High-resolution iterative reconstruction at extremely low sampling rate for Fourier single-pixel imaging via diffusion model.

The trade-off between imaging efficiency and imaging quality has always been encountered by Fourier single-pixel imaging (FSPI). To achieve high-resolution imaging, the increase in the number of measurements is necessitated, resulting in a reduction of imaging efficiency. Here, a novel high-quality reconstruction method for FSPI imaging via diffusion model was proposed. A score-based diffusion model is designed to learn prior information of the data distribution. The real-sampled low-frequency Fourier spectrum of the target is employed as a consistency term to iteratively constrain the model in conjunction with the learned prior information, achieving high-resolution reconstruction at extremely low sampling rates. The performance of the proposed method is evaluated by simulations and experiments. The results show that the proposed method has achieved superior quality compared with the traditional FSPI method and the U-Net method. Especially at the extremely low sampling rate (e.g., 1%), an approximately 241% improvement in edge intensity-based score was achieved by the proposed method for the coin experiment, compared with the traditional FSPI method. The method has the potential to achieve high-resolution imaging without compromising imaging speed, which will further expanding the application scope of FSPI in practical scenarios.

High-speed real 3D scene acquisition and 3D holographic reconstruction system based on ultrafast optical axial scanning.

The lack of three-dimensional (3D) content is one of the challenges that have been faced by holographic 3D display. Here, we proposed a real 3D scene acquisition and 3D holographic reconstruction system based on ultrafast optical axial scanning. An electrically tunable lens (ETL) was used for high-speed focus shift (up to 2.5 ms). A CCD camera was synchronized with the ETL to acquire multi-focused image sequence of real scene. Then, the focusing area of each multi-focused image was extracted by using Tenengrad operator, and the 3D image were obtained. Finally, 3D holographic reconstruction visible to the naked eye can be achieved by the layer-based diffraction algorithm. The feasibility and effectiveness of the proposed method have been demonstrated by simulation and experiment, and the experimental results agree well with the simulation results. This method will further expand the application of holographic 3D display in the field of education, advertising, entertainment, and other fields.

Bessel acoustic-beam acoustic lens for extending the depth of field of detection in optical-resolution photoacoustic microscopy.

As an important part of optical-resolution photoacoustic microscopy, the acoustic lens is responsible for efficient collection of photoacoustic signals. The spherical focused acoustic lens is commonly used in photoacoustic microscopy because of its efficient detection of the photoacoustic signal in the focus area. However, the narrow depth of field of the spherical focused acoustic lens limits the expansion of the depth of field of the photoacoustic microscopy. To solve this problem, a Bessel acoustic-beam acoustic lens is proposed. The Bessel acoustic-beam acoustic lens replaces the spherical concave surface with a conical concave surface to generate a Bessel acoustic beam with non-diffraction. Using the simulation model of Bessel acoustic-beam acoustic lens constructed by COMSOL Multiphysics, it is verified theoretically that the Bessel acoustic-beam acoustic lens can improve the depth of field of detection by ∼2 times. The Bessel acoustic-beam acoustic lens can further promote the capability of high-speed and large volumetric imaging of optical-resolution photoacoustic microscopy and will be helpful in the acquisition of physiological and pathological processes.

Controllable axial optical chain beams using a holographic method.

Axial optical chain (optical bottle beams) beams are widely used in optical micromanipulation, atom trapping, guiding and binding of microparticles and biological cells, etc. However, the generation of axial optical chain beams are not very flexible at present, and its important characteristics such as periodicity and phase shift cannot be easily regulated. Here, we propose a holographic method to achieve the axial optical chain beams with controllable periodicity and phase. A double annular phase diagram is generated based on the gratings and lenses algorithms. The beam incident to the double annular slits was tilted from the optical axis to produce concentric double annular beams. The annular beam with different radius will produce the zero-order Bessel beam with different axial wave vector. Axial optical chain beams is produced by interference of two zero-order Bessel beams with different axial wave vectors. The phase and periodicity of the axial optical chain beams can be changed by changing the initial phase difference and radius of the double annular slits of the double annular phase diagram, respectively. The feasibility and effectiveness of the proposed method are demonstrated by theoretical numerical analysis and experiments. This method will further expand the application of axial optical chain beams in optical tweezers, optical modulation and other fields.

