4.1 The 1064 nm nanosecond laser for PAFC and other PA application
Lasers with wavelengths > 950 nm are not widely used for in vivo
PA imaging and PAFC [3
] or used with low pulse rate [28
]. However, if one compares near-infrared lasers having high PRRs, a short pulse duration, a pulse energy level up to 50–100 μJ, and a suitable cost, the choice of lasers operating in the window of transparency of biological tissues (650–930 nm) is limited, compared to the choice of well established laser systems operating at 1064 nm. Our results may be persuasive for broader application of 1064-nm lasers, especially with high PRRs. PA signal amplitudes from blood vessels obtained at 1064 nm are identical to those acquired at 850–900 nm . The same was observed for background signal from skin only (i.e., without visible blood vessels, although we cannot exclude the presence of small capillaries). Thus, there was no significant increase in background signals of tissue components at 1064 nm. This finding opens the prospect of being able to select comparatively cheap and reliable laser sources operating at 1064 nm for the further development of the PA technique for flow cytometry, imaging, and microscopy.
Some potential, but not significant, drawbacks of this choice, from the viewpoint of sensitivity, are related to the limited number of PA contrast agents with absorption in this spectral range, such as melanin, CNTs, gold nanoshells, gold nanorods, and some other gold nanoparticles with different shapes and compositions. Further, light absorption by some nanoparticles at 1064 nm is 20–30% lower than at 650–900 nm. Taking into account a 10–20% increase in background signal from blood and skin, we expect total decrease in sensitivity at the level ~50% at 1064 nm compared to 850 nm. This situation, however, is improved due to the following: (1) the greater stability of more efficient laser sources operating at 1064 nm which may increase the accuracy of PT/PA measurements; (2) higher PRRs allowing increasing either the signal-to-noise ratio by 10–30-fold or the speed of PA analysis or imaging; and (3) an increase in the laser energy for in vivo
measurement, as the laser fluence safety level at 1064 nm is 100 mJ/cm2
compared to 20 mJ/cm2
in the visible spectral range [30
, illustrate some sources of noise to be considered in PAFC signal processing. Electronic noise (oscillations above 7 MHz level) with a typical duration of 1–2 µs is caused by the electromagnetic field generated by laser sources. Scattered laser light generates acoustic oscillations at the surface of the transducer that start right after the laser pulse. The moment when they appear does not depend on the distance from laser spot to transducer. With the transducer positioned at 4–6-mm distance from the laser beam, it takes 2–4 μs for acoustic waves generated by cells or nanoparticles to reach the transducer. We applied time-gating to select appropriate PA signals from the sample in time domain; thus, effects caused by both the electromagnetic field and scattered light were not recorded. Further digital bandpass filtration removes remaining noise and signal fluctuations. Standard deviation of the PA signal amplitudes recorded for the blood sample decreased 3-fold with the use of digital filtration.
4.2 PT and PA effects at high laser pulse repetition rates
At high PRRs, many signals are acquired from each cell or nanoparticle crossing the laser beam. In this case, one could expect heat accumulation by medium or nanoparticles that could affect generation of PA signals. Typically, there are two kinds of samples in PAFC: (a) bulk tissue, blood vessels, individual cells or (b) nanoparticles of interests in tissue and blood. Depending on the sample size, laser beam spot, laser pulse energy, and PRR, PA signal generation could be efficient for cells but not for blood, or vice versa. Heat accumulation can decrease efficacy of PA signal generation or cause formation of strong PA signals by the generation of nano- and microbubbles.
