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BackgroundHeart failure (HF) is a healthcare problem burdening patients, care teams, and health care systems. A relentless, downward spiral of decompensation, hospital admission, and functional deterioration is challenging to break, partly because of the lack of an objective, inexpensive tool to aid the clinician’s physical examination. We studied performance of a shortwave infrared (SWIR) molecular chemical imaging (MCI) tool to measure relative tissue congestion (TC) in HF patients’ shins, compared to MRI Dixon sequence TC measurements as ground truth.MethodsForty-seven (47) subjects underwent paired SWIR MCI and MRI measurements of their lower extremities. Thirty-six (36) subjects were hospitalized with decompensated HF while 11 healthy outpatients served as controls. A partial least squares (PLS) regression model was trained to ingest the SWIR MCI spectra and produce a CardioVerification Index (CVI) that mirrored MRI measurements.ResultsThe SWIR MCI model reflected MRI TC measurements accurately for all subjects with a 0.743 linear correlation coefficient. Surprisingly, the MRI results identified a significant fraction of non-HF subjects with elevated TC levels, so a sub-analysis was performed on “Low TC” subjects with low and undetectable levels of extremity edema. This subpopulation’s linear correlation between MRI and CVI was 0.674. A logistic classifier model differentiated HF from non-HF subjects; the area under the receiver operating characteristic curves was 0.906 for the entire subject group and 0.821 for the Low TC subpopulation.ConclusionSWIR MCI techniques can be used in a TC-measuring tool that replicates MRI TC measurements. Clinicians could use such tools to help guide therapy for HF patients during in-hospital management of acute HF decompensation and for outpatient monitoring. SWIR MCI’s ability to identify elevated TC in otherwise normal subjects may also meet the unmet need for a novel, widely applicable HF screening tool.

Introduction Colorectal cancer (CRC) is the third most common cancer in the U.S. Early detection of CRC can substantially increase survival rates. Test compliance may be improved by offering a blood-based test option. Methods Endoscopy II trial specimens were tested for AFP, CA19-9, CEA, hs-CRP, CyFra 21-1, Ferritin, Galectin-3, and TIMP-1 levels. These biomarkers, as well as patient demographic information (e.g., age, gender), were included in algorithm development. Six statistical methods were utilized to develop algorithms that would discriminate cancer vs. noncancers. Statistical methods included logistic regression, adaptive index modeling, partial least-squares discriminant analysis, feature vector (weighted and unweighted), and random forest. The performance of these algorithms was compared against benchmark criteria established for stool-based tests. Results Using several statistical methods, the presence of CRC and high-risk adenomas was detected with an AUCs of at least 0.65–0.76, with a few of models approaching the stool-based tests benchmark performance. Further, common markers were utilized across the different statistical techniques, with model complexities ranging from 3 to 9 markers. Conclusions Predictive models identified subjects with CRC and high-risk adenomas with the similar levels of statistical accuracy. Clinical performance differences were minimal across the statistical techniques, although the intuitive interpretations, model complexity, clinical adoption and implementation varied.

Significance: Peripheral pitting edema is a clinician-administered measure for grading edema. Peripheral edema is graded 0, 1 + , 2 + , 3 + , or 4 + , but subjectivity is a major limitation of this technique. A pilot clinical study for short-wave infrared (SWIR) molecular chemical imaging (MCI) effectiveness as an objective, non-contact quantitative peripheral edema measure is underway. Aim: We explore if SWIR MCI can differentiate populations with and without peripheral edema. Further, we evaluate the technology for correctly stratifying subjects with peripheral edema. Approach: SWIR MCI of shins from healthy subjects and heart failure (HF) patients was performed. Partial least squares discriminant analysis (PLS-DA) was used to discriminate the two populations. PLS regression (PLSR) was applied to assess the ability of MCI to grade edema. Results: Average spectra from edema exhibited higher water absorption than non-edema spectra. SWIR MCI differentiated healthy volunteers from a population representing all pitting edema grades with 97.1% accuracy (N = 103 shins). Additionally, SWIR MCI correctly classified shin pitting edema levels in patients with 81.6% accuracy. Conclusions: Our study successfully achieved the two primary endpoints. Application of SWIR MCI to monitor patients while actively receiving HF treatment is necessary to validate SWIR MCI as an HF monitoring technology.

Heart failure (HF) has a significant impact on patient outcomes and health care costs. Objective monitoring of pitting edema level of a HF patient may help clinicians reduce the volume of patient re-admissions. To address this, ChemImage is developing a Molecular Chemical Imaging (MCI) device for noninvasive measurement of peripheral edema level in HF patients. In an initial clinical study, edema grade was predicted in HF patients with 86% accuracy. Results from a follow-up clinical trial demonstrating the capability of MCI to monitor changes in a HF patient’s peripheral edema over time during the course of treatment will be presented.

