Arthritis diagnosis based upon the near-infrared spectrum of synovial fluid

Comparative profiling of serum biomarkers and ATR-FTIR spectroscopy for differential diagnosis of patients with rheumatoid and psoriatic arthritis - a pilot study

BACKGROUND

Rheumatoid arthritis (RA) and psoriatic arthritis (PsA) are chronic inflammatory diseases in which innate and adaptive responses of the immune system are induced. RA and PsA have complex signaling pathways. Despite the differences in their clinical presentation, there is a great demand for fast and accurate diagnosis of diseases to implement treatment and plan an individual therapeutic strategy quickly. In this report, we present the results of differential diagnosis of patients with RA and PsA and healthy subjects (C, control group), allowing for reliable differentiation of groups of rheumatoid patients based on biochemical parameters, attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectra, and combined data sets.

MATERIALS AND METHODS

Biochemical analyses, ELISA (enzyme-linked immunosorbent assays), and multiplex assays were conducted for blood sera from patients with RA (n = 32), patients with PsA (n = 28), and the control group (n = 18). ATR-FTIR spectra were collected for lyophilized sera.

RESULTS

The combination of six biochemical parameters (WBC, ESR, RF, CRP, HCC-4/CCL16, and HMGB1/HMGB) allowed the development of the partial least squares discriminant analysis (PLS-DA) model with an overall accuracy (OA) of 80% for test samples. The best separation between RA, PsA, and the control group was obtained utilizing spectral data. Using the interval PLS algorithm (iPLS) specific spectral ranges were selected and a classifier characterized by OA value for test set equal to 88% was obtained. This parameter, for the hybrid PLS-DA model constructed using selected biochemical parameters and a significantly reduced number of spectral variables, reached the level of 84%.

CONCLUSIONS

PLS-DA models developed on the basis of spectral data enable effective differentiation of patients with RA, patients with PsA, and healthy subjects. They appeared to be insensitive to existing inflammation processes which opens interesting perspectives for new diagnostic tests and algorithms for identification of patients with RA and PsA.

Infrared Spectroscopy of Synovial Fluid Shows Accuracy as an Early Biomarker in an Equine Model of Traumatic Osteoarthritis

Osteoarthritis is a leading cause of lameness and joint disease in horses. A simple, economical, and accurate diagnostic test is required for routine screening for OA. This study aimed to evaluate infrared (IR)-based synovial fluid biomarker profiling to detect early changes associated with a traumatically induced model of equine carpal osteoarthritis (OA). Unilateral carpal OA was induced arthroscopically in 9 of 17 healthy thoroughbred fillies; the remainder served as Sham-operated controls. The median age of both groups was 2 years. Synovial fluid (SF) was obtained before surgical induction of OA (Day 0) and weekly until Day 63. IR absorbance spectra were acquired from dried SF films. Following spectral pre-processing, predictive models using random forests were used to differentiate OA, Sham, and Control samples. The accuracy for distinguishing between OA and any other joint group was 80%. The classification accuracy by sampling day was 87%. For paired classification tasks, the accuracies by joint were 75% for OA vs. OA Control and 70% for OA vs. Sham. The accuracy for separating horses by group (OA vs. Sham) was 68%. In conclusion, SF IR spectroscopy accurately discriminates traumatically induced OA joints from controls.

Resolving the Near-Infrared Spectrum of Articular Cartilage

OBJECTIVE

Spectroscopic techniques, such as near-infrared (NIR) spectroscopy, are gaining significant research interest for characterizing connective tissues, particularly articular cartilage, because there is still a largely unmet need for rapid, accurate and objective methods for assessing tissue integrity in real-time during arthroscopic surgery. This study aims to identify the NIR spectral range that is optimal for characterizing cartilage integrity by (a) identifying the contribution of its major constituents (collagen and proteoglycans) to its overall spectrum using proxy constituent models and (b) determining constituent-specific spectral contributions that can be used for assessment of cartilage in its physiological state.

DESIGN

The NIR spectra of cartilage matrix constituent models were measured and compared with specific molecular components of organic compounds in the NIR spectral range in order to identify their bands and molecular assignments. To verify the identified bands, spectra of the model compounds were compared with those of native cartilage. Since water obscures some bands in the NIR range, spectral measurements of the native cartilage were conducted under conditions of decreasing water content to amplify features of the solid matrix components. The identified spectral bands were then compared and examined in the resulting spectra of the intact cartilage samples.

RESULTS

As water was progressively eliminated from cartilage, the specific contribution of the different matrix components was observed to correspond with those identified from the proxy cartilage component models.

CONCLUSION

Spectral peaks in the regions 5500 to 6250 cm-1 and 8100 to 8600 cm-1 were identified to be effective for characterizing cartilage proteoglycan and collagen contents, respectively.

Vibrational Spectroscopy in Assessment of Early Osteoarthritis-A Narrative Review

Osteoarthritis (OA) is a degenerative disease, and there is currently no effective medicine to cure it. Early prevention and treatment can effectively reduce the pain of OA patients and save costs. Therefore, it is necessary to diagnose OA at an early stage. There are various diagnostic methods for OA, but the methods applied to early diagnosis are limited. Ordinary optical diagnosis is confined to the surface, while laboratory tests, such as rheumatoid factor inspection and physical arthritis checks, are too trivial or time-consuming. Evidently, there is an urgent need to develop a rapid nondestructive detection method for the early diagnosis of OA. Vibrational spectroscopy is a rapid and nondestructive technique that has attracted much attention. In this review, near-infrared (NIR), infrared, (IR) and Raman spectroscopy were introduced to show their potential in early OA diagnosis. The basic principles were discussed first, and then the research progress to date was discussed, as well as its limitations and the direction of development. Finally, all methods were compared, and vibrational spectroscopy was demonstrated that it could be used as a promising tool for early OA diagnosis. This review provides theoretical support for the application and development of vibrational spectroscopy technology in OA diagnosis, providing a new strategy for the nondestructive and rapid diagnosis of arthritis and promoting the development and clinical application of a component-based molecular spectrum detection technology.

