Photoacoustic-based sO2 estimation through excised bovine prostate tissue with interstitial light delivery

Adaptation of a Clinical High-Frequency Transrectal Ultrasound System for Prostate Photoacoustic Imaging: Implementation and Pre-clinical Demonstration

OBJECTIVE

High-frequency, high-resolution transrectal micro-ultrasound (micro-US: ≥15 MHz) imaging of the prostate is emerging as a beneficial tool for scoring disease risk and accurately targeting biopsies. Adding photoacoustic (PA) imaging to visualize abnormal vascularization and accumulation of contrast agents in tumors has potential for guiding focal therapies. In this work, we describe a new imaging platform that combines a transrectal micro-US system with transurethral light delivery for PA imaging.

METHODS

A clinical transrectal micro-US system was adapted to acquire PA images synchronous to a tunable laser pulse. A transurethral side-firing optical fiber was developed for light delivery. A polyvinyl chloride (PVC)-plastisol phantom was developed and characterized to image PA contrast agents in wall-less channels. After resolution measurement in water, PA imaging was demonstrated in phantom channels with dyes and biodegradable nanoparticle contrast agents called porphysomes. In vivo imaging of a tumor model was performed, with porphysomes administered intravenously.

RESULTS

Photoacoustic imaging data were acquired at 5 Hz, and image reconstruction was performed offline. PA image resolution at a 14-mm depth was 74 and 261 μm in the axial and lateral directions, respectively. The speed of sound in PVC-plastisol was 1383 m/s, and the attenuation was 4 dB/mm at 20 MHz. PA signal from porphysomes was spectrally unmixed from blood signals in the tumor, and a signal increase was observed 3 h after porphysome injection.

CONCLUSION

A combined transrectal micro-US and PA imaging system was developed and characterized, and in vivo imaging demonstrated. High-resolution PA imaging may provide valuable additional information for diagnostic and therapeutic applications in the prostate.

Sensing of triglyceride concentration in blood solution using photoacoustic microscopy

The level of triglyceride (TG) in blood is essential to human health, and hypertriglyceridemia (TG level > 150 mg/dL) would lead to cardiovascular disease and acute pancreatitis that threaten human life. Routine methods for measuring the TG level in blood depend on a lipid panel blood test, which is invasive and not convenient. Here, we use photoacoustic (PA) microscopy to test the PA amplitude of blood solutions (based on hemoglobin powder as well as flowing sheep blood) with different TG concentrations. Interestingly, we observe that the PA amplitude increases with increasing TG concentration in blood solutions, which is attributed to the increase of the Grüneisen coefficient. The preliminary in vitro study shows that the PA methodology is able to detect the TG level down to 450 mg/dL. This finding provides an opportunity for using photoacoustics to noninvasively diagnose hypertriglyceridemia.

State-of-the-art techniques for imaging the vascular microenvironment in craniofacial bone tissue engineering applications

Vascularization is a crucial step during musculoskeletal tissue regeneration via bioengineered constructs or grafts. Functional vasculature provides oxygen and nutrients to the graft microenvironment, facilitates wound healing, enhances graft integration with host tissue, and ensures the long-term survival of regenerating tissue. Therefore, imaging de novo vascularization (i.e., angiogenesis), changes in microvascular morphology, and the establishment and maintenance of perfusion within the graft site (i.e., vascular microenvironment or VME) can provide essential insights into engraftment, wound healing, as well as inform the design of tissue engineering (TE) constructs. In this review, we focus on state-of-the-art imaging approaches for monitoring the VME in craniofacial TE applications, as well as future advances in this field. We describe how cutting-edge in vivo and ex vivo imaging methods can yield invaluable information regarding VME parameters that can help characterize the effectiveness of different TE constructs and iteratively inform their design for enhanced craniofacial bone regeneration. Finally, we explicate how the integration of novel TE constructs, preclinical model systems, imaging techniques, and systems biology approaches could usher in an era of "image-based tissue engineering."

