Imaging light fluence in blood vessels by combining photoacoustic fluctuation imaging and ultrasound power doppler.

Numerous optical biomedical imaging or therapeutic modalities suffer from unknown light fluence distribution at depths. Photoacoustic (PA) imaging enables imaging of blood vessels. At the scale of the acoustic resolution, PA imaging probes the product between the fluence and effective optical absorption that depends on the size or density of blood vessels. In the case of unresolved vessels, fluence and absorption can not be decoupled using PA imaging alone without the use of inverse problems. Thus, we propose combining two modalities that are sensitive to blood vessels to directly image fluence maps within vascularized areas, including in unresolved vessels. To achieve fluence imaging, the combination of photoacoustic fluctuation (PAFI) and Ultrasound Power Doppler (UPD) images is considered. After exposing a new theoretical expression of the UPD image, we establish a fluence imaging method giving quantitative fluence in blood vessels. This method universally applies to arbitrary hematocrit and multi-scale vessel imaging. Using a spherical sparse array, we demonstrate 3D fluence imaging within blood vessels in simulation and experiments which is not possible with PAFI alone. Fluence imaging involves resolution compensation with a PSF filter that is compared to alternative simpler corrections. Overall, we show that combining PAFI and UPD has the potential for real-time light dosimetry or could enhance quantitative inverse problems in photoacoustic imaging.

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.

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.

3D Monte Carlo simulation of light distribution in mouse brain in quantitative photoacoustic computed tomography.

BACKGROUND: Photoacoustic computed tomography (PACT) detects light-induced ultrasound (US) waves to reconstruct the optical absorption contrast of the biological tissues. Due to its relatively deep penetration (several centimeters in soft tissue), high spatial resolution, and inherent functional sensitivity, PACT has great potential for imaging mouse brains with endogenous and exogenous contrasts, which is of immense interest to the neuroscience community. However, conventional PACT either assumes homogenous optical fluence within the brain or uses a simplified attenuation model for optical fluence estimation. Both approaches underestimate the complexity of the fluence heterogeneity and can result in poor quantitative imaging accuracy. METHODS: To optimize the quantitative performance of PACT, we explore for the first time 3D Monte Carlo (MC) simulation to study the optical fluence distribution in a complete mouse brain model. We apply the MCX MC simulation package on a digital mouse (Digimouse) brain atlas that has complete anatomy information. To evaluate the impact of the brain vasculature on light delivery, we also incorporate the whole-brain vasculature in the Digimouse atlas. k-wave toolbox was used to investigate the effect of inhomogeneous illumination on the reconstructed images and chromophore concentration estimation. RESULTS: The simulation results clearly show that the optical fluence in the mouse brain is heterogeneous at the global level and can decrease by a factor of five with increasing depth. Moreover, the strong absorption and scattering of the brain vasculature also induce the fluence disturbance at the local level. CONCLUSIONS: Both global and local fluence heterogeneity contributes to the reduced quantitative accuracy of the reconstructed PACT images of mouse brain. Correcting the optical fluence distribution can improve the quantitative accuracy of PACT.

Quantitative PA tomography of high resolution 3-D images: Experimental validation in a tissue phantom.

Quantitative photoacoustic tomography aims to recover the spatial distribution of absolute chromophore concentrations and their ratios from deep tissue, high-resolution images. In this study, a model-based inversion scheme based on a Monte-Carlo light transport model is experimentally validated on 3-D multispectral images of a tissue phantom acquired using an all-optical scanner with a planar detection geometry. A calibrated absorber allowed scaling of the measured data during the inversion, while an acoustic correction method was employed to compensate the effects of limited view detection. Chromophore- and fluence-dependent step sizes and Adam optimization were implemented to achieve rapid convergence. High resolution 3-D maps of absolute concentrations and their ratios were recovered with high accuracy. Potential applications of this method include quantitative functional and molecular photoacoustic tomography of deep tissue in preclinical and clinical studies.

