Conventional Photoacoustic Tomography Research Articles

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.

A New Deep Learning Network for Mitigating Limited-view and Under-sampling Artifacts in Ring-shaped Photoacoustic Tomography

Photoacoustic tomography (PAT) is a hybrid technique for high-resolution imaging of optical absorption in tissue. Among various transducer arrays proposed for PAT, the ring-shaped transducer array is widely used in cross-sectional imaging applications. However, due to the high fabrication cost, most ring-shaped transducer arrays have a sparse transducer arrangement, which leads to limited-view problems and under-sampling artifacts. To address these issues, we paired conventional PAT reconstruction with deep learning, which recently achieved a breakthrough in image processing and tomographic reconstruction. In this study, we designed a convolutional neural network (CNN) called a ring-array deep learning network (RADL-net), which can eliminate limited-view and under-sampling artifacts in PAT images. The method was validated on a three-quarter ring transducer array using numerical simulation, phantom imaging, and in vivo imaging. Our results indicate that the proposed RADL-net significantly improves the quality of reconstructed images on a three-quarter ring transducer array. The method is also superior to the conventional compressed sensing (CS) algorithm.

Resolution Limits in Photoacoustic Imaging Caused by Acoustic Attenuation.

In conventional photoacoustic tomography, several effects contribute to the loss of resolution, such as the limited bandwidth and the finite size of the transducer, or the space-dependent speed of sound. They can all be compensated (in principle) technically or numerically. Frequency-dependent acoustic attenuation also limits spatial resolution by reducing the bandwidth of the photoacoustic signal, which can be numerically compensated only up to a theoretical limit given by thermodynamics. The entropy production, which is the dissipated energy of the acoustic wave divided by the temperature, turns out to be equal to the information loss, which cannot be compensated for by any reconstruction method. This is demonstrated for the propagation of planar acoustic waves in water, which are induced by short laser pulses and measured by piezoelectric acoustical transducers. It turns out that for water, where the acoustic attenuation is proportional to the squared frequency, the resolution limit is proportional to the square root of the distance and inversely proportional to the square root of the logarithm of the signal-to-noise ratio. The proposed method could be used in future work for media other than water, such as biological tissue, where acoustic attenuation has a different power-law frequency dependence.

Photoacoustic Classification of Tumor Model Morphology Based on Support Vector Machine: A Simulation and Phantom Study

Precise classification to distinguish malignancy of tumors is of great significance to accomplish high specificity diagnosis and avert unnecessary biopsy. Photoacoustic tomography (PAT) is a burgeoning new imaging modality, which combines optical contrast and ultrasound penetrating in a deep medium. However, it has not been fully exploited on the capability of PAT to discriminate tumors malignancy. In this paper, a multistatic classification approach in photoacoustic is proposed, which could discriminate malignant/benign tumors based on a feature in clinical diagnosis that tumors show different shape irregularity. The multistatic photoacoustic waves extract two different features to differentiate the two types of tumor models with high accuracy in three different scenarios using Support Vector Machines. In addition, two conventional PAT image reconstructing algorithm are also performed to reconstruct images as a comparative study, which unfortunately cannot differentiate their malignancy precisely because of limited detector bandwidth and strong acoustic distortion. We performed the feasibility study in this paper with both simulation and experimental results, which shows that the proposed multistatic photoacoustic classification to distinguish between malignant and benign tumors models works well, and could be easily applied for state-of-art array-based PAT system to ameliorate the diagnostic accuracy.

High-speed, low-cost, pulsed-laser-diode-based second-generation desktop photoacoustic tomography system.

Bulky, expensive Nd:YAG lasers are used in conventional photoacoustic tomography (PAT) systems, making them difficult to translate into clinics. Moreover, real-time imaging is not feasible when a single-element ultrasound transducer is used with these low-pulse-repetition-rate lasers (10-100Hz). Low-cost pulsed laser diodes (PLDs) can be used instead for photoacoustic imaging due to their high-pulse-repetition rates and compact size. Together with acoustic-reflector-based multiple single-element ultrasound transducers, a portable desktop PAT system was developed. This second-generation PLD-based PAT achieved 0.5s cross-sectional imaging time with high spatial resolution of ∼165 μm and an imaging depth of 3cm. The performance of this system was characterized using phantom and in vivo studies. Dynamic in vivo imaging was also demonstrated by monitoring the fast uptake and clearance of indocyanine green in small animal (rat) brain vasculature.

