Photoacoustic Research Articles

Oxygen-defect bismuth oxychloride nanosheets for ultrasonic cavitation effect enhanced sonodynamic and second near-infrared photo-induced therapy of breast cancer

Sonodynamic therapy (SDT) relies heavily on the presence of oxygen to induce cell death. Its effectiveness is thus diminished in the hypoxic regions of tumor tissue. To address this issue, the exploration of ultrasound-based synergistic treatment modalities has become a significant research focus. Here, we report an ultrasonic cavitation effect enhanced sonodynamic and 1208 nm photo-induced cancer treatment strategy based on thermoelectric/piezoelectric oxygen-defect bismuth oxychloride nanosheets (BNs) to realize the high-performance eradication of tumors. Upon ultrasonic irradiation, the local high temperature and high pressure generated by the ultrasonic cavitation effect combined with the thermoelectric and piezoelectric effects of BNs create a built-in electric field. This facilitates the separation of carriers, increasing their mobility and extending their lifetimes, thereby greatly improving the effectiveness of SDT and NIR-Ⅱ phototherapy on hypoxia. The Tween-20 modified BNs (TBNs) demonstrate ∼88.6 % elimination rate against deep-seated tumor cells under hypoxic conditions. In vivo experiments confirm the excellent antitumor efficacy of TBNs, achieving complete tumor elimination within 10 days with no recurrences. Furthermore, due to the high X-ray attenuation of Bi and excellent NIR-Ⅱ absorption, TBNs enable precise cancer diagnosis through photoacoustic (PA) imaging and computed tomography (CT).

Mesoporous platinum@copper selenide-based NIR-II photothermal agents with photothermal conversion efficiency over 80% for photoacoustic imaging and targeted cancer therapy

Elevating photothermal conversion efficiency (PCE) is the key to enhance curative efficacy during photothermal therapy. Nevertheless, current functionalized or synthetic methods for preparing photothermal agents with high PCE are too complicated, greatly hindering the development of photothermal therapy. In this study, we developed a tumor-targeting flower-like nanocomposite termed mesoporous platinum nanoparticles@Cu2-xSe-AS1411 (MPNPs@Cu2-xSe-AS1411, denoted as MPCSA) with remarkable PCE for high-resolution photoacoustic (PA) imaging guided photothermal/chemodynamic therapy for tumor ablation. We discovered that MPNPs served as carriers for delivering PA contrast agents. Cu2-xSe nanosheets emerged as promising near-infrared-II (NIR-II) PA imaging and photothermal/chemodynamic therapy agents owing to their strong localized surface plasmon resonance property in the NIR-II region. The amine-modified AS1411 aptamer, which is connected to the surface of the flower-like MPNPs@Cu2-xSe can target the nucleolar protein on the surface of 4T1 cells, achieving the accumulation of MPCSA at the tumor site in mice. Notably, these MPCSA nano-flowers exhibited an excellent PCE up to 82.33 % under 1064 nm laser irradiation, resulting in highly efficient cancer cell ablation and greatly hindering in vivo tumor growth. This study has paved the way for imaging-guided accurate cancer diagnosis and targeted cancer therapy.

Deep learning combined with attention mechanisms to assist radiologists in enhancing breast cancer diagnosis: a study on photoacoustic imaging.

Accurate prediction of breast cancer (BC) is essential for effective treatment planning and improving patient outcomes. This study proposes a novel deep learning (DL) approach using photoacoustic (PA) imaging to enhance BC prediction accuracy. We enrolled 334 patients with breast lesions from Shenzhen People's Hospital between January 2022 and January 2024. Our method employs a ResNet50-based model combined with attention mechanisms to analyze photoacoustic ultrasound (PA-US) images. Experiments demonstrated that the PAUS-ResAM50 model achieved superior performance, with an AUC of 0.917 (95% CI: 0.884 -0.951), sensitivity of 0.750, accuracy of 0.854, and specificity of 0.920 in the training set. In the testing set, the model maintained high performance with an AUC of 0.870 (95% CI: 0.778-0.962), sensitivity of 0.786, specificity of 0.872, and accuracy of 0.836. Our model significantly outperformed other models, including PAUS-ResNet50, BMUS-ResAM50, and BMUS-ResNet50, as validated by the DeLong test (p < 0.05 for all comparisons). Additionally, the PAUS-ResAM50 model improved radiologists' diagnostic specificity without reducing sensitivity, highlighting its potential for clinical application. In conclusion, the PAUS-ResAM50 model demonstrates substantial promise for optimizing BC diagnosis and aiding radiologists in early detection of BC.