In Vivo Quantitative Photoacoustic Diagnosis of Gastric and Intestinal Dysfunctions with a Broad pH-Responsive Sensor.

Gastrointestinal diseases affect many people in the world and significantly impair life quality and burden the healthcare system. The functional parameters of the gastrointestinal tract such as motility and pH can effectively reflect the changes of gastrointestinal activity in physiological and pathological conditions. Thus, a noninvasive method for real-time and quantitative measurement of gastrointestinal functional parameters in vivo is highly desired. At present, there are many strategies widely used for the diagnosis of gastrointestinal diseases in clinic, including X-ray barium meal examination, ultrasound imaging, radionuclide examination, endoscopy, etc. However, these methods are limited in determining the gastrointestinal status and cannot provide comprehensive quantitative information. Photoacoustic imaging (PAI) is a rapid noninvasive real-time imaging technique in which multiple types of functional and quantitative information can be simultaneously obtained. Unfortunately, very few ratiometric PAI contrast agents have been reported for quantification of gastrointestinal functional parameters in vivo. In this work, a broad, pH-responsive ratiometric sensor based on polyaniline and Au triangular nanoplates was developed. Utilizing the sensor as a contrast agent, PAI served as an all-in-one technique, accurately measuring the gastrointestinal functional parameters in a single test. Notably, this sensor was examined to be ultrasensitive with pH responses as fast as 0.6 s and durability as long as 24 h, and was repeatable and reversible for longitudinal monitoring. The quantitative results demonstrated a significant disorder in motility and decrease in pH for gastric and duodenal ulcers. Collectively, the combination of PAI and this broad pH-responsive sensor might be a promising candidate for quantitative diagnosis of gastrointestinal diseases.

Three-dimensional quantitative photoacoustic tomography using an adjoint radiance Monte Carlo model and gradient descent.

Quantitative photoacoustic tomography aims to recover maps of the local concentrations of tissue chromophores from multispectral images. While model-based inversion schemes are promising approaches, major challenges to their practical implementation include the unknown fluence distribution and the scale of the inverse problem. We describe an inversion scheme based on a radiance Monte Carlo model and an adjoint-assisted gradient optimization that incorporates fluence-dependent step sizes and adaptive moment estimation. The inversion is shown to recover absolute chromophore concentrations, blood oxygen saturation, and the Grüneisen parameter from in silico three-dimensional phantom images for different radiance approximations. The scattering coefficient is assumed to be homogeneous and known a priori.

Quantitative phase-filtered wavelength-modulated differential photoacoustic radar tumor hypoxia imaging toward early cancer detection.

Overcoming the limitations of conventional linear spectroscopy used in multispectral photoacoustic imaging, wherein a linear relationship is assumed between the absorbed optical energy and the absorption spectra of the chromophore at a specific location, is crucial for obtaining accurate spatially-resolved quantitative functional information by exploiting known chromophore-specific spectral characteristics. This study introduces a non-invasive phase-filtered differential photoacoustic technique, wavelength-modulated differential photoacoustic radar (WM-DPAR) imaging that addresses this issue by eliminating the effect of the unknown wavelength-dependent fluence. It employs two laser wavelengths modulated out-of-phase to significantly suppress background absorption while amplifying the difference between the two photoacoustic signals. This facilitates pre-malignant tumor identification and hypoxia monitoring, as minute changes in total hemoglobin concentration and hemoglobin oxygenation are detectable. The system can be tuned for specific applications such as cancer screening and SO2 quantification by regulating the amplitude ratio and phase shift of the signal. The WM-DPAR imaging of a head and neck carcinoma tumor grown in the thigh of a nude rat demonstrates the functional PA imaging of small animals in vivo. The PA appearance of the tumor in relation to tumor vascularity is investigated by immunohistochemistry. Phase-filtered WM-DPAR imaging is also illustrated, maximizing quantitative SO2 imaging fidelity of tissues. Oxygenation levels within a tumor grown in the thigh of a nude rat using the two-wavelength phase-filtered differential PAR method.