Mapping physiological and pathological functions of cortical vasculature through aggregation-induced emission nanoprobes assisted quantitative, in vivo NIR-II imaging

Aggregation-induced emission luminescence for angiography and atherosclerotic diagnosis

Optical imaging technology has become increasingly recognized for its utility in diagnosing atherosclerosis thanks to advantages such as high spatial resolution, rapid data acquisition, lack of radiation exposure, cost-effectiveness, minimal invasiveness, and limited side effects. However, traditional luminogens employed in optical diagnostics are often troubled by aggregation-caused quenching (ACQ) effect, causing diagnostic errors in vivo. Since Professor Tang discovered the aggregation-induced emission (AIE) phenomenon, AIE luminogens (AIEgens) have been rapidly developing and are considered as the next-generation fluorescent contrast agents for angiography and atherosclerotic diagnosis. This mini review will outline the use of AIEgens in angiography and the diagnosis of atherosclerosis, exploring different imaging models, including second near-infrared, two/multi-photon, and photoacoustic imaging, and will provide a forward-looking perspective on their potential in atherosclerotic diagnosis.

Nanocrystals for Deep-Tissue In Vivo Luminescence Imaging in the Near-Infrared Region

In vivo imaging technologies have emerged as a powerful tool for both fundamental research and clinical practice. In particular, luminescence imaging in the tissue-transparent near-infrared (NIR, 700-1700 nm) region offers tremendous potential for visualizing biological architectures and pathophysiological events in living subjects with deep tissue penetration and high imaging contrast owing to the reduced light-tissue interactions of absorption, scattering, and autofluorescence. The distinctive quantum effects of nanocrystals have been harnessed to achieve exceptional photophysical properties, establishing them as a promising category of luminescent probes. In this comprehensive review, the interactions between light and biological tissues, as well as the advantages of NIR light for in vivo luminescence imaging, are initially elaborated. Subsequently, we focus on achieving deep tissue penetration and improved imaging contrast by optimizing the performance of nanocrystal fluorophores. The ingenious design strategies of NIR nanocrystal probes are discussed, along with their respective biomedical applications in versatile in vivo luminescence imaging modalities. Finally, thought-provoking reflections on the challenges and prospects for future clinical translation of nanocrystal-based in vivo luminescence imaging in the NIR region are wisely provided.

Precise ligand engineering of Ir(III)-based photosensitizer with aggregation-induced emission for image-guided photodynamic therapy

Photodynamic therapy (PDT), which relies on the production of reactive oxygen species (ROS) induced by a photosensitizer to kill cancer cells, has become a non-invasive approach to combat cancer. However, the conventional aggregation-caused quenching effect, as well as the low ROS generation ability of photosensitizers, restrict their biological applications. In this work, a new Ir(III) complex with a dendritic ligand has been strategically designed and synthesized by ingenious modification of the ancillary ligand of a reported Ir(III) complex (Ir-1). The extended π-conjugation and multiple aromatic donor moieties endow the resulting complex Ir-2 with obvious aggregation-induced emission (AIE) activity and bathochromic emission. In in vitro experiments, importantly, Ir-2 nanoparticles exhibit the excellent photoinduced ROS generation capabilities of O2 •- and 1 O2 , as well as excellent biocompatibility and the lipid droplets (LDs) targeting feature. This study would provide useful guidance to design efficient Ir(III)-based photosensitizers used in biological applications in the future.

Enhancing Total Optical Throughput of Microscopy with Deep Learning for Intravital Observation

The significance of performing large-depth dynamic microscopic imaging in vivo for life science research cannot be overstated. However, the optical throughput of the microscope limits the available information per unit of time, i.e., it is difficult to obtain both high spatial and temporal resolution at once. Here, a method is proposed to construct a kind of intravital microscopy with high optical throughput, by making near-infrared-II (NIR-II, 900-1880 nm) wide-field fluorescence microscopy learn from two-photon fluorescence microscopy based on a scale-recurrent network. Using this upgraded NIR-II fluorescence microscope, vessels in the opaque brain of a rodent are reconstructed three-dimensionally. Five-fold axial and thirteen-fold lateral resolution improvements are achieved without sacrificing temporal resolution and light utilization. Also, tiny cerebral vessel dilatations in early acute respiratory failure mice are observed, with this high optical throughput NIR-II microscope at an imaging speed of 30 fps.

