We present the development of a photoacoustic tomography (PAT) imaging system with the demonstrated capability of obtaining high-throughput scans at a sustained rate of under 1 minute per animal using integrated robotics to assist in 3D PAT collection. This is a considerable achievement as there is currently no existing commercial or research PAT whole-body imaging system capable of high-throughput applications (15-20 animals per hour). High-throughput experimentation is imperative in the development, characterization, and use of rodent models of human diseases as it increases the number of animals that can be evaluated within a single experiment and may reduce the time under anesthesia for each animal, thereby improving the stability, duration, and confidence of longitudinal studies The developed system features coordinated automation for robotic animal manipulation, anesthesia distribution, temperature regulation, water management, laser excitation, and photoacoustic detection. Furthermore, as shown in validation studies using phantoms and live murine models, the prototype imaging platform demonstrates high-throughput performance while retaining high sensitivity and high resolution.
SignificanceDynamic photoacoustic computed tomography (PACT) is a valuable imaging technique for monitoring physiological processes. However, current dynamic PACT imaging techniques are often limited to two-dimensional spatial imaging. Although volumetric PACT imagers are commercially available, these systems typically employ a rotating measurement gantry in which the tomographic data are sequentially acquired as opposed to being acquired simultaneously at all views. Because the dynamic object varies during the data-acquisition process, the sequential data-acquisition process poses substantial challenges to image reconstruction associated with data incompleteness. The proposed image reconstruction method is highly significant in that it will address these challenges and enable volumetric dynamic PACT imaging with existing preclinical imagers.AimThe aim of this study is to develop a spatiotemporal image reconstruction (STIR) method for dynamic PACT that can be applied to commercially available volumetric PACT imagers that employ a sequential scanning strategy. The proposed reconstruction method aims to overcome the challenges caused by the limited number of tomographic measurements acquired per frame.ApproachA low-rank matrix estimation-based STIR (LRME-STIR) method is proposed to enable dynamic volumetric PACT. The LRME-STIR method leverages the spatiotemporal redundancies in the dynamic object to accurately reconstruct a four-dimensional (4D) spatiotemporal image.ResultsThe conducted numerical studies substantiate the LRME-STIR method’s efficacy in reconstructing 4D dynamic images from tomographic measurements acquired with a rotating measurement gantry. The experimental study demonstrates the method’s ability to faithfully recover the flow of a contrast agent with a frame rate of 10 frames per second, even when only a single tomographic measurement per frame is available.ConclusionsThe proposed LRME-STIR method offers a promising solution to the challenges faced by enabling 4D dynamic imaging using commercially available volumetric PACT imagers. By enabling accurate STIRs, this method has the potential to significantly advance preclinical research and facilitate the monitoring of critical physiological biomarkers.
Previous studies of dynamic photoacoustic computed tomography (PACT) consider the case where complete data can be rapidly acquired and employed to directly reconstruct a sequence of images. However, such frame-by-frame methods do not apply to commercially available volumetric PACT imaging systems with rotating gantries because the object varies during data acquisition. Furthermore, the rotation speed and the laser repetition rate limit the number of tomographic views per frame. In this study, a low-rank matrix estimation-based spatiotemporal image reconstruction method attuned to rotating-gantry volumetric PACT systems is proposed, and its accuracy is shown by numerical and experimental studies.
