搜索结果：Photoacoustics

Quantitative molecular imaging in photoacoustics is fundamentally limited by the ill-posed nature of spectral unmixing, where spectral overlap, noise, and unknown fluence introduce bias in conventional inversion-based methods. We introduce photoacoustic fingerprinting (PAF), a framework that reframes spectral unmixing as a fingerprint recognition problem. PAF interprets multispectral signals as high-dimensional fingerprints encoding both molecular composition and measurement distortions. Inspired by magnetic resonance fingerprinting, PAF uses a recurrent neural network trained on synthetic data spanning realistic mixtures, noise levels, and fluence variations to directly infer molecular concentrations from spectral shape. PAF enables accurate and robust quantification in regimes where conventional methods break down, including low signal-to-noise conditions, spectrally correlated mixtures, and unknown fluence distortions. In controlled simulations, PAF consistently outperformed non-negative least squares, with the largest gains observed for spectrally overlapping chromophores such as collagen. In phantom studies, PAF improved molecular specificity by correctly localizing collagen and recovering water contrast despite similar spectral reconstructions. In ex vivo mouse livers, PAF detected lipid accumulation associated with steatosis, and in human arteries, it identified molecular signatures consistent with thrombus and lipid-rich plaque. These results establish PAF as a generalizable framework for label-free molecular imaging and a promising step toward quantitative photoacoustic diagnostics.

Efficacy of antiangiogenic treatments is often linked to the complex interplay between tumor vascularization and oxygenation. Yet their relationship remains difficult to assess in vivo due to limitations of conventional clinical imaging techniques. We used a combination of noninvasive optoacoustic (OA) angiography and diffuse optical spectroscopy (DOS) to investigate the effects of the antiangiogenic therapy on vascular structure and oxygenation in subcutaneous xenograft model of Colo320 colon adenocarcinoma. Axitinib, a tyrosine kinase inhibitor targeting VEGF receptors, was administered into animals at 50 mg/kg, five days per week for four weeks. Raster-scan OA imaging was performed using 532 nm pulsed laser source and a wideband polyvinylidene difluoride (PVDF) detector. DOS measurements were conducted using a fiber-optic-based reflectance system. Immunohistochemical (IHC) analysis for CD31 and the hypoxia marker pimonidazole was used for validation. Axitinib treatment resulted in a thirtyfold reduction in the median tumor volume. OA imaging revealed reductions in volumetric vessel fraction and projected vessel area, while DOS showed a transient increase in blood oxygen saturation. IHC confirmed a decrease in microvessel density post-treatment and indicated larger hypoxic areas in treated tumors compared to controls at the experimental endpoint. The newly introduced approach thus facilitates experimental studies aiming at optimization of antiangiogenic treatment regimens and their subsequent combination with other treatment modalities, such as radiation therapy, where effectiveness may strongly depend on the vascular network condition and tumor oxygenation levels.

An innovative photoacoustic (PA) sensor based on a single multipass photoacoustic cell with cross-patterned spots has been developed to achieve simultaneous detection of dual-component gases. The multipass cell (MPC) integrates two fiber collimators, each operating at a distinct wavelength, to couple the respective excitation beams into the cell concurrently, inducing multiple reflections and forming two perpendicularly oriented sets of elliptically distributed spots. This dual-coupling design allows each collimator to be independently optimized for its target gas, thus fully utilizing available laser power even when absorption lines are far apart. The capability of the sensor was validated by employing two lasers at 1651 and 2327 nm to selectively excite methane (CH4) and carbon monoxide (CO), respectively. The concentration of water vapor (H2O) in the gas sample was maintained at about 18,000 ppm to avoid the influence from de-excitation rate change. In addition, the cross-interference between CH4 and CO was reduced to almost zero by optimizing the modulation currents. The developed system, confirming the effectiveness of the sensor in resolving and analyzing dual-gas mixtures, achieves minimum detection limits (MDLs) of 25 ppb for CH4 and 240 ppb for CO at 1 s averaging time, with corresponding normalized noise equivalent absorption (NNEA) coefficients of 2.8 × 10-10 and 5.2 × 10-10 cm-1 W Hz-1/2, respectively. The response time of the system is measured as 10 s using 10 ppm of CH4 and 100 ppm of CO, which evaluates the rapid-response capability of the developed system.

