Molecular Contrast Research Articles

Engineering Protein-Nanoparticle Hybrids as Targeted Contrast Agents.

Iron oxide nanoparticles (IONPs) have shown great promise in biomedical applications, particularly as MRI contrast agents due to their magnetic properties and biocompatibility. Although several IONPs have been approved by regulatory agencies as MRI contrast agents, their primary application as negative contrast agents limits their usage. Additionally, there is an emerging need for the development of molecular contrast agents that can specifically target biomarkers, enabling more accurate and sensitive diagnostics. To address these challenges, we exploited the engineerability of proteins to stabilize IONPs with tailored magnetic properties, creating protein-stabilized iron oxide nanoparticles (Prot-IONPs) and leveraged the chemical diversity of proteins to functionalize Prot-IONPs with targeting moieties. As a proof-of-concept, we used alendronate (Ald) to target atherosclerotic plaques in the aorta. Simple protein functionalization allowed targeting while maintaining the stability and relaxation properties of the Prot-IONPs. Prot-IONPs-Ald successfully enabled positive contrast imaging of atherosclerotic plaques in vivo in an atherosclerotic mouse model (ApoE-/- mice on a high-fat diet). This study demonstrates the potential of engineering protein-nanoparticle hybrids as versatile platforms for developing targeted in vivo MRI contrast agents.

Multimodal photoacoustic microscopy and optical coherence tomography ocular biomarker imaging in Alzheimer's disease in mice

Alzheimer's disease (AD) is a neurodegenerative disease characterized by amyloid beta (Aβ)-containing extracellular plaques and tau-containing intracellular neurofibrillary tangles. Reliable and more accessible biomarkers along with associated imaging methods are essential for early diagnosis and to develop effective therapeutic interventions. Described here is an integrated photoacoustic microscopy (PAM) and optical coherence tomography (OCT) dual-modality imaging system for multiple ocular biomarker imaging in an AD mouse model. Anti-Aβ-conjugated Au nanochains (AuNCs) were engineered and administered to the mice to provide molecular contrast of Aβ. The retinal vasculature structure and Aβ deposition in AD mice and wild-type (WT) mice were imaged simultaneously by dual-wavelength PAM. OCT distinguished significant differences in retinal layer thickness between AD and WT animals. With the unique ability of imaging the multiple ocular biomarkers via a coaxial multimodality imaging system, the proposed system provides a new tool for investigating the progression of AD in animal models, which could contribute to preclinical studies of AD.

SKYQUANT 3D: Quantifying Vascular Anatomy With an Open-Source Workflow for Comprehensive Analysis of Volumetric Optoacoustic Angiography Data.

Efficient visualization of the vascular system is of key importance in biomedical research into tumor angiogenesis, cerebrovascular alterations, and other angiopathies. Optoacoustic (OA) angiography offers a promising solution combining molecular optical contrast with high resolution and deep penetration of ultrasound. However, its hybrid nature implies complex data collection and processing workflows, with significant variability in methodologies across developers and users. To streamline interoperability, we introduce SKYQUANT 3D, a Python-based set of instructions for the Thermo Fisher Scientific Amira/Avizo 3D Visualization & Analysis Software. Our workflow simplifies the batch processing of volumetric optoacoustic angiography images, extracting meaningful quantitative information while also providing statistical analysis and graphical representation of the results. Quantification performance of SKYQUANT 3D is demonstrated using functional preclinical and clinical in vivo 3D OA angiographic tests involving ambient temperature variations and repositioning of the imaged limb.

Label-free 3D molecular imaging of living tissues using Raman spectral projection tomography

The ability to image tissues in three dimensions (3D) with label-free molecular contrast at the mesoscale would be a valuable capability in biology and biomedicine. Here, we introduce Raman spectral projection tomography (RSPT) for volumetric molecular imaging with optical sub-millimeter spatial resolution. We have developed a RSPT imaging instrument capable of providing 3D molecular contrast in transparent and semi-transparent samples. We also created a computational pipeline for multivariate reconstruction to extract label-free spatial molecular information from Raman projection data. Using these tools, we demonstrate imaging and visualization of phantoms of various complex shapes with label-free molecular contrast. Finally, we apply RSPT as a tool for imaging of molecular gradients and extracellular matrix heterogeneities in fixed and living tissue-engineered constructs and explanted native cartilage tissues. We show that there exists a favorable balance wherein employing Raman spectroscopy, with its advantages in live cell imaging and label-free molecular contrast, outweighs the reduction in imaging resolution and blurring caused by diffuse photon propagation. Thus, RSPT imaging opens new possibilities for label-free molecular monitoring of tissues.

