High-throughput Raman spectroscopy allows ex vivo characterization of murine small intestinal intra-epithelial lymphocytes (IEL).

T cells are considered to be critical drivers of intestinal inflammation in mice and people. The so called intra-epithelial lymphocyte (IEL) compartment largely consist of T cells. Interestingly, the specific regulation and contribution of IELs in the context of inflammatory bowel disease remains poorly understood, in part due to the lack of appropriate analysis tools. Powerful, label-free methods could ultimately provide access to this cell population and hence give valuable insight into IEL biology and even more to their disease-related functionalities. Raman spectroscopy has demonstrated over the last few years its potential for reliable cell characterization and differentiation, but its utility in regard to IEL exploration remains unknown. To address this question experimentally, we utilized a murine, T cell-driven experimental model system which is accepted to model human gut inflammation. Here, we repopulated the small intestinal IEL compartment (SI IELs) of Rag1-deficient mice endogenously lacking T cells by transferring naïve CD4+ T helper cells intraperitoneally. Using multivariate statistical analysis, high-throughput Raman spectroscopy managed to define a cell subpopulation ex vivo within the SI IEL pool of mice previously receiving T cells in vivo that displayed characteristic spectral features of lymphocytes. Raman data sets matched flow cytometry analyses with the latter identifying T cell receptor (TCR)αß+ CD4+ T cell population in SI IELs from T cell-transferred mice, but not from control mice, in an abundance comparable to the one detected by Raman spectroscopy. Hence, in this study, we provide experimental evidence for high-throughput Raman spectroscopy to be a novel, future tool to reliably identify and potentially further characterize the T cell pool of small intestinal IELs ex vivo.

Revealing the Chemical Composition of Birch Pollen Grains by Raman Spectroscopic Imaging.

The investigation of the biochemical composition of pollen grains is of the utmost interest for several environmental aspects, such as their allergenic potential and their changes in growth conditions due to climatic factors. In order to fully understand the composition of pollen grains, not only is an in-depth analysis of their molecular components necessary but also spatial information of, e.g., the thickness of the outer shell, should be recorded. However, there is a lack of studies using molecular imaging methods for a spatially resolved biochemical composition on a single-grain level. In this study, Raman spectroscopy was implemented as an analytical tool to investigate birch pollen by imaging single pollen grains and analyzing their spectral profiles. The imaging modality allowed us to reveal the layered structure of pollen grains based on the biochemical information of the recorded Raman spectra. Seven different birch pollen species collected at two different locations in Germany were investigated and compared. Using chemometric algorithms such as hierarchical cluster analysis and multiple-curve resolution, several components of the grain wall, such as sporopollenin, as well as the inner core presenting high starch concentrations, were identified and quantified. Differences in the concentrations of, e.g., sporopollenin, lipids and proteins in the pollen species at the two different collection sites were found, and are discussed in connection with germination and other growth processes.

Multimodal Scanning Microscope Combining Optical Coherence Tomography, Raman Spectroscopy and Fluorescence Lifetime Microscopy for Mesoscale Label-Free Imaging of Tissue.

Multimodal optical imaging of tissue has significant potential to become an indispensable diagnostic tool in clinical pathology. Conventional bright-field microscopy provides contrast based on attenuation or reflectance of light, having no depth-related information and no molecular specificity. Recent developments in biomedical optics have introduced a variety of optical modalities, such as Raman spectroscopy (RS), fluorescence lifetime imaging microscopy (FLIM) of endogenous fluorophores, optical coherence tomography (OCT), and others, which provide a distinct characteristic, i.e., molecular, chemical, and morphological information, of the sample. To harvest the full analytical potential of those modalities, we have developed a novel multimodal imaging system, which allows the co-registered acquisition of OCT/FLIM/RS on a single device. The present implementation allows the investigation of biological tissues in the mesoscale range, 0.1-5 mm in a correlated manner. Due to the co-registered acquisition of the modalities, it is possible to directly compare and evaluate the corresponding information between the three modalities. Moreover, by additionally preparing and characterizing entire pathological hematoxylin and eosin (H&E) slides of head and neck biopsies, it is also possible to correlate the multimodal spectroscopic information to any location of the ground truth H&E information. To the best of our knowledge, this is the first development and implementation of a compact and clinically applicable multimodal scanning microscope, which combines OCT, FLIM, and RS together with the possibility for co-registering H&E information for a morpho-chemical tissue characterization and a correlation with the pathological ground truth (H&E) of the underlying signal origin directly in a clinical environment.