The ability to perform dynamic imaging of time-varying physiological processes in small animal models is critically needed to understand the progression of human diseases and develop new therapies. Photoacoustic computed tomography (PACT) has been recognized as a promising tool for small animal imaging because of its relatively low expense, high resolution, and good signal-to-noise ratio. By exploiting the optical absorption of hemoglobin or exogenous contrast agents, dynamic PACT holds excellent potential for measuring important time-varying biomarkers like tumor vascular perfusion. Nonetheless, current dynamic PACT technologies possess several limitations. Most three-dimensional (3D) PACT imagers employ a tomographic measurement process in which a gantry containing acoustic transducers is rotated about the animal. Such a rotating gantry is advantageous for limiting the cost of the system due to the decreased number of acoustic transducers and associated electronics and for enabling convenient delivery of the light to the object. However, this presents significant challenges for dynamic image reconstruction because only a few tomographic views are available to reconstruct each temporal frame. This work presents an efficient and accurate dynamic image reconstruction method that can be deployed with widely available 3D imagers using rotating gantries. In particular, a low-rank matrix estimation based spatiotemporal image reconstruction (LRME-STIR) algorithm is proposed. In a stylized virtual dynamic contrast-enhanced imaging study, the proposed LRME-STIR algorithm is shown to accurately recover a well characterized dynamic numerical murine phantom in which tumor vascular perfusion and breathing motion are modeled.
SignificanceTo effectively study preclinical animal models, medical imaging technology must be developed with a high enough resolution and sensitivity to perform anatomical, functional, and molecular assessments. Photoacoustic (PA) tomography provides high resolution and specificity, and fluorescence (FL) molecular tomography provides high sensitivity; the combination of these imaging modes will enable a wide range of research applications to be studied in small animals.AimWe introduce and characterize a dual-modality PA and FL imaging platform using in vivo and phantom experiments.ApproachThe imaging platform’s detection limits were characterized through phantom studies that determined the PA spatial resolution, PA sensitivity, optical spatial resolution, and FL sensitivity.ResultsThe system characterization yielded a PA spatial resolution of 173 ± 17 μm in the transverse plane and 640 ± 120 μm in the longitudinal axis, a PA sensitivity detection limit not less than that of a sample with absorption coefficient μa = 0.258 cm − 1, an optical spatial resolution of 70 μm in the vertical axis and 112 μm in the horizontal axis, and a FL sensitivity detection limit not <0.9 μM concentration of IR-800. The scanned animals displayed in three-dimensional renders showed high-resolution anatomical detail of organs.ConclusionsThe combined PA and FL imaging system has been characterized and has demonstrated its ability to image mice in vivo, proving its suitability for biomedical imaging research applications.
KEYWORDS: Spatial resolution, Imaging systems, Ultrasonography, Photoacoustic imaging, In vivo imaging, Signal detection, Video, Functional imaging, Doppler effect, Data acquisition
We present the continued development a clinical ultrasound (US) imaging device with a photoacoustic (PA) mode. The combined USPA imaging platform is designed around a compact US component capable of B-mode, M-mode, color Doppler, and pulsed wave Doppler US imaging modes with a 128 element US probe. The PA mode can support a 256 element PA probe with real-time 2D imaging up to 20 Hz. The PA signals are amplified by a 40 dB pre-amplifier while US mode signals bypass the circuit, resulting in high quality PA images. We demonstrate the USPA platform’s capabilities using tissue-mimicking phantoms.
Dynamic reconstruction of three-dimensional (3D) photoacoustic tomography (PAT) recovers a sequence of 3D optical contrast distributions and enables to monitor time-varying changes of the chromophore concentrations in biological tissues. To achieve a high frame rate, only a limited-angle few-view (even a single-view) acoustic measurements can be collected at each time frame. These sparse incomplete data represent a formidable challenge to obtain sequences of reconstructed images with both high spatial and temporal resolution. Furthermore, dynamic PAT reconstruction is extremely computationally and memory expensive. High-resolution spatiotemporal reconstruction of 3D objects is, in fact, computationally unfeasible using naïve extensions of classical PAT reconstruction methods for static images. In this study, we present a fast and accurate randomized algorithm for dynamic PAT reconstruction from few tomographic views. Our method is based on the fact that, for many applications of clinical interest, dynamic PAT images are semi-separable in space and time. That is the sequence of PAT images can be expanded using a relatively small number r of basis functions in space and time. Under this assumption, the dynamic PAT reconstruction problem is reformulated as a penalized least squares model, where the nuclear norm of the space-time image is used for the regularization term. By use of a randomized truncated singular value thresholding method, our approach can be implemented in a memory-efficient (only need to store the r spatial and temporal basis functions) and computationally-scalable (only r PAT reconstructions per iteration) manner. The effectiveness of the proposed method is demonstrated using numerical simulation and experimental data of a 3D phantom.