Distinguishing active from quiescent disease in ANCA-associated vasculitis using attenuated total reflection Fourier-transform infrared spectroscopy

The current lack of a reliable biomarker of disease activity in anti-neutrophil cytoplasmic autoantibody (ANCA) associated vasculitis poses a significant clinical unmet need when determining relapsing or persisting disease. In this study, we demonstrate for the first time that attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy offers a novel and functional candidate biomarker, distinguishing active from quiescent disease with a high degree of accuracy. Paired blood and urine samples were collected within a single UK centre from patients with active disease, disease remission, disease controls and healthy controls. Three key biofluids were evaluated; plasma, serum and urine, with subsequent chemometric analysis and blind predictive model validation. Spectrochemical interrogation proved plasma to be the most conducive biofluid, with excellent separation between the two categories on PC2 direction (AUC 0.901) and 100% sensitivity (F-score 92.3%) for disease remission and 85.7% specificity (F-score 92.3%) for active disease on blind predictive modelling. This was independent of organ system involvement and current ANCA status, with similar findings observed on comparative analysis following successful remission-induction therapy (AUC > 0.9, 100% sensitivity for disease remission, F-score 75%). This promising technique is clinically translatable and warrants future larger study with longitudinal data, potentially aiding earlier intervention and individualisation of treatment.

Biomedical Vibrational Spectroscopy in the Era of Artificial Intelligence

Biomedical vibrational spectroscopy has come of age. The past twenty years have brought many advancements and new developments and now its practitioners face a new challenge: artificial intelligence. Artificial intelligence has the capability to detect meaningful relationships in data sets such as those found in an infrared or Raman spectrum. The present narrative assesses the degree to which biomedical vibrational spectroscopy has already embraced artificial intelligence and what can be expected going forward. This article belongs to the Special Issue Biomedical Applications of Infrared and Raman Spectroscopy.

Biomarkers in ANCA-Associated Vasculitis: Potential Pitfalls and Future Prospects

Over the past 3 decades, significant advancements in the understanding of the pathophysiology of ANCA-associated vasculitis has led to the development of a multitude of potential candidate biomarkers. Accompanied by the advent of increasingly effective therapeutic strategies, the need for a dependable biomarker to help determine the extent of disease activity and risk of relapse is ever present. Implementation of such a biomarker would enable tailored therapy, optimizing disease control while helping to mitigate unnecessary exposure to therapy and potential treatment-related damage. Although far from perfect, ANCA serology and B-cell population are the two main staple biomarker tools widely used in practice to help supplement clinical assessment. Over recent years, the application and progress of more novel biomarker tools have arisen in both organ-limited and multisystem disease, including genomics, urinary proteins, degradation products of the alternative complement system, cytokines, metabolomics, and biospectroscopy. Validation studies and clinical translation of these tools are required, with serial assessment of disease activity and determination of therapy according to biomarker status correlated with patient outcomes.

Infrared spectroscopy of serum as a potential diagnostic screening approach for naturally occurring canine osteoarthritis associated with cranial cruciate ligament rupture

OBJECTIVE

To evaluate infrared (IR) spectroscopy of serum as a screening tool to differentiate dogs affected by naturally occurring osteoarthritis (OA) associated with cranial cruciate ligament rupture (CrCLR) and controls.

METHOD

104 adult dogs with CrCLR (affected group) and 50 adult control dogs were recruited for this prospective observational study. Serum samples were collected preoperatively from CrCLR dogs and from a subset of these dogs at 4-, and 12-week post-surgical intervention to stabilize the affected stifles. Serum was collected once from control dogs. Dry films were made from serum samples, and IR absorbance spectra acquired. Data preprocessing, principal component analysis and multivariate analysis of covariance were performed to separate samples from the two groups, and to evaluate temporal differences. Weighted logistic regression with L1 regularization method was used to develop a predictive model. Model performance based on an independent test set was evaluated.

RESULTS

Spectral data analysis revealed significant separation between the sera of CrCLR and control dogs (P < 0.0001), but not amongst different time points in the OA group. The sensitivity, specificity, AUC and accuracy of the test set were 84.62%, 96.15%, 93.20% and 92.31% respectively.

CONCLUSIONS

These findings confirm the potential of IR-spectroscopy of serum with chemometrics methods to differentiate controls from dogs with OA associated with CrCLR. This is the first step in development of an economic, and comparatively simple IR-based screening serum test for OA. Utility of this tool as a clinical screening and diagnostic test requires further investigation and validation.

Vibrational Spectroscopy Fingerprinting in Medicine: from Molecular to Clinical Practice

In the last two decades, Fourier Transform Infrared (FTIR) and Raman spectroscopies turn out to be valuable tools, capable of providing fingerprint-type information on the composition and structural conformation of specific molecular species. Vibrational spectroscopy's multiple features, namely highly sensitive to changes at the molecular level, noninvasive, nondestructive, reagent-free, and waste-free analysis, illustrate the potential in biomedical field. In light of this, the current work features recent data and major trends in spectroscopic analyses going from in vivo measurements up to ex vivo extracted and processed materials. The ability to offer insights into the structural variations underpinning pathogenesis of diseases could provide a platform for disease diagnosis and therapy effectiveness evaluation as a future standard clinical tool.

Characterization of Articular Cartilage Recovery and Its Correlation with Optical Response in the Near-Infrared Spectral Range

OBJECTIVES

In this study, we examine the capacity of a new parameter, based on the recovery response of articular cartilage, to distinguish between healthy and damaged tissues. We also investigate whether or not this new parameter correlates with the near-infrared (NIR) optical response of articular cartilage.

