Miniaturized preamplifier integration in ultrasound transducer design for enhanced photoacoustic imaging.

Photoacoustic imaging (PAI) utilizes the photoacoustic effect to record both vascular and functional characteristics of a biological tissue. Photoacoustic signals have typically low amplitude that cannot be read efficiently by data acquisition systems. This necessitates the use of one or more amplifiers. These amplifiers are somewhat bulky (e.g., the ZFL-500LN+, Mini-Circuits, USA, or 351A-3-50-NI, Analog Modules Inc., USA). Here, we describe the fabrication and development process of a transducer with a built-in low-noise preamplifier that is encased within the transducer housing. This new, to the best of our knowledge, design could be advantageous for applications where a compact transducer + preamplifier is required. We demonstrate the performance of this compact detection unit in a laser scanning photoacoustic microscopy system by imaging a rat ear ex vivo and a rat brain vasculature in vivo.

Comprehensive framework of GPU-accelerated image reconstruction for photoacoustic computed tomography.

Significance: Photoacoustic computed tomography (PACT) is a promising non-invasive imaging technique for both life science and clinical implementations. To achieve fast imaging speed, modern PACT systems have equipped arrays that have hundreds to thousands of ultrasound transducer (UST) elements, and the element number continues to increase. However, large number of UST elements with parallel data acquisition could generate a massive data size, making it very challenging to realize fast image reconstruction. Although several research groups have developed GPU-accelerated method for PACT, there lacks an explicit and feasible step-by-step description of GPU-based algorithms for various hardware platforms. Aim: In this study, we propose a comprehensive framework for developing GPU-accelerated PACT image reconstruction (GPU-accelerated photoacoustic computed tomography), to help the research community to grasp this advanced image reconstruction method. Approach: We leverage widely accessible open-source parallel computing tools, including Python multiprocessing-based parallelism, Taichi Lang for Python, CUDA, and possible other backends. We demonstrate that our framework promotes significant performance of PACT reconstruction, enabling faster analysis and real-time applications. Besides, we also described how to realize parallel computing on various hardware configurations, including multicore CPU, single GPU, and multiple GPUs platform. Results: Notably, our framework can achieve an effective rate of ∼ 871 times when reconstructing extremely large-scale three-dimensional PACT images on a dual-GPU platform compared to a 24-core workstation CPU. In this paper, we share example codes via GitHub. Conclusions: Our approach allows for easy adoption and adaptation by the research community, fostering implementations of PACT for both life science and medicine.

3D Multiparametric Photoacoustic Computed Tomography of Primary and Metastatic Tumors in Living Mice.

Photoacoustic computed tomography (PACT), an emerging imaging modality in preclinical cancer research, can provide multiparametric 3D information about structures, physiological functions, and pharmacokinetics. Here, we demonstrate the use of high-definition 3D multiparametric PACT imaging of both primary and metastatic tumors in living mice to noninvasively monitor angiogenesis, carcinogenesis, hypoxia, and pharmacokinetics. The high-definition PACT system with a 1024-element hemispherical ultrasound transducer array provides an isotropic spatial resolution of 380 µm, an effective volumetric field-of-view of 12.8 mm × 12.8 mm × 12.8 mm without scanning, and an acquisition time of <30 s for a whole mouse body. Initially, we monitor the structural progression of the tumor microenvironment (e.g., angiogenesis and vessel tortuosity) after tumor cell inoculation. Then, we analyze the change in oxygen saturation of the tumor during carcinogenesis, verifying induced hypoxia in the tumor's core region. Finally, the whole-body pharmacokinetics are photoacoustically imaged after intravenous injection of micelle-loaded IR780 dye, and the in vivo PACT results are validated in vivo and ex vivo by fluorescence imaging. By employing the premium PACT system and applying multiparametric analyses to subcutaneous primary tumors and metastatic liver tumors, we demonstrate that this PACT system can provide multiparametric analyses for comprehensive cancer research.

Multiwavelength laser diode based portable photoacoustic and ultrasound imaging system for point of care applications.

