Fiber-optic probes enable cancer detection with FTIR spectroscopy

Molecular Fingerprint Detection Using Raman and Infrared Spectroscopy Technologies for Cancer Detection: A Progress Review

Molecular vibrations play a crucial role in physical chemistry and biochemistry, and Raman and infrared spectroscopy are the two most used techniques for vibrational spectroscopy. These techniques provide unique fingerprints of the molecules in a sample, which can be used to identify the chemical bonds, functional groups, and structures of the molecules. In this review article, recent research and development activities for molecular fingerprint detection using Raman and infrared spectroscopy are discussed, with a focus on identifying specific biomolecules and studying the chemical composition of biological samples for cancer diagnosis applications. The working principle and instrumentation of each technique are also discussed for a better understanding of the analytical versatility of vibrational spectroscopy. Raman spectroscopy is an invaluable tool for studying molecules and their interactions, and its use is likely to continue to grow in the future. Research has demonstrated that Raman spectroscopy is capable of accurately diagnosing various types of cancer, making it a valuable alternative to traditional diagnostic methods such as endoscopy. Infrared spectroscopy can provide complementary information to Raman spectroscopy and detect a wide range of biomolecules at low concentrations, even in complex biological samples. The article concludes with a comparison of the techniques and insights into future directions.

Analysis of urine using electronic tongue towards non-invasive cancer diagnosis

Electronic tongues (e-tongues) have been broadly employed in monitoring the quality of food, beverage, cosmetics, and pharmaceutical products, and in diagnosis of diseases, as the e-tongues can discriminate samples of high complexity, reduce interference of the matrix, offer rapid response. Compared to other analytical approaches using expensive and complex instrumentation as well as required sample preparation, the e-tongue is non-destructive, miniaturizable and on-site method with little or no preparation of samples. Even though e-tongues are successfully commercialized, their application in cancer diagnosis from urine samples is underestimated. In this review, we would like to highlight the various analytical techniques such as Raman spectroscopy, infrared spectroscopy, fluorescence spectroscopy, and electrochemical methods (potentiometry and voltammetry) used as e-tongues for urine analysis towards non-invasive cancer diagnosis. Besides, different machine learning approaches, for instance, supervised and unsupervised learning algorithms are introduced to analyze extracted chemical data. Finally, capabilities of e-tongues in distinguishing between patients diagnosed with cancer and healthy controls are highlighted.

Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach

Preclassification of raw infrared spectra has often been neglected in scientific literature. Separating spectra of low spectral quality, due to low signal-to-noise ratio, presence of artifacts, and low analyte presence, is crucial for accurate model development. Furthermore, it is very important for sparse data, where it becomes challenging to visually inspect spectra of different natures. Hence, a preclassification approach to separate infrared spectra for sparse data is needed. In this study, we propose a preclassification approach based on Multiplicative Signal Correction (MSC). The MSC approach was applied on human and the bovine knee cartilage broadband Fourier Transform Infrared (FTIR) spectra and on a sparse data subset comprising of only seven wavelengths. The goal of the preclassification was to separate spectra with analyte-rich signals (i.e., cartilage) from spectra with analyte-poor (and high-matrix) signals (i.e., water). The human datasets 1 and 2 contained 814 and 815 spectra, while the bovine dataset contained 396 spectra. A pure water spectrum was used as a reference spectrum in the MSC approach. A threshold for the root mean square error (RMSE) was used to separate cartilage from water spectra for broadband and the sparse spectral data. Additionally, standard noise-to-ratio and principle component analysis were applied on broadband spectra. The fully automated MSC preclassification approach, using water as reference spectrum, performed as well as the manual visual inspection. Moreover, it enabled not only separation of cartilage from water spectra in broadband spectral datasets, but also in sparse datasets where manual visual inspection cannot be applied.

Recent Advances in Biomedical Photonic Sensors: A Focus on Optical-Fibre-Based Sensing

In this invited review, we provide an overview of the recent advances in biomedical photonic sensors within the last five years. This review is focused on works using optical-fibre technology, employing diverse optical fibres, sensing techniques, and configurations applied in several medical fields. We identified technical innovations and advancements with increased implementations of optical-fibre sensors, multiparameter sensors, and control systems in real applications. Examples of outstanding optical-fibre sensor performances for physical and biochemical parameters are covered, including diverse sensing strategies and fibre-optical probes for integration into medical instruments such as catheters, needles, or endoscopes.

