Photoacoustic Tomography Imaging Research Articles

Investigating the Impact of Chronical Prenatal Alcohol Exposure on Fetal Vascular Development Across Pregnancy Stages Using Photoacoustic Tomography.

Prenatal alcohol exposure (PAE) is a major contributor to fetal alcohol spectrum disorder (FASD), resulting in neurodevelopmental abnormalities. This study utilizes photoacoustic tomography (PAT) to investigate the effects of PAE on fetal brain vasculature in mice. PAT imaging was conducted from embryonic Day 10 (E10) to Day 20 (E20), aimed to compare two alcohol-exposed groups with a control group. Key vascular parameters, including blood vessel diameter and density, and oxygen saturation (sO2), were analyzed. Results show significant reductions in vessel size and density, as well as reduced sO2 levels, in alcohol-exposed groups, especially from E14 onward, compared to controls. These findings underscore the vulnerability of the fetal brain to alcohol exposure during early development and highlight the potential of PAT as a valuable tool for investigating FASD-related vascular changes.

Improving the Theranostic Potential of Magnetic Nanoparticles by Coating with Natural Rubber Latex for Ultrasound, Photoacoustic Imaging, and Magnetic Hyperthermia: An In Vitro Study.

Magnetic nanoparticles (MNPs) have gained attention in theranostics for their ability to combine diagnostic imaging and therapeutic capabilities in a single platform, enhancing targeted treatment and monitoring. Surface coatings are essential for stabilizing MNPs, improving biocompatibility, and preventing oxidation that could compromise their functionality. Natural rubber latex (NRL) offers a promising coating alternative due to its biocompatibility and stability-enhancing properties. While NRL-coated MNPs have shown potential in applications such as magnetic resonance imaging, their effectiveness in theranostics, particularly magnetic hyperthermia (MH) and photoacoustic imaging (PAI), remains underexplored. In this study, iron oxide nanoparticles were synthesized via coprecipitation, using NRL as the coating agent. The samples were labeled by NRL amount used during synthesis: NRL-100 for 100 μL and NRL-400 for 400 μL. Characterization results showed that NRL-100 and NRL-400 samples exhibited improved stability with zeta potentials of -27 mV and -30 mV, respectively and higher saturation magnetization values of 79 emu/g and 88 emu/g of Fe3O4. Building on these findings, we evaluated the performance of these nanoparticles in biomedical applications, including magnetomotive ultrasound (MMUS), PAI, and MH. NRL-100 and NRL-400 samples showed greater displacements and higher contrast in MMUS than uncoated samples (5, 8, and 9 µm) at 0.5 wt%. In addition, NRL-coated samples demonstrated an improved signal-to-noise ratio (SNR) in PAI. SNR values were 24.72 (0.51), 31.44 (0.44), and 33.81 (0.46) dB for the phantoms containing uncoated MNPs, NRL-100, and NRL-400, respectively. Calorimetric measurements for MH confirmed the potential of NRL-coated MNPs as efficient heat-generating agents, showing values of 43 and 40 W/g for NRL-100 and NRL-400, respectively. Overall, NRL-coated MNPs showed great promise as contrast agents in MMUS and PAI imaging, as well as in MH applications.

Cross-sectional imaging of speed-of-sound distribution using photoacoustic reversal beacons

Photoacoustic tomography (PAT) enables non-invasive cross-sectional imaging of biological tissues, but it fails to map the spatial variation of speed-of-sound (SOS) within tissues. While SOS is intimately linked to density and elastic modulus of tissues, the imaging of SOS distribution serves as a complementary imaging modality to PAT. Moreover, an accurate SOS map can be leveraged to correct for PAT image degradation arising from acoustic heterogeneities. Herein, we propose a method for SOS imaging using scanned photoacoustic beacons excited by short laser pulse with inversion reconstruction. Our method is based on photoacoustic reversal beacons (PRBs), which are small light-absorbing targets with strong photoacoustic contrast. We excite and scan a number of PRBs positioned at the periphery of the target, and the generated photoacoustic waves propagate through the target from various directions, thereby achieve spatial sampling of the internal SOS. By picking up the PRB signal using a graph-based dynamic programing algorithm, we formulate a linear inverse model for pixel-wise SOS reconstruction and solve it with iterative optimization technique. We validate the feasibility of the proposed method through simulations, phantoms, and ex vivo biological tissue tests. Experimental results demonstrate that our approach can achieve accurate reconstruction of SOS distribution. Leveraging the obtained SOS map, we further demonstrate significantly enhanced PAT image reconstruction with acoustic correction.