Vascular diseases are a leading cause of death and disability worldwide. Despite having precursor conditions like peripheral arterial disease (PAD), they are often only diagnosed after the onset of stroke or heart attack. Low-cost, portable, noninvasive, point-of-care (POC), label-free assessment of deep vascular function benefits PAD diagnosis, especially in resource poor settings of the world. Doppler ultrasound-based blood flow measurements can diagnose PAD, albeit with limited sensitivity and specificity. To overcome this, here, we propose the first-of-its-kind dual-modality photoacoustic-and-ultrasound (PAUS) imaging system that integrates a multiwavelength pulsed laser diode (PLD) with a compact ultrasound data acquisition unit. The mesoscopic imaging depth of the portable PLD-PAUS system was validated using tissue phantoms, and its multispectral photoacoustic imaging capabilities were validated using an atherosclerosis-mimicking phantom. Furthermore, we demonstrated high-contrast volumetric in vivo photoacoustic imaging of rodent abdominal vasculature and quantified vessel reactivity due to hypercapnia stimulation. The multiparametric functional and molecular imaging capabilities of the PLD-PAUS system holds promise for POC applications.

Design, implementation, and analysis of a compressed sensing photoacoustic projection imaging system.

Significance: Compressed sensing (CS) uses special measurement designs combined with powerful mathematical algorithms to reduce the amount of data to be collected while maintaining image quality. This is relevant to almost any imaging modality, and in this paper we focus on CS in photoacoustic projection imaging (PAPI) with integrating line detectors (ILDs). Aim: Our previous research involved rather general CS measurements, where each ILD can contribute to any measurement. In the real world, however, the design of CS measurements is subject to practical constraints. In this research, we aim at a CS-PAPI system where each measurement involves only a subset of ILDs, and which can be implemented in a cost-effective manner. Approach: We extend the existing PAPI with a self-developed CS unit. The system provides structured CS matrices for which the existing recovery theory cannot be applied directly. A random search strategy is applied to select the CS measurement matrix within this class for which we obtain exact sparse recovery. Results: We implement a CS PAPI system for a compression factor of 4:3, where specific measurements are made on separate groups of 16 ILDs. We algorithmically design optimal CS measurements that have proven sparse CS capabilities. Numerical experiments are used to support our results. Conclusions: CS with proven sparse recovery capabilities can be integrated into PAPI, and numerical results support this setup. Future work will focus on applying it to experimental data and utilizing data-driven approaches to enhance the compression factor and generalize the signal class.

Artifact reduction in photoacoustic images by generating virtual dense array sensor from hemispheric sparse array sensor using deep learning.

PURPOSE: Vascular distribution is important information for diagnosing diseases and supporting surgery. Photoacoustic imaging is a technology that can image blood vessels noninvasively and with high resolution. In photoacoustic imaging, a hemispherical array sensor is especially suitable for measuring blood vessels running in various directions. However, as a hemispherical array sensor, a sparse array sensor is often used due to technical and cost issues, which causes artifacts in photoacoustic images. Therefore, in this study, we reduce these artifacts using deep learning technology to generate signals of virtual dense array sensors. METHODS: Generating 2D virtual array sensor signals using a 3D convolutional neural network (CNN) requires huge computational costs and is impractical. Therefore, we installed virtual sensors between the real sensors along the spiral pattern in three different directions and used a 2D CNN to generate signals of the virtual sensors in each direction. Then we reconstructed a photoacoustic image using the signals from both the real sensors and the virtual sensors. RESULTS: We evaluated the proposed method using simulation data and human palm measurement data. We found that these artifacts were significantly reduced in the images reconstructed using the proposed method, while the artifacts were strong in the images obtained only from the real sensor signals. CONCLUSION: Using the proposed method, we were able to significantly reduce artifacts, and as a result, it became possible to recognize deep blood vessels. In addition, the processing time of the proposed method was sufficiently applicable to clinical measurement.

Miniaturized Stacked Transducer for Intravascular Sonothrombolysis With Internal-Illumination Photoacoustic Imaging Guidance and Clot Characterization.

Thromboembolism in blood vessels can lead to stroke or heart attack and even sudden death unless brought under control. Sonothrombolysis enhanced by ultrasound contrast agents has shown promising outcome on effective treatment of thromboembolism. Intravascular sonothrombolysis was also reported recently with a potential for effective and safe treatment of deep thrombosis. Despite the promising treatment results, the treatment efficiency for clinical application may not be optimized due to the lack of imaging guidance and clot characterization during the thrombolysis procedure. In this paper, a miniaturized transducer was designed to have an 8-layer PZT-5A stacked with an aperture size of 1.4 × 1.4 mm2 and assembled in a customized two-lumen 10-Fr catheter for intravascular sonothrombolysis. The treatment process was monitored with internal-illumination photoacoustic tomography (II-PAT), a hybrid imaging modality that combines the rich contrast of optical absorption and the deep penetration of ultrasound detection. With intravascular light delivery using a thin optical fiber integrated with the intravascular catheter, II-PAT overcomes the penetration depth limited by strong optical attenuation of tissue. In-vitro PAT-guided sonothrombolysis experiments were carried out with synthetic blood clots embedded in tissue phantom. Clot position, shape, stiffness, and oxygenation level can be estimated by II-PAT at clinically relevant depth of ten centimeters. Our findings have demonstrated the feasibility of the proposed PAT-guided intravascular sonothrombolysis with real-time feedback during the treatment process.

