Monte Carlo-Based Optical Simulation of Optical Distribution in Deep Brain Tissues Using Sixteen Optical Sources.

Optical-based imaging has improved from early single-location research to further sophisticated imaging in 2D topography and 3D tomography. These techniques have the benefit of high specificity and non-radiative safety for brain detection and therapy. However, their performance is limited by complex tissue structures. To overcome the difficulty in successful brain imaging applications, we conducted a simulation using 16 optical source types within a brain model that is based on the Monte Carlo method. In addition, we propose an evaluation method of the optical propagating depth and resolution, specifically one based on the optical distribution for brain applications. Based on the results, the best optical source types were determined in each layer. The maximum propagating depth and corresponding source were extracted. The optical source propagating field width was acquired in different depths. The maximum and minimum widths, as well as the corresponding source, were determined. This paper provides a reference for evaluating the optical propagating depth and resolution from an optical simulation aspect, and it has the potential to optimize the performance of optical-based techniques.

An NIR fluorescent/photoacoustic dual-mode probe of NADPH for tumor imaging.

A novel probe was synthesized with a turn-on NIR fluorescent (NIRF)/photoacoustic (PA) response to NADPH, which was successfully applied in both monitoring intracellular NADPH and dual-modal imaging of tumor-bearing mice. It exhibits good potential in studying and understanding the tumor energy metabolism and treatment process related to NADPH.

Multi-segmented feature coupling for jointly reconstructing initial pressure and speed of sound in photoacoustic computed tomography.

SIGNIFICANCE: Photoacoustic computed tomography (PACT) is a fast-growing imaging modality. In PACT, the image quality is degraded due to the unknown distribution of the speed of sound (SoS). Emerging initial pressure (IP) and SoS joint-reconstruction methods promise reduced artifacts in PACT. However, previous joint-reconstruction methods have some deficiencies. A more effective method has promising prospects in preclinical applications. AIM: We propose a multi-segmented feature coupling (MSFC) method for SoS-IP joint reconstruction in PACT. APPROACH: In the proposed method, the ultrasound detectors were divided into multiple sub-arrays with each sub-array and its opposite counterpart considered to be a pair. The delay and sum algorithm was then used to reconstruct two images based on a subarray pair and estimated a direction-specific SoS, based on image correlation and the orientation of the subarrays. Once the data generated by all pairs of subarrays were processed, an image that was optimized in terms of minimal feature splitting in all directions was generated. Further, based on the direction-specific SoS, a model-based method was used to directly reconstruct the SoS distribution. RESULTS: Both phantom and animal experiments demonstrated feasibility and showed promising results compared with conventional methods, with less splitting and blurring and fewer distortions. CONCLUSIONS: The developed MSFC method shows promising results for both IP and SoS reconstruction. The MSFC method will help to optimize the image quality of PACT in clinical applications.

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.

Development of a digital breast phantom for photoacoustic computed tomography.

Photoacoustic (PA) imaging provides morphological and functional information about angiogenesis and thus is potentially suitable for breast cancer diagnosis. However, the development of PA breast imaging has been hindered by inadequate patients and a lack of ground truth images. Here, we report a digital breast phantom with realistic acoustic and optical properties, with which a digital PA-ultrasound imaging pipeline is developed to create a diverse pool of virtual patients with three types of masses: ductal carcinoma in situ, invasive breast cancer, and fibroadenoma. The experimental results demonstrate that our model is realistic, flexible, and can be potentially useful for accelerating the development of PA breast imaging technology.

Adaptive photoacoustic computed tomography.

For many optical imaging modalities, image qualities are inevitably degraded by wavefront distortions caused by varying light speed. In optical microscopy and astronomy, adaptive optics (AO) has long been applied to compensate for such unwanted aberrations. Photoacoustic computed tomography (PACT), despite relying on the ultrasonic wave for image formation, suffers from the acoustic version of the same problem. However, this problem has traditionally been regarded as an inverse problem of jointly reconstructing both the initial pressure and the sound speed distributions. In this work, we proposed a method similar to indirect wavefront sensing in AO. We argued that wavefront distortions can be extracted and corrected by a frequency domain analysis of local images. In addition to an adaptively reconstructed aberration-free image, the speed of sound map can be subsequently estimated. We demonstrated the method by in silico, phantom, and in vivo experiments.