Supramolecular assembly of Polydopamine@Fe nanoparticles with near-infrared light-accelerated cascade catalysis applied for synergistic photothermal-enhanced chemodynamic therapy

Chemodynamic therapy (CDT) via Fenton-like reaction is greatly attractive owing to its capability to generate highly cytotoxic •OH radicals from tumoral hydrogen peroxide (H2O2). However, the antitumor efficacy of CDT is often challenged by the relatively low radical generation efficiency and the high levels of antioxidative glutathione (GSH) in tumor microenvironment. Herein, an innovative photothermal Fenton-like catalyst, Fe-chelated polydopamine (PDA@Fe) nanoparticle, with excellent GSH-depleting capability is constructed via one-step molecular assembly strategy for dual-modal imaging-guided synergetic photothermal-enhanced chemodynamic therapy. Fe(III) ions in PDA@Fe nanoparticles can consume the GSH overexpressed in tumor microenvironment to avoid the potential •OH consumption, while the as-produced Fe(II) ions subsequently convert tumoral H2O2 into cytotoxic •OH radicals through the Fenton reaction. Notably, PDA@Fe nanoparticles demonstrate excellent near-infrared light absorption that results in superior photothermal conversion ability, which further boosts above-mentioned cascade catalysis to yield more •OH radicals for enhanced CDT. Taken together with T1-weighted magnetic resonance imaging (MRI) contrast enhancement (r1 = 8.13 mM−1 s−1) and strong photoacoustic (PA) imaging signal of PDA@Fe nanoparticles, this design finally realizes the synergistic photothermal-chemodynamic therapy. Overall, this work offers a new promising paradigm to effectively accommodate both imaging and therapy functions in one well-defined framework for personalized precision disease treatment.

Ultrafast measurement of photoacoustic parameters with mid-infrared frequency comb transients.

The photoacoustic (PA) effect has been widely used in various applications, including highly sensitive spectroscopy and label-free, non-invasive imaging. In this work, we demonstrate a fast and precise measurement of PA parameters for light-absorbing liquids using mid-infrared asynchronous sampling pump-probe measurements. To simulate the observed PA oscillation signals and extract various PA parameters as a function of pump power, we derived analytical solutions of the PA wave equation driven by a train of ultrashort Gaussian pump pulses. By fitting the analytical solution to the measured PA signals using a nonlinear curve fitting method, we could measure the PA parameters, including damping rate, viscosity, and natural frequency. Furthermore, the dynamic response of thermophysical properties of the chloroform solution is also investigated by measuring the variation of the Grüneisen parameter with pump power. We anticipate that this work will open new possibilities for precise in situ measurements of the thermal properties of light-absorbing liquids.

Photoacoustic Imaging Using Polysaccharide-Porphyrin Complexes by Photoirradiation at Long Wavelengths.

Photoacoustic (PA) imaging is a novel biological imaging technique with superior depth resolution compared to fluorescence imaging. The efficacy of PA imaging depends on contrast agents that possess considerable absorbance at longer wavelengths, coupled with high permeability in biological tissue and minimal fluorescence, achieved through mitigating aggregation-caused quenching (ACQ) that attenuates PA intensity. Despite the successful transfer of porphyrin 2 featuring amino moieties from polysaccharides to liposomes, most of 2 incorporated within λ-carrageenan (CGN-2 complex) remained in CGN under acidic lysosomal conditions (pH 5.0). Consequently, the CGN-2 complex exhibited a strong PA signal under 680 nm photoirradiation in Colon26 cells owing to the ACQ of 2. Moreover, the PA intensity of the CGN-2 complex was further enhanced under 780 nm photoirradiation owing to the increased absorbance at 780 nm facilitated by the redshift of the Q-band at pH 5.0.

Unsupervised denoising of photoacoustic images based on the Noise2Noise network.