The efficacy of photothermal therapy is fundamentally governed by the efficiency of non-radiative decay; however, current organic photothermal agents are severely limited by competitive energy flow pathways and sluggish excited-state decay kinetics. These dual bottlenecks prevent the maximization of heat generation per absorbed photon. To overcome these barriers, we designed energy barriers that divert energy from both radiative decay and triplet-state transfer toward non-radiative heat generation, thereby enhancing efficiency. Furthermore, by employing a consecutive twisted intramolecular charge transfer (ConTICT) mechanism, we accelerate the cycle rate of non-radiative relaxation. The long-wavelength, high-efficiency photothermal molecule Cy-CF3 undergoes ConTICT cycling 112 times per 10 ns, achieving a multiple photothermal cycle efficiency of 66.8%, thus addressing the challenge of slow return to the ground state. This holistic design strategy enables Cy-CF3 to achieve a high photothermal conversion efficiency of 87.4% under low-power irradiation (300 mW cm-2). Furthermore, it induces disruption of lysosomal structures, and blocks autophagy processes. Upon encapsulation into liposomes, the photothermal agent exhibits specific tumor site targeting, enables fluorescence/photothermal/photoacoustic trimodal deep-tissue imaging, and delivers robust in vivo antitumor therapeutic efficacy. This work presents a generalizable molecular strategy for precisely manipulating quantum energy flow to construct next-generation phototheranostics.

The assessment of lymphatic drainage function is essential for understanding the role of the lymphatic system in fluid homeostasis, immunosurveillance and disease processes. Conventional methods of evaluation rely on dynamic visualization with tracers, such as X-ray lymphangiography, lymphoscintigraphy and magnetic resonance lymphangiography. However, these methods have limitations in terms of invasiveness and resolution, and other aspects. Recent advances in optical technologies and nanomaterials technology have enabled the development of noninvasive, high-precision testing methods, such as photoacoustic imaging and optical coherence tomography, which have made it possible to visualize and analyze lymphatic flow rates, tracer clearance rates and functional abnormalities. In addition, the application of artificial intelligence-assisted analysis, multimodal imaging, and targeted nanoprobes has significantly improved the precision and clinical applicability of these methods. In this article, we systematically review the principles, characteristics, clinical applications and preclinical research progress of nine classical or novel lymphatic drainage function testing techniques. We also discuss the advantages and limitations of each technique and explore the future development trend, aiming to provide insights for basic research and clinical practice.

Optical-resolution photoacoustic microscopy (OR-PAM) is a promising noninvasive biomedical imaging technology capable of achieving micrometer or even sub-micrometer resolution. Its performance, however, is highly dependent on precise focusing. Traditional focusing methods are operator-dependent, low precise, and time-consuming, which greatly limits the practical applicability of OR-PAM, especially for users without sufficient training. In this study, we developed an autofocusing optical-resolution photoacoustic microscopy (AFOR-PAM) system by combining 3D motorized scan, unified data acquisition and motion control through a System-on-Chip (SoC) setup and an autofocusing algorithm based on a modified Brenner gradient function. The entire focusing process is fully automated and does not rely on the operator's experience. Phantom experiments verified the autofocusing capability of the AFOR-PAM system, requiring only 11 iterations and 1.4 s to complete a focusing process. In vivo imaging of the mice ears further demonstrated that AFOR-PAM can rapidly achieve more precise and reliable focusing than that with the conventional amplitude-based method. Moreover, the system exhibits strong robustness even under low signal-to-noise ratio (SNR) conditions. These advantages suggest that the proposed AFOR-PAM system has the potential to significantly broaden the practical applications of photoacoustic imaging in clinical settings.

