High-resolution Molecular Imaging Research Articles

MR Molecular Imaging of Extradomain-B Fibronectin for Assessing Progression and Therapy Resistance of Prostate Cancer.

Accurate assessment and characterization of the progression and therapy response of prostate cancer are essential for precision healthcare of patients diagnosed with the disease. MRI is a clinical imaging modality routinely used for diagnostic imaging and treatment planning of prostate cancer. Extradomain B fibronectin (EDB-FN) is an oncofetal subtype of fibronectin highly expressed in the extracellular matrix of aggressive cancers, including prostate cancer. It is a promising molecular target for the detection and risk-stratification of prostate cancer with high-resolution MR molecular imaging (MRMI). In this study, we investigated the effectiveness of MRMI with an EDB-FN specific contrast agent MT218 for assessing the progression and therapy resistance of prostate cancer. Low grade LNCaP prostate cancer cells became an invasive phenotype LNCaP-CXCR2 with elevated EDB-FN expression after acquisition of the C-X-C motif chemokine receptor 2 (CXCR2). MT218-MRMI showed brighter signal enhancement in LNCaP-CXCR2 tumor xenografts with a ∼2-fold contrast-to-noise (CNR) increase than in LNCaP tumors in mice. Enzalutamide-resistant C4-2-DR prostate cancer cells were more invasive, with higher EDB-FN expression than parental C4-2 cells. Brighter signal enhancement with a ∼2-fold CNR increase was observed in the C4-2-DR xenografts compared to that of C4-2 tumors in mice with MT218-MRMI. Interestingly, when invasive PC3 prostate cancer cells developed resistance to paclitaxel, the drug-resistant PC3-DR cells became less invasive with reduced EDB-FN expression than the parental PC3 cells. MT218-MRMI detected reduced brightness in the PC3-DR xenografts with more than 2-fold reduction of CNR compared to PC3 tumors in mice. The signal enhancement in all tumors was supported by the immunohistochemical staining of EDB-FN with the G4 monoclonal antibody. The results indicate that MRMI of EDB-FN with MT218 has promise for detection, risk stratification, and monitoring the progression and therapy response of invasive prostate cancer.

Automated Generation and Analysis of Molecular Images Using Generative Artificial Intelligence Models.

The development of scanning probe microscopy (SPM) has enabled unprecedented scientific discoveries through high-resolution imaging. Simulations and theoretical analysis of SPM images are equally important as obtaining experimental images since their comparisons provide fruitful understandings of the structures and physical properties of the investigated systems. So far, SPM image simulations are conventionally based on quantum mechanical theories, which can take several days in tasks of large-scale systems. Here, we have developed a scanning tunneling microscopy (STM) molecular image simulation and analysis framework based on a generative adversarial model, CycleGAN. It allows efficient translations between STM data and molecular models. Our CycleGAN-based framework introduces an approach for high-fidelity STM image simulation, outperforming traditional quantum mechanical methods in efficiency and accuracy. We envision that the integration of generative networks and high-resolution molecular imaging opens avenues in materials discovery relying on SPM technologies.

