Tomographic Ultrasound and LED-Based Photoacoustic System for Preclinical Imaging

U-Net enhanced real-time LED-based photoacoustic imaging

Photoacoustic (PA) imaging is hybrid imaging modality with good optical contrast and spatial resolution. Portable, cost-effective, smaller footprint light emitting diodes (LEDs) are rapidly becoming important PA optical sources. However, the key challenge faced by the LED-based systems is the low light fluence that is generally compensated by high frame averaging, consequently reducing acquisition frame-rate. In this study, we present a simple deep learning U-Net framework that enhances the signal-to-noise ratio (SNR) and contrast of PA image obtained by averaging low number of frames. The SNR increased by approximately four-fold for both in-class in vitro phantoms (4.39 ± 2.55) and out-of-class in vivo models (4.27 ± 0.87). We also demonstrate the noise invariancy of the network and discuss the downsides (blurry outcome and failure to reduce the salt & pepper noise). Overall, the developed U-Net framework can provide a real-time image enhancement platform for clinically translatable low-cost and low-energy light source-based PA imaging systems.

Development of an integrated dual-modality 3D bioluminescence tomography and ultrasound imaging system for small animal tumor imaging

Ultrasound (US) is a valuable tool for imaging soft tissue and visualizing tumor contours. Taking the benefits of US, we presented an integrated dual-modality imaging system in this paper that achieves three-dimensional (3D) bioluminescence tomography (BLT) with multi-view bioluminescence images and 3D US imaging. The purpose of this system is to perform non-invasive, long-term monitoring of tumor growth in 3D images. US images can enhance the accuracy of the 3D BLT reconstruction and the bioluminescence dose within an object. Furthermore, an integrated co-registered scanning geometry was used to capture the fused BLT and US images. We validated the system with an in vivo experiment involving tumor-bearing mice. The results demonstrated the feasibility of reconstructing 3D BLT images in the tumor region using 3D US images. We used the dice coefficient and locational error to evaluate the similarity between the reconstructed source region and the actual source region. The dice coefficient was 88.5%, and the locational error was 0.4 mm when comparing the BLT and 3D US images. The hybrid BLT/US system could provide significant benefits for reconstructing the source of tumor location and conducting quantitative analysis of tumor size.

Design and characterization of color printed polyurethane films as biomedical phantom layers

We propose a new, user-friendly and accessible approach for fabricating thin phantoms with controllable absorption properties in magnitude, spectral shape, and spatial distribution. We utilize a standard office laser color printer to print on polyurethane thin films (40 - 60 μm), commonly available as medical film dressings and ultrasound probe covers. We demonstrate that the optical attenuation and absorption of the printed films correlate linearly with the printer input settings (opacity), which facilitates a systematic phantom design. The optical and acoustic properties of these polyurethane films are similar to biological tissue. We argue that these thin phantoms are applicable to a wide range of biomedical applications. Here, we introduce two potential applications: (1) homogeneous epidermal melanin phantoms and (2) spatially resolved absorbers for photoacoustic imaging. We characterize the thin phantoms in terms of optical properties, thickness, microscopic structure, and reproducibility of the printing process.

Deep-Learning-Based Algorithm for the Removal of Electromagnetic Interference Noise in Photoacoustic Endoscopic Image Processing

Despite all the expectations for photoacoustic endoscopy (PAE), there are still several technical issues that must be resolved before the technique can be successfully translated into clinics. Among these, electromagnetic interference (EMI) noise, in addition to the limited signal-to-noise ratio (SNR), have hindered the rapid development of related technologies. Unlike endoscopic ultrasound, in which the SNR can be increased by simply applying a higher pulsing voltage, there is a fundamental limitation in leveraging the SNR of PAE signals because they are mostly determined by the optical pulse energy applied, which must be within the safety limits. Moreover, a typical PAE hardware situation requires a wide separation between the ultrasonic sensor and the amplifier, meaning that it is not easy to build an ideal PAE system that would be unaffected by EMI noise. With the intention of expediting the progress of related research, in this study, we investigated the feasibility of deep-learning-based EMI noise removal involved in PAE image processing. In particular, we selected four fully convolutional neural network architectures, U-Net, Segnet, FCN-16s, and FCN-8s, and observed that a modified U-Net architecture outperformed the other architectures in the EMI noise removal. Classical filter methods were also compared to confirm the superiority of the deep-learning-based approach. Still, it was by the U-Net architecture that we were able to successfully produce a denoised 3D vasculature map that could even depict the mesh-like capillary networks distributed in the wall of a rat colorectum. As the development of a low-cost laser diode or LED-based photoacoustic tomography (PAT) system is now emerging as one of the important topics in PAT, we expect that the presented AI strategy for the removal of EMI noise could be broadly applicable to many areas of PAT, in which the ability to apply a hardware-based prevention method is limited and thus EMI noise appears more prominently due to poor SNR.

