High-performance imaging is essential for widespread applications of photoacoustic tomography (PAT) in biomedicine. So far, no comprehensive studies are reported on the impact of system factors on imaging performance, in spite of their importance. Based on a prototype PAT scanner, we study eight factors associated with the acoustic reception process in PAT, namely, detector view angle, element number, center frequency, bandwidth, aperture size, focusing, orientation error, and scan step angle error, and investigated how they impact on the image quality. Simulations and experiments are both presented to support the findings in this study. This work is expected to provide a practical guide for advanced PAT scanner design with enhanced imaging performance.

Electronic digital convolutions could extract key features of objects for data processing and information identification in artificial intelligence, but they are time-cost and energy consumption due to the low response of electrons. Although massless photons enable high-speed and low-loss analog convolutions, two existing all-optical approaches including Fourier filtering and Green’s function have either limited functionality or bulky volume, thus restricting their applications in smart systems. Here, we report all-optical convolutional computing with a metasurface-singlet or -doublet imager, considered as the third approach, where its point spread function is modified arbitrarily via a complex-amplitude meta-modulator that enables functionality-unlimited kernels. Beyond one- and two-dimensional spatial differentiation, we demonstrate real-time, parallel, and analog convolutional processing of optical and biological specimens with challenging pepper-salt denoising and edge enhancement, which significantly enrich the toolkit of all-optical computing. Such meta-imager approach bridges multi-functionality and high-integration in all-optical convolutions, meanwhile possessing good architecture compatibility with digital convolutional neural networks.

Photoacoustic tomography (PAT) has become a fast-evolving biomedical imaging modality in recent years. In PAT, image reconstruction is a critical step to produce high-quality photoacoustic images from raw photoacoustic signals. To date, algorithms based on back projection are the most widely used image reconstruction techniques due to their simplicity and computational efficiency. However, images reconstructed by back projection contain negative values, especially at the edge of photoacoustic sources, which have no physical meaning and are essentially undesired artifacts. In this work, we study the formation mechanism, fundamental causes and removal strategies of the negativity artifacts in back-projection-based PAT. Our results show that limited detector bandwidth and limited view angle are two fundamental causes of negativity artifacts. When the bandwidth of a detector is limited, back-projection signals will be distorted as a result of the loss of frequency contents and negativity artifacts thus appear. When the view angle of the detector is limited, photoacoustic signals propagating in three-dimensional space will be partially lost, resulting in negativity artifacts. Post-processing strategies, such as envelope detection and forced zeroing can be used to remove the negativity artifacts but may cause problems. Since negativity artifacts are a common image quality degradation factor in PAT, understanding their characteristics may expedite the development of novel artifact-removal techniques and artifact-free image reconstruction algorithms, which are of importance to correct image interpretation and quantitative imaging.

Vast research has been carried out to fabricate tissue-mimicking phantoms, due to their convenient use and ease of storage, to assess and validate the performance of optical imaging devices. However, to the best of our knowledge, there has been little research on the use of multilayer tissue phantoms for optical imaging technology, although their structure is closer to that of real skin tissue. In this work, we design, fabricate, and characterize multilayer tissue-mimicking phantoms, with a morphological mouse ear blood vessel, that contain an epidermis, a dermis, and a hypodermis. Each tissue-mimicking phantom layer is characterized individually to match specific skin tissue layer characteristics. The thickness, optical properties (absorption coefficient and reduced scattering coefficient), oxygenation, and perfusion of skin are the most critical parameters for disease diagnosis and for some medical equipment. These phantoms can be used as calibration artifacts and help to evaluate optical imaging technologies.

Developing photothermal agents (PTAs) for tumor therapy has three prerequisites: selectively targeting tumors, efficiently converting near-infrared (NIR) photoenergy to heat, and degrading after the cure. These make up a combination rarely found in one material. Here a metal-acid treatment is reported to hydrogenate metal oxide, bestowing the produced H x MoO 3 with metal-like electronic structure which enables harvesting NIR-II light (1000−1350 nm wavelength). Importantly, created by putting acid protons into oxide, the H x MoO 3 nanomaterial can resist attacking from protons in acids but is vulnerable to hydroxyl ions in alkaline. After entering biological organism, H x MoO 3 PTAs persist long in acidic tumor microenvironment (TME, extracellular pH 6.5-6.9) while degrade quickly under the normal physiological environment (pH 7.2−7.4), naturally causing tumor-selective accumulation. Under 1064 nm NIR-II illumination, the H x MoO 3 achieves a high photothermal conversion efficiency of 60.9%, leading to a high tumor inhibition rate of ≈97.25%. Such a novel PTAs integrates merits of metal and oxide, opening a door of smart photothermal therapy with self-adaptive tumor-accumulation and automatic degradation after tumor hyperthermia.