Spatial resolution in photoacoustic computed tomography

Image restoration for ring-array photoacoustic tomography system based on blind spatially rotational deconvolution

Ring-array photoacoustic tomography (PAT) system has been widely used in noninvasive biomedical imaging. However, the reconstructed image usually suffers from spatially rotational blur and streak artifacts due to the non-ideal imaging conditions. To improve the reconstructed image towards higher quality, we propose a concept of spatially rotational convolution to formulate the image blur process, then we build a regularized restoration problem model accordingly and design an alternating minimization algorithm which is called blind spatially rotational deconvolution to achieve the restored image. Besides, we also present an image preprocessing method based on the proposed algorithm to remove the streak artifacts. We take experiments on phantoms and in vivo biological tissues for evaluation, the results show that our approach can significantly enhance the resolution of the image obtained from ring-array PAT system and remove the streak artifacts effectively.

Data-driven method of super-resolution image recovery for speckle-illumination photoacoustic computed tomography

Methods have been proposed in recent years aimed at pushing photoacoustic imaging resolution beyond the acoustic diffraction limit, among which those based on random speckle illumination show particular promise. In this Letter, we propose a data-driven deep learning approach to processing the added spatiotemporal information resulting from speckle illumination, where the neural network learns the distribution of absorbers from a series of different samplings of the imaged area. In ex-vivo experiments based on the tomography configuration with prominent artifacts, our method successfully breaks the acoustic diffraction limit and delivers better results in identifying individual targets when compared against a selection of other leading methods.

Sub-Nyquist sampling-based high-frequency photoacoustic computed tomography

High-frequency (greater than 30 MHz) photoacoustic computed tomography (PACT) provides the opportunity to reveal finer details of biological tissues with high spatial resolution. To record photoacoustic signals above 30 MHz, sampling rates higher than 60 MHz are required according to the Nyquist sampling criterion. However, the highest sampling rates supported by existing PACT systems are typically within the range of 40-60 MHz. Herein, we propose a novel PACT imaging method based on sub-Nyquist sampling. The results of numerical simulation, phantom experiment, and in vivo experiment demonstrate that the proposed imaging method can achieve high-frequency PACT imaging with a relatively low sampling rate. An axial resolution of 22 μm is achieved with a 30-MHz transducer and a 41.67-MHz sampling rate. To the best of our knowledge, this is the highest axial resolution ever achieved in PACT based on a sampling rate of not greater than 60 MHz. This work is expected to provide a practical way for high-frequency PACT imaging with limited sampling rates.

Multi-Scale Volumetric Dynamic Optoacoustic and Laser Ultrasound (OPLUS) Imaging Enabled by Semi-Transparent Optical Guidance

Major biological discoveries are made by interrogating living organisms with light. However, the limited penetration of un-scattered photons within biological tissues limits the depth range covered by optical methods. Deep-tissue imaging is achieved by combining light and ultrasound. Optoacoustic imaging exploits the optical generation of ultrasound to render high-resolution images at depths unattainable with optical microscopy. Recently, laser ultrasound has been suggested as a means of generating broadband acoustic waves for high-resolution pulse-echo ultrasound imaging. Herein, an approach is proposed to simultaneously interrogate biological tissues with light and ultrasound based on layer-by-layer coating of silica optical fibers with a controlled degree of transparency. The time separation between optoacoustic and ultrasound signals collected with a custom-made spherical array transducer is exploited for simultaneous 3D optoacoustic and laser ultrasound (OPLUS) imaging with a single laser pulse. OPLUS is shown to enable large-scale anatomical characterization of tissues along with functional multi-spectral imaging of chromophores and assessment of cardiac dynamics at ultrafast rates only limited by the pulse repetition frequency of the laser. The suggested approach provides a flexible and scalable means for developing a new generation of systems synergistically combining the powerful capabilities of optoacoustics and ultrasound imaging in biology and medicine.

