Tissue-mimicking Phantom Experiments Research Articles

SWENet: A Physics-Informed Deep Neural Network (PINN) for Shear Wave Elastography.

Shear wave elastography (SWE) enables the measurement of elastic properties of soft materials in a non-invasive manner and finds broad applications in various disciplines. The state-of-the-art SWE methods rely on the measurement of local shear wave speeds to infer material parameters and suffer from wave diffraction when applied to soft materials with strong heterogeneity. In the present study, we overcome this challenge by proposing a physics-informed neural network (PINN)-based SWE (SWENet) method. The spatial variation of elastic properties of inhomogeneous materials has been introduced in the governing equations, which are encoded in SWENet as loss functions. Snapshots of wave motions have been used to train neural networks, and during this course, the elastic properties within a region of interest illuminated by shear waves are inferred simultaneously. We performed finite element simulations, tissue-mimicking phantom experiments, and ex vivo experiments to validate the method. Our results show that the shear moduli of soft composites consisting of matrix and inclusions of several millimeters in cross-section dimensions with either regular or irregular geometries can be identified with excellent accuracy. The advantages of the SWENet over conventional SWE methods consist of using more features of the wave motions and enabling seamless integration of multi-source data in the inverse analysis. Given the advantages of SWENet, it may find broad applications where full wave fields get involved to infer heterogeneous mechanical properties, such as identifying small solid tumors with ultrasound SWE, and differentiating gray and white matters of the brain with magnetic resonance elastography.

A one-step method for quantitative microwave-induced thermoacoustic tomography.

Electrical conductivity directly correlates with tissue functional information such as blood and water contents, and quantitative extraction of tissue conductivity is of significant importance for disease detection and diagnosis using microwave-induced thermoacoustic tomography (TAT). The existing quantitative TAT (qTAT) approaches capable of extracting tissue conductivity require two steps for the recovery of conductivity. Such two steps approaches depend on an accurate knowledge of the microwave energy loss distribution in tissue and offer a slow computational convergence rate. The purpose of this study is to develop a new algorithm to reconstruct tissue conductivity with higher reconstruction accuracy and greater computational efficiency. We propose an improved qTAT method for direct recovery of tissue conductivity from thermoacoustic data measured along the boundary with only one step without the dependence of microwave energy loss information. The feasibility of our one-step qTAT method is validated in both simulated and tissue-mimicking phantom experiments with single-target and multi-target configurations with different contrast levels. Compared with the previous two-step methods, our one-step qTAT method improves the accuracy of conductivity recovery with approximately one-fold reduction in the mean absolute error (MAE) and root mean square error (RMSE) with p-values greater than 0.05. In addition, the convergence rate is improved by more than two folds for the one-step method. The study demonstrates that new method can quantitatively reconstruct conductivity of tissue more accurately and efficiently over the existing qTAT methods, leading to potentially enhanced accuracy for disease detection and diagnosis.

Panoramic volumetric clinical handheld photoacoustic and ultrasound imaging

Photoacoustic (PA) imaging has gained much attention, providing structural and functional information in combination with clinical ultrasound (US) imaging systems. 2D PA and US imaging is easily implemented, but its heavy dependence on operator skills makes 3D imaging preferable. In this study, we propose a panoramic volumetric clinical PA and US imaging system equipping a handheld imaging scanner weighing 600 g and measuring 70 × 62 × 110 mm3. Multiple PA/US scans were performed to cover a large field-of-view (FOV), and the acquired PA/US volumes were mosaic-stitched after manually correcting the positions and rotations in a total of 6 degrees of freedom. PA and US maximum amplitude projection images were visualized online, while spectral unmixed data was quantified offline. The performance of the system was tested via tissue-mimicking phantom experiments. The system’s potential was confirmed in vivo by panoramically imaging vascular networks in human arms and necks, with FOVs of 331 × 38 and 129 × 120 mm2, respectively. Further, we quantified hemoglobin oxygen saturation levels in the radial artery, brachial artery, carotid artery, and jugular vein. We hope that this system can be applied for various clinical fields such as cardiovascular imaging, dermatology, vascular surgery, internal medicine, and oncology.

