Clinical Photoacoustic Imaging Research Articles

In vivo multi-scale clinical photoacoustic imaging for analysis of skin vasculature and pigmentation: a comparative review

In vivo multi-scale clinical photoacoustic imaging for analysis of skin vasculature and pigmentation: a comparative review

Motion Compensation for 3D Multispectral Handheld Photoacoustic Imaging.

Three-dimensional (3D) handheld photoacoustic (PA) and ultrasound (US) imaging performed using mechanical scanning are more useful than conventional 2D PA/US imaging for obtaining local volumetric information and reducing operator dependence. In particular, 3D multispectral PA imaging can capture vital functional information, such as hemoglobin concentrations and hemoglobin oxygen saturation (sO2), of epidermal, hemorrhagic, ischemic, and cancerous diseases. However, the accuracy of PA morphology and physiological parameters is hampered by motion artifacts during image acquisition. The aim of this paper is to apply appropriate correction to remove the effect of such motion artifacts. We propose a new motion compensation method that corrects PA images in both axial and lateral directions based on structural US information. 3D PA/US imaging experiments are performed on a tissue-mimicking phantom and a human wrist to verify the effects of the proposed motion compensation mechanism and the consequent spectral unmixing results. The structural motions and sO2 values are confirmed to be successfully corrected by comparing the motion-compensated images with the original images. The proposed method is expected to be useful in various clinical PA imaging applications (e.g., breast cancer, thyroid cancer, and carotid artery disease) that are susceptible to motion contamination during multispectral PA image analysis.

A Deep Learning-Based Model That Reduces Speed of Sound Aberrations for Improved In Vivo Photoacoustic Imaging.

Photoacoustic imaging (PAI) has attracted great attention as a medical imaging method. Typically, photoacoustic (PA) images are reconstructed via beamforming, but many factors still hinder the beamforming techniques in reconstructing optimal images in terms of image resolution, imaging depth, or processing speed. Here, we demonstrate a novel deep learning PAI that uses multiple speed of sound (SoS) inputs. With this novel method, we achieved SoS aberration mitigation, streak artifact removal, and temporal resolution improvement all at once in structural and functional in vivo PA images of healthy human limbs and melanoma patients. The presented method produces high-contrast PA images in vivo with reduced distortion, even in adverse conditions where the medium is heterogeneous and/or the data sampling is sparse. Thus, we believe that this new method can achieve high image quality with fast data acquisition and can contribute to the advance of clinical PAI.

Towards clinical photoacoustic and ultrasound imaging: Probe improvement and real-time graphical user interface.

Photoacoustic imaging is a non-invasive and non-ionizing biomedical technique that has been investigated widely for various clinical applications. By taking the advantages of conventional ultrasound imaging, hand-held operation with a linear array transducer should be favorable for successful clinical translation of photoacoustic imaging. In this paper, we present new key updates contributed to the previously developed real-time clinical photoacoustic and ultrasound imaging system for improving the clinical usability of the system. We developed a seamless image optimization platform, designed a real-time parameter control software with a user-friendly graphical user interface, performed Monte Carlo simulation of the optical fluence in the imaging plane, and optimized the geometry of the imaging probe. The updated system allows optimizing of all imaging parameters while continuously acquiring the photoacoustic and ultrasound images in real-time. The updated system has great potential to be used in a variety of clinical applications such as assessing the malignancy of thyroid cancer, breast cancer, and melanoma. Impact statement Photoacoustic imaging is a promising biomedical imaging modality that can visualize both structural and functional information of biological tissue. Because of its easiness to be integrated with conventional ultrasound imaging systems, numerous studies have been conducted to develop and apply clinical photoacoustic imaging systems. However, most of the systems were not suitable for general-purpose clinical applications due to one of the following reasons: target specific design, immobility, inaccessible operation sequence, and lack of hand-held operation. This study demonstrates a real-time clinical photoacoustic and ultrasound imaging system, which can overcome the limitations of the previous systems for successful clinical translation.

Photoacoustic imaging of living mice enhanced with a low-cost contrast agent.