High-frequency surface-micromachined optical ultrasound transducer array for 3D micro photoacoustic computed tomography

This Letter reports a new, to the best of our knowledge, high-frequency surface-micromachined optical ultrasound transducer (HF-SMOUT) array for micro photoacoustic computed tomography (µPACT). An 11 × 11 mm2 2D array of 220 × 220 elements (35 µm in diameter) is designed, fabricated, and characterized. The optical resonance wavelength (ORW) of ≥90% of the elements falls within a 6-nm range. The acoustic center frequency and bandwidth of the elements are ∼14 MHz and ∼18 MHz (129%), respectively. The noise equivalent pressure (NEP) is 161 Pa (or 18 m P a/H z) within a measurement bandwidth of 5-75 MHz. The standard deviation of the ORW drift is 0.45 nm and 0.93 nm within 25°C-55°C, respectively, and during a seven-day continuous water immersion. PACT experiments are conducted to evaluate the imaging performances of the HF-SMOUT array. The spatial resolution is estimated as 90 µm (axial) and 250-750 µm (lateral) within a 10 × 10 mm2 field of view (FoV) and the imaging depth of 16 mm. A 3D PA image of a knotted black hair target is also successfully acquired. These results demonstrate the feasibility of using the HF-SMOUT array for µPACT applications.

On the imaging depth limit of photoacoustic tomography in the visible and first near-infrared windows

It is well known that photoacoustic tomography (PAT) can circumvent the photon scattering problem in optical imaging and achieve high-contrast and high-resolution imaging at centimeter depths. However, after two decades of development, the long-standing question of the imaging depth limit of PAT in biological tissues remains unclear. Here we propose a numerical framework for evaluating the imaging depth limit of PAT in the visible and the first near-infrared windows. The established framework simulates the physical process of PAT and consists of seven modules, including tissue modelling, photon transportation, photon to ultrasound conversion, sound field propagation, signal reception, image reconstruction, and imaging depth evaluation. The framework can simulate the imaging depth limits in general tissues, such as the human breast, the human abdomen-liver tissues, and the rodent whole body and provide accurate evaluation results. The study elucidates the fundamental imaging depth limit of PAT in biological tissues and can provide useful guidance for practical experiments.

Point spread function modeling for photoacoustic tomography - I: three-dimensional detection geometries

Photoacoustic computed tomography (PACT) has been under intensive investigation as a promising noninvasive biomedical imaging modality. Various acoustic detector arrays have been developed to achieve enhanced imaging performance. In this paper, we study the effect of the detection geometry on image quality through point spread function (PSF) modeling based on back-projection image reconstruction. Three commonly-used three-dimensional detection geometries, namely, spherical, cylindrical, and planar detector arrays, are investigated. The effect of detector bandwidth and aperture on PSF in these detection geometries is also studied. This work provides a performance evaluation tool for acoustic detector arrays used in PACT and can be helpful in the design and selection of detector arrays in practical imaging applications.

Influence mechanism of the temporal duration of laser irradiation on photoacoustic technique: a review

Significance

In the photoacoustic (PA) technique, the laser irradiation in the time domain (i.e., laser pulse duration) governs the characteristics of PA imaging-it plays a crucial role in the optical-acoustic interaction, the generation of PA signals, and the PA imaging performance.

Aim

We aim to provide a comprehensive analysis of the impact of laser pulse duration on various aspects of PA imaging, encompassing the signal-to-noise ratio, the spatial resolution of PA imaging, the acoustic frequency spectrum of the acoustic wave, the initiation of specific physical phenomena, and the photothermal-PA (PT-PA) interaction/conversion.

Approach

By surveying and reviewing the state-of-the-art investigations, we discuss the effects of laser pulse duration on the generation of PA signals in the context of biomedical PA imaging with respect to the aforementioned aspects.