Graded peripheral nerve injury creates mechanical allodynia proportional to the progression and severity of microglial activity within the spinal cord of male mice.

The reactivity of microglia within the spinal cord in response to nerve injury, has been associated with the development and maintenance of neuropathic pain. However, the temporal changes in microglial reactivity following nerve injury remains to be defined. Importantly, the magnitude of behavioural allodynia displayed and the relationship to the phenotypic microglial changes is also unexplored. Using a heterozygous CX3CR1gfp+ transgenic mouse strain, we monitored microglial activity as measured by cell density, morphology, process movement and process length over 14 days following chronic constriction of the sciatic nerve via in vivo confocal microscopy. Uniquely this relationship was explored in groups of male mice which had graded nerve injury and associated graded behavioural mechanical nociceptive sensitivity. Significant mechanical allodynia was quantified from the ipsilateral hind paw and this interacted with the extent of nerve injury from day 5 to day 14 (p < 0.009). The extent of this ipsilateral allodynia was proportional to the nerve injury from day 5 to 14 (Spearman rho = -0.58 to -0.77; p < 0.002). This approach allowed for the assessment of the association of spinal microglial changes with the magnitude of the mechanical sensitivity quantified behaviourally. Additionally, the haemodynamic response in the somatosensory cortex was quantified as a surrogate measure of neuronal activity. We found that spinal dorsal horn microglia underwent changes unilateral to the injury in density (Spearman rho = 0.47; p = 0.01), velocity (Spearman rho = -0.68; p = 0.00009), and circularity (Spearman rho = 0.55; p = 0.01) proportional to the degree of the neuronal injury. Importantly, these data demonstrate for the first time that the mechanical allodynia behaviour is not a binary all or nothing state, and that microglial reactivity change proportional to this behavioural measurement. Increased total haemoglobin levels in the somatosensory cortex of higher-grade injured animals was observed when compared to sham controls suggesting increased neuronal activity in this brain region. The degree of phenotypic microglial changes quantified here, may explain how microglia can induce both rapid onset and sustained functional changes in the spinal cord dorsal horn, following peripheral injury.

Virtual optical-resolution photoacoustic microscopy using the k-Wave method.

Deep learning has been widely used in image processing, quantitative analysis, and other applications in optical-resolution photoacoustic microscopy (OR-PAM). It requires a large amount of photoacoustic data for training and testing. However, due to the complex structure, high cost, slow imaging speed, and other factors of OR-PAM, it is difficult to obtain enough data required by deep learning, which limits the research of deep learning in OR-PAM to a certain extent. To solve this problem, a virtual OR-PAM based on k-Wave is proposed. The virtual photoacoustic microscopy mainly includes the setting of excitation light source and ultrasonic probe, scanning and signal processing, which can realize the common Gaussian-beam and Bessel-beam OR-PAMs. The system performance (lateral resolution, axial resolution, and depth of field) was tested by imaging a vertically tilted fiber, and the effectiveness and feasibility of the virtual simulation platform were verified by 3D imaging of the virtual vascular network. The ability to the generation of the dataset for deep learning was also verified. The construction of the virtual OR-PAM can promote the research of OR-PAM and the application of deep learning in OR-PAM.

A Simple Glutathione-Responsive Turn-On Theranostic Nanoparticle for Dual-Modal Imaging and Chemo-Photothermal Combination Therapy.

Constructing a tumor microenvironment stimuli activatable theranostic nanoparticle with simple components and preparation procedures for multimodality imaging and therapy remains a major challenge for current theranostic systems. Here we report a novel and simple glutathione (GSH)-responsive turn-on theranostic nanoparticle for dual-modal imaging and combination therapy. The theranostic nanoparticle, DHP, consisting of a disulfide-bond-linked hydroxyethyl starch paclitaxel conjugate (HES-SS-PTX) and a near-infrared (NIR) cyanine fluorophore DiR, is prepared with a simple one-step dialysis method. As DiR is encapsulated within the hydrophobic core formed by HES-SS-PTX, the fluorescence of DiR is quenched by the aggregation-caused quenching (ACQ) effect. Nonetheless, once DHP is internalized by cancer cells, the disulfide bond of HES-SS-PTX can be cleaved by intracellular GSH, leading to the synchronized release of conjugated PTX and loaded DiR. The released PTX could exert its therapeutic effect, while DiR could adsorb onto nearby endosome/lysosome membranes and regain its fluorescence. Thus, DHP could monitor the release and therapeutic effect of PTX through the fluorescence recovery of DiR. Remarkably, DHP can also be used as an in vivo probe for both fluorescent and photoacoustic imaging and at the same time achieves potent antitumor efficacy through chemo-photothermal combination therapy. This study provides novel insights into designing clinically translatable turn-on theranostic systems.