Detection and Differentiation of Bacterial and Fungal Infection of Neutrophils from Peripheral Blood Using Raman Spectroscopy.

Neutrophils are important cells of the innate immune system and the major leukocyte subpopulation in blood. They are responsible for recognizing and neutralizing invading pathogens, such as bacteria or fungi. For this, neutrophils are well equipped with pathogen recognizing receptors, cytokines, effector molecules, and granules filled with reactive oxygen species (ROS)-producing enzymes. Depending on the pathogen type, different reactions are triggered, which result in specific activation states of the neutrophils. Here, we aim to establish a label-free method to indirectly detect infections and to identify the cause of infection by spectroscopic characterization of the neutrophils. For this, isolated neutrophils from human peripheral blood were stimulated in an in vitro infection model with heat-inactivated Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacterial pathogens as well as with heat-inactivated and viable fungi (Candida albicans). Label-free and nondestructive Raman spectroscopy was used to characterize neutrophils on a single cell level. Phagocytized fungi could be visualized in a few high-resolution false color images of individual neutrophils using label-free Raman spectroscopic imaging. Using a high-throughput screening Raman spectroscope (HTS-RS), Raman spectra of more than 2000 individual neutrophils from three different donors were collected in each treatment group, yielding a data set of almost 20 000 neutrophil spectra. Random forest classification models were trained to differentiate infected and noninfected cells with high accuracy (90%). Among the neutrophils challenged with pathogens, even the cause of infection, bacterial or fungal, was predicted correctly with 92% accuracy. Therefore, Raman spectroscopy enables reliable neutrophil phenotyping and infection diagnosis in a label-free manner. In contrast to the microbiological diagnostic standard, where the pathogen is isolated in time-consuming cultivation, this Raman-based method could potentially be blood-culture independent, thus saving precious time in bloodstream infection diagnostics.

Development and evaluation of a hand-held fiber-optic Raman probe with an integrated autofocus unit.

Current implementations of fiber-optic Raman spectroscopy probes are frequently based on non-contact probes with a fixed focus and thus and have to precisely maintain the probe-to-sample distance to ensure a sufficient signal collection. We propose and experimentally demonstrate a novel hand-held fiber-optic Raman probe design, which is based on a liquid lens autofocusing unit, combined with a distance sensor and an in-house developed algorithm to precisely determine the probe-to-sample distance. The reported probe significantly improves the signal stability even for hand-held operation, while reducing distance-dependent artifacts for the acquisition of Raman spectra and can improve the acquisition of Raman spectra in a variety of applications.

Combined Raman and AFM detection of changes in HeLa cervical cancer cells induced by CeO2 nanoparticles - molecular and morphological perspectives.

The design of nanoparticles for application in medical diagnostics and therapy requires a thorough understanding of various aspects of nanoparticle-cell interactions. In this work, two unconventional methods for the study of nanoparticle effects on cells, Raman spectroscopy and atomic force microscopy (AFM), were employed to track the molecular and morphological changes that are caused by the interaction between cervical carcinoma-derived HeLa cells and two types of cerium dioxide (CeO2) nanoparticles, ones with dextran coating and the others with no coating. Multivariate statistical analyses of Raman spectra, such as principal component analysis and partial least squares regression, were applied in order to extract the variations in the vibrational features of cell biomolecules and through them, the changes in biomolecular content and conformation. Both types of nanoparticles induced changes in DNA, lipid and protein contents of the cell and variations of the protein secondary structure, whereas dextran-coated CeO2 affected the cell-growth rate to a higher extent. Atomic force microscopy showed changes in cell roughness, cell height and nanoparticle effects on surface molecular layers. The method differentiated between the impact of dextran-coated and uncoated CeO2 nanoparticles with higher precision than performed viability tests. Due to the holistic approach provided by vibrational information on the overall cell content, accompanied by morphological modifications observed by high-resolution microscopy, this methodology offers a wider picture of nanoparticle-induced cell changes, in a label-free single-cell manner.

Morpho-molecular ex vivo detection and grading of non-muscle-invasive bladder cancer using forward imaging probe based multimodal optical coherence tomography and Raman spectroscopy.