SINGLE-CELL AND SPATIAL OMICS FOR MAPPING CELLULAR SENESCENCE IN HEALTH, AGING AND DISEASE

Abstract NIH SenNet consortium aims to dissect the heterogeneity of senescent cells (SnCs) and map their impact on the microenvironment at a single cell resolution and in the spatial tissue context, which requires the implementation of an array of omics technologies to comprehensively identify, characterize, and spatially profile SnCs across tissues in humans and mice. These technologies are broadly categorized into two groups –single cell omics and spatial mapping. To achieve single cell resolution and overcome the scarcity of SnCs, high-throughput single-cell and single-nucleus transcriptomic techniques have become a mainstay tool for surveying tens of thousands of cells to identify transcriptional signatures in rare cell populations, enabling discovery of potential new SnC biomarkers. Novel single cell mass spectrometry methods are developed for unbiased discovery of proteomic signatures of SnCs. A hallmark of SnCs is the senescence-associated secretory phenotype (SASP), which requires the use of proteomics, secretomics, metabolomics and lipidomics, especially SASP-associated extracellular vesicles, for comprehensive characterization of SAPS. High resolution molecular and cellular imaging of gene expression (e.g., MERFISH) or protein markers (e.g., CODEX) is critical for the study of SnCs in the large-scale tissue context. NGS-based spatial omics sequencing is poised to bridge the gap to realize both genome scale and cellular resolution in mapping SnCs in tissue. Novel technologies such as Seq-Scope and Pixel-Seq developed within SenNet further enabled subcellular resolution. SenNet investigators also developed spatially resolved epigenome and multi-omics sequencing techniques to link transcriptional or proteomic phenotype of SnCs to epigenetic mechanism. Further integration with high-resolution imaging makes spatial omics the crucial linchpin in connecting mechanistic underpinnings and molecular signatures with morphological features and spatial distribution. All these are critical for the construction of a map of SnCs and associated niches in the native tissue environment implicated in human health, aging, and disease, which is one of the main goals of the SenNet consortium.

From conventional to cutting edge imaging in rheumatology

Imaging instruments, such as conventional X‑ray, ultrasound and magnetic resonance imaging (MRI) are now fully established and highly valued in the care of rheumatology patients. However, the information provided by these imaging modalities in their current form is of limited utility for the prognostic prediction of individual patient outcomes. This article illuminates an important part of the development of imaging and shows that the vision of personalized medicine is becoming increasingly more tangible due to the further development of high-resolution imaging techniques, molecular imaging and artificial intelligence.

Microscopy-Directed Imaging Mass Spectrometry for Rapid High Spatial Resolution Molecular Imaging of Glomeruli.

The glomerulus is a multicellular functional tissue unit (FTU) of the nephron that is responsible for blood filtration. Each glomerulus contains multiple substructures and cell types that are crucial for their function. To understand normal aging and disease in kidneys, methods for high spatial resolution molecular imaging within these FTUs across whole slide images is required. Here we demonstrate a workflow using microscopy-driven selected sampling to enable 5 μm pixel size matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) of all glomeruli within whole slide human kidney tissues. Such high spatial resolution imaging entails large numbers of pixels, increasing the data acquisition times. Automating FTU-specific tissue sampling enables high-resolution analysis of critical tissue structures, while concurrently maintaining throughput. Glomeruli were automatically segmented using coregistered autofluorescence microscopy data, and these segmentations were translated into MALDI IMS measurement regions. This allowed high-throughput acquisition of 268 glomeruli from a single whole slide human kidney tissue section. Unsupervised machine learning methods were used to discover molecular profiles of glomerular subregions and differentiate between healthy and diseased glomeruli. Average spectra for each glomerulus were analyzed using Uniform Manifold Approximation and Projection (UMAP) and k-means clustering, yielding 7 distinct groups of differentiated healthy and diseased glomeruli. Pixel-wise k-means clustering was applied to all glomeruli, showing unique molecular profiles localized to subregions within each glomerulus. Automated microscopy-driven, FTU-targeted acquisition for high spatial resolution molecular imaging maintains high-throughput and enables rapid assessment of whole slide images at cellular resolution and identification of tissue features associated with normal aging and disease.

Space and Time Coherent Mapping for Subcellular Resolution of Imaging Mass Spectrometry.

Space and time coherent mapping (STCM) is a technology developed in our laboratory for improved matrix-assisted laser desorption ionization (MALDI) time of flight (TOF) imaging mass spectrometry (IMS). STCM excels in high spatial resolutions, which probe-based scanning methods cannot attain in conventional MALDI IMS. By replacing a scanning probe with a large field laser beam, focusing ion optics, and position-sensitive detectors, STCM tracks the entire flight trajectories of individual ions throughout the ionization process and visualizes the ionization site on the sample surface with a subcellular scale of precision and a substantially short acquisition time. Results obtained in thinly sectioned leech segmental ganglia and epididymis demonstrate that STCM IMS is highly suited for (1) imaging bioactive lipid messengers such as endocannabinoids and the mediators of neuronal activities in situ with spatial resolution sufficient to detail subcellular localization, (2) integrating resultant images in mass spectrometry to optically defined cell anatomy, and (3) assembling a stack of ion maps derived from mass spectra for cluster analysis. We propose that STCM IMS is the choice over a probe-based scanning mass spectrometer for high-resolution single-cell molecular imaging.