Morphological-adaptive photoacoustic tomography with flexible transducer and flexible orientation light.

Although conventional photoacoustic tomography (PAT) provides high optical contrast and high ultrasound resolution in depth, its fixed-energy-distribution laser and unchangeable-shaped detector hinder its implementations on clinical routine breast screening. In this Letter, for the first time, to the best of our knowledge, we present a fully flexible photoacoustic coupling system (FPACS) that integrates optical fiber bundles and a flexible ultrasonic transducer for morphological-adaptive breast detection. The experimental results show that the system has better resolution and higher energy utilization than traditional PAT systems, even at the edge of the imaging region. Moreover, the system can achieve morphological adaption, suggesting that the FPACS provides the potential for clinical routine breast screening.

Use of acoustic reflector to make a compact photoacoustic tomography system.

A typical photoacoustic tomography (PAT) system uses a Q-switched Nd:YAG laser for irradiating the sample and a single-element ultrasound transducer (UST) for acquiring the photoacoustic data. Conventionally, in PAT systems, the UST is held in a horizontal position and moved in a circular motion around the sample in full 2 ? radians. Horizontal positioning of the UST requires a large water tank to house, and load on the motor is also high. To overcome this limitation, we used the UST in the vertical plane instead of the horizontal plane. The photoacoustic (PA) waves generated from the sample are directed to the detector surface using an acoustic reflector placed at 45 deg to the transducer body. Hence, we can reduce the scanning radius, which, in turn, will reduce the size of the water tank and load on the motor, and the overall conventional PAT system size can be minimized. In this work, we demonstrate that with this system configuration, we acquire nearly similar images for phantom and in vivo data as that of the conventional PAT system using both flat and focused USTs.

Two schemes for quantitative photoacoustic tomography based on Monte Carlo simulation.

The aim of this study was to develop novel methods for photoacoustically determining the optical absorption coefficient of biological tissues using Monte Carlo (MC) simulation. In this study, the authors propose two quantitative photoacoustic tomography (PAT) methods for mapping the optical absorption coefficient. The reconstruction methods combine conventional PAT with MC simulation in a novel way to determine the optical absorption coefficient of biological tissues or organs. Specifically, the authors' two schemes were theoretically and experimentally examined using simulations, tissue-mimicking phantoms, ex vivo, and in vivo tests. In particular, the authors explored these methods using several objects with different absorption contrasts embedded in turbid media and by using high-absorption media when the diffusion approximation was not effective at describing the photon transport. The simulations and experimental tests showed that the reconstructions were quantitatively accurate in terms of the locations, sizes, and optical properties of the targets. The positions of the recovered targets were accessed by the property profiles, where the authors discovered that the off center error was less than 0.1 mm for the circular target. Meanwhile, the sizes and quantitative optical properties of the targets were quantified by estimating the full width half maximum of the optical absorption property. Interestingly, for the reconstructed sizes, the authors discovered that the errors ranged from 0 for relatively small-size targets to 26% for relatively large-size targets whereas for the recovered optical properties, the errors ranged from 0% to 12.5% for different cases. The authors found that their methods can quantitatively reconstruct absorbing objects of different sizes and optical contrasts even when the diffusion approximation is unable to accurately describe the photon propagation in biological tissues. In particular, their methods are able to resolve the intrinsic difficulties that occur when quantitative PAT is conducted by combining conventional PAT with the diffusion approximation or with radiation transport modeling.

