Special Section on Selected Topics in Biophotonics: Photoacoustic Tomography and Fiber-Based Lasers and Supercontinuum Sources

Tutorial on photoacoustic tomography

[+] Author Affiliations
Yong Zhou, Junjie Yao, Lihong V. Wang

Washington University in St. Louis, Department of Biomedical Engineering, Optical Imaging Laboratory, One Brookings Drive, Campus Box 1097, St. Louis, Missouri 63130, United States

J. Biomed. Opt. 21(6), 061007 (Apr 18, 2016). doi:10.1117/1.JBO.21.6.061007
History: Received January 26, 2016; Accepted March 22, 2016
Text Size: A A A

Open Access Open Access

Abstract.  Photoacoustic tomography (PAT) has become one of the fastest growing fields in biomedical optics. Unlike pure optical imaging, such as confocal microscopy and two-photon microscopy, PAT employs acoustic detection to image optical absorption contrast with high-resolution deep into scattering tissue. So far, PAT has been widely used for multiscale anatomical, functional, and molecular imaging of biological tissues. We focus on PAT’s basic principles, major implementations, imaging contrasts, and recent applications.

Figures in this Article

Photoacoustic tomography (PAT), also called optoacoustic tomography, is a three-dimensional (3-D) imaging modality based on the photoacoustic (PA) effect. Although the PA effect was discovered more than a century ago by Alexander Graham Bell, it has found applications in biomedical imaging only in the last decade or so. Nowadays, PAT is one of the largest research areas in biomedical optics and is still growing rapidly.1

Harnessing both rich optical absorption contrast and high ultrasonic resolution, PAT is a hybrid imaging modality that can image deep tissues. While pure optical imaging modalities can also detect optical absorption by monitoring intensity variations in transmitted or reflected light, their sensitivities are usually two orders of magnitude lower than that of PAT.2 In addition, because acoustic waves scatter much more weakly than light in biological tissues, they can propagate a greater distance than photons without losing their original propagation directions, providing PAT with high spatial resolution at depths. While pure ultrasonic imaging can also achieve high spatial resolution in deep tissues, its mechanical contrast is incapable of providing certain physiological parameters, such as the oxygen saturation of hemoglobin and the metabolic rate of oxygen.

Several comprehensive reviews of PAT can be found in the literature;1,321 some are general,1,35,11,21 and some focus on specific areas, such as PAT’s application in imaging molecules,9 microvasculature,6 tumors,17 the brain,16 and small animals.15 Here, we will review the fundaments of PAT, including its principles, major implementations, system characteristics, main contrast agents, and recent applications.

Initial Pressure Rise

In PAT, a short-pulsed light source is typically used to irradiate the tissue, resulting in broadband PA waves with a frequency content extending to several tens or even hundreds of megahertz for acoustic detection. Following absorption of the light, an initial temperature rise induces a pressure rise, which propagates as a photoacoustic wave and finally is detected by a single-element ultrasonic transducer or a transducer array. There are two important time scales in the generation of PA waves,2 the thermal relaxation time (τth) and the stress relaxation time (τs). τth denotes the thermal relaxation (thermal diffusion) time of the desired voxel, and is given by Display Formula

τth=dc2αth,(1)
where dc is the desired spatial resolution and αth is the thermal diffusivity (m2/s). τs, which characterizes the stress relaxation time of the desired voxel, is given by Display Formula
τs=dcvs,(2)
where vs is the speed of sound (m/s).

Upon laser excitation, the fractional volume expansion of the heated region dV/V can be expressed as Display Formula

dVV=κp+βT,(3)
where κ denotes the isothermal compressibility (Pa1), p denotes the change in pressure (Pa), β denotes the thermal coefficient of volume expansion (K1), and T denotes the change in temperature (K).

If the laser pulse duration is shorter than τth and τs, the excitation satisfies both thermal and stress confinements. In this situation, the fractional volume change is negligible. Thus, the initial pressure rise p0 can be derived from Display Formula

p0=βTκ.(4)

Further, the local temperature rise can be expressed as Display Formula

T=ηthAeρCV,(5)
where ηth is the percentage of absorbed light converted into heat, and Ae is the specific optical energy deposition (J/m3). Substituting Eq. (5) into Eq. (4), we have Display Formula
p0=βκρCVηthAe.(6)

By defining the Gruneisen parameter Γ (dimensionless) as Display Formula

Γ=βκρCV,(7)

Equation (6) becomes Display Formula

p0=ΓηthAe.(8)
For single-photon optical absorption, Ae is proportional to the local optical fluence F (J/cm2). In this case, Eq. (8) becomes Display Formula
p0=ΓηthμaF,(9)
where μa is the optical absorption coefficient (cm1). Based on Eq. (9), the initial pressure rise is proportional to μa and F. Γ and ηth are usually approximated as constants, although they have been found to depend on the tissue type;22,23 thus, if p0 can be measured and F is known, μa can be recovered. After the generation of the initial pressure p0, an acoustic wave starts to propagate at the speed of sound in the material. The propagation in an inviscid medium can be described by general photoacoustic equations in the time-domain, as discussed in Sec. 2.2.

Photoacoustic Wave Propagation

The propagation and generation of acoustic pressure p(r,t) at position r and time t is governed by the following wave equation: Display Formula

(21vs22t2)p(r,t)=βκvs22T(r,t)t2.(10)

Note that T represents the temperature rise instead of the temperature, i.e., the temperature rise above its initial value. Under the condition of thermal confinement, where heat conduction is negligible, the heat diffusion equation becomes Display Formula

ρCVT(r,t)t=H(r,t),(11)
where H is the heating function, defined as the thermal energy deposited per unit volume and per unit time. Note that the heating function H is related to the specific optical energy deposition Ae by the following equation: Display Formula
H(r,t)=ηthAe(r,t)  t.(12)

Substituting Eq. (11) into Eq. (10), we have Display Formula

(21vs22t2)p(r,t)=βCPH(r,t)t,(13)
where CP is the specific heat capacity at constant pressure.

Solving Eq. (13) with the Green function approach, we have the following delta heating response: Display Formula

pδ(r,t)=14πvs2t[drp0(r)|rr|δ(t|rr|vs)],(14)
where p0(r) is the initial pressure rise at location r. If the heating pulse has a finite duration, the response can be computed by convolution Display Formula
p(r,t)=+dtpδ(r,tt)S(t),(15)
where S(t) is the temporal profile of the excitation pulse.

The goal of PA imaging is to retrieve the local pressure rise p0 inside the tissue. Based on Eq. (9), if we know the local optical fluence F, the absorption coefficient μa can then be calculated. In practice, the adjacent fluence F in the tissue is usually comparable, but the absorption coefficient μa differs considerably. For example, blood in the visible light region has much stronger absorption than other components in tissue.14 Thus, if F is assumed to be regionally homogeneous in anatomic PA imaging, then p0 can be used to directly map the relative absorption coefficient μa. There are two basic methods to recover the original p0 distribution inside the target once the pressures at the observation points are measured:11 reconstruction-based image formation and focused-scanning image formation. While the former is the basis of photoacoustic computed tomography (PACT), the latter is commonly used for photoacoustic microscopy (PAM) and occasionally for photoacoustic macroscopy (PAMac). Because PAM and PAMac mainly differ in their spatial resolution, i.e., PAM has a spatial resolution less than 50  μm while PAMac does not, we will only discuss PAM in this review paper.

Image Formation in Photoacoustic Computed Tomography

For PACT, the light is expanded to illuminate the whole object to be imaged. PA signals are acquired at multiple locations around the object, either by using a transducer array or by scanning a single-element transducer to simulate an array. Next, back-projecting all the PA data, similar to traditional computed tomography or positron emission tomography imaging, generates PA images of the object. Note that in order to detect PA signals from the same object at multiple locations, a transducer or transducer array with a large acceptance angle is desirable. Several methods are widely used for PA image formation,24,2530 such as universal back-projection (UBP)25 and time reversal.26

Demonstrated in spherical, cylindrical, and planar detection geometries, the UBP algorithm has the following formula: Display Formula

p0(r)=1Ω0SdΩ0×2[p(r,t)tp(r,t)t]|vst=|rr|,(16)
where Ω0 is the solid angle of the entire detection surface S with respect to a source point at r. The factor dΩ0/Ω0 weighs the contribution from each element on the detection surface S. The term p(r,t) is the direct back-projection of the detected PA signals onto a spherical surface centered at r. The first derivative with respect to time represents a ramp filter, which suppresses low frequency signals. In the UBP algorithm, the medium is assumed to be acoustically lossless and homogeneous.

The time-reversal method has recently been recognized as the least restrictive reconstruction algorithm: it can work for any closed geometry and can incorporate acoustic heterogeneities. In the time-reversal method, the measured acoustic pressure is retransmitted into the medium in time reversed order. The same wave equation is solved from t=T to t=0, where T is the maximum time for the acoustic wave to traverse the detection region. The measured pressure data are treated either as boundary conditions or as a source. To solve the wave equation, numerical methods are employed, such as time-domain finite-difference techniques or k-space pseudospectral methods. Thus, the time-reversal method is more computationally intensive than the UBP method, especially for 3-D image reconstruction.

Image Formation in Photoacoustic Microscopy

Different from reconstruction-based methods, the focused-scanning scheme of PAM usually focuses both the optical excitation and acoustic detection. If the optical focus is tighter than the acoustic focus, the technique is called optical resolution photoacoustic microscopy (OR-PAM);31,32 otherwise, it is called acoustic resolution photoacoustic microscopy (AR-PAM).3335 In both cases, each laser pulse generates a one-dimensional (1-D) photoacoustic image (A-line) along the axial direction. Raster-scanning laterally and then piecing together all the A-lines provides a 3-D PA image. Because each signal acquired by the transducer directly represents a 1-D image of a single line inside the object after minimal signal processing, there is no need for image reconstruction. Although raster-scanning is used in most cases, there are alternative scanning methods, such as circumferential-section-scanning for endoscopic imaging,36,3740 3-D arbitrary scanning for blood vessel monitoring,41 and random access scanning for cell tracking.42

As mentioned earlier, based on their different image formation mechanism, PA systems can be classified as either reconstruction-based PACT or focused-scanning-based PAM. In this section, we discuss typical PA systems and their characteristics, including spatial resolution, imaging speed, and penetration depth.