DESIGN

Normal and artificially degenerated (proteoglycan-depleted) bovine cartilage samples were nondestructively probed using NIR spectroscopy. Subsequently they were subjected to a load and unloading protocol, and the recovery response was logged during unloading. The recovery parameter, elastic rebound ( E_R), is based on the strain energy released as the samples underwent instantaneous elastic recovery.

RESULTS

Our results reveal positive relationship between the rebound parameter and cartilage proteoglycan content (normal samples: 2.20 ± 0.10 N mm; proteoglycan-depleted samples: 0.50 ± 0.04 N mm for 1 hour of enzymatic treatment and 0.13 ± 0.02 N mm for 4 hours of enzymatic treatment). In addition, multivariate analysis using partial least squares regression was employed to investigate the relationship between E_R and NIR spectral data. The results reveal significantly high correlation ( R²_cal = 98.35% and R²_val = 79.87%; P < 0.0001), with relatively low error (14%), between the recovery and optical response of cartilage in the combined NIR regions 5,450 to 6,100 cm^-1 and 7,500 to 12,500 cm^-1.

CONCLUSION

We conclude that E_R can indicate the mechanical condition and state of health of articular cartilage. The correlation of E_R with cartilage optical response in the NIR range could facilitate real-time evaluation of the tissue's integrity during arthroscopic surgery and could also provide an important tool for cartilage assessment in tissue engineering and regeneration research.

Lymphatic imaging to assess rheumatoid flare: mechanistic insights and biomarker potential

Proliferation of draining lymphatic vessels coupled with dynamic changes in lymph node volume and flow are characteristic features in rheumatoid arthritis (RA). Furthermore, impaired lymph egress from inflamed synovium is associated with joint flare in murine models of inflammatory-erosive arthritis. Unfortunately, advances towards a greater understanding of lymphatic changes in RA pathogenesis have been slow due to the absence of outcome measures to quantify lymphatic function in vivo. While lymphoscintigraphy is the current standard to assess lymphedema and sentinel lymph nodes in cancer patients, its sensitivity and specificity are inadequate to study lymphatics in RA. The emergence of high-resolution MRI, power Doppler ultrasound, and near-infrared imaging that permits real-time quantification of lymphatic function in animal models has been a major advance, and these techniques have produced a new paradigm of altered lymphatic function that underlies both acute arthritic flare and chronic inflammation. In acute flare, lymphatic drainage increases several fold, whereas no lymphatic contractions are detected in lymph vessels draining chronic arthritic joints. Moreover, these outcomes are now being adapted to study lymphatics in RA towards the development of novel biomarkers of arthritic flare and the discovery of new therapeutic targets. In particular, interventions that directly increase lymphatic egress from diseased joints by opening collateral lymphatic vessels, and that restore lymphatic vessel contractions, provide novel therapeutic approaches with potential for minimal toxicity and immunosuppression. To summarize the origins of this field, recent advances, and future directions, we herein review: current knowledge of lymphatics in RA based on classic literature; new in-vivo imaging modalities that have elucidated how lymphatics modulate acute versus chronic joint inflammation in murine models; and how these preclinical outcome measures are being translated to study lymphatic function in RA inflammation and how effective RA therapies alter lymphatic flow and lymph nodes draining flaring joints.

Trial registration: ClinicalTrials.gov NCT02680067. Registered 7 December 2015; ClinicalTrials.gov NCT01098201. Registered 30 March 2010; and ClinicalTrials.gov NCT01083563. Registered 8 March 2010.

Near infrared spectroscopic imaging assessment of cartilage composition: Validation with mid infrared imaging spectroscopy

Disease or injury to articular cartilage results in loss of extracellular matrix components which can lead to the development of osteoarthritis (OA). To better understand the process of disease development, there is a need for evaluation of changes in cartilage composition without the requirement of extensive sample preparation. Near infrared (NIR) spectroscopy is a chemical investigative technique based on molecular vibrations that is increasingly used as an assessment tool for studying cartilage composition. However, the assignment of specific molecular vibrations to absorbance bands in the NIR spectrum of cartilage, which arise from overtones and combinations of primary absorbances in the mid infrared (MIR) spectral region, has been challenging. In contrast, MIR spectroscopic assessment of cartilage is well-established, with many studies validating the assignment of specific bands present in MIR spectra to specific molecular vibrations. In the current study, NIR imaging spectroscopic data were obtained for compositional analysis of tissues that served as an in vitro model of OA. MIR spectroscopic data obtained from the identical tissue regions were used as the gold-standard for collagen and proteoglycan (PG) content. MIR spectroscopy in transmittance mode typically requires a much shorter pathlength through the sample (≤10 microns thick) compared to NIR spectroscopy (millimeters). Thus, this study first addressed the linearity of small absorbance bands in the MIR region with increasing tissue thickness, suitable for obtaining a signal in both the MIR and NIR regions. It was found that the linearity of specific, small MIR absorbance bands attributable to the collagen and PG components of cartilage (at 1336 and 856 cm(-1), respectively) are maintained through a thickness of 60 μm, which was also suitable for NIR data collection. MIR and NIR spectral data were then collected from 60 μm thick samples of cartilage degraded with chondroitinase ABC as a model of OA. Partial least squares (PLS) regression using NIR spectra as input predicted the MIR-determined compositional parameters of PG/collagen within 6% of actual values. These results indicate that NIR spectral data can be used to assess molecular changes that occur with cartilage degradation, and further, the data provide a foundation for future clinical studies where NIR fiber optic probes can be used to assess the progression of cartilage degradation.