One of the advantages of photoacoustic imaging (PAI) is that its image contrast may come from exogenous agents. Such advantage leads to the development of a great number of exogenous probes. However, the biosafety of most of these contrast agents has not yet been confirmed, thus hindering their clinical translation. In this work, we report on the utilization of a clinically commonly used nutritional medicine, the Intralipid, as a new contrast agent for photoacoustic imaging. Intralipid consists of soybean oil, lecithin and glycerin and has long been adapted in clinical practices, mainly as a parenteral nutrition. In our study, we found that with Intralipid, the imaging sensitivity of PAI can be effectively enhanced, as demonstrated in in vivo imaging of different organs of nude mice. Further imaging studies on cancerous mice showed not only a twofold PA signal enhancement, but also a strong and long-lasting signal aggregation in the tumor region. Our result revealed the potential of Intralipid to be used in clinical PAI applications, since it is clinically safe, and can be easily prepared at very low cost.

Real-time delay-multiply-and-sum beamforming with coherence factor for in vivo clinical photoacoustic imaging of humans

In the clinical photoacoustic (PA) imaging, ultrasound (US) array transducers are typically used to provide B-mode images in real-time. To form a B-mode image, delay-and-sum (DAS) beamforming algorithm is the most commonly used algorithm because of its ease of implementation. However, this algorithm suffers from low image resolution and low contrast drawbacks. To address this issue, delay-multiply-and-sum (DMAS) beamforming algorithm has been developed to provide enhanced image quality with higher contrast, and narrower main lobe compared but has limitations on the imaging speed for clinical applications. In this paper, we present an enhanced real-time DMAS algorithm with modified coherence factor (CF) for clinical PA imaging of humans in vivo. Our algorithm improves the lateral resolution and signal-to-noise ratio (SNR) of original DMAS beamformer by suppressing the background noise and side lobes using the coherence of received signals. We optimized the computations of the proposed DMAS with CF (DMAS-CF) to achieve real-time frame rate imaging on a graphics processing unit (GPU). To evaluate the proposed algorithm, we implemented DAS and DMAS with/without CF on a clinical US/PA imaging system and quantitatively assessed their processing speed and image quality. The processing time to reconstruct one B-mode image using DAS, DAS with CF (DAS-CF), DMAS, and DMAS-CF algorithms was 7.5, 7.6, 11.1, and 11.3 ms, respectively, all achieving the real-time imaging frame rate. In terms of the image quality, the proposed DMAS-CF algorithm improved the lateral resolution and SNR by 55.4% and 93.6 dB, respectively, compared to the DAS algorithm in the phantom imaging experiments. We believe the proposed DMAS-CF algorithm and its real-time implementation contributes significantly to the improvement of imaging quality of clinical US/PA imaging system.

Multidirectional reception of photoacoustic signals for higher resolution imaging

The imaging of microvasculature of the synovial membrane is important for the early detection of rheumatoid arthritis (RA). Photoacoustic (PA) imaging is an imaging modality that is compatible with the advantages of high spatial resolution in optical imaging and high penetration depth in ultrasound imaging. Linear probes are mainly used in clinical PA imaging. However, it is difficult for linear probes to acquire the PA signal completely from a point sound source in tissue because the area for signal reception is limited. In the present study, high resolution PA imaging as proposed by receiving the PA signals with linear probes placed at multiple angles around the imaging target to generate a compound PA image. The proposed method was compared to the conventional method with a single linear probe by computer simulation and measurement. The proposed method showed significant improvement of resolution and contrast.

Clinical photoacoustic imaging platforms

Photoacoustic imaging (PAI) is a new promising medical imaging technology available for diagnosing and assessing various pathologies. PAI complements existing imaging modalities by providing information not currently available for diagnosing, e.g., oxygenation level of the underlying tissue. Currently, researchers are translating PAI from benchside to bedside to make unique clinical advantages of PAI available for patient care. The requirements for a successful clinical PAI system are; deeper imaging depth, wider field of view, and faster scan time than the laboratory-level PAI systems. Currently, many research groups and companies are developing novel technologies for data acquisition/signal processing systems, detector geometry, and an acoustic sensor. In this review, we summarize state-of-the-art clinical PAI systems with three types of the imaging transducers: linear array transducer, curved linear array transducer, and volumetric array transducer. We will also discuss the limitations of the current PAI systems and describe latest techniques being developed to address these for further enhancing the image quality of PAI for successful clinical translation.

Hand-held Clinical Photoacoustic Imaging System for Real-time Non-invasive Small Animal Imaging.