Improvement of spatial resolution in photoacoustic microscopy using transmissive adaptive optics with a low-frequency ultrasound transducer.

Maintaining a high spatial resolution in photoacoustic microscopy (PAM) of deep tissues is difficult due to large aberration in an objective lens with high numerical aperture and photoacoustic wave attenuation. To address the issue, we integrate transmission-type adaptive optics (AO) in high-resolution PAM with a low-frequency ultrasound transducer (UT), which increases the photoacoustic wave detection efficiency. AO improves lateral resolution and depth discrimination in PAM, even for low-frequency ultrasound waves by focusing a beam spot in deep tissues. Using the proposed PAM, we increased the lateral resolution and depth discrimination for blood vessels in mouse ears.

Development of a Compact Photoacoustic Tomography Imaging System with Dual Single-Element Transducers for Image Enhancement.

OBJECTIVE: This paper proposes a new photoacoustic computed tomography (PACT) imaging system employing dual ultrasonic transducers with different frequencies. When imaging complex biological tissues, photoacoustic (PA) signals with multiple frequencies are produced simultaneously; however, due to the limited bandwidth of a single-frequency transducer, the received PA signals with specific frequencies may be missing, leading to a low imaging quality. METHODS: In contrast to our previous work, the proposed system has a compact volume as well as specific selection of the detection center frequency of the transducer, which can provide a comprehensive range for the detection of PA signals. In this study, a series of numerical simulation and phantom experiments were performed to validate the efficacy of the developed PACT system. RESULTS: The images generated by our system combined the advantages of both high resolution and ideal brightness/contrast. CONCLUSION: The interchangeability of transducers with different frequencies provides potential for clinical deployment under the circumstance where a single frequency transducer cannot perform well.

Chromatic-aberration-free multispectral optical-resolution photoacoustic microscopy using reflective optics and a supercontinuum light source.

A supercontinuum (SC) light source enables multispectral photoacoustic imaging at excitation wavelengths in the visible-to-near-infrared range. However, for such a broad optical wavelength range, chromatic aberration is non-negligible. We developed a multispectral optical-resolution photoacoustic microscopy (MS-OR-PAM) setup with a nanosecond pulsed SC light source and a reflective objective lens to avoid chromatic aberration. Chromatic aberrations generated by reflective and conventional objective lenses were compared, and the images acquired using the reflective objective were not affected by chromatic aberration. Hence, MS-OR-PAM with the reflective objective was used to distinguish red blood cells from melanoma cells via spectral subtraction processing.

A Comparative Study of Four Total Variational Regularization Reconstruction Algorithms for Sparse-View Photoacoustic Imaging.

Photoacoustic imaging (PAI) is a new nonionizing, noninvasive biomedical imaging technology that has been employed to reconstruct the light absorption characteristics of biological tissues. The latest developments in compressed sensing (CS) technology have shown that it is possible to accurately reconstruct PAI images from sparse data, which can greatly reduce scanning time. This study focuses on the comparative analysis of different CS-based total variation regularization reconstruction algorithms, aimed at finding a method suitable for PAI image reconstruction. The performance of four total variation regularization algorithms is evaluated through the reconstruction experiment of sparse numerical simulation signal and agar phantom signal data. The evaluation parameters include the signal-to-noise ratio and normalized mean absolute error of the PAI image and the CPU time. The comparative results demonstrate that the TVAL3 algorithm can well balance the quality and efficiency of the reconstruction. The results of this study can provide some useful guidance for the development of the PAI sparse reconstruction algorithm.

Hyperspectral absorption microscopy using photoacoustic remote sensing.

An improved method of remote optical absorption spectroscopy and hyperspectral optical absorption imaging is described which takes advantage of the photoacoustic remote sensing detection architecture. A wide collection of photoacoustic excitation wavelengths ranging from 210 nm to 1550 nm was provided by a nanosecond tunable source allowing access to various salient endogenous chromophores such as DNA, hemeproteins, and lipids. Sensitivity of the device was demonstrated by characterizing the infrared absorption spectrum of water. Meanwhile, the efficacy of the technique was explored by recovering cell nuclei and oxygen saturation from a live chicken embryo model and by recovering adipocytes from freshly resected murine adipose tissue. This represents a continued investigation into the characteristics of the hyperspectral photoacoustic remote sensing technique which may represent an effective means of non-destructive endogenous contrast characterization and visualization.