Tumor Starvation Induced Spatiotemporal Control over Chemotherapy for Synergistic Therapy.

By integrating the characteristics of each therapy modality and material chemistry, a multitherapy modality is put forward: tumor starvation triggered synergism with sensitized chemotherapy. Following starvation-induced amplification of pathological abnormalities in tumors, chemotherapy is arranged to be locally activated and accurately reinforced to perfect multitherapy synergism from spatial and temporal perspectives. To this end, glucose oxidase (GOD) and a hypoxic prodrug of tirapazamine (TPZ) are loaded in acidity-decomposable calcium carbonate (CaCO3 ) nanoparticles concurrently tethered by hyaluronic acid. This hybrid nanotherapeutic shows a strong tendency to accumulate in tumors postinjection due to the cooperation between passive and active targeting mechanisms. The GOD-driven oxidation reaction deprives tumors of glucose for starvation therapy and concomitantly induces tumorous abnormality amplifications including elevated acidity and exacerbated hypoxia. Programmatically, the acidity amplification causes CaCO3 decomposition, offering not only spatial control over the liberation of embedded TPZ just within tumors but also the temporal control over timely chemotherapy initiation to match the occurrence of hypoxia amplification and thus benefiting perfect synergism between starvation therapy and chemotherapy.

Folic acid modified Pluronic F127 coating Ag2S quantum dot for photoacoustic imaging of tumor cell-targeting.

In this study, an oil-soluble Ag2S quantum dot (QD) was synthesized through thermal decomposition using the single-source precursor method, and Pluronic F127 (PF127), a triblock copolymer functionalized with folic acid (FA), was deposited on the surface of the QD, then a water-soluble PF127-FA@Ag2S nanoprobe with targeting ability was fabricated. The as-prepared PF127-FA@Ag2S exhibited spheroidal morphology and high dispersibility, with average diameters of 115 ± 20.7 nm (as observed by transmission electron microscopy). No obvious toxicity of the PF127-FA@Ag2S nanoprobe was found in standard 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide assay and colony-formation assay, indicating good biocompatibility and safety. The resulting PF127-FA@Ag2S exhibited excellent stability between 4 °C-40 °C. Additionally, the capacity of the tumor cell-targeting high contrast enhanced photoacoustic imaging of PF127-FA@Ag2S was verified in comparison with A547 and HeLa cells. In other words, the excellent properties of PF127-FA@Ag2S show great potential in further research for targeting and photoacoustic imaging.

A multifunctional targeting probe with dual-mode imaging and photothermal therapy used in vivo.

BACKGROUND: Ag2S has the characteristics of conventional quantum dot such as broad excitation spectrum, narrow emission spectrum, long fluorescence lifetime, strong anti-bleaching ability, and other optical properties. Moreover, since its fluorescence emission is located in the NIR-II region, has stronger penetrating ability for tissue. Ag2S quantum dot has strong absorption during the visible and NIR regions, it has good photothermal and photoacoustic response under certain wavelength excitation. RESULTS: 200 nm aqueous probe Ag2S@DSPE-PEG2000-FA (Ag2S@DP-FA) with good dispersibility and stability was prepared by coating hydrophobic Ag2S with the mixture of folic acid (FA) modified DSPE-PEG2000 (DP) and other polymers, it was found the probe had good fluorescent, photoacoustic and photothermal responses, and a low cell cytotoxicity at 50 µg/mL Ag concentration. Blood biochemical analysis, liver enzyme and tissue histopathological test showed that no significant influence was observed on blood and organs within 15 days after injection of the probe. In vivo and in vitro fluorescence and photoacoustic imaging of the probe further demonstrated that the Ag2S@DP-FA probe had good active targeting ability for tumor. In vivo and in vitro photothermal therapy experiments confirmed that the probe also had good ability of killing tumor by photothermal. CONCLUSIONS: Ag2S@DP-FA was a safe, integrated diagnosis and treatment probe with multi-mode imaging, photothermal therapy and active targeting ability, which had a great application prospect in the early diagnosis and treatment of tumor.