Validation of photoacoustic/ultrasound dual imaging in evaluating blood oxygen saturation

Photoacoustic imaging (PAI) was performed to evaluate oxygen saturation (sO₂) of blood-mimicking phantoms, femoral arteries in beagles, and radial arteries in humans at various sO₂ plateaus. The accuracy (root mean square error, RMSE) of PAI sO₂ compared with reference sO₂ was calculated. In blood-mimicking phantoms, PAI achieved an accuracy of 1.49% and a mean absolute error (MAE) of 1.09% within 25 mm depth, and good linearity (R = 0.968; p < 0.001) was obtained between PAI sO₂ and reference sO₂. In canine femoral arteries, PAI achieved an accuracy of 2.16% and an MAE of 1.58% within 8 mm depth (R = 0.965; p < 0.001). In human radial arteries, PAI achieved an accuracy of 3.97% and an MAE of 3.28% in depth from 4 to 14 mm (R = 0.892; p < 0.001). For PAI sO₂ evaluation at different depths in healthy volunteers, the RMSE accuracy of PAI sO₂ increased from 2.66% to 24.96% with depth increasing from 4 to 14 mm. Through the multiscale method, we confirmed the feasibility of the hand-held photoacoustic/ultrasound (PA/US) in evaluating sO₂. These results demonstrate the potential clinical value of PAI in evaluating blood sO₂. Consequently, protocols for verifying the feasibility of medical devices based on PAI may be established.

Spectral crosstalk in photoacoustic computed tomography

Multispectral photoacoustic (PA) imaging faces two major challenges: the spectral coloring effect, which has been studied extensively as an optical inversion problem, and the spectral crosstalk, which is basically a result of non-ideal acoustic inversion. So far, there is no systematic work to analyze the spectral crosstalk because acoustic inversion and spectroscopic measurement are always treated as decoupled. In this work, we theorize and demonstrate through a series of simulations and experiments how imperfect acoustic inversion induces inaccurate PA spectrum measurement. We provide detailed analysis to elucidate how different factors, including limited bandwidth, limited view, light attenuation, out-of-plane signal, and image reconstruction schemes, conspire to render the measured PA spectrum inaccurate. We found that the model-based reconstruction outperforms universal back-projection in suppressing the spectral crosstalk in some cases.

In-vivo functional and structural retinal imaging using multiwavelength photoacoustic remote sensing microscopy

Many important eye diseases as well as systemic disorders manifest themselves in the retina. Retinal imaging technologies are rapidly growing and can provide ever-increasing amounts of information about the structure, function, and molecular composition of retinal tissue in-vivo. Photoacoustic remote sensing (PARS) is a novel imaging modality based on all-optical detection of photoacoustic signals, which makes it suitable for a wide range of medical applications. In this study, PARS is applied for in-vivo imaging of the retina and estimating oxygen saturation in the retinal vasculature. To our knowledge, this is the first time that a non-contact photoacoustic imaging technique is applied for in-vivo imaging of the retina. Here, optical coherence tomography is also used as a well-established retinal imaging technique to navigate the PARS imaging beams and demonstrate the capabilities of the optical imaging setup. The system is applied for in-vivo imaging of both microanatomy and the microvasculature of the retina. The developed system has the potential to advance the understanding of the ocular environment and to help in monitoring of ophthalmic diseases.

Clinically translatable quantitative molecular photoacoustic imaging with liposome-encapsulated ICG J-aggregates

Photoacoustic (PA) imaging is a functional and molecular imaging technique capable of high sensitivity and spatiotemporal resolution at depth. Widespread use of PA imaging, however, is limited by currently available contrast agents, which either lack PA-signal-generation ability for deep imaging or their absorbance spectra overlap with hemoglobin, reducing sensitivity. Here we report on a PA contrast agent based on targeted liposomes loaded with J-aggregated indocyanine green (ICG) dye (i.e., PAtrace) that we synthesized, bioconjugated, and characterized to addresses these limitations. We then validated PAtrace in phantom, in vitro, and in vivo PA imaging environments for both spectral unmixing accuracy and targeting efficacy in a folate receptor alpha-positive ovarian cancer model. These study results show that PAtrace concurrently provides significantly improved contrast-agent quantification/sensitivity and SO₂ estimation accuracy compared to monomeric ICG. PAtrace's performance attributes and composition of FDA-approved components make it a promising agent for future clinical molecular PA imaging.