3-D Visualization of Atlantic salmon skin through Ultrasound and Photoacoustic Microscopy.

Three-dimensional photoacoustic imaging (PAM) has emerged as a promising technique for non-invasive label-free visualization and characterization of biological tissues with high spatial resolution and functional contrast. The application of PAM and ultrasound as a microscopy technique of study for Atlantic salmon skin is presented here. A custom ultrasound and photoacoustic experimental setup was used for conducting this experiment with a sample preparation method where the salmon skin is embedded in agarose and lifted from the bottom of the petridish. The results of C-scan, B-scan, and overlayed images of ultrasound and photoacoustic are presented. The results are then analyzed for understanding the pigment map and its relation to salmon behavior to external stimuli. The photoacoustic images are compared with the optical images and analyzed further. A custom colormap and alpha map is designed and the matrices responsible for PAM and ultrasound are inserted together to overlay the ultrasound image and PAM image on top of each other. In this study, we propose an approach that combines scanning acoustic microscopy (SAM) images with PAM images for providing a comprehensive understanding of the salmon skin tissue. Overlaying acoustic and photoacoustic images enabled unique visualization of tissue morphology, with respect to identification of structural features in the context of their pigment distribution.

JQR-Net: joint quantitative reconstruction network for dual-modal photoacoustic and optical coherence tomography imaging.

Photoacoustic (PA) and optical coherence tomography (OCT) imaging are complementary imaging modalities with distinct contrast mechanisms, penetration depths, and spatial resolutions. Integrating these two modalities into a dual-modal PA-OCT imaging system enables the simultaneous acquisition of multimodal signals within a single scan. This integration supports quantitative reconstruction of tissue characteristics, offering a more precise and comprehensive analysis than single-modal imaging. In this paper, we propose a deep learning approach for joint quantitative reconstruction in dual-modal PA-OCT imaging, potentially advancing imaging capabilities for detailed tissue examination and disease analysis. We develop a deep neural network that performs end-to-end mapping from photoacoustically induced pressure signals and backscattered OCT signals to parametric images representing the spatial distribution of optical absorption and attenuation coefficients. This network provides both morphological and functional insights. To the best of our knowledge, this is the first deep learning model designed to simultaneously reconstruct multiple tissue characteristic parameters from dual-modal imaging signals, facilitating in-depth tissue characterization.

In vivo assessment of cardiac radiofrequency ablation in a large-animal model using photoacoustic-ultrasound imaging.

One of the fundamental unmet clinical needs within cardiac electrophysiology is intraoperative assessment of catheter ablation, which can lead to recurrent arrhythmias and subsequent complications if ineffective. This work demonstrates photoacoustic imaging (PAI) of radiofrequency ablation (RFA) lesions in an in vivo swine model (n=3). Spectral unmixing of PAI data provides local myocardial characterization (e.g., oxygen saturation & tissue ablation) by overlaying unmixed PAI images with B-mode ultrasound imaging (PAI/US), with the latter providing anatomical context. Based on stained gross pathology, areas of central tissue necrosis coincided with increases in unmixed ablated regions of the myocardium. An average contrast-to-noise ratio of 2.8±0.2 confirmed lesion detectability, while the lesion dimensions quantified from PAI and pathology did not present significant differences. In vivo PAI of RFA lesions to determine ablation characteristics could lead to a paradigm shift in catheter ablation assessment and improve clinical outcomes.