Age differential response to bevacizumab therapy in choroidal neovascularization in rabbits

Choroidal neovascularization (CNV) in young rabbits has been shown to have a rapid, robust response after treatment with bevacizumab, an anti-vascular endothelial growth factor (VEGF) medication. This investigation evaluates an age differential response to bevacizumab in older populations of rabbits using multimodal high resolution molecular imaging. Young (4 months old) and life span (14 months old) rabbits were given subretinal injections of Matrigel and VEGF to produce CNV. All CNV rabbit models were then treated with a bevacizumab intravitreal injection. Rabbits were then monitored longitudinally using photoacoustic microscopy (PAM), optical coherence tomography (OCT), color photography, and fluorescence imaging. Chain-like gold nanoparticle clusters (CGNP) conjugated with tripeptide arginylglycylaspartic acid (RGD) was injected intravenously for molecular imaging. Robust CNV developed in both young and old rabbits. After intravitreal bevacizumab injection, fluorescence signals were markedly decreased 90.13% in the young group. In contrast, old rabbit CNV area decreased by only 10.56% post-bevacizumab treatment. OCT images confirmed a rapid decrease of CNV in the young group. CGNPs demonstrated high PAM signal in old rabbits and minimal PAM signal in young rabbits after bevacizumab, indicating CNV regression. There is a significant difference in response to intravitreal bevacizumab treatment between young and old rabbits with CNV which can be monitored with multimodal molecular imaging. Old rabbits demonstrate significant persistent disease activity. This represents the first large eye model of persistent disease activity of CNV and could serve as the foundation for future investigations into the mechanism of persistent disease activity and the development of novel therapies.

Mitochondria-Targeted Fluorescence/Photoacoustic Dual-Modality Imaging Probe Tailored for Visual Precise Diagnosis of Drug-Induced Liver Injury.

The multispectral optoacoustic tomography (MSOT) technique can be used to perform high-resolution molecular imaging under deep tissues, which gives the technology significant prospective for clinical application. Here, we developed a superoxide anion (O2•-)-activated MSOT and fluorescence dual-modality imaging probe (APSA) for early diagnosis of drug-induced liver injury (DILI). APSA can respond quickly to O2•-, resulting in an absorption peak blueshift from 845 to 690 nm, which also leads to the photoacoustic (PA) signal at 690 nm and the fluorescence signal at 748 nm increases linearly with increasing O2•- concentration, which can be utilized to assess the extent of liver damage. The developed MSOT imaging method can eliminate background interference from hematopoietic tissue by collecting the PA signals excited at 680, 690, 740, 760, 800, 845, and 900 nm wavelengths to achieve noninvasive in situ visual diagnosis of DILI. The developed fluorescence imaging method can be used for the imaging of endogenous O2•- in living cells and anatomic diagnosis of liver injury. The developed probe has broad application prospects in the early diagnosis of DILI.

Methylated tetra-amide derivatives of paramagnetic complexes for magnetic resonance biosensing with both BIRDS and CEST.

