for ease of comparison.

Having explored the application of the flow circuit under static concentration values, we then examined the response of the PAT instrument to dynamic changes in dye concentrations for MB and ICG [Figs. 5(c) and 5(d)]. PA images were unmixed using the literature spectra and those recorded live using the online spectrometer, and then converted to absolute concentration values using the linear models (LM) calculated and plotted in Figs. 5(a) and 5(b). Neglecting the initial lag phase (which could not be experimentally determined and therefore was not incorporated into the model), the rates of concentration change match reasonably well with those predicted by the model [Eq. (5)]. However, there is a notable discrepancy between the dynamics calculated using the literature and online spectra for ICG unmixing; if the lag phase were corrected for, the online unmixing would be the closer match to the model and this is again likely to be a consequence of the concentration-dependent change in spectral shape, which is incorporated in the online spectra but not the single literature spectrum.

3.2.

Blood Oxygenation Measurements

To demonstrate the closed nature of the blood flow circuit, blood was fully oxygenated by adding approximately $15\mu \mathrm{L}$ 0.2% v/v ${\mathrm{H}}_2{\mathrm{O}}_2$ to 8-mL mouse blood and then injecting this into the flow system and circulating it for several minutes. Figure 6 shows the blood oxygen saturation (${\mathrm{sO}}_2$) measured within the flow circuit by: the ${\mathrm{pO}}_2$ probe, the online spectrometer, and PAT. The ${\mathrm{sO}}_2$ was calculated from the ${\mathrm{pO}}_2$ data using Eq. (2) and from the online spectrometer and PAT data through spectral unmixing. To enable comparison between the methods independently, unmixing was performed using the spectra inherent to each system: for the online spectrometer, experimentally measured spectra were used as endmembers, whereas for PAT data, the literature spectra were used. As hoped, all three ${\mathrm{sO}}_2$ measurements show consistent values over time. However, the ${\mathrm{sO}}_2$ calculated from the unmixed PA images under-reads by about 13% compared to the ground truth ${\mathrm{sO}}_2$ calculated from the ${\mathrm{pO}}_2$ probe and the online flow spectrometer.

Fig. 6

Assessment of blood oxygenation within the flow circuit under closed conditions. Blood oxygen saturation (${\mathrm{sO}}_2$) was calculated using the three independent methods: the ${\mathrm{pO}}_2$ probe measurements [using Eq. (2)]; unmixing of the spectra measured using the online flow spectrometer (with experimentally measured spectra as end-members); unmixing of the mean pixel intensities in the PA images (with literature spectra as end-members) acquired while blood circulated in the flow system for 200 s.

In addition to investigating static blood oxygenation within the circuit, the full range of blood ${\mathrm{sO}}_2$ values (100% to 0%) were explored by injecting sodium hydrosulfite into the flow circuit in order to gradually deoxygenate the blood. The blood ${\mathrm{sO}}_2$ values cover the expected dynamic range when calculated from both the ${\mathrm{pO}}_2$ probe and the online spectrometer [Fig. 7(a)]; however, PA signal intensities show markedly different behaviors when unmixed with spectra [Fig. 7(b)] from the literature or from the online flow spectrometer. The ${\mathrm{sO}}_2$ values calculated by unmixing with the experimentally measured spectra [gray dotted line, Fig. 7(a)] show good agreement with the spectrometer-derived ground truth values [orange/red line, Fig. 7(a)], except for somewhat over-reading the oxygenation for ${\mathrm{sO}}_2$ values below about 20%. They also show a dynamic range comparable to that obtained from the ${\mathrm{pO}}_2$ probe and Severinghaus model. However, the ${\mathrm{sO}}_2$ values calculated by unmixing with the literature spectra [pink dashed line, Fig. 7(a)] surprisingly exhibit a dramatically reduced dynamic range (86% to 58%); this may be due to the unmixing spectra and/or spectral coloring.

Fig. 7

Dynamic deoxygenation of the circulating blood. (a) Change in blood oxygen saturation (${\mathrm{sO}}_2$) measured using the ${\mathrm{pO}}_2$ probe, online spectrometer, and PAT system while injecting 3% w/v sodium hydrosulfite in PBS over a period of 9 min. The anomalous data for the online spectrometer around 100 s may be due to a small bubble passing through the circuit. (b) Literature spectra for oxy- and deoxyhemoglobin used for spectral unmixing,⁷ compared to spectra obtained from the online spectrometer at the start and end of dynamic deoxygenation.

Two further investigations explored the potential impact of spectral colouring. First, spatially resolved ${\mathrm{sO}}_2$ measurements were calculated [Fig. 8(a)]. Unlike the results in Figs. 6 and 7 that were calculated from the mean of the ROI defined on the tube cross-sectional area, the results in Fig. 8(a) entailed unmixing first using the wavelength-dependent intensities of the single pixel at the tube center, and then repeatedly unmixing for the mean intensities of pixels found in circles increasing in one pixel ($75\mu \mathrm{m}$) increments toward the perimeter of the ROI. For the fully oxygenated blood, the ${\mathrm{sO}}_2$ values are consistent across the tube diameter, but as the blood becomes deoxygenated there is a clear trend toward ${\mathrm{sO}}_2$ over-reading at the center of the tube; this is a clear demonstration of spectral coloring. A second illustration of spectral coloring is shown in Fig. 8(b) where experiments were repeated with absorbing nigrosin dye incoporated into the background of the tissue-mimicking phantom surrounding the flow circuit tube; in all the previous experiments, the agar background was optically scattering but assumed to have negligible absorption. Increasing the background absorption causes increasing inaccuracy of the ${\mathrm{sO}}_2$ relative to the ground truth since wavelengths of light are preferentially absorbed by the nigrosin dye, leading to overestimation of the contribution of oxyhemoglobin to the PA signal. A simple light fluence correction, implemented by dividing the images by the known nigrosin spectrum (Sec. 2.4), restored consistent ${\mathrm{sO}}_2$ measurements irrespective of the background absorption, providing evidence that this over-reading phenomenon is indeed related to spectral coloring.

Fig. 8

Investigation of spectral coloring. (a) Spatial profiles of blood oxygen saturation (${\mathrm{sO}}_2$) as a function of distance from the center of the flow circuit tube by PA unmixing with spectra measured using the online spectrometer during dynamic blood oxygenation (Fig. 7). (b) Impact of correction for the absorption spectrum of the nigrosin dye included in the background of the tissue-mimicking phantom as a function of dye concentration. For absorption coefficients of $>0{\mathrm{cm}}^{-1}$, the ${\mathrm{sO}}_2$ (gray bars) deviated from the ground truth value (dotted line); accurate values were restored by recalculating ${\mathrm{sO}}_2$ (orange bars) after dividing the photoacoustic images by the relevant nigrosin spectrum as described in the text.