A Miniature Forward-Looking Phased-Array Transducer for Interventional Biopsy Guidance

Ultrasound-guided interventional biopsy is becoming an increasingly popular and valuable tool in the clinic. Conventionally, low-frequency (1–5 MHz) ultrasound probes are employed on the patient’s body surface for guiding interventional procedures, leading to low imaging resolution and low puncture accuracy. Several efforts have been made to achieve precise punctures, such as inserting a miniaturized high-frequency phased-array transducer into the patient’s body. However, the interventional devices (introducer biopsy needles) are all separate from those ultrasound probes, which will cause additional damage and operation complexity. Therefore, in this work, a miniature higher frequency phased-array probe integrated with a 0.4 mm intervention working channel is developed, which had 48 array elements and an outer diameter of only 3 mm. The center frequency and −6 dB bandwidth of this probe are measured as 26.2 MHz and 59.6%, respectively. For evaluating its guiding performance, the wire-phantom, ex vivo tissue, and tissue-mimicking phantom experiments were tested. According to the experiments, the axial imaging resolution and lateral resolution can be calculated as 88 and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$278~\mu \text{m}$ </tex-math></inline-formula> at a distance of 2 mm far away, respectively, and the effective detecting depth is 12 mm. All these results show that our proposed ultrasound transducer and method can adapt to the works in high-precision interventional guidance.

Acoustic super-resolved spatiotemporal monitoring of theranostic nanodroplets with tuned post-activation dynamics

Phase-change nanodroplets (PCNDs) have been used as controllable theranostic agents in diverse therapeutic and diagnostic scenarios over the years. However, there is still a pressing need to monitor the accurate distribution of non-flowing extravascular PCNDs by clinical ultrasound for further quantitative analysis. Here, we propose a spatiotemporally super-resolved ultrasound monitoring technique based on tuned post-activation dynamics of high-bulk-boiling-point PCNDs with customized perfluorocarbon cores. The underlying idea was to make the stochastic recondensation-induced contrast signal dominate the total post-activation signal, thus obtaining detectable and resolvable recondensation signals at physiological temperature. The recondensation signal was extracted by inter-frame subtraction and then processed by a deep learning-based detection algorithm tailored to the recondensation signal patterns. Experiments in tissue-mimicking phantoms demonstrate that co-restricting the concentration of PCNDs and the focus-wave activation pulse duration could help generate recondensation signals with ideal detectability and sparsity for accurate monitoring. Meanwhile, the quantitative analysis of the super-resolved results shows the spatiotemporal sensitivity of the proposed technique under varying concentrations and activation pulse durations, which was consistent with the patterns drawn from the total post-activation signal and existing theories on post-activation dynamics of PCNDs. This technique may be suitable for in-depth extravascular monitoring and dose analysis for PCNDs-involved therapies.

Dual-Mode Volumetric Optoacoustic and Contrast Enhanced Ultrasound Imaging With Spherical Matrix Arrays.

Spherical matrix arrays represent an advantageous tomographic detection geometry for non-invasive deep tissue mapping of vascular networks and oxygenation with volumetric optoacoustic tomography (VOT). Hybridization of VOT with ultrasound (US) imaging remains difficult with this configuration due to the relatively large inter-element pitch of spherical arrays. We suggest a new approach for combining VOT and US contrast-enhanced 3D imaging employing injection of clinically-approved microbubbles. Power Doppler (PD) and US localization imaging were enabled with a sparse US acquisition sequence and model-based inversion based on infimal convolution of total variation (ICTV) regularization. In vitro experiments in tissue-mimicking phantoms and in living mouse brain demonstrate the powerful capabilities of the new dual-mode imaging approach attaining 80 μm spatial resolution and a more than 10 dB signal to noise improvement with respect to a classical delay and sum beamformer. Microbubble localization and tracking allowed for flow velocity mapping up to 40 mm/s.