Paramagnetic agents that utilize two mechanisms to provide physiological information by magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI) are described. MRI with chemical exchange saturation transfer (CEST) takes advantage of the agent's exchangeable protons (e.g., -OH or -NHx , where 2 ≥ x ≥ 1) to create pH contrast. The agent's incorporation of non-exchangeable protons (e.g., -CHy , where 3 ≥ y ≥ 1) makes it possible to map tissue temperature and/or pH using an MRSI method called biosensor imaging of redundant deviation in shifts (BIRDS). Hybrid probes based upon 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetate chelate (DOTA4- ) and its methylated analog (1,4,7,10-tetraazacyclododecane-α, α', α″, α‴-tetramethyl-1,4,7,10-tetraacetate, DOTMA4- ) were synthesized, and modified to create new tetra-amide chelates. Addition of several methyl groups per pendent arm of the symmetrical chelates, positioned proximally and distally to thulium ions (Tm3+ ), gave rise to favorable BIRDS properties (i.e., high signal-to-noise ratio (SNR) from non-exchangeable methyl proton peaks) and CEST responsiveness (i.e., from amide exchangeable protons). Structures of the Tm3+ probes elucidate the influence of methyl group placement on sensor performance. An eight-coordinate geometry with high symmetry was observed for the complexes: Tm-L1 was based on DOTA4- , whereas Tm-L2 and Tm-L3 were based on DOTMA4- , where the latter contained an additional carboxylate at the distal end of each arm. The distance of Tm3+ from terminal methyl carbons is a key determinant for sustaining BIRDS temperature sensitivity without compromising CEST pH contrast; however, water solubility was influenced by introduction of hydrophobic methyl groups and hydrophilic carboxylate. Combined BIRDS and CEST detection of Tm-L2, which features two high-SNR methyl peaks and a strong amide CEST peak, should enable simultaneous temperature and pH measurements for high-resolution molecular imaging in vivo.

Deep UV Microscopy Identifies Prostatic Basal Cells: An Important Biomarker for Prostate Cancer Diagnostics.

Objective and Impact Statement. Identifying benign mimics of prostatic adenocarcinoma remains a significant diagnostic challenge. In this work, we developed an approach based on label-free, high-resolution molecular imaging with multispectral deep ultraviolet (UV) microscopy which identifies important prostate tissue components, including basal cells. This work has significant implications towards improving the pathologic assessment and diagnosis of prostate cancer. Introduction. One of the most important indicators of prostate cancer is the absence of basal cells in glands and ducts. However, identifying basal cells using hematoxylin and eosin (H&E) stains, which is the standard of care, can be difficult in a subset of cases. In such situations, pathologists often resort to immunohistochemical (IHC) stains for a definitive diagnosis. However, IHC is expensive and time-consuming and requires more tissue sections which may not be available. In addition, IHC is subject to false-negative or false-positive stains which can potentially lead to an incorrect diagnosis. Methods. We leverage the rich molecular information of label-free multispectral deep UV microscopy to uniquely identify basal cells, luminal cells, and inflammatory cells. The method applies an unsupervised geometrical representation of principal component analysis to separate the various components of prostate tissue leading to multiple image representations of the molecular information. Results. Our results show that this method accurately and efficiently identifies benign and malignant glands with high fidelity, free of any staining procedures, based on the presence or absence of basal cells. We further use the molecular information to directly generate a high-resolution virtual IHC stain that clearly identifies basal cells, even in cases where IHC stains fail. Conclusion. Our simple, low-cost, and label-free deep UV method has the potential to improve and facilitate prostate cancer diagnosis by enabling robust identification of basal cells and other important prostate tissue components.

Extracting physical characteristics of higher-order chromatin structures from 3D image data

Higher-order chromatin structures have functional impacts on gene regulation and cell identity determination. Using high-throughput sequencing (HTS)-based methods like Hi-C, active or inactive compartments and open or closed topologically associating domain (TAD) structures can be identified on a cell population level. Recently developed high-resolution three-dimensional (3D) molecular imaging techniques such as 3D electron microscopy with in situ hybridization (3D-EMSIH) and 3D structured illumination microscopy (3D-SIM) enable direct detection of physical representations of chromatin structures in a single cell. However, computational analysis of 3D image data with explainability and interpretability on functional characteristics of chromatin structures is still challenging. We developed Extracting Physical-Characteristics from Images of Chromatin Structures (EPICS), a machine-learning based computational method for processing high-resolution chromatin 3D image data. Using EPICS on images produced by 3D-EMISH or 3D-SIM techniques, we generated more direct 3D representations of higher-order chromatin structures, identified major chromatin domains, and determined the open or closed status of each domain. We identified several high-contributing features from the model as the major physical characteristics that define the open or closed chromatin domains, demonstrating the explainability and interpretability of EPICS. EPICS can be applied to the analysis of other high-resolution 3D molecular imaging data for spatial genomics studies. The R and Python codes of EPICS are available athttps://github.com/zang-lab/epics.

