Photoacoustic tomography and sensing in biomedicine

SKYQUANT 3D: Quantifying Vascular Anatomy With an Open-Source Workflow for Comprehensive Analysis of Volumetric Optoacoustic Angiography Data

Efficient visualization of the vascular system is of key importance in biomedical research into tumor angiogenesis, cerebrovascular alterations, and other angiopathies. Optoacoustic (OA) angiography offers a promising solution combining molecular optical contrast with high resolution and deep penetration of ultrasound. However, its hybrid nature implies complex data collection and processing workflows, with significant variability in methodologies across developers and users. To streamline interoperability, we introduce SKYQUANT 3D, a Python-based set of instructions for the Thermo Fisher Scientific Amira/Avizo 3D Visualization & Analysis Software. Our workflow simplifies the batch processing of volumetric optoacoustic angiography images, extracting meaningful quantitative information while also providing statistical analysis and graphical representation of the results. Quantification performance of SKYQUANT 3D is demonstrated using functional preclinical and clinical in vivo 3D OA angiographic tests involving ambient temperature variations and repositioning of the imaged limb.

Removing Artifacts in Transcranial Photoacoustic Imaging With Polarized Self-Attention Dense-UNet

OBJECTIVE

Photoacoustic imaging (PAI) is a promising transcranial imaging technique. However, the distortion of photoacoustic signals induced by the skull significantly influences its imaging quality. We aimed to use deep learning for removing artifacts in PAI.

METHODS

In this study, we propose a polarized self-attention dense U-Net, termed PSAD-UNet, to correct the distortion and accurately recover imaged objects beneath bone plates. To evaluate the performance of the proposed method, a series of experiments was performed using a custom-built PAI system.

RESULTS

The experimental results showed that the proposed PSAD-UNet method could effectively implement transcranial PAI through a one- or two-layer bone plate. Compared with the conventional delay-and-sum and classical U-Net methods, PSAD-UNet can diminish the influence of bone plates and provide high-quality PAI results in terms of structural similarity and peak signal-to-noise ratio. The 3-D experimental results further confirm the feasibility of PSAD-UNet in 3-D transcranial imaging.

CONCLUSION

PSAD-UNet paves the way for implementing transcranial PAI with high imaging accuracy, which reveals broad application prospects in preclinical and clinical fields.

Reconstructing Cancellous Bone From Down-Sampled Optical-Resolution Photoacoustic Microscopy Images With Deep Learning

OBJECTIVE

Bone diseases deteriorate the microstructure of bone tissue. Optical-resolution photoacoustic microscopy (OR-PAM) enables high spatial resolution of imaging bone tissues. However, the spatiotemporal trade-off limits the application of OR-PAM. The purpose of this study was to improve the quality of OR-PAM images without sacrificing temporal resolution.

METHODS

In this study, we proposed the Photoacoustic Dense Attention U-Net (PADA U-Net) model, which was used for reconstructing full-scanning images from under-sampled images. Thereby, this approach breaks the trade-off between imaging speed and spatial resolution.

RESULTS

The proposed method was validated on resolution test targets and bovine cancellous bone samples to demonstrate the capability of PADA U-Net in recovering full-scanning images from under-sampled OR-PAM images. With a down-sampling ratio of [4, 1], compared to bilinear interpolation, the Peak Signal-to-Noise Ratio and Structural Similarity Index Measure values (averaged over the test set of bovine cancellous bone) of the PADA U-Net were improved by 2.325 dB and 0.117, respectively.

CONCLUSION

The results demonstrate that the PADA U-Net model reconstructed the OR-PAM images well with different levels of sparsity. Our proposed method can further facilitate early diagnosis and treatment of bone diseases using OR-PAM.

Recent Advances in Photoacoustic Imaging: Current Status and Future Perspectives

Photoacoustic imaging (PAI) is an emerging hybrid imaging modality that combines high-contrast optical imaging with high-spatial-resolution ultrasound imaging. PAI can provide a high spatial resolution and significant imaging depth by utilizing the distinctive spectroscopic characteristics of tissue, which gives it a wide variety of applications in biomedicine and preclinical research. In addition, it is non-ionizing and non-invasive, and photoacoustic (PA) signals are generated by a short-pulse laser under thermal expansion. In this study, we describe the basic principles of PAI, recent advances in research in human and animal tissues, and future perspectives.

Advances in Noninvasive Molecular Imaging Probes for Liver Fibrosis Diagnosis

Liver fibrosis is a wound-healing response to chronic liver injury, which may lead to cirrhosis and cancer. Early-stage fibrosis is reversible, and it is difficult to precisely diagnose with conventional imaging modalities such as magnetic resonance imaging, positron emission tomography, single-photon emission computed tomography, and ultrasound imaging. In contrast, probe-assisted molecular imaging offers a promising noninvasive approach to visualize early fibrosis changes in vivo, thus facilitating early diagnosis and staging liver fibrosis, and even monitoring of the treatment response. Here, the most recent progress in molecular imaging technologies for liver fibrosis is updated. We start by illustrating pathogenesis for liver fibrosis, which includes capillarization of liver sinusoidal endothelial cells, cellular and molecular processes involved in inflammation and fibrogenesis, as well as processes of collagen synthesis, oxidation, and cross-linking. Furthermore, the biological targets used in molecular imaging of liver fibrosis are summarized, which are composed of receptors on hepatic stellate cells, macrophages, and even liver collagen. Notably, the focus is on insights into the advances in imaging modalities developed for liver fibrosis diagnosis and the update in the corresponding contrast agents. In addition, challenges and opportunities for future research and clinical translation of the molecular imaging modalities and the contrast agents are pointed out. We hope that this review would serve as a guide for scientists and students who are interested in liver fibrosis imaging and treatment, and as well expedite the translation of molecular imaging technologies from bench to bedside.

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

Significance

Photoacoustic computed tomography (PACT) is a promising non-invasive imaging technique for both life science and clinical implementations. To achieve fast imaging speed, modern PACT systems have equipped arrays that have hundreds to thousands of ultrasound transducer (UST) elements, and the element number continues to increase. However, large number of UST elements with parallel data acquisition could generate a massive data size, making it very challenging to realize fast image reconstruction. Although several research groups have developed GPU-accelerated method for PACT, there lacks an explicit and feasible step-by-step description of GPU-based algorithms for various hardware platforms.

Aim

In this study, we propose a comprehensive framework for developing GPU-accelerated PACT image reconstruction (GPU-accelerated photoacoustic computed tomography), to help the research community to grasp this advanced image reconstruction method.

Approach

We leverage widely accessible open-source parallel computing tools, including Python multiprocessing-based parallelism, Taichi Lang for Python, CUDA, and possible other backends. We demonstrate that our framework promotes significant performance of PACT reconstruction, enabling faster analysis and real-time applications. Besides, we also described how to realize parallel computing on various hardware configurations, including multicore CPU, single GPU, and multiple GPUs platform.