The smuggling of drug into correctional facilities through the mail is a major concern. ChemImage has developed the VeroVisionTM mail screener system, which highlights drugs from background based on score imagery computed from selected wavelengths based on the chemical signatures. More recently, sophisticated techniques to hide drugs by dissolution into paper are being used. We introduce a combined heterogeneous anomaly detection with a deep learning classifier. Anomaly detection initially extracts suspect stain patterns. A You Only Look Once (YOLO) based classifier then classifies anomalies as drug or non-drug stain patterns. We report its first successful detection on a limited set of meth samples, with 87.4% probability of detection (PD) and 7.0% probability of false alarm (PFA). The results show that widefield, multispectral short-field infrared (SWIR) imaging can allow for dissolved concealed drug screening of mail which has benefits for mail inspection efficiency and accuracy.

Explosive, chemical and narcotic materials, when in the wrong hands, pose an immediate threat to public health and safety. As the nature of these threats become more pervasive and lethal to innocent bystanders and unsuspecting military and law enforcement authorities, there is a growing demand for rapid and effective detection of materials in real-time with a high degree of autonomy and portability at safe distances. In an effort to address this need, ChemImage has been developing novel, adaptable, handheld, short-wave infrared (SWIR) molecular chemical imaging systems for real-time analysis of complex environments, including for detection of hazardous materials (e.g., explosives, chemical warfare agents, drugs of abuse). At the heart of this sensor is the Conformal Filter (CF), which is a liquid crystal based tunable filter (LCTF) that transmits multi-band waveforms that mimic the functionality of a discriminant vector for classification of target threats amongst background clutter. Real-time detection (≥10 detection fps) is achieved by operating two CFs in tandem within a dual polarization (DP) system, allowing for simultaneous acquisition of the compressed hyperspectral imaging data. This paper will focus on the development, characterization and testing results of a prototype handheld DP-CF sensor. Details of the autonomous, low size, weight and power (SWaP) sensor and applications of the technology to address realworld detection challenges including High Throughput Mail Screening (HTMS) and Chemical Warfare Agent (CWA) surveying and mapping will be discussed.

INTRODUCTION AND OBJECTIVE:Visualization and detection of tumors during extirpative surgeries can be challenging. Currently, there is no intraoperative imaging device to detect kidney tumors and de...

Significance: A key risk faced by oncological surgeons continues to be complete removal of tumor. Currently, there is no intraoperative imaging device to detect kidney tumors during excision. Aim: We are evaluating molecular chemical imaging (MCI) as a technology for real-time tumor detection and margin assessment during tumor removal surgeries. Approach: In exploratory studies, we evaluate visible near infrared (Vis-NIR) MCI for differentiating tumor from adjacent tissue in ex vivo human kidney specimens, and in anaesthetized mice with breast or lung tumor xenografts. Differentiation of tumor from nontumor tissues is made possible with diffuse reflectance spectroscopic signatures and hyperspectral imaging technology. Tumor detection is achieved by score image generation to localize the tumor, followed by application of computer vision algorithms to define tumor border. Results: Performance of a partial least squares discriminant analysis (PLS-DA) model for kidney tumor in a 22-patient study is 0.96 for area under the receiver operating characteristic curve. A PLS-DA model for in vivo breast and lung tumor xenografts performs with 100% sensitivity, 83% specificity, and 89% accuracy. Conclusion: Detection of cancer in surgically resected human kidney tissues is demonstrated ex vivo with Vis-NIR MCI, and in vivo on mice with breast or lung xenografts.

As the nature of explosive, chemical and narcotic threats become more pervasive and lethal to innocent bystanders and unsuspecting military and law enforcement authorities, there is a growing demand for rapid and effective detection of materials in real-time with a high degree of autonomy at safe distances. In an effort to address this need, ChemImage has been developing novel, adaptable, short-wave infrared (SWIR) molecular chemical imaging systems for real-time analysis of complex environments, including for detection of hazardous materials (e.g., explosives, chemical warfare agents, drugs of abuse). At the heart of these systems is the Conformal Filter (CF), which is a liquid crystal (LC)-based tunable filter that transmits multi-band waveforms. Building on concepts of multivariate optical computing, the CF is tuned electro-optically and dynamically to mimic the functionality of a discriminant vector for classification. The resulting integrated detector response approximates the detection response of conventional hyperspectral imaging with only two discrete measurements instead of hundreds to thousands. Real-time detection is achieved by operating two CFs in tandem within a dual polarization (DP) system, which exploits the polarization sensitivity of the LC filters and allows for simultaneous acquisition of the compressed hyperspectral imagery. This paper will discuss the development, characterization, and test results of a prototype, handheld CF sensor, with a focus on its application to explosives, chemical and narcotic threat detection.