Perspectives on infrared spectroscopic imaging from cancer diagnostics to process analysis

This perspective paper discusses the recent and potential developments in the application of infrared spectroscopic imaging, with a focus on Fourier transform infrared (FTIR) spectroscopic imaging. The current state-of-the-art has been briefly reported, that includes recent trends and advances in applications of FTIR spectroscopic imaging to biomedical systems. Here, some new opportunities for research in the biomedical field, particularly for cancer diagnostics, and also in the engineering field of process analysis; as well as challenges in FTIR spectroscopic imaging are discussed. Current and future prospects that will bring spectroscopic imaging technologies to the frontier of advanced medical diagnostics and to process analytics in engineering applications will be outlined in this opinion paper.

Fiber Probe for Simultaneous Mid-Infrared and Fluorescence Spectroscopic Analysis

A multispectral fiber optic probe has been developed that enables simultaneous analysis of various liquid and solid samples using attenuated total reflection mid-infrared spectroscopy and fluorimetry. The probe design was optimized using ray-tracing simulation of the light propagation. Technical evaluation of the probe has confirmed its output signal quality that was comparable to that of respective probes for single methods. The capability of the probe to deliver complementary chemical information from the same measurement point has been illustrated using model samples of biological tissue. Qualitative analysis of the biological tissue is one of the most important applications of the developed multispectral probe.

Technical Note: Noninvasive mid-IR fiber-optic evanescent wave spectroscopy (FEWS) for early detection of skin cancers

PURPOSE

Melanoma is the most lethal of the three primary skin cancers, including also basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), which are less lethal. The accepted diagnosis process involves manually observing a suspicious lesion through a Dermascope (i.e., a magnifying glass), followed by a biopsy. This process relies on the skill and the experience of a dermatologist. However, to the best of our knowledge, there is no accepted automatic, noninvasive, and rapid method for the early detection of the three types of skin cancer, distinguishing between them and noncancerous lesions, and identifying each of them. It is our aim to develop such a system.

METHODS

We developed a fiber-optic evanescent wave spectroscopy (FEWS) system based on middle infrared (mid-IR) transmitting AgClBr fibers and a Fourier-transform infrared spectrometer (FTIR). We used the system to perform mid-IR spectral measurements on suspicious lesions in 90 patients, before biopsy, in situ, and in real time. The lesions were then biopsied and sent for pathology. The spectra were analyzed and the differences between pathological and healthy tissues were found and correlated.

RESULTS

Five of the lesions measured were identified as melanomas, seven as BCC, and three as SCC. Using mathematical analyses of the spectra of these lesions we were able to tell that all were skin cancers and we found specific and easily identifiable differences between them.

CONCLUSIONS

This FEWS method lends itself to rapid, automatic and noninvasive early detection and characterization of skin cancers. It will be easily implemented in community clinics and has the potential to greatly simplify the diagnosis process.

Identification and Quantitative Determination of Lactate Using Optical Spectroscopy-Towards a Noninvasive Tool for Early Recognition of Sepsis

Uninterrupted monitoring of serum lactate levels is a prerequisite in the critical care of patients prone to sepsis, cardiogenic shock, cardiac arrest, or severe lung disease. Yet there exists no device to continuously measure blood lactate in clinical practice. Optical spectroscopy together with multivariate analysis is proposed as a viable noninvasive tool for estimation of lactate in blood. As an initial step towards this goal, we inspected the plausibility of predicting the concentration of sodium lactate (NaLac) from the UV/visible, near-infrared (NIR), and mid-infrared (MIR) spectra of 37 isotonic phosphate-buffered saline (PBS) samples containing NaLac ranging from 0 to 20 mmol/L. UV/visible (300–800 nm) and NIR (800–2600 nm) spectra of PBS samples were collected using the PerkinElmer Lambda 1050 dual-beam spectrophotometer, while MIR (4000–500 cm⁻¹) spectra were collected using the Spectrum two FTIR spectrometer. Absorption bands in the spectra of all three regions were identified and functional groups were assigned. The concentration of lactate in samples was predicted using the Partial Least-Squares (PLS) regression analysis and leave-one-out cross-validation. The regression analysis showed a correlation coefficient (R²) of 0.926, 0.977, and 0.992 for UV/visible, NIR, and MIR spectra, respectively, between the predicted and reference samples. The RMSECV of UV/visible, NIR, and MIR spectra was 1.59, 0.89, and 0.49 mmol/L, respectively. The results indicate that optical spectroscopy together with multivariate models can achieve a superior technique in assessing lactate concentrations.