Results

Notably, our framework can achieve an effective rate of ∼ 871 times when reconstructing extremely large-scale three-dimensional PACT images on a dual-GPU platform compared to a 24-core workstation CPU. In this paper, we share example codes via GitHub.

Conclusions

Our approach allows for easy adoption and adaptation by the research community, fostering implementations of PACT for both life science and medicine.

Statistical estimation theory detection limits for label-free imaging

Significance

The emergence of label-free microscopy techniques has significantly improved our ability to precisely characterize biochemical targets, enabling non-invasive visualization of cellular organelles and tissue organization. However, understanding each label-free method with respect to the specific benefits, drawbacks, and varied sensitivities under measurement conditions across different types of specimens remains a challenge.

Aim

We link all of these disparate label-free optical interactions together and compare the detection sensitivity within the framework of statistical estimation theory.

Approach

To achieve this goal, we introduce a comprehensive unified framework for evaluating the bounds for signal detection with label-free microscopy methods, including second-harmonic generation, third-harmonic generation, coherent anti-Stokes Raman scattering, coherent Stokes Raman scattering, stimulated Raman loss, stimulated Raman gain, stimulated emission, impulsive stimulated Raman scattering, transient absorption, and photothermal effect. A general model for signal generation induced by optical scattering is developed.

Results

Based on this model, the information obtained is quantitatively analyzed using Fisher information, and the fundamental constraints on estimation precision are evaluated through the Cramér-Rao lower bound, offering guidance for optimal experimental design and interpretation.

Conclusions

We provide valuable insights for researchers seeking to leverage label-free techniques for non-invasive imaging applications for biomedical research and clinical practice.

Compressed Sensing for Biomedical Photoacoustic Imaging: A Review

Photoacoustic imaging (PAI) is a rapidly developing emerging non-invasive biomedical imaging technique that combines the strong contrast from optical absorption imaging and the high resolution from acoustic imaging. Abnormal biological tissues (such as tumors and inflammation) generate different levels of thermal expansion after absorbing optical energy, producing distinct acoustic signals from normal tissues. This technique can detect small tissue lesions in biological tissues and has demonstrated significant potential for applications in tumor research, melanoma detection, and cardiovascular disease diagnosis. During the process of collecting photoacoustic signals in a PAI system, various factors can influence the signals, such as absorption, scattering, and attenuation in biological tissues. A single ultrasound transducer cannot provide sufficient information to reconstruct high-precision photoacoustic images. To obtain more accurate and clear image reconstruction results, PAI systems typically use a large number of ultrasound transducers to collect multi-channel signals from different angles and positions, thereby acquiring more information about the photoacoustic signals. Therefore, to reconstruct high-quality photoacoustic images, PAI systems require a significant number of measurement signals, which can result in substantial hardware and time costs. Compressed sensing is an algorithm that breaks through the Nyquist sampling theorem and can reconstruct the original signal with a small number of measurement signals. PAI based on compressed sensing has made breakthroughs over the past decade, enabling the reconstruction of low artifacts and high-quality images with a small number of photoacoustic measurement signals, improving time efficiency, and reducing hardware costs. This article provides a detailed introduction to PAI based on compressed sensing, such as the physical transmission model-based compressed sensing method, two-stage reconstruction-based compressed sensing method, and single-pixel camera-based compressed sensing method. Challenges and future perspectives of compressed sensing-based PAI are also discussed.

Adaptation of a Clinical High-Frequency Transrectal Ultrasound System for Prostate Photoacoustic Imaging: Implementation and Pre-clinical Demonstration

OBJECTIVE

High-frequency, high-resolution transrectal micro-ultrasound (micro-US: ≥15 MHz) imaging of the prostate is emerging as a beneficial tool for scoring disease risk and accurately targeting biopsies. Adding photoacoustic (PA) imaging to visualize abnormal vascularization and accumulation of contrast agents in tumors has potential for guiding focal therapies. In this work, we describe a new imaging platform that combines a transrectal micro-US system with transurethral light delivery for PA imaging.

METHODS

A clinical transrectal micro-US system was adapted to acquire PA images synchronous to a tunable laser pulse. A transurethral side-firing optical fiber was developed for light delivery. A polyvinyl chloride (PVC)-plastisol phantom was developed and characterized to image PA contrast agents in wall-less channels. After resolution measurement in water, PA imaging was demonstrated in phantom channels with dyes and biodegradable nanoparticle contrast agents called porphysomes. In vivo imaging of a tumor model was performed, with porphysomes administered intravenously.

RESULTS

Photoacoustic imaging data were acquired at 5 Hz, and image reconstruction was performed offline. PA image resolution at a 14-mm depth was 74 and 261 μm in the axial and lateral directions, respectively. The speed of sound in PVC-plastisol was 1383 m/s, and the attenuation was 4 dB/mm at 20 MHz. PA signal from porphysomes was spectrally unmixed from blood signals in the tumor, and a signal increase was observed 3 h after porphysome injection.

CONCLUSION

A combined transrectal micro-US and PA imaging system was developed and characterized, and in vivo imaging demonstrated. High-resolution PA imaging may provide valuable additional information for diagnostic and therapeutic applications in the prostate.

Real-time dual-modal photoacoustic and fluorescence small animal imaging

By combining optical absorption contrast and acoustic resolution, photoacoustic imaging (PAI) has broken the barrier in depth for high-resolution optical imaging. Meanwhile, Fluorescence imaging (FLI), owing to advantages of high sensitivity and high specificity with abundant fluorescence agents and proteins, has always been playing a key role in live animal studies. Based on different optical contrast mechanisms, PAI and FLI can provide important complementary information to each other. In this work, we uniquely designed a Photoacoustic-Fluorescence (PA-FL) imaging system that provides real-time dual modality imaging, in which a half-ring ultrasonic array is employed for high quality PA tomography and a specially designed optical window allows simultaneous whole-body fluorescence imaging. The performance of this dual modality system was demonstrated in live animal studies, including real-time monitoring of perfusion and metabolic processes of fluorescent dyes. Our study indicates that the PA-FL imaging system has unique potential for live small animal research.

Single-stage approach for estimating optical parameters in spectral quantitative photoacoustic tomography

In quantitative photoacoustic tomography, the optical parameters of a target, most importantly the concentrations of chromophores such as deoxygenated and oxygenated hemoglobin, are estimated from photoacoustic data measured on the boundary of the target. In this work, a numerical approximation of a forward model for spectral quantitative photoacoustic tomography is constructed by utilizing the diffusion approximation for light propagation, the acoustic wave equation for ultrasound propagation, and spectral models of optical absorption and scattering to describe the wavelength dependence of the optical parameters. The related inverse problem is approached in the framework of Bayesian inverse problems. Concentrations of four chromophores (deoxygenated and oxygenated hemoglobin, water, and lipid), two scattering parameters (reference scattering and scattering power), and the Grüneisen parameter are estimated in a single-stage from photoacoustic data. The methodology is evaluated using numerical simulations in different full-view and limited-view imaging settings. The results show that, utilizing spectral data and models, the spectral optical parameters and the Grüneisen parameter can be simultaneously estimated. Furthermore, the approach can also be utilized in limited-view imaging situations.