INTRODUCTION AND OBJECTIVES:Visualization of critical structures during surgery can be challenging, and misidentification can lead to iatrogenic injuries. Augmentation of a surgeon's ability to dis...

Heart failure (HF) occurs when the heart is unable to pump enough blood to meet blood and oxygen requirements and is among the most common causes for hospitalization in the United States. A retrospective analysis determined that 22% of HF patients are readmitted within 30 days of release from the hospital, and the costs for readmission are substantial. Measuring the severity of peripheral edema is one method for monitoring the treatment of a HF patient. Pitting peripheral edema is a subjective measure administered by clinicians who create an indentation mid-tibia and observe depth and time to resolve the indentation. The results are graded 0, 1, 2, 3 or 4, and this information is used in the patient treatment plan. ChemImage is engaged in a clinical study to determine whether Molecular Chemical Imaging (MCI) in the short wave infrared (SWIR) spectral region can provide an objective measure of peripheral edema in HF patients. In this paper, the performance of SWIR MCI for discriminating between healthy volunteers and HF patients with high grade pitting edema will be presented. This technology may provide a non-invasive methodology for quantitative peripheral edema measurement. As the technology matures, it is envisioned patient self-monitoring, with wireless transmission of edema levels while at home, can aid clinicians in monitoring HF patients for necessary treatment changes remotely, to improve patient outcomes, and ultimately, reduce HF hospital readmission rates.

Improved patient outcomes highlight the need to avoid errors in surgery. Molecular Chemical Imaging (MCI) aids in identifying critical structures without reagents and in vivo results are presented for a range of surgical applications.

Hyperspectral imaging (HSI) systems can provide detection and identification of a variety of targets in the presence of complex backgrounds. However, current generation sensors are typically large, costly to field, do not usually operate in real time and have limited sensitivity and specificity. Despite these shortcomings, HSI-based intelligence has proven to be a valuable tool, thus resulting in increased demand for this type of technology. By moving the next generation of HSI technology into a more adaptive configuration, and a smaller and more cost effective form factor, HSI technologies can help maintain a competitive advantage for the U.S. armed forces as well as local, state and federal law enforcement agencies. Operating near the physical limits of HSI system capability is often necessary and very challenging, but is often enabled by rigorous modeling of detection performance. Specific performance envelopes we consistently strive to improve include: operating under low signal to background conditions; at higher and higher frame rates; and under less than ideal motion control scenarios. An adaptable, low cost, low footprint, standoff sensor architecture we have been maturing includes the use of conformal liquid crystal tunable filters (LCTFs). These Conformal Filters (CFs) are electro-optically tunable, multivariate HSI spectrometers that, when combined with Dual Polarization (DP) optics, produce optimized spectral passbands on demand, which can readily be reconfigured, to discriminate targets from complex backgrounds in real-time. With DARPA support, ChemImage Sensor Systems (CISS™) in collaboration with Research Triangle Institute (RTI) International are developing a novel, real-time, adaptable, compressive sensing short-wave infrared (SWIR) hyperspectral imaging technology called the Reconfigurable Conformal Imaging Sensor (RCIS) based on DP-CF technology. RCIS will address many shortcomings of current generation systems and offer improvements in operational agility and detection performance, while addressing sensor weight, form factor and cost needs. This paper discusses recent test and performance modeling results of a RCIS breadboard apparatus.

A need exists for effective, real-time detection of chemical, explosive and illicit drug threats. ChemImage Sensor Systems has developed, validated and fielded a variety of hyperspectral imaging based sensors to address this need.

Hyperspectral imaging (HSI) systems can provide sensitive and specific detection and identification of high value targets in the presence of complex backgrounds. However, current generation sensors are typically large and costly to field, and do not usually operate in real-time. Sensors that are capable of real-time operation have to compromise on the number of spectral bands, image definition, and/or the number of targets being detected. Additionally, these systems command a high cost and are typically designed and configured for specific mission profiles, making them unable to adapt to multiple threats within often rapidly evolving and dynamic missions. Despite these shortcomings, HSI-based sensors have proven to be valuable tools, thus resulting in increased demand for HSI technology. A cost-effective sensor system that can easily and quickly adapt to accomplish significantly different tasks in a changing environment is highly desirable. The capability to detect and identify user-defined targets in complex backgrounds under a range of varying conditions with an easily reconfigured, automated, real-time, portable HSI sensor is a critical need. ChemImage Sensor Systems (CISSTM) is developing a novel real-time, adaptable, compressive sensing short-wave infrared (SWIR) hyperspectral imaging technology called the Reconfigurable Conformal Imaging Sensor (RCIS). RCIS will address many shortcomings of current generation systems and offer improvements in operational agility and detection performance, while addressing sensor weight, form factor and cost needs. This paper discusses the development of the RCIS system, and considers its application in various use scenarios.