In this study, we implemented an unsupervised deep learning method, the Noise2Noise network, for the improvement of linear-array-based photoacoustic (PA) imaging. Unlike supervised learning, which requires a noise-free ground truth, the Noise2Noise network can learn noise patterns from a pair of noisy images. This is particularly important for in vivo PA imaging, where the ground truth is not available. In this study, we developed a method to generate noise pairs from a single set of PA images and verified our approach through simulation and experimental studies. Our results reveal that the method can effectively remove noise, improve signal-to-noise ratio, and enhance vascular structures at deeper depths. The denoised images show clear and detailed vascular structure at different depths, providing valuable insights for preclinical research and potential clinical applications.

Influence of water vapor concentration on photoacoustic spectroscopy‐based characteristic gas analysis of transformer faults

AbstractThe water vapor in the ambient air affects the accuracy of the photoacoustic (PA) dissolved gas analysis system for transformer health monitoring. A laser PA system was evaluated by dry and humidified standard gases to study the influence of water vapor concentration on PA gas detection. Theoretical analysis was conducted on the effect of gas molecule relaxation on PA signal detection. A high‐frequency resonant PA cell and a low‐frequency nonresonant PA cell were used to detect acetylene (C2H2) and carbon monoxide (CO), respectively. The experimental results show that the PA signal of humidified CO is about 12 times higher than PA signal of dry gas for the resonant PA detection system, respectively. In addition, as the frequency is increased from 30 to 980 Hz, the PA signals of humidified and dry CO attenuate by 1.5 and 6.9 times, respectively.

Portable Photoacoustic Analytical System Combined with Wearable Hydrogel Patch for pH Monitoring in Chronic Wounds.

Timely diagnosis, monitoring, and management of chronic wounds play crucial roles in improving patients' quality of life, but clinical evaluation of chronic wounds is still ambiguous and relies heavily on the experience of clinician, resulting in increased social and financial burden and delay of optimal treatment. During the different stages of the healing process, specific and dynamic changes of pH values in the wound exudate can be used as biomarkers to reflect the wound status. Herein, a pH-responsive agent with well-behaved photoacoustic (PA) properties, nitrazine yellow (NY), was incorporated in poly(vinyl alcohol)/sucrose (PVA/Suc) hydrogel to construct a wearable pH-sensing patch (PVA/Suc/NY hydrogel) for monitoring of pH values during chronic wound healing. According to Rosencwaig-Gersho theory and the combination of 3D printing technology, the PA chamber volume and chopping frequency were systematically optimized to improve the sensitivity of the PA analytical system. The prepared PVA/Suc/NY hydrogel patch had excellent mechanical properties and flexibility and could maintain conformal contact with skin. Moreover, combined with the miniaturized PA analytical device, it had the potential to detect pH values (5.0-9.0) free from the color interference of blood and therapeutic drugs, which provides a valuable strategy for wound pH value monitoring by PA quantitation. This strategy of combining the wearable hydrogel patch with portable PA analysis offers broad new prospects for the treatment and management of chronic wounds due to its features of simple operation, time savings, and anti-interference.

Optimization on artifacts in photoacoustic images based on spectrum analyses and signal extraction.

Photoacoustic (PA) imaging is a promising technology for functional imaging of biological tissues, offering optical contrast and acoustic penetration depth. However, the presence of signal aliasing from multiple PA sources within the same imaging object can introduce artifacts and significantly impact the quality of the PA tomographic images. In this study, an optimized method is proposed to suppress these artifacts and enhance image quality effectively. By leveraging signal time-frequency spectrum, signals from each PA source can be extracted. Subsequently, the images are reconstructed using these extracted signals and fused together to obtain an optimized image. To verify this proposed method, PA imaging experiments were conducted on two phantoms and two in vitro samples and the distribution relative error and root mean square error of the images obtained through conventional and optimized methods were calculated. The results demonstrate that the proposed method successfully suppresses the artifacts and substantially improves the image quality.