In vivo imaging tools for functional assessment of biomaterials implanted bone regeneration

Since the discovery of X-rays and its first use in imaging of a hand, bone tissue has been the chapter of interest in medical imaging. However, X-ray imaging poses limitations nowadays owing to the augmented complexity of implant scaffolds as well as with the advances in bone engineering. As a result, advanced follow-up imaging techniques are of paramount necessity for effective postoperative characterization. Moreover, it is also needed to search for non-invasive, high-sensitivity, and high-resolution structural, functional, and molecular imaging techniques such as acoustic, optical, magnetic, X-Ray, electron, ultrasound, and nuclear imaging, etc. as an alternative to normally used X-ray computed tomography. Further, enthusiastic preclinical scanners have turned out to be accessible, with sensitivity and resolution even superior to clinical scanners, as a consequence helping a rapid transformation from preclinical to clinical applications. Besides, recently, bone-specific probes and contrast agents are developing for better imaging tools in bone-tissue engineering applications. This review highlights such emerging preclinical imaging tools, each with its individual potencies and flaws, either used only or in combination. In particular, multimodal imaging will significantly add to improve the present understanding in the characterization of bone regenerative processes.

Fiber-based source of 500 kW mid-infrared solitons.

Fiber-based sources delivering high-energy few-cycle pulses at high repetition rates are currently being developed in the near-infrared spectral range, thanks to the wide availability of telecommunication-grade optical fibers and components. Similar sources in the middle-wave infrared (mid-IR) spectral domain, however, are scarce, although such sources are of high interest for applications such as high-precision frequency metrology and molecular spectroscopy or as a seed source to reach further into the mid-IR via coherent nonlinear processes. Here we report on the design of a fiber-based source of 50-nJ energy 90 fs duration pulses up to 2950 nm, corresponding to 500 kW peak power. To obtain this level of peak power we exploit multi-solitonic fission and soliton self-frequency shift in large mode area fibers excited by picosecond pulses emitted at 2 µm from a megahertz repetition rate fiber laser. We leverage mature silica-based fiber technology up to 2.4 µm and restrict the use of fluoride fiber to the very last frequency-shifting stage. The level of instantaneous power and ultra-short duration achieved in this Letter pave the way to all-fiber format generation of an ultra-broadband coherent continuum in the mid-IR with profound implications for applications such as high-resolution molecular spectroscopy and imaging.

High-Resolution Label-Free Molecular Imaging of Brain Tumor.

Molecular imaging has long been recognized as an important tool for diagnosis, characterization, and monitoring of treatment responses of brain tumors. Magnetic resonance spectroscopic imaging (MRSI) is a label-free molecular imaging technique capable of mapping metabolite distributions non-invasively. Several metabolites detectable by MRSI, including Choline, Lactate and N-Acetyl Aspartate, have been proved useful biomarkers for brain tumor characterization. However, clinical application of MRSI has been limited by poor resolution, small spatial coverage, low signal-to-noise ratio and long scan time. This work presents a novel MRSI method for fast, high-resolution metabolic imaging of brain tumor. This method synergistically integrates fast acquisition sequence, sparse sampling, subspace modeling and machine learning to enable 3D mapping of brain metabolites with a spatial resolution of 2.0×3.0×3.0 mm3 in a 7-minute scan. Experimental results obtained from patients with diagnosed brain tumor showed great promise for capturing small-size tumors and revealing intra-tumor metabolic heterogeneities.Clinical Relevance - This paper presents a novel technique for label-free molecular imaging of brain tumor. With further development, this technology may enable many potential clinical applications, from tumor detection, characterization, to assessment of treatment efficacy.

