Review of in vivo optical molecular imaging and sensing from x-ray excitation

High-Spatial-Resolution Benchtop X-ray Fluorescence Imaging through Bragg-Diffraction-Based Focusing with Bent Mosaic Graphite Crystals: A Simulation Study

X-ray fluorescence imaging (XFI) can localize diagnostic or theranostic entities utilizing nanoparticle (NP)-based probes at high resolution in vivo, in vitro, and ex vivo. However, small-animal benchtop XFI systems demonstrating high spatial resolution (variable from sub-millimeter to millimeter range) in vivo are still limited to lighter elements (i.e., atomic number Z≤45). This study investigates the feasibility of focusing hard X-rays from solid-target tubes using ellipsoidal lens systems composed of mosaic graphite crystals with the aim of enabling high-resolution in vivo XFI applications with mid-Z (42≤Z≤64) elements. Monte Carlo simulations are performed to characterize the proposed focusing-optics concept and provide quantitative predictions of the XFI sensitivity, in silico tumor-bearing mice models loaded with palladium (Pd) and barium (Ba) NPs. Based on simulation results, the minimum detectable total mass of PdNPs per scan position is expected to be on the order of a few hundred nanograms under in vivo conform conditions. PdNP masses as low as 150 ng to 50 ng could be detectable with a resolution of 600 μm when imaging abdominal tumor lesions across a range of low-dose (0.8 μGy) to high-dose (8 μGy) exposure scenarios. The proposed focusing-optics concept presents a potential step toward realizing XFI with conventional X-ray tubes for high-resolution applications involving interesting NP formulations.

Radiation-induced acoustic signal denoising using a supervised deep learning framework for imaging and therapy monitoring

Radiation-induced acoustic (RA) imaging is a promising technique for visualizing the invisible radiation energy deposition in tissues, enabling new imaging modalities and real-time therapy monitoring. However, RA imaging signal often suffers from poor signal-to-noise ratios (SNRs), thus requiring measuring hundreds or even thousands of frames for averaging to achieve satisfactory quality. This repetitive measurement increases ionizing radiation dose and degrades the temporal resolution of RA imaging, limiting its clinical utility. In this study, we developed a general deep inception convolutional neural network (GDI-CNN) to denoise RA signals to substantially reduce the number of frames needed for averaging. The network employs convolutions with multiple dilations in each inception block, allowing it to encode and decode signal features with varying temporal characteristics. This design generalizes GDI-CNN to denoise acoustic signals resulting from different radiation sources. The performance of the proposed method was evaluated using experimental data of x-ray-induced acoustic, protoacoustic, and electroacoustic signals both qualitatively and quantitatively. Results demonstrated the effectiveness of GDI-CNN: it achieved x-ray-induced acoustic image quality comparable to 750-frame-averaged results using only 10-frame-averaged measurements, reducing the imaging dose of x-ray-acoustic computed tomography (XACT) by 98.7%; it realized proton range accuracy parallel to 1500-frame-averaged results using only 20-frame-averaged measurements, improving the range verification frequency in proton therapy from 0.5 to 37.5 Hz; it reached electroacoustic image quality comparable to 750-frame-averaged results using only a single frame signal, increasing the electric field monitoring frequency from 1 fps to 1k fps. Compared to lowpass filter-based denoising, the proposed method demonstrated considerably lower mean-squared-errors, higher peak-SNR, and higher structural similarities with respect to the corresponding high-frame-averaged measurements. The proposed deep learning-based denoising framework is a generalized method for few-frame-averaged acoustic signal denoising, which significantly improves the RA imaging's clinical utilities for low-dose imaging and real-time therapy monitoring.

X-ray Activated Nanoplatforms for Deep Tissue Photodynamic Therapy

Photodynamic therapy (PDT), the use of light to excite photosensitive molecules whose electronic relaxation drives the production of highly cytotoxic reactive oxygen species (ROS), has proven an effective means of oncotherapy. However, its application has been severely constrained to superficial tissues and those readily accessed either endoscopically or laparoscopically, due to the intrinsic scattering and absorption of photons by intervening tissues. Recent advances in the design of nanoparticle-based X-ray scintillators and photosensitizers have enabled hybridization of these moieties into single nanocomposite particles. These nanoplatforms, when irradiated with diagnostic doses and energies of X-rays, produce large quantities of ROS and permit, for the first time, non-invasive deep tissue PDT of tumors with few of the therapeutic limitations or side effects of conventional PDT. In this review we examine the underlying principles and evolution of PDT: from its initial and still dominant use of light-activated, small molecule photosensitizers that passively accumulate in tumors, to its latest development of X-ray-activated, scintillator-photosensitizer hybrid nanoplatforms that actively target cancer biomarkers. Challenges and potential remedies for the clinical translation of these hybrid nanoplatforms and X-ray PDT are also presented.