Results

First, we discuss the impact of laser pulse duration on the PA signal amplitude and its correlation with the lateral resolution of PA imaging. Subsequently, the relationship between the axial resolution of PA imaging and the laser pulse duration is analyzed with consideration of the acoustic frequency spectrum. Furthermore, we examine the manipulation of the pulse duration to trigger physical phenomena and its relevant applications. In addition, we elaborate on the tuning of the pulse duration to manipulate the conversion process and ratio from the PT to PA effect.

Conclusions

We contribute to the understanding of the physical mechanisms governing pulse-width-dependent PA techniques. By gaining insight into the mechanism behind the influence of the laser pulse, we can trigger the pulse-with-dependent physical phenomena for specific PA applications, enhance PA imaging performance in biomedical imaging scenarios, and modulate PT-PA conversion by tuning the pulse duration precisely.

In vivo monitoring of hemodynamic changes in ischemic stroke using photoacoustic tomography

Ischemic stroke occurs when a blood vessel supplying the brain is blocked, leading to decreased blood flow. Early diagnosis and treatment are crucial. However, existing clinical imaging methods have limitations, such as safety issues and low time resolution. To address these challenges, we propose using photoacoustic tomography (PAT) with a contrast agent, known for its high resolution and contrast capabilities. Our study involved imaging brain vasculature in three groups: normal, unilateral common carotid artery ligation (UCAL), and middle cerebral artery occlusion (MCAO). On the ischemic stroke side, we observed reduced blood vessel density and hemodynamic changes were evident after injecting indocyanine green for PAT. The photoacoustic intensity was notably lower in the ligated sides of the UCAL and MCAO groups, with statistically significant differences between the three groups. This work highlights PAT's potential as a powerful tool for early diagnosis and guidance in ischemic stroke cases.

Spatially-variant image deconvolution for photoacoustic tomography

Photoacoustic tomography (PAT) system can reconstruct images of biological tissues with high resolution and contrast. However, in practice, the PAT images are usually degraded by spatially variant blur and streak artifacts due to the non-ideal imaging conditions and chosen reconstruction algorithms. Therefore, in this paper, we propose a two-phase restoration method to progressively improve the image quality. In the first phase, we design a precise device and measuring method to obtain spatially variant point spread function samples at preset positions of the PAT system in image domain, then we adopt principal component analysis and radial basis function interpolation to model the entire spatially variant point spread function. Afterwards, we propose a sparse logarithmic gradient regularized Richardson-Lucy (SLG-RL) algorithm to deblur the reconstructed PAT images. In the second phase, we present a novel method called deringing which is also based on SLG-RL to remove the streak artifacts. Finally, we evaluate our method with simulation, phantom and in vivo experiments, respectively. All the results show that our method can significantly improve the quality of PAT images.

The sound of blood: photoacoustic imaging in blood analysis

Blood analysis is a ubiquitous and critical aspect of modern medicine. Analyzing blood samples requires invasive techniques, various testing systems, and samples are limited to relatively small volumes. Photoacoustic imaging (PAI) is a novel imaging modality that utilizes non-ionizing energy that shows promise as an alternative to current methods. This paper seeks to review current applications of PAI in blood analysis for clinical use. Furthermore, we discuss obstacles to implementation and future directions to overcome these challenges. Firstly, we discuss three applications to cellular analysis of blood: sickle cell, bacteria, and circulating tumor cell detection. We then discuss applications to the analysis of blood plasma, including glucose detection and anticoagulation quantification. As such, we hope this article will serve as inspiration for PAI's potential application in blood analysis and prompt further studies to ultimately implement PAI into clinical practice.

