Photoacoustic clutter reduction by inversion of a linear scatter model using plane wave ultrasound measurements

Performance evaluation of mesoscopic photoacoustic imaging

Photoacoustic mesoscopy visualises vascular architecture at high-resolution up to ~3 mm depth. Despite promise in preclinical and clinical imaging studies, with applications in oncology and dermatology, the accuracy and precision of photoacoustic mesoscopy is not well established. Here, we evaluate a commercial photoacoustic mesoscopy system for imaging vascular structures. Typical artefact types are first highlighted and limitations due to non-isotropic illumination and detection are evaluated with respect to rotation, angularity, and depth of the target. Then, using tailored phantoms and mouse models, we investigate system precision, showing coefficients of variation (COV) between repeated scans [short term (1 h): COV= 1.2%; long term (25 days): COV= 9.6%], from target repositioning (without: COV=1.2%, with: COV=4.1%), or from varying in vivo user experience (experienced: COV=15.9%, unexperienced: COV=20.2%). Our findings show robustness of the technique, but also underscore general challenges of limited-view photoacoustic systems in accurately imaging vessel-like structures, thereby guiding users when interpreting biologically-relevant information.

Optimized Reconstruction Procedure of Photoacoustic Imaging for Reflection Artifacts Reduction

Photoacoustic (PA) imaging technology is of some value in medical diagnoses such as breast cancer detection, vasculature imaging, and surgery navigating. While as most imaging objects are bounded, the received RF signals consist of the direct-arrived signals (DAS) from the PA sources and the boundary-reflected signals (BRS). The undesired BRS will severely impair the quality during the image reconstruction. They will bring in many artifacts and confuse the actual shape and location of the PA sources. We improved the reconstruction procedure by removing the BRS before the regular reconstruction process to suppress those artifacts. To verify our proposed method, we compared the results of the conventional and optimized procedures experimentally. In terms of qualitative observation, the reconstructed images by the optimized procedure illustrate fewer artifacts and more accurate shapes of the PA sources. To quantitatively evaluate the traditional and the optimized imaging procedure, we calculated the Distribution Relative Error (DRE) between each experiment result and its standard drawing of the phantoms. For both phantoms and the ex-vivo sample, the DREs of reconstruction result by the optimized reconstruction procedure decrease significantly. The results suggest that the optimized reconstruction process can effectively suppress the reflection artifacts and improve the shape accuracy of the PA sources.

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.

Suppression of acoustic reflection artifact in endoscopic photoacoustic tomographic images based on approximation of ideal signals

BACKGROUND:

In endoscopic photoacoustic tomography (EPAT), the photoacoustically induced ultrasonic wave reflects at tissue boundaries due to the acoustic inhomogeneity of the imaged tissue, resulting in reflection artifacts (RAs) in the reconstructed images.

OBJECTIVE:

To suppress RAs in EPAT image reconstruction for improving the image quality.

METHODS:

A method was presented to render the cross-sectional images of the optical absorption with reduced RAs from acoustic measurements. The ideal photoacoustic signal was recovered from acoustic signals collected by the detector through solving a least square problem. Then, high-quality images of the optical absorption distribution were reconstructed from the ideal signal.

RESULTS:

The results demonstrated the improvement in the quality of the images rendered by this method in comparison with the conventional back-projection (BP) reconstructions. Compared with the short lag spatial coherence (SLSC) method, the peak signal-to-noise ratio (PSNR), normalized mean square absolute distance (NMSAD), and structural similarity (SSIM) were improved by up to 8%, 20%, and 5%, respectively.

CONCLUSIONS:

This method was capable of rendering images displaying the complex tissue types with reduced RAs and lower computational burden in comparison with previously developed methods.

Feasibility of identifying reflection artifacts in photoacoustic imaging using two-wavelength excitation

One of the remaining challenges of bringing photoacoustic imaging to clinics is the occurrence of reflection artifacts. Previously, we proposed a method using multi-wavelength excitation to identify and remove the RAs. However, this method requires at least 3 wavelengths. Here we improve the method further by reducing the required number of wavelengths to 2. We experimentally demonstrate this new method and compare it with the previous one. Results show that this new method holds great feasibility for identifying reflection artifacts in addition to preserving all advantages of the previous method.