Unsupervised adversarial neural network for enhancing vasculature in photoacoustic tomography images using optical coherence tomography angiography

Photoacoustic tomography (PAT) is a powerful imaging modality for visualizing tissue physiology and exogenous contrast agents. However, PAT faces challenges in visualizing deep-seated vascular structures due to light scattering, absorption, and reduced signal intensity with depth. Optical coherence tomography angiography (OCTA) offers high-contrast visualization of vasculature networks, yet its imaging depth is limited to a millimeter scale. Herein, we propose OCPA-Net, a novel unsupervised deep learning method that utilizes the rich vascular feature of OCTA to enhance PAT images. Trained on unpaired OCTA and PAT images, OCPA-Net incorporates a vessel-aware attention module to enhance deep-seated vessel details captured from OCTA. It leverages a domain-adversarial loss function to enforce structural consistency and a novel identity invariant loss to mitigate excessive image content generation. We validate the structural fidelity of OCPA-Net on simulation experiments, and then demonstrate its vascular enhancement performance on in vivo imaging experiments of tumor-bearing mice and contrast-enhanced pregnant mice. The results show the promise of our method for comprehensive vessel-related image analysis in preclinical research applications.

Quantitative evaluation of lower limb varicose veins using photoacoustic imaging

PurposeVaricose veins in the lower extremities are dilated subcutaneous varicose veins with a diameter of ≥ 3 mm, caused by increased venous pressure resulting from backflow of blood due to venous valve insufficiency (Gloviczki in Handbook of venous disorders: guidelines of the American venous forum, Hodder Arnold, London, 2009). When diagnosing varicose veins, the shape and thickness of the blood vessels should be accurately visualized in three dimensions. In this study, we investigated a new method for numerical evaluation of vascular morphology related to varicose veins in the lower extremities, using a photoacoustic imaging (PAI) system, which can acquire high-resolution and three-dimensional images noninvasively.MethodsNine patients with varicose veins participated in the study, and their images were captured using an optical camera and PAI system. We visualized the vascular structure, created a blood presence density (BPD) heat map, and examined the correlation between BPD and location of varicose veins.ResultsThe obtained photoacoustic (PA) images demonstrated the ability of this method to visualize vessels ranging from as small as 0.2 mm in diameter to large, dilated vessels in three dimensions. Furthermore, the study revealed a correlation between the high-density part of the BPD heat map generated from the PAI images and the presence of varicose veins.ConclusionPAI is a promising technique for noninvasive and accurate diagnosis of varicose veins in the lower extremities. By providing valuable information on the morphology and hemodynamics of the varicose veins, PAI may facilitate their early detection and treatment.

Xanthene-Based Dyes for Photoacoustic Imaging and their Use as Analyte-Responsive Probes.

Developing imaging tools that can report on the presence of disease-relevant analytes in multicellular organisms can provide insight into fundamental disease mechanisms as well as provide diagnostic tools for the clinic. Photoacoustic imaging (PAI) is a light-in, sound-out imaging technique that allows for high resolution, deep-tissue imaging with applications in pre-clinical and point-of-care settings. The continued development of near-infrared (NIR) absorbing small-molecule dyes promises to improve the capabilities of this emerging imaging modality. For example, new dye scaffolds bearing chemoselective functionalities are enabling the detection and quantification of disease-relevant analytes through activity-based sensing (ABS) approaches. Recently described strategies to engineer NIR absorbing xanthenes have enabled development of analyte-responsive PAI probes using this classic dye scaffold. Herein, we present current strategies for red-shifting the spectral properties of xanthenes via bridging heteroatom or auxochrome modifications. Additionally, we explore how these strategies, coupled with chemoselective spiroring-opening approaches, have been employed to create ABS probes for in vivo detection of hypochlorous acid, nitric oxide, copper (II), human NAD(P)H: quinone oxidoreductase isozyme 1, and carbon monoxide. Given the versatility of the xanthene scaffold, we anticipate continued growth and development of analyte-responsive PAI imaging probes based on this dye class.