Near-infrared spectroscopy for medical applications: Current status and future perspectives

The near-infrared radiation (NIR) window, also known as the "optical window" or "therapeutic window", is the range of wavelengths that has the maximum depth of penetration in tissue. Indeed, because NIR is minimally absorbed by water and hemoglobin, spectra readings can be easily collected from the body surface. Recent reports have shown the potential of NIR spectroscopy in various medical applications, including functional analysis of the brain and other tissues, as well as an analytical tool for diagnosing diseases. The broad applicability of NIR spectroscopy facilitates the diagnosis and therapy of diseases as well as elucidating their pathophysiology. This review introduces recent advances and describes new studies in NIR to demonstrate potential clinical applications of NIR spectroscopy.

Hyperspectral imaging for detection of arthritis: feasibility and prospects

Rheumatoid arthritis (RA) is a disease that frequently leads to joint destruction. It has a high incidence rate worldwide, and the disease significantly reduces patients’ quality of life. Detecting and treating inflammatory arthritis before structural damage to the joint has occurred is known to be essential for preventing patient disability and pain. Existing diagnostic technologies are expensive, time consuming, and require trained personnel to collect and interpret data. Optical techniques might be a fast, noninvasive alternative. Hyperspectral imaging (HSI) is a noncontact optical technique which provides both spectral and spatial information in one measurement. In this study, the feasibility of HSI in arthritis diagnostics was explored by numerical simulations and optimal imaging parameters were identified. Hyperspectral reflectance and transmission images of RA and normal human joint models were simulated using the Monte Carlo method. The spectral range was 600 to 1100 nm. Characteristic spatial patterns for RA joints and two spectral windows with transmission were identified. The study demonstrated that transmittance images of human joints could be used as one parameter for discrimination between arthritic and unaffected joints. The presented work shows that HSI is a promising imaging modality for the diagnostics and follow-up monitoring of arthritis in small joints.

How do visual, spectroscopic and biomechanical changes of cartilage correlate in osteoarthritic knee joints?

BACKGROUND

Characteristic changes in cartilage of human knee joints with different degrees of osteoarthritis (OA) have been investigated by visual, biophotonical and biomechanical examination. Knowledge about the cartilage composition and changes during the development of OA is important for diagnostic decisions and understanding the pathogenesis of OA.

METHODS

Thirty two patients with severe knee OA received endoprosthetic replacement. During surgical intervention cartilage specimen were harvested from defined surface areas of the joints. The degree of cartilage defects was classified visually (ICRS Grade: International Cartilage Repair Society), biophotonically (NIRS: near infrared spectroscopy) and biomechanically (Young's Modulus). To characterise links between the investigated parameters the Spearman's rank correlation coefficient was used.

FINDINGS

Significant negative correlations were found between visual macroscopic degree of degeneration (ICRS Grade) and biophotonic characteristics (NIRS) (rho=-0.467) or cartilage stiffness (Young's Modulus) (rho=-0.501). Between NIRS and Young's Modulus significant positive correlation of rho=0.535 was detected.

INTERPRETATION

Visual, biophotonic and biomechanical properties of cartilage reveal strong correlations in all degrees of cartilage defects in patients with severe OA. According to these results, we indicate that an objective, non-invasive and non-destructive measurement of cartilage properties during open and arthroscopic knee surgery is possible by NIRS and provide a novel tool to evaluate disease intervention and treatment.

Detection and evaluation of initial cartilage pathology in man: A comparison between MRT, arthroscopy and near-infrared spectroscopy (NIR) in their relation to initial knee pain

BACKGROUND AND AIMS

MRI and arthroscopy are important methods in the evaluation of cartilage pathology. But frequently initial changes of cartilage in combination with chronic knee pain cannot be detected by employing these two methods. Better diagnostic tools for the detection of the early stages of osteoarthritis (OA) are required. The objective of this study was to show that near-infrared spectroscopy (NIRS) can be incorporated into routine arthroscopy to improve detection and assessment of the initial cartilage pathology. Furthermore correlations between findings in MRI, arthroscopy and NIRS in patients with initial symptoms of OA have studied.

METHODS

Patients (n=21, 12 women, 9 men, age: 15-59 years, mean 34.19 years) with knee pain lasting for at least half a year without any trauma of the knee in their history were interviewed (body weight, smoking behaviour) and clinically evaluated using the Knee Injury and Osteoarthritis Outcome Score (KOOS). Also serum parameters (cholesterol, lipids) were analysed, conventional X-rays in three directions (evaluated according to Kellgren and Lawrence) and MRI (evaluation of cartilage damage according to the ICRS-score) were performed preoperatively in all patients. During subsequent arthroscopy cartilage damage was evaluated according to the ICRS-score. In addition the spectral reflection of cartilage was investigated in all knees using a special micro-glass-fiber probe in the near-infrared light region (spectral range between 1150 and 1475nm). To characterize relations between the investigated parameters the Spearman's rank correlation coefficient was used. Inter-observer variance was calculated employing the Cohens-Kappa-test.

RESULTS

MRI demonstrated a strong inter-observer variance with no significant correlations to other parameters. The same was observed for arthroscopic findings. Only NIRS showed significant correlations with three out of five KOOS subscores. Within the general parameters only smoking behaviour showed a significant correlation with two of the KOOS-scores. NIRS therefore seemed to be a sensitive diagnostic tool in detection of initial pathology in human cartilage. The additional necessary time for the spectroscopic investigation as part of the routine arthroscopy ranged between 3 and 7min (mean: 4min 18s).

CONCLUSION

Particularly for early-stage cartilage lesions (ICRS 0/I) MRI and arthroscopy have rather low predictive value. The inter-observer variance is very high (Cohens-Kappa<0.4). Correlations found between NIRS and KOOS suggest that NIRS potentially can be used for detection of initial cartilage pathology and may be helpful in the evaluation of the benefit of different medical or surgical interventions at early-stage of articular cartilage damage.