Photoacoustic Computed Tomography (PACT) leverages the photoacoustic effect for high-resolution anatomical and molecular imaging. We developed an advanced PACT system using eight conventional linear arrays arranged in a half-ring geometry, achieving a balance between cost-efficiency and enhanced image quality through a large-aperture detection setup. Although this large-aperture PACT system provides high-quality imaging for in-vivo human applications, it is susceptible to optical shadowing and misalignment issues between optical paths and detection planes, particularly during complex and large-target imaging, such as imaging of the human hand. These issues can lead to degraded image quality. To address these issues, we implemented an encoder-decoder structure-based deep learning (DL) enhancement strategy. The DL model was initially trained using a paired PACT single-finger dataset, which included images obtained with full detection using all eight transducers and those with low detection using fewer transducers or elements. For human-hand PACT imaging, the DL-enhanced system, trained exclusively with the single-finger dataset, effectively mitigated the image quality issues by improving contrast-to-noise ratios and the clarity of vessel structures. These findings validate the efficacy of the DL-enhanced PACT system for complex anatomical imaging applications, such as diagnosing peripheral arterial disease.

Near-infrared fluorescence (NIRF) can deliver high-contrast, video-rate, non-contact imaging of tumor-targeted contrast agents with the potential to guide surgeries excising solid tumors. However, it has been met with skepticism for wide-margin excision due to sensitivity and resolution limitations at depths larger than ~ 5 mm in tissue. To address this limitation, fast-sweep photoacoustic-ultrasound (PAUS) imaging is proposed to complement NIRF. In an exploratory in vitro feasibility study using dark-red bovine muscle tissue, we observed that PAUS scanning can identify tozuleristide, a clinical stage investigational imaging agent, at a concentration of 20 µM from the background at depths estimated to be of up to ~ 34 mm, highly extending the capabilities of NIRF alone. The capability of spectroscopic PAUS imaging was tested by direct injection of 20 µM tozuleristide into bovine muscle tissue at a depth of ~ 8 mm. Experimental results demonstrate that multi-point laser fluence compensation and strong clutter suppression enabled by the unique capabilities of the fast-sweep approach greatly improve spectroscopic accuracy and the PA detection limit and strongly reduce image artifacts. Thus, the complementary NIRF-PAUS approach can be promising for comprehensive pre- (with PA) and intra- (with NIRF) operative solid tumor detection and wide-margin excision in optically guided solid tumor surgery.

The effectiveness of immunotherapy for hepatocellular carcinoma (HCC) is severely compromised by an immunosuppressive tumor microenvironment (TME) dominated by M2-polarized tumor-associated macrophages (TAMs), coupled with a lack of reliable strategies for real-time treatment monitoring. To address this, we developed a pH-responsive nanoimmunomodulator derived from macrophage exosomes for spatiotemporal TAM reprogramming combined with second near-infrared (NIR-II) theranostics. Our nanoplatform (anti-CD47 conjugated Croc@DMPC/Ag2Te/exosome, termed aCD47-CATE) is functionalized with anti-CD47 antibodies to block the CD47-"don't eat me" signal. For precise theranostics, it co-encapsulates silver telluride quantum dots for high-contrast NIR-II fluorescence imaging and croconaine J-aggregates that serve as efficient photothermal converters (emission >1100 nm) and acid-activated photoacoustic probes. The aCD47-CATE platform integrates acid-activated ratiometric photoacoustic imaging with NIR-II fluorescence for accurate tumor targeting and delineation. It effectively blocks CD47 to promote macrophage phagocytosis while exerting mild photothermal effects under NIR-II irradiation to induce immunogenic cell death. This combined action potently remodels the immunosuppressive TME, achieving significant antitumor efficacy. Transcriptomic profiling validated this mechanism, showing enhanced T-cell and macrophage activation alongside suppressed immunosuppressive signals. Collectively, aCD47-CATE represents a robust and multifaceted theranostic platform for image-guided photothermal immunotherapy in HCC.

Accurate and timely assessment of burn depth is critical for determining effective treatment strategies and improving patient outcomes. However, traditional diagnostic methods, such as visual inspection and histological analysis, are constrained by subjectivity, invasiveness, and diagnostic delays. Photoacoustic imaging (PAI), a hybrid modality combining optical contrast with ultrasonic resolution, has emerged as a promising tool for biomedical applications due to its high sensitivity to endogenous chromophores and capability for depth-resolved functional imaging. Although various PAI configurations have been investigated for non-invasive burn assessment, a comprehensive synthesis of this specific application is currently lacking. To address this gap, this review provides a detailed overview of the fundamental principles of PAI, evaluates its distinct advantages in burn depth assessment, and discusses current technological advancements, translational challenges, and future perspectives.

Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by synovial infiltration of polarized M1 macrophages that secrete pro-inflammatory cytokines (TNF-α/IL-1/IL-6) and activate JAK-STAT/NF-κB pathways. These events disrupt the osteoblast-osteoclast balance to induce cartilage degradation and bone erosion. Current disease-modifying antirheumatic drugs (DMARDs), including tofacitinib, show limited efficacy due to systemic toxicity, poor bone-targeting capacity, and inability to restore bone homeostasis. To overcome these limitations, we developed a multifunctional nanoplatform (MBGN-Tofa@PDA-FA) based on magnesium-doped mesoporous bioactive glass nanoparticles (Mg-MBGNs) to codeliver the JAK inhibitor tofacitinib and osteoimmunomodulatory Mg2+/Ca2+ ions, aiming to overcome the severe systemic toxicity of free drugs. This system suppresses inflammation by polarizing macrophages from a pro-inflammatory M1 phenotype to an anti-inflammatory M2 phenotype (M1-to-M2 repolarization), and synergistically promotes osteoblast differentiation. Polydopamine (PDA) coating improves colloidal stability and enables photoacoustic imaging (PAI), while folic acid (FA) modification ensures selective uptake by folate receptor-overexpressing macrophages. By integrating imaging with targeted therapeutic delivery, this platform provides both real-time monitoring and enhanced treatment efficacy. Collectively, our strategy establishes a promising precision theranostic approach for RA by uniting targeted immunomodulation, bone regeneration, and treatment evaluation. Furthermore, in vivo evaluations demonstrated the excellent biodistribution and biosafety profile of this nanoplatform, reinforcing its strong potential for clinical translation.

High quality-factor (High-Q) photoacoustic (PA) resonators are widely recognized for their superior signal enhancement in trace gas sensing; however, their practical deployment is fundamentally limited by extreme sensitivity of the resonance frequency and quality factor to variations in gas composition, gas concentration, and pressure. Existing resonance-tracking strategies typically suffer from either slow response, increased system complexity, or incompatibility with continuous-wave laser excitation, preventing simultaneous high-precision sensing and real-time resonance stabilization. Here, we report a heterodyne photoacoustic (H-PA) excitation framework that enables simultaneous gas concentration measurement and real-time tracking of intrinsic resonance parameters in high-Q PA resonators under rapid acquisition. By exploiting the transient acoustic response induced during fast laser wavelength scanning under off-resonant modulation, the proposed method converts resonance-encoded information into a low-frequency heterodyne signal that can be efficiently demodulated without additional modulation bandwidth or electronic locking circuits. The H-PA framework is theoretically established using a modal transient response model and experimentally validated using a high-Q H-type PA cell operating in the first-order radial mode. Continuous tracking of the resonance frequency and quality factor is demonstrated, with frequency deviations confined within ± 1 Hz and quality factor uncertainties below ± 50. Notably, resonance tracking and gas detection are achieved within a single acquisition cycle of 250 ms, representing a substantial improvement over conventional resonance-profiling techniques. By decoupling resonance tracking from steady-state frequency scanning and electronic locking, the proposed H-PA excitation framework provides a general, fast-response, and low-complexity solution for stabilizing high-Q PA sensors against resonance drift induced by variations in gas composition, gas concentration, and pressure, thereby removing a critical bottleneck for their deployment in real-time, high-precision gas sensing applications.

Integrative multiscale imaging bridges the gap between macroscopic organ structures and microscopic cellular processes, enabling holistic visualization of anatomy and function across scales. Photoacoustic imaging (PAI) leverages melanin's potent contrast for label-free melanoma detection, yet its potential in lung imaging, challenged by air-tissue acoustic impedance mismatch, remains unexplored for melanoma lung metastases (MLMs). We used hierarchical multiscale PAI, transitioning from whole-body macroscale to localized mesoscale and single-cell-resolution microscale. PAI also guided photoablation interventions in the first and second near-infrared windows, requiring only 10.4 pg intracellular melanin/cell. Bioinformatic analysis of human MLM tissues revealed perturbed signaling pathways compared with normal skin and lung tissues, accounting for dysfunctional melanogenesis to enable label-free PAI with high sensitivity and specificity. Malignant MLM lesions in living mice, resected mouse lungs, and human lungs were delineated with margins closely conforming to histology. The high sensitivity allowed visualization of low-cellularity microsatellite foci down to a few tens of cell clusters, with sufficient penetration in the lungs of mice and Bama minipigs. The multiscale imaging methodology streamlines a theranostic workflow and specifically identifies MLM burden in a progressive, label-free manner, which may aid real-time tumor ablation in the future.