Full-view LED-based optoacoustic tomography

Optoacoustic tomography is commonly performed with bulky and expensive short-pulsed solid-state lasers providing high per-pulse energies in the millijoule range. Light emitting diodes (LEDs) represent a cost-effective and portable alternative for optoacoustic signal excitation that can additionally provide excellent pulse-to-pulse stability. Herein, we introduce a full-view LED-based optoacoustic tomography (FLOAT) system for deep tissue in vivo imaging. It is based on a custom-made electronic unit driving a stacked array of LEDs, which attains 100 ns pulse width and highly stable (0.62 % standard deviation) total per-pulse energy of 0.48 mJ. The illumination source is integrated into a circular array of cylindrically-focused ultrasound detection elements to result in a full-view tomographic configuration, which plays a critical role in circumventing limited-view effects, enhancing the effective field-of-view and image quality for cross-sectional (2D) imaging. We characterized the FLOAT performance in terms of pulse width, power stability, excitation light distribution, signal-to-noise and penetration depth. FLOAT of the human finger revealed a comparable imaging performance to that achieved with the standard pulsed Nd:YAG laser. It is anticipated that this compact, affordable and versatile illumination technology will facilitate optoacoustic imaging developments in resource-limited settings for biological and clinical applications.

Streak artifact suppressed back projection for sparse-view photoacoustic computed tomography

The development of fast and accurate image reconstruction algorithms under constrained data acquisition conditions is important for photoacoustic computed tomography (PACT). Sparse-view measurements have been used to accelerate data acquisition and reduce system complexity; however, reconstructed images suffer from sparsity-induced streak artifacts. In this paper, a modified back-projection (BP) method termed anti-streak BP is proposed to suppress streak artifacts in sparse-view PACT reconstruction. During the reconstruction process, the anti-streak BP finds the back-projection terms contaminated by high-intensity sources with an outlier detection method. Then, the weights of the contaminated back-projection terms are adaptively adjusted to eliminate the effects of high-intensity sources. The proposed anti-streak BP method is compared with the conventional BP method on both simulation and in vivo data. The anti-streak BP method shows substantially fewer artifacts in the reconstructed images, and the streak index is 54% and 20% lower than that of the conventional BP method on simulation and in vivo data, when the transducer number N=128. The anti-streak BP method is a powerful improvement of the BP method with the ability of artifact suppression.

Application of photoacoustic computed tomography in biomedical imaging: A literature review

Photoacoustic computed tomography (PACT) is a hybrid imaging modality that combines optical excitation and acoustic detection techniques. It obtains high-resolution deep-tissue images based on the deep penetration of light, the anisotropy of light absorption in objects, and the photoacoustic effect. Hence, PACT shows great potential in biomedical sample imaging. Recently, due to its advantages of high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth, PACT has received increasing attention in preclinical and clinical practice. To date, there has been a proliferation of PACT systems designed for specific biomedical imaging applications, from small animals to human organs, from ex vivo to in vivo real-time imaging, and from simple structural imaging to functional and molecular imaging with external contrast agents. Therefore, it is of great importance to summarize the previous applications of PACT systems in biomedical imaging and clinical practice. In this review, we searched for studies related to PACT imaging of biomedical tissues and samples over the past two decades; divided the studies into two categories, PACT imaging of preclinical animals and PACT imaging of human organs and body parts; and discussed the significance of the studies. Finally, we pointed out the future directions of PACT in biomedical applications. With the development of exogenous contrast agents and advances of imaging technique, in the future, PACT will enable biomedical imaging from organs to whole bodies, from superficial vasculature to internal organs, from anatomy to functions, and will play an increasingly important role in biomedical research and clinical practice.

Sound out the impaired perfusion: Photoacoustic imaging in preclinical ischemic stroke

Acoustically detecting the optical absorption contrast, photoacoustic imaging (PAI) is a highly versatile imaging modality that can provide anatomical, functional, molecular, and metabolic information of biological tissues. PAI is highly scalable and can probe the same biological process at various length scales ranging from single cells (microscopic) to the whole organ (macroscopic). Using hemoglobin as the endogenous contrast, PAI is capable of label-free imaging of blood vessels in the brain and mapping hemodynamic functions such as blood oxygenation and blood flow. These imaging merits make PAI a great tool for studying ischemic stroke, particularly for probing into hemodynamic changes and impaired cerebral blood perfusion as a consequence of stroke. In this narrative review, we aim to summarize the scientific progresses in the past decade by using PAI to monitor cerebral blood vessel impairment and restoration after ischemic stroke, mostly in the preclinical setting. We also outline and discuss the major technological barriers and challenges that need to be overcome so that PAI can play a more significant role in preclinical stroke research, and more importantly, accelerate its translation to be a useful clinical diagnosis and management tool for human strokes.