Quantitative photoacoustic tomography: modeling and inverse problems

Significance

Quantitative photoacoustic tomography (QPAT) exploits the photoacoustic effect with the aim of estimating images of clinically relevant quantities related to the tissue's optical absorption. The technique has two aspects: an acoustic part, where the initial acoustic pressure distribution is estimated from measured photoacoustic time-series, and an optical part, where the distributions of the optical parameters are estimated from the initial pressure.

Aim

Our study is focused on the optical part. In particular, computational modeling of light propagation (forward problem) and numerical solution methodologies of the image reconstruction (inverse problem) are discussed.

Approach

The commonly used mathematical models of how light and sound propagate in biological tissue are reviewed. A short overview of how the acoustic inverse problem is usually treated is given. The optical inverse problem and methods for its solution are reviewed. In addition, some limitations of real-life measurements and their effect on the inverse problems are discussed.

Results

An overview of QPAT with a focus on the optical part was given. Computational modeling and inverse problems of QPAT were addressed, and some key challenges were discussed. Furthermore, the developments for tackling these problems were reviewed. Although modeling of light transport is well-understood and there is a well-developed framework of inverse mathematics for approaching the inverse problem of QPAT, there are still challenges in taking these methodologies to practice.

Conclusions

Modeling and inverse problems of QPAT together were discussed. The scope was limited to the optical part, and the acoustic aspects were discussed only to the extent that they relate to the optical aspect.

Review of low-cost light sources and miniaturized designs in photoacoustic microscopy

Significance

Photoacoustic microscopy (PAM) is a promising imaging technique to provide structural, functional, and molecular information for preclinical and clinical studies. However, expensive and bulky lasers and motorized stages have limited the broad applications of conventional PAM systems. A recent trend is to use low-cost light sources and miniaturized designs to develop a compact PAM system and expand its applications from benchtop to bedside.

Aim

We provide (1) an overview of PAM systems and their limitations, (2) a comprehensive review of PAM systems with low-cost light sources and their applications, (3) a comprehensive review of PAM systems with miniaturized and handheld scanning designs, and (4) perspective applications and a summary of the cost-effective and miniaturized PAM systems.

Approach

Papers published before July 2023 in the area of using low-cost light sources and miniaturized designs in PAM were reviewed. They were categorized into two main parts: (1) low-cost light sources and (2) miniaturized or handheld designs. The first part was classified into two subtypes: pulsed laser diode and continuous-wave laser diode. The second part was also classified into two subtypes: galvanometer scanner and micro-electro-mechanical system scanner.

Results

Significant progress has been made in the development of PAM systems based on low-cost and compact light sources as well as miniaturized and handheld designs.

Conclusions

The review highlights the potential of these advancements to revolutionize PAM technology, making it more accessible and practical for various applications in preclinical studies, clinical practice, and long-term monitoring.

Effect of pulsed laser parameters on photoacoustic flow cytometry efficiency in vitro and in vivo

Photoacoustic flow cytometry is one of the most effective approaches to detect "alien" objects in the bloodstream, including circulating tumor cells, blood clots, parasites, and emboli. However, the possibility of detecting high-amplitude signals from these objects against the background of blood depends on the parameters of the laser pulse. So, the dependencies of photoacoustic signals amplitude and number on laser pulse energy (5-150 μJ), pulse length (1, 2, 5 ns), and pulse repetition rate (2, 5, 10 kHz) for the melanoma cells were investigated. First, the PA responses of a melanoma cell suspension in vitro were measured to directly assess the efficiency of converting laser light into an acoustic signal. After it, the same dependence with the developed murine model based on constant rate melanoma cell injection into the animal blood flow was tested. Both in vivo and in vitro experiments show that signal generation efficiency increases with laser pulse energy above 15 μJ. Shorter pulses, especially 1 ns, provide more efficient signal generation as well as higher pulse rates. A higher pulse rate also provides more efficient signal generation, but also leads to overheating of the skin. The results show the limits where the photoacoustic flow cytometry system can be effectively used for the detection of circulating tumor cells in undiluted blood both for in vitro experiments and for in vivo murine models.

Assembly of fluorophore J-aggregates with nanospacer onto mesoporous nanoparticles for enhanced photoacoustic imaging

Many fluorophores, such as indocyanine green (ICG), have poor photostability and low photothermal efficiency hindering their wide application in photoacoustic (PA) tomography. In the present study, a supramolecular assembly approach was used to develop the hybrid nanoparticles (Hy NPs) of ICG and porous silicon (PSi) as a novel contrast agent for PA tomography. ICG was assembled on the PSi NPs to form J-aggregates within 30 min. The Hy NPs presented a red-shifted absorption, improved photothermal stability, and enhanced PA performance. Furthermore, 1-dodecene (DOC) was assembled into the NPs as a 'nanospacer', which enhanced non-radiative decay for increased thermal release. Compared to the Hy NPs, adding DOC into the Hy NPs (DOC-Hy) increased the PA signal by 83%. Finally, the DOC-Hy was detectable in PA tomography at 1.5 cm depth in tissue phantom even though its concentration was as low as 6.25 µg/mL, indicating the potential for deep tissue PA imaging.

Deep Learning Enhanced Volumetric Photoacoustic Imaging of Vasculature in Human

The development of high-performance imaging processing algorithms is a core area of photoacoustic tomography. While various deep learning based image processing techniques have been developed in the area, their applications in 3D imaging are still limited due to challenges in computational cost and memory allocation. To address those limitations, this work implements a 3D fully-dense (3DFD) U-net to linear array based photoacoustic tomography and utilizes volumetric simulation and mixed precision training to increase efficiency and training size. Through numerical simulation, phantom imaging, and in vivo experiments, this work demonstrates that the trained network restores the true object size, reduces the noise level and artifacts, improves the contrast at deep regions, and reveals vessels subject to limited view distortion. With these enhancements, 3DFD U-net successfully produces clear 3D vascular images of the palm, arms, breasts, and feet of human subjects. These enhanced vascular images offer improved capabilities for biometric identification, foot ulcer evaluation, and breast cancer imaging. These results indicate that the new algorithm will have a significant impact on preclinical and clinical photoacoustic tomography.