Raman spectroscopy of synovial fluid as a tool for diagnosing osteoarthritis

For many years, viscosity has been the primary method used by researchers in rheumatology to assess the physiochemical properties of synovial fluid in both normal and osteoarthritic patients. However, progress has been limited by the lack of methods that provide multiple layers of information, use small sample volumes, and are rapid. Raman spectroscopy was used to assess the biochemical composition of synovial fluid collected from 40 patients with clinical evidence of knee osteoarthritis (OA) at the time of elective surgical treatment. Severity of knee osteoarthritis was assessed by a radiologist using Kellgren/Lawrence (K/L) scores from knee joint x rays, while light microscopy and Raman spectroscopy were used to examine synovial fluid (SF) aspirates (2 to 10 microL), deposited on fused silica slides. We show that Raman bands used to describe protein secondary structure and content can be used to detect changes in synovial fluid from osteoarthritic patients. Several Raman band intensity ratios increased significantly in spectra collected from synovial fluid in patients with radiological evidence of moderate-to-severe osteoarthritis damage. These ratios can be used to provide a "yes/no" damage assessment. These studies provide evidence that Raman spectroscopy would be a suitable candidate in the evaluation of joint damage in knee osteoarthritis patients.

Toward point-of-care diagnostic metabolic fingerprinting: quantification of plasma creatinine by infrared spectroscopy of microfluidic-preprocessed samples

Infrared (IR) spectroscopy has previously been established as a means to accurately quantify several serum and urine metabolites, based upon spectroscopy of dry films. The same technique has also provided the basis to develop certain diagnostic tests, developed in the 'metabolomics' spirit. Here, we report on the further development of an integrated microfluidic-IR technology and technique, customized with the aim of dramatically extending the capabilities of IR spectroscopy in both analytical and diagnostic (metabolomic) applications. By exploiting the laminar fluid diffusion interface (LFDI), serum specimens are processed to yield product streams that are better suited for metabolic fingerprinting; metabolites are captured within the aqueous product stream, while proteins (which otherwise dominate the spectra of films dried from serum) are present in much reduced concentration. Spectroscopy of films dried from the aqueous stream then provides enhanced diagnostic and analytical sensitivity. The manuscript introduces an LFDI card design that is customized for integration with IR spectroscopy, and details the development of a quantitative assay for serum creatinine--based upon LFDI-processed serum samples--that is substantially more accurate (standard error of calibration, SEC = 43 micromol/L) than the corresponding assay based upon unprocessed serum specimens (SEC = 138 micromol/L). Preliminary results of diffusion modeling are reported, and the prospects for further optimization of the technique, guided by accurate modeling, are discussed.

Metabolic fingerprinting as a diagnostic tool

Within the framework of systems biology, functional analyses at all 'omic levels have seen an intense level of activity during the first decade of the twenty-first century. These include genomics, transcriptomics, proteomics, metabolomics and lipidomics. It could be said that metabolomics offers some unique advantages over the other 'omics disciplines and one of the core approaches of metabolomics for disease diagnostics is metabolic fingerprinting. This review provides an overview of the main metabolic fingerprinting approaches used for disease diagnostics and includes: infrared and Raman spectroscopy, Nuclear magnetic resonance (NMR) spectroscopy, followed by an introduction to a wide range of novel mass spectrometry-based methods, which are currently under intense investigation and developmental activity in laboratories worldwide. It is hoped that this review will act as a springboard for researchers and clinicians across a wide range of disciplines in this exciting era of multidisciplinary and novel approaches to disease diagnostics.

Detection of calcium phosphate crystals in the joint fluid of patients with osteoarthritis - analytical approaches and challenges

Clinically, osteoarthritis (OA) is characterised by joint pain, stiffness after immobility, limitation of movement and, in many cases, the presence of basic calcium phosphate (BCP) crystals in the joint fluid. The detection of BCP crystals in the synovial fluid of patients with OA is fraught with challenges due to the submicroscopic size of BCP, the complex nature of the matrix in which they are found and the fact that other crystals can co-exist with them in cases of mixed pathology. Routine analysis of joint crystals still relies almost exclusively on the use of optical microscopy, which has limited applicability for BCP crystal identification due to limited resolution and the inherent subjectivity of the technique. The purpose of this Critical Review is to present an overview of some of the main analytical tools employed in the detection of BCP to date and the potential of emerging technologies such as atomic force microscopy (AFM) and Raman microspectroscopy for this purpose.

Diagnosis of basal cell carcinoma by infrared spectroscopy of whole blood samples applying soft independent modeling class analogy

Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy was applied to discriminate the blood samples obtained from healthy people and those with basal cell carcinoma, demonstrating high accuracy while soft independent modeling class analogy (SIMCA) chemometric technique is benefited. It was aimed to classify the normal case and cancer case blood samples through the use of ATR-FTIR spectroscopy as a rapid method while the sample preparation is so easy in comparison with the common pathologic methods. A total of 72 blood samples, including 32 cancer and 40 normal cases, were analyzed in 1,800-900 cm(-1) spectral region. Results showed 97.6% of accuracy being compared with the current clinical methods. Research results were exemplified with comparable data of other classification methods such as principal component analysis (PCA) and Cluster analysis. The residual errors in prediction (REP) of calibration model for normal and cancerous groups in SIMCA method were 0.00362 and 0.00343, respectively.

Identification of infrared absorption spectral characteristics of synovial fluid of horses with osteochondrosis of the tarsocrural joint

OBJECTIVE

To determine the feasibility of the use of Fourier-transform infrared (FTIR) spectroscopy within the midinfrared range to differentiate synovial fluid samples of joints with osteochondrosis from those of control samples.

ANIMALS

33 horses with osteochondrosis of the tarsocrural joint and 31 horses free of tarsocrural joint disease.

PROCEDURES

FTIR spectroscopy of synovial fluid was used. Sixty-four synovial fluid samples from the tarsocrural joint were collected. Of these, 33 samples were from horses with radiographic evidence of osteochondrosis of the tarsocrural joint and 31 from control joints. Disease-associated features within infrared spectra of synovial fluid were statistically selected for spectral classification, and the variables identified were used in a classification model. Linear discriminant analysis and leave-one-out cross-validation were used to develop a classifier to identify joints with osteochondrosis.

