Photoacoustic imaging is a promising method for visualizing biological tissues with optical absorbers. This article provides an overview of the rapidly developing field of photoacoustic imaging. Photoacoustics, the physical basis of photoacoustic imaging, is analyzed briefly. The merits of photoacoustic technology, compared with optical imaging and ultrasonic imaging, are described. Various imaging techniques are also discussed, including scanning tomography, computed tomography and original detection of photoacoustic imaging. Finally, some biomedical applications of photoacoustic imaging are summarized.

Photoacoustic imaging in biomedicine

Near-infrared fluorescence (NIRF) imaging is an attractive modality for early cancer detection with high sensitivity and multi-detection capability. Due to convenient modification by conjugating with moieties of interests, NIRF probes are ideal candidates for cancer targeted imaging. Additionally, the combinatory application of NIRF imaging and other imaging modalities that can delineate anatomical structures extends fluorometric determination of biomedical information. Moreover, nanoparticles loaded with NIRF dyes and anticancer agents contribute to the synergistic management of cancer, which integrates the advantage of imaging and therapeutic functions to achieve the ultimate goal of simultaneous diagnosis and treatment. Appropriate probe design with targeting moieties can retain the original properties of NIRF and pharmacokinetics. In recent years, great efforts have been made to develop new NIRF probes with better photostability and strong fluorescence emission, leading to the discovery of numerous novel NIRF probes with fine photophysical properties. Some of these probes exhibit tumoricidal activities upon light radiation, which holds great promise in photothermal therapy, photodynamic therapy, and photoimmunotherapy. This review aims to provide a timely and concise update on emerging NIRF dyes and multifunctional agents. Their potential uses as agents for cancer specific imaging, lymph node mapping, and therapeutics are included. Recent advances of NIRF dyes in clinical use are also summarized.

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Near-infrared fluorescent probes in cancer imaging and therapy: an emerging field.

Interventional applications of photoacoustic imaging typically require visualization of point-like targets, such as the small, circular, cross-sectional tips of needles, catheters, or brachytherapy seeds. When these point-like targets are imaged in the presence of highly echogenic structures, the resulting photoacoustic wave creates a reflection artifact that may appear as a true signal. We propose to use deep learning techniques to identify these types of noise artifacts for removal in experimental photoacoustic data. To achieve this goal, a convolutional neural network (CNN) was first trained to locate and classify sources and artifacts in pre-beamformed data simulated with $k$ -Wave. Simulations initially contained one source and one artifact with various medium sound speeds and 2-D target locations. Based on 3,468 test images, we achieved a 100% success rate in classifying both sources and artifacts. After adding noise to assess potential performance in more realistic imaging environments, we achieved at least 98% success rates for channel signal-to-noise ratios (SNRs) of −9dB or greater, with a severe decrease in performance below −21dB channel SNR. We then explored training with multiple sources and two types of acoustic receivers and achieved similar success with detecting point sources. Networks trained with simulated data were then transferred to experimental waterbath and phantom data with 100% and 96.67% source classification accuracy, respectively (particularly when networks were tested at depths that were included during training). The corresponding mean ± one standard deviation of the point source location error was 0.40 ± 0.22 mm and 0.38 ± 0.25 mm for waterbath and phantom experimental data, respectively, which provides some indication of the resolution limits of our new CNN-based imaging system. We finally show that the CNN-based information can be displayed in a novel artifact-free image format, enabling us to effectively remove reflection artifacts from photoacoustic images, which is not possible with traditional geometry-based beamforming.

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Photoacoustic Source Detection and Reflection Artifact Removal Enabled by Deep Learning

Developing safe and effective nanoprobes for targeted imaging and selective therapy of gastric cancer stem cells (GCSCs) has become one of the most promising anticancer strategies. Herein, gold nanostars-based PEGylated multifunctional nanoprobes were prepared with conjugated CD44v6 monoclonal antibodies (CD44v6-GNS) as the targeting ligands. It was observed that the prepared nanoprobes had high affinity towards GCSC spheroid colonies and destroyed them completely with a low power density upon near-infrared (NIR) laser treatment (790 nm, 1.5 W/cm(2), 5 min) in vitro experiment. Orthotopic and subcutaneous xenografted nude mice models of human gastric cancer were established. Subsequently, biodistribution and photothermal therapeutic effects after being intravenously injected with the prepared nanoprobes were assessed. Photoacoustic imaging revealed that CD44v6-GNS nanoprobes could target the gastric cancer vascular system actively at 4 h post-injection, while the probes inhibited tumor growth remarkably upon NIR laser irradiation, and even extended survivability of the gastric cancer-bearing mice. The CD44v6-GNS nanoprobes exhibited great potential for applications of gastric cancer targeted imaging and photothermal therapy in the near future.

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CD44v6 Monoclonal Antibody-Conjugated Gold Nanostars for Targeted Photoacoustic Imaging and Plasmonic Photothermal Therapy of Gastric Cancer Stem-like Cells.

Background
One of the most important areas of Raman medical diagnostics is identification and characterization of cancerous and noncancerous tissues. The methods based on Raman scattering has shown significant potential for probing human breast tissue to provide valuable information for early diagnosis of breast cancer. A vibrational fingerprint from the biological tissue provides information which can be used to identify, characterize and discriminate structures in breast tissue, both in the normal and cancerous environment.

