Iterative image reconstruction in transcranial photoacoustic tomography based on the elastic wave equation

Quantitative Optical Imaging of Oxygen in Brain Vasculature

The intimate relationship between neuronal activity and cerebral oxygenation underpins fundamental brain functions like cognition, sensation, and motor control. Optical imaging offers a noninvasive approach to assess brain oxygenation and often serves as an indirect proxy for neuronal activity. However, deciphering neurovascular coupling─the intricate interplay between neuronal activity, blood flow, and oxygen delivery─necessitates independent, high spatial resolution, and high temporal resolution measurements of both microvasculature oxygenation and neuronal activation. This Perspective examines the established optical techniques employed for brain oxygen imaging, specifically functional near-infrared spectroscopy, photoacoustic imaging, optical coherence tomography, and two-photon phosphorescent lifetime microscopy, highlighting their fundamental principles, strengths, and limitations. Several other emerging optical techniques are also introduced. Finally, we discuss key technological challenges and future directions for quantitative optical oxygen imaging, paving the way for a deeper understanding of oxygen metabolism in the brain.

Computational wave-based photoacoustic imaging through an unknown thick aberrating layer

We introduce a physics-based computational reconstruction framework for non-invasive photoacoustic tomography through a thick aberrating layer. Our wave-based approach leverages an analytic formulation of diffraction to beamform a photoacoustic image, when the aberrating layer profile is known. When the profile of the aberrating layer is unknown, the same analytical formulation serves as the basis for an automatic-differentiation regularized optimization algorithm that simultaneously reconstructs both the profile of the aberrating layer and the optically absorbing targets. Results from numerical studies and proof-of-concept experiments show promise for fast beamforming that takes into account diffraction effects occurring in the propagation through thick, highly-aberrating layers.

A frequency-domain model-based reconstruction method for transcranial photoacoustic imaging: A 2D numerical investigation

Phase aberration caused by the skull is a major barrier to achieving high quality photoacoustic images of human and non-human primates' brains. To address this issue, time-reversal methods have been used but they are computationally demanding and slow due to relying on solving the full-wave equation. The proposed approach is based on model-based image reconstruction in the frequency-domain to achieve near real-time image reconstruction. The relationship between an imaging region and transducer array elements can be mathematically described as a model matrix and the image reconstruction can be performed by pseudo-inverse of the model matrix. The model matrix is numerically calculated due to the lack of analytical solutions for transcranial ultrasound. However, this calculation only needs to be performed once for a given experimental setup and the same acoustic medium, and is an offline process not affecting the actual image reconstruction time. This non-iterative mode-based method demonstrates a substantial improvement in image reconstruction time, being approximately 18 times faster than the time-reversal method, all while maintaining comparable image quality.

Evaluation of ultrasound sensors for transcranial photoacoustic sensing and imaging

Photoacoustic imaging through skull bone causes strong attenuation and distortion of the acoustic wavefront, which diminishes image contrast and resolution. As a result, transcranial photoacoustic measurements in humans have been challenging to demonstrate. In this study, we investigated the acoustic transmission through the human skull to design an ultrasound sensor suitable for transcranial PA imaging and sensing. We measured the frequency dependent losses of human cranial bones ex vivo, compared the performance of a range of piezoelectric and optical ultrasound sensors, and imaged skull phantoms using a PA tomograph based on a planar Fabry-Perot sensor. All transcranial photoacoustic measurements show the typical effects of frequency and thickness dependent attenuation and aberration associated with acoustic propagation through bone. The performance of plano-concave optical resonator ultrasound sensors was found to be highly suitable for transcranial photoacoustic measurements.

Photoacoustic Imaging and Characterization of Bone in Medicine: Overview, Applications, and Outlook

Photoacoustic techniques have shown promise in identifying molecular changes in bone tissue and visualizing tissue microstructure. This capability represents significant advantages over gold standards (i.e., dual-energy X-ray absorptiometry) for bone evaluation without requiring ionizing radiation. Instead, photoacoustic imaging uses light to penetrate through bone, followed by acoustic pressure generation, resulting in highly sensitive optical absorption contrast in deep biological tissues. This review covers multiple bone-related photoacoustic imaging contributions to clinical applications, spanning bone cancer, joint pathologies, spinal disorders, osteoporosis, bone-related surgical guidance, consolidation monitoring, and transsphenoidal and transcranial imaging. We also present a summary of photoacoustic-based techniques for characterizing biomechanical properties of bone, including temperature, guided waves, spectral parameters, and spectroscopy. We conclude with a future outlook based on the current state of technological developments, recent achievements, and possible new directions.