Improved two-point frequency shift power method for measurement of shear wave attenuation

Quantitative assessment of mechanical properties of biological soft tissues is frequently evaluated using a noninvasive modality, called ultrasound shear wave elastography (SWE). SWE typically exerts an acoustic radiation force (ARF) to produce shear waves propagating in the lateral direction for which velocities and attenuations are measured. The tissue viscoelasticity is commonly studied by investigating the shear wave phase velocity curves. Viscoelastic tissue properties can also be characterized through utilizing various shear wave attenuation techniques. In this study, we propose an improved method for measuring the shear wave attenuation, called two-point frequency shift power (2P-FSP), which is an improved version of the two-point frequency shift (2P-FS) method. The technique is fully data driven and does not use a rheological model for mathematical modeling. The 2P-FSP method utilizes the power spectra frequency shift of shear waves measured at two spatial positions, which provides robustness to noise. The conceptual basis for the 2P-FSP is provided and tested with numerical and experimental data. We investigated how the location of the first signal and the distance interval between the two locations influence the shear wave attenuation measurement in the 2P-FSP technique. We utilized the 2P-FSP method on numerical phantom data generated using a finite-difference-based method in tissue-mimicking viscoelastic media. Moreover, we tested the 2P-FSP method with data from custom-made tissue-mimicking viscoelastic phantom experiments, and ex vivo porcine liver. We compared results from the proposed technique with results from 2P-FS and analytical values in the case of simulations. The results showed that the 2P-FSP method provides improved results over the 2P-FS technique for lower signal-to-noise ratio (SNR) and locations farther from the push location considered, and can be used to measure attenuation of viscoelastic soft tissues.

Compressed Sensing Photoacoustic Imaging Reconstruction Using Elastic Net Approach.

Photoacoustic imaging involves reconstructing an estimation of the absorbed energy density distribution from measured ultrasound data. The reconstruction task based on incomplete and noisy experimental data is usually an ill-posed problem that requires regularization to obtain meaningful solutions. The purpose of the work is to propose an elastic network (EN) model to improve the quality of reconstructed photoacoustic images. To evaluate the performance of the proposed method, a series of numerical simulations and tissue-mimicking phantom experiments are performed. The experiment results indicate that, compared with the L 1-norm and L 2-normbased regularization methods with different numerical phantoms, Gaussian noise of 10-50 dB, and different regularization parameters, the EN method with α = 0.5 has better image quality, calculation speed, and antinoise ability.

Phase Velocity Estimation With Expanded Bandwidth in Viscoelastic Phantoms and Tissues.

Ultrasound shear wave elastography (SWE) is a technique used to measure mechanical properties to evaluate healthy and pathological soft tissues. SWE typically employs an acoustic radiation force (ARF) to generate laterally propagating shear waves that are tracked in the spatiotemporal domains, and algorithms are used to estimate the wave velocity. The tissue viscoelasticity is often examined through analyzing the shear wave phase velocity dispersion curves, which is the variation of phase velocity with frequency or wavelength. A number of available methods to estimate dispersion exist, which can differ in resolution and variance. Moreover, most of these techniques reconstruct dispersion curves for a limited frequency band. In this work, we propose a novel method used for dispersion curve calculation. Our unique approach uses a generalized Stockwell transformation combined with a slant frequency-wavenumber analysis (GST-SFK). We tested the GST-SFK method on numerical phantom data generated using a finite-difference-based method in tissue-mimicking viscoelastic media. In addition, we evaluated the method on numerical shear wave motion data with different amounts of white Gaussian noise added. Additionally, we performed tests on data from custom-made tissue-mimicking viscoelastic phantom experiments, ex vivo porcine liver measurements, and in vivo liver tissue experiments. We compared results from our method with two other techniques used for estimating shear wave phase velocity: the two-dimensional Fourier transform (2D-FT) and the eigenvector (EV) method. Tests carried out revealed that the GST-SFK method provides dispersion curve estimates with lower errors over a wider frequency band in comparison to the 2D-FT and EV methods. In addition, the GST-SFK provides expanded bandwidth by a factor of two or more to be used for phase velocity estimation, which is meaningful for a tissue dispersion analysis in vivo.

Water-cooled microwave ablation array for bloodless rapid transection of the liver