To distinguish between equilibrium and heat accumulation, one needs to consider heat diffusion in the sample. In PT-based methods, the efficacy of laser energy conversion into thermal effects is maximal in the case of negligible heat diffusion from the sample into the surrounding medium as determined by thermal confinement t
is the laser pulse width and τT
is the thermal relaxation time) [1
]. For a spherical configuration, τT
/27k, where D
is the diameter of the target and k
is the thermal diffusivity of the sample (1.4×10−7
/s for water). For typical targets with sizes D
in the range of 100 nm, 1 µm, 10 µm, and 100 µm (e.g., nanoparticles, organelles, cells, or bulk media with a 100-µm laser spot), the thermal relaxation time τT
is ~3 ns, 0.3 µs, 30 µs, and 3 ms, respectively. Thus, for a single 10-ns laser pulse, thermal confinement is fulfilled for most large targets; and it is not fulfilled for very small nanoparticles. However, this does not take in account heat accumulation at high PRRs that may reduce the amplitude of PT effects. For successive laser pulses, we can introduce a PRR confinement defined as f
. For f
, there is enough time for heat diffusion to remove heat from the target to surrounding medium before the next pulse comes. For the typical targets indicated above, f
was estimated as 300 MHz, 3 MHz, 30 kHz, and 300 Hz, respectively. For example, the 300 Hz estimated for bulk samples corresponds well with the optimal frequencies used in PT thermal-lens spectroscopy method [2
Flow in the vessel partly eases off thermal confinement as it removes excess heat from the laser spot and target [2
]. This may decrease possible laser damage of the tissues and facilitate fulfillment of PRR confinement. For a flowing sample, the lifespan of target is defined as τf
, where D
is the laser beam size along blood vessel and v
is the linear flow velocity. For τf
could be estimated as f
. For example, with a flow velocity v
~50 cm/s (large artery), the laser beam width, D
~10 µm and cell of 10 µm in the diameter, f
can be increased to 50 kHz compared to 10 kHz in static condition. For larger targets, the benefits in speed would be higher.
In photoacoustics, an efficient PA effect can be observed under fulfillment of the acoustic confinement defined as t
, where τA
is the travel time for an acoustic wave through a target with diameter of D
is the speed of sound in the medium (for water c
cm/s). For 100-nm and 10-µm targets, τA
are 10 ns and 100 ps, respectively. Thus, a nanosecond laser that is effective in the PA detection of single cells might be less effective in the case of nanoparticle detection. However, our previous and current data demonstrate excellent PA sensitivity for small nanoparticles [5
]. We hypothesize that, probably, fast temperature increases in nanoparticles due to fast non-radiative relaxation at the picoseconds time scale [31
] may efficiently generate PA oscillations. Or acoustic confinement, like thermal confinement, is not important for nonlinear mode with fast nanobubble expansion that generates strong thermal [31
] and acoustic phenomena, even with nanosecond pulses.
Overlapping of acoustic waves should limit f
. In the presence of acoustic reflections, the recorded acoustic response would be formed by a train of oscillations whose duration, τTR
, is determined by transducer and setup parameters. With a τTR
of ~5–15 µs, a PRR at f
should be <200 kHz and ~60 kHz, respectively. Minimization of acoustic reflections and optimization of transducer response could decrease τTR
to the 10-ns or 1-µs level, which could allow using f
at the levels of 100 MHz and 1 MHz, respectively. Moreover, overlapping of successive PA signals  could be used to enhance PA signals by fitting appropriate “resonant” PRR [1
]. Indeed, we observed summation of individual oscillations at a f
of 420-kHz providing a 2–4-fold increase in signal amplitude .
Thus, for generation of acoustic signals from nanoparticles in linear mode, we considered five confinements: thermal, acoustic, flow escape time, and overlapping of thermal and acoustic waves. Under f
rep greater than f
max calculated according to these confinements, linear PA signals from the sample would be degraded.
To verify these assumptions, we tested a solution containing 1-μm CNT aggregates in static conditions at a high f
rep. Above, we predicted that for f
rep values up to 3 MHz, there will be no effect of heat accumulation in the linear mode. PA signals observed experimentally were in a good correlation with our estimations: at a 1.0-μJ laser pulse energy level, local heat generation was not enough to generate even nanobubbles; only linear effects were observed . The shape of the PT thermal-lens signals acquired from the sample prove this assumption . In this mode, PA signal amplitude was almost constant up to f
rep = 0.5 MHz. Formation of stationary PT thermal-lens signals observed  indicates heat accumulation in the solution. At a higher laser pulse energy of 2 μJ , we observed effective bubble generation, though there was no sample decomposition or solution boiling until f
rep = 50 kHz. The average laser power at high PRRs heated the solution, simplified bubble generation, and led to increases in observed PA signal amplitudes. Nano- and microbubbles generation in this mode was proved by time-resolved PT thermal-lens techniques .