Deep-Learning-Based High-Intensity Focused Ultrasound Lesion Segmentation in Multi-Wavelength Photoacoustic Imaging

Photoacoustic (PA) imaging can be used to monitor high-intensity focused ultrasound (HIFU) therapies because ablation changes the optical absorption spectrum of the tissue, and this change can be detected with PA imaging. Multi-wavelength photoacoustic (MWPA) imaging makes this change easier to detect by repeating PA imaging at multiple optical wavelengths and sampling the optical absorption spectrum more thoroughly. Real-time pixel-wise classification in MWPA imaging can assist clinicians in monitoring HIFU lesion formation and will be a crucial milestone towards full HIFU therapy automation based on artificial intelligence. In this paper, we present a deep-learning-based approach to segment HIFU lesions in MWPA images. Ex vivo bovine tissue is ablated with HIFU and imaged via MWPA imaging. The acquired MWPA images are then used to train and test a convolutional neural network (CNN) for lesion segmentation. Traditional machine learning algorithms are also trained and tested to compare with the CNN, and the results show that the performance of the CNN significantly exceeds traditional machine learning algorithms. Feature selection is conducted to reduce the number of wavelengths to facilitate real-time implementation while retaining good segmentation performance. This study demonstrates the feasibility and high performance of the deep-learning-based lesion segmentation method in MWPA imaging to monitor HIFU lesion formation and the potential to implement this method in real time.

Optomechanical force sensor operating over wide detection range

A detector with both broad operation range and high sensitivity is desirable in the measurement of weak periodic forces. Based on a nonlinear dynamical mechanism of locking the mechanical oscillation amplitude in optomechanical systems, we propose a force sensor that realizes the detection through the cavity field sidebands modified by an unknown external periodic force. Under the mechanical amplitude locking condition, the unknown external force happens to modify the locked oscillation amplitude linearly to its magnitude, thus achieving a linear scaling between the sideband changes read by the sensor and the magnitude of the force to be measured. This linear scaling range is found to be comparable to the applied pump drive amplitude, so the sensor can measure a wide range of force magnitude. Because the locked mechanical oscillation is rather robust against thermal perturbation, the sensor works well at room temperature. In addition to weak periodic forces, the same setup can as well detect static forces, though the detection ranges are much narrower.

Quantitative photoacoustic tomography with light fluence compensation based on radiance Monte Carlo model

Objective. Photoacoustic tomography (PAT) is a rapidly evolving imaging modality that provides images with high contrast and spatial resolution showing the optical properties of biological tissues. The photoacoustic pressure is proportional to the product of the optical absorption coefficient and the local light fluence. The essential challenge in reconstructing quantitative images representing spatially varying absorption coefficients is the unknown light fluence. In addition, optical attenuation induces spatial variations in the light fluence, and the heterogeneity of the fluence determines the limits of reconstruction quality and depth.Approach.In this work, a reconstruction enhancement scheme is proposed to compensate for the variation in the light fluence in the absorption coefficient recovery. The inverse problem of the radiance Monte Carlo model describing light transport through the tissue is solved by using an alternating optimization strategy. In the iteration, the absorption coefficients and photon weights are alternately updated.Main results.The method provides highly accurate quantitative images of absorption coefficients in simulations, phantoms, andin vivostudies. The results show that the method has great potential for improving the accuracy of absorption coefficient recovery compared to conventional reconstruction methods that ignore light fluence variations. Comparison with state-of-the-art fluence compensation methods shows significant improvements in root mean square error, normalized mean square absolute distance, and structural similarity metrics.Significance.This method achieves high precision quantitative imaging by compensating for nonuniform light fluence without increasing the complexity and operation of the imaging system.

Recent progress of nanostructure-based enrichment of circulating tumor cells and downstream analysis

The isolation and detection of circulating tumor cells (CTCs) play an important role in early cancer diagnosis and prognosis, providing easy access to identify metastatic cells before clinically detectable metastases. In the past 20 years, according to the heterogeneous expression of CTCs on the surface and their special physical properties (size, morphology, electricity, etc.), a series of in vitro enrichment methods of CTCs have been developed based on microfluidic chip technology, nanomaterials and various nanostructures. In recent years, the in vivo detection of CTCs has attracted considerable attention. Photoacoustic flow cytometry and fluorescence flow cytometry were used to detect CTCs in a noninvasive manner. In addition, flexible magnetic wire and indwelling intravascular non-circulating CTCs isolation system were developed for in vivo CTCs study. In the aspect of downstream analysis, gene analysis and drug sensitivity tests of enriched CTCs were developed based on various existing molecular analysis techniques. All of these studies constitute a complete study of CTCs. Although the existing reviews mainly focus on one aspect of capturing CTCs study, a review that includes the in vivo and in vitro capture and downstream analysis study of CTCs is highly needed. This review focuses on not only the classic work and latest research progress in in vitro capture but also includes the in vivo capture and downstream analysis, discussing the advantages and significance of the different research methods and providing new ideas for solving the heterogeneity and rarity of CTCs.

Non-contact detection of ultrasound with light - Review of recent progress

In this article, we present an overview of recent progress in non-contact remote optical detection of ultrasound in application to nondestructive testing and evaluation of materials. The focus of the review is on the latest advances in optical detection that offer mature and robust field-applicable solutions for diagnostics and imaging of engineered structures. We provide a detailed description of these solutions, including their operation principles, their evolution from the previously known designs to commercial devices, and their contribution to solving the most important problems associated with non-contact optical detection of ultrasound. Several application examples are presented to demonstrate the capabilities of optical detection and provide ideas to a reader on how it can be used in practice. We also discuss the main challenges of modern non-contact detectors which have not yet been addressed, as well as the directions and prospects for their development.

Acoustic-Based Theranostic Probes Activated by Tumor Microenvironment for Accurate Tumor Diagnosis and Assisted Tumor Therapy

Acoustic-based imaging techniques, including ultrasonography and photoacoustic imaging, are powerful noninvasive approaches for tumor imaging owing to sound transmission facilitation, deep tissue penetration, and high spatiotemporal resolution. Usually, imaging modes were classified into "always-on" mode and "activatable" mode. Conventional "always-on" acoustic-based probes often have difficulty distinguishing lesion regions of interest from surrounding healthy tissues due to poor target-to-background signal ratios. As compared, activatable probes have attracted attention with improved sensitivity, which can boost or amplify imaging signals only in response to specific biomolecular recognition or interactions. The tumor microenvironment (TME) exhibits abnormal physiological conditions that can be used to identify tumor sections from normal tissues. Various types of organic dyes and biomaterials can react with TME, leading to obvious changes in their optical properties. The TME also affects the self-assembly or aggregation state of nanoparticles, which can be used to design activatable imaging probes. Moreover, acoustic-based imaging probes and therapeutic agents can be coencapsulated into one nanocarrier to develop nanotheranostic probes, achieving tumor imaging and cooperative therapy. Satisfactorily, ultrasound waves not only accelerate the release of encapsulated therapeutic agents but also activate therapeutic agents to exert or enhance their therapeutic performance. Meanwhile, various photoacoustic probes can convert photon energy into heat under irradiation, achieving photoacoustic imaging and cooperative photothermal therapy. In this review, we focus on the recently developed TME-triggered ultrasound and photoacoustic theranostic probes for precise tumor imaging and targeted tumor therapy.

