Combined diffuse optical tomography and photoacoustic tomography for enhanced functional imaging of small animals: a methodological study on phantoms

Deep learning methods hold promise for light fluence compensation in three-dimensional optoacoustic imaging

SIGNIFICANCE

Quantitative optoacoustic imaging (QOAI) continues to be a challenge due to the influence of nonlinear optical fluence distribution, which distorts the optoacoustic image representation. Nonlinear optical fluence correction in OA imaging is highly ill-posed, leading to the inaccurate recovery of optical absorption maps. This work aims to recover the optical absorption maps using deep learning (DL) approach by correcting for the fluence effect.

AIM

Different DL models were compared and investigated to enable optical absorption coefficient recovery at a particular wavelength in a nonhomogeneous foreground and background medium.

APPROACH

Data-driven models were trained with two-dimensional (2D) Blood vessel and three-dimensional (3D) numerical breast phantom with highly heterogeneous/realistic structures to correct for the nonlinear optical fluence distribution. The trained DL models such as U-Net, Fully Dense (FD) U-Net, Y-Net, FD Y-Net, Deep residual U-Net (Deep ResU-Net), and generative adversarial network (GAN) were tested to evaluate the performance of optical absorption coefficient recovery (or fluence compensation) with in-silico and in-vivo datasets.

RESULTS

The results indicated that FD U-Net-based deconvolution improves by about 10% over reconstructed optoacoustic images in terms of peak-signal-to-noise ratio. Further, it was observed that DL models can indeed highlight deep-seated structures with higher contrast due to fluence compensation. Importantly, the DL models were found to be about 17 times faster than solving diffusion equation for fluence correction.

CONCLUSIONS

The DL methods were able to compensate for nonlinear optical fluence distribution more effectively and improve the optoacoustic image quality.

Noninvasive hemoglobin sensing and imaging: optical tools for disease diagnosis

SIGNIFICANCE

Measurement and imaging of hemoglobin oxygenation are used extensively in the detection and diagnosis of disease; however, the applied instruments vary widely in their depth of imaging, spatiotemporal resolution, sensitivity, accuracy, complexity, physical size, and cost. The wide variation in available instrumentation can make it challenging for end users to select the appropriate tools for their application and to understand the relative limitations of different methods.

AIM

We aim to provide a systematic overview of the field of hemoglobin imaging and sensing.

APPROACH

We reviewed the sensing and imaging methods used to analyze hemoglobin oxygenation, including pulse oximetry, spectral reflectance imaging, diffuse optical imaging, spectroscopic optical coherence tomography, photoacoustic imaging, and diffuse correlation spectroscopy.

RESULTS

We compared and contrasted the ability of different methods to determine hemoglobin biomarkers such as oxygenation while considering factors that influence their practical application.

CONCLUSIONS

We highlight key limitations in the current state-of-the-art and make suggestions for routes to advance the clinical use and interpretation of hemoglobin oxygenation information.

Compact fiber-free parallel-plane multi-wavelength diffuse optical tomography system for breast imaging

To facilitate the clinical applicability of the diffuse optical inspection device, a compact multi-wavelength diffuse optical tomography system for breast imaging (compact-DOTB) with a fiber-free parallel-plane structure was designed and fabricated for acquiring three-dimensional optical properties of the breast in continuous-wave mode. The source array consists of 56 surface-mounted micro light-emitting diodes (LEDs), each integrating three wavelengths (660, 750, and 840 nm). The detector array is arranged with 56 miniaturized surface-mounted optical sensors, each encapsulating a high-sensitivity photodiode (PD) and a low-noise current amplifier with a gain of 24×. The system provides 3,136 pairs of source-detector measurements at each wavelength, and the fiber-free design largely ensures consistency between source/detection channels while effectively reducing the complexity of system operation and maintenance. We have evaluated the compact-DOTB system's characteristics and demonstrated its performance in terms of reconstruction positioning accuracy and recovery contrast with breast-sized phantom experiments. Furthermore, the breast cancer patient studies have been carried out, and the quantitative results indicate that the compact-DOTB system is able to observe the changes in the functional tissue components of the breast after receiving the neoadjuvant chemotherapy (NAC), demonstrating the great potential of the proposed compact system for clinical applications, while its cost and ease of operation are competitive with the existing breast-DOT devices.

Nonlinear iterative perturbation scheme with simplified spherical harmonics (SP3 ) light propagation model for quantitative photoacoustic tomography

When using quantitative photoacoustic tomography (q-PAT) reconstruction to recover the optical absorption coefficients of tissue, the commonly used diffusion equation has several limitations in the case of the objects that have small geometries and high-absorption or low-scattering areas. Furthermore, the conventional perturbation reconstruction strategy is unsatisfactory when the target tissue containing large heterogeneous features. We herein present a modified q-PAT implementation that employs the higher-order photon migration model achieving the tradeoff between mathematical rigidity and computational efficiency. Besides, a nonlinear iterative method is proposed to obtain the perturbations of optical absorption considering the updating of the sensitivity matrix in calculating the fluence perturbations. Consequently, the distribution of tissue optical properties can be recovered in a robust way even if the targets with high absorption are included. The proposed approach has been validated by simulation, phantom and in vivo experiments, exhibiting promising performances in image fidelity and quantitative feasibility for practical applications.