Solvent Effects in Hyperpolarization of 15N Nuclei in [15N3]Metronidazole and [15N3]Nimorazole Antibiotics via SABRE‐SHEATH**

AbstractMetronidazole and nimorazole are antibiotics of a nitroimidazole group which also may be potentially utilized as hypoxia radiosensitizers for the treatment of cancerous tumors. Hyperpolarization of 15N nuclei in these compounds using SABRE‐SHEATH (Signal Amplification By Reversible Exchange in SHield Enables Alignment Transfer to Heteronuclei) approach provides dramatic enhancement of detection sensitivity of these analytes using magnetic resonance spectroscopy and imaging. Methanol‐d4 is conventionally employed as a solvent in SABRE hyperpolarization process. Herein, we investigate SABRE‐SHEATH hyperpolarization of isotopically labeled [15N3]metronidazole and [15N3]nimorazole in nondeuterated methanol and ethanol solvents. Optimization of such hyperpolarization parameters as polarization transfer magnetic field, temperature, parahydrogen flow rate and pressure allowed us to obtain an average 15N polarization of up to 7.2–7.4 % for both substrates. The highest 15N polarizations were observed in methanol‐d4 for [15N3]metronidazole and in ethanol for [15N3]nimorazole. At a clinically relevant magnetic field of 1.4 T the 15N nuclei of these substrates possess long characteristic hyperpolarization lifetimes (T1) of ca. 1 to ca. 7 min. This study represents a major step toward SABRE in more biocompatible solvents, such as ethanol, and also paves the way for future utilization of these hyperpolarized nitroimidazoles as molecular contrast agents for MRI visualization of tumors.

Nanoscale volumetric fluorescence imaging via photochemical sectioning.

Optical nanoscopy of intact biological specimens has been transformed by recent advancements in hydrogel-based tissue clearing and expansion, enabling the imaging of cellular and subcellular structures with molecular contrast. However, existing high-resolution fluorescence microscopes have limited imaging depth, which prevents the study of whole-mount specimens without physical sectioning. To address this challenge, we developed "photochemical sectioning," a spatially precise, light-based sample sectioning process. By combining photochemical sectioning with volumetric lattice light-sheet imaging and petabyte-scale computation, we imaged and reconstructed axons and myelination sheaths across entire mouse olfactory bulbs at nanoscale resolution. An olfactory-bulb-wide analysis of myelinated and unmyelinated axons revealed distinctive patterns of axon degeneration and de-/dysmyelination in the neurodegenerative mouse, highlighting the potential for peta- to exabyte-scale super-resolution studies using this approach.

Ex vivo optical coherence tomography combined with near infrared targeted fluorescence: towards in-vivo esophageal cancer detection.

Early detection of (pre)malignant esophageal lesions is critical to improve esophageal cancer morbidity and mortality rates. In patients with advanced esophageal adenocarcinoma (EAC) who undergo neoadjuvant chemoradiation therapy, the efficacy of therapy could be optimized and unnecessary surgery prevented by the reliable assessment of residual tumors after therapy. Optical coherence tomography (OCT) provides structural images at a (sub)-cellular level and has the potential to visualize morphological changes in tissue. However, OCT lacks molecular imaging contrast, a feature that enables the study of biological processes at a cellular level and can enhance esophageal cancer diagnostic accuracy. We combined OCT with near-infrared fluorescence molecular imaging using fluorescently labelled antibodies (immuno-OCT). The main goal of this proof of principle study is to investigate the feasibility of immuno-OCT for esophageal cancer imaging. We aim to assess whether the sensitivity of our immuno-OCT device is sufficient to detect the tracer uptake using an imaging dose (∼100 times smaller than a dose with therapeutic effects) of a targeted fluorescent agent. The feasibility of immuno-OCT was demonstrated ex-vivo on dysplastic lesions resected from Barrett's patients and on esophageal specimens resected from patients with advanced EAC, who were respectively topically and intravenously administrated with the tracer bevacizumab-800CW. The detection sensitivity of our system (0.3 nM) is sufficient to detect increased tracer uptake with micrometer resolution using an imaging dose of labelled antibodies. Moreover, the absence of layered structures that are typical of normal esophageal tissue observed in OCT images of dysplastic/malignant esophageal lesions may further aid their detection. Based on our preliminary results, immuno-OCT could improve the detection of dysplastic esophageal lesions.