PATLAB: A graphical computational software package for photoacoustic computed tomography research

Photoacoustic tomography (PAT) provides high resolution optical images of tissue at depths of up to several centimetres. This modality has been of interest to researchers for at least 30 years and is still the subject of intensive research. However, PAT researchers lack access to a comprehensive open-source graphical simulation and reconstruction software package. In this article, we introduce PATLAB, an open-source MATLAB-based graphical software package that can perform both PAT simulation and image reconstruction. PATLAB is simple to use yet is capable of complex PAT data processing tasks and offers advanced users a framework to build and test new methods.

Thin ceramic PZT dual- and multi-frequency pMUT arrays for photoacoustic imaging

Miniaturized ultrasonic transducer arrays with multiple frequencies are key components in endoscopic photoacoustic imaging (PAI) systems to achieve high spatial resolution and large imaging depth for biomedical applications. In this article, we report on the development of ceramic thin-film PZT-based dual- and multi-frequency piezoelectric micromachined ultrasonic transducer (pMUT) arrays and the demonstration of their PAI applications. With chips sized 3.5 mm in length or 10 mm in diameter, square and ring-shaped pMUT arrays incorporating as many as 2520 pMUT elements and multiple frequencies ranging from 1 MHz to 8 MHz were developed for endoscopic PAI applications. Thin ceramic PZT with a thickness of 9 μm was obtained by wafer bonding and chemical mechanical polishing (CMP) techniques and employed as the piezoelectric layer of the pMUT arrays, whose piezoelectric constant d ₃₁ was measured to be as high as 140 pm/V. Benefiting from this high piezoelectric constant, the fabricated pMUT arrays exhibited high electromechanical coupling coefficients and large vibration displacements. In addition to electrical, mechanical, and acoustic characterization, PAI experiments with pencil leads embedded into an agar phantom were conducted with the fabricated dual- and multi-frequency pMUT arrays. Photoacoustic signals were successfully detected by pMUT elements with different frequencies and used to reconstruct single and fused photoacoustic images, which clearly demonstrated the advantages of using dual- and multi-frequency pMUT arrays to provide comprehensive photoacoustic images with high spatial resolution and large signal-to-noise ratio simultaneously.

Biomedical Application of Photoacoustics: A Plethora of Opportunities

The photoacoustic (PA) technique is a non-invasive, non-ionizing hybrid technique that exploits laser irradiation for sample excitation and acquires an ultrasound signal generated due to thermoelastic expansion of the sample. Being a hybrid technique, PA possesses the inherent advantages of conventional optical (high resolution) and ultrasonic (high depth of penetration in biological tissue) techniques and eliminates some of the major limitations of these conventional techniques. Hence, PA has been employed for different biomedical applications. In this review, we first discuss the basic physics of PA. Then, we discuss different aspects of PA techniques, which includes PA imaging and also PA frequency spectral analysis. The theory of PA signal generation, detection and analysis is also detailed in this work. Later, we also discuss the major biomedical application area of PA technique.

Deep learning methods hold promise for light fluence compensation in three-dimensional optoacoustic imaging

SIGNIFICANCE

Quantitative optoacoustic imaging (QOAI) continues to be a challenge due to the influence of nonlinear optical fluence distribution, which distorts the optoacoustic image representation. Nonlinear optical fluence correction in OA imaging is highly ill-posed, leading to the inaccurate recovery of optical absorption maps. This work aims to recover the optical absorption maps using deep learning (DL) approach by correcting for the fluence effect.

AIM

Different DL models were compared and investigated to enable optical absorption coefficient recovery at a particular wavelength in a nonhomogeneous foreground and background medium.

APPROACH

Data-driven models were trained with two-dimensional (2D) Blood vessel and three-dimensional (3D) numerical breast phantom with highly heterogeneous/realistic structures to correct for the nonlinear optical fluence distribution. The trained DL models such as U-Net, Fully Dense (FD) U-Net, Y-Net, FD Y-Net, Deep residual U-Net (Deep ResU-Net), and generative adversarial network (GAN) were tested to evaluate the performance of optical absorption coefficient recovery (or fluence compensation) with in-silico and in-vivo datasets.

RESULTS

The results indicated that FD U-Net-based deconvolution improves by about 10% over reconstructed optoacoustic images in terms of peak-signal-to-noise ratio. Further, it was observed that DL models can indeed highlight deep-seated structures with higher contrast due to fluence compensation. Importantly, the DL models were found to be about 17 times faster than solving diffusion equation for fluence correction.

CONCLUSIONS

The DL methods were able to compensate for nonlinear optical fluence distribution more effectively and improve the optoacoustic image quality.

Modeling toolchain for realistic simulation of photoacoustic data acquisition

SIGNIFICANCE

Physics-based simulations of photoacoustic (PA) signals are used to validate new methods, to characterize PA setups and to generate training datasets for machine learning. However, a thoroughly validated PA simulation toolchain that can simulate realistic images is still lacking.

AIM

A quantitative toolchain was developed to model PA image acquisition in complex tissues, by simulating both the optical fluence and the acoustic wave propagation.

APPROACH

Sampling techniques were developed to decrease artifacts in acoustic simulations. The performance of the simulations was analyzed by measuring the point spread function (PSF) and using a rotatable three-channel phantom, filled with cholesterol, a human carotid plaque sample, and porcine blood. Ex vivo human plaque samples were simulated to validate the methods in more complex tissues.

RESULTS

The sampling techniques could enhance the quality of the simulated PA images effectively. The resolution and intensity of the PSF in the turbid medium matched the experimental data well. Overall, the appearance, signal-to-noise ratio and speckle of the images could be simulated accurately.

CONCLUSIONS

A PA toolchain was developed and validated, and the results indicate a great potential of PA simulations in more complex and heterogeneous media.