Improving vascular imaging with co-planar mutually guided photoacoustic and diffuse optical tomography: a simulation study

Diffuse optical tomography (DOT) and photoacoustic tomography (PAT) are functional imaging modalities that provide absorption coefficient maps of the tissue. Spatial resolution of DOT is relatively low due to light scattering characteristics of the tissue. On the other hand, although PAT can resolve regions of different absorptions with a high spatial resolution, measuring the absolute value of optical absorptions using PAT is challenging due to unknown light fluence distribution in the tissue. Development of image guidance techniques using a priori information of imaging target structure has been shown to increase the accuracy of DOT. PAT is one such method that can be used as a complementary modality to serve as a guide for DOT image reconstruction. On the other hand, estimated fluence map provided by DOT can be used to quantitatively correct PAT images. In this study we introduce a mutually-guided imaging system for fast and simultaneous optical and photoacoustic measurements of tissue absorption map, where DOT is guided by the PAT image and vice versa. Using the obtained absorption map of the tissue, we then estimate the tissue scattering map. We conducted this study using a series of simulations on digital phantoms and demonstrated the effectiveness of the proposed method.

Efficient optical parameter mapping based on time-domain radiative transfer equation combined with parallel programming

A two-dimensional optical parameter mapping based on the time-domain radiative transfer equation (TD-RTE) is studied in this work. The finite element method with structured and unstructured grids is employed to solve TD-RTE and OpenMP parallel technology is employed to improve the computing efficiency. The sequential quadratic programming algorithm is used as a powerful optimization method to reconstruct absorption and scattering parameter fields and the maximum a posteriori estimation is employed by introducing the regularization term into the objective function to improve the ill-posed inverse problem. In addition, the effects of measurement errors on reconstruction accuracy are investigated thoroughly. All the simulation results demonstrate that the reconstructed scheme we developed is accurate and efficient in optical parameter mapping based on TD-RTE.

Spectral correction for handheld optoacoustic imaging by means of near-infrared optical tomography in reflection mode

In vivo imaging of tissue/vasculature oxygen saturation levels is of prime interest in many clinical applications. To this end, the feasibility of combining two distinct and complementary imaging modalities is investigated: optoacoustics (OA) and near-infrared optical tomography (NIROT), both operating noninvasively in reflection mode. Experiments were conducted on two optically heterogeneous phantoms mimicking tissue before and after the occurrence of a perturbation. OA imaging was used to resolve submillimetric vessel-like optical absorbers at depths up to 25 mm, but with a spectral distortion in the OA signals. NIROT measurements were utilized to image perturbations in the background and to estimate the light fluence inside the phantoms at the wavelength pair (760 nm, 830 nm). This enabled the spectral correction of the vessel-like absorbers' OA signals: the error in the ratio of the absorption coefficient at 830 nm to that at 760 nm was reduced from 60%-150% to 10%-20%. The results suggest that oxygen saturation (SO ₂ ) levels in arteries can be determined with <10% error and furthermore, that relative changes in vessels' SO ₂ can be monitored with even better accuracy. The outcome relies on a proper identification of the OA signals emanating from the studied vessels.

Plasmonic Optical Imaging of Gold Nanorods Localization in Small Animals

Gold nanoparticles (GNP) have been intensively investigated for applications in cancer imaging and therapy. Most imaging studies focused on microscopic imaging. Their potential as optical imaging probes for whole body small animal imaging has rarely been explored. Taking advantage of their surface plasmon resonance (SPR) properties, we aim to develop a noninvasive diffuse optical imaging method to map the distribution of a special type of GNP, gold nanorods (GNR), in small animals. We developed an integrated dual-modality imaging system capable of both x-ray computed tomography (XCT) and diffuse optical tomography (DOT). XCT provides the animal anatomy and contour required for DOT; DOT maps the distribution of GNR in the animal. This SPR enhanced optical imaging (SPROI) technique was investigated using simulation, phantom and mouse experiments. The distribution of GNR at various concentrations (0.1-100 nM, or 3.5 ug/g-3.5 mg/g) was successfully reconstructed from centimeter-scaled volumes. SPROI detected GNR at 18 μg/g concentration in the mouse breast tumor, and is 3 orders more sensitive than x-ray imaging. This study demonstrated the high sensitivity of SPROI in mapping GNR distributions in small animals. It does not require additional imaging tags other than GNR themselves. SPROI can be used to detect tumors targeted by GNR via passive targeting based on enhanced permeability and retention or via active targeting using biologically conjugated ligands.

Toward whole-body quantitative photoacoustic tomography of small-animals with multi-angle light-sheet illuminations

Several attempts to achieve the quantitative photoacoustic tomography (q-PAT) have been investigated using point sources or a single-angle wide-field illumination. However, these schemes normally suffer from low signal-to-noise ratio (SNR) or poor quantification in imaging applications on large-size domains, due to the limitation of ANSI-safety incidence and incompleteness in the data acquisition. We herein present a q-PAT implementation that uses multi-angle light-sheet illuminations and calibrated recovering-and-averaging iterations. The scheme can obtain more complete information on the intrinsic absorption from the multi-angle illumination mode, and collect SNR-boosted photoacoustic signals in the selected planes from the wide-field light-sheet excitation. Therefore, the sliced absorption maps over whole body of small-animals can be recovered in a measurement-flexible, noise-robust and computation-economic way. The proposed approach is validated by phantom, ex vivo and in vivo experiments, exhibiting promising performances in image fidelity and quantitative accuracy for practical applications.