Non-muscle-invasive bladder cancer affects millions of people worldwide, resulting in significant discomfort to the patient and potential death. Today, cystoscopy is the gold standard for bladder cancer assessment, using white light endoscopy to detect tumor suspected lesion areas, followed by resection of these areas and subsequent histopathological evaluation. Not only does the pathological examination take days, but due to the invasive nature, the performed biopsy can result in significant harm to the patient. Nowadays, optical modalities, such as optical coherence tomography (OCT) and Raman spectroscopy (RS), have proven to detect cancer in real time and can provide more detailed clinical information of a lesion, e.g. its penetration depth (stage) and the differentiation of the cells (grade). In this paper, we present an ex vivo study performed with a combined piezoelectric tube-based OCT-probe and fiber optic RS-probe imaging system that allows large field-of-view imaging of bladder biopsies, using both modalities and co-registered visualization, detection and grading of cancerous bladder lesions. In the present study, 119 examined biopsies were characterized, showing that fiber-optic based OCT provides a sensitivity of 78% and a specificity of 69% for the detection of non-muscle-invasive bladder cancer, while RS, on the other hand, provides a sensitivity of 81% and a specificity of 61% for the grading of low- and high-grade tissues. Moreover, the study shows that a piezoelectric tube-based OCT probe can have significant endurance, suitable for future long-lasting in vivo applications. These results also indicate that combined OCT and RS fiber probe-based characterization offers an exciting possibility for label-free and morpho-chemical optical biopsies for bladder cancer diagnostics.

High-throughput screening Raman microspectroscopy for assessment of drug-induced changes in diatom cells.

High-throughput screening Raman spectroscopy (HTS-RS) with automated localization algorithms offers unsurpassed speed and sensitivity to investigate the effect of dithiothreitol on the diatom Phaedactylum tricornutum. The HTS-RS capability that was demonstrated for this model system can be transferred to unmet analytical applications such as kinetic in vivo studies of microalgal assemblages.

High-content screening Raman spectroscopy (HCS-RS) of panitumumab-exposed colorectal cancer cells.

Raman spectroscopy can provide the biomolecular fingerprint of a cell in a label-free manner. Although a variety of clinical and biomedical applications have been demonstrated, the method remains largely a niche technology. The two main problems are the complexity of data acquisition and the complexity of data analysis. Generally, Raman measurements are performed manually and require a substantial amount of time. This, on the other hand, frequently results in a low number of samples and hence with questionable statistical evaluation. Here, we propose an automated high content screening Raman spectroscopy (HCS-RS) platform, which can perform a series of experiments without human interaction, significantly increasing the number of measured samples and making the measurement more reliable. The automated image processing of bright field images in combination with automatic spectral acquisition of the molecular fingerprint of cells exposed to different physiological conditions enables label-free high content screening applications. The performance of the developed HCS-RS platform is demonstrated by investigating the effect of panitumumab on SW48 and SW480 colorectal cancer cells with wild-type and mutated K-RAS, respectively, in a series of concentrations. Our result indicates that the increased content of panitumumab prohibits the activation of the MAP kinase of the colorectal cancer cells with wild-type K-RAS strongly, whereas there is no significant effect on the K-RAS mutated cells. Moreover, the relative amount of the panitumumab content present in the cells is determined from the Raman spectral information, which could be beneficial for personalized patient treatment.

Label-free molecular mapping and assessment of glycogen in C. elegans.

Caenorhabditis elegans is an animal model frequently used in research on the effects of metabolism on organismal aging. This comes with a requirement for methods to investigate metabolite content, turnover, and distribution. The aim of our study was to assess the use of a label-free approach to determine both content and distribution of glycogen, the storage form of glucose, in C. elegans. To this end, we grew C. elegans worms under three different dietary conditions for 24-48 h, representing starvation, regular diet and a high glucose diet, followed by analysis of glycogen content. Glycogen analysis was performed on fixed individual whole worms using Raman micro-spectroscopy (RMS). Results were confirmed by comparison with two conventional assays, i.e. iodine staining of worms and enzymatic determination of glycogen. RMS was further used to assess overall lipid and protein content and distribution in the same samples used for glycogen analysis. Expectedly, both glycogen and lipid content were highest in worms grown on a high glucose diet, lower in regularly fed, and lowest in starved nematodes. In summary, RMS is a method suitable for analysis of glycogen content in C. elegans that has the advantage over established methods that (i) individual worms (rather than hundreds per sample) can be analyzed, (ii) glycogen distribution can be assessed at subcellular resolution and (iii) the distribution patterns of other macromolecules can be assessed from the same worms. Thus, RMS has the potential to be used as a sensitive, accurate, cost-effective and high throughput method to evaluate glycogen stores in C. elegans.