Aggregation-Induced Emission (AIE), Life and Health

Light has profoundly impacted modern medicine and healthcare, with numerous luminescent agents and imaging techniques currently being used to assess health and treat diseases. As an emerging concept in luminescence, aggregation-induced emission (AIE) has shown great potential in biological applications due to its advantages in terms of brightness, biocompatibility, photostability, and positive correlation with concentration. This review provides a comprehensive summary of AIE luminogens applied in imaging of biological structure and dynamic physiological processes, disease diagnosis and treatment, and detection and monitoring of specific analytes, followed by representative works. Discussions on critical issues and perspectives on future directions are also included. This review aims to stimulate the interest of researchers from different fields, including chemistry, biology, materials science, medicine, etc., thus promoting the development of AIE in the fields of life and health.

Mapping port wine stain in vivo by optical coherence tomography angiography and multi-metric characterization

Port wine stain (PWS) is a congenital cutaneous capillary malformation composed of ecstatic vessels, while the microstructure of these vessels remains largely unknown. Optical coherence tomography angiography (OCTA) serves as a non-invasive, label-free and high-resolution tool to visualize the 3D tissue microvasculature. However, even as the 3D vessel images of PWS become readily accessible, quantitative analysis algorithms for their organization have mainly remained limited to analysis of 2D images. Especially, 3D orientations of vasculature in PWS have not yet been resolved at a voxel-wise basis. In this study, we employed the inverse signal-to-noise ratio (iSNR)-decorrelation (D) OCTA (ID-OCTA) to acquire 3D blood vessel images in vivo from PWS patients, and used the mean-subtraction method for de-shadowing to correct the tail artifacts. We developed algorithms which mapped blood vessels in spatial-angular hyperspace in a 3D context, and obtained orientation-derived metrics including directional variance and waviness for the characterization of vessel alignment and crimping level, respectively. Combining with thickness and local density measures, our method served as a multi-parametric analysis platform which covered a variety of morphological and organizational characteristics at a voxel-wise basis. We found that blood vessels were thicker, denser and less aligned in lesion skin in contrast to normal skin (symmetrical parts of skin lesions on the cheek), and complementary insights from these metrics led to a classification accuracy of ∼90% in identifying PWS. An improvement in sensitivity of 3D analysis was validated over 2D analysis. Our imaging and analysis system provides a clear picture of the microstructure of blood vessels within PWS tissues, which leads to a better understanding of this capillary malformation disease and facilitates improvements in diagnosis and treatment of PWS.

Highly accurate, automated quantification of 2D/3D orientation for cerebrovasculature using window optimizing method

SIGNIFICANCE

Deep-imaging of cerebral vessels and accurate organizational characterization are vital to understanding the relationship between tissue structure and function.

AIM

We aim at large-depth imaging of the mouse brain vessels based on aggregation-induced emission luminogens (AIEgens), and we create a new algorithm to characterize the spatial orientation adaptively with superior accuracy.

APPROACH

Assisted by AIEgens with near-infrared-II excitation, three-photon fluorescence (3PF) images of large-depth cerebral blood vessels are captured. A window optimizing (WO) method is developed for highly accurate, automated 2D/3D orientation determination. The application of this system is demonstrated by establishing the orientational architecture of mouse cerebrovasculature down to the millimeter-level depth.

RESULTS

The WO method is proved to have significantly higher accuracy in both 2D and 3D cases than the method with a fixed window size. Depth- and diameter-dependent orientation information is acquired based on in vivo 3PF imaging and the WO analysis of cerebral vessel images with a penetration depth of 800 μm in mice.

CONCLUSIONS

We built an imaging and analysis system for cerebrovasculature that is conducive to applications in neuroscience and clinical fields.

Identification of human ovarian cancer relying on collagen fiber coverage features by quantitative second harmonic generation imaging

Ovarian cancer has the highest mortality rate among all gynecological cancers, containing complicated heterogeneous histotypes, each with different treatment plans and prognoses. The lack of screening test makes new perspectives for the biomarker of ovarian cancer of great significance. As the main component of extracellular matrix, collagen fibers undergo dynamic remodeling caused by neoplastic activity. Second harmonic generation (SHG) enables label-free, non-destructive imaging of collagen fibers with submicron resolution and deep sectioning. In this study, we developed a new metric named local coverage to quantify morphologically localized distribution of collagen fibers and combined it with overall density to characterize 3D SHG images of collagen fibers from normal, benign and malignant human ovarian biopsies. An overall diagnosis accuracy of 96.3% in distinguishing these tissue types made local and overall density signatures a sensitive biomarker of tumor progression. Quantitative, multi-parametric SHG imaging might serve as a potential screening test tool for ovarian cancer.