Microorganism-enabled photosynthetic oxygeneration and ferroptosis induction reshape tumor microenvironment for augmented nanodynamic therapy

Nanodynamic therapy (NDT) based on reactive oxygen species (ROS) generation has been envisioned as a distinct modality for efficient cancer treatment. However, insufficient ROS generation and partial ROS consumption frequently limit the theraputic effect and outcome of NDT owing to the low oxygen (O2) tension and high glutathione (GSH) level in tumor microenvironment (TME). To circumvent these critical issues, we herein proposed and engineered the biodegradable GSH-depletion Mn(III)-riched manganese oxide nanospikes (MnOx NSs) with the photosynthetic bacterial cyanobacteria (Cyan) as a high-efficient and synergistic platform to reshape TME by simultaneously increasing oxygen content and decreasing GSH level. Specifically, under the trigger of acidity, MnOx NSs reacted with photosynthetic oxygen can generate toxic singlet oxygen (1O2). Moreover, MnOx NSs significantly reduced intracellular GSH, resulting in decreased GPX4 activity, which induced tumor cell non-apoptotic ferroptosis. Consequently, this combined strategy based on coadministration with Cyan and MnOx NSs demonstrated the superior antitumor efficacy via amplification of oxidative stress in 4T1 tumor-bearing mice for the synergetic oxygen-augmented nanodynamic/ferroptosis therapy. This work highlights a facile synergistic micro-/nano-system with the specific capability of reshaping TME to augment the sensitivity and therapeutic efficacy of NDT in solid hypoxic tumor therapy.

Size-adjustable ring-shape photoacoustic tomography imager in vivo

Photoacoustic tomography (PAT) has become a novel biomedical imaging modality for scientific research and clinical diagnosis. It combines the advantages of spectroscopic optical absorption contrast and acoustic resolution with deep penetration. In this article, an imaging size-adjustable PAT system is proposed for potential clinical applications such as breast cancer detection and screening, which can adapt to imaging targets with various sizes. Comparing with the conventional PAT setup with a fixed radius ring shape ultrasound transducer (UT) array, the proposed system is more flexible for imaging diverse size targets based on sectorial ultrasound transducer arrays (SUTAs). Four SUTAs form a 128-channel UT array for photoacoustic detection, where each SUTA has 32 elements. Such four SUTAs are controlled by four stepper motors, respectively, and can change their distribution layout position to adapt for various imaging applications. In this proposed system, the radius of the imaging region of interest (ROI) can be adjusted from 50 to 100 mm, which is much more flexible than the conventional PAT system with a full ring UT array. The simulation experiments using the MATLAB k-wave toolbox demonstrate the feasibility of the proposed system. To further validate the proposed system, imaging of pencil leads made phantom, ex-vivo pork breast with indocyanine green (ICG) injected, and in-vivo human wrist, finger and ankle are conducted to prove its feasibility for potential clinical applications.

Weighted model-based optoacoustic reconstruction for partial-view geometries

Acoustic heterogeneities in biological samples are known to cause artifacts in tomographic optoacoustic (photoacoustic) image reconstruction. A statistical weighted model-based reconstruction approach was previously introduced to mitigate such artifacts. However, this approach does not reliably provide high-quality reconstructions for partial-view imaging systems, which are common in preclinical and clinical optoacoustics. In this article, the capability of the weighted model-based algorithm is extended to generate optoacoustic reconstructions with less distortions for partial-view geometry data. This is achieved by manipulating the weighting scheme based on the detector geometry. Using partial-view optoacoustic tomography data from a tissue-mimicking phantom containing a strong acoustic reflector, tumors grafted onto mice, and a mouse brain with intact skull, the proposed partial-view-corrected weighted model-based algorithm is shown to mitigate reflection artifacts in reconstructed images without distorting structures or boundaries, compared with both conventional model-based and the weighted model-based algorithms. It is also demonstrated that the partial-view-corrected weighted model-based algorithm has the additional advantage of suppressing streaking artifacts due to the partial-view geometry itself in the presence of a very strong optoacoustic chromophore. Due to its enhanced performance, the partial-view-corrected weighted model-based algorithm may prove useful for improving the quality of partial-view multispectral optoacoustic tomography, leading to enhanced visualization of functional parameters such as tissue oxygenation.

A Review of High-Frequency Ultrasonic Transducers for Photoacoustic Imaging Applications

Photoacoustic imaging (PAI) is a new and rapidly growing hybrid biomedical imaging modality that combines the virtues of both optical and ultrasonic (US) imaging. The nature of the interaction between light and ultrasound waves allows PAI to make good use of the rich contrast produced by optics while retaining the imaging depths in US imaging. High-frequency US transducers are an important part of the PAI systems, used to detect the high-frequency and broad-bandwidth photoacoustic signals excited by the target tissues irradiated by short laser pulses. Advancement in high-frequency US transducer technology has influenced the boost of PAI to broad applications. Here, we present a review on high-frequency US transducer technologies for PAI applications, including advanced piezoelectric materials and representative transducers. In addition, we discuss the new challenges and directions facing the development of high-frequency US transducers for PAI applications.

Spectroscopic photoacoustic microscopic imaging during single spatial scan using broadband excitation light pulses with wavelength-dependent time delay

In most multispectral optical-resolution photoacoustic microscopy (OR-PAM), spatial scanning is repeated for each excitation wavelength, which decreases throughput and causes motion artifacts during spectral processing. This study proposes a new spectroscopic OR-PAM technique to acquire information on the photoacoustic signal intensity and excitation wavelength from single spatial scans. The technique involves irradiating an imaging target with two broadband optical pulses with and without wavelength-dependent time delays. The excitation wavelength of the sample is then calculated by measuring the time delay between the photoacoustic signals generated by the two optical pulses. This technique is validated by measuring the excitation wavelengths of dyes in tubes. Furthermore, we demonstrate the three-dimensional spectroscopic OR-PAM of cells stained with suitable dyes. Although the tradeoff between excitation efficiency and excitation bandwidth must be adjusted based on the application, combining the proposed technique with fast spatial scanning methods can significantly contribute to recent OR-PAM applications, such as monitoring quick biological events and microscale tracking of moving materials.

Programmable Acoustic Delay-Line Enabled Low-Cost Photoacoustic Tomography System

Photoacoustic tomography (PAT) is an emerging technology for biomedical imaging that combines the superiorities of high optical contrast and acoustic penetration. In the PAT system, more PA signals are preferred to be detected from full field of view to reconstruct the PA images with higher fidelity. However, the requirement for more PA signals' detection leads to more time consumption for single-channel scanning-based PAT system or higher cost of data acquisition (DAQ) module for an array-based PAT system. To address this issue, we proposed a programmable acoustic delay-line (PADL) module to reduce DAQ cost and accelerate imaging speed for PAT system. The module is based on bidirectional conversion between acoustic signals and electrical signals, including ultrasound transmission in between to provide sufficient time delay. The acoustic delay-line module achieves tens or hundreds of microseconds' delay for each channel and is controlled by a programmable control unit. In this work, it achieves to merge four inputs of PA signals into one output signal, which can be recovered into original four PA signals in the digital domain after DAQ. The imaging experiments of pencil leads embedded in agar phantom are conducted by the PAT system equipped with the proposed PADL module, which demonstrated its feasibility to reduce the cost of the PAT system. An in vivo study of human finger PAT imaging with delay-line module verified its feasibility for biomedical imaging applications.