DOCK-PET: database of CNS kinetic parameters in the healthy human brain for existing PET tracers.

Information about developed positron emission tomography (PET) tracers and obtained clinical PET images is publicly available in a database. However, findings regarding the kinetic parameters of PET tracers are yet to be summarized. Therefore, in this study, we created an open-access database of central nervous system (CNS) kinetic parameters in the healthy human brain for existing PET tracers (DOCK-PET). Our database includes information on the kinetic parameters and compounds of existing CNS-PET tracers. The kinetic parameter dataset comprises the analysis methods, VT, BPND, K parameters, relevant literature, and study details. The list of PET tracers and kinetic parameter information was compiled through keyword-based searches of PubMed and the Molecular Imaging and Contrast Agent Database (MICAD). The kinetic parameters obtained, including VT, BPND, and K parameters, were reorganized based on the defined brain anatomical regions. All data were rigorously double-checked before being summarized in Microsoft Excel and JavaScript Object Notation (JSON) formats. Of the 247 PET tracers identified through searches using the PubMed and MICAD websites, the kinetic parameters of 120 PET tracers were available. Among the 120 PET tracers, compound structures with chemical and physical properties were obtained from the PubChem website or the ChemDraw software. Furthermore, the affinity information of the 104 PET tracers was gathered from PubChem or extensive literature surveys of the 120 PET tracers. We developed a comprehensive open-access database, DOCK-PET, that includes both kinetic parameters of healthy humans and compound information for existing CNS-PET tracers.

Attention-Based MultiOffset Deep Learning Reconstruction of Chemical Exchange Saturation Transfer (AMO-CEST) MRI.

One challenge of chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is the long scan time due to multiple acquisitions of images at different saturation frequency offsets. k-space under-sampling strategy is commonly used to accelerate MRI acquisition, while this could introduce artifacts and reduce signal-to-noise ratio (SNR). To accelerate CEST-MRI acquisition while maintaining suitable image quality, we proposed an attention-based multioffset deep learning reconstruction network (AMO-CEST) with a multiple radial k-space sampling strategy for CEST-MRI. The AMO-CEST also contains dilated convolution to enlarge the receptive field and data consistency module to preserve the sampled k-space data. We evaluated the proposed method on a mouse brain dataset containing 5760 CEST images acquired at a pre-clinical 3 T MRI scanner. Quantitative results demonstrated that AMO-CEST showed obvious improvement over zero-filling method with a PSNR enhancement of 11 dB, a SSIM enhancement of 0.15, and a NMSE decrease of [Formula: see text] in three acquisition orientations. Compared with other deep learning-based models, AMO-CEST showed visual and quantitative improvements in images from three different orientations. We also extracted molecular contrast maps, including the amide proton transfer (APT) and the relayed nuclear Overhauser enhancement (rNOE). The results demonstrated that the CEST contrast maps derived from the CEST images of AMO-CEST were comparable to those derived from the original high-resolution CEST images. The proposed AMO-CEST can efficiently reconstruct high-quality CEST images from under-sampled k-space data and thus has the potential to accelerate CEST-MRI acquisition.