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Raman imaging at biological interfaces: applications in breast cancer diagnosis

We present a method to speed up the acquisition of multispectral photoacoustic data sets by using unipolar orthogonal Golay codes as excitation sequences for the irradiation system. Multispectral photoacoustic coded excitation (MS-PACE) allows acquiring photoacoustic data sets for two irradiation wavelengths simultaneously and separating them afterwards, thus improving the SNR or speeding up the measurement. We derive an analytical estimation of the SNR improvement using MS-PACE compared to time equivalent averaging. We demonstrate the feasibility of the method by successfully imaging a phantom composed of two dyes using unipolar orthogonal Golay codes as excitation sequence for two high power laser diodes operating at two different wavelengths. The experimental results show very good agreement with the theoretical predictions.

Multispectral photoacoustic coded excitation imaging using unipolar orthogonal Golay codes

Photoacoustic (PA) imaging attracts a great deal of attention as an innovative modality for longitudinal, non-invasive, functional and molecular imaging in oncology. Gold nanoparticles (AuNPs) are identified as superior, NIR-absorbing PA contrast agents for biomedical applications. Until now, no systematic comparison of the optical extinction and PA efficiency of water-soluble AuNPs of various geometries and small sizes has been performed.Here spherical AuNPs with core diameters of 1.0, 1.4 and 11.2 nm, nanorods with longitudinal/transversal elongation of 38/9 and 44/12 nm and hollow nanospheres with outer/inner diameters of 33/19, 57/30, 68/45 and 85/56 nm were synthesized. The diode laser set-up with excitations at 650, 808, 850 and 905 nm allowed us to correlate the molar PA signal intensity with the molar extinction of the respective AuNPs. Deviations were explained by differences in heat transfer from the particle to the medium and, for larger particles, by the scattering of light. The molar PA intensity of 1.0 nm AuNPs was comparable to the commonly used organic dye methylene blue, and rapidly increased with the lateral size of AuNPs.

Size-dependent multispectral photoacoustic response of solid and hollow gold nanoparticles

Photoacoustic imaging aims to visualize light absorption properties of biological tissue by receiving a sound wave that is generated inside the observed object as a result of the photoacoustic effect. In clinical applications, the strong light absorption in human skin is a major problem. When high amplitude photoacoustic waves that originate from skin absorption propagate into the tissue, they are reflected back by acoustical scatterers and the reflections contribute to the received signal. The artifacts associated with these reflected waves are referred to as clutter or skin echo and limit the applicability of photoacoustic imaging for medical applications severely. This study seeks to exploit the acoustic tissue information gained by plane wave ultrasound measurements with a linear array in order to correct for reflections in the photoacoustic image. By deriving a theory for clutter waves in k-space and a matching inversion approach, photoacoustic measurements compensated for clutter are shown to be recovered.

Photoacoustic clutter reduction by inversion of a linear scatter model using plane wave ultrasound measurements.

Multispectral photoacoustic laser diode systems have multiple wavelengths available simultaneously. In addition to multispectral imaging, this can be exploited to increase the signal to noise ratio (SNR) by combining these wavelengths to form a combined image, but at the loss of spectral information. Here, a novel signal processing concept is introduced, which optimizes the SNR in the reconstructions of single wavelength data from combined acquisitions while simultaneously permitting to obtain a higher SNR fused image from the same data. The concept is derived for an arbitrary number of wavelengths; it is also applicable at low pulse repetition frequencies. The concept is applied in an experiment using two wavelengths, verifying the theoretical results.

Optimized SNR simultaneous multispectral photoacoustic imaging with laser diodes.

Photoacoustic imaging (PAI) combines high ultrasound resolution with optical contrast. Laser-generated ultrasound
is potentially beneficial for cancer detection, blood oxygenation imaging, and molecular imaging. PAI
is generally performed using solid state Nd:YAG lasers in combination with optical parametric oscillators. An
alternative approach uses laser diodes with higher pulse repetition rates but lower power. Thus, improvement
in signal-to-noise ratio (SNR) is a key step towards applying laser diodes in PAI. To receive equivalent image
quality using laser diodes as with Nd:YAG lasers, the lower power must be compensated by averaging, which can
be enhanced through coded excitation. In principle, perfect binary sequences such as orthogonal Golay codes
can be used for this purpose when acquiring data at multiple wavelengths. On the other hand it was shown for
a single wavelength that sidelobes can remain invisible even if imperfect sequences are used. Moreover, SNR can
be further improved by using an imperfect sequence compared to Golay codes. Here, we show that pseudorandom
sequences are a good choice for multispectral photoacoustic coded excitation (MSPACE). Pseudorandom
sequences based upon maximal length shift register sequences (m-sequences) are introduced and analyzed for the
purpose of use in MSPACE. Their gain in SNR exceeds that of orthogonal Golay codes for finite code lengths.
Artefacts are introduced, but may remain invisible depending on SNR and code length.

Martin F. Beckmann

Papers

Multispectral photoacoustic coded excitation imaging using unipolar orthogonal Golay codes

Size-dependent multispectral photoacoustic response of solid and hollow gold nanoparticles

Photoacoustic clutter reduction by inversion of a linear scatter model using plane wave ultrasound measurements.

Optimized SNR simultaneous multispectral photoacoustic imaging with laser diodes.

Multispectral photoacoustic coded excitation using pseudorandom codes