RESULTS

12 significant subregions were identified that met the selection criteria. The stepwise discriminant procedure resulted in the final selection of 6 optimal regions that most contributed to the discriminatory power of the classification algorithm. Infrared spectra derived from synovial fluid of joints with osteochondrosis were differentiated from the control samples with accuracy of 77% (81% specificity and 73% sensitivity).

CONCLUSIONS AND CLINICAL RELEVANCE

The disease-associated characteristics of infrared spectra of synovial fluid from joints with osteochondrosis may be exploited via appropriate feature selection and classification algorithms to differentiate joints with osteochondrosis from those of control joints. Further study with larger sample size including age-, breed-, and sex-matched control horses would further validate the clinical value of infrared spectroscopy for the diagnosis of osteochondrosis in horses.

Use of Fourier transform infrared microscopy for the evaluation of drug efficiency

Fourier transform infrared (FTIR) spectroscopy has been used by chemists as a powerful tool to characterize inorganic and organic compounds. In this study, we examine the potential of FTIR microspectroscopy for early evaluation of therapy efficiency. For this purpose, we examine the effect of acyclovir (a known antiherpetic drug) on the development of herpes simplex virus type 1 (HSV-1) infection in cell culture. Also, we examine spectral changes in lymphocytes obtained from leukemia patients after appropriate chemotherapy treatment. Our results show early and significant spectral indicators for successful infection of Vero cells with HSV-1. Treatment of these infected cells with increasing doses of acyclovir reduces clearly the spectral changes caused by the infection in a correlation with inhibiting the development of the cytopathic effect (CPE) induced by this virus. Also significant and consistent spectral differences between lymphocytes from human leukemia patients compared to that from healthy persons are obtained. Treatment of these leukemia patients with appropriate drugs reduces significantly these spectral differences in a correlation with the improvement of the patient's clinical situation. It seems that FTIR spectroscopy can be used as an effective tool for early evaluation of the efficiency of drugs.

Use of infrared spectroscopy for diagnosis of traumatic arthritis in horses

OBJECTIVE

To evaluate use of infrared spectroscopy for diagnosis of traumatic arthritis in horses.

ANIMALS

48 horses with traumatic arthritis and 5 clinically and radiographically normal horses.

PROCEDURES

Synovial fluid samples were collected from 77 joints in 48 horses with traumatic arthritis. Paired samples (affected and control joints) from 29 horses and independent samples from an affected (n = 12) or control (7) joint from 19 horses were collected for model calibration. A second set of 20 normal validation samples was collected from 5 clinically and radiographically normal horses. Fourier transform infrared spectra of synovial fluids were acquired and manipulated, and data from affected joints were compared with controls to identify spectroscopic features that differed significantly between groups. A classification model that used linear discriminant analysis was developed. Performance of the model was determined by use of the 2 validation datasets.

RESULTS

A classification model based on 3 infrared regions classified spectra from the calibration dataset with overall accuracy of 97% (sensitivity, 93%; specificity, 100%). The model, with cost-adjusted prior probabilities of 0.60:0.40, yielded overall accuracy of 89% (sensitivity, 83%; specificity, 100%) for the first validation sample dataset and 100% correct classification of the second set of independent normal control joints.

CONCLUSIONS AND CLINICAL RELEVANCE

The infrared spectroscopic patterns of fluid from joints with traumatic arthritis differed significantly from the corresponding patterns for controls. These alterations in absorption patterns may be used via an appropriate classification algorithm to differentiate the spectra of affected joints from those of controls.

Automated search for arthritic patterns in infrared spectra of synovial fluid using adaptive wavelets and fuzzy C-means analysis

Analysis of synovial fluid by infrared (IR) clinical chemistry requires expert interpretation and is susceptible to subjective error. The application of automated pattern recognition (APR) may enhance the utility of IR analysis. Here, we describe an APR method based on the fuzzy C-means cluster adaptive wavelet (FCMC-AW) algorithm, which consists of two parts: one is a FCMC using the features from an M-band feature extractor adopting the adaptive wavelet algorithm and the second is a Bayesian classifier using the membership matrix generated by the FCMC. A FCMC-cross-validated quadratic probability measure (FCMC-CVQPM) criterion is used under the assumption that the class probability density is equal to the value of the membership matrix. Therefore, both values of posterior probabilities and selection criterion MFQ can be obtained through the membership matrix. The distinctive advantage of this method is that it provides not only the 'hard' classification of a new pattern, but also the confidence of this classification, which is reflected by the membership matrix.

A robust clustering approach for NMR spectra of natural product extracts

A robust method was developed to cluster similar NMR spectra from partially purified extracts obtained from a range of marine sponges and a plant biota. The NMR data were acquired using microtiter plate NMR (VAST) in protonated solvents. A sample data set which contained several clusters was used to optimize the protocol. The evaluation of the robustness was performed using three different clustering methods: tree clustering analysis, K-means clustering and multidimensional scaling. These methods were compared for consistency using the sample data set and the optimized methodology was applied to clustering of a set of spectra from partially purified biota extracts.

Laminar fluid diffusion interface preconditioning of serum and urine for reagent-free infrared clinical analysis and diagnostics

A number of reagent-free infrared spectroscopic diagnostic and analytical methods have been established previously making use of dry biofluid films. For example, this approach has successfully measured high concentration analytes of serum and urine. However, a number of low concentration diagnostically relevant analytes presently elude detection by infrared spectroscopy. This is due in part to their relatively low concentration and in part to spectral interference by other strongly absorbing constituents. The applicability of the technique would be broadened substantially if it were possible to concentrate and separate lower concentration analytes, e. g., serum creatinine and urine proteins, from the obscuring presence of relatively high concentration compounds. One possible means to achieve this is through microfluidic sample preconditioning based on laminar fluid diffusion interfaces. The objective of this study was therefore to qualitatively assess the performance of this technology in preferentially separating certain serum and urine analytes of clinical interest that presently lie just below the threshold of detection by infrared spectroscopy. Observations from simulated and genuine urine and serum samples strongly suggest that this process should improve existing accuracy and extend the range of detectable analytes.