Precise diagnosis and treatment of glioblastoma (GBM) remain challenging. The overexpression level of carbonic anhydrase IX (CA IX), a key biomarker for GBM, is correlated with tumor malignancy. Herein, we reported a CA IX-activated nanosensor (MPC@BDPCA NPs) for near-infrared imaging and synergistic phototherapy of orthotopic GBM. The tailor-made core agent, a BODIPY derivative (BDPCA) incorporates a benzenesulfonamide moiety that selectively binds to CA IX, inducing rotational restriction of the probe and resulting in fluorescence turn-on response. Owing to this specific activating mechanism, BDPCA enables a high-contrast fluorescence and photoacoustic dual-modal imaging for quantitative CA IX sensing. Notably, an extended π-conjugation combined with a donor-acceptor molecular design optimizes both radiative and nonradiative decay pathways, affording efficient photothermal conversion and reactive oxygen species generation under 660 nm irradiation. To enhance blood-brain barrier (BBB) penetration in orthotopic GBM models, BDPCA was encapsulated within pH-degradable polymer shell via in situ polymerization, employing 2-methacryloyloxyethyl phosphorylcholine (MPC) as monomer to improve biocompatibility and facilitate receptor-mediated BBB transport. The resulting MPC@BDPCA NPs exhibit selective CA IX sensing, multimodal imaging capability, efficient BBB penetration, and potent synergistic phototherapy. This work highlights a versatile nanoscale sensing and diagnostic platform for precision imaging and therapeutic intervention of GBM.

All-optical ultrasound sensors have recently emerged as promising candidates to replace conventional piezoelectric transducers in photoacoustic imaging, owing to their broad bandwidth, compact active area, and good compatibility with light excitation. While non‑interferometric designs offer advantages in robustness, ease of fabrication, and multiplexing capability, their sensitivity is often limited by short acousto‑optic interaction lengths. Here, we demonstrate that multiple reflection provides an effective strategy to overcome this constraint. The core of our approach is a carefully designed optical cavity that enables the probe beam to undergo multiple round‑trips within a confined region, thereby substantially extending the effective acousto‑optic interaction path. When applied to beam‑deflection ultrasound sensing, a direct side‑by‑side comparison reveals that this design achieves a 3.5‑fold enhancement in sensitivity over conventional single‑pass detection. We further illustrate the utility of this sensitivity‑enhanced all‑optical ultrasound sensor through photoacoustic microscopy of a leaf‑skeleton phantom and in vivo imaging of the vascular network in a mouse ear.

Spectroscopic photoacoustic (sPA) imaging can potentially estimate blood oxygenation saturation (sO2) in vivo noninvasively. However, quantitatively accurate results require accurate optical fluence estimates. Robust modeling in heterogeneous tissue, where light with different wavelengths can experience significantly different absorption and scattering, is difficult. In this work, we developed a deep neural network (Hybrid-Net) for sPA imaging to simultaneously estimate sO2 in blood vessels and segment those vessels from surrounding background tissue. sO2 error was minimized only in blood vessels segmented in Hybrid-Net, resulting in more accurate predictions. Hybrid-Net was first trained on simulated sPA data (at 700 nm and 850 nm) representing initial pressure distributions from three-dimensional Monte Carlo simulations of light transport in breast tissue. Then, for experimental verification, the network was retrained on experimental sPA data (at 700 nm and 850 nm) acquired from simple tissue mimicking phantoms with an embedded blood pool. Quantitative measures were used to evaluate Hybrid-Net performance with an averaged segmentation accuracy of ≥ 0.978 in simulations with varying noise levels (0 dB-35 dB) and 0.999 in the experiment, and an averaged sO2 mean squared error of ≤ 0.048 in simulations with varying noise levels (0 dB-35 dB) and 0.002 in the experiment. Overall, these results show that Hybrid-Net can provide accurate blood oxygenation without estimating the optical fluence, and this study could lead to improvements in sO2 estimation in vivo.