Colorectal cancer (CRC) is the third most common cancer in men and women in the United States. Raman Molecular Imaging (RMI) is an effective technique to evaluate human tissue, cells and bodily fluids, including blood serum for disease diagnosis. ChemImage Corporation, in collaboration with clinicians, has been engaged in development of an in vitro diagnostic Raman assay focused on CRC detection. The Raman Assay for Colorectal Cancer (RACC) exploits the high specificity of Raman imaging to distinguish diseased from normal dried blood serum droplets without additional reagents. Pilot Study results from testing of hundreds of biobank patient samples have demonstrated that RACC detects CRC with high sensitivity and specificity. However, expanded clinical trials, which are ongoing, are revealing a host of important preanalytical considerations associated with sample collection, sample storage and stability, sample shipping, sample preparation and sample interferents, which impact detection performance. Results from recent clinical studies will be presented.

Background: Prostate cancer (PCa) is the most common cancer in males and the second leading cause of cancer deaths. One of the most confounding problems faced by urologists is predicting the progression of PCa. Current prognostic tools for PCa rely solely on clinical and pathologic variables that cannot always accurately predict the progression of the disease. More accurate diagnostic tools to aid clinicians and patients to decide the course of treatment, even in the early stage of cancer, have long been sought. In a prospective study, we utilized Raman molecular imaging (RMI) to identify patients at risk for biochemical recurrence following a prostatectomy. RMI is a technology that combines the molecular chemical analysis capability of Raman spectroscopy with high-definition digital image visualization, enabling analysis of the molecular environment of prostate tissue by providing highly specific molecular imaging data. Objective: The aim of this study is to evaluate RMI as a methodology for predicting the outcome of PCa patients following radical prostatectomy. Methods: PCa patients who underwent prostatectomy were prospectively enrolled with informed consent. Surgeries were performed by two practiced surgeons in a single clinical center from 2009–2011, and 60 months’ follow-up time was recorded. Pathology data were reviewed by one genitourinary pathologist. Preoperative and postoperative data (preoperation prostate-specific antigen level [PSA], Nadir PSA, Gleason scores, pathologic stage, biochemical recurrence time) were recorded, and biochemical failure was defined as 2 consecutive increases in postoperative PSA (≥0.2 ng/mL). Patient identifiers were removed. Raman molecular images were collected from unstained prostatectomy tissue sections. Raman spectral data were extracted from epithelial and stromal regions, and multivariate statistical methodologies were applied to these spectra. Partial least squares discriminant analysis (PLS-DA) was employed in conjunction with leave-one-patient-out cross-validation to generate models based on the pathology data and RMI. Results: Initial data analysis was performed on a representative population of 38 PCa patients. In this population the mean (median) age at the time of diagnosis was 60 (61) years; the pathologic stage for 57.9% of the patients was T3 and for 42.1% of the patients T2. Nine patients (23.7%) progressed to biochemical failure in 60 months. Analysis of RMI performed on prostatectomy tissues from these patients indicates that the RMI data are distinguishable between those with biochemical failure (progressors) and those with no evidence of disease (NED). A PLS-DA model comprising 9 progressors and 29 NED patients differentiated between the two tissue classes with 89% sensitivity and 90% specificity, and with an area under the ROC curve of 0.87. In this model, classification accuracy was 90% and the p–value < 0.01. Analysis revealed most notable differentiation between progressors and NEDs when evaluating the epithelium and stroma as separate histologic elements. A PLS-DA model based on epithelial cells from 9 progressors and 10 NEDs discriminated between the two populations with 89% sensitivity and 100% specificity, with AUROC of 0.92 and a p-value < 0.01. A similar model differentiated between the stroma of progressors and NEDs with 100% specificity and 100% sensitivity, and a p-value well below 0.01. Conclusion: RMI is a novel technique that shows promise for identifying patients at risk of progression by visualizing molecular information not seen using other current methods. In Gleason 7 disease, RMI indicates distinctive chemical differences in patients who had biochemical failure postoperatively. This preliminary work lays the foundation for the further study of RMI for evaluating prostate tissue and developing an assay that may impact clinicians and patients with PCa. Citation Format: Arash Samiei, Ralph Miller, Jeffrey Cohen, Heather Gomer, Shona Stewart, Patrick Treado. Prospective study on the use of Raman molecular imaging to determine postoperative oncological outcomes in patients with prostate cancer: Analysis of a single center [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr B079.