Photoacoustic imaging for surgical guidance: Principles, applications, and outlook

Minimally invasive surgeries often require complicated maneuvers and delicate hand-eye coordination and ideally would incorporate "x-ray vision" to see beyond tool tips and underneath tissues prior to making incisions. Photoacoustic imaging has the potential to offer this feature but not with ionizing x-rays. Instead, optical fibers and acoustic receivers enable photoacoustic sensing of major structures-such as blood vessels and nerves-that are otherwise hidden from view. This imaging process is initiated by transmitting laser pulses that illuminate regions of interest, causing thermal expansion and the generation of sound waves that are detectable with conventional ultrasound transducers. The recorded signals are then converted to images through the beamforming process. Photoacoustic imaging may be implemented to both target and avoid blood-rich surgical contents (and in some cases simultaneously or independently visualize optical fiber tips or metallic surgical tool tips) in order to prevent accidental injury and assist device operators during minimally invasive surgeries and interventional procedures. Novel light delivery systems, counterintuitive findings, and robotic integration methods introduced by the Photoacoustic & Ultrasonic Systems Engineering Lab are summarized in this invited Perspective, setting the foundation and rationale for the subsequent discussion of the author's views on possible future directions for this exciting frontier known as photoacoustic-guided surgery.

Reflection artifact identification in photoacoustic imaging using multi-wavelength excitation

Photoacoustic imaging has been a focus of research for clinical applications owing to its ability for deep visualization with optical absorption contrast. However, there are various technical challenges remaining for this technique to find its place in clinics. One of the challenges is the occurrence of reflection artifacts. The reflection artifacts may lead to image misinterpretation. Here we propose a new method using multiple wavelengths for identifying and removing the reflection artifacts. By imaging the sample with multiple wavelengths, the spectral response of the features in the photoacoustic image is obtained. We assume that the spectral response of the reflection artifact is better correlated with the proper image feature of its corresponding absorber than with other features in the image. Based on this, the reflection artifacts can be identified and removed. Here, we experimentally demonstrated the potential of this method for real-time identification and correction of reflection artifacts in photoacoustic images in phantoms as well as in vivo using a handheld photoacoustic imaging probe.

Image reconstruction with the Heaviside equation in photoacoustic tomography accounting for dispersive acoustic media

A challenging issue in photoacoustic biomedical imaging is to take into account the presence of dispersive acoustic media, since these are prone to induce amplitude attenuation and scattering of the photoacoustic frequency components. These perturbations are largely the cause for which the photoacoustic tomographic image reconstruction from projections lacks a plane-wave transport formalism. Attending this problem, we further develop an analytic formalism of the transport and its numerical implementation accounting for dispersive acoustic media. We differentiate three variations of an acoustically perturbing media. Our object of interest is a numerical description of the light absorption map of a coronal human breast image. Then, we analyze conditions for which the propagation of photoacoustic perturbations can obey the generalized Heaviside telegraph equation. In addition, we provide a study of the causality consistency of the wave propagation models. We observe transport implications due to the presence of dispersive acoustic media and derive model adjustments that include attenuation and diffusion approximations within the two-dimensional forward problem. Next, we restore the inverse problem description with the deduced perturbation components. Finally, we solve the nonlinear inverse problem with a numerical strategy for a filtered backprojection reconstruction. At a stage prior to the image reconstruction, we compensate for the effect of acoustic attenuation and diffusion to calculate the inversions of the wave perturbations located within the projections. In this way, we manage to significantly reduce reconstruction artifacts. In consequence, we prevent the use of some additional image processing of noise reduction. We demonstrate a feasible strategy on how to solve the stated nonlinear inverse problem of photoacoustic tomography accounting for dispersive acoustic media. In particular, we emphasize efforts to achieve an analytical description, and thus an algorithm is placed, for imaged sound perturbations to be cleaned from acoustic scattering in a simplified manner.