Activity-based photoacoustic probe for biopsy-free assessment of copper in murine models of Wilson's disease and liver metastasis.

The development of high-performance photoacoustic (PA) probes that can monitor disease biomarkers in deep tissue has the potential to replace invasive medical procedures such as a biopsy. However, such probes must be optimized for in vivo performance and exhibit an exceptional safety profile. In this study, we have developed PACu-1, a PA probe designed for biopsy-free assessment (BFA) of hepatic Cu via photoacoustic imaging. PACu-1 features a Cu(I)-responsive trigger appended to an aza-BODIPY dye platform that has been optimized for ratiometric sensing. Owing to its excellent performance, we were able to detect basal levels of Cu in healthy wild-type mice as well as elevated Cu in a Wilson's disease model and in a liver metastasis model. To showcase the potential impact of PACu-1 for BFA, we conducted two blind studies in which we were able to successfully identify Wilson's disease animals from healthy control mice in each instance.

QEPAS sensor in a butterfly package and its application.

Molecular gases are highly relevant in healthcare, production control, safety, and environmental monitoring. They often appear in small concentrations. The measurement of trace gases has increasingly become a key technique in those domains. Quartz-enhanced photoacoustic spectroscopy (QEPAS) is a suitable method that can provide the required low detection limits in such applications at comparatively low cost and small size. For mobile implementation, the size of an entire sensor unit matters. In this paper, we present a QEPAS sensor that fits into a standard butterfly package, its characterization, and its application on CH4 and CO2.

Multiparametric Photoacoustic Analysis of Human Thyroid Cancers In Vivo.

Thyroid cancer is one of the most common cancers, with a global increase in incidence rate for both genders. Ultrasound-guided fine-needle aspiration is the current gold standard to diagnose thyroid cancers, but the results are inaccurate, leading to repeated biopsies and unnecessary surgeries. To reduce the number of unnecessary biopsies, we explored the use of multiparametric photoacoustic (PA) analysis in combination with the American Thyroid Association (ATA) Guideline (ATAP). In this study, we performed in vivo multispectral PA imaging on thyroid nodules from 52 patients, comprising 23 papillary thyroid cancer (PTC) and 29 benign cases. From the multispectral PA data, we calculated hemoglobin oxygen saturation level in the nodule area, then classified the PTC and benign nodules with multiparametric analysis. Statistical analyses showed that this multiparametric analysis of multispectral PA responses could classify PTC nodules. Combining the photoacoustically indicated probability of PTC and the ATAP led to a new scoring method that achieved a sensitivity of 83% and a specificity of 93%. This study is the first multiparametric analysis of multispectral PA data of thyroid nodules with statistical significance. As a proof of concept, the results show that the proposed new ATAP scoring can help physicians examine thyroid nodules for fine-needle aspiration biopsy, thus reducing unnecessary biopsies. SIGNIFICANCE: This report highlights a novel photoacoustic scoring method for risk stratification of thyroid nodules, where malignancy of the nodules can be diagnosed with 83% sensitivity and 93% specificity.

Isotopic gas analysis by means of mid-infrared photoacoustic spectroscopy targeting human exhaled air.

There is a great need for cost-efficient non-invasive medical diagnostic tools for analyzing humanly exhaled air. Compared to present day methods, photoacoustic spectroscopy (PAS) can provide a compact and portable (bedside), sensitive and inexpensive solution. We demonstrate a novel portable photoacoustic spectroscopic platform for isotopic measurements of methane (CH4). We identify and discriminate the 12CH4- and 13CH4 isotopologues and determine their mixing ratio. An Allan deviation analysis shows that the noise equivalent concentration for CH4 is 200 ppt (pmol/mol) at 100 s of integration time, corresponding to a normalized noise equivalent absorption coefficient of 5.1×10-9Wcm-1Hz-1/2, potentially making the PAS sensor a truly disruptive instrument for bedside monitoring using isotope tracers by providing real-time metabolism data to clinical personnel.

Towards Transabdominal Functional Photoacoustic Imaging of the Placenta: Improvement in Imaging Depth Through Optimization of Light Delivery.