Fast quantitative MRI: Spiral Acquisition Matching-Based Algorithm (SAMBA) for Robust T1 and T2 Mapping

Conventional diagnostic images from Magnetic Resonance Imaging (MRI) are typically qualitative and require subjective interpretation. Alternatively, quantitative MRI (qMRI) methods have become more prevalent in recent years with multiple clinical and preclinical imaging applications. Quantitative MRI studies on preclinical MRI scanners are being used to objectively assess tissues and pathologies in animal models and to evaluate new molecular MRI contrast agents. Low-field preclinical MRI scanners (≤3.0T) are particularly important in terms of evaluating these new MRI contrast agents at human MRI field strengths. Unfortunately, these low-field preclinical qMRI methods are challenged by long acquisition times, intrinsically low MRI signal levels, and susceptibility to motion artifacts. In this study, we present a new rapid qMRI method for a preclinical 3.0T MRI scanner that combines a Spiral Acquisition with a Matching-Based Algorithm (SAMBA) to rapidly and quantitatively evaluate MRI contrast agents. In this initial development, we compared SAMBA with gold-standard Spin Echo MRI methods using Least Squares Fitting (SELSF) in vitro phantoms and demonstrated shorter scan times without compromising measurement accuracy or repeatability. These initial results will pave the way for future in vivo qMRI studies using state-of-the-art chemical probes.

Merged Molecular Switches Excel as Optoacoustic Dyes: Azobenzene-Cyanines Are Loud and Photostable NIR Imaging Agents.

Optoacoustic (or photoacoustic) imaging promises micron-resolution noninvasive bioimaging with much deeper penetration (>cm) than fluorescence. However, optoacoustic imaging of enzyme activity would require loud, photostable, NIR-absorbing molecular contrast agents, which remain unknown. Most organic molecular contrast agents are repurposed fluorophores, with severe shortcomings of photoinstability or phototoxicity under optoacoustic imaging, as consequences of their slow S1→S0 electronic relaxation. We now report that known fluorophores can be rationally modified to reach ultrafast S1→S0 rates, without much extra molecular complexity, simply by merging them with molecular switches. Here, we merge azobenzene switches with cyanine dyes to give ultrafast relaxation (<10 ps, >100-fold faster). Without even adapting instrument settings, these azohemicyanines display outstanding improvements in signal longevity (>1000-fold increase of photostability) and signal loudness (>3-fold even at time zero). We show why this simple but unexplored design strategy can still offer stronger performance in the future, and can also increase the spatial resolution and the quantitative linearity of photoacoustic response over extended longitudinal imaging. By bringing the world of molecular switches and rotors to bear on problems facing optoacoustic agents, this practical strategy will help to unleash the full potential of optoacoustic imaging in fundamental studies and translational uses.

Merged Molecular Switches Excel as Optoacoustic Dyes: Azobenzene–Cyanines Are Loud and Photostable NIR Imaging Agents

AbstractOptoacoustic (or photoacoustic) imaging promises micron‐resolution noninvasive bioimaging with much deeper penetration (&gt;cm) than fluorescence. However, optoacoustic imaging of enzyme activity would require loud, photostable, NIR‐absorbing molecular contrast agents, which remain unknown. Most organic molecular contrast agents are repurposed fluorophores, with severe shortcomings of photoinstability or phototoxicity under optoacoustic imaging, as consequences of their slow S1→S0 electronic relaxation. We now report that known fluorophores can be rationally modified to reach ultrafast S1→S0 rates, without much extra molecular complexity, simply by merging them with molecular switches. Here, we merge azobenzene switches with cyanine dyes to give ultrafast relaxation (&lt;10 ps, &gt;100‐fold faster). Without even adapting instrument settings, these azohemicyanines display outstanding improvements in signal longevity (&gt;1000‐fold increase of photostability) and signal loudness (&gt;3‐fold even at time zero). We show why this simple but unexplored design strategy can still offer stronger performance in the future, and can also increase the spatial resolution and the quantitative linearity of photoacoustic response over extended longitudinal imaging. By bringing the world of molecular switches and rotors to bear on problems facing optoacoustic agents, this practical strategy will help to unleash the full potential of optoacoustic imaging in fundamental studies and translational uses.

Background-free correlation spectroscopy using an infrared mode-locked laser.

The recent advances in infrared laser technology are expanding the capabilities and applications of vibrational spectroscopy. A promising approach utilizing broadband infrared mode-locked lasers is background-free (BF) absorption spectroscopy. This method captures the free-induction decay (FID) of excited molecules while suppressing the background light. It is unique in that the signal strength increases with input optical power but eventually struggles with detector noise when targeting fewer molecules. In this paper, we present a novel method of multiplexed background-free spectroscopy using a spectral mask whose transmittance has a strong correlation with the absorption spectrum of a target molecule. We successfully demonstrate an order of magnitude increase in the sensitivity due to multiplexing as well as a high molecular contrast due to the spectral correlation. The presented results indicate the promising potential of the method for sensitive and selective detection of trace molecules.