Studies on acute human infections using FTIR microspectroscopy and cluster analysis

A novel methodology for the diagnosis of acute infections using FTIR microspectroscopy (FTIR-MSP) data on blood components and cluster analysis is presented. Blood samples were collected from 11 patients suffering from various infections and 16 age-matched healthy human controls. Blood components such as white blood cells, red blood cells, and plasma were isolated using standard procedures and FTIR-MSP of these components was utilized. A cluster analysis of the FTIR spectra was performed. The spectra obtained from the three blood components of patients were different from those of controls. The FTIR spectra of white blood cells from patients suffering infections were significantly different from the controls. Cluster analyses of averaged FTIR-MSP spectra of white blood cells provided 100% classification between patients and healthy controls.

Spectroscopic evaluation of the effect of a red microalgal polysaccharide on herpes-infected Vero cells

The sulfated polysaccharide obtained from a species of red microalga has proved to be a potent antiviral agent against various members of the herpes family. In the present study, we used microscopic Fourier transform infrared spectroscopy (FT-IR) to investigate differences between normal cells, those infected with herpes viruses, and infected cells treated with red microalgal polysaccharide. FT-IR enables the characterization of cell or tissue pathology based on characteristic molecular vibrational spectra of the cells. The advantage of microscopic FT-IR spectroscopy over conventional FT-IR spectroscopy is that it facilitates inspection of restricted regions of cell cultures or tissue. Our results showed significant spectral differences at early stages of infection between infected and noninfected cells, and between infected cells treated with the polysaccharide and those not treated. In infected cells, there was an impressive decrease in sugar content and a considerable increase in phosphate levels in conjunction with the infection progress. Our results also proved that sugars penetrated and accumulated inside cells treated with the red microalgal polysaccharide. These could have been sugar fragments of low molecular weight present in the polysaccharide solution, despite purification by dialysis. Such sugar accumulation might be responsible for a breakdown in the internal steps of the viral replication cycle.

Analysis of temporomandibular joint synovial fluid using Fourier transform/infrared spectroscopy

PURPOSE

In recent years infrared spectroscopy has been increasingly used for the analytical determination of biologic fluids and tissues. With the help of this method it was possible to investigate the various types of arthritis affecting the knee joint, among others. The aim of our study was to show that infrared spectroscopy can also be used as a method to analyze the synovial fluid of the temporomandibular joint to differentiate between inflammatory and noninflammatory disorders.

MATERIALS AND METHODS

Using Fourier transform/infrared spectroscopy analysis, comparable absorption spectra with characteristic signals in the corresponding range of wavelength were shown and used to prove pathologic alterations in the synovial fluid. Samples of 22 patients with arthritis of the temporomandibular joint and 12 patients with noninflammatory internal derangement were investigated and compared with each other.

RESULTS

Our measurements presented a distinct intensity difference between the absorption spectra of patients who had arthritis and those without signs of an inflammatory change but with an internal derangement as control specimens. Due to the small number of undiluted samples it was not possible to follow up with a multivariant analysis, necessary for a differential diagnostic evaluation between the individual types of arthritis.

CONCLUSIONS

A certain differentiation between arthritic and noninflamed temporomandibular joints can be noted with infrared spectroscopy of the synovial fluid. This represents a valuable option for minimally invasive diagnostic proof of inflammation in cases of joint disorders.

Automated mode-of-action detection by metabolic profiling

Rapid classification and identification of the mode-of-action of bioactive compounds applied to plants can be achieved by a robust and easy-to-use metabolic-profiling method. This method uses artificial neural network analysis of one-dimensional proton NMR spectra of aqueous plant extracts to rapidly classify changes in the total metabolic profile caused by application of crop protection chemicals.

Determination of cholesterol in atherosclerotic plaques using near infrared diffuse reflection spectroscopy

The aim of this investigation was to examine whether near infrared diffuse reflection spectroscopy is an acceptable tool for the determination of cholesterol content in atherosclerotic plaques. Using an FT-spectrophotometer (lambda=1000-2500 nm) and fiberoptic systems (d=4 mm), the cholesterol content could be determined in mixtures of the primary compounds of the aortic wall with acceptable precision. Considering the inhomogeneous distribution of cholesterol and cholesterol esters in atherosclerotic plaques the determination of total cholesterol using this method is of acceptable efficacy, even though the calibration procedure did not reflect the composition correctly. Using an energy dose of less than 100 mW/cm(2) to avoid damage to endothelial cells, arterial tissue of about 170-200 microm thickness attenuates the reflected NIRS signal by up to 50%. Cholesterol levels could be determined accurately in atherosclerotic lesions in human aortic specimens obtained by autopsy. The correlation coefficient between the NIRS results and those of HPLC analysis calculated in the investigation of 82 different areas of 18 human aortic specimens was 0.926 (y=0.869x+0. 771, external validation). Acceptable results were also achieved by means of a coronary-catheterlike fiberoptic strand (d=l mm), despite the worsened signal/noise ratio. The results show that the development of a coronary catheter using NIRS appears to be possible in principle.

