Objective determination of peripheral edema in heart failure patients using short-wave infrared molecular chemical imaging.

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.

Visible near infrared reflectance molecular chemical imaging of human ex vivo carcinomas and murine in vivo carcinomas.

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.

Raman imaging.

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.

Raman spectroscopic discrimination of cell response to chemical and physical inactivation.

Raman spectroscopy was applied to study Escherichia coli and Staphylococcus epidermidis cells that were inactivated by different chemicals and stress conditions including starvation and high temperature. E. coli cells exposed to starvation conditions over several days lost viability at the same rate that spectral bands assigned to DNA and RNA bases decreased in intensity. Band intensities correlate with standard plate counts with R(2) = 0.99 and R(2) = 0.97, respectively. Principal components analysis and discriminant analysis multivariate statistical techniques were used to evaluate the spectral data collected. Significant changes were observed in the spectra of treated cells in comparison with their respective controls (samples without treatment). As a result, there was a significant differentiation between viable and non-viable cells (treated and non-treated cells) in the first and second principal component plots for all the treatments. Discriminant analysis was used along with PCA to estimate a classification rate based on viability status of the cells. Non-viable cells were differentiated from viable cells with classification rates that ranged between 60 and 90% for specific treatments (i.e., EDTA-treated cells versus control cells). The classification rate obtained considering all the treatments (non-viable cells) and controls (viable cells) at the same time for each of the species studied was 86%. The classification rate based on species differentiation when all the spectra (viable and non-viable) were used was 87%. These results suggest that Raman spectroscopy is a powerful tool that can be used to evaluate viability and to study metabolic changes in microorganisms. It is a robust method for bacterial identification even when high spectral variations are introduced.

Studying bacterial metabolic states using Raman spectroscopy.

Natural metabolic variability expected during characteristic growth phases in batch cultures of Escherichia coli and Staphylococcus epidermidis were studied by Raman spectroscopy. Spectral changes induced by metabolic changes found in the growth phases (i.e., lag, exponential, stationary, and decay) were identified. Maximum intensity of bands assigned to DNA and RNA bases are seen at the beginning of the exponential phase, when cells are metabolically active, and minimum intensities are seen when cells are decaying. High agreement in spectral variation due to growth phases was seen for all the trials that were performed, four growth cycles for E. coli and two for S. epidermidis. Batch cultures were monitored by standard plate counts to identify all growth phases, including decay. Spectral data were analyzed by principal component analysis (PCA) and discriminant analysis to identify similarities and differences and to estimate a classification performance based on growth phases. For the species evaluated, spectra during decay are grouped closer to each other and separated from lag, exponential, and stationary cells. These results suggest that Raman spectroscopy can be used to study metabolic states in bacteria and in particular cell viability.

Raman spectroscopy and chemical imaging for quantification of filtered waterborne bacteria.

Rapid and reliable assessment of pathogenic microbial contamination in water is critically important. In the present work we evaluated the suitability of Raman Spectroscopy and Chemical Imaging as enumeration techniques for waterborne pathogens. The prominent C-H stretching band observed between 2800-3000 cm(-1) of the spectrum is used for quantification purposes. This band provides the highest intensity of the bacterial-spectrum bands facilitating the detection of low number of microorganisms. The intensity of the Raman response correlates with number of cells present in drops of sample water on aluminum-coated slides. However, concentration of pathogens in drinking and recreational water is low, requiring a concentration step, i.e., filtering. Subsequent evaluation of filtering approaches for water sampling for Raman detection showed significant background signal from alumina and silver membranes that reduces method sensitivity. Samples concentrated by filtration show good correlation between Raman spectroscopy and other quantification methods including turbidity (R(2)=0.92), plate counts (R(2)=0.87) and dry weight (R(2)=0.97). Background interferences did not allow for evaluation of this relationship at low cell concentrations.

Effects of treatment protocols and subcutaneous implantation on bovine pericardium: a Raman spectroscopy study.

Using Raman microspectroscopy, we have studied mineral deposition on bovine pericardia, fixed according to three different protocols and either implanted subcutaneously or not implanted (controls). A lightly carbonated apatitic phosphate mineral, similar to that found in bone tissue, was deposited on the surface of a glutaraldehyde-fixed, implanted pericardium. Implanted pericardia fixed in glutaraldehyde followed by treatment in either an 80% ethanol or a 5% octanol/40% ethanol solution did not mineralize on implantation. Collagen secondary structure changes were observed on glutaraldehyde fixation by monitoring the center of gravity of the amide I envelope. It is proposed that the decrease in the amide I center of gravity frequency for the glutaraldehyde-fixed tissue compared to the nonfixed tissue is due to an increase in nonreducible collagen cross-links (1660 cm(-1)) and a decrease in reducible cross-links (1690 cm(-1)). The amide I center of gravity in the glutaraldehyde/ethanol-fixed pericardium was higher than the glutaraldehyde-fixed tissue center of gravity. This increase in center of gravity could possibly be due to a decrease in hydrogen bonding within the collagen fibrils following the ethanol pretreatment. In addition, we found a secondary structure change to the pericardial collagen after implantation: an increase in the frequency of the center of gravity of amide I is indicative of an increase in cross-links.