Given the model above, we may speculate that PAFC at high PRRs would benefit from thermal confinement observed for light-absorbing media, such as blood (heat accumulation would decrease linear background signal of blood), while PA effect from a small cell or a nanoparticle would not be degraded. This may increase PA contrast of small targets (e.g. individual nanoparticles) in the presence of blood cells or other light absorbing substances. The effects of nanobubbles formation from localized overheating or of acoustic signal overlapping could be used to further enhance signals from small targets passing the detection zone. We believe that temporal overlapping mode, with an optimized f
, could be combined with spatial overlapping mode [27
] by selecting the laser energy level and nanoparticle parameters, including size, concentration, and spatial distribution. According to our calculations, these combined modes can amplify PA signals up to 10–50 times. We also propose the use of a high-PRR laser to generate periodic, relatively stable nano- and microbubbles around nanoparticle clusters to enhance both PA and PT diagnostic techniques and PT therapy of cancer and infections.
4.3 In vitro and in vivo assessment of PAFC
As we demonstrated , PAFC makes it possible to count nanoparticles in flow. With thick vessels or tubes, nanoparticles and cells flowing far from the irradiated zone would be missed, and an estimation of their numbers would be inaccurate. To avoid this, we implemented a cylindrical lens (an approach previously reported in [8
]) to shape the laser beam into a linear strip. In this case, peak counts and peak widths are linearly dependent on the CNT concentration and the f
, respectively [, ]. Our experimental data have proven that this setup can operate at very high linear flow velocities up to 2.5 m/s. Along with peak count, there is a need to measure cell or particle velocity in flow. Conventional PA methods measure flow rate, but not the velocity, of a individual single cell or nanoparticle clusters [4
]. Our data demonstrate that peak width corresponds well with the nanoparticle lifetime in the laser spot. For a certain f
and known laser spot size, DL
, linear velocity v
of a cell or nanoparticle could be estimated from the measured peak width, Δt
, as v
At a high f
, it is possible to increase detection sensitivity by averaging amplitudes of PA signals, which leads to a reduction of random noise. For example, if a CNT aggregate is exposed to five laser pulses at 5 kHz [, , and ], then at a f
of 100 kHz the same aggregate would be irradiated by 100 pulses. Thus, with data smoothing by moving the average filter, the background noise is decreased by √N
times, where N
is the period of filtration (size of the averaged data subset) [1
]. For a 10-point subset, there is a
= 3.1 times decrease in random noise. Peak amplitude remains the same if peak width is larger than N
. Averaging of the in vitro
results proved this prediction, with the ratio between peak amplitude and background signal fluctuation increasing according to √N
law. The correlation coefficient for the linear curve describing the ratio between peak amplitude and standard deviation of the background signal (signal-to-noise ratio) at different PRRs is 0.98.
In general, one could expect two types of signals from nanoparticles in the laser beam, depending on the presence and the size of nanoparticle aggregates . Individual nanoparticles, evenly spread in the medium, would act as a molecular solution and slightly increase the PA response of the sample. Significant-size aggregates would absorb laser radiation locally, thus providing a dramatic increase in the amplitude of PA signal.
The clearance kinetics of CNTs can easily be estimated from the distribution of peaks in the time after injection  as the rate of CNTs detection significantly decreases after 15-20 minutes. High-amplitude PA signals disappear from the traces recorded first [ and ]; so 15 min after injection there are only small CNTs in circulatory, that can be associated with clearance of large aggregates . For each object passing through a laser beam, we can determine several parameters, such as peak amplitude and width [ and –]. Given a known size distribution of injected particles (which is not the case with the CNTs used in this study), the distribution of peak widths  could be used to speculate about the flow velocity and aggregate formation in flow.