Glutathione-activated biotin-targeted dual-modal imaging probe with improved PDT/PTT synergistic therapy

BackgroundGlutathione (GSH), a highly abundant thiol compound within cells, plays a critical role in physiological processes and exhibits close correlation with cancer. Among molecular imaging technologies, most probes have relatively short emission wavelengths and lack photoacoustic imaging (PA) capability, resulting in the inability to obtain tissue images with high penetration depth. The presence of GSH in the tumor microenvironment neutralizes ROS, diminishing the therapeutic effect of PDT, thus resulting in often unsatisfactory therapeutic efficacy. Therefore, it is imperative to develop a dual-modal probe for the detection of GSH and the diagnosis and treatment of cancer. ResultsIn this study, we synthesized a novel dual-modal probe, Cy-Bio-GSH, utilizing near-infrared fluorescence (NIRF) and photoacoustic (PA) imaging techniques for GSH detection. The probe integrates cyanine dye as the fluorophore, nitroazobenzene as the recognition moiety, and biotin as the tumor-targeting moiety. Upon reacting with GSH, the probe emits NIR fluorescence at 820 nm and generates a PA signal. Significantly, this reaction activates the photodynamic and photothermal properties of the probe. By depleting GSH and employing a synergistic photothermal therapy (PTT) treatment, the therapeutic efficacy of photodynamic therapy (PDT) is remarkably enhanced. In-vivo experiments confirm the capability of the probe to detect GSH via NIRF and PA imaging. Notably, the combined tumor-targeting ability and PDT/PTT synergistic therapy enhance therapeutic outcomes for tumors and facilitate their ablation. SignificanceA novel tumor-targeting and dual-modal imaging probe (Cy-Bio-GSH) is synthesized, exhibiting remarkable sensitivity and selectivity to GSH, enabling the visualization of GSH in cells and the differentiation between normal and cancer cells. Cy-Bio-GSH enhances PDT/PTT with effective killing of cancer cells and makes the ablation of tumors in mice. This work represents the first tumor-targeting probe for GSH detection, and provides crucial tool for cancer diagnosis and treatment by dual-modal imaging with improved PDT/PTT synergistic therapy.

Score-based generative model-assisted information compensation for high-quality limited-view reconstruction in photoacoustic tomography

Photoacoustic tomography (PAT) regularly operates in limited-view cases owing to data acquisition limitations. The results using traditional methods in limited-view PAT exhibit distortions and numerous artifacts. Here, a novel limited-view PAT reconstruction strategy that combines model-based iteration with score-based generative model was proposed. By incrementally adding noise to the training samples, prior knowledge can be learned from the complex probability distribution. The acquired prior is then utilized as constraint in model-based iteration. The information of missing views can be gradually compensated by cyclic iteration to achieve high-quality reconstruction. The performance of the proposed method was evaluated with the circular phantom and in vivo experimental data. Experimental results demonstrate the outstanding effectiveness of the proposed method in limited-view cases. Notably, the proposed method exhibits excellent performance in limited-view case of 70° compared with traditional method. It achieves a remarkable improvement of 203% in PSNR and 48% in SSIM for the circular phantom experimental data, and an enhancement of 81% in PSNR and 65% in SSIM for in vivo experimental data, respectively. The proposed method has capability of reconstructing PAT images in extremely limited-view cases, which will further expand the application in clinical scenarios.

An Indocyanine Green-Based Nanoprobe for In Vivo Detection of Cellular Senescence.

There is an urgent need to improve conventional cancer-treatments by preventing detrimental side effects, cancer recurrence and metastases. Recent studies have shown that presence of senescent cells in tissues treated with chemo- or radiotherapy can be used to predict the effectiveness of cancer treatment. However, although the accumulation of senescent cells is one of the hallmarks of cancer, surprisingly little progress has been made in development of strategies for their detection in vivo. To address a lack of detection tools, we developed a biocompatible, injectable organic nanoprobe (NanoJagg), which is selectively taken up by senescent cells and accumulates in the lysosomes. The NanoJagg probe is obtained by self-assembly of indocyanine green (ICG) dimers using a scalable manufacturing process and characterized by a unique spectral signature suitable for both photoacoustic tomography (PAT) and fluorescence imaging. In vitro, ex vivo and in vivo studies all indicate that NanoJaggs are a clinically translatable probe for detection of senescence and their PAT signal makes them suitable for longitudinal monitoring of the senescence burden in solid tumors after chemotherapy or radiotherapy.