This study was conducted to evaluate the feasibility of using Raman chemical imaging (i.e., Raman imaging microspectroscopy) to establish chemical identity, particle size and particle size distribution (PSD) for a representative corticosteroid in aqueous nasal spray suspension formulations.The Raman imaging PSD protocol was validated using polystyrene (PS) microsphere size standards (NIST-traceable). A Raman spectral library was developed for the active and inactive compounds in the formulation. Four nasal sprays formulated with beclomethasone dipropionate (BDP) ranging in size from 1.4 to 8.3 microm were imaged by both Raman and brightfield techniques. The Raman images were then processed to calculate the PSD for each formulation.Within each region examined, active pharmaceutical ingredient (API) particles are unambiguously identified and the total number of those particles, particle size and PSD of API free of excipients and PSD of API particles adhered to other excipients are reported.Good statistical agreement is obtained between the reported and measured sizes of the PS microspheres. BDP particles were clearly distinguishable from those of excipients. Raman chemical imaging (RCI) is able to differentiate between and identify the chemical makeup of multiple components in complex BDP sample and placebo mixtures. The Raman chemical imaging method (coupled Raman and optical imaging) shows promise as a method for characterizing particle size and shape of corticosteroid in aqueous nasal spray suspension formulations. However, rigorous validation of RCI for PSD analysis is incomplete and requires additional research effort. Some specific areas of concern are discussed.

Molecular Chemical Imaging, using liquid crystal tunable filters combined with visible/near-infrared hyperspectral imaging and advanced exploitation algorithms, provides a reagentless detection technique for assessing tumor margins in human tissues.

Electron irradiation during reflection high-energy electron diffraction is shown to affect the growth of ZnSe and ZnMgSe by molecular beam epitaxy. The high-energy electrons produce an electron stimulated desorption effect during growth of ZnSe which primarily affects adsorbed Se. Se desorption rates under electron irradiation are shown to be significantly larger than thermal desorption rates. Electron irradiation also decreases ZnSe growth rates under Zn-rich conditions. The decrease in growth rate can be suppressed by either growth under Se-rich conditions or by using high-index substrate orientations, in this case (211)B. High-energy electron irradiation does not alter composition during the growth of ZnMgSe.

Silicon integrated circuits are fabricated by the creation of complex layered structures. The complexity of these structures provides many opportunities for impurities, improperly annealed dopants, and stress effects to cause device contamination and failure. Nondestructive metrology techniques that rapidly and noninvasively screen for defects and relate silicon device structure to device performance are of value. We describe the first use of a liquid crystal tunable filter (LCTF) Raman chemical imaging microscope to assess the crystallinity of silicon semiconductor integrated circuits in a rapid and nondestructive manner without the need for sample preparation. The instrument has demonstrated lateral spatial resolving power of better than 250 nm and is equipped with a tunable imaging spectrometer having a spectral bandpass of 7.6 cm−1. The instrument rapidly produces high-definition Raman images where each image pixel contains a high-quality Raman spectrum. When combined with powerful processing strategies, the Raman chemical imaging system has demonstrated spectral resolving power of 0.03 cm−1 in a test silicon semiconductor wafer fabricated by using ion implantation. In addition, we have applied Raman chemical imaging for volumetric Raman imaging by analyzing the surface distribution of polycrystalline thin film structures. The approaches described here for the first time are generally applicable to the nondestructive metrology of silicon and compound semiconductor devices.

An integrated analytical approach, which combines elemental [scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM/EDS)] and molecular (Raman) chemical imaging techniques, has been utilized for the characterization of a residual phase of gallium in mixed oxide (MOX) surrogate material. Surrogate MOX materials are comprised of CeO2 in place of PuO2. In real MOX materials, PuO2 is mixed with UO2 as a commercial fuel source. A Ga phase remains in the surrogate sample following reductive heating experiments designed to explore the removal of gallium from weapons-grade plutonium. The SEM/EDS data reveal the concentration of Ga within the grain boundaries of the sample and a distribution of Ce and O throughout the sample matrix. Molecular analysis provided by Raman chemical matrix imaging correlates with the SEM/EDS elemental imaging results. Specifically, the Raman data suggest that the matrix is comprised of CeO2 and grain boundaries are a mixed phase comprised of CeO2 with a form of Ga, most likely a CeGaO3 perovskite phase having a cubic structure.

In the automotive industry, ethylene-propylene rubber (EPR) is mixed with polypropylene (PP) to form a thermoplastic olefin (TPO) for use as car bumpers and fascia. An adhesion promoting primer, chlorinated polyolefin (CPO), is spray coated onto the TPO surface to increase adhesion of the base and clear coat paints to the low surface free energy TPO substrate. The surface morphology of rubber domains within the CPO-coated TPO substrate contributes strongly to the material characteristics, including impact resistance and adhesion properties. However, elastomer-phase analysis is challenging using traditional microanalysis imaging techniques. The authors employ fluorescence and Raman chemical imaging to characterize the TPO architecture in order to better understand the surface properties of coated TPO. Fluorescence imaging makes use of Nile red (NR), a fluorescent solvatochromic dye, solvated in the primer, which is effective in differentiating rubber from polypropylene on the basis of large variations in the fluorescence quantum efficiency. Confocal fluorescence chemical imaging performed on T PO coated with NR-doped CPO shows a thin (2--3 {micro}m) layer of elastomer that has migrated to the TPO surface. Raman chemical imaging is in direct agreement with the fluorescence experiments by measuring the intrinsic vibrational signatures of CPO, EPR, and PP without themore » need for dyes or stains. Raman contrast is enhanced using cosine correlation analysis, a novel multivariate processing technique that provides chemical contrast on the basis of differences in spectral shape.« less