Background Microwaves (MWs) deliver relatively high temperatures into biological tissue and cover a large ablation zone. This study aims to evaluate the efficacy and effectiveness of water-cooled double-needle MW ablation arrays in assisting the hepatic transection of an in vivo pig model. Methods Our research program comprised computer modeling, tissue-mimicking phantom experiments, and in vivo pig liver experiments. Computer modeling was based on the finite element method (FEM) to evaluate ablation temperature distributions. In tissue-mimicking phantom and in vivo pig liver ablation experiments, the performances of the water-cooled MW ablation array and conventional clamp crushing liver resection were compared. Results FEM showed that the maximum lateral ablation diameter at 100 W output and a duration of 60 s was 3 cm (assessed at 50 °C isotherm). In the phantom, the maximum transverse ablation diameter of the double-needle MW ablation increased rapidly to 3 cm in 60 s at 50 W. The blood loss and blood loss per transection area in Group A were significantly lower than those in Group B (18 (7–26) ml vs. 34 (19–57) ml, and 2.4 (2–3.1) ml/cm2 vs. 6.9 (3.2–8.3) ml/cm2, respectively) (p < 0.05). The transection speed in Group A (2.6(1.9–3.8) cm2/min) was significantly faster than that in Group B (1.7(1.1–2.2) cm2/min) (p < 0.05). Conclusion In this experimental model, the new water-cooled MW array-assisted liver resection (LR) has the potential advantage of less blood loss and rapid removal than the conventional LR.

Micro Air-Pulse Spatial Deformation Spreading Characterizes Degree of Anisotropy in Tissues.

In optical coherence elastography (OCE), air-pulse stimulation has been widely used to produce propagation of mechanical waves for elastic characterization of tissues. In this paper, we propose the use of spatial deformation spreading (SDS) on the surface of samples produced by air-pulse stimulation for the OCE of transverse isotropic tissues. Experiments in isotropic tissue-mimicking phantoms and anisotropic chicken tibialis muscle were conducted using a spectral-domain optical coherence tomography system synchronized with a confocal air-pulse stimulation. SDS measurements were compared with wave speeds values calculated at different propagation angles. We found an approximately linear relationship between shear wave speed and SDS in isotropic phantoms, which was confirmed with predictions made by the numerical integration of a wave propagation model. Experimental measurements in chicken muscle show a good agreement between SDS and surface wave speed taken along and across the axis of symmetry of the tissues, also called degree of anisotropy. In summary, these results demonstrated the capabilities of SDS produced by the air-pulse technique in measuring the shear elastic anisotropy of transverse isotropic tissues.

Characterization of tissue mimicking phantoms and soft tissues using ultrasound shear wave elastography and power-law models

Characterization of mechanical properties of tissue has become an important area of study over the last two decades. Shear wave elastography (SWE) is being used in many clinical applications to characterize, and multiple mechanical properties are being reported. To more comprehensively characterize soft tissues, we have focused on frequency-domain methods for evaluating viscoelasticity. We measure the shear wave velocity and attenuation and the variation with frequency. We will present results with the Kelvin-Voigt fractional derivative model and general power laws to characterize data from SWE experiments in tissue-mimicking phantoms and exvivo and in vivo tissue. Tissue mimicking phantoms from CIRS, inc., that have varying amounts of viscoelasticity will be investigated. Measurements from ex vivo and in vivo liver and kidney will also be used for this study. We will examine the range of the power-law exponents associated with these samples and the different models to provide understanding of the range of these parameters and how well tissue mimicking phantoms realize the parameters measured in soft tissues.

A time-aligned plane wave compounding method for high frame rate shear wave elastography

Shear wave elastography (SWE) is an established ultrasonic imaging technique, that provides quantitative measurements of tissue mechanical properties. This technique relies on the combination of acoustic radiation force push beams to generate propagating shear waves and ultrafast imaging, which allows high two-dimensional imaging frame rates to capture the induced motion. Utilizing coherent plane wave compounding (PWC) can improve signal-to-noise ratio (SNR) of acquired data. While the image quality improves, the pulse repetition frequency (PRF) is reduced, reaching limiting bandwidths to perform SWE. To address these challenges, a method for making SWE measurements with high PRF and SNR is presented. The idea follows the Time Aligned Sequential Tracking method, proposed to allow SWE with enhanced SNR in conventional clinical ultrasound scanners. The time alignment process is applied here to the full field-of-view, acquired by using plane waves transmitted at different angles. In this way, the full PRF and SNR gains are obtained. Results are shown from experiments in tissue-mimicking phantoms, where motion and extracted shear wave velocity are compared for the traditional and proposed data processing schemes. Preliminary results on arterial phantoms are also discussed, to emphasize the beneficial effects of the method in dispersive geometries.