Artificial intelligence-augmented, label-free molecular imaging method for tissue identification, cancer diagnosis, and cancer margin detection.

Label-free high-resolution molecular and cellular imaging strategies for intraoperative use are much needed, but not yet available. To fill this void, we developed an artificial intelligence-augmented molecular vibrational imaging method that integrates label-free and subcellular-resolution coherent anti-stokes Raman scattering (CARS) imaging with real-time quantitative image analysis via deep learning (artificial intelligence-augmented CARS or iCARS). The aim of this study was to evaluate the capability of the iCARS system to identify and differentiate the parathyroid gland and recurrent laryngeal nerve (RLN) from surrounding tissues and detect cancer margins. This goal was successfully met.

Living-System-Driven Evolution of Self-Assembled-Peptide Probes: For Boosting Glioma Theranostics.

The primary principle for new molecular evolution is from nature, mimicking nature, and beyond nature, since it is extremely important for the artificial molecules to keep their structure and function in the natural system. It is especially true for the self-assembled supramolecular construction in situ in complicated living bodies. Herein, we put forward a directed evolution strategy consisting of high-content screening from the living system and artificial modification in order to find "totipotential peptides" in a precise way. Progressive dimension reduction of the capability and precise anchoring of the target were realized. Through the living system evolution, we obtain a glioma-targeting and living system-induced self-assembled leading compound CCP. Through the artificial evolution, CCP was further stapled and was hydrophobically modified as NSCCP2, which demonstrated stability and NIR-II emission characteristics. NSCCP2 could realize high-resolution molecular imaging and therapy simultaneously. We envision that the strategy and its applications provide a new method for molecular discovery and improve the performance of peptide nano-self-assemblies for diagnostics and therapy.

Focused x-ray luminescence imaging system for small animals based on a rotary gantry.

.Significance: The ability to detect and localize specific molecules through tissue is important for elucidating the molecular basis of disease and treatment. Unfortunately, most current molecular imaging tools in tissue either lack high spatial resolution (e.g., diffuse optical fluorescence tomography or positron emission tomography) or lack molecular sensitivity (e.g., micro-computed tomography, ). X-ray luminescence imaging emerged about 10 years ago to address this issue by combining the molecular sensitivity of optical probes with the high spatial resolution of x-ray imaging through tissue. In particular, x-ray luminescence computed tomography (XLCT) has been demonstrated as a powerful technique for the high-resolution imaging of deeply embedded contrast agents in three dimensions (3D) for small-animal imaging.Aim: To facilitate the translation of XLCT for small-animal imaging, we have designed and built a small-animal dedicated focused x-ray luminescence tomography (FXLT) scanner with a scanner, synthesized bright and biocompatible nanophosphors as contrast agents, and have developed a deep-learning-based reconstruction algorithm.Approach: The proposed FXLT imaging system was designed using computer-aided design software and built according to specifications. nanophosphors doped with europium or terbium were synthesized with a silica shell for increased biocompatibility and functionalized with biotin. A deep-learning-based XLCT image reconstruction was also developed based on the residual neural network as a data synthesis method of projection views from few-view data to enhance the reconstructed image quality.Results: We have built the FXLT scanner for small-animal imaging based on a rotational gantry. With all major imaging components mounted, the motor controlling the gantry can be used to rotate the system with a high accuracy. The synthesized nanophosphors displayed distinct x-ray luminescence emission, which enables multi-color imaging, and has successfully been bound to streptavidin-coated substrates. Lastly, numerical simulations using the proposed deep-learning-based reconstruction algorithm has demonstrated a clear enhancement in the reconstructed image quality.Conclusions: The designed FXLT scanner, synthesized nanophosphors, and deep-learning-based reconstruction algorithm show great potential for the high-resolution molecular imaging of small animals.

A systematic review of imaging studies of human brown adipose tissue.