Photoacoustic Source Detection and Reflection Artifact Removal Enabled by Deep Learning

Interventional applications of photoacoustic imaging typically require visualization of point-like targets, such as the small, circular, cross-sectional tips of needles, catheters, or brachytherapy seeds. When these point-like targets are imaged in the presence of highly echogenic structures, the resulting photoacoustic wave creates a reflection artifact that may appear as a true signal. We propose to use deep learning techniques to identify these types of noise artifacts for removal in experimental photoacoustic data. To achieve this goal, a convolutional neural network (CNN) was first trained to locate and classify sources and artifacts in pre-beamformed data simulated with -Wave. Simulations initially contained one source and one artifact with various medium sound speeds and 2-D target locations. Based on 3,468 test images, we achieved a 100% success rate in classifying both sources and artifacts. After adding noise to assess potential performance in more realistic imaging environments, we achieved at least 98% success rates for channel signal-to-noise ratios (SNRs) of -9dB or greater, with a severe decrease in performance below -21dB channel SNR. We then explored training with multiple sources and two types of acoustic receivers and achieved similar success with detecting point sources. Networks trained with simulated data were then transferred to experimental waterbath and phantom data with 100% and 96.67% source classification accuracy, respectively (particularly when networks were tested at depths that were included during training). The corresponding mean ± one standard deviation of the point source location error was 0.40 ± 0.22 mm and 0.38 ± 0.25 mm for waterbath and phantom experimental data, respectively, which provides some indication of the resolution limits of our new CNN-based imaging system. We finally show that the CNN-based information can be displayed in a novel artifact-free image format, enabling us to effectively remove reflection artifacts from photoacoustic images, which is not possible with traditional geometry-based beamforming.

Rapid scanning wide-field clutter elimination in epi-optoacoustic imaging using comb LOVIT

Epi-style optoacoustic (OA) imaging provides flexibility by integrating the irradiation optics and ultrasound receiver, yet clutter generated by optical absorption near the probe obscures deep OA sources. Localised vibration tagging (LOVIT) retrieves OA signal from images that are acquired with and without a preceding ultrasonic pushing beam: Radiation force leads to a phase shift of signals coming from the focal area resulting in their visibility in a difference image, whereas clutter from outside the pushing beam is eliminated. Disadvantages of a single-focus approach are residual clutter from inside the pushing beam above the focus, and time-intensive scanning of the focus to retrieve a large field-of-view. To speed up acquisition, we propose to create multiple foci in parallel, forming comb-shaped ARF patterns. By subtracting OA images obtained with interleaved combs, this technique moreover results in greatly improved clutter reduction in phantoms mimicking optical, acoustic and elastic properties of breast tissue.

Rapid scanning wide-field clutter elimination in epi-optoacoustic imaging using comb LOVIT

Epi-style optoacoustic (OA) imaging provides flexibility by integrating the irradiation optics and ultrasound receiver, yet clutter generated by optical absorption near the probe obscures deep OA sources. Localised vibration tagging (LOVIT) retrieves OA signal from images that are acquired with and without a preceding ultrasonic pushing beam: Radiation force leads to a phase shift of signals coming from the focal area resulting in their visibility in a difference image, whereas clutter from outside the pushing beam is eliminated. Disadvantages of a single-focus approach are residual clutter from inside the pushing beam above the focus, and time-intensive scanning of the focus to retrieve a large field-of-view. To speed up acquisition, we propose to create multiple foci in parallel, forming comb-shaped ARF patterns. By subtracting OA images obtained with interleaved combs, this technique moreover results in greatly improved clutter reduction in phantoms mimicking optical, acoustic and elastic properties of breast tissue.

Feasibility of photoacoustic/ultrasound imaging of synovitis in finger joints using a point-of-care system

We evaluate a portable ultrasound and photoacoustic imaging (PAI) system for the feasibility of a point-of-care assessment of clinically evident synovitis. Inflamed and non-inflamed proximal interphalangeal joints of 10 patients were examined and compared with joints from 7 healthy volunteers. PAI scans, ultrasound power Doppler (US-PD), and clinical examination were performed. We quantified the amount of photoacoustic (PA) signal using a region of interest (ROI) drawn over the hypertrophic joint space. PAI response was increased 4 to 10 fold when comparing inflamed with contralateral non-inflamed joints and with joints from healthy volunteers (p < 0.001 for both). US-PD and PAI were strongly correlated (Spearman's ρ = 0.64, with 95% CI: 0.42, 0.79). Hence, PAI using a compact handheld probe is capable of detecting clinically evident synovitis. This motivates further investigation into the predictive value of PAI, including multispectral PAI, with other established modalities such as US-PD or MRI.