Model-based optical and acoustical compensation for photoacoustic tomography of heterogeneous mediums

Photoacoustic tomography (PAT) is a non-invasive, high-resolution imaging modality, capable of providing functional and molecular information of various pathologies, such as cancer. One limitation of PAT is the depth and wavelength dependent optical fluence, which results in reduced PA signal amplitude from deeper tissue regions. These factors can therefore introduce errors into quantitative measurements such as oxygen saturation (sO₂) or the localization and concentration of various chromophores. The variation in the speed-of-sound between different tissues can also lead to distortions in object location and shape. Compensating for these effects allows PAT to be used more quantitatively. We have developed a proof-of-concept algorithm capable of compensating for the heterogeneity in speed-of-sound and depth dependent optical fluence. Speed-of-sound correction was done by using a straight ray-based algorithm for calculating the family of iso-time-of-flight contours between the transducers and every pixel in the imaging grid, while fluence compensation was done by utilizing the graphics processing unit (GPU) accelerated software MCXCL for Monte Carlo modeling of optical fluence variation. This algorithm was tested on a polyvinyl chloride plastisol (PVCP) phantom, which contained cyst mimics and blood inclusions to test the algorithm under relatively heterogeneous conditions. Our results indicate that our PAT algorithm can compensate for the speed-of-sound variation and depth dependent fluence effects within a heterogeneous phantom. The results of this study will pave the way for further development and evaluation of the proposed method in more complex in-vitro and ex-vivo phantoms, as well as compensating for the wavelength-dependent optical fluence in spectroscopic PAT.

Multiple illumination learned spectral decoloring for quantitative optoacoustic oximetry imaging

SIGNIFICANCE

Quantitative measurement of blood oxygen saturation (sO2) with optoacoustic (OA) imaging is one of the most sought after goals of quantitative OA imaging research due to its wide range of biomedical applications.

AIM

A method for accurate and applicable real-time quantification of local sO2 with OA imaging.

APPROACH

We combine multiple illumination (MI) sensing with learned spectral decoloring (LSD). We train LSD feedforward neural networks and random forests on Monte Carlo simulations of spectrally colored absorbed energy spectra, to apply the trained models to real OA measurements. We validate our combined MI-LSD method on a highly reliable, reproducible, and easily scalable phantom model, based on copper and nickel sulfate solutions.

RESULTS

With this sulfate model, we see a consistently high estimation accuracy using MI-LSD, with median absolute estimation errors of 2.5 to 4.5 percentage points. We further find fewer outliers in MI-LSD estimates compared with LSD. Random forest regressors outperform previously reported neural network approaches.

CONCLUSIONS

Random forest-based MI-LSD is a promising method for accurate quantitative OA oximetry imaging.

Evaluating online filtering algorithms to enhance dynamic multispectral optoacoustic tomography

Multispectral optoacoustic tomography (MSOT) is an emerging imaging modality, which is able to capture data at high spatiotemporal resolution using rapid tuning of the excitation laser wavelength. However, owing to the necessity of imaging one wavelength at a time to the exclusion of others, forming a complete multispectral image requires multiple excitations over time, which may introduce aliasing due to underlying spectral dynamics or noise in the data. In order to mitigate this limitation, we have applied kinematic α and α β filters to multispectral time series, providing an estimate of the underlying multispectral image at every point in time throughout data acquisition. We demonstrate the efficacy of these methods in suppressing the inter-frame noise present in dynamic multispectral image time courses using a multispectral Shepp-Logan phantom and mice bearing distinct renal cell carcinoma tumors. The gains in signal to noise ratio provided by these filters enable higher-fidelity downstream analysis such as spectral unmixing and improved hypothesis testing in quantifying the onset of signal changes during an oxygen gas challenge.