Photoacoustic Computed Tomography

Current PACT systems use spherical,43,4446 cylindrical,15,4752 or planar detection geometry.5360 Each geometry has several implementations. For spherical-view systems, either an arc-shaped transducer array44 or a hemispherical array with a spiral pattern45,46 is used. In both cases, mechanical scanning is required for dense spatial sampling, and 3-D reconstruction is performed. Figure 1(a) shows a hemispherical array based PACT system,46 with 512 ultrasonic transducer elements distributed in a hemispherical shell with a radius of 127 mm. The diameter of each transducer element is 3 mm, and the center frequency is 2 MHz, with a 70% bandwidth. The transducer array is scanned spirally to achieve dense spatial sampling for image reconstruction. As shown in Fig. 1(a), the bottom of the hemispherical shell contains an aperture for light delivery. In this case, pulses from an Alexandrite laser at 756 nm are used to excite the target. Depending on the spiral scanning pattern, total data acquisition time varies from 12 s for the smallest spiral (24-mm radius) to 3.2 min for the largest spiral (96-mm radius). Using a thin graphite fiber phantom (6-μm diameter), the resolution of this system was quantified to be 0.42 mm. Because spherical-view detection was implemented, this resolution was constant at different graphite fiber orientations. A 5.3-cm penetration was achieved in the phantom. As shown in Fig. 1(b), blood vessels in the breasts of two healthy volunteers were clearly imaged although their depths are not shown.

Graphic Jump Location
Fig. 1
F1 :

Hemispherical array based photoacoustic computed tomography (PACT) system and its representative images. (a) Schematic of a spherical-view photoacoustic system. (b) Representative human breast images from two healthy volunteers (1) and (2). R, right breast and L, left breast. Reproduced with permission from Refs. 45 and 46.

A representative cylindrical-view PACT system48 is shown in Fig. 2. The system contains a 512-element full ring transducer array with a ring diameter of 5 cm. Each transducer element has a center frequency of 5 MHz and an 80% (one-way) detection bandwidth.61 To improve the cross-sectional imaging ability, each element is cylindrically focused to reject out-of-plane signals. The combined foci from all elements provide a central imaging region with a 20  mm diameter and 1-mm thickness. Strictly speaking, such a system is a circular-view system, since only a ring is used to reconstruct the image instead of a cylinder. However, by taking advantage of its cylindrical focusing capability, high-quality two-dimensional (2-D) cross-sectional images are attainable. In addition, by scanning the sample or the array along the elevational direction, 3-D images can be acquired. Within the imaging region, the system provides 100- to 250-μm transverse resolution in the circumferential direction and 100-μm axial resolution in the radial direction. Limited by its 64-channel data acquisition and 10-Hz laser, the system acquires one frame/1.25  s. However, by employing a 512-channel real-time data acquisition system and a faster laser, higher rate imaging can be realized. Because of the fixed ring diameter, only 1-cm penetration depth was reported. As shown in Figs. 2(b) and 2(c), blood-rich organs, such as the liver, kidneys, spleen, spine, and GI tracts can be clearly visualized. In addition, blood-poor organs, such as the bladder, can also be imaged with the help of a near-infrared contrast agent (IRDye800, LI-COR, Inc.), as shown in Fig. 2(d).

Graphic Jump Location
Fig. 2
F2 :

Cylindrical-view PACT system and its representative images. (a) Schematic of the system, showing the confocal design of both the optics and acoustics. (b)–(d) In vivo images of athymic mice acquired by the system at different anatomical locations: (b) liver, (c) kidneys, and (d) bladder. BL, bladder; BM, backbone muscle; GI, GI tract; KN, kidney; LV, liver; PV, portal vein; SC, spinal cord; SP, spleen; and VC, vena cava. Reproduced with permission from Ref. 48.

There are different implementations for planar-view PACT, using either a 2-D ultrasound transducer array44,53 or a Fabry–Perot interferometer (FPI).55,60 Generally, the 2-D transducer array based PACT system has a higher frame rate, while the FPI-based system has higher sensitivity and a larger receiving angle. Figure 3(a) is a schematic of the FPI-based PACT system.62 In this type of PA imaging, the deformation of pressure-sensitive materials (e.g., polymer) is measured by optical resonance. The PA excitation beam was at 640 nm, and the PA probing beam was at 1550 nm. By raster scanning the probe beam across the FPI surface, photoacoustic waves can be mapped in 2-D. Depending on the detector bandwidth (22 MHz in this work), the axial resolution of this system was 27  μm. The lateral resolution was about 120  μm, which was determined by primarily the detection bandwidth and angular range. To scan an area of 16×16  mm2, the image acquisition time was about 8 min, which was limited by the 50-Hz pulse repetition rate of the excitation laser. The in vivo penetration depth of this system was demonstrated to be more than 10 mm. As shown in Fig. 3(b), two embryos (shaded in red) with detailed structures, such as the liver, ribs, pulmonary vein, and right atrium, can be clearly imaged.

Graphic Jump Location
Fig. 3
F3 :

Fabry–Perot interferometer (FBI) based PACT system. (a) Schematic and (b) a representative image of a FBI based PACT system. The red parts in (b) indicate the location of embryos. Reproduced with permission from Ref. 62.

Photoacoustic Microscopy

As mentioned earlier, there are two types of PAM: OR-PAM and AR-PAM. In OR-PAM, although the optical focus determines its lateral resolution, the detection transducer is also placed confocally with the optical focus to maximize the system’s detection sensitivity. Similarly, in AR-PAM, the excitation beam fills the entire acoustic focus to maximize the system’s sensitivity. The axial resolution in both OR-PAM and AR-PAM is determined by the detection bandwidth of the transducer. Due to the frequency dependence of acoustic attenuation, the bandwidth is chosen according to the desired imaging depth.

As shown in Fig. 4(a), a typical OR-PAM system employs an optical lens to focus light into the sample. A light-sound combiner transmits the light and reflects the sound. The combiner is composed of a right-angled prism, a thin layer of silicone oil, and a rhomboid prism for acoustic-optical coaxial alignment. Usually the laser beam is tightly focused, whose diameter can range from several hundred nanometers to several micrometers, depending on the numerical aperture (NA) of the optical focusing lens, the wavelength of the excitation beam, and the desired imaging depth. Relying on the tight optical focus, the penetration of an OR-PAM system is limited to about one transport mean free path in tissue (1  mm).12,63,64 However, by using longer wavelength laser pulses, which have longer transport mean free paths, the penetration limit can be increased.65 OR-PAM can image vasculature in a mouse ear,31 eye,6669 and brain31,70,71 clearly. Figure 4(b) shows a representative mouse ear image acquired with OR-PAM, where both a capillary bed and flowing red blood cells can be clearly visualized.

Graphic Jump Location
Fig. 4
F4 :

Typical optical resolution photoacoustic microscopy (OR-PAM) system. (a) Schematic and (b) a representative image of OR-PAM. BS, beam splitter; ConL, condenser lens; CorL, correction lens; FC, fiber collimator; HbT, total hemoglobin concentration; ND, neutral density; PD, photodiode; RAP, right-angle prism; RBC, red blood cell; RhP, rhomboid prism; SMF, single-mode fiber; SO, silicone oil; and US, ultrasonic transducer. Reproduced with permission from Ref. 31.

As shown in Fig. 5(a), in a typical AR-PAM system, the laser beam passes through a conical lens to form a ring-shaped illumination pattern.34,72,7375 The beam is then focused into the target by custom-made mirrors. The optical illumination on the skin surface has a donut shape with a dark center to minimize strong surface signals. Since acoustic scattering is much weaker than optical scattering in tissue, tight acoustic focusing can be maintained at depths. For example, using a 50-MHz center frequency transducer with an NA of 0.44, a lateral resolution of 45  μm was achieved with an imaging depth of more than 3 mm. By choosing transducers with different center frequencies and NAs, the lateral resolutions can be scaled. Note that although acoustic scattering is weak in tissue, high frequency ultrasound signals suffer strong attenuation. In the end, the attenuation becomes the limiting factor for deep high-resolution AR-PAM imaging. Figure 5(b) shows a representative AR-PAM image of a human forearm, where detailed vasculatures can be clearly discerned. Figure 5(c) is a photo of the forearm, where the red box indicates the image area of 8  mm×8  mm.

Graphic Jump Location
Fig. 5
F5 :

Typical acoustic resolution photoacoustic microscopy (AR-PAM) system. (a) Schematic and (b) a representative image of AR-PAM. AL, acoustic lens; CL, conical lens; FC, fiber coupler; M, mirror; MMF, multimode fiber; PD, photodiode; and UT, ultrasonic transducer. (c) Red box is the image area. Reproduced with permission from Ref. 74.

The lateral and axial resolutions as well as imaging depth are summarized in Table 1.

Table Grahic Jump Location
Table 1Summary of typical PA system characteristics.
Table Footer NoteaBased on in vivo data.
Table Footer NotebBased on phantom data.

Theoretically speaking, any material with sufficiently high optical absorption can be detected by PAT. Thus, by choosing the right wavelengths, PAT potentially can be used to image all materials. Specifically, in biological applications, absorbers are usually divided into endogenous and exogenous categories. We will discuss these two categories in Secs. 5.1 and 5.2.

Endogenous Contrast Agents

The primary advantage of endogenous contrast agents is that they allow label-free imaging, so they do not affect the original biological environment. In biological tissue, there are varieties of optical absorbers,14 such as DNA/RNA,79,80 cytochromes,81 bilirubin,82 myoglobin,83,84 hemoglobin,85,86 methemoglobin,87 carboxyhemoglobin,88 melanin,54,89,90 lipid,9193 water,94,95 and glucose.96,97 Among all these agents, DNA/RNA is commonly used for cell nuclear imaging in the ultraviolet region [Fig. 6(a)],79 hemoglobin is widely used for vascular imaging in the visible and the near-infrared spectral regions [Fig. 6(b)],19 and melanin is employed for melanoma tumor imaging in the near-infrared region [Fig. 6(c)].54 In addition, in the near-infrared region, lipids and water are used for atherosclerotic plaque98,99 and injury94 imaging, respectively. As shown in Fig. 7, different endogenous contrast agents have different absorption spectra. Thus, PAT can separate them with spectral measurement, when the local optical fluence is known.