Photoacoustic digital brain and deep-learning-assisted image reconstruction

Photoacoustic tomography (PAT) is a newly developed medical imaging modality, which combines the advantages of pure optical imaging and ultrasound imaging, owning both high optical contrast and deep penetration depth. Very recently, PAT is studied in human brain imaging. Nevertheless, while ultrasound waves are passing through the human skull tissues, the strong acoustic attenuation and aberration will happen, which causes photoacoustic signals' distortion. In this work, we use 180 T1 weighted magnetic resonance imaging (MRI) human brain volumes along with the corresponding magnetic resonance angiography (MRA) brain volumes, and segment them to generate the 2D human brain numerical phantoms for PAT. The numerical phantoms contain six kinds of tissues, which are scalp, skull, white matter, gray matter, blood vessel and cerebrospinal fluid. For every numerical phantom, Monte-Carlo based optical simulation is deployed to obtain the photoacoustic initial pressure based on optical properties of human brain. Then, two different k-wave models are used for the skull-involved acoustic simulation, which are fluid media model and viscoelastic media model. The former one only considers longitudinal wave propagation, and the latter model takes shear wave into consideration. Then, the PA sinograms with skull-induced aberration is taken as the input of U-net, and the skull-stripped ones are regarded as the supervision of U-net to train the network. Experimental result shows that the skull's acoustic aberration can be effectively alleviated after U-net correction, achieving conspicuous improvement in quality of PAT human brain images reconstructed from the corrected PA signals, which can clearly show the cerebral artery distribution inside the human skull.

Android mobile-platform-based image reconstruction for photoacoustic tomography

Significance

In photoacoustic tomography (PAT), numerous reconstruction algorithms have been utilized to recover initial pressure rise distribution from the acquired pressure waves. In practice, most of these reconstructions are carried out on a desktop/workstation and the mobile-based reconstructions are far-flung. In recent years, mobile phones are becoming so ubiquitous, and most of them encompass a higher computing ability. Hence, realizing PAT image reconstruction on a mobile platform is intrinsic, and it will enhance the adaptability of PAT systems with point-of-care applications.

Aim

To implement PAT image reconstruction in Android-based mobile platforms.

Approach

For implementing PAT image reconstruction in Android-based mobile platforms, we proposed an Android-based application using Python to perform beamforming process in Android phones.

Results

The performance of the developed application was analyzed on different mobile platforms using both simulated and experimental datasets. The results demonstrate that the developed algorithm can accomplish the image reconstruction of in vivo small animal brain dataset in 2.4 s. Furthermore, the developed application reconstructs PAT images with comparable speed and no loss of image quality compared to that on a laptop. Employing a two-fold downsampling procedure could serve as a viable solution for reducing the time needed for beamforming while preserving image quality with minimal degradation.

Conclusions

We proposed an Android-based application that achieves image reconstruction on cheap, small, and universally available phones instead of relatively bulky expensive desktop computers/laptops/workstations. A beamforming speed of 2.4 s is achieved without hampering the quality of the reconstructed image.

Coregistered transcranial optoacoustic and magnetic resonance angiography of the human brain

Imaging modalities capable of visualizing the human brain have led to major advances in neurology and brain research. Multi-spectral optoacoustic tomography (MSOT) has gained importance for studying cerebral function in rodent models due to its unique capability to map changes in multiple hemodynamic parameters and to directly visualize neural activity within the brain. The technique further provides molecular imaging capabilities that can facilitate early disease diagnosis and treatment monitoring. However, transcranial imaging of the human brain is hampered by acoustic attenuation and other distortions introduced by the skull. Here, we demonstrate non-invasive transcranial MSOT angiography of pial veins through the temporal bone of an adult healthy volunteer. Time-of-flight (TOF) magnetic resonance angiography (MRA) and T₁-weighted structural magnetic resonance imaging (MRI) were further acquired to facilitate anatomical registration and interpretation. The superior middle cerebral vein in the temporal cortex was identified in the MSOT images, matching its location observed in the TOF-MRA images. These initial results pave the way toward the application of MSOT in clinical brain imaging.

Marchenko Green’s Function Retrieval in Layered Elastic Media from Two-Sided Reflection and Transmission Data

By solving a Marchenko equation, Green’s functions at an arbitrary (inner) depth level inside an unknown elastic layered medium can be retrieved from single-sided reflection data, which are collected at the top of the medium. To date, it has only been possible to obtain an exact solution if the medium obeyed stringent monotonicity conditions and if all forward-scattered (non-converted and converted) transmissions between the acquisition level and the inner depth level were known a priori. We introduce an alternative Marchenko equation by revising the window operators that are applied in its derivation. We also introduce an auxiliary equation for transmission data, which are collected at the bottom of the medium, and a coupled equation, which is based on both reflection and transmission data. We show that the joint system of the Marchenko equation, the auxiliary equation and the coupled equation can be succesfully inverted when broadband reflection and transmission data are available. This results in a novel methodology for elastodynamic Green’s function retrieval from two-sided data. Apart from these data, our approach requires P- and S-wave transmission times between the inner depth level and the top of the medium, as well as two angle-dependent amplitude scaling factors, which can be estimated from the data by enforcing energy conservation.

