Photoacoustic Imaging Applications Research Articles

High-sensitivity fiber-tip acoustic sensor with ultrathin gold diaphragm

Miniature acoustic sensors with high sensitivity are highly desired for applications in medical photoacoustic imaging, acoustic communications and industrial nondestructive testing. However, conventional acoustic sensors based on piezoelectric, piezoresistive and capacitive detectors usually require a large element size on a millimeter to centimeter scale to achieve a high sensitivity, greatly limiting their spatial resolution and the application in space-confined sensing scenarios. Herein, by using single-crystal two-dimensional gold flakes (2DGFs) as the sensing diaphragm of an extrinsic Fabry-Perot interferometer on a fiber tip, we demonstrate a miniature optical acoustic sensor with high sensitivity. Benefiting from the ultrathin thickness (∼8 nm) and high reflectivity of the 2DGF, the fiber-tip acoustic sensor gives an acoustic pressure sensitivity of ∼300 mV/Pa in the frequency range from 100 Hz to 20 kHz. The noise-equivalent pressure of the fiber-tip acoustic sensor at the frequency of 13 kHz is as low as 62.8 µPa/Hz1/2, which is one or two orders of magnitude lower than that of reported optical acoustic sensors with the same size.

Biosynthesis of NIR-II Ag2Se Quantum Dots with Bacterial Catalase for Photoacoustic Imaging and Alleviating-Hypoxia Photothermal Therapy.

Developing the second near-infrared (NIR-II) photoacoustic (PA) agent is of great interest in bioimaging. Ag2Se quantum dots (QDs) are one kind of potential probe for applications in NIR-II photoacoustic imaging (PAI). However, the surfaces with excess anions of Ag2Se QDs, which increase the probability of nonradiative transitions of excitons benefiting PA imaging, are not conducive to binding electron donor ligands for potential biolabeling and imaging. In this study, Staphylococcus aureus (S. aureus) cells are driven for the biosynthesis of Ag2Se QDs with catalase (CAT). Biosynthesized Ag2Se (bio-Ag2Se-CAT) QDs are produced in Se-enriched environment of S. aureus and have a high Se-rich surface. The photothermal conversion efficiency of bio-Ag2Se-CAT QDs at 808 and 1064nm is calculated as 75.3% and 51.7%, respectively. Additionally, the PA signal responsiveness of bio-Ag2Se-CAT QDs is ≈10 times that of the commercial PA contrast agent indocyanine green. In particular, the bacterial CAT is naturally attached to bio-Ag2Se-CAT QDs surface, which can effectively relieve tumor hypoxia. The bio-Ag2Se-CAT QDs can relieve heat-initiated oxidative stress while undergoing effective photothermal therapy (PTT). Such biosynthesis method of NIR-II bio-Ag2Se-CAT QDs opens a new avenue for developing multifunctional nanomaterials, showing great promise for PAI, hypoxia alleviation, and PTT.

Effect of PVP Molecular Weights on the Synthesis of Ultrasmall Cus Nanoflakes: Synthesis, Properties, and Potential Application for Phototheranostics.

Copper sulfide nanoparticles (CuS) hold tremendous potential for applications in photothermal therapy (PTT) and photoacoustic imaging (PAI). However, the conventional chemical coprecipitation method often leads to particle agglomeration issues. To overcome this challenge, we utilized polyvinylpyrrolidone (PVP) as a stabilizing agent, resulting in the synthesis of small PVP-CuS nanoparticles named PC10, PCK30, and PC40. Our study aimed to investigate how different molecular weights of PVP influence the nanoparticles' crystalline characteristics and essential properties, especially their photoacoustic and photothermal responses. While prior research on PVP-assisted CuS nanoparticles has been conducted, our study delves deeper into this area, providing insights into optical properties. Remarkably, all synthesized nanoparticles exhibited a crystalline structure, were smaller than 10 nm, and featured an absorbance peak at 1020 nm, indicating their robust photoacoustic and photothermal capabilities. Among these nanoparticles, PC10 emerged as the standout performer, displaying superior photoacoustic properties. Our photothermal experiments demonstrated significant temperature increases in all cases, with PC10 achieving an impressive efficiency of 51%. Moreover, cytotoxicity assays revealed the nanoparticles' compatibility with cells, coupled with an enhanced incidence of apoptosis compared to necrosis. These findings underscore the promising potential of PVP-stabilized CuS nanoparticles for advanced cancer theranostics.

