Method For Photoacoustic Tomography Research Articles

Multiscale photoacoustic tomography using reversibly switchable thermochromics.

Based on acoustic detection of optical absorption, photoacoustic tomography (PAT) allows functional and molecular imaging beyond the optical diffusion limit with high spatial resolution. However, multispectral functional and molecular PAT is often limited by decreased spectroscopic accuracy and reduced detection sensitivity in deep tissues, mainly due to wavelength-dependent optical attenuation and inaccurate acoustic inversion. Previous work has demonstrated that reversible color-shifting can drastically improve the detection sensitivity of PAT by suppressing nonswitching background signals. We aim to develop a new color switching-based PAT method using reversibly switchable thermochromics (ReST). We developed a family of ReST with excellent water dispersion, biostability, and temperature-controlled color changes by surface modification of commercial thermochromic microcapsules with the hydrophilic polysaccharide alginate. The optical absorbance of the ReST was switched on and off repeatedly by modulating the surrounding temperature, allowing differential photoacoustic detection that effectively suppressed the nonswitching background signal and substantially improved image contrast and detection sensitivity. We demonstrate reversible thermal-switching imaging of ReST in vitro and in vivo using three PAT modes at different length scales. ReST-enabled PAT is a promising technology for high-sensitivity deep tissue imaging of molecular activity in temperature-related biomedical applications, such as cancer thermotherapy.

The researches on convolutional beamforming for linear-array photoacoustic tomography

The convolutional beamforming algorithm (COBA) which can be easily implemented by fast Fourier transform (FFT) and is suitable for real-time photoacoustic tomography (PAT) is introduced. In order to reveal the imaging effects of COBA, the photoacoustic images reconstructed by COBA, delay-and-sum algorithm (DAS), and minimum variance (MV) are investigated. The results demonstrate that the COBA significantly improves the lateral resolution and the contrast of the photoacoustic images. Moreover, the coherence factor (CF) as an adaptive weighting is used in COBA, the combined method shows that better lateral resolution and contrast of photoacoustic images can be obtained, which can be a potential imaging method for linear-array PAT.

A Deep Learning Approach for the Photoacoustic Tomography Recovery From Undersampled Measurements.

Photoacoustic tomography (PAT) is a propitious imaging modality, which is helpful for biomedical study. However, fast PAT imaging and denoising is an exigent task in medical research. To address the problem, recently, methods based on compressed sensing (CS) have been proposed, which accede the low computational cost and high resolution for implementing PAT. Nevertheless, the imaging results of the sparsity-based methods strictly rely on sparsity and incoherence conditions. Furthermore, it is onerous to ensure that the experimentally acquired photoacoustic data meets CS’s prerequisite conditions. In this work, a deep learning–based PAT (Deep-PAT)method is instigated to overcome these limitations. By using a neural network, Deep-PAT is not only able to reconstruct PAT from a fewer number of measurements without considering the prerequisite conditions of CS, but also can eliminate undersampled artifacts effectively. The experimental results demonstrate that Deep-PAT is proficient at recovering high-quality photoacoustic images using just 5% of the original measurement data. Besides this, compared with the sparsity-based method, it can be seen through statistical analysis that the quality is significantly improved by 30% (approximately), having average SSIM = 0.974 and PSNR = 29.88 dB with standard deviation ±0.007 and ±0.089, respectively, by the proposed Deep-PAT method. Also, a comparsion of multiple neural networks provides insights into choosing the best one for further study and practical implementation.

Noninvasive Photoacoustic and Fluorescence Sentinel Lymph Node Identification using Dye-Loaded Perfluorocarbon Nanoparticles

The contrast mechanisms used for photoacoustic tomography (PAT) and fluorescence imaging differ in subtle, but significant, ways. The design of contrast agents for each or both modalities requires an understanding of the spectral characteristics as well as intra- and intermolecular interactions that occur during formulation. We found that fluorescence quenching that occurs in the formulation of near-infrared (NIR) fluorescent dyes in nanoparticles results in enhanced contrast for PAT. The ability of the new PAT method to utilize strongly absorbing chromophores for signal generation allowed us to convert a highly fluorescent dye into an exceptionally high PA contrast material. Spectroscopic characterization of the developed NIR dye-loaded perfluorocarbon-based nanoparticles for combined fluorescence and PA imaging revealed distinct dye-dependent photophysical behavior. We demonstrate that the enhanced contrast allows detection of regional lymph nodes of rats in vivo with time-domain optical and photoacoustic imaging methods. The results further show that the use of fluorescence lifetime imaging, which is less dependent on fluorescence intensity, provides a strategic approach to bridge the disparate contrast reporting mechanisms of fluorescence and PA imaging methods.