Graphic Jump Location
Fig. 6
F6 :

PAT imaging of endogenous contrast agents: DNA/RNA (a), hemoglobin (b), and melanin (c). Reproduced with permission from Ref. 14.

Graphic Jump Location
Fig. 7
F7 :

Absorption spectra of the main endogenous pigments in tissue at normal concentrations. HbO2, oxygenated hemoglobin; HbR, deoxygenated hemoglobin; MbO2, oxygenated myoglobin; and MbR, deoxygenated myoglobin. Reproduced with permission from Refs. 79, 19, and 54.

A representative application of spectral decomposition is to quantify the oxygen saturation of hemoglobin (sO2) in blood vessels by differentiating signals from oxy-hemoglobin (HbO2) and deoxy-hemoglobin (HbR). As derived above, the measured PA amplitude of blood is proportional to the local fluence and the absorption coefficient of blood Display Formula

p(λ1)=kμa(λ1)F(λ1)=k[ϵHbR(λ1)CHbR+ϵHbO2(λ1)CHbO2]F(λ1),(17)
where p(λ1) is the measured PA amplitude at wavelength λ1, k is a system constant, μa is the blood absorption coefficient, F is the optical fluence. ϵHbR and ϵHbO2 are the molar extinction coefficients of HbR and HbO2, respectively, and CHbR and CHbO2 are the concentrations of HbR and HbO2, respectively. For a given system, k is a constant. In OR-PAM, which works within the optical ballistic regime, F can be corrected for by measuring the surface optical fluence. Thus, by performing measurements at two wavelengths, the relative concentrations of HbR and HbO2 can be quantified Display Formula
CHbR=kp(λ1)ϵHbR(λ2)p(λ2)ϵHbR(λ1)ϵHbR(λ1)ϵHbO2(λ2)ϵHbR(λ2)ϵHbO2(λ1),(18)
and Display Formula
CHbO2=kp(λ1)ϵHbR(λ2)p(λ2)ϵHbR(λ1)ϵHbR(λ2)ϵHbO2(λ1)ϵHbR(λ1)ϵHbO2(λ2),(19)
where λ2 stands for the second wavelength. By definition, the sO2 value can be calculated as Display Formula
sO2=CHbO2CHbO2+  CHbR=p(λ1)ϵHbR(λ2)p(λ2)ϵHbR(λ1)p(λ1)[ϵHbR(λ2)ϵHbO2(λ2)]p(λ2)[ϵHbR(λ1)ϵHbO2(λ1)].(20)
However, in AR-PAM and PACT, which work in the optical (quasi)diffusive regime, it is challenging to correct for F. So far, several methods have been proposed to address this issue and achieve more accurate sO2 measurement in the optical (quasi)diffusive regime,100103 such as directly fitting the temporal profiles of PA signals,100,103 analyzing their acoustic spectra,101 and measuring their dynamics.102

Exogenous Contrast Agents

Compared with endogenous contrast agents, exogenous ones can be engineered to absorb at specific wavelengths to maximize their detection sensitivities. In addition, exogenous agents can be made to bind to only certain molecules; thus, these molecules can be selectively imaged by PAT. So far, a variety of exogenous agents have been developed,9,104,105 including nanoparticles,106109 organic dyes,110115 and proteins.116,117 Recently, for PA imaging, agents with specially designed functions have been developed, such as photosensitizing,118,119 activatable,120 and switchable agents.121123 Note that since hemoglobin and water have strong absorption in the visible and midinfrared regions, respectively, most of these exogenous agents are designed to work in the near-infrared window, i.e., from 700 to 1350 nm. Usually, to enable more accurate spectral decomposition, two or more wavelengths are chosen to image blood and exogenous contrasts separately. Figure 8 shows two examples of using exogenous contrast agents in PA imaging: methylene blue115 and gold nanoparticles.108 Before the contrasts were injected, only blood vessels could be detected, as shown in Figs. 8(a) and 8(c). However, after injecting the contrasts, a sentinel lymph node and tumor appeared with high contrast, as seen in Figs. 8(b) and 8(d), respectively.

Graphic Jump Location
Fig. 8
F8 :

PAT imaging aided by exogenous contrast agents. PA images acquired before (a) and 52  min after (b) methylene blue injection, showing a dramatic PA signal increase in a sentinel lymph node (SLN). PA images acquired (c) before and (d) 6 h after gold nanoparticle injection, showing a significant PA signal increase in a melanoma tumor. Reproduced with permission from Refs. 115 (a) and (b) and 108 (c) and (d).

With its multiparameter and multiscale imaging capability, PAT has been applied in many different disciplines, including cardiology,77,124,125 dermatology,126129 oncology,130133 ophthalmology,67,69,134136 gastroenterology,3638,40,137140 hematology,141143 and neurology.144147 In terms of imaging locations, PAT can be used for human breast imaging148150 and small-animal imaging of the brain,70,151,152 ear,153155 eye,134136 liver,15 intestine,156 and skin.54,90 In terms of functionality, PAT has been widely used for anatomical,157,158 functional,159161 molecular,9,82 and metabolic imaging.162,163 As for object size, PAT can detect objects ranging from organelles to human organs or whole-body small animals.11 PAT has been used for both small animal imaging (such as zebrafish,164 mice,165 rats,151 and rabbits166) and human imaging.72 In this review paper, rather than cover details of all the applications, we will simply list the most recent advances and significant applications of PAT.

High Speed Imaging of Mouse Brain Functions

PAT has been extensively applied for brain studies. Wang et al.47 reported the first in vivo mouse brain function study with PAT. Using a circular-view PACT system, they imaged rat brain responses to vibrational stimulations to whiskers. Because a single-element ultrasonic transducer with a center frequency of 3.5 MHz was used, both the frame rate and spatial resolution were limited. With newer techniques, both the frame rate and spatial resolution have been significantly improved. For example, using an ultrasonic transducer array with 512 elements, mouse brain imaging at one frame per 1.25 s has been achieved.48 Using OR-PAM, optical resolution mouse brain images, i.e., at micrometer or submicrometer level resolution, were obtained.167

Recently, Yao et al.70 reported fast functional PAM (ffPAM) for mouse brain function imaging in action. Working as OR-PAM, this system has a lateral resolution of 3  μm and an axial resolution of 15  μm. Using a water-immersed microelectromechanical system (MEMS) scanning mirror along with a 500 kHz repetition rate laser, ffPAM has a 2-D frame rate of 400 Hz over a 3-mm scanning range. With a 3×2  mm2 field of view, a 3-D volumetric rate of 1 Hz can be achieved. By using a single-wavelength pulse-width-based method (PW-sO2), ffPAM can perform high speed imaging of sO2 up to a 1-D rate of 100 kHz. As shown in Fig. 9(a), to implement the PW-sO2 method, lasers with different pulse widths are used, i.e., 3 ps and 3 ns. Figure 9(b) shows a representative PA image of the mouse brain with the skull intact, where the cortex vasculature can be visualized in detail. With the PW-sO2 method, only 40 s were required to acquire the sO2 map shown in Fig. 9(c).

Graphic Jump Location
Fig. 9
F9 :

Fast functional PAM (ffPAM) of the mouse brain. (a) Schematic of the ffPAM system. MEMS, microelectromechanical system; OAC, optical-acoustic combiner; PBS, polarizing beam splitter; and UT, ultrasonic transducer. Anatomical (b) and (c) functional images of the mouse brain. sO2, oxygen saturation of hemoglobin; and SV, skull vessel. Reproduced with permission from Ref. 70.

To further demonstrate the fast functional imaging capability, the authors studied mouse cortical responses to electrical stimulations of the hindlimbs. As shown in Fig. 10(a), upon stimulations, PA signals in the corresponding regions increased. In addition, sO2 levels increased in veins and deep capillary beds upon stimulation, as shown in Fig. 10(b). However, there was no arterial sO2 response, which is consistent with the fact that arterial blood had not reached the capillaries for oxygen exchange and thus maintained a high oxygenation level.

Graphic Jump Location
Fig. 10
F10 :

ffPAM of brain responses to electrical stimulations of the hindlimbs of mice. (a) Fractional PA amplitude changes during left hindlimb stimulation (LHS) and right hindlimb stimulation (RHS). (b) sO2 imaging (marked by the dashed box) before and during stimulations of the left hindlimb. Reproduced with permission from Ref. 70.

Sentinel Lymph Node Biopsy Guidance in Patients with Breast Cancer

Sentinel lymph node (SLN) biopsy is a standard of care in diagnosing cancer, including breast and melanoma cancers. Because the SLN is the first node in the lymphatic system that drains a tumor site, metastasis can be diagnosed by SLN biopsy. A positive biopsy result suggests that cancer has spread to the node and probably to distant organs. Recently, a handheld dual-modality ultrasound (US) and PAT system was used to accurately identify an SLN and thus to precisely guide SLN biopsy.168

The dual-modality system was modified from a clinical US scanner (iU22, Philips Healthcare). To highlight SLNs in patients, a very common clinical contrast agent, methylene blue, was used. As shown in Fig. 11, laser pulses at two wavelengths of 665 and 1064 nm spectrally differentiated methylene blue from other major absorbers, such as blood. The pulse width was around 6.5 ns, and the pulse repetition rate was 10 Hz. With a custom-built data acquisition computer, this system could achieve a frame rate of 5 Hz for coregistered US and PA imaging. To improve the detection sensitivity and operation convenience, the light delivery fiber bundles and ultrasonic transducer array were integrated into a single probe, as shown in Fig. 11. Because the probe is handheld, it is convenient for physicians to operate for SLN biopsy guidance.

Graphic Jump Location
Fig. 11
F11 :

Schematic of the dual-modality ultrasound and photoacoustic system for SLN detection. Reproduced with permission from Ref. 168.