Surface roughness-induced absorption acts as an ovarian cancer cells growth sensor-monitor

Uncontrolled growth of ovarian cancer cells is the fifth leading cause of female cancer deaths since most ovarian cancer patients are diagnosed at an advanced stage of metastatic disease. Here, we report on the sensor for monitoring the cancer treatment efficiency in real-time. We measure the optical interaction between the evanescent fields of microfiber and ovarian cancer inter-cellular medium at different treatment stages. Spectral absorption signatures are correlated with optical micrographs and western blot tests. We found that the treatment of tumor cells with induces both cells growth arrest and alter the spectral lines in a dose-dependent manner. These observations are mediated by surface roughness out of silica glass material, form an essential step toward the development of early detection of response to cancer therapy.

Applications of Fourier transform infrared spectroscopy to pharmaceutical preparations

Introduction: Various pharmaceutical preparations are widely used for clinical treatment. Elucidation of the mechanisms of drug release and evaluation of drug efficacy in biological samples are important in drug design and drug quality control.Areas covered: This review classifies recent applications of Fourier transform infrared (FTIR) spectroscopy in the field of medicine to comprehend drug release and diffusion. Drug release is affected by many factors of preparations, such as drug delivery system and microstructure polymorphism. The applications of FTIR imaging and nano-FTIR technique in biological samples lay a foundation for studying drug mechanism in vivo.Expert opinion: FTIR spectroscopy meets the research needs on preparations to understand the processes and mechanisms underlying drug release. The combination of attenuated total reflectance-FTIR imaging and nano-FTIR accompanied by chemometrics is a potent tool to overcome the deficiency of conventional infrared detection. FTIR shows an enormous potential in drug characterization, drug quality control, and bio-sample detection.

Fast and reliable determination of Escherichia coli susceptibility to antibiotics: Infrared microscopy in tandem with machine learning algorithms

Antimicrobial drugs have an important role in controlling bacterial infectious diseases. However, the increasing resistance of bacteria to antibiotics has become a global health care problem. Rapid determination of antimicrobial susceptibility of clinical isolates is often crucial for the optimal antimicrobial therapy. The conventional methods used in medical centers for susceptibility testing are time-consuming (>2 days). Two bacterial culture steps are needed, the first is used to grow the bacteria from urine on agar plates to determine the species of the bacteria (~24 hours). The second culture is used to determine the susceptibility by growing colonies from the first culture for another 24 hours. Here, the main goal is to examine the potential of infrared microscopy combined with multivariate analysis, to reduce the time it takes to identify Escherichia coli susceptibility to antibiotics and to determine the optimum choice of antibiotic to which the bacteria will respond. E coli colonies of the first culture from patients with urinary tract infections (UTI) were examined for the bacterial susceptibility using Fourier-transform infrared (FTIR). Our results show that it is possible to determine the optimum choice of antibiotic with better than 89% sensitivity, in the time span of few minutes, following the first culture.

Rapid infrared mapping for highly accurate automated histology in Barrett's oesophagus