Translation of photoacoustic imaging into the clinic is a major challenge. Handheld real-time clinical photoacoustic imaging systems are very rare. Here, we report a combined photoacoustic and clinical ultrasound imaging system by integrating an ultrasound probe with light delivery for small animal imaging. We demonstrate this by showing sentinel lymph node imaging in small animals along with minimally invasive real-time needle guidance. A clinical ultrasound platform with access to raw channel data allows the integration of photoacoustic imaging leading to a handheld real-time clinical photoacoustic imaging system. Methylene blue was used for sentinel lymph node imaging at 675 nm wavelength. Additionally, needle guidance with dual modal ultrasound and photoacoustic imaging was shown using the imaging system. Depth imaging of up to 1.5 cm was demonstrated with a 10 Hz laser at a photoacoustic imaging frame rate of 5 frames per second.

Hand-held Clinical Photoacoustic Imaging System for Real-time Non-invasive Small Animal Imaging

Hand-held Clinical Photoacoustic Imaging System for Real-time Non-invasive Small Animal Imaging

Three-dimensional photoacoustic imaging via scanning a one dimensional linear unfocused ultrasound array.

Three-dimensional (3D) photoacoustic imaging can be achieved by a two-dimensional (2D) ultrasound array matrix. However, the 2D matrix consisting of hundreds or thousands of transducer elements makes it not only expensive, but also a big technical challenge for both probe manufacturing and parallel data acquisition. In this study, we performed the photoacoustic imaging by scanning an unfocused linear ultrasound array probe over a planar geometry, resulting in an equivalent 2D matrix probe. The phantom study demonstrated that this method substantially increased imaging quality, which has great potential for animal and clinical photoacoustic imaging.

NH4HCO3 gas-generating liposomal nanoparticle for photoacoustic imaging in breast cancer.

In this study, we have developed a biodegradable nanomaterial for photoacoustic imaging (PAI). Its biodegradation products can be fully eliminated from a living organism. It is a gas-generating nanoparticle of liposome-encapsulating ammonium bicarbonate (NH4HCO3) solution, which is safe, effective, inexpensive, and free of side effects. When lasers irradiate these nanoparticles, NH4HCO3 decomposes to produce CO2, which can absorb much of the light energy under laser irradiation with a specific wavelength, and then expand under heat to generate a thermal acoustic wave. An acoustic detector can detect this wave and show it as a photoacoustic signal on a display screen. The intensity of the photoacoustic signal is enhanced corresponding to an increase in time, concentration, and temperature. During in vivo testing, nanoparticles were injected into tumor-bearing nude mice through the caudal vein, and photoacoustic signals were detected from the tumor, reaching a peak in 4 h, and then gradually disappearing. There was no damage to the skin or subcutaneous tissue from laser radiation. Our developed gas-generating nanomaterial, NH4HCO3 nanomaterial, is feasible, effective, safe, and inexpensive. Therefore, it is a promising material to be used in clinical PAI.

Clinical photoacoustic imaging of cancer.

Photoacoustic imaging is a hybrid technique that shines laser light on tissue and measures optically induced ultrasound signal. There is growing interest in the clinical community over this new technique and its possible clinical applications. One of the most prominent features of photoacoustic imaging is its ability to characterize tissue, leveraging differences in the optical absorption of underlying tissue components such as hemoglobin, lipids, melanin, collagen and water among many others. In this review, the state-of-the-art photoacoustic imaging techniques and some of the key outcomes pertaining to different cancer applications in the clinic are presented.

Synthetic-aperture based photoacoustic re-beamforming (SPARE) approach using beamformed ultrasound data.

Photoacoustic (PA) imaging has been developed for various clinical and pre-clinical applications, and acquiring pre-beamformed channel data is necessary to reconstruct these images. However, accessing these pre-beamformed channel data requires custom hardware to enable parallel beamforming, and is available for a limited number of research ultrasound platforms. To broaden the impact of clinical PA imaging, our goal is to devise a new PA reconstruction approach that uses ultrasound post-beamformed radio frequency (RF) data rather than raw channel data, because this type of data is readily available in both clinical and research ultrasound systems. In our proposed Synthetic-aperture based photoacoustic re-beamforming (SPARE) approach, post-beamformed RF data from a clinical ultrasound scanner are considered as input data for an adaptive synthetic aperture beamforming algorithm. When receive focusing is applied prior to obtaining these data, the focal point is considered as a virtual element, and synthetic aperture beamforming is implemented assuming that the photoacoustic signals are received at the virtual element. The resolution and SNR obtained with the proposed method were compared to that obtained with conventional delay-and-sum beamforming with 99.87% and 91.56% agreement, respectively. In addition, we experimentally demonstrated feasibility with a pulsed laser diode setup. Results indicate that the post-beamformed RF data from any commercially available ultrasound platform can potentially be used to create PA images.