As shown in Fig. 12, by combining both US and PA, the SLN in a patient with breast cancer can be clearly detected. In addition, taking advantage of its high frame rate, this system can provide guidance for fine needle aspiration biopsy (FNAB) with minimal invasiveness. Because both the SLN and the needle can be imaged with high contrast, FNAB can be performed with high accuracy.

Graphic Jump Location
Fig. 12
F12 :

In vivo images of a human axilla acquired by US (a), PA (b), and both (c). Reproduced with permission from Ref. 168.

Multiscale Photoacoustic Tomography with Photo-Switchable Protein Contrast

A reversibly switchable bacterial phytochrome, Rhodopseudomonas palustris (BphP1), has been recently combined with PAT for deep molecular imaging with improved detection sensitivity and spatial resolution.121 BphP1 has two states: Pfr and Pr. Upon 730- to 790-nm light illumination, it undergoes a Pfr→Pr photoconversion; while upon 630- to 690-nm light illumination, Pr→Pfr photoconversion happens. For simplicity, the Pfr state of BphP1 was denoted as the ON state and the Pr state as the OFF state. In the reported work, 780 nm light was used for Pfr→Pr photoconversion, and 630-nm light was used for Pr→Pfr photoconversion. Because the background absorbers, primarily blood, did not have the same switchable properties as BphP1, taking differential images largely suppressed the background signals and thus increased the detection sensitivity for BphP1-expressing tumors in deep tissue.

First implementing BphP1 with a circular-view PACT system, the authors observed a noise-equivalent detection sensitivity of 20 U87 human glioblastoma cells expressing BphP1, as shown in Fig. 13(a). With the single-wavelength differential method, the CNR was about 34-fold higher than the two-wavelength spectral unmixing method. In the in vivo experiment, a mouse was imaged 1 week after injection of BphP1-expressing U87 cells into its left kidney. As shown in Fig. 13(b), although major organs, such as the skin, kidneys, spleen, and bladder, can all be clearly imaged, the tumor in the left kidney could not be detected because of the overwhelming blood signals. However, after 20 cycles of photoswitching, the differential image showed the tumor at depths up to 8 mm with high contrast, as seen in Figs. 13(b) and 13(c). The line profiles in Fig. 13(b) show that while the background blood signals remained unchanged, the photoswitchable tumor had clearly different signals in the ON- and OFF-state images [Fig. 13(d)]. A histological examination taken after PA imaging confirmed the tumor, as shown in Fig. 13(e). Another tumor detection experiment, in a mouse brain, also showed the superior sensitivity of the BphP1-enhanced PACT system, as shown in Fig. 13(f).

Graphic Jump Location
Fig. 13
F13 :

Circular-view PACT system combined with reversely switchable BphP1 for deep imaging. (a) Contrast-to-noise ratio (CNR) of U87 cells imaged by PACT at 10-mm depth. (b) Whole-body mouse images acquired with BphP1 at different state. The differential image clearly shows that the tumor is at the left kidney. (c) An overlay of the differential image (in color) and the blood-dominated OFF-state image (in grayscale). (d) Normalized PA amplitude along the dashed line in (b), showing the contrast enhancement of the tumor in the differential image. (e) A histology image of the left kidney showing the tumor region. (f) PACT image of a mouse brain with a U87 tumor expressing BphP1. The tumor was 3  mm beneath the scalp. Reproduced with permission from Ref. 121.

Combined with a high NA (1.4 in this work) OR-PAM system [Fig. 14(a)], this reversely switchable protein can also be used for super-resolution PA imaging (RS-SPAM). As shown in Fig. 14(b), because the switching-off rate is proportional to the local excitation intensity, PA signals from the center of the excitation spot will decay faster than those from the periphery. By fitting the nonlinear signal-decay process, a high-order coefficient can be extracted and thus subdiffraction resolution can be achieved. As shown in Figs. 14(c)14(g), RS-SPAM showed much finer lateral and axial resolutions. The lateral resolution was quantified to be 141  nm, which is about twofold better than that of conventional PAM, and the axial resolution was around 400 nm in RS-SPAM, which was around 75 times better than that of conventional PAM.

Graphic Jump Location
Fig. 14
F14 :

Reversely switchable BphP1-enhanced super-resolution PAM (RS-SPAM). (a) Schematic of the RS-SPAM system. (b) Subdiffraction-resolution principle. In the diffraction-limited excitation volume (green), part of the ON-state BphP1 molecules (black dots) are switched to the OFF state, where the switching rate is proportional to the local optical intensity. The differential signals generate super-resolution images. (c) Conventional (Conv.) PAM and RS-SPAM images of BphP1-expressing bacteria, showing the superior lateral resolution of RS-SPAM. (d) Zoomed-in images of the dashed box areas in (c). (e) Normalized PA amplitude along the dashed line in (d). (f) Depth-encoded RS-SPAM image of BphP1-expressing U87 cells. (g) x-z cross images of two stacked U87 cells, showing the finer axial resolution of RS-SPAM. Reproduced with permission from Ref. 121.

In summary, PAT is a highly scalable imaging modality with major implementations of PAM and PACT. In PAM, light is focused into the target and a focused transducer is typically used for the signal detection. Thus, its lateral resolution is determined by either the optical focus (OR-PAM) or acoustic focus (AR-PAM), depending on which one is tighter. In OR-PAM, the lateral resolution is given by 0.51λo/NAo, where λo is the light wavelength, and NAo is the NA of the optical focusing lens. In AR-PAM, the lateral resolution is given by 0.72λa/NAa, where λa is the central acoustic wavelength of the ultrasonic transducer, and NAa is the NA of the acoustic lens. The difference in the scaling factors arises because optical excitation is based on light intensity, while ultrasonic detection is based on acoustic amplitude. In both cases, the axial resolution is given by 0.88c/Δf, where c is the speed of sound in soft tissue, and Δf is the bandwidth of the ultrasonic transducer. This axial resolution formula also applies to PACT systems. However, unlike PAM, lateral resolutions in PACT are usually not a constant. Thus, we can see that by choosing different optical focusing lenses or ultrasonic transducers, both lateral and axial resolution can be changed. Super optical resolution has been achieved in OR-PAM.169 In addition, because acoustic attenuation in tissues increases with the acoustic frequency, ultrasonic transducers with different center frequencies should be chosen according to the desired imaging penetration limit. The maximum penetration achieved in PA images is 7  cm with a lateral resolution about 720  μm.11

PAT is also a multiparameter imaging modality. In most of the cases, because hemoglobin provides the highest contrast in biological imaging, most studies focus on extracting and studying blood-related parameters, such as blood vessel diameter,31 blood flow speed,170,171 hemoglobin oxygen concentration,19,31 blood pulse wave velocity,172 and the metabolic rate of oxygen.162 PAT has provided valuable information for studying vasculature-related diseases, such as stroke,173 diabetes,174 and atherosclerosis.98,175,176 In addition, because neural activities are closely related to hemodynamics, measuring these hemodynamic parameters is also useful for neurological studies, such as studies on epilepsy,177 resting state functional connectivity,152 and stimulation responses.147 Because of its high contrast in comparison to other absorbers, such as melanin54 and DNA/RNA,79 PAT can also image other important biological parameters. Imaging melanin can provide the depth of melanoma, as well as its rate of growth and metastatic rate,54 which are all very important parameters in diagnosing and treating melanoma patients. Imaging DNA/RNA provides a tool for label-free measurement of cell nuclear density, which potentially can be used for tumor demarcation.

PAT has become one of the fastest growing fields in biomedical imaging. So far, PAT has translated several important applications into clinics, which may help solve existing problems in health care. For example, noninvasive detection of SLNs168 in patients can potentially provide minimally invasive cancer staging, and quantification of melanoma depth54 can potentially guide more accurate surgeries, both reducing morbidity and costs. With advances in new techniques, we anticipate that PAT will provide valuable information for disease diagnosis as well as treatment.

The authors would like to thank Professor James Ballard for manuscript editing. This work was sponsored in part by National Institutes of Health Grant Nos. DP1 EB016986 (NIH Director’s Pioneer Award), R01 CA186567 (NIH Director’s Transformative Research Award), and S10 RR026922. L. V. W. has a financial interest in Microphotoacoustics, Inc., which, however, did not support this work.