Barrett's oesophagus (BE) is a premalignant condition that can progress to oesophageal adenocarcinoma. Endoscopic surveillance aims to identify potential progression at an early, treatable stage, but generates large numbers of tissue biopsies. Fourier transform infrared (FTIR) mapping was used to develop an automated histology tool for detection of BE and Barrett's neoplasia in tissue biopsies. 22 oesophageal tissue samples were collected from 19 patients. Contiguous frozen tissue sections were taken for pathology review and FTIR imaging. 45 mid-IR images were measured on an Agilent 620 FTIR microscope with an Agilent 670 spectrometer. Each image covering a 140 μm × 140 μm region was measured in 5 minutes, using a 1.1 μm² pixel size and 64 scans per pixel. Principal component fed linear discriminant analysis was used to build classification models based on spectral differences, which were then tested using leave-one-sample-out cross validation. Key biochemical differences were identified by their spectral signatures: high glycogen content was seen in normal squamous (NSQ) tissue, high glycoprotein content was observed in glandular BE tissue, and high DNA content in dysplasia/adenocarcinoma samples. Classification of normal squamous samples versus 'abnormal' samples (any stage of Barrett's) was performed with 100% sensitivity and specificity. Neoplastic Barrett's (dysplasia or adenocarcinoma) was identified with 95.6% sensitivity and 86.4% specificity. Highly accurate pathology classification can be achieved with FTIR measurement of frozen tissue sections in a clinically applicable timeframe.

Amalgam tattoo versus melanocytic neoplasm - Differential diagnosis of dark pigmented oral mucosa lesions using infrared spectroscopy

Background

Dark pigmented lesions of the oral mucosa can represent a major diagnostic challenge. A biopsy is usually required to determine the nature of such intraoral discolorations. This study investigates the potential use of infrared spectroscopy for differential diagnosis of amalgam tattoos versus benign or malignant melanocytic neoplasms.

Materials and methods

For this retrospective study, formalin-fixed paraffin-embedded tissue (FFPE) specimens of dark pigmented lesions concerning the oral mucosa or the lip were investigated using mid infrared spectroscopy. The samples were chosen from patients who had undergone a mucosal biopsy at the University Hospital Innsbruck (Austria) between the years 2000 and 2017. Principal component analysis was used for data exploration. Evaluation was based on the superimposition of the recorded spectra and the corresponding histologic slides.

Results

In total, 22 FFPE specimens were analyzed. Clear differences were found between amalgam and non-amalgam samples. A general weakening of the penetrating infrared radiation allowed for unspecific discrimination between these two classes. An overall accuracy in predicting the correct class of 95.24% was achieved.

Conclusion

Infrared spectroscopy appears to be a suitable technique to differentiate between amalgam tattoos and melanocytic lesions in FFPE samples. It could potentially be applied in vivo, too, serving as a non-invasive diagnostic tool for intraoral dark pigmented lesions.

Pancreatic cancer subtypes: a roadmap for precision medicine

Pancreatic ductal adenocarcinoma (PDAC) is projected to become the second cause of cancer-related deaths by 2020. Although it has traditionally been approached as a disease, accumulated evidences point to the clinical heterogeneity of this disease, which translate into disparity in outcomes among the patients. Much emphasis has been put into patient classification introducing a platform for more tailored therapies. In the last 10 years, there have been important advances in the understanding of the molecular pathogenesis of PDAC, which has culminated with a comprehensive integrated genomic analysis from RNA expression profiles. Bailey et al. defined four subtypes and the different transcriptional networks underlying them. Firstly, we briefly describe and compare different subtyping approaches, which are mostly based on tissue mRNA expression analysis. We propose that these latest approaches to disease classification embrace not only those patients that are surgically resectable (20%), but even patients ineligible for surgery. Such considerations will include possible reclassification of these specific subtypes, enabling more personalized diagnosis and individualized treatment. The ultimate goal of this review is to identify current challenges in this area and summarize current efforts in developing clinical modalities that can effectively identify these subtypes in order to advance Precision Medicine. KEY MESSAGES   • Pancreatic cancer can no longer be considered as one disease.   • The heterogeneity underlying pancreatic cancer patients makes therapeutic options based on one-size-fits-all approach ineffective.   • Identifying patients that could benefit from a specific treatment would help to avoid futile therapy approaches and to improve outcomes and quality of life of those whose long-term survival is unpromising.

IDH1 mutation in human glioma induces chemical alterations that are amenable to optical Raman spectroscopy

INTRODUCTION

Mutations in the isocytrate dehydrogenase 1 (IDH1) gene are early genetic events in glioma pathogenesis and cause profound metabolic changes. Because this genotype is found in virtually every tumor cell, therapies targeting mutant IDH1 protein are being developed. The intraoperative administration of those therapies would require fast technologies for the determination of IDH1 genotype. As of today, there is no such diagnostic test available. Recently, infrared spectroscopy was shown to bridge this gap. Here, we tested Raman spectroscopy for analysis of IDH1 genotype in glioma, which constitutes an alternative contact-free technique with the potential of being applicable in situ.