Spatially resolved elemental and molecular information has been obtained for complex inorganic mixed-phase systems, including plutonium-contaminated ash samples, with the use of micro-X-ray fluorescence (MXRF), micro-Raman, and micro-infrared imaging spectroscopies. Approaches for spatially guided analysis and the combination of multispectral data sets to improve assignment of chemical composition are discussed for two heterogeneous materials. This novel integrated experimental approach provides the advantages of a very small sample size and the ability to correlate elemental analysis with molecular functional group analysis for species identification, as well as insight into chemical interactions in complex matrices.

Thermoplastic olefins (TPOs) are an important class of materials in the automotive industry. The surface properties of TPOs tend to prohibit adhesion of paints used to increase the longevity and en...

Apparatus and methods for spatially resolved Raman chemical imaging of breast tissue is disclosed. A region of breast tissue is illuminated with monochromatic light. A spatially organized area of endogenous molecules in the tissue is then detected in the region by detecting a Raman shifted light signal. The Raman shifted light signal is spatially resolved in at least one direction and is thus useful for examining breast tissue, especially to detect malignant tissue.

ChemImage has developed a SWIR Hyperspectral Imaging (HSI) sensor which uses hyperspectral imaging for wide area surveillance and standoff detection of surface residues. Existing detection technologies often require close proximity for sensing or detecting, endangering operators and costly equipment. Furthermore, most of the existing sensors do not support autonomous, real-time, mobile platform based detection of threats. The SWIR HSI sensor provides real-time standoff detection of surface residues. The SWIR HSI sensor provides wide area surveillance and HSI capability enabled by liquid crystal tunable filter technology. Easy-to-use detection software with a simple, intuitive user interface produces automated alarms and real-time display of threat and type. The system has potential to be used for the detection of variety of threats including chemicals and illicit drug substances and allows for easy updates in the field for detection of new hazardous materials. SWIR HSI technology could be used by law enforcement for standoff screening of suspicious locations and vehicles in pursuit of illegal labs or combat engineers to support route-clearance applications- ultimately to save the lives of soldiers and civilians. In this paper, results from a SWIR HSI sensor, which include detection of various materials in bulk form, as well as residue amounts on vehicles, people and other surfaces, will be discussed.

The utility of Hyper Spectral Imaging (HSI) passive chemical detection employing wide field, standoff imaging continues to be advanced in detection applications. With a drive for reduced SWaP (Size, Weight, and Power), increased speed of detection and sensitivity, developing a handheld platform that is robust and user-friendly increases the detection capabilities of the end user. In addition, easy to use handheld detectors could improve the effectiveness of locating and identifying threats while reducing risks to the individual. ChemImage Sensor Systems (CISS) has developed the HSI Aperio™ sensor for real time, wide area surveillance and standoff detection of explosives, chemical threats, and narcotics for use in both government and commercial contexts. Employing liquid crystal tunable filter technology, the HSI system has an intuitive user interface that produces automated detections and real-time display of threats with an end user created library of threat signatures that is easily updated allowing for new hazardous materials. Unlike existing detection technologies that often require close proximity for sensing and so endanger operators and costly equipment, the handheld sensor allows the individual operator to detect threats from a safe distance. Uses of the sensor include locating production facilities of illegal drugs or IEDs by identification of materials on surfaces such as walls, floors, doors, deposits on production tools and residue on individuals. In addition, the sensor can be used for longer-range standoff applications such as hasty checkpoint or vehicle inspection of residue materials on surfaces or bulk material identification. The CISS Aperio™ sensor has faster data collection, faster image processing, and increased detection capability compared to previous sensors.

A Lyot-type liquid crystal tunable filter (LCTF) suitable for high-definition Raman chemical imaging has been developed. The LCTF has been incorporated into an efficient Raman imaging system that provides significant performance advantages relative to any previous approach to Raman microscopy. The LCTF and associated optical path is physically compact, which accommodates integration of the LCTF within an infinity-corrected optical microscope. The LCTF simultaneously provides diffraction-limited spatial resolution and 7.6-cm-1 spectral bandpass across the full free spectral range of the imaging spectrometer. The LCTF Raman microscope successfully integrates, in a facile manner, the utility of optical microscopy and the analytical capabilities of Raman spectroscopy. In this paper the LCTF Raman imaging system is described in detail, as well as results of initial studies of polymer and corrosion product model systems.