Wang  L. V., and Gao  L., “Photoacoustic microscopy and computed tomography: from bench to bedside,” Annu. Rev. Biomed. Eng.. 16, , 155 –185 (2014).CrossRef
Wang  L. V., “Tutorial on photoacoustic microscopy and computed tomography,” IEEE J. Sel. Top. Quantum Electron.. 14, (1 ), 171 –179 (2008).CrossRef
Beard  P., “Biomedical photoacoustic imaging,” Interface Focus. 1, (4 ), 602 –631 (2011).CrossRef
Yao  J., and Wang  L. V., “Photoacoustic tomography: fundamentals, advances and prospects,” Contrast Media Mol. Imaging. 6, (5 ), 332 –345 (2011).CrossRef
Ntziachristos  V., “Going deeper than microscopy: the optical imaging frontier in biology,” Nat. Methods. 7, (8 ), 603 –614 (2010). 1548-7091 CrossRef
Hu  S., and Wang  L. V., “Photoacoustic imaging and characterization of the microvasculature,” J. Biomed. Opt.. 15, (1 ), 011101  (2010). 1083-3668 CrossRef
Li  C., and Wang  L. V., “Photoacoustic tomography and sensing in biomedicine,” Phys. Med. Biol.. 54, (19 ), R59 –R97 (2009).CrossRef
Wang  L. V., “Multiscale photoacoustic microscopy and computed tomography,” Nat. Photonics. 3, (9 ), 503 –509 (2009).CrossRef
Kim  C., , Favazza  C., and Wang  L. V., “In vivo photoacoustic tomography of chemicals: high-resolution functional and molecular optical imaging at new depths,” Chem. Rev.. 110, (5 ), 2756 –2782 (2010).CrossRef
Cai  X.  et al., “Photoacoustic microscopy in tissue engineering,” Mater. Today. 16, (3 ), 67 –77 (2013).CrossRef
Wang  L. V., and Hu  S., “Photoacoustic tomography: in vivo imaging from organelles to organs,” Science. 335, (6075 ), 1458 –1462 (2012). 0036-8075 CrossRef
Yao  J., and Wang  L. V., “Photoacoustic microscopy,” Laser Photon. Rev.. 7, (5 ), 758 –778 (2013).CrossRef
Yao  J., , Song  L., and Wang  L. V., “Photoacoustic microscopy superdepth, superresolution, and superb contrast,” IEEE Pulse. 6, (3 ), 34 –37 (2015).CrossRef
Yao  J., and Wang  L. V., “Sensitivity of photoacoustic microscopy,” Photoacoustics. 2, (2 ), 87 –101 (2014).CrossRef
Xia  J., and Wang  L. V., “Small-animal whole-body photoacoustic tomography: a review,” IEEE Trans. Bio-Med. Eng.. 61, (5 ), 1380 –1389 (2014).CrossRef
Yao  J., and Wang  L. V., “Photoacoustic brain imaging: from microscopic to macroscopic scales,” Neurophotonics. 1, (1 ), 011003  (2014).CrossRef
Mallidi  S., , Luke  G. P., and Emelianov  S., “Photoacoustic imaging in cancer detection, diagnosis, and treatment guidance,” Trends Biotechnol.. 29, (5 ), 213 –221 (2011).CrossRef
Cox  B.  et al., “Quantitative spectroscopic photoacoustic imaging: a review,” J. Biomed. Opt.. 17, (6 ), 061202  (2012). 1083-3668 CrossRef
Hu  S., and Wang  L. V., “Optical-resolution photoacoustic microscopy: auscultation of biological systems at the cellular level,” Biophys. J.. 105, (4 ), 841 –847 (2013).CrossRef
Wang  L. V., “Prospects of photoacoustic tomography,” Med. Phys.. 35, (12 ), 5758 –5767 (2008).CrossRef
Wang  L. V., “Multiscale photoacoustic microscopy and computed tomography,” Nat. Photonics. 3, (9 ), 503 –509 (2009). 1749-4885 CrossRef
Yao  D. K.  et al., “Photoacoustic measurement of the Gruneisen parameter of tissue,” J. Biomed. Opt.. 19, (1 ), 017007  (2014). 1083-3668 CrossRef
Gao  L.  et al., “Intracellular temperature mapping with fluorescence-assisted photoacoustic-thermometry,” Appl. Phys. Lett.. 102, (19 ) (2013).CrossRef
Xu  M. H., and Wang  L. H. V., “Photoacoustic imaging in biomedicine,” Rev. Sci. Instrum.. 77, (4 ), 041101  (2006).CrossRef
Xu  M. H., and Wang  L. H. V., “Universal back-projection algorithm for photoacoustic computed tomography,” Phys. Rev. E. 71, (1 ), 016706   (2005).CrossRef
Treeby  B. E., and Cox  B. T., “k-Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields,” J. Biomed. Opt.. 15, (2 ), 021314  (2010).CrossRef
Xu  M., and Wang  L. V., “Analytic explanation of spatial resolution related to bandwidth and detector aperture size in thermoacoustic or photoacoustic reconstruction,” Phys. Rev. E. 67, (5 Pt 2 ), 056605  (2003).CrossRef
Wang  K.  et al., “Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography,” Phys. Med. Biol.. 57, (17 ), 5399 –5423 (2012).CrossRef
Wang  K.  et al., “Discrete imaging models for three-dimensional optoacoustic tomography using radially symmetric expansion functions,” IEEE Trans. Med. Imaging. 33, (5 ), 1180 –1193 (2014).CrossRef
Wang  K.  et al., “An imaging model incorporating ultrasonic transducer properties for three-dimensional optoacoustic tomography,” IEEE Trans. Med. Imaging. 30, (2 ), 203 –214 (2011).CrossRef
Hu  S., , Maslov  K., and Wang  L. V., “Second-generation optical-resolution photoacoustic microscopy with improved sensitivity and speed,” Opt. Lett.. 36, (7 ), 1134 –1136 (2011). 0146-9592 CrossRef
Maslov  K.  et al., “Optical-resolution photoacoustic microscopy for in vivo imaging of single capillaries,” Opt. Lett.. 33, (9 ), 929 –931 (2008). 0146-9592 CrossRef
Zhang  H. F., , Maslov  K., and Wang  L. H. V., “In vivo imaging of subcutaneous structures using functional photoacoustic microscopy,” Nat. Protoc.. 2, (4 ), 797 –804 (2007).CrossRef
Zhang  H. F.  et al., “Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging,” Nat. Biotechnol.. 24, (7 ), 848 –851 (2006).CrossRef
Maslov  K., , Stoica  G., and Wang  L. H. V., “In vivo dark-field reflection-mode photoacoustic microscopy,” Opt. Lett.. 30, (6 ), 625 –627 (2005). 0146-9592 CrossRef
Yang  J. M.  et al., “Photoacoustic endoscopy,” Opt. Lett.. 34, (10 ), 1591 –1593 (2009). 0146-9592 CrossRef
Yang  J. M.  et al., “Catheter-based photoacoustic endoscope,” J. Biomed. Opt.. 19, (6 ), 066001  (2014). 1083-3668 CrossRef
Yang  J. M.  et al., “Optical-resolution photoacoustic endomicroscopy in vivo,” Biomed. Opt. Express.. 6, (3 ), 918 –932 (2015).CrossRef
Yang  J. M.  et al., “Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo,” Nat. Med.. 18, (8 ), 1297 –1302 (2012). 1078-8956 CrossRef
Li  C. Y.  et al., “Urogenital photoacoustic endoscope,” Opt. Lett.. 39, (6 ), 1473 –1476 (2014). 0146-9592 CrossRef
Yeh  C.  et al., “Three-dimensional arbitrary trajectory scanning photoacoustic microscopy,” J. Biophotonics. 8, (4 ), 303 –308 (2015).CrossRef
Liang  J. Y.  et al., “Random-access optical-resolution photoacoustic microscopy using a digital micromirror device,” Opt. Lett.. 38, (15 ), 2683 –2686 (2013). 0146-9592 CrossRef
Kruger  R. A.  et al., “Thermoacoustic molecular imaging of small animals,” Mol. Imaging. 2, (2 ), 113 –123 (2003).CrossRef
Brecht  H. P.  et al., “Whole-body three-dimensional optoacoustic tomography system for small animals,” J. Biomed. Opt.. 14, (6 ), 064007  (2009). 1083-3668 CrossRef
Kruger  R. A.  et al., “Photoacoustic angiography of the breast,” Med. Phys.. 37, (11 ), 6096 –6100 (2010).CrossRef
Kruger  R. A.  et al., “Dedicated 3D photoacoustic breast imaging,” Med. Phys.. 40, (11 ), 113301  (2013).CrossRef
Wang  X. D.  et al., “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol.. 21, (7 ), 803 –806 (2003).CrossRef
Xia  J.  et al., “Whole-body ring-shaped confocal photoacoustic computed tomography of small animals in vivo,” J. Biomed. Opt.. 17, (5 ), 050506  (2012). 1083-3668 CrossRef
Li  C. H., and Wang  L. H. V., “Photoacoustic tomography of the mouse cerebral cortex with a high-numerical-aperture-based virtual point detector,” J. Biomed. Opt.. 14, (2 ), 024047  (2009). 1083-3668 CrossRef
Li  C. H.  et al., “Real-time photoacoustic tomography of cortical hemodynamics in small animals,” J. Biomed. Opt.. 15, (1 ), 010509  (2010). 1083-3668 CrossRef
Buehler  A.  et al., “Video rate optoacoustic tomography of mouse kidney perfusion,” Opt. Lett.. 35, (14 ), 2475 –2477 (2010). 0146-9592 CrossRef
Nie  L. M.  et al., “Photoacoustic tomography through a whole adult human skull with a photon recycler,” J. Biomed. Opt.. 17, (11 ), 110506  (2012). 1083-3668 CrossRef
Wang  Y.  et al., “In vivo three-dimensional photoacoustic imaging based on a clinical matrix array ultrasound probe,” J. Biomed. Opt.. 17, (6 ), 061208  (2012). 1083-3668 CrossRef
Zhou  Y.  et al., “Handheld photoacoustic probe to detect both melanoma depth and volume at high speed in vivo,” J. Biophotonics. 1, (7 ) (2015).CrossRef
Zhang  E., , Laufer  J., and Beard  P., “Backward-mode multiwavelength photoacoustic scanner using a planar Fabry-Perot polymer film ultrasound sensor for high-resolution three-dimensional imaging of biological tissues,” Appl. Opt.. 47, (4 ), 561 –577 (2008).CrossRef
Piras  D.  et al., “Photoacoustic imaging of the breast using the twente photoacoustic mammoscope: present status and future perspectives,” IEEE J. Sel. Top. Quantum Electronics. 16, (4 ), 730 –739 (2010).CrossRef
Heijblom  M.  et al., “Visualizing breast cancer using the Twente photoacoustic mammoscope: What do we learn from twelve new patient measurements?” Opt. Express.. 20, (11 ), 11582 –11597 (2012). 1094-4087 CrossRef
Heijblom  M.  et al., “Appearance of breast cysts in planar geometry photoacoustic mammography using 1064-nm excitation,” J. Biomed. Opt.. 18, (12 ), 126009  (2013). 1083-3668 CrossRef
Laufer  J.  et al., “Three-dimensional noninvasive imaging of the vasculature in the mouse brain using a high resolution photoacoustic scanner,” Appl. Optics. 48, (10 ), D299 –D306 (2009).CrossRef
Laufer  J.  et al., “In vivo preclinical photoacoustic imaging of tumor vasculature development and therapy,” J. Biomed. Opt.. 17, (5 ), 056016  (2012). 1083-3668 CrossRef
Xia  J.  et al., “Wide-field two-dimensional multifocal optical-resolution photoacoustic-computed microscopy,” Opt. Lett.. 38, (24 ), 5236 –5239 (2013). 0146-9592 CrossRef
Laufer  J.  et al., “In vivo photoacoustic imaging of mouse embryos,” J. Biomed. Opt.. 17, (6 ), 061220  (2012). 1083-3668 CrossRef