METHODS

Human glioma samples (n = 36) were obtained during surgery and cryosections were prepared. IDH1 mutations were assessed using DNA sequencing and 100 Raman spectra were obtained for each sample.

RESULTS

Analysis of Raman spectra revealed increased intensities in spectral bands related to DNA in IDH1 mutant glioma while bands assigned to molecular vibrations of lipids were significantly decreased. Moreover, intensities of Raman bands assigned to proteins differed in IDH1 mutant and IDH1 wild-type glioma, suggesting alterations in the protein profile. The selection of five bands (498, 826, 1003, 1174 and 1337 cm^-1) allowed the classification of Raman spectra according to IDH1 genotype with a correct rate of 89%.

CONCLUSION

Raman spectroscopy constitutes a simple, rapid and safe procedure for determination of the IDH1 mutation that shows great promise for clinically relevant in situ diagnostics.

Rapid intra-operative diagnosis of kidney cancer by attenuated total reflection infrared spectroscopy of tissue smears

Herein, a technique to analyze air-dried kidney tissue impression smears by means of attenuated total reflection infrared (ATR-IR) spectroscopy is presented. Spectral tumor markers-absorption bands of glycogen-are identified in the ATR-IR spectra of the kidney tissue smear samples. Thin kidney tissue cryo-sections currently used for IR spectroscopic analysis lack such spectral markers as the sample preparation causes irreversible molecular changes in the tissue. In particular, freeze-thaw cycle results in degradation of the glycogen and reduction or complete dissolution of its content. Supervised spectral classification was applied to the recorded spectra of the smears and the test spectra were classified with a high accuracy of 92% for normal tissue and 94% for tumor tissue, respectively. For further development, we propose that combination of the method with optical fiber ATR probes could potentially be used for rapid real-time intra-operative tissue analysis without interfering with either the established protocols of pathological examination or the ordinary workflow of operating surgeon. Such approach could ensure easier transition of the method to clinical applications where it may complement the results of gold standard histopathology examination and aid in more precise resection of kidney tumors.

Tendinopathy diagnosis and treatment monitoring using attenuated total reflectance-Fourier transform infrared spectroscopy

Tendinopathy, an important sports injury afflicting athletes and general public, is associated with huge economic losses. The currently used diagnostic tests are subjective, show moderate sensitivity and specificity; while treatment failures persist despite advances in therapy. This highlights the need for tendinopathy diagnostic and treatment monitoring tools. This study investigates tendon injury, natural healing and effect of treatment using ATR-FTIR complemented with histopathology. Control (C), injured (I) and treated (T) rat tendons were extracted 3, 7, 14 and 28 days post-injury/treatment, representing phases of healing; and subjected to hematoxylin & eosin staining as well as spectroscopy. While C showed no change, I- and T-related histological changes could be clearly observed in stained sections. ATR-FTIR spectra highlighted the biochemical changes within groups. Multivariate analysis could classify C, I and T with 75%; different days between groups with 84%; and different days within group with 65% efficiency. Results suggest that such analysis can not only identify C, I or T but also different phases of healing. Difference between I and T at different time points also suggest change in rate of healing. Further studies may help develop this technique for clinical diagnosis and treatment monitoring in future.

Compositional analysis of lignocellulosic biomass: conventional methodologies and future outlook

The composition and structural properties of lignocellulosic biomass have significant effects on its downstream conversion to fuels, biomaterials, and building-block chemicals. Specifically, the recalcitrance to modification and compositional variability of lignocellulose make it challenging to optimize and control the conditions under which the conversion takes place. Various characterization protocols have been developed over the past 150 years to elucidate the structural properties and compositional patterns that affect the processing of lignocellulose. Early characterization techniques were developed to estimate the relative digestibility and nutritional value of plant material after ingestion by ruminants and humans alike (e.g. dietary fiber). Over the years, these empirical techniques have evolved into statistical approaches that give a broader and more informative analysis of lignocellulose for conversion processes, to the point where an entire compositional and structural analysis of lignocellulosic biomass can be completed in minutes, rather than weeks. The use of modern spectroscopy and chemometric techniques has shown promise as a rapid and cost effective alternative to traditional empirical techniques. This review serves as an overview of the compositional analysis techniques that have been developed for lignocellulosic biomass in an effort to highlight the motivation and migration towards rapid, accurate, and cost-effective data-driven chemometric methods. These rapid analysis techniques can potentially be used to optimize future biorefinery unit operations, where large quantities of lignocellulose are continually processed into products of high value.