Application of High-Throughput Screening Raman Spectroscopy (HTS-RS) for Label-Free Identification and Molecular Characterization of Pollen.

Pollen studies play a critical role in various fields of science. In the last couple of decades, replacement of manual identification of pollen by image-based methods using pollen morphological features was a great leap forward, but challenges for pollen with similar morphology remain, and additional approaches are required. Spectroscopy approaches for identification of pollen, such as Raman spectroscopy has potential benefits over traditional methods, due to the investigation of the intrinsic molecular composition of a sample. However, current Raman-based characterization of pollen is complex and time-consuming, resulting in low throughput and limiting the statistical significance of the acquired data. Previously demonstrated high-throughput screening Raman spectroscopy (HTS-RS) eliminates the complexity as well as human interaction by incorporation full automation of the data acquisition process. Here, we present a customization of HTS-RS for pollen identification, enabling sampling of a large number of pollen in comparison to other state-of-the-art Raman pollen investigations. We show that using Raman spectra we are able to provide a preliminary estimation of pollen types based on growth habits using hierarchical cluster analysis (HCA) as well as good taxonomy of 37 different Pollen using principal component analysis-support vector machine (PCA-SVM) with good accuracy even for the pollen specimens sharing similar morphological features. Our results suggest that HTS-RS platform meets the demands for automated pollen detection making it an alternative method for research concerning pollen.

High-Throughput Screening Raman Spectroscopy Platform for Label-Free Cellomics.

We present a high-throughput screening Raman spectroscopy (HTS-RS) platform for a rapid and label-free macromolecular fingerprinting of tens of thousands eukaryotic cells. The newly proposed label-free HTS-RS platform combines automated imaging microscopy with Raman spectroscopy to enable a rapid label-free screening of cells and can be applied to a large number of biomedical and clinical applications. The potential of the new approach is illustrated by two applications. (1) HTS-RS-based differential white blood cell count. A classification model was trained using Raman spectra of 52 218 lymphocytes, 48 220 neutrophils, and 7 294 monocytes from four volunteers. The model was applied to determine a WBC differential for two volunteers and three patients, producing comparable results between HTS-RS and machine counting. (2) HTS-RS-based identification of circulating tumor cells (CTCs) in 1:1, 1:9, and 1:99 mixtures of Panc1 cells and leukocytes yielded ratios of 55:45, 10:90, and 3:97, respectively. Because the newly developed HTS-RS platform can be transferred to many existing Raman devices in all laboratories, the proposed implementation will lead to a significant expansion of Raman spectroscopy as a standard tool in biomedical cell research and clinical diagnostics.

A droplet-based microfluidic chip as a platform for leukemia cell lysate identification using surface-enhanced Raman scattering.

A new approach is presented for cell lysate identification which uses SERS-active silver nanoparticles and a droplet-based microfluidic chip. Eighty-nanoliter droplets are generated by injecting silver nanoparticles, KCl as aggregation agent, and cell lysate containing cell constituents, such as nucleic acids, carbohydrates, metabolites, and proteins into a continuous flow of mineral oil. This platform enables accurate mixing of small volumes inside the meandering channels of the quartz chip and allows acquisition of thousands of SERS spectra with 785 nm excitation at an integration time of 1 s. Preparation of three batches of three leukemia cell lines demonstrated the experimental reproducibility. The main advantage of a high number of reproducible spectra is to apply statistics for large sample populations with robust classification results. A support vector machine with leave-one-batch-out cross-validation classified SERS spectra with sensitivities, specificities, and accuracies better than 99% to differentiate Jurkat, THP-1, and MONO-MAC-6 leukemia cell lysates. This approach is compared with previous published reports about Raman spectroscopy for leukemia detection, and an outlook is given for transfer to single cells. A quartz chip was designed for SERS at 785 nm excitation. Principal component analysis of SERS spectra clearly separates cell lysates using variations in band intensity ratios.