Adaptively multi-scale microstructure characterization of cancellous bone via photoacoustic signal decomposition

Osteoporosis is a systemic disease with a high incidence in the elderly and seriously affects the quality of life of patients. Photoacoustic (PA) technology, which combines the advantages of light and ultrasound, can provide information about the physiological structure and chemical information of biological tissues in a non-invasive and non-radiative way. Due to the complex structural characteristics of bone tissue, PA signals generated by bone tissue are non-stationary and nonlinear. However, conventional PA signal processing methods are not effective for non-stationary signal processing. In this study, an empirical mode decomposition (EMD)-based Hilbert-Huang transform (HHT) PA signal analysis method, called HHT PA signal analysis (HPSA), was developed to assess the microstructure information of bone tissue, which is closely related to bone health. The feasibility of the HPSA method in bone health assessment was proven by numerical simulation and experimental studies on animal samples with different bone volume/total volume (BV/TV) and bone mineral densities. First, based on adaptive EMD, the different modes correlated with multi-scale information were mined from the PA signal, the correlations between different intrinsic mode function (IMF) modes and BV/TVs were analyzed, and the optimal mode for more efficient PA time–frequency analysis was selected. Second, multi-wavelength HPSA was used to assess the changes in the chemical components of the bone tissue. The results demonstrate that the HPSA method can distinguish bones with different BV/TVs and microstructure conditions adaptively with high efficiency. They further emphasize the potential of PA techniques in characterizing biological tissues in bones for early and rapid detection of bone diseases.

Masked cross-domain self-supervised deep learning framework for photoacoustic computed tomography reconstruction

Accurate image reconstruction is crucial for photoacoustic (PA) computed tomography (PACT). Recently, deep learning has been used to reconstruct PA images with a supervised scheme, which requires high-quality images as ground truth labels. However, practical implementations encounter inevitable trade-offs between cost and performance due to the expensive nature of employing additional channels for accessing more measurements. Here, we propose a masked cross-domain self-supervised (CDSS) reconstruction strategy to overcome the lack of ground truth labels from limited PA measurements. We implement the self-supervised reconstruction in a model-based form. Simultaneously, we take advantage of self-supervision to enforce the consistency of measurements and images across three partitions of the measured PA data, achieved by randomly masking different channels. Our findings indicate that dynamically masking a substantial proportion of channels, such as 80%, yields meaningful self-supervisors in both the image and signal domains. Consequently, this approach reduces the multiplicity of pseudo solutions and enables efficient image reconstruction using fewer PA measurements, ultimately minimizing reconstruction error. Experimental results on in-vivo PACT dataset of mice demonstrate the potential of our self-supervised framework. Moreover, our method exhibits impressive performance, achieving a structural similarity index (SSIM) of 0.87 in an extreme sparse case utilizing only 13 channels, which outperforms the performance of the supervised scheme with 16 channels (0.77 SSIM). Adding to its advantages, our method can be deployed on different trainable models in an end-to-end manner, further enhancing its versatility and applicability.

Probe fusion all-optic OCT-PAM dual-mode imaging system for biomedical imaging

We proposed a non-contact photoacoustic (PA) detection method using spectral domain optical coherence tomography (SDOCT). Two interference spectrums (A-lines) were acquired before and after the PA excitation with SDOCT. PA signal propagated within the sample causing the vibration. The vibration inner the sample introduced phase change between the acquired two A-lines. Thus, the PA signal can be detected by evaluating the difference in phase between the two A-lines. Based on the method, an OCT-PAM dual-mode imaging system was constructed. In the system, SDOCT served as the detection unit for PAM. Thus, the combination of the two imaging modalities was simplified. Another advantage of the system is that it realizes non-contact all-optic detection, which is attractive for biomedical imaging. Using the system, we imaged phantoms of carbon fibers, asparagus leaves and human hairs. Furthermore, the cortical vasculature of rat was imaged in vivo and the flow status was evaluated quantitatively.