Development of a blood oxygenation phantom for photoacoustic tomography combined with online pO2 detection and flow spectrometry

Photoacoustic tomography (PAT) is intrinsically sensitive to blood oxygen saturation (sO2) in vivo. However, making accurate sO2 measurements without knowledge of tissue- and instrumentation-related correction factors is extremely challenging. We have developed a low-cost flow phantom to facilitate validation of PAT systems. The phantom is composed of a flow circuit of tubing partially embedded within a tissue-mimicking material, with independent sensors providing online monitoring of the optical absorption spectrum and partial pressure of oxygen in the tube. We first test the flow phantom using two small molecule dyes that are frequently used for photoacoustic imaging: methylene blue and indocyanine green. We then demonstrate the potential of the phantom for evaluating sO2 using chemical oxygenation and deoxygenation of blood in the circuit. Using this dynamic assessment of the photoacoustic sO2 measurement in phantoms in relation to a ground truth, we explore the influence of multispectral processing and spectral coloring on accurate assessment of sO2. Future studies could exploit this low-cost dynamic flow phantom to validate fluence correction algorithms and explore additional blood parameters such as pH and also absorptive and other properties of different fluids.

Photoacoustic-based oxygen saturation assessment of murine femoral bone marrow in a preclinical model of leukemia

A variety of hematological diseases manifest in the bone marrow (BM), broadly characterized as BM failure (BMF). BMF can be caused by acute lymphoblastic leukemia (ALL), which results in an expansion of hypoxic regions in the BM. Because of this hypoxic presentation, there is potential for improved characterization of BMF through in vivo assessment of oxygenation in the BM cavity. Photoacoustic (PA) imaging can provide local assessment of intravascular oxygen saturation (SO₂), which has been shown to correlate with pimonidazole-assessed hypoxia. This study introduces an optimized PA imaging technique to assess SO₂ within the femoral BM cavity through disease progression in a murine model of ALL. Results show a statistically significant difference with temporal changes in SO₂ (from baseline) between control and diseased cohorts, demonstrating the potential of PA imaging for noninvasive, label-free monitoring of BMF diseases.

Photoacoustic oximetry imaging performance evaluation using dynamic blood flow phantoms with tunable oxygen saturation

Multispectral photoacoustic oximetry imaging (MPOI) is an emerging hybrid modality that enables the spatial mapping of blood oxygen saturation (SO2) to depths of several centimeters. To facilitate MPOI device development and clinical translation, well-validated performance test methods and improved quantitative understanding of physical processes and best practices are needed. We developed a breast-mimicking blood flow phantom with tunable SO2 and used this phantom to evaluate a custom MPOI system. Results provide quantitative evaluation of the impact of phantom medium properties (Intralipid versus polyvinyl chloride plastisol) and device design parameters (different transducers) on SO2 measurement accuracy, especially depth-dependent performance degradation due to fluence artifacts. This approach may guide development of standardized test methods for evaluating MPOI devices.

Improved Photoacoustic-Based Oxygen Saturation Estimation With SNR-Regularized Local Fluence Correction

As photoacoustic (PA) imaging makes its way into the clinic, the accuracy of PA-based metrics becomes increasingly important. To address this need, a method combining finite-element-based local fluence correction (LFC) with signal-to-noise-ratio (SNR) regularization was developed and validated to accurately estimate oxygen saturation (SO₂) in tissue. With data from a Vevo LAZR system, performance of our LFC approach was assessed in ex vivo blood targets (37.6%-99.6% SO₂) and in vivo rat arteries. Estimation error of absolute SO₂ and change in SO₂ reduced from 10.1% and 6.4%, respectively, without LFC to 2.8% and 2.0%, respectively, with LFC, while the accuracy of the LFC method was correlated with the number of wavelengths acquired. This paper demonstrates the need for an SNR-regularized LFC to accurately quantify SO₂ with PA imaging.

Confidence Estimation for Machine Learning-Based Quantitative Photoacoustics

In medical applications, the accuracy and robustness of imaging methods are of crucial importance to ensure optimal patient care. While photoacoustic imaging (PAI) is an emerging modality with promising clinical applicability, state-of-the-art approaches to quantitative photoacoustic imaging (qPAI), which aim to solve the ill-posed inverse problem of recovering optical absorption from the measurements obtained, currently cannot comply with these high standards. This can be attributed to the fact that existing methods often rely on several simplifying a priori assumptions of the underlying physical tissue properties or cannot deal with realistic noise levels. In this manuscript, we address this issue with a new method for estimating an indicator of the uncertainty of an estimated optical property. Specifically, our method uses a deep learning model to compute error estimates for optical parameter estimations of a qPAI algorithm. Functional tissue parameters, such as blood oxygen saturation, are usually derived by averaging over entire signal intensity-based regions of interest (ROIs). Therefore, we propose to reduce the systematic error of the ROI samples by additionally discarding those pixels for which our method estimates a high error and thus a low confidence. In silico experiments show an improvement in the accuracy of optical absorption quantification when applying our method to refine the ROI, and it might thus become a valuable tool for increasing the robustness of qPAI methods.