Prodrug Nanosensitizer Overcomes the Radiation Resistance of Hypoxic Tumor

Clinical radiation therapy (RT) is often hindered by the low radiation energy absorption coefficient and the hypoxic features of tumor tissues. Among the tremendous efforts devoted to overcoming the barriers to efficient RT, the application of hypoxic radiosensitizers and cell-cycle-specific chemotherapeutics has shown great potential. However, their effectiveness is often compromised by their limited bioavailability, especially in the hypoxic region, which plays a major role in radioresistance. Herein, to simultaneously improve the delivery efficacy of both hypoxic radiosensitizer and cell-cycle-specific drug, a gambogic acid (GA) metronidazole (MN) prodrug (GM) was designed and synthesized based on GA, a naturally occurring chemotherapeutic and multiple pathway inhibitor, and MN, a typical hypoxic radiosensitizer. In combination with MN-containing block copolymers, the prodrug nanosensitizer (NS) of GM was obtained. Owing to the bioreduction of MN, the as-designed prodrug could be efficiently delivered to hypoxic cells and act on mitochondria to cause the accumulation of reactive oxygen species. The strong G₂/M phase arrest caused by the prodrug NS could further sensitize treated cells to external radiation under hypoxic conditions by increasing DNA damage and delaying DNA repair. After coadministration of the NS with a well-established tissue-penetrating peptide, efficient tumor accumulation, deep tumor penetration, and highly potent chemoradiotherapy could be achieved.

Advances and opportunities in nanoimaging agents for the diagnosis of inflammatory lung diseases

The development of rapid, noninvasive diagnostics to detect lung diseases is a great need after the COVID-2019 outbreak. The nanotechnology-based approach has improved imaging and facilitates the early diagnosis of inflammatory lung diseases. The multifunctional properties of nanoprobes enable better spatial-temporal resolution and a high signal-to-noise ratio in imaging. Targeted nanoimaging agents have been used to bind specific tissues in inflammatory lungs for early-stage diagnosis. However, nanobased imaging approaches for inflammatory lung diseases are still in their infancy. This review provides a solution-focused approach to exploring medical imaging technologies and nanoprobes for the detection of inflammatory lung diseases. Prospects for the development of contrast agents for lung disease detection are also discussed.

64Cu-labeling of small extracellular vesicle surfaces via a cross-bridged macrocyclic chelator for pharmacokinetic study by positron emission tomography imaging

We developed a method of labeling the surfaces of small extracellular vesicles (sEVs) with ⁶⁴Cu using a cross-bridged, macrocyclic chelator (CB-TE1A1P) and applied to pharmacokinetics study with positron emission tomography (PET). After incubation in 20% plasma for 10 min, approximately a half of the ⁶⁴Cu was desorbed from ⁶⁴Cu-labeled sEVs purified by phosphate-buffered saline wash, suggesting partly weak interaction without coordinating to CB-TE1A1P. After subsequent purification with albumin, ⁶⁴Cu desorption was greatly reduced, resulting in a radiochemical stability of 95.7%. Notably, labeling did not alter the physicochemical and biological properties of sEVs. After intravenous injection, ⁶⁴Cu-labeled sEVs rapidly disappeared from the systemic blood circulation and accumulated mainly in the liver and spleen of macrophage-competent mice. In macrophage-depleted mice, ⁶⁴Cu-labeled sEVs remained in the blood circulation for a longer period and gradually accumulated in the liver and spleen, suggesting mechanisms of hepatic and splenic accumulation other than macrophage-dependent phagocytosis. The comparison of tissue uptake clearance between macrophage-competent and macrophage-depleted mice suggests that macrophages contributed to 67% and 76% of sEV uptake in the liver and spleen, respectively. The application of this method in pharmacokinetics PET studies can be useful in preclinical and clinical research and the development of sEV treatment modalities.

Cherenkov Luminescence in Tumor Diagnosis and Treatment: A Review

Malignant tumors rank as a leading cause of death worldwide. Accurate diagnosis and advanced treatment options are crucial to win battle against tumors. In recent years, Cherenkov luminescence (CL) has shown its technical advantages and clinical transformation potential in many important fields, particularly in tumor diagnosis and treatment, such as tumor detection in vivo, surgical navigation, radiotherapy, photodynamic therapy, and the evaluation of therapeutic effect. In this review, we summarize the advances in CL for tumor diagnosis and treatment. We first describe the physical principles of CL and discuss the imaging techniques used in tumor diagnosis, including CL imaging, CL endoscope, and CL tomography. Then we present a broad overview of the current status of surgical resection, radiotherapy, photodynamic therapy, and tumor microenvironment monitoring using CL. Finally, we shed light on the challenges and possible solutions for tumor diagnosis and therapy using CL.

Contrast agents for x-ray luminescence computed tomography

Imaging probes are an important consideration for any type of contrast agent-based imaging method. X-ray luminescence imaging (XLI) and x-ray luminescence computed tomography (XLCT) are both contrast agent-based imaging methods that employ x-ray excitable scintillating imaging probes that emit light to be measured for optical imaging. In this work, we compared the performance of several select imaging probes, both commercial and self-synthesized, for application in XLI/XLCT imaging. Commercially available cadmium telluride quantum dots (CdTe QDs) and europium-doped gadolinium oxysulfide (GOS:Eu) microphosphor as well as synthesized NaGdF4 nanophosphors doped with either europium or terbium were compared through their x-ray luminescence emission spectra, luminescence intensity, and also by performing XLCT scans using phantoms embedded with each of the imaging probes. Each imaging probe displayed a unique emission spectrum that was ideal for deep-tissue optical imaging. In terms of luminescence intensity, due to the large particle size, GOS:Eu had the brightest emission, followed by NaGdF4:Tb, NaGdF4:Eu, and finally the CdTe QDs. Lastly, XLCT scans showed that each imaging probe could be reconstructed with good shape and location accuracy.