Optical ultrasound sensors for photoacoustic imaging: a review.

Photoacoustic (PA) imaging is an emerging biomedical imaging modality that can map optical absorption contrast in biological tissues by detecting ultrasound signal. Piezoelectric transducers are commonly used in PA imaging to detect the ultrasound signals. However, piezoelectric transducers suffer from low sensitivity when the dimensions are reduced and are easily influenced by electromagnetic interference. To avoid these limitations, various optical ultrasound sensors have been developed and shown their great potential in PA imaging. Our study aims to summarize recent progress in optical ultrasound sensor technologies and their applications in PA imaging. The commonly used optical ultrasound sensing techniques and their applications in PA systems are reviewed. The technical advances of different optical ultrasound sensors are summarized. Optical ultrasound sensors can provide wide bandwidth and improved sensitivity with miniatured size, which enables their applications in PA imaging. The optical ultrasound sensors are promising transducers in PA imaging to provide higher-resolution images and can be used in new applications with their unique advantages.

Development and validation of nomograms using photoacoustic imaging and 2D ultrasound to predict breast nodule benignity and malignancy.

The application of photoacoustic imaging (PAI), utilizing laser-induced ultrasound, shows potential in assessing blood oxygenation in breast nodules. However, its effectiveness in distinguishing between malignant and benign nodules remains insufficiently explored. This study aims to develop nomogram models for predicting the benign or malignant nature of breast nodules using PAI. A prospective cohort study enrolled 369 breast nodules, subjecting them to PAI and ultrasound examination. The training and testing cohorts were randomly divided into two cohorts in a ratio of 3:1. Based on the source of the variables, three models were developed, Model 1: photoacoustic-BIRADS+BMI + blood oxygenation, Model 2: BIRADS+Shape+Intranodal blood (Doppler) + BMI, Model 3: photoacoustic-BIRADS+BIRADS+ Shape+Intranodal blood (Doppler) + BMI + blood oxygenation. Risk factors were identified through logistic regression, resulting in the creation of three predictive models. These models were evaluated using calibration curves, subject receiver operating characteristic (ROC), and decision curve analysis. The area under the ROC curve for the training cohort was 0.91 (95% confidence interval, 95% CI: 0.88-0.95), 0.92 (95% CI: 0.89-0.95), and 0.97 (95% CI: 0.96-0.99) for Models 1-3, and the ROC curve for the testing cohort was 0.95 (95% CI: 0.91-0.98), 0.89 (95% CI: 0.83-0.96), and 0.97 (95% CI: 0.95-0.99) for Models 1-3. The calibration curves demonstrate that the model's predictions agree with the actual values. Decision curve analysis suggests a good clinical application.

Miniaturized Optical Ultrasound Sensors and their Applications in Photoacoustic Imaging (Invited)

Miniaturized Optical Ultrasound Sensors and their Applications in Photoacoustic Imaging (Invited)

Machine learning assisted designing of Indacenodithiophene (IDT)-based polymers for future application of photoacoustic imaging