In Vivo PET Detection of Lung Micrometastasis in Mice by Targeting Endothelial VCAM-1 Using a Dual-Contrast PET/MRI Probe.

Current clinical diagnostic imaging methods for lung metastases are sensitive only to large tumours (1-2 mm cross-sectional diameter), and early detection can dramatically improve treatment. We have previously demonstrated that an antibody-targeted MRI contrast agent based on microparticles of iron oxide (MPIO; 1 μm diameter) enables the imaging of endothelial vascular cell adhesion molecule-1 (VCAM-1). Using a mouse model of lung metastasis, upregulation of endothelial VCAM-1 expression was demonstrated in micrometastasis-associated vessels but not in normal lung tissue, and binding of VCAM-MPIO to these vessels was evident histologically. Owing to the lack of proton MRI signals in the lungs, we modified the VCAM-MPIO to include zirconium-89 (89Zr, t1/2 = 78.4 h) in order to allow the in vivo detection of lung metastases by positron emission tomography (PET). Using this new agent (89Zr-DFO-VCAM-MPIO), it was possible to detect the presence of micrometastases within the lung in vivo from ca. 140 μm in diameter. Histological analysis combined with autoradiography confirmed the specific binding of the agent to the VCAM-1 expressing vasculature at the sites of pulmonary micrometastases. By retaining the original VCAM-MPIO as the basis for this new molecular contrast agent, we have created a dual-modality (PET/MRI) agent for the concurrent detection of lung and brain micrometastases.

Cellpose as a reliable method for single-cell segmentation of autofluorescence microscopy images.

Autofluorescence microscopy uses intrinsic sources of molecular contrast to provide cellular-level information without extrinsic labels. However, traditional cell segmentation tools are often optimized for high signal-to-noise ratio (SNR) images, such as fluorescently labeled cells, and unsurprisingly perform poorly on low SNR autofluorescence images. Therefore, new cell segmentation tools are needed for autofluorescence microscopy. Cellpose is a deep learning network that is generalizable across diverse cell microscopy images and automatically segments single cells to improve throughput and reduce inter-human biases. This study aims to validate Cellpose for autofluorescence imaging, specifically from multiphoton intensity images of NAD(P)H. Manually segmented nuclear masks of NAD(P)H images were used to train new Cellpose models. These models were applied to PANC-1 cells treated with metabolic inhibitors and patient-derived cancer organoids (across 9 patients) treated with chemotherapies. These datasets include co-registered fluorescence lifetime imaging microscopy (FLIM) of NAD(P)H and FAD, so fluorescence decay parameters and the optical redox ratio (ORR) were compared between masks generated by the new Cellpose model and manual segmentation. The Dice score between repeated manually segmented masks was significantly lower than that of repeated Cellpose masks (p<0.0001) indicating greater reproducibility between Cellpose masks. There was also a high correlation (R 2 >0.9) between Cellpose and manually segmented masks for the ORR, mean NAD(P)H lifetime, and mean FAD lifetime across 2D and 3D cell culture treatment conditions. Masks generated from Cellpose and manual segmentation also maintain similar means, variances, and effect sizes between treatments for the ORR and FLIM parameters. Overall, Cellpose provides a fast, reliable, reproducible, and accurate method to segment single cells in autofluorescence microscopy images such that functional changes in cells are accurately captured in both 2D and 3D culture.

Mid-infrared gas absorption spectroscopy using a silicon germanium waveguide based chirped supercontinuum

We report the simulations of coherent supercontinuum generation from 2.63 to 8.04 μm in a silicon germanium photonic waveguide. The influence of input quantum noise pulses on coherence of the generated spectra was investigated. A high value of first order degree of coherence (i.e. 0.98) on supercontinuum spectra was predicted numerically. Our mid-infrared simulated coherent chirped supercontinuum source was then used as the input light source in absorption spectroscopy of carbon dioxide and methane gases. The simulated absorbance spectra for these greenhouse gases have high molecular contrast, thanks to the intense, chirped supercontinuum used.