Evaluation of Shifted Excitation Raman Difference Spectroscopy and Comparison to Computational Background Correction Methods Applied to Biochemical Raman Spectra.

Raman spectroscopy provides label-free biochemical information from tissue samples without complicated sample preparation. The clinical capability of Raman spectroscopy has been demonstrated in a wide range of in vitro and in vivo applications. However, a challenge for in vivo applications is the simultaneous excitation of auto-fluorescence in the majority of tissues of interest, such as liver, bladder, brain, and others. Raman bands are then superimposed on a fluorescence background, which can be several orders of magnitude larger than the Raman signal. To eliminate the disturbing fluorescence background, several approaches are available. Among instrumentational methods shifted excitation Raman difference spectroscopy (SERDS) has been widely applied and studied. Similarly, computational techniques, for instance extended multiplicative scatter correction (EMSC), have also been employed to remove undesired background contributions. Here, we present a theoretical and experimental evaluation and comparison of fluorescence background removal approaches for Raman spectra based on SERDS and EMSC.

Label-Free Molecular Imaging of Biological Cells and Tissues by Linear and Nonlinear Raman Spectroscopic Approaches.

Raman spectroscopy is an emerging technique in bioanalysis and imaging of biomaterials owing to its unique capability of generating spectroscopic fingerprints. Imaging cells and tissues by Raman microspectroscopy represents a nondestructive and label-free approach. All components of cells or tissues contribute to the Raman signals, giving rise to complex spectral signatures. Resonance Raman scattering and surface-enhanced Raman scattering can be used to enhance the signals and reduce the spectral complexity. Raman-active labels can be introduced to increase specificity and multimodality. In addition, nonlinear coherent Raman scattering methods offer higher sensitivities, which enable the rapid imaging of larger sampling areas. Finally, fiber-based imaging techniques pave the way towards in vivo applications of Raman spectroscopy. This Review summarizes the basic principles behind medical Raman imaging and its progress since 2012.

Rapid acquisition of mean Raman spectra of eukaryotic cells for a robust single cell classification.

Raman spectroscopy has previously been used to identify eukaryotic and prokaryotic cells. While prokaryotic cells are small in size and can be assessed by a single Raman spectrum, the larger size of eukaryotic cells and their complex organization requires the acquisition of multiple Raman spectra to properly characterize them. A Raman spectrum from a diffraction-limited spot at an arbitrary location within a cell results in spectral variations that affect classification approaches. To probe whole cells with Raman imaging at high spatial resolution is time consuming, because a large number of Raman spectra need to be collected, resulting in low cell throughput and impairing statistical analysis due to low cell numbers. Here we propose a method to overcome the effects of cellular heterogeneity by acquiring integrated Raman spectra covering a large portion of a cell. The acquired spectrum represents the mean macromolecular composition of a cell with an exposure time that is comparable to acquisition of a single Raman spectrum. Data sets were collected from T lymphocyte Jurkat cells, and pancreatic cell lines Capan1 and MiaPaca2. Cell classification by support vector machines was compared for single spectra, spectra of images and integrated Raman spectra of cells. The integrated approach provides better and more stable prediction for individual cells, and in the current implementation, the mean macromolecular information of a cell can be acquired faster than with the acquisition of individual spectra from a comparable region. It is expected that this approach will have a major impact on the implementation of Raman based cell classification.

Applications of coherent Raman scattering microscopies to clinical and biological studies.

Coherent anti-Stokes Raman scattering (CARS) microscopy and stimulated Raman scattering (SRS) microscopy are two nonlinear optical imaging modalities that are at the frontier of label-free and chemical specific biological and clinical diagnostics. The applications of coherent Raman scattering (CRS) microscopies are multifold, ranging from investigation of basic aspects of cell biology to the label-free detection of pathologies. This review summarizes recent progress of biological and clinical applications of CRS between 2008 and 2014, covering applications such as lipid droplet research, single cell analysis, tissue imaging and multiphoton histopathology of atherosclerosis, myelin sheaths, skin, hair, pharmaceutics, and cancer and surgical margin detection.

Investigating drug induced changes in single, living lymphocytes based on Raman micro-spectroscopy.