Ultrasound Deep Learning for Wall Segmentation and Near-Wall Blood Flow Measurement

Studies of medical flow imaging have technical limitations for accurate analysis of blood flow dynamics and vessel wall interaction at arteries. We propose a new deep learning-based boundary detection and compensation (DL-BDC) technique in ultrasound (US) imaging. It can segment vessel boundaries by harnessing the convolutional neural network and wall motion compensation in the analysis of near-wall flow dynamics. The network enables training from real and synthetic US images together. The performance of the technique is validated through synthetic US images and tissue-mimicking phantom experiments. The neural network performs well with high Dice coefficients of over 0.94 and 0.9 for lumens and walls, outperforming previous segmentation techniques. Then, the performance of the wall motion compensation is examined for compliant phantoms. When DL-BDC is applied to flow influenced by wall motion, root-mean-square errors are less than 0.07%. The technique is utilized to analyze flow dynamics and wall interaction with varying elastic moduli of the phantoms. The results show that the flow dynamics and wall shear stress values are consistent with the expected values of the compliant phantoms, and their wall motion behavior is observed with pulse wave propagation. This strategy makes US imaging capable of simultaneous measurement of blood flow and vessel dynamics in human arteries for their accurate interaction analysis. DL-BDC can segment vessel walls fast, accurately, and robustly. It enables to measure the near-wall flow precisely by determining the vessel boundary dynamics. This approach can be beneficial in flow dynamics and wall interaction analyses in various biomedical applications.

Phase Modulation Beamforming for Ultrafast Plane-Wave Imaging.

In order to improve the spatial resolution for high-frame-rate imaging, a new image formation approach is proposed based on introducing very weak aberration into received data, then combining the multiple results by taking the pixel-wise standard deviation of multiple aberrated images and subtracting the result from the delay-and-sum image. This approach is demonstrated in simulations, tissue-mimicking phantom experiments, and in vivo imaging. Simulations indicate the lateral full-width half-maximum (FWHM) of targets decreases by 38.24% ± 6.38%. In imaging wire targets in a tissue-mimicking phantom at 7.8 MHz, wire target FWHM decreases by 35.91% ± 5.39%. However, contrast was observed to decrease by 1.23 dB and contrast-to-noise ratio (CNR) by 18.5% in phantom studies due to the subtraction of similar images, which increases the number of dark pixels in the image. Finally, the proposed technique is tested in vivo, with images showing improvements similar to those in tissue-mimicking phantoms, including increased separation between closely spaced targets.

Computer modeling and in vitro experimental study of water-cooled microwave ablation array

Introduction Microwaves (MWs) quickly deliver relatively high temperatures into tumors and cover a large ablation zone. We present a research protocol for using water-cooled double-needle MW ablation arrays for tumor ablation here. Material and methods Our research program includes computer modeling, tissue-mimicking phantom experiments, and in vitro swine liver experiments. The computer modeling is based on the finite element method (FEM) to evaluate ablation temperature distributions. In tissue-mimicking phantom and in vitro swine liver ablation experiments, the performances of the new device and the single-needle MW device currently used in clinical practice are compared. Results FEM shows that the maximum transverse ablation diameter (MTAD) is 4.2 cm at 100 W output and 300 s (assessed at the 50 °C isotherm). In the tissue-mimicking phantom, the MTDA is 2.6 cm at 50 W and 300 s in single-needle MW ablation, and 4 cm in double needle MW ablation array. In in vitro swine liver experiments, the MTAD is 2.820 ± 0.127 cm at 100 W and 300 s in single-needle MW ablation, and 3.847 ± 0.103 cm in MW ablation array. Conclusion A new type of water-cooled MW ablation array is designed and tested, and has potential advantages over currently used devices.

Two-Point Frequency Shift Method for Shear Wave Attenuation Measurement.