Photoacoustic reflection artifact reduction using photoacoustic-guided focused ultrasound: comparison between plane-wave and element-by-element synthetic backpropagation approach

Reflection artifacts caused by acoustic inhomogeneities constitute a major problem in epi-mode biomedical photoacoustic imaging. Photoacoustic transients from the skin and superficial optical absorbers traverse into the tissue and reflect off echogenic structures to generate reflection artifacts. These artifacts cause difficulties in the interpretation of images and reduce contrast and imaging depth. We recently developed a method called PAFUSion (photoacoustic-guided focused ultrasound) to circumvent the problem of reflection artifacts in photoacoustic imaging. We already demonstrated that the photoacoustic signals can be backpropagated using synthetic aperture pulse-echo data for identifying and reducing reflection artifacts in vivo. In this work, we propose an alternative variant of PAFUSion in which synthetic backpropagation of photoacoustic signals is based on multi-angled plane-wave ultrasound measurements. We implemented plane-wave and synthetic aperture PAFUSion in a handheld ultrasound/photoacoustic imaging system and demonstrate reduction of reflection artifacts in phantoms and in vivo measurements on a human finger using both approaches. Our results suggest that, while both approaches are equivalent in terms of artifact reduction efficiency, plane-wave PAFUSion requires less pulse echo acquisitions when the skin absorption is the main cause of reflection artifacts.

Deep tissue photoacoustic computed tomography with a fast and compact laser system

Photoacoustic computed tomography (PACT) holds great promise for biomedical imaging, but wide-spread implementation is impeded by the bulkiness of flash-lamp-pumped laser systems, which typically weigh between 50 - 200 kg, require continuous water cooling, and operate at a low repetition rate. Here, we demonstrate that compact lasers based on emerging diode technologies are well-suited for preclinical and clinical PACT. The diode-pumped laser used in this study had a miniature footprint (13 × 14 × 7 cm³), weighed only 1.6 kg, and outputted up to 80 mJ per pulse at 1064 nm. In vitro, the laser system readily provided over 4 cm PACT depth in chicken breast tissue. In vivo, in addition to high resolution, non-invasive brain imaging in living mice, the system can operate at 50 Hz, which enabled high-speed cross-sectional imaging of murine cardiac and respiratory function. The system also provided high quality, high-frame rate, and non-invasive three-dimensional mapping of arm, palm, and breast vasculature at multi centimeter depths in living human subjects, demonstrating the clinical viability of compact lasers for PACT.

In vivo demonstration of reflection artifact reduction in photoacoustic imaging using synthetic aperture photoacoustic-guided focused ultrasound (PAFUSion)

Reflection artifacts caused by acoustic inhomogeneities are a critical problem in epi-mode biomedical photoacoustic imaging. High light fluence beneath the probe results in photoacoustic transients, which propagate into the tissue and reflect back from echogenic structures. These reflection artifacts cause problems in image interpretation and significantly impact the contrast and imaging depth. We recently proposed a method called PAFUSion (Photoacoustic-guided focused ultrasound) to identify such reflection artifacts in photoacoustic imaging. In its initial version, PAFUSion mimics the inward-travelling wavefield from small blood vessel-like PA sources by applying ultrasound pulses focused towards these sources, and thus provides a way to identify the resulting reflection artifacts. In this work, we demonstrate reduction of reflection artifacts in phantoms and in vivo measurements on human volunteers. In view of the spatially distributed PA sources that are found in clinical applications, we implemented an improved version of PAFUSion where photoacoustic signals are backpropagated to imitate the inward travelling wavefield and thus the reflection artifacts. The backpropagation is performed in a synthetic way based on the pulse-echo acquisitions after transmission on each single element of the transducer array. The results provide a direct confirmation that reflection artifacts are prominent in clinical epi-photoacoustic imaging, and that PAFUSion can strongly reduce these artifacts to improve deep-tissue photoacoustic imaging.