Looking deep inside tissue with photoacoustic molecular probes: a review

Significance

Deep tissue noninvasive high-resolution imaging with light is challenging due to the high degree of light absorption and scattering in biological tissue. Photoacoustic imaging (PAI) can overcome some of the challenges of pure optical or ultrasound imaging to provide high-resolution deep tissue imaging. However, label-free PAI signals from light absorbing chromophores within the tissue are nonspecific. The use of exogeneous contrast agents (probes) not only enhances the imaging contrast (and imaging depth) but also increases the specificity of PAI by binding only to targeted molecules and often providing signals distinct from the background.

Aim

We aim to review the current development and future progression of photoacoustic molecular probes/contrast agents.

Approach

First, PAI and the need for using contrast agents are briefly introduced. Then, the recent development of contrast agents in terms of materials used to construct them is discussed. Then, various probes are discussed based on targeting mechanisms, in vivo molecular imaging applications, multimodal uses, and use in theranostic applications.

Results

Material combinations are being used to develop highly specific contrast agents. In addition to passive accumulation, probes utilizing activation mechanisms show promise for greater controllability. Several probes also enable concurrent multimodal use with fluorescence, ultrasound, Raman, magnetic resonance imaging, and computed tomography. Finally, targeted probes are also shown to aid localized and molecularly specific photo-induced therapy.

Conclusions

The development of contrast agents provides a promising prospect for increased contrast, higher imaging depth, and molecularly specific information. Of note are agents that allow for controlled activation, explore other optical windows, and enable multimodal use to overcome some of the shortcomings of label-free PAI.

On the Retrieval of Forward-Scattered Waveforms From Acoustic Reflection and Transmission Data With the Marchenko Equation

A Green's function in an acoustic medium can be retrieved from reflection data by solving a multidimensional Marchenko equation. This procedure requires a priori knowledge of the initial focusing function, which can be interpreted as the inverse of a transmitted wavefield as it would propagate through the medium, excluding (multiply) reflected waveforms. In practice, the initial focusing function is often replaced by a time-reversed direct wave, which is computed with help of a macro velocity model. Green's functions that are retrieved under this (direct-wave) approximation typically lack forward-scattered waveforms and their associated multiple reflections. We examine whether this problem can be mitigated by incorporating transmission data. Based on these transmission data, we derive an auxiliary equation for the forward-scattered components of the initial focusing function. We demonstrate that this equation can be solved in an acoustic medium with mass density contrast and constant propagation velocity. By solving the auxiliary and Marchenko equation successively, we can include forward-scattered waveforms in our Green's function estimates, as we demonstrate with a numerical example.

Massively parallel functional photoacoustic computed tomography of the human brain

Blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging of the human brain requires bulky equipment for the generation of magnetic fields. Photoacoustic computed tomography obviates the need for magnetic fields by using light and sound to measure deoxyhaemoglobin and oxyhaemoglobin concentrations to then quantify oxygen saturation and blood volumes. Yet, the available imaging speeds, fields of view (FOV), sensitivities and penetration depths have been insufficient for functional imaging of the human brain. Here, we show that massively parallel ultrasonic transducers arranged hemispherically around the human head can produce tomographic images of the brain with a 10-cm-diameter FOV and spatial and temporal resolutions of 350 µm and 2 s, respectively. In patients who had a hemicraniectomy, a comparison of functional photoacoustic computed tomography and 7 T BOLD functional magnetic resonance imaging showed a strong spatial correspondence in the same FOV and a high temporal correlation between BOLD signals and photoacoustic signals, with the latter enabling faster detection of functional activation. Our findings establish the use of photoacoustic computed tomography for human brain imaging.

Rapid Volumetric Optoacoustic Tracking of Individual Microparticles In Vivo Enabled by a NIR-Absorbing Gold-Carbon Shell

Rapid volumetric in vivo visualization of circulating microparticles can facilitate new biomedical applications, such as blood flow characterization or targeted drug delivery. However, existing imaging modalities generally lack the sensitivity to detect the weak signals generated by individual micrometer-sized particles distributed across millimeter- to centimeter-scale depths in living mammalian tissues. Also, the temporal resolution is typically insufficient to track the particles in an entire three-dimensional region. Herein, we introduce a new type of monodisperse (4 μm) silica-core microparticle coated with a shell formed by a multilayered structure of carbon nanotubes (CNT) and gold nanoparticles (AuNP) to provide strong optoacoustic (OA) absorption-based contrast. We capitalize on the unique advantages of a state-of-the-art high-frame-rate OA tomography system to visualize and track the motion of these core-shell particles individually and volumetrically as they flow throughout the mouse brain vasculature. The feasibility of localizing individual solid particles smaller than red blood cells opens new opportunities for mapping the blood flow velocity, enhancing the resolution and visibility of OA images, and developing new biosensing assays.