Fast Nano-IR Hyperspectral Imaging Empowered by Large-Dataset-Free Miniaturized Spatial-Spectral Network.

The emerging field of nanoscale infrared (nano-IR) offers label-free molecular contrast, yet its imaging speed is limited by point-by-point traverse acquisition of a three-dimensional (3D) data cube. Here, we develop a spatial-spectral network (SS-Net), a miniaturized deep-learning model, together with compressive sampling to accelerate the nano-IR imaging. The compressive sampling is performed in both the spatial and spectral domains to accelerate the imaging process. The SS-Net is trained to learn the mapping from small nano-IR image patches to the corresponding spectra. With this elaborated mapping strategy, the training can be finished quickly within several minutes using the subsampled data, eliminating the need for a large-labeled dataset of common deep learning methods. We also designed an efficient loss function, which incorporates the image and spectral similarity to enhance the training. We first validate the SS-Net on an open stimulated Raman-scattering dataset; the results exhibit the potential of 10-fold imaging speed improvement with state-of-the-art performance. We then demonstrate the versatility of this approach on atomic force microscopy infrared (AFM-IR) microscopy with 7-fold imaging speed improvement, even on nanoscale Fourier transform infrared (nano-FTIR) microscopy with up to 261.6 folds faster imaging speed. We further showcase the generalization of this method on AFM-force volume-based multiparametric nanoimaging. This method establishes a paradigm for rapid nano-IR imaging, opening new possibilities for cutting-edge research in materials, photonics, and beyond.

Size-controlled synthesis of gold nanoparticles and related molecular imaging contrast for computed tomography

Size-controlled synthesis of gold nanoparticles and related molecular imaging contrast for computed tomography

Fluorescence saturation imaging microscopy: molecular fingerprinting with a standard confocal microscope.

Molecular specificity in fluorescence imaging of cells and tissues can be increased by measuring parameters other than intensity. For instance, fluorescence lifetime imaging became a widespread modality for biomedical optics. Previously, we suggested using the fluorescence saturation effect at pulsed laser excitation to map the absorption cross-section as an additional molecular contrast in two-photon microscopy [Opt. Lett.47(17), 4455 (2022).10.1364/OL.465605]. Here, it is shown that, somewhat counterintuitive, fluorescence saturation can be observed under cw excitation in a standard confocal microscopy setup. Mapping the fluorescence saturation parameter allows obtaining additional information about the fluorophores in the system, as demonstrated by the example of peptide hydrogel, stained cells and unstained thyroid gland. The suggested technique does not require additional equipment and can be implemented on confocal systems as is.

Investigating cartilage-related diseases by polarization-resolved second harmonic generation (P-SHG) imaging.

Establishing quantitative parameters for differentiating between healthy and diseased cartilage tissues by examining collagen fibril degradation patterns facilitates the understanding of tissue characteristics during disease progression. These findings could also complement existing clinical methods used to diagnose cartilage-related diseases. In this study, cartilage samples from normal, osteoarthritis (OA), and rheumatoid arthritis (RA) tissues were prepared and analyzed using polarization-resolved second harmonic generation (P-SHG) imaging and quantitative image texture analysis. The enhanced molecular contrast obtained from this approach is expected to aid in distinguishing between healthy and diseased cartilage tissues. P-SHG image analysis revealed distinct parameters in the cartilage samples, reflecting variations in collagen fibril arrangement and organization across different pathological states. Normal tissues exhibited distinct χ33/χ31 values compared with those of OA and RA, indicating collagen type transition and cartilage erosion with chondrocyte swelling, respectively. Compared with those of normal tissues, OA samples demonstrated a higher degree of linear polarization, suggesting increased tissue birefringence due to the deposition of type-I collagen in the extracellular matrix. The distribution of the planar orientation of collagen fibrils revealed a more directional orientation in the OA samples, associated with increased type-I collagen, while the RA samples exhibited a heterogeneous molecular orientation. This study revealed that the imaging technique, the quantitative analysis of the images, and the derived parameters presented in this study could be used as a reference for disease diagnostics, providing a clear understanding of collagen fibril degradation in cartilage.