An Indocyanine Green‐Based Nanoprobe for In Vivo Detection of Cellular Senescence

AbstractThere is an urgent need to improve conventional cancer‐treatments by preventing detrimental side effects, cancer recurrence and metastases. Recent studies have shown that presence of senescent cells in tissues treated with chemo‐ or radiotherapy can be used to predict the effectiveness of cancer treatment. However, although the accumulation of senescent cells is one of the hallmarks of cancer, surprisingly little progress has been made in development of strategies for their detection in vivo. To address a lack of detection tools, we developed a biocompatible, injectable organic nanoprobe (NanoJagg), which is selectively taken up by senescent cells and accumulates in the lysosomes. The NanoJagg probe is obtained by self‐assembly of indocyanine green (ICG) dimers using a scalable manufacturing process and characterized by a unique spectral signature suitable for both photoacoustic tomography (PAT) and fluorescence imaging. In vitro, ex vivo and in vivo studies all indicate that NanoJaggs are a clinically translatable probe for detection of senescence and their PAT signal makes them suitable for longitudinal monitoring of the senescence burden in solid tumors after chemotherapy or radiotherapy.

Skin Imaging Using Optical Coherence Tomography and Photoacoustic Imaging: A Mini-Review

This article provides an overview of the progress made in skin imaging using two emerging imaging modalities, optical coherence tomography (OCT) and photoacoustic imaging (PAI). Over recent years, these technologies have significantly advanced our understanding of skin structure and function, offering non-invasive and high-resolution insights previously unattainable. The review begins by briefly describing the fundamental principles of how OCT and PAI capture images. It then explores the evolving applications of OCT in dermatology, ranging from diagnosing skin disorders to monitoring treatment responses. This article continues by briefly describing the capabilities of PAI imaging, and how PAI has been used for melanoma and non-melanoma skin cancer detection and characterization, vascular imaging, and more. The third section describes the development of multimodal skin imaging systems that include OCT, PAI, or both modes. A comparative analysis between OCT and PAI is presented, elucidating their respective strengths, limitations, and synergies in the context of skin imaging.

Deep learning acceleration of iterative model-based light fluence correction for photoacoustic tomography

Photoacoustic tomography (PAT) is a promising imaging technique that can visualize the distribution of chromophores within biological tissue. However, the accuracy of PAT imaging is compromised by light fluence (LF), which hinders the quantification of light absorbers. Currently, model-based iterative methods are used for LF correction, but they require extensive computational resources due to repeated LF estimation based on differential light transport models. To improve LF correction efficiency, we propose to use Fourier neural operator (FNO), a neural network specially designed for estimating partial differential equations, to learn the forward projection of light transport in PAT. Trained using paired finite-element-based LF simulation data, our FNO model replaces the traditional computational heavy LF estimator during iterative correction, such that the correction procedure is considerably accelerated. Simulation and experimental results demonstrate that our method achieves comparable LF correction quality to traditional iterative methods while reducing the correction time by over 30 times.

Correlation between oxygenation status of extra-synovial tissue of wrist and disease activity in rheumatoid arthritis: a photoacoustic imaging study.

Rheumatoid arthritis (RA) is characterized by hypoxia in the synovial tissue. While photoacoustic imaging (PA) offers a method to evaluate tissue oxygenation in RA patients, studies exploring the link between extra-synovial tissue of wrist oxygenation and disease activity remain scarce. We aimed to assess synovial oxygenation in RA patients using a multimodal photoacoustic-ultrasound (PA/US) imaging system and establish its correlation with disease activity. A retrospective study was conducted on 111 patients with RA and 72 healthy controls from 2022 to 2023. Dual-wavelength PA imaging quantified oxygen saturation (So2) levels in the synovial membrane and peri-wrist region. Oxygenation states were categorised as hyperoxia, intermediate oxygenation, and hypoxia based on So2 values. The association between oxygenation levels and the clinical disease activity index was evaluated using a one-way analysis of variance, complemented by the Kruskal-Wallis test with Bonferroni adjustment. Of the patients with RA, 39 exhibited hyperoxia, 24 had intermediate oxygenation, and 48 had hypoxia in the wrist extra-synovial tissue. All of the control participants exhibited the hyperoxia status. Oxygenation levels in patients with RA correlated with clinical metrics. Patients with intermediate oxygenation had a lower disease activity index compared with those with hypoxia and hyperoxia. A significant correlation exists between wrist extra-synovial tissue oxygenation and disease activity in patients with RA.