The acousto-optic tunable filter (AOTF) is a digitally accessible, compact, solid-state spectrometer that is well suited to high-frequency optical switching and wavelength selection. With injection of a combination of radio-frequency signals into its transducer, the AOTF acts as an electronically controllable, multiplexing spectrometer. The multiplexing AOTF in this study is employed in two distinct fashions. The first of these utilizes the multiplexing AOTF as a matched filter whose intended spectral profile (i.e., bandpass and band symmetry) is controlled almost at will, providing unprecedented flexibility and high throughput. Second, the multiplexing AOTF is employed for the first time as a Hadamard transform spectrometer. In operation, the integrated intensity on the detector measures combinations of the diffracted wavelengths. The light encodement is performed without the use of physical masks and is governed by HT mathematics, which allow efficient recovery of the optical spectrum. Appreciable signal-to-noise enhancement is demonstrated with the HT AOTF spectrometer.

A generally applicable methodology for routine, noninvasive chemical image characterization of materials is described. The methodology is based on Raman imaging microscopy employing a solid-state acoustooptic electronically tunable imaging spectrometer integrated within a laser-excited optical microscope. Multichannel charge-coupled device detection is employed to capture the Raman images. Chemical imaging with electronically tunable filters can be performed automatically under computer control, making analysis of unknowns routine. The Raman chemical imaging system is applied to the visualization of polypropylene/polyurethane blends. Raman chemical imaging is complementary to electron microscopy for polymer blend characterization ; however, Raman imaging does not require as extensive sample preparation. Raman imaging provides images having molecular specificity at the spatial resolution of the optical microscope, without the use of dyes or stains. Chemical image contrast is provided by the intrinsic vibrational signature of the polymer constituents in the blend.

A powerful new mid-infrared spectroscopic chemical imaging technique combining step-scan Fourier transform Michelson interferometry with indium antimonide focal-plane array (FPA) image detection is described. The coupling of an infrared focal-plane array detector to an interferometer provides an instrumental multiplex/multichannel advantage. Specifically, the multiple detector elements enable spectra at all pixels to be collected simultaneously, while the interferometer portion of the system allows all the spectral frequencies to be measured concurrently. With this method of mid-infrared spectroscopic imaging, the fidelity of the generated spectral images is limited only by the number of pixels on the FPA detector, and only several seconds of starting time is required for spectral image acquisition. This novel, high-definition technique represents the future of infrared chemical imaging analysis, a new discipline within the chemical and material sciences, which combines the capability of spectroscopy for molecular analysis with the power of visualization. In particular, chemical imaging is broadly applicable for noninvasive, molecular characterization of heterogeneous materials, since all solid-state materials exhibit chemical nonuniformity that exists either by design or by development during the course of material preparation or fabrication. Imaging, employing Raman and infrared spectroscopy, allows the precise characterization of the chemical composition, domain structure, and chemical architecture of a variety of substances. This information is often crucial to a wide range of activities, extending from the fabrication of new materials to a basic understanding of biological samples. In this study, step-scan imaging principles, instrument design details, and infrared chemical imaging results are presented. Since the prospect of performing high-resolution and high-definition mid-infrared chemical imaging very rapidly has been achieved with the step-scan approach, the implications for the chemical analysis of materials are many and varied.

The past decade has seen an enormous increase in the number and breadth of imaging techniques developed for analysis in many industries, including pharmaceuticals, food, and especially biomedicine. Rather than accept single-dimensional forms of information, users now demand multidimensional assessment of samples. High specificity and the need for little or no sample preparation make Raman imaging a highly attractive analytical technique and provide motivation for continuing advances in its supporting technology and utilization. This review discusses the current tools employed in Raman imaging, the recent advances, and the major applications in this ever-growing analytical field.

Acousto-optic tunable filters (AOTF) and liquid crystal tunable filters (LCTF) are evaluated for their suitability as fluorescence microscopy imaging spectrometers. AOTFs are solid-state birefringent crystals that provide an electronically tunable spectral notch passband in response to an applied acoustic field. LCTFs also provide a notch passband that can be controlled by incorporating liquid crystal waveplate retarders within a Lyot birefringent filter. In this paper, spectroscopic performance and imaging quality are contrasted by evaluation of model systems. Studies include transmission imaging of standard resolution targets, multispectral fluorescence emission imaging of tagged polystyrene microspheres, and immunofluorescence imaging of neurotransmitters within rat-brainstem thin sections. In addition, the first use of LCTFs for Raman microscopy is demonstrated. Raman microscopy is a noninvasive spectral imaging technique that can provide chemically significant image contrast complementary to fluorescence microscopy without the use of stains or tags.