Photoacoustic Imaging for Medical Diagnostics

Photoacoustic imaging has the potential to provide real-time, non-invasive diagnosis of numerous prevalent diseases, due to the technology’s unique ability to visualize molecular changes deep within living tissue with spatial resolution comparable to ultrasound. Photoacoustic imaging is a hybrid imaging technique that combines the contrast capabilities and spectral sensitivities of optical imaging with the resolution and tissue penetration capabilities of ultrasound. During the photoacoustic imaging process, materials absorb light energy, and convert the light to heat via non-radiative relaxation. When materials heat, they expand in size due to their thermoelastic properties, which generates a pressure wave. These pressure waves can propagate through the surrounding environment to be detected at the surface. This effect is familiar to everyone who has experienced a summer thunderstorm—lightning rapidly heats the air, resulting in the air expanding and generating audible thunder. In general, the heating which induces the expansion of the material (e.g., the thermoacoustic effect) could be caused by many forms of energy transfer, but the term “photoacoustic” specifies the conversion of light into heat, resulting in the generation of characteristic sound waves. The photoacoustic effect was first discovered by Alexander Graham Bell in 1880.1 His experiments deduced that an intermittent bright light could heat optically absorbing materials, causing expansion of the material in a way that generated audible vibrational waves. Bell demonstrated that darker fibers produced louder sounds than lighter fibers, a principle which is consistent with the general photoacoustic relationship in use today—the amplitude of the generated photoacoustic signal is proportional to the amount of absorbed light. Bell also showed, by separating white light with a prism, certain color combinations of light and fibers could generate a louder sound. Today, multiwavelength photoacoustic imaging uses this same principle, changing the wavelength of the light and correlating the amplitude of the photoacoustic response to the absorption spectra of the materials being imaged. A modern application of the photoacoustic effect is the generation of medical images of biological chromophores typically present in tissue, which can absorb light energy resulting in the generation of photoacoustic transients. The photoacoustic pressure waves can be received by ultrasound transducers at the external surface of the tissue, making photoacoustic imaging a non-invasive, non-ionizing medical imaging method capable of resolution similar to ultrasound, at significant tissue depth. Photoacoustic medical imaging was first proposed in the mid-1990s,2,3 and initial reports of using the photoacoustic effect to image live animals were published nine years later.4 Today, many in vivo demonstrations of photoacoustic imaging of biomedical applications relevant to medical diagnostics exist, including cancer,5,6 brain vasculature and function,7–9 cardiovascular,10 and tissue engineering scaffolds,11,12 prompting translational advances in clinical photoacoustic imaging.13 While existing medical imaging methods, including ultrasound, are capable of producing remarkable images of what lies beneath our skin, most of these imaging methods provide contrast between anatomical features within tissue—for example, the difference in acoustic impedance between soft tissue and a tumor provide contrast within an ultrasound image. Though the anatomy is critical to understanding the image, in many diseases the anatomy alone cannot be used to indicate a particular diagnosis conclusively. Instead, the physiological and biochemical properties of the system influence the disease progression, and therefore the prognosis of the patient. Functional imaging capabilities are required to provide physiological information, while biochemical information can be provided by molecular imaging. In comparison to ultrasound, photoacoustic imaging provides improved capabilities for functional and molecular imaging. For example, the blood oxygen saturation, an important functional property relevant to many disease processes, can be assessed using photoacoustics.7 Photoacoustic imaging can also provide molecular information through the use of a probe or tracer, which can be used to generate the needed contrast to produce an image.14 Because of the potential to perform real-time, non-invasive in vivo functional and molecular imaging, photoacoustic imaging is increasingly being applied as both a clinical and preclinical method aimed at improving medical diagnostics.