A multifunctional targeted nanoprobe with high NIR-II PAI/MRI performance for precise theranostics of orthotopic early-stage hepatocellular carcinoma

Early diagnosis and effective treatment of hepatocellular carcinoma (HCC) is quite critical for improving patients' prognosis. The combination of second near-infrared window photoacoustic imaging (NIR-II PAI) and T₂-magnetic resonance imaging (T₂-MRI) is promising for achieving omnibearing information on HCC diagnosis due to the complementary advantages of outstanding optical contrast, high temporospatial resolution and soft-tissue resolution. Thus, the rational design of a multifunctional targeted nanoplatform with outstanding performance in dual-modal NIR-II PAI/T₂-MRI is particularly valuable for precise diagnosis and imaging-guided non-invasive photothermal therapy (PTT) of early-stage HCC. Herein, a versatile targeted organic-inorganic hybrid nanoprobe was synthesized as a HCC-specific contrast agent for sensitive and efficient theranostics. The developed multifunctional targeted nanoprobe yielded superior HCC specificity, reliable stability and biocompatibility, high imaging contrast in both NIR-II PAI and T₂-MRI, and an excellent photothermal conversion efficiency (74.6%). Furthermore, the theranostic efficiency of the targeted nanoprobe was systematically investigated using the orthotopic early HCC-bearing mice model. The NIR-II PAI exhibited sensitive detection of ultra-small HCCs (diameter less than 1.8 mm) and long-term real-time monitoring of the tumor and nanoprobe targeting process in deep tissues. The T₂-MRI demonstrated clear imaging contrast and a spatial relationship between micro-HCC and adjacent structures for a comprehensive description of the tumor. Moreover, when using the targeted nanoprobe, the non-invasively targeted PTT of orthotopic early HCC was carried out under reliable dual-modal imaging guidance with remarkable anti-tumor efficiency and biosafety. This study provides an insight for constructing a multifunctional targeted nanoplatform for precise and comprehensive theranostics of early-stage HCC, which would greatly benefit the patients in the era of precision medicine.

Biomedical Photoacoustic Imaging and Sensing Using Affordable Resources

The photoacoustic (PA) effect, also called the optoacoustic effect, was discovered in the 1880s by Alexander Graham Bell and has been utilized for biomedical imaging and sensing applications since the early 1990s [...].

Simultaneous Dual-Modal Multispectral Photoacoustic and Ultrasound Macroscopy for Three-Dimensional Whole-Body Imaging of Small Animals

Photoacoustic imaging is a promising medical imaging technique that provides excellent function imaging of an underlying biological tissue or organ. However, it is limited in providing structural information compared to other imaging modalities, such as ultrasound imaging. Thus, to offer complete morphological details of biological tissues, photoacoustic imaging is typically integrated with ultrasound imaging. This dual-modal imaging technique is already implemented on commercial clinical ultrasound imaging platforms. However, commercial platforms suffer from limited elevation resolution compared to the lateral and axial resolution. We have successfully developed a dual-modal photoacoustic and ultrasound imaging to address these limitations, specifically targeting animal studies. The system can acquire whole-body images of mice in vivo and provide complementary structural and functional information of biological tissue information simultaneously. The color-coded depth information can be readily obtained in photoacoustic images using complementary information from ultrasound images. The system can be used for several biomedical applications, including drug delivery, biodistribution assessment, and agent testing.

Oxygen Saturation Imaging Using LED-Based Photoacoustic System

Oxygen saturation imaging has potential in several preclinical and clinical applications. Dual-wavelength LED array-based photoacoustic oxygen saturation imaging can be an affordable solution in this case. For the translation of this technology, there is a need to improve its accuracy and validate it against ground truth methods. We propose a fluence compensated oxygen saturation imaging method, utilizing structural information from the ultrasound image, and prior knowledge of the optical properties of the tissue with a Monte-Carlo based light propagation model for the dual-wavelength LED array configuration. We then validate the proposed method with oximeter measurements in tissue-mimicking phantoms. Further, we demonstrate in vivo imaging on small animal and a human subject. We conclude that the proposed oxygen saturation imaging can be used to image tissue at a depth of 6–8 mm in both preclinical and clinical applications.

Portable and Affordable Light Source-Based Photoacoustic Tomography

Photoacoustic imaging is a hybrid imaging modality that offers the advantages of optical (spectroscopic contrast) and ultrasound imaging (scalable spatial resolution and imaging depth). This promising modality has shown excellent potential in a wide range of preclinical and clinical imaging and sensing applications. Even though photoacoustic imaging technology has matured in research settings, its clinical translation is not happening at the expected pace. One of the main reasons for this is the requirement of bulky and expensive pulsed lasers for excitation. To accelerate the clinical translation of photoacoustic imaging and explore its potential in resource-limited settings, it is of paramount importance to develop portable and affordable light sources that can be used as the excitation light source. In this review, we focus on the following aspects: (1) the basic theory of photoacoustic imaging; (2) inexpensive light sources and different implementations; and (3) important preclinical and clinical applications, demonstrated using affordable light source-based photoacoustics. The main focus will be on laser diodes and light-emitting diodes as they have demonstrated promise in photoacoustic tomography-the key technological developments in these areas will be thoroughly reviewed. We believe that this review will be a useful opus for both the beginners and experts in the field of biomedical photoacoustic imaging.