Raman spectroscopy is a powerful tool for label-free, single cell characterization. In many reported studies, a Raman spectrum is acquired from a fraction of the cell volume and used as a representative signature of the whole cell to identify and discriminate between cell populations. It has remained an open question whether this is the most suitable approach since the spectra may not truly represent the cell as a whole and critical biochemical information could therefore be lost. To address this question, we developed a line-scan Raman microscope to acquire Raman images of single lymphocytes exposed to the chemotherapeutic drug doxorubicin for 24 to 96 hours. Principal component analysis was able to separate cells based on their drug-exposure times. Difference spectra on the mean data for the different time-points revealed that changes are related to a decrease in mean nucleic acid content and an increase in mean protein and lipid content. Vertex component analysis was used to extract the pure component spectra of lipids, nucleic acids, and proteins. Quantitative analysis of the data revealed that biochemical changes occurred at both local subcellular (i.e. molecular density) and global cellular (i.e. total observable molecular content) levels. However, significant differences between the trends in the local and global changes were observed. While local nucleic acid content decreased with increasing drug exposure time, the total cellular nucleic acid content remained relatively constant. For protein, local content remained relatively constant for all exposure times while the total protein content in the cell increased ∼3 fold. Lipid content in the entire cell increased ∼5 fold, compared to a smaller increase in lipid at the local level. These results show that valuable information about the biochemical changes throughout the entire cell can be missed if only Raman spectra of localized cell regions are used. These findings are expected to have a major impact on the future development of Raman spectroscopy for cytometry applications.

A novel mouse model of nonalcoholic steatohepatitis with significant insulin resistance.

Currently available models insufficiently reflect the pathogenic alternation of nonalcoholic steatohepatitis\NASH), such as insulin resistance. The present study aimed to characterize a novel NASH model caused by feeding the diet containing conjugated linoleic acid (CLA). In this study, mice were fed a control diet or the diet containing 0.5% CLA for 8 weeks. The insulin tolerance test (ITT) and homeostasis model assessment of insulin resistance (HOMA-IR) were used to determine the extent of insulin resistance. Liver lipotoxicity and inflammation were assessed by endoplasmic reticulum (ER) stress, autolipophagy, recruitment of Kupffer cells and hepatic stellate cell (HSC) activation. We found that liver weight was markedly increased, and histopathological examination showed marked macrosteatosis with focal hepatocellular death through apoptosis, and mild pericellular fibrosis with Kupffer cell recruitment and HSC activation, as well as light chain IIIß-positive cells and enhanced ER stress in mice fed the CLA-containing diet. Enhanced synthesis and reduced ß-oxidation of fatty acids resulted in their accumulation and lipotoxicity in hepatocytes. A biophotonic technology revealed lipid droplet accumulation in the liver from mice fed the CLA-containing diet, and Raman spectroscopic analysis indicated that these lipid droplets predominantly contained saturated fatty acids. Elevated fasting insulin levels, abnormal ITT and HOMA-IR confirmed the marked insulin resistance in these mice. Decreased phosphorylation of the insulin-signaling molecule Akt was partially responsible for the significant insulin resistance. In conclusion, Mice fed the diet containing CLA-developed steatohepatitis with marked insulin resistance, which is similar to the characteristics observed in NASH patients. The further characterization of this model would be particularly useful for revealing the critical role of insulin resistance in NASH development in conditions such as metabolic syndrome, diabetes and obesity.

Coherent anti-Stokes emission from gold nanorods and its potential for imaging applications.

We used coherent anti-Stokes scattering (CAS) to characterize individual gold nanorods (GNRs) and GNR aggregates. By creating samples with different densities of GNRs on silicon wafer substrates, we were able to determine surface coverage by scanning electron microscopy (SEM) and then correlate the coverage to the CAS intensities of the samples. The observed CAS signal intensity was quadratically dependent on the number of particles. We also examined the CAS signal as a function of the excitation polarization and found that the strongest signals in regularly oriented GNRs were observed when the beam polarization was aligned with the longitudinal axis of the GNRs. Irregularly oriented GNRs exhibited a different scattering pattern to that observed for regularly oriented GNRs. The polarization-dependent scattering from oriented GNRs showed cos(6)(θ) behavior. By imaging nanoscale-sized GNR patterns using CAS and evaluating the results with SEM, we show that CAS can be used for efficient, label-free imaging of nanoscale metallic particles.