Fast axial-scanning photoacoustic microscopy using tunable acoustic gradient lens.

An optical-resolution photoacoustic microscope (OR-PAM) with capability of fast axial-scanning was developed by using a tunable acoustic gradient (TAG) lens. The TAG lens was designed to continuously changing the focal plane of OR-PAM by modulating its refractive power with fast-changing ultrasonic standing wave. The performance was shown by imaging a carbon fiber. We achieved a DoF of about 750 µm. The head of a zebrafish was also imaged to further demonstrate the feasibility of our method.

Unsupervised disentanglement strategy for mitigating artifact in photoacoustic tomography under extremely sparse view.

Traditional methods under sparse view for reconstruction of photoacoustic tomography (PAT) often result in significant artifacts. Here, a novel image to image transformation method based on unsupervised learning artifact disentanglement network (ADN), named PAT-ADN, was proposed to address the issue. This network is equipped with specialized encoders and decoders that are responsible for encoding and decoding the artifacts and content components of unpaired images, respectively. The performance of the proposed PAT-ADN was evaluated using circular phantom data and the animal in vivo experimental data. The results demonstrate that PAT-ADN exhibits excellent performance in effectively removing artifacts. In particular, under extremely sparse view (e.g., 16 projections), structural similarity index and peak signal-to-noise ratio are improved by ∼188 % and ∼85 % in in vivo experimental data using the proposed method compared to traditional reconstruction methods. PAT-ADN improves the imaging performance of PAT, opening up possibilities for its application in multiple domains.

Accelerated model-based iterative reconstruction strategy for sparse-view photoacoustic tomography aided by multi-channel autoencoder priors.

Photoacoustic tomography (PAT) commonly works in sparse view due to data acquisition limitations. However, reconstruction suffers from serious deterioration (e.g., severe artifacts) using traditional algorithms under sparse view. Here, a novel accelerated model-based iterative reconstruction strategy for sparse-view PAT aided by multi-channel autoencoder priors was proposed. A multi-channel denoising autoencoder network was designed to learn prior information, which provides constraints for model-based iterative reconstruction. This integration accelerates the iteration process, leading to optimal reconstruction outcomes. The performance of the proposed method was evaluated using blood vessel simulation data and experimental data. The results show that the proposed method can achieve superior sparse-view reconstruction with a significant acceleration of iteration. Notably, the proposed method exhibits excellent performance under extremely sparse condition (e.g., 32 projections) compared with the U-Net method, with an improvement of 48% in PSNR and 12% in SSIM for in vivo experimental data.

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.

High-resolution volumetric information fusion for depth of field enhancement in photoacoustic microscopy.

Optical-resolution photoacoustic microscopy suffers from limited depth of field due to the strongly focused laser beam. Here, a novel volumetric information fusion is proposed to achieve large volumetric and high-resolution imaging. First, three-dimensional stationary wavelet transform was performed on the multi-focus data to obtain eight wavelet coefficients. Differential evolution based on joint weighted evaluation was then employed to optimize the block size of division for each wavelet coefficient. The proposed fusion rule using standard deviation for focus detection was used to fuse the corresponding sub-coefficients. Finally, photoacoustic imaging with large depth of field can be achieved by the inverse stationary wavelet transform. Performance test shows that the depth of field of photoacoustic imaging can be doubled without sacrificing lateral resolution. The proposed volumetric information fusion can further promote the capability of volumetric imaging of optical-resolution photoacoustic microscopy and will be helpful in the acquisition of physiological and pathological process.

Noise insensitive volumetric fusion method for enhanced photoacoustic microscopy.

Significance: Photoacoustic imaging is an emerging imaging modality that combines the high contrast of optical imaging and the high penetration of acoustic imaging. However, the strong focusing of the laser beam in optical-resolution photoacoustic microscopy (OR-PAM) leads to a limited depth-of-field (DoF). Aim: Here, a volumetric photoacoustic information fusion method was proposed to achieve large volumetric photoacoustic imaging at low cost. Approach: First, the initial decision map was built through the focus detection based on the proposed three-dimensional Laplacian operator. Majority filter-based consistency verification and Gaussian filter-based map smoothing were then utilized to generate the final decision map for the construction of photoacoustic imaging with extended DoF. Results: The performance of the proposed method was tested to show that our method can expand the limited DoF by a factor of 1.7 without the sacrifice of lateral resolution. Four sets of multi-focus vessel data at different noise levels were fused to verify the effectiveness and robustness of the proposed method. Conclusions: The proposed method can efficiently extend the DoF of OR-PAM under different noise levels.