Brown adipose tissue (BAT) is involved in energy dissipation and has been linked to weight loss, insulin sensitivity, and reduced risk of atherosclerotic disease. BAT is found most often in the supraclavicular region, as well as mediastinal and paravertebral areas, and it is predominantly seen in young persons. BAT is activated by cold temperature and the sympathetic nervous system. In humans, BAT was initially detected via 2-deoxy-2-[18 F]fluoro-d-glucose (FDG) positron emission tomography/computed tomography (PET/CT), a high-resolution molecular imaging modality used to identify and stage malignancies. Recent studies have shown that BAT can be localized using conventional imaging modalities, such as CT or magnetic resonance imaging, as well as radiotracers used for single-photon emission CT. In this systematic review, we have summarized the evidence for BAT detection in humans using various imaging techniques.

Deep Learning Approach for Dynamic Sparse Sampling for High-Throughput Mass Spectrometry Imaging.

A Supervised Learning Approach for Dynamic Sampling (SLADS) addresses traditional issues with the incorporation of stochastic processes into a compressed sensing method. Statistical features, extracted from a sample reconstruction, estimate entropy reduction with regression models, in order to dynamically determine optimal sampling locations. This work introduces an enhanced SLADS method, in the form of a Deep Learning Approach for Dynamic Sampling (DLADS), showing reductions in sample acquisition times for high-fidelity reconstructions between ~ 70-80% over traditional rectilinear scanning. These improvements are demonstrated for dimensionally asymmetric, high-resolution molecular images of mouse uterine and kidney tissues, as obtained using Nanospray Desorption ElectroSpray Ionization (nano-DESI) Mass Spectrometry Imaging (MSI). The methodology for training set creation is adjusted to mitigate stretching artifacts generated when using prior SLADS approaches. Transitioning to DLADS removes the need for feature extraction, further advanced with the employment of convolutional layers to leverage inter-pixel spatial relationships. Additionally, DLADS demonstrates effective generalization, despite dissimilar training and testing data. Overall, DLADS is shown to maximize potential experimental throughput for nano-DESI MSI.

Abstract 14935: Targeted Optical Molecular Imaging of Atheroma Calcification Using Novel Aldendronate-based Probe

Background/Objectives: Vascular spotty calcification is an actively regulated biological process resulting in plaque vulnerability. We investigated the feasibility of a novel alendronate-based near-infrared fluorescence (NIRF)-emitting probe to specifically target atherosclerotic calcification in a murine model in vivo using our customized high-resolution multichannel intravital molecular imaging system (IVFM). Methods/Results: We have fabricated a calcium-binding NIRF probe by chemically coupling alendronate, a specific targeting ligand, and NIRF-emitting Cy5.5 to the ends of azide-PEG-NHS ester (Al-Cy5.5). Prepared Al-Cy5.5 has high affinity for calcium phosphate-containing bone minerals. In vitro, Al-Cy5.5 specifically binds to RANKL-induced osteogenic-macrophages as compared to macrophages (p<0.01). On whole body fluorescence imaging to assess time-dependent excretion, NIRF signals remained visible up to 48 hrs. Then, in mice with calcified plaque induced by a combination diet of high-cholesterol and warfarin, Al-Cy5.5 (2.5 mg/kg) was intravenously injected. 48 hrs after administration, murine calcified atheroma was assessed using a customized high-resolution multichannel IVFM, which demonstrated highly enhanced NIRF signals in vivo in the calcified areas of murine carotid plaques (p<0.01, Figure). Ex vivo laser scanning fluorescence microscopic and immune-histological findings from the corresponding sister sections well corroborated the in vivo imaging results, which demonstrated the co-localization of NIRF signals with plaque calcifications (von-Kossa stain). Conclusions: Our novel calcification targeted probe, Al-Cy5.5, was able to selectively target atheroma calcification in vivo in a murine model as assessed by optical IVFM. This novel targetable strategy is expected to provide a promising theranostic basis for calcified high-risk plaques by integration with multimodal customized catheter imaging system.