We present the results on development of the 3D imaging platform combining photoacoustic tomography and fluorescence (PAFT) for preclinical and biological research. This combined multimodal imaging instrument addresses known deficiencies in sensitivity, spatial resolution, and anatomical registration of the individual imaging components. Multiangle photoacoustic projections, excited by an OPO operating in the near-infrared window, of a live anesthetized animal are used to reconstruct large volumes (30 cm3) that show deep anatomical vasculature and blood-rich tissues with resolutions exceeding 150 μm. A sCMOS camera is used for simultaneous co-registered multi-angle optical imaging. The images of a fluorescent dual-contrast agent are then reconstructed into a 3D volume using a tomographic algorithm. A separate 532-nm low-energy pulsed laser excitation is used for skin topography and imaging of superficial vasculature. All three imaging channels can be combined to produce spatially accurate in vivo volumes showing an animal’s skin, deep anatomical structures, and distribution of photosensitive molecular contrast agents. PAFT’s photoacoustic sensitivity was assessed using contrast agents in a phantom study. We demonstrate biomedical imaging application of PAFT’s combined imaging modalities by observing biodistribution of a dual-contrast agent injected intravenously to in vivo preclinical murine models.
PhotoSound Technologies specializes in the development of electronics solutions for massive parallel data acquisition applicable to the fields of photoacoustics (PA), X-ray acoustics, including 3D dosimetry, and ultrasound. PhotoSound’s Legion ADC256 R1.1, released in 2018, is a 256-channel 12-bit ADC with a sampling rate of 40 MHz. The ADC256’s average data bandwidth is limited by its USB3 PC interface, which has a data rate up to 3 Gbps per board. Multiple ADC256 boards can operate fully in parallel. On software level configurations, multiple ADC256 boards are represented as a single ADC board with increased number of channels. The incoming ultrasound (US) upgrades and modifications of ADC256 will enable combination and alternation of US and PA modes using the same probe. PhotoSound MoleculUS is a medical-grade Telemed US system combined with a PA-optimized ADC. MoleculUS utilizes clinical US probes to produce US images which can be interleaved with PA imaging by enabling optical fiber illumination. The other ADC256 modification, advanced PAUS oriented for research, will have PCIe PC interface for raw PA and US data and arbitrary software control over beamformer profiles, limited by high-voltage power only. The data in ultrasound and photoacoustics modes is user accessible in raw format and can be delivered to CUDA GPU using MATLAB parallel computing (CUDA) toolbox or other tools. Multiple PAUS boards can work in parallel in both PA and US modes.
KEYWORDS: Skin, Luminescence, Photoacoustic spectroscopy, Tissues, 3D image processing, Animal model studies, Preclinical imaging, Spatial resolution, In vivo imaging, Acquisition tracking and pointing
We report on the development of a preclinical 3D imaging platform integrating photoacoustic tomography and fluorescence (PAFT). The proposed multimodal imaging concept addresses known deficiencies in sensitivity, anatomical registration, and spatial resolution of the individual imaging modalities. Multi-view photoacoustic and optical projections of the studied animal are utilized to reconstruct large (27 cm3) volumes showing vascular network and blood-rich tissues, as well as regions with induced optical/fluorescence contrast with 3D resolution exceeding 150 μm. An additional 532-nm low-energy pulsed laser excitation is implemented as a separate imaging channel for registration over skin topography and superficial vasculature. PAFT technology enables functional and molecular volumetric imaging using wide range of fluorescent and luminescent biomarkers, nanoparticles, and other photosensitive constructs mapped with high fidelity over robust anatomical structures of the studied animal model. We demonstrated the PAFT performance using phantoms and by in vivo imaging of preclinical murine models.
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