Noise-insensitive defocused signal and resolution enhancement for optical-resolution photoacoustic microscopy via deep learning.

Optical-resolution photoacoustic microscopy suffers from narrow depth of field and a significant deterioration in defocused signal intensity and spatial resolution. Here, a method based on deep learning was proposed to enhance the defocused resolution and signal-to-noise ratio. A virtual optical-resolution photoacoustic microscopy based on k-wave was used to obtain the datasets of deep learning with different noise levels. A fully dense U-Net was trained with randomly distributed sources to improve the quality of photoacoustic images. The results show that the PSNR of defocused signal was enhanced by more than 1.2 times. An over 2.6-fold enhancement in lateral resolution and an over 3.4-fold enhancement in axial resolution of defocused regions were achieved. The large volumetric and high-resolution imaging of blood vessels further verified that the proposed method can effectively overcome the deterioration of the signal and the spatial resolution due to the narrow depth of field of optical-resolution photoacoustic microscopy.

Sparse-view reconstruction for photoacoustic tomography combining diffusion model with model-based iteration.

As a non-invasive hybrid biomedical imaging technology, photoacoustic tomography combines high contrast of optical imaging and high penetration of acoustic imaging. However, the conventional standard reconstruction under sparse view could result in low-quality image in photoacoustic tomography. Here, a novel model-based sparse reconstruction method for photoacoustic tomography via diffusion model was proposed. A score-based diffusion model is designed for learning the prior information of the data distribution. The learned prior information is utilized as a constraint for the data consistency term of an optimization problem based on the least-square method in the model-based iterative reconstruction, aiming to achieve the optimal solution. Blood vessels simulation data and the animal in vivo experimental data were used to evaluate the performance of the proposed method. The results demonstrate that the proposed method achieves higher-quality sparse reconstruction compared with conventional reconstruction methods and U-Net. In particular, under the extreme sparse projection (e.g., 32 projections), the proposed method achieves an improvement of ∼ 260 % in structural similarity and ∼ 30 % in peak signal-to-noise ratio for in vivo data, compared with the conventional delay-and-sum method. This method has the potential to reduce the acquisition time and cost of photoacoustic tomography, which will further expand the application range.

Multiscale photoacoustic imaging without motion using single-pixel imaging.

The conventional photoacoustic microscopy usually uses mechanical raster scanning to obtain three-dimensional information, and the imaging speed is limited. Meanwhile, the conventional photoacoustic microscopy can only be performed at one single scale due to fixed resolution, it cannot make full use of multiscale information for integrated imaging. Here, we proposed a multiscale photoacoustic microscopy based on single-pixel imaging. A sequence of sinusoidal fringes with varying spatial frequencies is used to obtain the Fourier coefficients in the case of a single ultrasonic transducer. By controlling the spatial frequency of fringe, the acquisition of Fourier coefficients can be controlled and multiscale imaging can be achieved. The feasibility of this method is verified by theory and simulation. The results show that the lateral resolution can be tuned from several microns to tens of microns without mechanical scanning. This method will expand the application of photoacoustic imaging in biomedical research.

Prospective Respiration-Gated Photoacoustic Microscopy.

OBJECTIVE: Photoacoustic microscopy (PAM) is a promising biomedical imaging technique that relies on sequential excitation to generate three-dimensional images. It combines the high contrast of optical imaging with high penetration depth of ultrasound imaging. The normal respiration rate of mice is greater than 3 Hz, which leads to motion artifacts in most reported PAM for in vivo imaging. METHODS: Here, we introduce a prospective respiratory gating (PRG) method for PAM to address this problem. We captured the mouse's respiratory signal with a laser displacement sensor, and the photoacoustic signal was acquired at specific phase points of the respiratory signal. The scanning mode and the scanning timing were also designed and evaluated. We combined this method with our PAM to demonstrate its feasibility. RESULTS: Our experiments show that the proposed method can help remove motion artifacts well, and the subcutaneous vascular imaging results of the mouse abdominal region with PRG are much better than those without any gating.