Ultrasound shear wave elastography (SWE) is an increasingly used noninvasive modality for quantitative evaluation of tissue mechanical properties. SWE typically uses an acoustic radiation force to produce laterally propagating shear waves that are tracked in the spatial and temporal domains, in order to obtain the wave velocity. One of the ways to study the viscoelasticity is through studying the shear wave phase velocity dispersion curves. Shear wave attenuation can be also characterized in viscoelastic tissues with methods that use multiple lateral data samples. In this article, we present an alternative method for measuring the shear wave attenuation without using a rheological model two-point frequency shift (2P-FS). The technique uses information related to the amplitude spectra FS of shear waves measured at only two lateral locations. The theoretical basis for the 2P-FS is derived and validated. We examined how the first signal position and the distance between the two locations affect the shear wave attenuation estimation in the 2P-FS method. We tested this new method on digital phantom data created using the local interaction simulation approach (LISA) in viscoelastic media. Moreover, we tested data acquired from custom-made tissue-mimicking viscoelastic phantom experiments and ex vivo porcine liver measurements. We compared results from the 2P-FS method with the other two techniques used for assessing a shear wave attenuation: the FS-based method and the attenuation-measuring ultrasound shear wave elastography (AMUSE) technique. In addition, we evaluated the 2P-FS algorithm with different levels of added white Gaussian noise to the shear wave particle velocity using numerical phantoms. Tests conducted showed that the 2P-FS method gives robust results based on only two measurements and can be used to measure attenuation of viscoelastic soft tissues.

Monitoring of Adult Zebrafish Heart Regeneration Using High-Frequency Ultrasound Spectral Doppler and Nakagami Imaging.

This paper reports the feasibility of Nakagami imaging in monitoring the regeneration process of zebrafish hearts in a noninvasive manner. In addition, spectral Doppler waveforms that are typically used to access the diastolic function were measured to validate the performance of Nakagami imaging. A 30-MHz high-frequency ultrasound array transducer was used to acquire backscattered echo signal for spectral Doppler and Nakagami imaging. The performances of both methods were validated with flow and tissue-mimicking phantom experiments. For in vivo experiments, both spectral Doppler and Nakagami imaging were simultaneously obtained from adult zebrafish with amputated hearts. Longitudinal measurements were performed for five zebrafish. From the experiments, the E/A ratio measured using spectral Doppler imaging increased at 3 days post-amputation (3 dpa) and then decreased to the value before amputation, which were consistent with previous studies. Similar results were obtained from the Nakagami imaging where the Nakagami parameter value increased at 3 dpa and decreased to its original value. These results suggested that the Nakagami and spectral Doppler imaging would be useful techniques in monitoring the regeneration of heart or tissues.

Longitudinal shear waves for elastic characterization of tissues in optical coherence elastography

In dynamic optical coherence elastography (OCE), surface acoustic waves are the predominant perturbations. They constrain the quantification of elastic modulus to the direction of wave propagation only along the surface of tissues, and disregard elasticity gradients along depth. Longitudinal shear waves (LSW), on the other hand, can be generated at the surface of the tissue and propagate through depth with desirable properties for OCE: (1) LSW travel at the shear wave speed and can discriminate elasticity gradients along depth, and (2) the displacement of LSW is longitudinally polarized along the direction of propagation; therefore, it can be measured by a phase-sensitive optical coherence tomography system. In this study, we explore the capabilities of LSW generated by a circular glass plate in contact with a sample using numerical simulations and tissue-mimicking phantom experiments. Results demonstrate the potential of LSW in detecting an elasticity gradient along axial and lateral directions simultaneously. Finally, LSW are used for the elastography of ex vivo mouse brain and demonstrate important implications in in vivo and in situ measurements of local elasticity changes in brain and how they might correlate with the onset and progression of degenerative brain diseases.

Performance of optoacoustic and fluorescence imaging in detecting deep-seated fluorescent agents.

Fluorescent contrast agents are widely employed in biomedical research. While many studies have reported deep tissue imaging of fluorescent moieties using either fluorescence-based or absorption-based (optoacoustic) imaging systems, no systematic comparison has been performed regarding the actual performance of these imaging modalities in detecting deep-seated fluorescent agents. Herein, an integrated imager combining epi-fluorescence and volumetric optoacoustic imaging capabilities has been employed in order to evaluate image degradation with depth for several commonly-used near-infrared dyes in both modes. We performed controlled experiments in tissue-mimicking phantoms containing deeply embedded targets filled with different concentrations of Alexa Fluor 700, Alexa Fluor 750, indocyanine green (ICG) and IRDye 800CW. The results are further corroborated by multi-modal imaging of ICG through mouse tissues in vivo. It is shown that optoacoustics consistently provides better sensitivity in differentiating fluorescent targets located at depths beyond 2 mm in turbid tissues, as quantified by evaluating image contrast, signal to noise ratio and spatial resolution performance.