Denoising of pre-beamformed photoacoustic data using generative adversarial networks

We have trained generative adversarial networks (GANs) to mimic both the effect of temporal averaging and of singular value decomposition (SVD) denoising. This effectively removes noise and acquisition artifacts and improves signal-to-noise ratio (SNR) in both the radio-frequency (RF) data and in the corresponding photoacoustic reconstructions. The method allows a single frame acquisition instead of averaging multiple frames, reducing scan time and total laser dose significantly. We have tested this method on experimental data, and quantified the improvement over using either SVD denoising or frame averaging individually for both the RF data and the reconstructed images. We achieve a mean squared error (MSE) of 0.05%, structural similarity index measure (SSIM) of 0.78, and a feature similarity index measure (FSIM) of 0.85 compared to our ground-truth RF results. In the subsequent reconstructions using the denoised data we achieve a MSE of 0.05%, SSIM of 0.80, and a FSIM of 0.80 compared to our ground-truth reconstructions.

Photoacoustic imaging for monitoring of stroke diseases: A review

Stroke is the leading cause of death and disability after ischemic heart disease. However, there is lacking a non-invasive long-time monitoring technique for stroke diagnosis and therapy. The photoacoustic imaging approach reconstructs images of an object based on the energy excitation by optical absorption and its conversion to acoustic waves, due to corresponding thermoelastic expansion, which has optical resolution and acoustic propagation. This emerging functional imaging method is a non-invasive technique. Due to its precision, this method is particularly attractive for stroke monitoring purpose. In this paper, we review the achievements of this technology and its applications on stroke, as well as the development status in both animal and human applications. Also, various photoacoustic systems and multi-modality photoacoustic imaging are introduced as for potential clinical applications. Finally, the challenges of photoacoustic imaging for monitoring stroke are discussed.

Photoacoustic computed tomography for functional human brain imaging [Invited]

The successes of magnetic resonance imaging and modern optical imaging of human brain function have stimulated the development of complementary modalities that offer molecular specificity, fine spatiotemporal resolution, and sufficient penetration simultaneously. By virtue of its rich optical contrast, acoustic resolution, and imaging depth far beyond the optical transport mean free path (∼1 mm in biological tissues), photoacoustic computed tomography (PACT) offers a promising complementary modality. In this article, PACT for functional human brain imaging is reviewed in its hardware, reconstruction algorithms, in vivo demonstration, and potential roadmap.

Comparison of compressional and elastic wave simulations for patient-specific planning prior to transcranial photoacoustic-guided neurosurgery

SIGNIFICANCE

Simulations have the potential to be a powerful tool when planning the placement of photoacoustic imaging system components for surgical guidance. While elastic simulations (which include both compressional and shear waves) are expected to more accurately represent the physical transcranial acoustic wave propagation process, these simulations are more time-consuming and memory-intensive than the compressional-wave-only simulations that our group previously used to identify optimal acoustic windows for transcranial photoacoustic imaging.

AIM

We present qualitative and quantitative comparisons of compressional and elastic wave simulations to determine which option is more suitable for preoperative surgical planning.

APPROACH

Compressional and elastic photoacoustic k-Wave simulations were performed based on a computed tomography volume of a human cadaver head. Photoacoustic sources were placed in the locations of the internal carotid arteries and likely positions of neurosurgical instrument tips. Transducers received signals from three previously identified optimal acoustic windows (i.e., the ocular, nasal, and temporal regions). Target detectability, image-based target size estimates, and target-to-instrument distances were measured using the generalized contrast-to-noise ratio (gCNR), resolution, and relative source distances, respectively, for each simulation method.

RESULTS

The gCNR was equivalent between compressional and elastic simulations. The areas of the -6  dB contours of point spread functions utilized to measure resolution differed by 0.33 to 3.35  mm2. Target-to-instrument distance measurements were within 1.24 mm of the true distances.

CONCLUSIONS

These results indicate that it is likely sufficient to utilize the less time-consuming, less memory-intensive compressional wave simulations for presurgical planning.

Another decade of photoacoustic imaging

Photoacoustic imaging - a hybrid biomedical imaging modality finding its way to clinical practices. Although the photoacoustic phenomenon was known more than a century back, only in the last two decades it has been widely researched and used for biomedical imaging applications. In this review we focus on the development and progress of the technology in the last decade (2010-2020). From becoming more and more user friendly, cheaper in cost, portable in size, photoacoustic imaging promises a wide range of applications, if translated to clinic. The growth of photoacoustic community is steady, and with several new directions researchers are exploring, it is inevitable that photoacoustic imaging will one day establish itself as a regular imaging system in the clinical practices.