Real-time whole-brain imaging of hemodynamics and oxygenation at micro-vessel resolution with ultrafast wide-field photoacoustic microscopy

High-speed high-resolution imaging of the whole-brain hemodynamics is critically important to facilitating neurovascular research. High imaging speed and image quality are crucial to visualizing real-time hemodynamics in complex brain vascular networks, and tracking fast pathophysiological activities at the microvessel level, which will enable advances in current queries in neurovascular and brain metabolism research, including stroke, dementia, and acute brain injury. Further, real-time imaging of oxygen saturation of hemoglobin (sO₂) can capture fast-paced oxygen delivery dynamics, which is needed to solve pertinent questions in these fields and beyond. Here, we present a novel ultrafast functional photoacoustic microscopy (UFF-PAM) to image the whole-brain hemodynamics and oxygenation. UFF-PAM takes advantage of several key engineering innovations, including stimulated Raman scattering (SRS) based dual-wavelength laser excitation, water-immersible 12-facet-polygon scanner, high-sensitivity ultrasound transducer, and deep-learning-based image upsampling. A volumetric imaging rate of 2 Hz has been achieved over a field of view (FOV) of 11 × 7.5 × 1.5 mm³ with a high spatial resolution of ~10 μm. Using the UFF-PAM system, we have demonstrated proof-of-concept studies on the mouse brains in response to systemic hypoxia, sodium nitroprusside, and stroke. We observed the mouse brain's fast morphological and functional changes over the entire cortex, including vasoconstriction, vasodilation, and deoxygenation. More interestingly, for the first time, with the whole-brain FOV and micro-vessel resolution, we captured the vasoconstriction and hypoxia simultaneously in the spreading depolarization (SD) wave. We expect the new imaging technology will provide a great potential for fundamental brain research under various pathological and physiological conditions.

Enhancing Finite Element-Based Photoacoustic Tomography by Localized Reconstruction Method

Iterative reconstruction algorithm based on finite element (FE) modeling is a powerful approach in photoacoustic tomography (PAT). However, an iterative inverse algorithm using conventional FE meshing of the entire imaging zone is computationally demanding, which hinders this powerful tool in applications where quick image acquisition and/or a large image matrix is needed. To address this challenge, parallel computing techniques are proposed and implemented in the field. Here, we present an alternative approach for 2D PAT, which locoregionally reconstructs the region of interest (ROI) instead of the full imaging zone. Our simulated and phantom experimental results demonstrate that this ROI reconstruction algorithm can produce almost the same image quality as the conventional full zone-based reconstruction algorithm; however, the computation time can be significantly reduced without any additional hardware cost by more than two orders of magnitude (100-fold). This algorithm is further applied and validated in an in vivo study. The major vessel structures in a rat’s brain can be imaged clearly using our ROI-based approach, coupled with a mesh of 11,801 nodes. This novel algorithm can also be parallelized using MPI or GPU acceleration techniques to further enhance the reconstruction performance of FE-based PAT.

Photoacoustic characterization of bone physico-chemical information

Osteoporosis usually alters the chemical composition and physical microstructure of bone. Currently, most clinical techniques for bone assessment are focused on the either bone microstructure or bone mineral density (BMD). In this study, a novel multi-wavelength photoacoustic time-frequency spectral analysis (MWPA-TFSA) method was introduced based on the optical absorption spectra and photoacoustic effects of biological macromolecules, which evaluates changes in bone chemical composition and microstructure. The results demonstrated that osteoporotic bones had decreased BMD, more lipids, and wider trabecular separation filled with larger marrow clusters, which were consistent with multiple gold-standard results, suggesting that the MWPA-TFSA method has the potential to provide a thorough bone physico-chemical information evaluation noninvasively and nonradiatively.

Photoacoustic Imaging in Biomedicine and Life Sciences

Photo-acoustic imaging, also known as opto-acoustic imaging, has become a widely popular modality for biomedical applications. This hybrid technique possesses the advantages of high optical contrast and high ultrasonic resolution. Due to the distinct optical absorption properties of tissue compartments and main chromophores, photo-acoustics is able to non-invasively observe structural and functional variations within biological tissues including oxygenation and deoxygenation, blood vessels and spatial melanin distribution. The detection of acoustic waves produced by a pulsed laser source yields a high scaling range, from organ level photo-acoustic tomography to sub-cellular or even molecular imaging. This review discusses significant novel technical solutions utilising photo-acoustics and their applications in the fields of biomedicine and life sciences.

Adaptive stochastic Gauss-Newton method with optical Monte Carlo for quantitative photoacoustic tomography

SIGNIFICANCE

The image reconstruction problem in quantitative photoacoustic tomography (QPAT) is an ill-posed inverse problem. Monte Carlo method for light transport can be utilized in solving this image reconstruction problem.

AIM

The aim was to develop an adaptive image reconstruction method where the number of photon packets in Monte Carlo simulation is varied to achieve a sufficient accuracy with reduced computational burden.

APPROACH

The image reconstruction problem was formulated as a minimization problem. An adaptive stochastic Gauss-Newton (A-SGN) method combined with Monte Carlo method for light transport was developed. In the algorithm, the number of photon packets used on Gauss-Newton (GN) iteration was varied utilizing a so-called norm test.

RESULTS

The approach was evaluated with numerical simulations. With the proposed approach, the number of photon packets needed for solving the inverse problem was significantly smaller than in a conventional approach where the number of photon packets was fixed for each GN iteration.

CONCLUSIONS

The A-SGN method with a norm test can be utilized in QPAT to provide accurate and computationally efficient solutions.

Multiphysical numerical study of photothermal therapy of glioblastoma with photoacoustic temperature monitoring in a mouse head

This paper presents a multiphysical numerical study of a photothermal therapy performed on a numerical phantom of a mouse head containing a glioblastoma. The study has been designed to be as realistic as possible. Heat diffusion simulations were performed on the phantom to understand the temperature evolution in the mouse head and therefore in the glioblastoma. The thermal dose has been calculated and lesions caused by heat are shown. The thermal damage on the tumor has also been quantified. To improve the effectiveness of the therapy, the photoabsorber's concentration was increased locally, at the tumor site, to mimic the effect of using absorbing contrast agents such as nanoparticles. Photoacoustic simulations were performed in order to monitor temperature in the phantom: as the Grüneisen parameter changes with the temperature, the photoacoustic signal undergoes changes that can be linked to temperature evolution. These photoacoustic simulations were performed at different instants during the therapy and the evolution of the photoacoustic signal as a function of the spatio-temporal distribution of the temperature in the phantom was observed and quantified. We have developed in this paper a numerical tool that can be used to help defining key parameters of a photothermal therapy.