Validation of noninvasive photoacoustic measurements of sagittal sinus oxyhemoglobin saturation in hypoxic neonatal piglets

We hypothesize that noninvasive photoacoustic imaging can accurately measure cerebral venous oxyhemoglobin saturation (So₂) in a neonatal model of hypoxia-ischemia. In neonatal piglets, which have a skull thickness comparable to that of human neonates, we compared the photoacoustic measurement of sagittal sinus So₂ against that measured directly by blood sampling over a wide range of conditions. Systemic hypoxia was produced by decreasing inspired oxygen stepwise (i.e., 100, 21, 19, 17, 15, 14, 13, 12, 11, and 10%) with and without unilateral or bilateral ligation of the common carotid arteries to enhance hypoxia-ischemia. Transcranial photoacoustic sensing enabled us to detect changes in sagittal sinus O₂ saturation throughout the tested range of 5-80% without physiologically relevant bias. Despite lower cortical perfusion and higher oxygen extraction in groups with carotid occlusion at equivalent inspired oxygen, photoacoustic measurements successfully provided a robust linear correlation that approached the line of identity with direct blood sample measurements. Receiver-operating characteristic analysis for discriminating So₂ <30% showed an area under the curve of 0.84 for the pooled group data, and 0.87, 0.91, and 0.92 for hypoxia alone, hypoxia plus unilateral occlusion, and hypoxia plus bilateral occlusion subgroups, respectively. The detection precision in this critical range was confirmed with sensitivity (87.0%), specificity (86.5%), accuracy (86.8%), positive predictive value (90.5%), and negative predictive value (81.8%) in the combined dataset. These results validate the capability of photoacoustic sensing technology to accurately monitor sagittal sinus So₂ noninvasively over a wide range and support its use for early detection of neonatal hypoxia-ischemia. NEW & NOTEWORTHY We present data to validate the noninvasive photoacoustic measurement of sagittal sinus oxyhemoglobin saturation. In particular, this paper demonstrates the robustness of this methodology during a wide range of hemodynamic and physiological changes induced by the stepwise decrease of fractional inspired oxygen to produce hypoxia and by unilateral and bilateral ligation of the common carotid arteries preceding hypoxia to produce hypoxia-ischemia. This technique may be useful for diagnosing risk of neonatal hypoxic-ischemic encephalopathy.

In vivo photoacoustic imaging of chorioretinal oxygen gradients

Chorioretinal imaging has a crucial role for the patients with chorioretinal vascular diseases, such as neovascular age-related macular degeneration. Imaging oxygen gradients in the eye could better diagnose and treat ocular diseases. Here, we describe the use of photoacoustic ocular imaging (PAOI) in measuring chorioretinal oxygen saturation (CR  -  sO2) gradients in New Zealand white rabbits (n  =  5) with ocular ischemia. We observed good correlation (R2  =  0.98) between pulse oximetry and PAOI as a function of different oxygen percentages in inhaled air. We then used an established ocular ischemia model in which intraocular pressure is elevated to constrict ocular blood flow, and notice a positive correlation (R2  =  0.92) between the injected volume of phosphate buffered saline (PBS) and intraocular pressure (IOP) as well as a negative correlation (R2  =  0.98) between CR  -  sO2 and injected volume of PBS. The CR  -  sO2 was measured before (baseline), during (ischemia), and after the infusion (600-μL PBS). The ischemia-reperfusion model did not affect the measurement of the sO2 using a pulse oximeter on the animal's paw, but the chorioretinal PAOI signal showed a nearly sixfold decrease in CR  -  sO2 (n  =  5, p  =  0.00001). We also observe a sixfold decrease in CR  -  sO2 after significant elevation of IOP during ischemia, with an increase close to baseline during reperfusion. These data suggest that PAOI can detect changes in chorioretinal oxygenation and may be useful for application to imaging oxygen gradients in ocular disease.