Non-invasive imaging tools are essential for diagnosis of complex disease. Photoacoustic (PA) imaging is a multiscale noninvasive imaging modality with high resolution and sensitivity for deep-seated pathologies. However, microenvironment of some pathologies produce PA signals compromising the optical resolution of PA imaging. This demands the construction of PA imaging agents to avoid the low signal to noise ratio with improved resolution and sensitivity. In this study, we use machine learning to design the IDT-based polymers with their absorption coefficient in NIR-I region. We used the database of polymer structures and properties to identify promising candidates for PAI. The models were then used to predict the properties of new IDT-based polymers with optimized absorption, biocompatibility and acoustic performance. Several promising candidates were identified and their in silico synthesis potential and PA imaging performance was predicted. The results demonstrates the potential of machine learning-guided polymers design for PA imaging agents and suggest that IDT-based polymers could be a valuable addition to the toolkit of PA imaging contrast agents.

Photoacoustic Imaging as a Novel Non-invasive Biomarker to Assess Intestinal Tissue Oxygenation and Motility in Neonatal Rats

BackgroundWithin the premature infant intestine, oxygenation and motility play key physiological roles in healthy development and disease such as necrotizing enterocolitis. To date, there are limited techniques to reliably assess these physiological functions that are also clinically feasible for critically ill infants. To address this clinical need, we hypothesized that photoacoustic imaging (PAI) can provide non-invasive assessment of intestinal tissue oxygenation and motility to characterize intestinal physiology and health. MethodsUltrasound and photoacoustic images were acquired in 2-day and 4-day old neonatal rats. For PAI assessment of intestinal tissue oxygenation, an inspired gas challenge was performed using hypoxic, normoxic, and hyperoxic inspired oxygen (FiO2). For intestinal motility, oral administration of ICG contrast agent was used to compare control animals to an experimental model of loperamide-induced intestinal motility inhibition. ResultsPAI demonstrated progressive increases in oxygen saturation (sO2) as FiO2 increased, while the pattern of oxygen localization remained relatively consistent in both 2-day and 4-day old neonatal rats. Analysis of intraluminal ICG contrast enhanced PAI images yielded a map of the motility index in control and loperamide treated rats. From PAI analysis, loperamide significantly inhibited intestinal motility, with a 32.6% decrease in intestinal motility index scores in 4-day old rats. ConclusionThese data establish the feasibility and application of PAI to non-invasively and quantitatively measure intestinal tissue oxygenation and motility. This proof-of-concept study is an important first step in developing and optimizing photoacoustic imaging to provide valuable insight into intestinal health and disease to improve the care of premature infants.

Zero-Dimensional Carbon Nanomaterials for Fluorescent Sensing and Imaging.

Advances in nanotechnology and nanomaterials have attracted considerable interest and play key roles in scientific innovations in diverse fields. In particular, increased attention has been focused on carbon-based nanomaterials exhibiting diverse extended structures and unique properties. Among these materials, zero-dimensional structures, including fullerenes, carbon nano-onions, carbon nanodiamonds, and carbon dots, possess excellent bioaffinities and superior fluorescence properties that make these structures suitable for application to environmental and biological sensing, imaging, and therapeutics. This review provides a systematic overview of the classification and structural properties, design principles and preparation methods, and optical properties and sensing applications of zero-dimensional carbon nanomaterials. Recent interesting breakthroughs in the sensitive and selective sensing and imaging of heavy metal pollutants, hazardous substances, and bioactive molecules as well as applications in information encryption, super-resolution and photoacoustic imaging, and phototherapy and nanomedicine delivery are the main focus of this review. Finally, future challenges and prospects of these materials are highlighted and envisaged. This review presents a comprehensive basis and directions for designing, developing, and applying fascinating fluorescent sensors fabricated based on zero-dimensional carbon nanomaterials for specific requirements in numerous research fields.