Real-time in vivo cancer diagnosis using Raman spectroscopy

Raman spectroscopy has becoming a practical tool for rapid in vivo tissue diagnosis. This paper provides an overview on the latest development of real-time in vivo Raman systems for cancer detection. Instrumentation, data handling, as well as oncology applications of Raman techniques were covered. Optic fiber probes designs for Raman spectroscopy were discussed. Spectral data pre-processing, feature extraction, and classification between normal/benign and malignant tissues were surveyed. Applications of Raman techniques for clinical diagnosis for different types of cancers, including skin cancer, lung cancer, stomach cancer, oesophageal cancer, colorectal cancer, cervical cancer, and breast cancer, were summarized. Schematic of a real-time Raman spectrometer for skin cancer detection. Without correction, the image captured on CCD camera for a straight entrance slit has a curvature. By arranging the optic fiber array in reverse orientation, the curvature could be effectively corrected.

Computational chemical imaging for cardiovascular pathology: chemical microscopic imaging accurately determines cardiac transplant rejection

Rejection is a common problem after cardiac transplants leading to significant number of adverse events and deaths, particularly in the first year of transplantation. The gold standard to identify rejection is endomyocardial biopsy. This technique is complex, cumbersome and requires a lot of expertise in the correct interpretation of stained biopsy sections. Traditional histopathology cannot be used actively or quickly during cardiac interventions or surgery. Our objective was to develop a stain-less approach using an emerging technology, Fourier transform infrared (FT-IR) spectroscopic imaging to identify different components of cardiac tissue by their chemical and molecular basis aided by computer recognition, rather than by visual examination using optical microscopy. We studied this technique in assessment of cardiac transplant rejection to evaluate efficacy in an example of complex cardiovascular pathology. We recorded data from human cardiac transplant patients’ biopsies, used a Bayesian classification protocol and developed a visualization scheme to observe chemical differences without the need of stains or human supervision. Using receiver operating characteristic curves, we observed probabilities of detection greater than 95% for four out of five histological classes at 10% probability of false alarm at the cellular level while correctly identifying samples with the hallmarks of the immune response in all cases. The efficacy of manual examination can be significantly increased by observing the inherent biochemical changes in tissues, which enables us to achieve greater diagnostic confidence in an automated, label-free manner. We developed a computational pathology system that gives high contrast images and seems superior to traditional staining procedures. This study is a prelude to the development of real time in situ imaging systems, which can assist interventionists and surgeons actively during procedures.

Near-infrared spectroscopy as a diagnostic tool for distinguishing between normal and malignant colorectal tissues

Cancer diagnosis is one of the most important tasks of biomedical research and has become the main objective of medical investigations. The present paper proposed an analytical strategy for distinguishing between normal and malignant colorectal tissues by combining the use of near-infrared (NIR) spectroscopy with chemometrics. The successive projection algorithm-linear discriminant analysis (SPA-LDA) was used to seek a reduced subset of variables/wavenumbers and build a diagnostic model of LDA. For comparison, the partial least squares-discriminant analysis (PLS-DA) based on full-spectrum classification was also used as the reference. Principal component analysis (PCA) was used for a preliminary analysis. A total of 186 spectra from 20 patients with partial colorectal resection were collected and divided into three subsets for training, optimizing, and testing the model. The results showed that, compared to PLS-DA, SPA-LDA provided more parsimonious model using only three wavenumbers/variables (4065, 4173, and 5758 cm⁻¹) to achieve the sensitivity of 84.6%, 92.3%, and 92.3% for the training, validation, and test sets, respectively, and the specificity of 100% for each subset. It indicated that the combination of NIR spectroscopy and SPA-LDA algorithm can serve as a potential tool for distinguishing between normal and malignant colorectal tissues.