Classification of breast tumors by grade and steroid receptor status using pattern recognition analysis of infrared spectra

Infrared (IR) spectroscopy applied to tissue sections yields complex spectra that provide a molecular fingerprint of the tissue. We have studied a cohort of 77 breast tumors by IR spectroscopy to develop an objective method for the assignment of grade of breast tumors. Although the major variations between spectra from different tumors were in absorptions arising from triglycerides (adipose tissue) and collagen, subtle changes in spectra could be detected that were independent of cellularity and tissue composition. Using a specific multivariate pattern recognition strategy to associate these changes in spectra with different tumor grades, we then were able to accurately reclassify tumors by grade (87% accuracy; kappa = 0.835). A similar approach allowed classification of steroid receptor status (93% accuracy; kappa = 0.852). We conclude that IR spectroscopy may have clinical utility in the objective assignment of breast tumor grade.

Multianalyte serum analysis using mid-infrared spectroscopy

This study assesses the potential for using mid-infrared (mid-IR) spectroscopy of dried serum films as the basis for the simultaneous quantitation of eight serum analytes: total protein, albumin, triglycerides, cholesterol, glucose, urea, creatinine and uric acid. Infrared transmission spectra were acquired for 300 serum samples, each analysed independently using accepted reference clinical chemical methods. Quantitation methods were based upon the infrared spectra and reference analyses for 200 specimens, and the models validated using the remaining 100 samples. Standard errors in the IR-predicted analyte levels (Sy/x) were 2.8 g/L (total protein), 2.2 g/L (albumin), 0.23 mmol/L (triglycerides), 0.28 mmol/L (cholesterol), 0.41 mmol/L (glucose) and 1.1 mmol/L for urea, with correlation coefficients (IR vs reference analyses) of 0.95 or better. The IR method emerged to be less suited for creatinine (Sy/x = mumol/L) and uric acid (Sy/x = 140 mumol/L) due to the relatively low concentrations typical of these analytes.

Infrared spectroscopic analysis of biomedical specimens using glass substrates

We report on the use of glass substrates for the infrared spectroscopic analysis of dried serum, amniotic fluid, and synovial fluid films. New analytical applications of infrared spectroscopy are emerging rapidly, spurred largely by ever-improving instrumentation, combined with the widespread availability of powerful chemometric methods. We have recently begun to focus upon potential applications in both clinical chemistry and medical diagnostics. For example, serum analysis, the determination of fetal lung maturity, and the differential diagnosis of arthritis have all recently been demonstrated to be feasible on the basis of the infrared spectra of films dried from the appropriate samples (serum, amniotic fluid, or synovial fluid). However, the transition from the laboratory into clinical usage hinges on the availability of IR-transparent substrates that are both inexpensive and readily obtainable. We have demonstrated in this study that despite limited transparency in the IR region, clinical analyses and diagnostic spectral classifications may nevertheless be carried out using glass as a substrate for the IR measurements.

Infrared spectroscopy: a new frontier in medicine

As we enter the second half of the nineties, one of the major challenges for biological infrared spectroscopists is to transfer the knowledge we have gained from studies on isolated molecules to the complex world of medicine. That it is possible to meet this challenge is suggested by comparison with the development of other biophysical techniques, such as magnetic resonance spectroscopy and imaging, which have already found their place in medical research and practice. The Spectroscopy Group in Winnipeg is developing and evaluating a variety of new IR techniques for the analysis of body fluids and tissues, both in vitro and in vivo. Herein, we review these methodologies, which comprise both instrumental (imaging and spatially localized IR spectroscopy) and interpretational procedures aimed at optimizing the measurements and their conversion to biodiagnostic information.

Prediction of fetal lung maturity from near-infrared spectra of amniotic fluid

OBJECTIVE

The aim of this study was to attempt to correlate the quantitative data obtained from the near-infrared (near-IR) spectra of amniotic fluid with the lecithin/sphingomyelin (L/S) ratio determined from thin layer chromatographic analysis on the same samples, in order to establish the feasibility of near-IR spectroscopy as an alternate method for the prediction of fetal lung development.

METHODS

Samples of amniotic fluid were obtained by amniocentesis from 52 patients between the 26th and 41st week of pregnancy. About 350 microliters of amniotic fluid was required to record the near-IR spectrum over the entire spectral range between 400 and 2500 nm using a commercial spectrometer. The L/S ratio was determined independently by thin layer chromatography (TLC) for each sample. For correlating the infrared spectra with the TLC-based L/S ratios, a partial least squares analysis was used.

RESULTS

The L/S ratios predicted from the near-IR spectra of amniotic fluid were highly correlated and in excellent agreement with those determined by TLC (r = 0.91).

CONCLUSION

Near-IR spectroscopy has the potential to become an alternate method to TLC for prediction of fetal pulmonary maturity.

Infrared spectroscopy of dystrophic mdx mouse muscle tissue distinguishes among treatment groups

Four groups of mdx mice (deflazacort, high dose of 1.5 mg/kg and low dose of 0.75 mg/kg; prednisone, 1.0 mg/kg; and a placebo) were examined in a double-blind protocol. The experiments tested the hypothesis that infrared spectroscopy can distinguish among gastrocnemius muscle tissues derived from dystrophic animals (n = 22) from different treatment groups and from control muscle tissue (n = 23). Results showed that muscle, inflamed muscle, and tendon can be distinguished on the basis of their infrared absorption patterns. Distinctions among the spectra of the four treatment groups were sought with automated pattern-recognition methods. These classification methods, based either on spectral regions (900-1,500 cm-1) or on principal-component analysis, were in close agreement, assigning 15 or 16, respectively, of 22 mdx spectra to the correct treatment group. Both trials cleanly separated the high-dose deflazacort from the placebo group of muscles, whereas the prednisone and low-dose deflazacort groups were persistently confused in these classifications. Changes in the histology of muscle inflammation paralleled the spectral-classification results. Thus the proposed method, combining infrared spectroscopy with pattern-recognition algorithms, can distinguish treatment effects on muscle tissue. Specific spectral features characteristic of tissue type, disease progression, and treatment effects are not yet elucidated.