Zhou  Y., , Yao  J. J., and Wang  L. H. V., “Optical clearing-aided photoacoustic microscopy with enhanced resolution and imaging depth,” Opt. Lett.. 38, (14 ), 2592 –2595 (2013). 0146-9592 CrossRef
Liu  Y., , Zhang  C., and Wang  L. H. V., “Effects of light scattering on optical-resolution photoacoustic microscopy,” J. Biomed. Opt.. 17, (12 ), 126014  (2012). 1083-3668 CrossRef
Hai  P. F.  et al., “Near-infrared optical-resolution photoacoustic microscopy,” Opt. Lett.. 39, (17 ), 5192 –5195 (2014). 0146-9592 CrossRef
Hu  S.  et al., “Label-free photoacoustic ophthalmic angiography,” Opt. Lett.. 35, (1 ), 1 –3 (2010). 0146-9592 CrossRef
Wu  N.  et al., “High-resolution dual-modality photoacoustic ocular imaging,” Opt. Lett.. 39, (8 ), 2451 –2454 (2014). 0146-9592 CrossRef
Song  W.  et al., “Integrating photoacoustic ophthalmoscopy with scanning laser ophthalmoscopy, optical coherence tomography, and fluorescein angiography for a multimodal retinal imaging platform,” J. Biomed. Opt.. 17, (6 ), 061206  (2012). 1083-3668 CrossRef
Liu  X. J.  et al., “Optical coherence photoacoustic microscopy for in vivo multimodal retinal imaging,” Opt. Lett.. 40, (7 ), 1370 –1373 (2015). 0146-9592 CrossRef
Yao  J. J.  et al., “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods. 12, (5 ), 407 –410 (2015).CrossRef
Hu  S.  et al., “Functional transcranial brain imaging by optical-resolution photoacoustic microscopy,” J. Biomed. Opt.. 14, (4 ), 040503  (2009). 1083-3668 CrossRef
Zhou  Y.  et al., “Microcirculatory changes identified by photoacoustic microscopy in patients with complex regional pain syndrome type I after stellate ganglion blocks,” J. Biomed. Opt.. 19, (8 ), 086017  (2014). 1083-3668 CrossRef
Zhang  H. F.  et al., “In vivo volumetric imaging of subcutaneous microvasculature by photoacoustic microscopy,” Opt. Express.. 14, (20 ), 9317 –9323 (2006). 1094-4087 CrossRef
Favazza  C. P., , Cornelius  L. A., and Wang  L. H. V., “In vivo functional photoacoustic microscopy of cutaneous microvasculature in human skin,” J. Biomed. Opt.. 16, (2 ), 026004  (2011). 1083-3668 CrossRef
Favazza  C. P.  et al., “In vivo photoacoustic microscopy of human cutaneous microvasculature and a nevus,” J. Biomed. Opt.. 16, (1 ), 016015  (2011). 1083-3668 CrossRef
Zhang  C., , Maslov  K., and Wang  L. H. V., “Subwavelength-resolution label-free photoacoustic microscopy of optical absorption in vivo,” Opt. Lett.. 35, (19 ), 3195 –3197 (2010). 0146-9592 CrossRef
Wang  L. D.  et al., “Video-rate functional photoacoustic microscopy at depths,” J. Biomed. Opt.. 17, (10 ), 106007  (2012). 1083-3668 CrossRef
Ke  H. X.  et al., “Performance characterization of an integrated ultrasound, photoacoustic, and thermoacoustic imaging system,” J. Biomed. Opt.. 17, (5 ), 056010  (2012). 1083-3668 CrossRef
Yao  D. K.  et al., “In vivo label-free photoacoustic microscopy of cell nuclei by excitation of DNA and RNA,” Opt. Lett.. 35, (24 ), 4139 –4141 (2010). 0146-9592 CrossRef
Yao  D. K.  et al., “Optimal ultraviolet wavelength for in vivo photoacoustic imaging of cell nuclei,” J. Biomed. Opt.. 17, (5 ), 056004  (2012). 1083-3668 CrossRef
Zhang  C.  et al., “Label-free photoacoustic microscopy of cytochromes,” J. Biomed. Opt.. 18, (2 ), 020504  (2013). 1083-3668 CrossRef
Zhou  Y.  et al., “Photoacoustic microscopy of bilirubin in tissue phantoms,” J. Biomed. Opt.. 17, (12 ), 126019  (2012). 1083-3668 CrossRef
Zhang  C.  et al., “Label-free photoacoustic microscopy of myocardial sheet architecture,” J. Biomed. Opt.. 17, (6 ), 060506  (2012). 1083-3668 CrossRef
Goldschmidt  B. S.  et al., “Photoacoustic measurement of refractive index of dye solutions and myoglobin for biosensing applications,” Biomed. Opt. Express.. 4, (11 ), 2463 –2476 (2013).CrossRef
Zhang  H. F.  et al., “Imaging of hemoglobin oxygen saturation variations in single vessels in vivo using photoacoustic microscopy,” Appl. Phys. Lett.. 90, (5 ), 053901  (2007). CrossRef
Zhou  Y.  et al., “Calibration-free absolute quantification of particle concentration by statistical analyses of photoacoustic signals in vivo,” J. Biomed. Opt.. 19, (3 ), 037001  (2014). 1083-3668 CrossRef
Tang  M.  et al., “Noninvasive photoacoustic microscopy of methemoglobin in vivo,” J. Biomed. Opt.. 20, (3 ), 036007  (2015). 1083-3668 CrossRef
Chen  Z. J., , Yang  S. H., and Xing  D., “In vivo detection of hemoglobin oxygen saturation and carboxyhemoglobin saturation with multiwavelength photoacoustic microscopy,” Opt. Lett.. 37, (16 ), 3414 –3416 (2012). 0146-9592 CrossRef
Staley  J.  et al., “Growth of melanoma brain tumors monitored by photoacoustic microscopy,” J. Biomed. Opt.. 15, (4 ), 040510  (2010). 1083-3668 CrossRef
Zhou  Y.  et al., “Handheld photoacoustic microscopy to detect melanoma depth in vivo,” Opt. Lett.. 39, (16 ), 4731 –4734 (2014). 0146-9592 CrossRef
Wang  H. W.  et al., “Label-free bond-selective imaging by listening to vibrationally excited molecules,” Phys. Rev. Lett.. 106, (23 ), 238106  (2011).CrossRef
Yakovlev  V. V.  et al., “Stimulated Raman photoacoustic imaging,” Proc. Natl. Acad. Sci. U. S. A.. 107, (47 ), 20335 –20339 (2010).CrossRef
Yakovlev  V. V.  et al., “Monitoring stimulated Raman scattering with photoacoustic detection,” Opt. Lett.. 36, (7 ), 1233 –1235 (2011). 0146-9592 CrossRef
Xu  Z., , Zhu  Q. I., and Wang  L. H. V., “In vivo photoacoustic tomography of mouse cerebral edema induced by cold injury,” J. Biomed. Opt.. 16, (6 ), 066020  (2011). 1083-3668 CrossRef
Xu  Z., , Li  C. H., and Wang  L. V., “Photoacoustic tomography of water in phantoms and tissue,” J. Biomed. Opt.. 15, (3 ), 036019  (2010). 1083-3668 CrossRef
Kottmann  J.  et al., “Glucose sensing in human epidermis using mid-infrared photoacoustic detection,” Biomed. Opt. Express. 3, (4 ), 667 –680 (2012).CrossRef
Pleitez  M. A.  et al., “In vivo noninvasive monitoring of glucose concentration in human epidermis by mid-infrared pulsed photoacoustic spectroscopy,” Anal. Chem.. 85, (2 ), 1013 –1020 (2013).CrossRef
Wang  P.  et al., “High-speed intravascular photoacoustic imaging of lipid-laden atherosclerotic plaque enabled by a 2-kHz barium nitrite Raman laser,” Sci. Rep.. 4,  (2014).CrossRef
Wang  B.  et al., “Detection of lipid in atherosclerotic vessels using ultrasound-guided spectroscopic intravascular photoacoustic imaging,” Opt. Express.. 18, (5 ), 4889 –4897 (2010). 1094-4087 CrossRef
Wang  Y., and Wang  R. K., “Photoacoustic recovery of an absolute optical absorption coefficient with an exact solution of a wave equation,” Phys. Med. Biol.. 53, (21 ), 6167 –6177 (2008).CrossRef
Guo  Z. J.  et al., “Quantitative photoacoustic microscopy of optical absorption coefficients from acoustic spectra in the optical diffusive regime,” J. Biomed. Opt.. 17, (6 ), 066011  (2012). 1083-3668 CrossRef
Xia  J.  et al., “Calibration-free quantification of absolute oxygen saturation based on the dynamics of photoacoustic signals,” Opt. Lett.. 38, (15 ), 2800 –2803 (2013). 0146-9592 CrossRef
Petrov  Y. Y.  et al., “Multiwavelength optoacoustic system for noninvasive monitoring of cerebral venous oxygenation: a pilot clinical test in the internal jugular vein,” Opt. Lett.. 31, (12 ), 1827 –1829 (2006). 0146-9592 CrossRef
Zackrisson  S., , van de Ven  S. M. W. Y., and Gambhir  S. S., “Light in and sound out: emerging translational strategies for photoacoustic imaging,” Cancer Res.. 74, (4 ), 979 –1004 (2014).CrossRef
Luke  G. P., , Yeager  D., and Emelianov  S. Y., “Biomedical applications of photoacoustic imaging with exogenous contrast agents,” Ann. Biomed. Eng.. 40, (2 ), 422 –437 (2012).CrossRef
De La Zerda  A.  et al., “Carbon nanotubes as photoacoustic molecular imaging agents in living mice,” Nat. Nanotechnol.. 3, (9 ), 557 –562 (2008).CrossRef
Kim  C.  et al., “In vivo photoacoustic mapping of lymphatic systems with plasmon-resonant nanostars,” J. Mater. Chem.. 21, (9 ), 2841 –2844 (2011).CrossRef
Kim  C.  et al., “In vivo molecular photoacoustic tomography of melanomas targeted by bioconjugated gold nanocages,” ACS Nano. 4, (8 ), 4559 –4564 (2010). 1936-0851 CrossRef
Pan  D. P. J.  et al., “Photoacoustic sentinel lymph node imaging with self-assembled copper neodecanoate nanoparticles,” ACS Nano. 6, (2 ), 1260 –1267 (2012). 1936-0851 CrossRef
Yao  J. J.  et al., “Evans blue dye-enhanced capillary-resolution photoacoustic microscopy in vivo,” J. Biomed. Opt.. 14, (5 ), 054049  (2009). 1083-3668 CrossRef
Ashkenazi  S., “Photoacoustic lifetime imaging of dissolved oxygen using methylene blue,” J. Biomed. Opt.. 15, (4 ), 040501  (2010). 1083-3668 CrossRef
Wang  X. D.  et al., “Noninvasive photoacoustic angiography of animal brains in vivo with near-infrared light and an optical contrast agent,” Opt. Lett.. 29, (7 ), 730 –732 (2004). 0146-9592 CrossRef
Ku  G., and Wang  L. H. V., “Deeply penetrating photoacoustic tomography in biological tissues enhanced with an optical contrast agent,” Opt. Lett.. 30, (5 ), 507 –509 (2005). 0146-9592 CrossRef
Chatni  M. R.  et al., “Functional photoacoustic microscopy of pH,” J. Biomed. Opt.. 16, (10 ), 100503  (2011). 1083-3668 CrossRef
Song  K. H.  et al., “Noninvasive photoacoustic identification of sentinel lymph nodes containing methylene blue in vivo in a rat model,” J. Biomed. Opt.. 13, (5 ), 054033  (2008). 1083-3668 CrossRef
Li  L.  et al., “Photoacoustic imaging of lacZ gene expression in vivo,” J. Biomed. Opt.. 12, (2 ), 020504  (2007). 1083-3668 CrossRef
Cai  X.  et al., “Multi-scale molecular photoacoustic tomography of gene expression,” PLoS One. 7, (8 ), e43999  (2012). 1932-6203 CrossRef
Ho  C. J. H.  et al., “Multifunctional photosensitizer-based contrast agents for photoacoustic imaging,” Sci. Rep.. 4,  (2014).CrossRef