Functional photoacoustic imaging of the placenta could provide an innovative tool to diagnose preeclampsia, monitor fetal growth restriction, and determine the developmental impacts of gestational diabetes. However, transabdominal photoacoustic imaging is limited in imaging depth due to the tissue's scattering and absorption of light. The aim of this paper was to investigate the impact of geometry and wavelength on transabdominal light delivery. Our methods included the development of a multilayer model of the abdominal tissue and simulation of the light propagation using Monte Carlo methods. A bifurcated light source with varying incident angle of light, distance between light beams, and beam area was simulated to analyze the effect of light delivery geometry on the fluence distribution at depth. The impact of wavelength and the effects of variable thicknesses of adipose tissue and muscle were also studied. Our results showed that the beam area plays a major role in improving the delivery of light to deep tissue, in comparison to light incidence angle or distance between the bifurcated fibers. Longer wavelengths, with incident fluence at the maximum permissible exposure limit, also increases fluence within deeper tissue. We validated our simulations using a commercially available light delivery system and ex vivo human placental tissue. Additionally, we compared our optimized light delivery to a commercially available light delivery system, and conclude that our optimized geometry could improve imaging depth more than 1.6×, bringing the imaging depth to within the needed range for transabdominal imaging of the human placenta.

Improving reliability and reducing costs of cardiotoxicity assessments using laser-induced cell poration on microelectrode arrays.

Drug-induced cardiotoxicity is a major barrier to drug development and a main cause of withdrawal of marketed drugs. Drugs can strongly alter the spontaneous functioning of the heart by interacting with the cardiac membrane ion channels. If these effects only surface during in vivo preclinical tests, clinical trials or worse after commercialization, the societal and economic burden will be significant and seriously hinder the efficient drug development process. Hence, cardiac safety pharmacology requires in vitro electrophysiological screening assays of all drug candidates to predict cardiotoxic effects before clinical trials. In the past 10 years, microelectrode array (MEA) technology began to be considered a valuable approach in pharmaceutical applications. However, an effective tool for high-throughput intracellular measurements, compatible with pharmaceutical standards, is not yet available. Here, we propose laser-induced optoacoustic poration combined with CMOS-MEA technology as a reliable and effective platform to detect cardiotoxicity. This approach enables the acquisition of high-quality action potential recordings from large numbers of cardiomyocytes within the same culture well, providing reliable data using single-well MEA devices and single cardiac syncytia per each drug. Thus, this technology could be applied in drug safety screening platforms reducing times and costs of cardiotoxicity assessments, while simultaneously improving the data reliability.

Capture and Isolation of Circulating Melanoma Cells Using Photoacoustic Flowmetry.

Early detection of cancer has been a goal of cancer research in general and melanoma research in particular (Birnbaum et al., Lancet Glob Health 6:e885-e893, 2018; Alendar et al., Bosnian J Basic Med Sci 9:77-80, 2009). Early detection of metastasis has been targeted as pivotal to increasing survival rates (Menezes et al., Adv Cancer Res 132:1-44, 2016). Melanoma, though curable in its early stages, has a dramatic decrease in survival rates once metastasis has occurred (Sharma et al., Biotechnol Adv 36:1063-1078, 2018). The transition to metastasis is not well understood and is an area of increasing interest. Metastasis is always premeditated by the shedding of circulating tumor cells (CTCs) from the primary tumor. The ability to isolate rare CTCs from the bloodstream has led to a host of new targets and therapies for cancer (Micalizzi et al., Genes Dev 31:1827-1840, 2017). Detection of CTCs also allows for disease progression to be tracked in real time while eliminating the need to wait for additional tumors to grow. Using a photoacoustic flowmeter, in which we induce ultrasonic responses from circulating melanoma cells (CMCs), we identify and quantify these cells in order to track disease progression. Additionally, these CMCs are captured and isolated allowing for future analysis such as RNA-Seq or microarray analysis.

High-speed photoacoustic-guided wavefront shaping for focusing light in scattering media.

Wavefront shaping is becoming increasingly attractive as it promises to enable various biomedical applications by breaking through the optical diffusion limit that prevents light focusing at depths larger than ∼1mm in biological tissue. However, despite recent advancements in wavefront shaping technology, such as those exploiting non-invasive photoacoustic-guidance, in vivo demonstrations remain challenging mainly due to rapid tissue speckle decorrelation. In this work, we report a high-speed photoacoustic-guided wavefront shaping method with a relatively simple experimental setup, based on the characterization of a scattering medium with a real-valued intensity transmission matrix. We demonstrated light focusing through an optical diffuser by optimizing 4096 binary amplitude modulation modes of a digital micromirror device within ∼300ms, leading to a system runtime of 75 µs per input mode, which is 3 orders of magnitude smaller than the smallest runtime reported in literature so far using photoacoustic-guided wavefront shaping. Thus, our method is a solid step forward toward in vivo applications of wavefront shaping.