Pretheranostic agents with extraordinaryNIRF/photoacoustic imaging performanceand photothermal oncotherapy efficacy

Cervical cancer, the most common gynecological malignancy, significantly and adversely affects women's physical health and well-being. Traditional surgical interventions and chemotherapy, while potentially effective, often entail serious side effects that have led to an urgent need for novel therapeutic methods. Photothermal therapy (PTT) has emerged as a promising approach due to its ability to minimize damage to healthy tissue. Connecting a biothiol detection group to PTT-sensitive molecules can improve tumor targeting and further minimize potential side effects. In this study, we developed a near-infrared fluorescence (NIRF)/photoacoustic (PA) dual-mode probe, S-NBD, which demonstrated robust PTT performance. This innovative probe is capable of activating NIRF/PA signals to enable the detection of biothiols with high emission wavelength (838 nm) and large Stokes shift (178 nm), allowing for in vivo monitoring of cancer cells. Additionally, the probe achieved an outstanding photothermal conversion efficiency of 67.1%. The application of laser irradiation (660 nm, 1.0 W/cm2, 5 min) was able to achieve complete tumor ablation without recurrence. In summary, this seminal study presents a pioneering NIRF/PA dual-mode dicyanoisophorone-based probe for biothiol imaging, incorporating features from PTT for the first time. This pioneering approach achieves the dual objectives of improving tumor diagnosis and treatment.

Enhanced photoacoustic signal processing using empirical mode decomposition and machine learning

ABSTRACT In this study, we propose a robust photoacoustic (PA) signal processing framework for a material independent defect detection using empirical mode decomposition (EMD) and machine learning algorithms. First, a database of the PA signals with 960 samples has been obtained from aluminium, iron, plastic and wood materials using a laser, microphone and data acquisition board-based PA apparatus. Second, the EMD based time and time-frequency domain techniques are proposed to extract robust cross-material feature space focusing on laser induced acoustic signal, and the decomposed intrinsic mode (IMF) with 14 extracted features are performed on totally 960 samples PA signals to evaluate k-nearest neighbour (k-NN), decision tree (DT) and support vector machine (SVM) classifiers. Inter- material and cross-material evaluations are performed, and the accuracy rates up to 100% for SVM and 97.77% for k-NN are yielded.

Tuning Tumor Targeting and Ratiometric Photoacoustic Imaging by Fine-Tuning Torsion Angle for Colorectal Liver Metastasis Diagnosis.

Photoacoustic (PA) tomography is an emerging biomedical imaging technology for precision cancer medicine. Conventional small-molecule PA probes usually exhibit a single PA signal and poor tumor targeting that lack the imaging reliability. Here, we introduce a series of cyanine/hemicyanine interconversion dyes (denoted Cy-HCy) for PA/fluorescent dual-mode probe development that features optimized ratiometric PA imaging and tunable tumor-targeting ability for precise diagnosis and resection of colorectal cancer (CRC). Importantly, Cy-HCy can be presented in cyanine (inherent tumor targeting and long NIR PA wavelength) and hemicyanine (poor tumor targeting and short NIR PA wavelength) by fine-tuning torsion angle and the ingenious transformation between cyanine and hemicyanine through regulation optically tunable group endows the NIR ratiometric PA and tunable tumor-targeting properties. To demonstrate the applicability of Cy-HCy dyes, we designed the first small-molecule tumor-targeting and NIR ratiometric PA probe Cy-HCy-H2S for precise CRC liver metastasis diagnosis, activated by H2S (a CRC biomarker). Using this probe, we not only visualized the subcutaneous tumor and liver metastatic cancers in CRC mouse models but also realized PA and fluorescence image-guided tumor excision. We expect that Cy-HCy will be generalized for creating a wide variety of inherently tumor-targeting NIR ratiometric PA probes in oncological research and practice.

High-Precision Photoacoustic Neural Modulation Uses a Non-Thermal Mechanism.

Neuromodulation is a powerful tool for fundamental studies in neuroscience and potential treatments of neurological disorders. Both photoacoustic (PA) and photothermal (PT) effects are harnessed for non-genetic high-precision neural stimulation. Using a fiber-based device excitable by a nanosecond pulsed laser and a continuous wave laser for PA and PT stimulation, respectively, PA and PT neuromodulation is systematically investigated at the single neuron level. These results show that to achieve the same level of neuron activation recorded by Ca2+ imaging, the laser energy needed for PA stimulation is 1/40 of that needed for PT stimulation. The threshold energy for PA stimulation is found to be further reduced in neurons overexpressing mechano-sensitive channels, indicating direct involvement of mechano-sensitive channels in PA stimulation. Electrophysiology study of single neurons upon PA and PT stimulation is performed by patch clamp recordings. Electrophysiological features induced by PA are distinct from those by PT, confirming that PA and PT stimulation operate through different mechanisms. These insights offer a foundation for the rational design of more efficient and safer non-genetic neural modulation approaches.