Multispectral interlaced sparse sampling photoacoustic tomography based on directional total variation

BACKGROUND AND OBJECTIVE

Photoacoustic tomography (PAT) is capable of obtaining cross-sectional images of small animals that represent the optical absorption of biological tissues. The multispectral Interlaced Sparse Sampling PAT, or ISS-PAT, is a previously proposed PAT imaging method that offered high quality images with much sparser transducer angular coverage. Although it provides superior imaging performance, the original ISS-PAT method suffered from a heavy computation burden, which hinders its practical application.

METHODS

Here, we propose a new regularization scheme based on the directional total variation (dTV) for ISS-PAT. This method efficiently imposes the structural information by considering both the edge position and direction information of the anatomical prior image in ISS-PAT. It does not require image segmentation, and can be conveniently solved by a modified alternating direction of multipliers (ADMM) algorithm.

RESULTS

We perform simulation, tissue mimicking phantom and in vivo small animal experiments to evaluate the proposed scheme. The reconstructed PAT images showed image quality and spectral un-mixing accuracy close to those obtained by non-local means based ISS-PAT, but with much shorter image reconstruction time. For a 1/6 sparse sampling rate, the average efficiency improvement is nearly 16-folds.

CONCLUSIONS

The experimental results demonstrate the feasibility of the dTV regularization scheme for ISS-PAT. Its efficient image reconstruction performance facilitates the potential of the hardware realization and practical applications of the ISS-PAT.

Enhanced visibility through microbubble-induced photoacoustic fluctuation imaging

A photoacoustic contrast mechanism is presented based on the photoacoustic fluctuations induced by microbubbles flowing inside a micro-vessel filled with a continuous absorber. It is demonstrated that the standard deviation of a homogeneous absorber mixed with microbubbles increases non-linearly as the microbubble concentration and microbubble size is increased. This effect is then utilized to perform photoacoustic fluctuation imaging with increased visibility and contrast of a blood flow phantom.

Recent Advances in the Development and Applications of Conjugated Polymer dots

Conjugated polymer dots or semiconducting polymer nanoparticles (Pdots) are nanoparticles prepared based on organic polymers. Pdots have the advantages of lower cost, simple preparation process, good biocompatibility, excellent stability, easy...

Photoacoustic measurement of localized optical dichroism in chiral crystals

In this communication, we present a novel method to measure local optical dichroism (OD) in opaque crystal powder suspensions using photoacoustic (PA) effect. Our method is based upon the novel laser speckle contrast technique, in combination with a simple statistical approach, we were able to measure the OD of chiral crystals suspensions under completely random orientation.

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

OBJECTIVE

This paper proposes a new photoacoustic computed tomography (PACT) imaging system employing dual ultrasonic transducers with different frequencies. When imaging complex biological tissues, photoacoustic (PA) signals with multiple frequencies are produced simultaneously; however, due to the limited bandwidth of a single-frequency transducer, the received PA signals with specific frequencies may be missing, leading to a low imaging quality.

METHODS

In contrast to our previous work, the proposed system has a compact volume as well as specific selection of the detection center frequency of the transducer, which can provide a comprehensive range for the detection of PA signals. In this study, a series of numerical simulation and phantom experiments were performed to validate the efficacy of the developed PACT system.

RESULTS

The images generated by our system combined the advantages of both high resolution and ideal brightness/contrast.

CONCLUSION

The interchangeability of transducers with different frequencies provides potential for clinical deployment under the circumstance where a single frequency transducer cannot perform well.

A Copolymer-in-Oil Tissue-Mimicking Material With Tuneable Acoustic and Optical Characteristics for Photoacoustic Imaging Phantoms

Photoacoustic imaging (PAI) standardisation demands a stable, highly reproducible physical phantom to enable routine quality control and robust performance evaluation. To address this need, we have optimised a low-cost copolymer-in-oil tissue-mimickingmaterial formulation. The base material consists of mineral oil, copolymer and stabiliser with defined Chemical Abstract Service numbers. Speed of sound c(f) and acoustic attenuation coefficient α (f) were characterised over 2-10 MHz; optical absorption μa ( λ ) and reduced scattering μs '( λ ) coefficients over 450-900 nm. Acoustic properties were optimised by modifying base component ratios and optical properties were adjusted using additives. The temporal, thermomechanical and photo-stabilitywere studied, alongwith intra-laboratory fabrication and field-testing. c(f) could be tuned up to (1516±0.6) [Formula: see text] and α (f) to (17.4±0.3)dB · cm -1 at 5 MHz. The base material exhibited negligible μa ( λ ) and μs '( λ ), which could be independently tuned by addition of Nigrosin or TiO2 respectively. These properties were stable over almost a year and were minimally affected by recasting. The material showed high intra-laboratory reproducibility (coefficient of variation <4% for c ( f ), α ( f ), optical transmittance and reflectance), and good photo- and mechanical-stability in the relevant working range (20-40°C). The optimised copolymer-in-oil material represents an excellent candidate for widespread application in PAI phantoms, with properties suitable for broader use in biophotonics and ultrasound imaging standardisation efforts.

Activity of keloids evaluated by multimodal photoacoustic/ultrasonic imaging system

Multiple objective assessments have been used to assess the activity of keloids to compare different therapeutic regimens and facilitate the best individual treatment choice for patients, but none of them are standardized. A multimodal photoacoustic/ultrasonic (PA/US) imaging system, including photoacoustic imaging, elastography, ultra-micro-angiography, and conventional US technologies (gray scale US, color Doppler US, and power Doppler US), was applied to evaluate keloids by a radiologist. Growing stages were defined by patients, and Vancouver Scar Scale (VSS) was assessed by a plastic surgeon. A comprehensive model based on multimodal ultrasound parameters (poor-echo pattern, high vascular density, decreased elasticity, and low SO₂ within the keloid) and VSS might be a potential indicator of active keloids, comparing with VSS alone. The multimodal PA/US imaging system could be a promising technique for keloids assessment.

Unsupervised Body Hair Detection by Positive-Unlabeled Learning in Photoacoustic Image

Photoacoustic (PA) imaging is a new imaging technology that can non-invasively visualize blood vessels and body hair in 3D. It is useful in cosmetic surgery for detecting body hair and computing metrics such as the number and thicknesses of hairs. Previous supervised body hair detection methods often do not work if the imaging conditions change from training data. We propose an unsupervised hair detection method. Hair samples were automatically extracted from unlabeled samples using prior knowledge about spatial structure. If hair (positive) samples and unlabeled samples are obtained, Positive Unlabeled (PU) learning becomes possible. PU methods can learn a binary classifier from positive samples and unlabeled samples. The advantage of the proposed method is that it can estimate an appropriate decision boundary in accordance with the distribution of the test data. Experimental results using real PA data demonstrate that the proposed approach effectively detects body hairs.