3D printed Fabry-Perot acoustic probe with a glass horn tube

Sensing an incoming acoustic signal is typically associated with absorbing the energy, perturbing the measurement and therefore causing a deformation of the sensing elements, which is mainly related to the acoustic wave pressure. Here, we demonstrated a fiber-tip based Fabry-Perot (FP) acoustic probe sensor, which was directly printed on an optical fiber tip by a two-photon 3D printing technique and assembled by a glass horn structure, which can improve the sensitivity. It showed that the sensor has a −3 dB bandwidth of 366.05 kHz at the first resonant frequency of 467.84 kHz. A low noise-limited minimum detectable pressure level of 4.71 mPa/Hz1/2@100 kHz is obtained. Due to the acoustic wave focusing property of the horn structure, the detected signal intensity can be amplified by 4 times as the sensor located at the bottom position. It demonstrates that 3D printed micro acoustic devices could be used for weak acoustic wave detection in the applications of partial discharge, photoacoustic imaging and non-destructive detection.

Thirty years of research on photoacoustic imaging in the field of cancer: A scientometric analysis of hotspots, bursts, and research trends.

As a novel imaging modality based on photoacoustic effects, photoacoustic imaging (PAI) has shown great potential in biomedical applications, especially in the field of cancer. The purpose of our research was to identify collaborations between different institutions, authors, and countries, and to explore the hotspots and prospects of PAI research in the field of cancer. We downloaded publications on PAI research from the Science Citation Index-Expanded (SCI-E) of the Web of Science Core Collection database. Bibliometric analysis was performed using VOSviewer and CiteSpace software. A total of 2561 papers related to PAI research in the field of cancer were identified. A total of 10,105 authors participated in the PAI study, of which the majority (69.33%) authors participated in only 1 article. China (1638, 63.96%) was the country with the most articles in this field, and the Chinese Academy of Sciences (329, 12.85%) was the most productive institution. ACS Applied Materials & Interfaces (146, 5.70%) was the most productive journal and ACS Nano (7262 co-citations) was the most co-cited journal. Current hot topics of PAI research in the cancer field were the construction and development of multifunctional photoacoustic nanoprobes to achieve the integration of tumor detection and treatment. The application of photoacoustic imaging in the field of cancer is in the vigorous development stage and has a bright prospect. There was a wealth of cooperation between authors, countries, and institutions. Our findings can provide information about the future direction of funding agencies and research groups.

Efficient Photoacoustic Image Synthesis with Deep Learning.

Photoacoustic imaging potentially allows for the real-time visualization of functional human tissue parameters such as oxygenation but is subject to a challenging underlying quantification problem. While in silico studies have revealed the great potential of deep learning (DL) methodology in solving this problem, the inherent lack of an efficient gold standard method for model training and validation remains a grand challenge. This work investigates whether DL can be leveraged to accurately and efficiently simulate photon propagation in biological tissue, enabling photoacoustic image synthesis. Our approach is based on estimating the initial pressure distribution of the photoacoustic waves from the underlying optical properties using a back-propagatable neural network trained on synthetic data. In proof-of-concept studies, we validated the performance of two complementary neural network architectures, namely a conventional U-Net-like model and a Fourier Neural Operator (FNO) network. Our in silico validation on multispectral human forearm images shows that DL methods can speed up image generation by a factor of 100 when compared to Monte Carlo simulations with 5×108 photons. While the FNO is slightly more accurate than the U-Net, when compared to Monte Carlo simulations performed with a reduced number of photons (5×106), both neural network architectures achieve equivalent accuracy. In contrast to Monte Carlo simulations, the proposed DL models can be used as inherently differentiable surrogate models in the photoacoustic image synthesis pipeline, allowing for back-propagation of the synthesis error and gradient-based optimization over the entire pipeline. Due to their efficiency, they have the potential to enable large-scale training data generation that can expedite the clinical application of photoacoustic imaging.