Caught in the act: revealing the metastatic process by live imaging

The prognosis of metastatic cancer in patients is poor. Interfering with metastatic spread is therefore important for achieving better survival from cancer. Metastatic disease is established through a series of steps, including breaching of the basement membrane, intravasation and survival in lymphatic or blood vessels, extravasation, and growth at distant sites. Yet, although we know the steps involved in metastasis, the cellular and molecular mechanisms of dissemination and colonization of distant organs are incompletely understood. Here, we review the important insights into the metastatic process that have been gained specifically through the use of imaging technologies in murine, chicken embryo and zebrafish model systems, including high-resolution two-photon microscopy and bioluminescence. We further discuss how imaging technologies are beginning to allow researchers to address the role of regional activation of specific molecular pathways in the metastatic process. These technologies are shedding light, literally, on almost every step of the metastatic process, particularly with regards to the dynamics and plasticity of the disseminating cancer cells and the active participation of the microenvironment in the processes.

Optical spectroscopic methods for intraoperative diagnosis

Molecular analytical methods are increasingly needed for a quick and reliable analysis of tissue in an operating room to provide more information during operations. In this Trends article, we highlight the current state and the developments of optical spectroscopic methods as intra operative tools. The clinical problem and challenges are illustrated on the example of brain tumor surgery. While fluorescence microscopy is already used, vibrational spectroscopy techniques will complement the standard method for brain tissue diagnostics. New portable instruments are currently available and can be stationed in the operating room for quick evaluation of tissue. The promise and limitations of fluorescence and vibrational spectroscopy as intraoperative tools are surveyed in this report.

Fiber-optic Fourier transform infrared spectroscopy for remote label-free sensing of medical device surface contamination

As a potential major source of biochemical contamination, medical device surfaces are of critical safety concerns in the clinical practice and public health. The development of innovative sensing methods for accurate and real-time detection of medical device surface contamination is essential to protect patients from high risk infection. In this paper, we demonstrate an alternative fiber-optic Fourier Transform Infrared (FTIR) spectroscopy based sensing approach for remote, non-contact, and label-free detection of biochemical contaminants in the mid-infrared (mid-IR) region. The sensing probe is designed using mid-IR hollow fibers and FTIR measurements are carried out in reflection mode. Bovine Serum Albumin (BSA) and bacterial endotoxin of different concentrations under thoroughly dry condition are used to evaluate the detection sensitivity. The devised system can identify ≤0.0025% (≤4 × 10(11) molecules) BSA and 0.5% (0.5 EU/ml) endotoxin concentration. The developed sensing approach may be applied to detect various pathogens that pose public health threats.

Infrared spectroscopic studies of cells and tissues: triple helix proteins as a potential biomarker for tumors

In this work, the infrared (IR) spectra of living neural cells in suspension, native brain tissue, and native brain tumor tissue were investigated. Methods were developed to overcome the strong IR signal of liquid water so that the signal from the cellular biochemicals could be seen. Measurements could be performed during surgeries, within minutes after resection. Comparison between normal tissue, different cell lineages in suspension, and tumors allowed preliminary assignments of IR bands to be made. The most dramatic difference between tissues and cells was found to be in weaker IR absorbances usually assigned to the triple helix of collagens. Triple helix domains are common in larger structural proteins, and are typically found in the extracellular matrix (ECM) of tissues. An algorithm to correct offsets and calculate the band heights and positions of these bands was developed, so the variance between identical measurements could be assessed. The initial results indicate the triple helix signal is surprisingly consistent between different individuals, and is altered in tumor tissues. Taken together, these preliminary investigations indicate this triple helix signal may be a reliable biomarker for a tumor-like microenvironment. Thus, this signal has potential to aid in the intra-operational delineation of brain tumor borders.