Near-infrared spectroscopy is a sensitive, noninvasive method for chemical analyses, and its integration with imaging technologies represents a potent tool for the study of a wide range of materials. In this communication the use of an indium antimonide (InSb) multichannel imaging detector for near-infrared absorption spectroscopic microscopy is described. In particular, a 128 × 128 pixel InSb staring array camera has been combined with a refractive optical microscope and an acousto-optic tunable filter (AOTF) to display chemically discriminative, spatially resolved, vibrational spectroscopic images of biological and polymeric systems. AOTFs are computer-controlled bandpass filters that provide high speed, random wavelength access, wide spectral coverage, and high spectral resolution. Although AOTFs inherently have a wide range of spectroscopic applications, we apply this technology to NIR absorption microscopy between 1 and 2.5 μm. The spectral interval is well matched to the optical characteristics of both the NIR refractive microscope and the AOTF, thereby providing near-diffraction-limited performance with a practical spatial resolution of 1 to 2 μm. Design principles of this novel instrumentation and representative applications of the technique are presented for various model systems.

Introduction Microscopies based on the vibrational spectrum of a molecule provide perhaps the closest approach to universally applicable, chemically selective contrast generation techniques. Infrared and Raman microscopic imaging both use the technology of light microscopy, although in modified form. The mid-infrared and the near-infrared are both employed for microscopic observation. Raman imaging uses the visible region. Like the underlying spectroscopies, infrared microscopy is more widely practiced than Raman microscopy. And like the underlying spectroscopies, each has its characteristic advantages and drawbacks.

Hyperspectral imaging sensors for the detection of challenging targets in complex environments are maturing. Hyperspectral imaging sensors generate significant volumes of data that need to be reduced to a manageable form on a timescale that’s relevant to its intended use.

A solid-state acousto-optic tunable filter (AOTF) is combined with krypton laser excitation (647 nm), holographic Raman filters, and photon-counting silicon avalanche photodiode (APD) detection to construct a miniaturized Raman spectrometer with no moving parts. The physically compact AOTF and the highly integrated APD provide a rugged, digitally controlled spectrometer of moderate spectral resolution and with a footprint comparable in size to a laboratory notebook. Instrument design details are considered and representative spectra are reported. Potential areas of application for this prototype Raman spectrometer are also discussed.

Raman microspectroscopy is used to probe the age and milieu parameters for suspensions of bacteria for their detection in water backgrounds. No studies have been reported on the fate of Raman signatures over time for biologicals stored in water matrices. A FALCON II Raman Chemical Imaging System (ChemImage, Pittsburgh, PA) and 532 nm laser excitation source acquired the Raman spectra. MATLAB principal components (PC) analysis software was employed for data reduction. Suspensions of Bacillus atrophaeus, Bacillus thuringiensis , and three strains of E. coli (EC) were prepared in distilled and recipe tap water. Aliquots at 5 min, 5 hr, and 1, 2, and 7 days at 25 C were dried on microscope slides in replicate. Adequate spectral differences were observed for all three organism species. Microscope analysis showed that freshly suspended Bacillus spores and EC vegetative cells, in both water matrices, remained as spores after seven days. Agar plate growth procedures showed that the bacteria were still viable even after seven days resting in both water matrices. All three bacterial species were separated based on PC analysis; however, the three EC strains coalesced. The water matrix parameter was inconsistent in its ability to separate the Raman spectra in PC plots of the five bacteria. Within each group, the time parameter poorly separated the bacterial resting suspensions as the aging proceeded. A Mahalanobis linkage distance analysis (dendrogram) for all three species and strains in both water matrices confirmed a random order for all five suspension times.

In this communication, we describe a technique for obtaining high-fidelity Raman images and Raman spectra. The instrumentation provides the ability to rapidly collect large-format images with the number of image pixels limited only by the number of detector elements in the silicon charge-coupled device (CCD). Wavelength selection is achieved with an acousto-optic tunable filter (AOTF), which maintains image fidelity while providing spectral selectivity. Under computer control the AOTF is capable of µs tuning speeds within the operating range of the filter (400–1900 nm). The AOTF is integrated with the CCD and holographic Raman filters to comprise an entirely solid-state Raman imager containing no moving parts. In operation, the AOTF is placed in front of the CCD and tuned over the desired spectral interval. The two-dimensional CCD detector is employed as a true imaging camera, providing a full multichannel advantage over competitive Raman imaging techniques. Images and spectra are presented of a mixture of dipalmitoylphosphatidylcholine (DPPC) and L-asparagine, which serves as a model system for the study of both lipid/peptide and lipid/protein interactions in intact biological materials. The Raman images are collected in only several seconds and indicate the efficacy of this rapid technique for discriminating between multiple components in complex matrices. Additionally, high-quality Raman spectra of the spatially resolved microscopic regions are easily obtained.