Listening to light scattering in turbid media: quantitative optical scattering imaging using photoacoustic measurements with one-wavelength illumination

Biomedical photoacoustic tomography (PAT), as a potential imaging modality, can visualize tissue structure and function with high spatial resolution and excellent optical contrast. It is widely recognized that the ability of quantitatively imaging optical absorption and scattering coefficients from photoacoustic measurements is essential before PAT can become a powerful imaging modality. Existing quantitative PAT (qPAT), while successful, has been focused on recovering absorption coefficient only by assuming scattering coefficient a constant. An effective method for photoacoustically recovering optical scattering coefficient is presently not available. Here we propose and experimentally validate such a method for quantitative scattering coefficient imaging using photoacoustic data from one-wavelength illumination. The reconstruction method developed combines conventional PAT with the photon diffusion equation in a novel way to realize the recovery of scattering coefficient. We demonstrate the method using various objects having scattering contrast only or both absorption and scattering contrasts embedded in turbid media. The listening-to-light-scattering method described will be able to provide high resolution scattering imaging for various biomedical applications ranging from breast to brain imaging.

Image reconstruction in intravascular photoacoustic imaging

Intravascular photoacoustic (IVPA) imaging is a technique for visualizing atherosclerotic plaques with differential composition. Unlike conventional photoacoustic tomography scanning, where the scanning device rotates around the subject, the scanning aperture in IVPA imaging is enclosed within the imaged object. The display of the intravascular structure is typically obtained by converting detected photoacoustic waves into Cartesian coordinates, which can produce images with severe artifacts. Because the acquired data are highly limited, there does not exist a stable reconstruction algorithm for such imaging geometry. The purpose of this work was to apply image reconstruction concepts to explore the feasibility and efficacy of image reconstruction algorithms in IVPA imaging using traditional analytical formulas, such as a filtered back-projection (FBP) and the lambda-tomography method. Although the closed-form formulas are not exact for the IVPA system, a general picture of and interface information about objects are provided. To improve the quality of the reconstructed image, the iterative expectation maximization and penalized least-squares methods were adopted to minimize the difference between the measured signals and those generated by a reconstructed image. In this work, we considered both the ideal point detector and the acoustic transducers with finite- size aperture. The transducer effects including the spatial response of aperture and acoustoelectrical impulse responses were incorporated in the system matrix to reduce the aroused distortion in the IVPA reconstruction. Computer simulations and experiments were carried out to validate the methods. The applicability and the limitation of the reconstruction method were also discussed.

Photoacoustic image reconstruction from few-detector and limited-angle data

Photoacoustic tomography (PAT) is an emerging non-invasive imaging technique with great potential for a wide range of biomedical imaging applications. However, the conventional PAT reconstruction algorithms often provide distorted images with strong artifacts in cases when the signals are collected from few measurements or over an aperture that does not enclose the object. In this work, we present a total-variation-minimization (TVM) enhanced iterative reconstruction algorithm that can provide excellent photoacoustic image reconstruction from few-detector and limited-angle data. The enhancement is confirmed and evaluated using several phantom experiments.

Tomographic imaging of absolute optical absorption coefficient in turbid media using combined photoacoustic and diffusing light measurements

We present a new method that can provide high resolution images of absolute optical absorption coefficient in heterogeneous turbid media. In this method, acoustic measurements in conventional photoacoustic tomography are combined with diffusing light measurements to separate the product of absorption coefficient and optical fluence or photon density. We validate this method using a series of tissuelike phantom experiments. The experimental results show that targets as small as 0.5 mm in diameter with optical absorption contrasts as low as 1.5 relative to a 50 mm diameter scattering background medium can be clearly detected.

Reconstruction of optical absorption coefficient maps of heterogeneous media by photoacoustic tomography coupled with diffusion equation based regularized Newton method

We describe a novel reconstruction method that allows for quantitative recovery of optical absorption coefficient maps of heterogeneous media using tomographic photoacoustic measurements. Images of optical absorption coefficient are obtained from a diffusion equation based regularized Newton method where the absorbed energy density distribution from conventional photoacoustic tomography serves as the measured field data. We experimentally demonstrate this new method using tissue-mimicking phantom measurements and simulations. The reconstruction results show that the optical absorption coefficient images obtained are quantitative in terms of the shape, size, location and optical property values of the heterogeneities examined.