Learned regularization for image reconstruction in sparse-view photoacoustic tomography

Constrained data acquisitions, such as sparse view measurements, are sometimes used in photoacoustic computed tomography (PACT) to accelerate data acquisition. However, it is challenging to reconstruct high-quality images under such scenarios. Iterative image reconstruction with regularization is a typical choice to solve this problem but it suffers from image artifacts. In this paper, we present a learned regularization method to suppress image artifacts in model-based iterative reconstruction in sparse view PACT. A lightweight dual-path network is designed to learn regularization features from both the data and the image domains. The network is trained and tested on both simulation and in vivo datasets and compared with other methods such as Tikhonov regularization, total variation regularization, and a U-Net based post-processing approach. Results show that although the learned regularization network possesses a size of only 0.15% of a U-Net, it outperforms other methods and converges after as few as five iterations, which takes less than one-third of the time of conventional methods. Moreover, the proposed reconstruction method incorporates the physical model of photoacoustic imaging and explores structural information from training datasets. The integration of deep learning with a physical model can potentially achieve improved imaging performance in practice.

Improved photoacoustic images via wavefront shaping modulation based on the scattering structure

Multispectral optoacoustic tomography (MSOT) has become the dominant technical solution for photoacoustic imaging (PAI). However, the laser source of fiber output in the current MSOT method is typically a TEM00 Gaussian beam, which is prone to artifacts and incomplete due to the uneven distribution of the irradiated light intensity. Here, we propose a novel method to improve the quality of photoacoustic image reconstruction by modulating the wavefront shaping of the incident laser beam based on the designed scattering structure. In the experiment, we add the designed scattering structure to the current hemispherical photoacoustic transducer array device. Through experiments and simulations, we investigate and compare the effects of different scattering structures on laser intensity modulation. The results show that an ED1-C20 diffusion structure with a scattering angle of 20 degrees has the most effective modulation of the beam intensity distribution. And we choose gold nanoparticles of 50-100 nanometers (nm) diameters and index finger capillary vessels respectively as the medium of PAI. We obtain the highest ratio of PAI area increases of gold nanoparticles and index finger to devices compare without scattering structure is 29.69% and 634.94%, respectively. Experimental results demonstrate that our method is significantly higher quality than traditional methods, which has great potential for theoretical application in medical PAI.

Ultrasound-guided adaptive photoacoustic tomography

Image formation in photoacoustic tomography (PAT) is generally based on the assumption that biological tissues are acoustically homogeneous. However, this does not hold, especially when strongly heterogeneous tissues, such as bones and air cavities, are present. Tissue heterogeneity can cause acoustic reflection, refraction, and scattering at interfaces, which may create distortions and artifacts in final images. To mitigate this problem, we propose an adaptive photoacoustic (PA) image reconstruction method based on prior structural information of an acoustically heterogeneous region extracted from ultrasound images. The method works in three steps: acoustic heterogeneity identification via ultrasound imaging; acoustically heterogeneous region segmentation; and adaptive time-domain raw data truncation and image reconstruction. The data truncation is based on a variable cutoff time, which can be adaptively determined according to the relative position of a transducer and an acoustically heterogeneous region. Numerical and in vivo experimental imaging results of human fingers demonstrate that the proposed ultrasound-guided adaptive image reconstruction method can effectively suppress acoustic heterogeneity-induced artifacts and substantially improve image quality. This work provides a practical way to mitigate the influence of acoustic heterogeneity in PAT.

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.