A Review on the Roles of Photoacoustic Imaging for Conventional and Novel Clinical Diagnostic Applications

Photoacoustic imaging is a promising medical imaging modality that enables the visualization of molecular functional and morphological information of biological tissues. Its clinical potential has been widely investigated for assessing and diagnosing various diseases. Currently, several research groups are developing photoacoustic imaging systems for translation from the laboratory to the clinic. In particular, the integration of photoacoustic imaging into existing diagnostic ultrasound applications, such as cancer diagnosis, has shown promising results. Additionally, recent research has explored the application of photoacoustic imaging for novel clinical uses. In this review paper, recent trials of photoacoustic imaging in both conventional and novel clinical applications are summarized and evaluated. Additionally, current limitations and future directions of photoacoustic imaging for successful translation into the clinical world are discussed. The aim of this review is to provide a comprehensive overview of the recent advancements in photoacoustic imaging and highlight its potential for clinical diagnosis and treatment. It is hoped that this review will contribute to the development of improved diagnostic and therapeutic approaches for a wide range of diseases using photoacoustic imaging.

Numerical Modelling of the Optical–Acoustical Characterization of an Anti-Resonant Bragg Hollow Core Fiber

Anti-resonant hollow core fibers (AR-HCFs) provide a promising solution for photothermal spectroscopy and photoacoustic imaging applications. Here, the AR-HCF serves as a micro platform to induce the photothermal/photoacoustic effect. Since the Bragg structure can induce multiple AR effects compared with the general AR-HCF, we proposed a novel device, the AR-BHCF (AR-HCF with Bragg cladding), to enhance the excitation efficiency. The simulation and experimental results validate that the AR-BHCF dominates in having a stronger ability to confine the optical field in the air core indeed. Then, the acoustic signal stimulated by the photoacoustic effect will propagate along with the fiber axial, and part of it will penetrate out of the AR-BHCF. The results revealed that the transmission bandwidth of the acoustic wave in the AR-BHCF ranges from 1 Hz to 1 MHz, covering infrasound to ultrasound. In particular, a constant coefficient of 0.5 exists in the acoustic wave fading process, related to the propagation frequency and time. The acoustic signal can be monitored in real time, assisted by the ultra-highly sensitive sensor head. Therefore, BHCF-based devices combined with photoacoustic techniques may accelerate their sensing applications. Meanwhile, this scheme shines a light on the theoretical foundation of novel short-haul distributed acoustic sensing.

Application of Photoacoustic Imaging for Pneumonia Detection

Application of Photoacoustic Imaging for Pneumonia Detection

Heavy-atom engineered hypoxia-responsive probes for precisive photoacoustic imaging and cancer therapy

Photoacoustic agents combining photodynamic therapy (PDT) and photothermal therapy (PTT) functions have emerged as potent theranostic agents for combating cancer. The molecular approaches for enhancing the near-infrared (NIR)-absorption and maximizing non-radiative energy transfer are essential for effective photoacoustic imaging (PAI) and therapy applications. In addition, such molecules with high specificity and affinity to cancer cells are urgently needed, which would further decrease the side effect during treatments. In this study, we applied a heavy-atom engineering strategy and introduced p-aminophenol, -thio, and -seleno moieties into NIR heptamethine cyanine (Cy7) skeleton (Cy7-X-NH2, X = O, S, Se) to significantly increase photothermal conversion efficiency for PTT and promote intersystem crossing for PDT. Additionally, we designed a series of nitroreductase (NTR)-activated photoacoustic probes (Cy7-X-NO2, X = O, S, Se), and target hypoxic tumors with NTR overexpression. Our prostate cancer targeting probe, Cy7-Se-NO2-KUE, exhibited specific tumor photoacoustic signals and effective tumor killing through outstanding synergistic PTT/PDT in vivo. These findings highlighted a versatile strategy for cancer photoacoustic diagnosis and enhanced phototherapy.

Recent Advances in Photoacoustic Agents for Theranostic Applications.