Automated three-dimensional image registration for longitudinal photoacoustic imaging.

Photoacoustic tomography (PAT) has great potential in monitoring disease progression and treatment response in breast cancer. However, due to variations in breast repositioning, there is a chance of geometric misalignment between images. Further, poor repositioning can affect light fluence distribution and imaging field-of-view, making images different from one another. The net effect is that it becomes challenging to distinguish between image changes due to repositioning effects and those due to true biological variations. The aim is to develop a three-dimensional image registration framework for geometrically aligning repeated PAT volumetric images, which are potentially affected by repositioning effects such as misalignment, changed radiant exposure conditions, and different fields-of-view. The proposed framework involves the use of a coordinate-based neural network to represent the displacement field between pairs of PAT volumetric images. A loss function based on normalized cross correlation and Frangi vesselness feature extraction at multiple scales was implemented. We refer to our image registration framework as MUVINN-reg, which stands for multiscale vesselness-based image registration using neural networks. The approach was tested on a longitudinal dataset of healthy volunteer breast PAT images acquired with the hybrid photoacoustic-ultrasound Photoacoustic Mammoscope 3 imaging system. The registration performance was also tested under unfavorable repositioning conditions such as intentional mispositioning, and variation in breast-supporting cup size between measurements. A total of 13 pairs of repeated PAT scans were included in this study. MUVINN-reg showed excellent performance in co-registering each pair of images. The proposed framework was shown to be robust to image intensity shifts and field-of-view changes. Furthermore, MUVINN-reg could align vessels at imaging depths greater than 4cm. The proposed framework will enable the use of PAT for quantitative and reproducible monitoring of disease progression and treatment response.

PreFlap: From Photoacoustic Tomography Images to Vascular Mapping Sheets for Improved Preoperative Flap Evaluation.

Advancements in technology have improved image acquisition and processing in the field of medical imaging, giving medical doctors the tools to implement effective medical care. In plastic surgery, despite advances in anatomical knowledge and technology, problems in preoperative planning for flap surgery remain. In this study, we propose a new protocol to analyze three-dimensional (3D) Photoacoustic tomography images and generate two-dimensional (2D) mapping sheets that can help surgeons identify perforators and the perfusion territory during preoperative planning. The core of this protocol is PreFlap, a new algorithm that converts 3D photoacoustic tomography images into 2D vascular mapping images. Experimental results demonstrate that PreFlap can improve preoperative flap evaluation, thus can greatly saving surgeons' time and improving surgical outcomes.

Unsupervised Fusion of Misaligned PAT and MRI Images via Mutually Reinforcing Cross-Modality Image Generation and Registration.

Photoacoustic tomography (PAT) and magnetic resonance imaging (MRI) are two advanced imaging techniques widely used in pre-clinical research. PAT has high optical contrast and deep imaging range but poor soft tissue contrast, whereas MRI provides excellent soft tissue information but poor temporal resolution. Despite recent advances in medical image fusion with pre-aligned multimodal data, PAT-MRI image fusion remains challenging due to misaligned images and spatial distortion. To address these issues, we propose an unsupervised multi-stage deep learning framework called PAMRFuse for misaligned PAT and MRI image fusion. PAMRFuse comprises a multimodal to unimodal registration network to accurately align the input PAT-MRI image pairs and a self-attentive fusion network that selects information-rich features for fusion. We employ an end-to-end mutually reinforcing mode in our registration network, which enables joint optimization of cross-modality image generation and registration. To the best of our knowledge, this is the first attempt at information fusion for misaligned PAT and MRI. Qualitative and quantitative experimental results show the excellent performance of our method in fusing PAT-MRI images of small animals captured from commercial imaging systems.

A photoacoustic tomography image reconstruction method based on forward imaging model

A photoacoustic tomography image reconstruction method based on forward imaging model