Distinction of leukemia patients' and healthy persons' serum using FTIR spectroscopy

In this paper, FTIR spectroscopy was applied to compare the serum from leukemia patients with the serum from healthy persons. IR spectra of leukemia patients' serum were similar with IR spectra of healthy persons' serum, and they were all made up of proteins, lipids and nucleic acids, etc. In order to identify leukemia patients' serum and healthy persons' serum, the H1075/H1542, H1045/H1467, H2959/H2931 ratios were measured. The H2959/H2931 ratio had the highest significant difference among these ratios and might be a useful factor for identifying leukemia patients' serum and healthy persons' serum. Furthermore, from curve fitting, the RNA/DNA (A1115/A1028) ratios were observed to be lower in leukemia patients' serum than those in healthy persons' serum. The results indicated FTIR spectroscopic study of serum might be a useful tool in the field of leukemia research and diagnosis.

Infrared fiber optic probe evaluation of degenerative cartilage correlates to histological grading

BACKGROUND

Osteoarthritis (OA), a degenerative cartilage disease, results in alterations of the chemical and structural properties of tissue. Arthroscopic evaluation of full-depth tissue composition is limited and would require tissue harvesting, which is inappropriate in daily routine. Fourier transform infrared (FT-IR) spectroscopy is a modality based on molecular vibrations of matrix components that can be used in conjunction with fiber optics to acquire quantitative compositional data from the cartilage matrix.

PURPOSE

To develop a model based on infrared spectra of articular cartilage to predict the histological Mankin score as an indicator of tissue quality.

STUDY DESIGN

Comparative laboratory study.

METHODS

Infrared fiber optic probe (IFOP) spectra were collected from nearly normal and more degraded regions of tibial plateau articular cartilage harvested during knee arthroplasty (N = 61). Each region was graded using a modified Mankin score. A multivariate partial least squares algorithm using second-derivative spectra was developed to predict the histological modified Mankin score.

RESULTS

The partial least squares model derived from IFOP spectra predicted the modified Mankin score with a prediction error of approximately 1.4, which resulted in approximately 72% of the Mankin-scored tissues being predicted correctly and 96% being predicted within 1 grade of their true score.

CONCLUSION

These data demonstrate that IFOP spectral parameters correlate with histological tissue grade and can be used to provide information on tissue composition.

CLINICAL RELEVANCE

Infrared fiber optic probe studies have significant potential for the evaluation of cartilage tissue quality without the need for tissue harvest. Combined with arthroscopy, IFOP analysis could facilitate the definition of tissue margins in debridement procedures.

Habits with killer instincts: in vivo analysis on the severity of oral mucosal alterations using autofluorescence spectroscopy

Oral habits like chewing and smoking are main causes of oral cancer, which has a higher mortality rate than many other cancer forms. Currently, the long term survival rate of oral cancer is less than 50%, as a majority of cases are detected very late. The clinician's main challenge is to differentiate among a multitude of red, white, or ulcerated lesions. Hence, new noninvasive, reliable, and fast techniques for the discrimination of oral cavity disorders are to be developed. This study includes autofluorescence spectroscopic screening of normal volunteers with and without lifestyle oral habits and patients with oral submucous fibrosis (OSF). The spectra from different sites of habitués, non-habitués, and OSF patients were analyzed using the intensity ratio, redox ratio, and linear discriminant analysis (LDA). The spectral disparities among these groups are well demonstrated in the emission regions of collagen and Flavin adenine dinucleotide. We observed that LDA gives better efficiency of classification than the intensity ratio technique. Even the differentiation of habitués and non-habitués could be well established with LDA. The study concludes that the clinical application of autofluorescence spectroscopy along with LDA, yields spontaneous screening among individuals, facilitating better patient management for clinicians and better quality of life for patients.

Spectral signatures of colonic malignancies in the mid-infrared region: from basic research to clinical applicability

The process of carcinogenesis in the colon progresses through several overlapping stages, making the evaluation process challenging, as well as subjective. Owing to the complexity of colonic tissues and the search for a technique that is rapid and foolproof for precise grading and evaluation of biopsies, many spectroscopic techniques have been evaluated in the past few decades for their efficiency and clinical compatibility. Fourier-transform infrared spectroscopy, being quantitative and objective, has the capacity for automation and relevance to cancer diagnosis. This article highlights investigations on the application of Fourier-transform infrared spectroscopy (particularly microscopy) in colon cancer diagnosis and parallel developments in data analysis techniques for the characterization of spectral signatures of malignant tissues in the colon.