Quantitative three-dimensional photoacoustic tomography of the finger joints: an in vivo study.

We present for the first time in vivo full three-dimensional (3-D) photoacoustic tomography (PAT) of the distal interphalangeal joint in a human subject. Both absorbed energy density and absorption coefficient images of the joint are quantitatively obtained using our finite-element-based photoacoustic image reconstruction algorithm coupled with the photon diffusion equation. The results show that major anatomical features in the joint along with the side arteries can be imaged with a 1-MHz transducer in a spherical scanning geometry. In addition, the cartilages associated with the joint can be quantitatively differentiated from the phalanx. This in vivo study suggests that the 3-D PAT method described has the potential to be used for early diagnosis of joint diseases such as osteoarthritis and rheumatoid arthritis.

Imaging of laser induced ultrasound with a spiral phase contrast method

Optical snapshot images of photo-acoustically generated sound waves in a water tank can be obtained by 'spiral phase contrast filtering', a variant of phase contrast imaging. To this end a two-dimensional transmission image of the ultrasonic field is recorded by illuminating the water volume by an expanded nanosecond laser pulse, and guiding the transmitted beam through a spiral phase plate (SPP) placed in a Fourier plane of the optical path. This generates a strong intensity contrast at gradients of the refractive index, corresponding to acoustically induced pressure gradients in the liquid. As an advantage with respect to a standard knife-edge Schlieren method, the spiral phase filter provides an isotropic contrast enhancement of refractive index modulations. Thus the method has the potential to act as a fast imaging method for photo-acoustic tomography.

Experimental evaluation of reconstruction algorithms for limited view photoacoustic tomography with line detectors

A method for photoacoustic tomography is presented that uses line integrals over the acoustic wave field from a photoacoustic source for the reconstruction of a three-dimensional image. The line integrals are acquired with an optical line sensor based on a Mach–Zehnder interferometer. Image reconstruction is a two-step process. In the first step data from a scan of the line outside the object are used to reconstruct a linear projection of the source distribution. In the second step the inverse linear Radon transform is applied to multiple projections taken at different directions. This study focuses on the first step comparing two different open scan curves of the line detector around the object and corresponding two-dimensional reconstruction algorithms. An open curve, such as a 180° arc or an ‘L’ formed by two lines, establishes a limited view problem for which limitations exist concerning the stability of the reconstruction. Using experimental data from phantoms, time domain direct and iterative reconstruction algorithms as well as frequency domain (FD) algorithms are compared. The results indicate that although the image quality for all algorithms is similar, the FD algorithms offer much faster reconstruction speed, whereas the time domain algorithms allow for a refinement of image quality by including special correction procedures.

Finite-element-based photoacoustic tomography: phantom and chicken bone experiments

We describe a photoacoustic image reconstruction algorithm that is based on the finite-element solution to the photoacoustic wave equation in the frequency domain. Our reconstruction approach is an iterative Newton method coupled with combined Marquardt and Tikhonov regularizations that can extract the spatial distribution of optical-absorption property in heterogeneous media. We demonstrate this algorithm by using phantom and chicken bone measurements from a circular scanning photoacoustic tomography system. The results obtained show that millimeter-sized phantom objects and chicken bones and/or joints can be clearly detected using our finite-element-based photoacoustic tomography method.

Exact series reconstruction in photoacoustic tomography with circular integrating detectors

A method for photoacoustic tomography is presented that uses circular integrals of the acoustic wave for the reconstruction of a three-dimensional image. Image reconstruction is a two-step process: In the first step data from a stack of circular integrating detectors are used to reconstruct the circular projection of the source distribution. In the second step the inverse circular Radon transform is applied. In this article we establish inversion formulas for the first step, which involves an inverse problem for the axially symmetric wave equation. Numerical results are presented that show the validity and robustness of the resulting algorithm.