Tri-modality in vivo imaging for tumor detection with combined ultrasound, photoacoustic, and photoacoustic elastography

A comprehensive understanding of a tumor is required for accurate diagnosis and effective treatment. However, currently, there is no single imaging modality that can provide sufficient information. Photoacoustic (PA) imaging is a hybrid imaging technique with high spatial resolution and detection sensitivity, which can be combined with ultrasound (US) imaging to provide both optical and acoustic contrast. Elastography can noninvasively map the elasticity distribution of biological tissue, which reflects pathological conditions. In this study, we incorporated PA elastography into a commercial US/PA imaging system to develop a tri-modality imaging system, which has been tested for tumor detection using four mice with different physiological conditions. The results show that this tri-modality imaging system can provide complementary information on acoustic, optical, and mechanical properties. The enabled visualization and dimension estimation of tumors can lead to a more comprehensive tissue characterization for diagnosis and treatment.

Quartz Enhanced Photoacoustic Spectroscopy on Solid Samples.

Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS) is a technique in which the sound wave is detected by a quartz tuning fork (QTF). It enables particularly high specificity with respect to the excitation frequency and is well known for an extraordinarily sensitive analysis of gaseous samples. We have developed the first photoacoustic (PA) cell for QEPAS on solid samples. Periodic heating of the sample is excited by modulated light from an interband cascade laser (ICL) in the infrared region. The cell represents a half-open cylinder that exhibits an acoustical resonance frequency equal to that of the QTF and, therefore, additionally amplifies the PA signal. The antinode of the sound pressure of the first longitudinal overtone can be accessed by the sound detector. A 3D finite element (FE) simulation confirms the optimal dimensions of the new cylindrical cell with the given QTF resonance frequency. An experimental verification is performed with an ultrasound micro-electromechanical system (MEMS) microphone. The presented frequency-dependent QEPAS measurement exhibits a low noise signal with a high-quality factor. The QEPAS-based investigation of three different solid synthetics resulted in a linearly dependent signal with respect to the absorption.

Laser-activated perfluorocarbon nanodroplets for intracerebral delivery and imaging via blood–brain barrier opening and contrast-enhanced imaging

BackgroundUltrasound and photoacoustic (US/PA) imaging is a promising tool for in vivo visualization and assessment of drug delivery. However, the acoustic properties of the skull limit the practical application of US/PA imaging in the brain. To address the challenges in targeted drug delivery to the brain and transcranial US/PA imaging, we introduce and evaluate an intracerebral delivery and imaging strategy based on the use of laser-activated perfluorocarbon nanodroplets (PFCnDs).MethodsTwo specialized PFCnDs were developed to facilitate blood‒brain barrier (BBB) opening and contrast-enhanced US/PA imaging. In mice, PFCnDs were delivered to brain tissue via PFCnD-induced BBB opening to the right side of the brain. In vivo, transcranial US/PA imaging was performed to evaluate the utility of PFCnDs for contrast-enhanced imaging through the skull. Ex vivo, volumetric US/PA imaging was used to characterize the spatial distribution of PFCnDs that entered brain tissue. Immunohistochemical analysis was performed to confirm the spatial extent of BBB opening and the accuracy of the imaging results.ResultsIn vivo, transcranial US/PA imaging revealed localized photoacoustic (PA) contrast associated with delivered PFCnDs. In addition, contrast-enhanced ultrasound (CEUS) imaging confirmed the presence of nanodroplets within the same area. Ex vivo, volumetric US/PA imaging revealed PA contrast localized to the area of the brain where PFCnD-induced BBB opening had been performed. Immunohistochemical analysis revealed that the spatial distribution of immunoglobulin (IgG) extravasation into the brain closely matched the imaging results.ConclusionsUsing our intracerebral delivery and imaging strategy, PFCnDs were successfully delivered to a targeted area of the brain, and they enabled contrast-enhanced US/PA imaging through the skull. Ex vivo imaging, and immunohistochemistry confirmed the accuracy and precision of the approach.Graphical