Attia  A. B.  et al., “Phthalocyanine photosensitizers as contrast agents for in vivo photoacoustic tumor imaging,” Biomed. Opt. Express. 6, (2 ), 591 –598 (2015).CrossRef
Morgounova  E.  et al., “Photoacoustic lifetime contrast between methylene blue monomers and self-quenched dimers as a model for dual-labeled activatable probes,” J. Biomed. Opt.. 18, (5 ), 056004  (2013). 1083-3668 CrossRef
Yao  J.  et al., “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat Methods. (2015).CrossRef
Stiel  A. C.  et al., “High-contrast imaging of reversibly switchable fluorescent proteins via temporally unmixed multispectral optoacoustic tomography,” Opt. Lett.. 40, (3 ), 367 –370 (2015). 0146-9592 CrossRef
Galanzha  E. I.  et al., “Photoacoustic and photothermal cytometry using photoswitchable proteins and nanoparticles with ultrasharp resonances,” J. Biophotonics. 8, (1–2 ), 81 –93 (2015).CrossRef
Zemp  R. J.  et al., “Realtime photoacoustic microscopy of murine cardiovascular dynamics,” Opt. Express.. 16, (22 ), 18551 –18556 (2008). 1094-4087 CrossRef
Taruttis  A.  et al., “Real-time imaging of cardiovascular dynamics and circulating gold nanorods with multispectral optoacoustic tomography,” Opt. Express.. 18, (19 ), 19592 –19602 (2010). 1094-4087 CrossRef
Song  L. A.  et al., “Ultrasound-array-based real-time photoacoustic microscopy of human pulsatile dynamics in vivo,” J. Biomed. Opt.. 15, (2 ), 021303  (2010). 1083-3668 CrossRef
Aizawa  K.  et al., “Photoacoustic monitoring of burn healing process in rats,” J. Biomed. Opt.. 13, (6 ), 064020  (2008). 1083-3668 CrossRef
Sato  S.  et al., “Photoacoustic diagnosis of burns in rats,” J. Trauma. 59, (6 ), 1450 –1455 (2005).CrossRef
Zhang  H. F.  et al., “Imaging acute thermal burns by photoacoustic microscopy,” J. Biomed. Opt.. 11, (5 ), 054033  (2006). 1083-3668 CrossRef
de la Zerda  A.  et al., “Ultrahigh sensitivity carbon nanotube agents for photoacoustic molecular imaging in living mice,” Nano Lett.. 10, (6 ), 2168 –2172 (2010). 1530-6984 CrossRef
Li  M. L.  et al., “In-vivo photoacoustic microscopy of nanoshell extravasation from solid tumor vasculature,” J. Biomed. Opt.. 14, (1 ), 010507  (2009). 1083-3668 CrossRef
Kang  J.  et al., “Photoacoustic imaging of breast microcalcifications: a validation study with 3-dimensional ex vivo data and spectrophotometric measurement,” J. Biophotonics. 8, (1–2 ), 71 –80 (2015).CrossRef
Sim  C.  et al., “Photoacoustic-based nanomedicine for cancer diagnosis and therapy,” J. Control Release. 203, , 118 -125 (2015).CrossRef
Nam  S. Y., and Emelianov  S. Y., “Array-based real-time ultrasound and photoacoustic ocular imaging,” J. Opt. Soc. Korea. 18, (2 ), 151 –155 (2014).CrossRef
Song  W.  et al., “Multimodal photoacoustic ophthalmoscopy in mouse,” J. Biophotonics. 6, (6–7 ), 505 –512 (2013).CrossRef
Liu  T.  et al., “Fundus camera guided photoacoustic ophthalmoscopy,” Curr. Eye Res.. 38, (12 ), 1229 –1234 (2013).CrossRef
Yang  J. M.  et al., “Three-dimensional photoacoustic endoscopic imaging of the rabbit esophagus,” PLoS One. 10, (4 ) (2015). 1932-6203 CrossRef
Hajireza  P., , Shi  W., and Zemp  R., “Label-free in vivo GRIN-lens optical resolution photoacoustic micro-endoscopy,” Laser Phys. Lett.. 10, (5 ), 055603  (2013).CrossRef
Hajireza  P.  et al., “Optical resolution photoacoustic microendoscopy with ultrasound-guided insertion and array system detection,” J. Biomed. Opt.. 18, (9 ), 090502  (2013). 1083-3668 CrossRef
Yang  J. M.  et al., “A 2.5-mm diameter probe for photoacoustic and ultrasonic endoscopy,” Opt. Express. 20, (21 ), 23944 –23953 (2012). 1094-4087 CrossRef
Kneipp  M.  et al., “Functional real-time optoacoustic imaging of middle cerebral artery occlusion in mice,” PLoS One. 9, (4 ) (2014). 1932-6203 CrossRef
Bai  X. S.  et al., “Intravascular optical-resolution photoacoustic tomography with a 1.1 mm diameter catheter,” PLoS One. 9, (3 ) (2014). 1932-6203 CrossRef
Galanzha  E. I.  et al., “In vivo flow cytometry of circulating clots using negative photothermal and photoacoustic contrasts,” Cytom Part A. 79A, (10 ), 814 –824 (2011).CrossRef
Liao  L. D.  et al., “Transcranial imaging of functional cerebral hemodynamic changes in single blood vessels using in vivo photoacoustic microscopy,” J. Cereb. Blood Flow Metab.. 32, (6 ), 938 –951 (2012).CrossRef
Liao  L. D.  et al., “Imaging brain hemodynamic changes during rat forepaw electrical stimulation using functional photoacoustic microscopy,” NeuroImage. 52, (2 ), 562 –570 (2010). 1053-8119 CrossRef
Yao  J. J.  et al., “Noninvasive photoacoustic computed tomography of mouse brain metabolism in vivo,” NeuroImage. 64, , 257 -266 (2013). 1053-8119 CrossRef
Tsytsarev  V.  et al., “Photoacoustic microscopy of microvascular responses to cortical electrical stimulation,” J. Biomed. Opt.. 16, (7 ), 076002  (2011). 1083-3668 CrossRef
Heijblom  M., , Steenbergen  W., and Manohar  S., “Clinical photoacoustic breast imaging,” IEEE Pulse. 6, (3 ), 42 –46 (2015).CrossRef
Gould  T., , Wang  Q. Z., and Pfefer  T. J., “Optical-thermal light-tissue interactions during photoacoustic breast imaging,” Biomed. Opt. Express. 5, (3 ), 832 –847 (2014).CrossRef
Xia  W. F.  et al., “An optimized ultrasound detector for photoacoustic breast tomography,” Med. Phys.. 40, (3 ), 032901  (2013).CrossRef
Lin  L.  et al., “In vivo deep brain imaging of rats using oral-cavity illuminated photoacoustic computed tomography,” J. Biomed. Opt.. 20, (1 ), 016019  (2015). 1083-3668 CrossRef
Nasiriavanaki  M.  et al., “High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain,” Proc. Natl. Acad. Sci. U. S. A.. 111, (1 ), 21 –26 (2014).CrossRef
Zhang  R. Y.  et al., “In vivo optically encoded photoacoustic flowgraphy,” Opt. Lett.. 39, (13 ), 3814 –3817 (2014). 0146-9592 CrossRef
Zhang  C.  et al., “Slow-sound photoacoustic microscopy,” Appl. Phys. Lett.. 102, (16 ) (2013).CrossRef
Zhang  C.  et al., “Reflection-mode submicron-resolution in vivo photoacoustic microscopy,” J. Biomed. Opt.. 17, (2 ), 020501  (2012). 1083-3668 CrossRef
Yao  J. J.  et al., “Double-illumination photoacoustic microscopy,” Opt. Lett.. 37, (4 ), 659 –661 (2012). 0146-9592 CrossRef
Zou  X. T.  et al., “Polydimethylsiloxane thin film characterization using all-optical photoacoustic mechanism,” Appl. Opt.. 52, (25 ), 6239 –6244 (2013).CrossRef
Zhang  E. Z.  et al., “In vivo high-resolution 3D photoacoustic imaging of superficial vascular anatomy,” Phys. Med. Biol.. 54, (4 ), 1035 –1046 (2009).CrossRef
Zhou  Y.  et al., “Calibration-free in vivo transverse blood flowmetry based on cross correlation of slow time profiles from photoacoustic microscopy,” Opt. Lett.. 38, (19 ), 3882 –3885 (2013). 0146-9592 CrossRef
Yao  J. J.  et al., “Absolute photoacoustic thermometry in deep tissue,” Opt. Lett.. 38, (24 ), 5228 –5231 (2013). 0146-9592 CrossRef
Liang  J. Y.  et al., “Cross-correlation-based transverse flow measurements using optical resolution photoacoustic microscopy with a digital micromirror device,” J. Biomed. Opt.. 18, (9 ), 096004  (2013). 1083-3668 CrossRef
Yao  J. J.  et al., “Label-free oxygen-metabolic photoacoustic microscopy in vivo,” J. Biomed. Opt.. 16, (7 ), 076003  (2011). 1083-3668 CrossRef
Ning  B.  et al., “Ultrasound-aided multi-parametric photoacoustic microscopy of the mouse brain,” Sci. Rep.. 5, , 18775  (2015).CrossRef
Li  G.  et al., “Multiview Hilbert transformation for full-view photoacoustic computed tomography using a linear array,” J. Biomed. Opt.. 20, (6 ), 066010  (2015). 1083-3668 CrossRef
Xia  J.  et al., “Retrospective respiration-gated whole-body photoacoustic computed tomography of mice,” J. Biomed. Opt.. 19, (1 ), 016003  (2014). 1083-3668 CrossRef
Hennen  S. N.  et al., “Photoacoustic tomography imaging and estimation of oxygen saturation of hemoglobin in ocular tissue of rabbits,” Exp. Eye Res.. 138, , 153 –158 (2015). 0014-4835 CrossRef
Wang  L. D., , Maslov  K., and Wang  L. H. V., “Single-cell label-free photoacoustic flowoxigraphy in vivo,” Proc. Natl. Acad. Sci. U. S. A.. 110, (15 ), 5759 –5764 (2013).CrossRef
Garcia-Uribe  A.  et al., “Dual-modality photoacoustic and ultrasound imaging system for noninvasive sentinel lymph node detection in patients with breast cancer,” Sci. Rep.. 5, , 15748  (2015).CrossRef
Danielli  A.  et al., “Label-free photoacoustic nanoscopy,” J. Biomed. Opt.. 19, (8 ), 086006  (2014). 1083-3668 CrossRef
Zhou  Y., , Liang  J., and Wang  L. V., “Cuffing-based photoacoustic flowmetry in humans in the optical diffusive regime,” J. Biophotonics. (2015).CrossRef
Zhou  Y.  et al., “In vivo photoacoustic flowmetry at depths of the diffusive regime based on saline injection,” J. Biomed. Opt.. 20, (8 ), 087001  (2015).CrossRef
Yeh  C. H.  et al., “Photoacoustic microscopy of blood pulse wave,” J. Biomed. Opt.. 17, (7 ), 070504  (2012). 1083-3668 CrossRef
Zhu  X. H.  et al., “Simultaneous and noninvasive imaging of cerebral oxygen metabolic rate, blood flow and oxygen extraction fraction in stroke mice,” NeuroImage. 64, , 437 –447 (2013). 1053-8119 CrossRef
Krumholz  A.  et al., “Functional photoacoustic microscopy of diabetic vasculature,” J. Biomed. Opt.. 17, (6 ), 060502  (2012). 1083-3668 CrossRef
Yeager  D.  et al., “Intravascular photoacoustic imaging of exogenously labeled atherosclerotic plaque through luminal blood,” J. Biomed. Opt.. 17, (10 ), 106016  (2012). 1083-3668 CrossRef
Wu  M.  et al., “Impact of device geometry on the imaging characteristics of an intravascular photoacoustic catheter,” Appl. Opt.. 53, (34 ), 8131 –8139 (2014).CrossRef
Wang  B.  et al., “Photoacoustic tomography system for noninvasive real-time three-dimensional imaging of epilepsy,” Biomed. Opt. Express. 3, (6 ), 1427 –1432 (2012).CrossRef