Photoacoustic agents are widely used in various theranostic applications. By evaluating the biodistribution obtained from photoacoustic images, the effectiveness of theranostic agents in terms of their delivery efficiency and treatment responses can be analyzed. Through this study, we evaluate and summarize the recent advances in photoacoustic-guided phototherapy, particularly in photothermal and photodynamic therapy. This overview can guide the future directions for theranostic development. Because of the recent applications of photoacoustic imaging in clinical trials, theranostic agents with photoacoustic monitoring have the potential to be translated into the clinical world.

Assessment of nonalcoholic fatty liver function by photoacoustic imaging

SignificanceThe assessment of liver function plays an important role in the diagnosis of nonalcoholic fatty liver disease (NAFLD). Current noninvasive imaging methods have limited applicability in this regard.AimWe report an application of multispectral photoacoustic imaging (PAI), an emerging modality, to visualize lipid accumulation and liver function in NAFLD.ApproachWe first demonstrated the liver function reserve with indocyanine green (ICG) to verify the organ’s dysfunction due to NAFLD in a rabbit model. We then noninvasively quantified lipid content in the liver using multispectral PAI. The in vivo PAI results were compared and verified with photoacoustic ex vivo images and liver biopsy.ResultsA significant difference in the lipidmean value was observed [lipidmean = 0.081 ± 0.0161 arbitrary units (a.u.) control versus NAFLD 0.198 ± 0.048 a.u., P = 0.003]. Similar to in vivo analysis, a significant difference in lipidmean was observed (lipidmean = 0.0673 ± 0.0165 versus 0.486 ± 0.073 a.u., P < 0.0001) between control and NAFLD group ex vivo. For liver function, the control group showed a rapid decrease after the peak point, whereas the elimination of ICG for the NAFLD group was slower.ConclusionsOur study shows that PAI has the potential to provide a noninvasive biomarker for the assessment of liver function and lipid accumulation for NAFLD diagnosis and treatment.

A Deep Learning Method for Motion Artifact Correction in Intravascular Photoacoustic Image Sequence.

In vivo application of intravascular photoacoustic (IVPA) imaging for coronary arteries is hampered by motion artifacts associated with the cardiac cycle. Gating is a common strategy to mitigate motion artifacts. However, a large amount of diagnostically valuable information might be lost due to one frame per cycle. In this work, we present a deep learning-based method for directly correcting motion artifacts in non-gated IVPA pullback sequences. The raw signal frames are classified into dynamic and static frames by clustering. Then, a neural network named Motion Artifact Correction (MAC)-Net is designed to correct motion in dynamic frames. Given the lack of the ground truth information on the underlying dynamics of coronary arteries, we trained and tested the network using a computer-generated dataset. Based on the results, it has been observed that the trained network can directly correct motion in successive frames while preserving the original structures without discarding any frames. The improvement in the visual effect of the longitudinal view has been demonstrated based on quantitative evaluation of the inter-frame dissimilarity. The comparison results validated the motion-suppression ability of our method comparable to gating and image registration-based non-learning methods, while maintaining the integrity of the pullbacks without image preprocessing. Experimental results from in vivo intravascular ultrasound and optical coherence tomography pullbacks validated the feasibility of our method in the in vivo intracoronary imaging scenario.

Photoacoustic imaging for investigating tumor hypoxia: a strategic assessment.

Hypoxia causes the expression of signaling molecules which regulate cell division, lead to angiogenesis, and further, in the tumor microenvironment, promote resistance to chemotherapy and radiotherapy, and induce metastasis. Photoacoustic imaging (PAI) takes advantage of unique absorption characteristics of chromophores in tissues and provides the opportunity to construct images with a high degree of spatial and temporal resolution. In this review, we discuss the physiologic characteristics of tumor hypoxia, and current applications of PAI using endogenous (label free imaging) and exogenous (organic and inorganic) contrast agents. Features of various methods in terms of their efficacy for determining physiologic and proteomic phenomena are analyzed. This review demonstrates that PAI has the potential to understand tumor growth and metastasis development through measurement of regulatory molecule concentrations, oxygen gradients, and vascular distribution.