Accurate classification of endometrial pathology is clinically challenging due to the heterogeneous and focal nature of precancerous and malignant lesions. Vascular remodeling is closely linked to tumor progression and may serve as a biomarker for malignancy. We aim to characterize a label-free optical-resolution photoacoustic microscopy (OR-PAM) approach for high-resolution imaging and quantitative characterization and separability assessment of endometrial vasculature. A custom-built OR-PAM system was used to image 34 fresh uterus samples with histologically confirmed diagnoses: normal, benign, endometrial intraepithelial neoplasia (EIN), and endometrial cancer (EC). Thirty-one quantitative vascular features were extracted from structural and spectral analyses of the photoacoustic data, and five statistically significant and minimally correlated features were selected for the separability assessment framework. A pairwise cosine similarity matrix based on these features was computed to construct a weighted similarity network, which was embedded into a two-dimensional (2D) space with a force-directed layout. A logistic regression boundary was applied to the 2D embedding to evaluate separability between normal/benign and EC/EIN clusters. A logistic regression classifier was developed from a cosine similarity matrix and cross-validated using a leave-one-out strategy. The cosine-similarity network graph placed 39 of 40 images on the expected side of the separation boundary. The logistic regression classifier yielded an area under the ROC curve (AUC) of 0.943, demonstrating strong discrimination between normal/benign and EC/EIN groups. OR-PAM combined with imaging feature analysis enables robust differentiation of endometrial pathologies and demonstrates potential as a noninvasive optical biopsy tool for endometrial assessment.

The design of novel aggregation-induced emission (AIE)-active molecules represents a cutting-edge strategy for integrated phototheranostics in the second near-infrared (NIR-II) window. This review systematically outlines rational molecular engineering approaches based on D-A, D-A-D, and A-D-A systems to achieve red-shifted NIR-II absorption/emission, enhanced AIE characteristics, and balanced radiative and non-radiative decay pathways. These AIEgens enable high-contrast NIR-II fluorescence imaging (FLI) and photoacoustic imaging (PAI) for precise tumor localization, while concurrently facilitating efficient photothermal therapy (PTT) and robust photodynamic therapy (PDT) through both type-I and type-II mechanisms. Nanoformulations of these molecules exhibit excellent stability, biocompatibility, and passive targeting via the enhanced permeability and retention (EPR) effect. We further highlight representative "all-in-one" AIE platforms that demonstrate synergistic PTT/PDT under multimodal imaging guidance, offering a promising paradigm for precision cancer theranostics. Challenges and future directions in clinical translation and combination therapy are also discussed.

Photoacoustic (PA) sensing has garnered growing interest as a volumetric optical-acoustic transduction modality that mitigates optical scattering and enables sensitive detection in complex matrices. However, conventional PA assays rely on diffusion-dominated biochemical reaction kinetics and endpoint-based signal acquisition, which limit their capacity for rapid and real-time monitoring. Here, we report a magnetic-actuation-enhanced indirect PA sensing platform that integrates rotating magnetic fields (RMFs) with real-time PA detection to accelerate and continuously monitor operationally homogeneous immunoassays (without separation or washing steps). Functionalized magnetic nanoparticles (MNPs) were actuated by the RMF into dynamic chained or clustered structures, thereby enhancing collision frequency with target analytes and promoting target-induced aggregation. The resultant MNP aggregates caused interparticle light shielding, enhanced light scattering of the particle system, and underwent rapid sedimentation, thereby modulating the PA signal amplitude, which enabled continuous volumetric PA monitoring. Using cardiac troponin I as a clinical target, the platform achieved detection limits of 0.9 pM (22 pg/mL) in buffer and 2 pM (48 pg/mL) in 50% serum, outperforming conventional passive or endpoint assays. Clinical serum validation showed strong concordance with a clinical reference method, underscoring the platform's utility in point-of-care diagnostics.