Yong Zhou is currently a graduate student in biomedical engineering at Washington University in St. Louis, under the supervision of Dr. Lihong V. Wang, Gene K. Beare Distinguished Professor. His research focuses on the development of photoacoustic imaging systems.

Junjie Yao received his BE and ME degrees in biomedical engineering from Tsinghua University, Beijing, in 2006 and 2008, respectively, under the tutelage of Prof. Jing Bai. He received his PhD in biomedical engineering at Washington University in St. Louis (WUSTL), in 2013, under the tutelage of Prof. Lihong V. Wang. He is currently a postdoctoral research associate at WUSTL. His research interest is in photoacoustic, optical, and ultrasound imaging technologies in biomedicine.

Lihong V. Wang is the Beare distinguished professor at Washington University, has published 425 journal articles (h-index = 96, citations >36,000) and delivered 420 keynote/plenary/invited talks. His laboratory published the first functional photoacoustic CT and 3-D photoacoustic microscopy. He received the Goodman Award for his Biomedical Optics textbook, NIH Director’s Pioneer Award, OSA Mees Medal, IEEE Technical Achievement and Biomedical Engineering Awards, SPIE Britton Chance Biomedical Optics Award, and an honorary doctorate from Lund University, Sweden.

© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Yong Zhou ; Junjie Yao and Lihong V. Wang
"Tutorial on photoacoustic tomography", J. Biomed. Opt. 21(6), 061007 (Apr 18, 2016). ; http://dx.doi.org/10.1117/1.JBO.21.6.061007


Figures

Graphic Jump Location
Fig. 1
F1 :

Hemispherical array based photoacoustic computed tomography (PACT) system and its representative images. (a) Schematic of a spherical-view photoacoustic system. (b) Representative human breast images from two healthy volunteers (1) and (2). R, right breast and L, left breast. Reproduced with permission from Refs. 45 and 46.

Graphic Jump Location
Fig. 2
F2 :

Cylindrical-view PACT system and its representative images. (a) Schematic of the system, showing the confocal design of both the optics and acoustics. (b)–(d) In vivo images of athymic mice acquired by the system at different anatomical locations: (b) liver, (c) kidneys, and (d) bladder. BL, bladder; BM, backbone muscle; GI, GI tract; KN, kidney; LV, liver; PV, portal vein; SC, spinal cord; SP, spleen; and VC, vena cava. Reproduced with permission from Ref. 48.

Graphic Jump Location
Fig. 3
F3 :

Fabry–Perot interferometer (FBI) based PACT system. (a) Schematic and (b) a representative image of a FBI based PACT system. The red parts in (b) indicate the location of embryos. Reproduced with permission from Ref. 62.

Graphic Jump Location
Fig. 11
F11 :

Schematic of the dual-modality ultrasound and photoacoustic system for SLN detection. Reproduced with permission from Ref. 168.

Graphic Jump Location
Fig. 12
F12 :

In vivo images of a human axilla acquired by US (a), PA (b), and both (c). Reproduced with permission from Ref. 168.

Graphic Jump Location
Fig. 13
F13 :

Circular-view PACT system combined with reversely switchable BphP1 for deep imaging. (a) Contrast-to-noise ratio (CNR) of U87 cells imaged by PACT at 10-mm depth. (b) Whole-body mouse images acquired with BphP1 at different state. The differential image clearly shows that the tumor is at the left kidney. (c) An overlay of the differential image (in color) and the blood-dominated OFF-state image (in grayscale). (d) Normalized PA amplitude along the dashed line in (b), showing the contrast enhancement of the tumor in the differential image. (e) A histology image of the left kidney showing the tumor region. (f) PACT image of a mouse brain with a U87 tumor expressing BphP1. The tumor was 3  mm beneath the scalp. Reproduced with permission from Ref. 121.

Graphic Jump Location
Fig. 14
F14 :

Reversely switchable BphP1-enhanced super-resolution PAM (RS-SPAM). (a) Schematic of the RS-SPAM system. (b) Subdiffraction-resolution principle. In the diffraction-limited excitation volume (green), part of the ON-state BphP1 molecules (black dots) are switched to the OFF state, where the switching rate is proportional to the local optical intensity. The differential signals generate super-resolution images. (c) Conventional (Conv.) PAM and RS-SPAM images of BphP1-expressing bacteria, showing the superior lateral resolution of RS-SPAM. (d) Zoomed-in images of the dashed box areas in (c). (e) Normalized PA amplitude along the dashed line in (d). (f) Depth-encoded RS-SPAM image of BphP1-expressing U87 cells. (g) x-z cross images of two stacked U87 cells, showing the finer axial resolution of RS-SPAM. Reproduced with permission from Ref. 121.

Graphic Jump Location
Fig. 10
F10 :

ffPAM of brain responses to electrical stimulations of the hindlimbs of mice. (a) Fractional PA amplitude changes during left hindlimb stimulation (LHS) and right hindlimb stimulation (RHS). (b) sO2 imaging (marked by the dashed box) before and during stimulations of the left hindlimb. Reproduced with permission from Ref. 70.

Graphic Jump Location
Fig. 9
F9 :

Fast functional PAM (ffPAM) of the mouse brain. (a) Schematic of the ffPAM system. MEMS, microelectromechanical system; OAC, optical-acoustic combiner; PBS, polarizing beam splitter; and UT, ultrasonic transducer. Anatomical (b) and (c) functional images of the mouse brain. sO2, oxygen saturation of hemoglobin; and SV, skull vessel. Reproduced with permission from Ref. 70.

Graphic Jump Location
Fig. 8
F8 :

PAT imaging aided by exogenous contrast agents. PA images acquired before (a) and 52  min after (b) methylene blue injection, showing a dramatic PA signal increase in a sentinel lymph node (SLN). PA images acquir