IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.

Vibrational spectroscopy can provide rapid, label-free, and objective analysis for the clinical domain. Spectroscopic analysis of biofluids such as blood components (e.g. serum and plasma) and others in the proximity of the diseased tissue or cell (e.g. bile, urine, and sputum) offers non-invasive diagnostic/monitoring possibilities for future healthcare that are capable of rapid diagnosis of diseases via specific spectral markers or signatures. Biofluids offer an ideal diagnostic medium due to their ease and low cost of collection and daily use in clinical biology. Due to the low risk and invasiveness of their collection they are widely welcomed by patients as a diagnostic medium. This review underscores recent research within the field of biofluid spectroscopy and its use in myriad pathologies such as cancer and infectious diseases. It highlights current progresses, advents, and pitfalls within the field and discusses future spectroscopic clinical potentials for diagnostics. The requirements and issues surrounding clinical translation are also considered.

Non-specific symptoms, as well as the lack of a cost-effective test to triage patients in primary care, has resulted in increased time-to-diagnosis and a poor prognosis for brain cancer patients. A rapid, cost-effective, triage test could significantly improve this patient pathway. A blood test using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy for the detection of brain cancer, alongside machine learning technology, is advancing towards clinical translation. However, whilst the methodology is simple and does not require extensive sample preparation, the throughput of such an approach is limited. Here we describe the development of instrumentation for the analysis of serum that is able to differentiate cancer and control patients at a sensitivity and specificity of 93.2% and 92.8%. Furthermore, preliminary data from the first prospective clinical validation study of its kind are presented, demonstrating how this innovative technology can triage patients and allow rapid access to imaging.

The implications of this study for clinical practice and health planning are considerable. The findings identify groups (men, unmarried individuals, and those living in lower income areas) at higher risk for institutionalized death-groups that may be targeted for possible interventions to promote home death when home death is preferred by patients and their families. Further, the findings suggest that site of death is influenced by available health-system resources. Thus, if home death is to be supported, the relative availability of hospital beds and hospice providers may be an effective policy tool for promoting home death.

Fourier transform infrared (FTIR) spectroscopy is a vibrational spectroscopic technique that uses infrared radiation to vibrate molecular bonds within the sample that absorbs it. As different samples contain different molecular bonds or different configurations of molecular bonds, FTIR allows us to obtain chemical information on molecules within the sample. Fourier transform infrared microspectroscopy in conjunction with a principal component-discriminant function analysis (PC-DFA) algorithm was applied to the grading of prostate cancer (CaP) tissue specimens. The PC-DFA algorithm is used alongside the established diagnostic measures of Gleason grading and the tumour/node/metastasis system. Principal component-discriminant function analysis improved the sensitivity and specificity of a three-band Gleason score criterion diagnosis previously reported by attaining an overall sensitivity of 92.3% and specificity of 99.4%. For the first time, we present the use of a two-band criterion showing an association of FTIR-based spectral characteristics with clinically aggressive behaviour in CaP manifest as local and/or distal spread. This paper shows the potential for the use of spectroscopic analysis for the evaluation of the biopotential of CaP in an accurate and reproducible manner.

Vibrational spectroscopies, based on infrared absorption and/or Raman scattering provide a detailed fingerprint of a material, based on the chemical content. Diagnostic and prognostic tools based on these technologies have the potential to revolutionise our clinical systems leading to improved patient outcome, more efficient public services and significant economic savings. However, despite these strong drivers, there are many fundamental scientific and technological challenges which have limited the implementation of this technology in the clinical arena, although recent years have seen significant progress in addressing these challenges. This review examines (i) the state of the art of clinical applications of infrared absorption and Raman spectroscopy, and (ii) the outstanding challenges, and progress towards translation, highlighting specific examples in the areas of in vivo, ex vivo and in vitro applications. In addition, the requirements of instrumentation suitable for use in the clinic, strategies for pre-processing and statistical analysis in clinical spectroscopy and data sharing protocols, will be discussed. Emerging consensus recommendations are presented, and the future perspectives of the field are assessed, particularly in the context of national and international collaborative research initiatives, such as the UK EPSRC Clinical Infrared and Raman Spectroscopy Network, the EU COST Action Raman4Clinics, and the International Society for Clinical Spectroscopy.

Gliomas are the most frequent primary brain tumours in adults with over 9,000 people diagnosed each year in the UK. A rapid, reagent-free and cost-effective diagnostic regime using serum spectroscopy would allow for rapid diagnostic results and for swift treatment planning and monitoring within the clinical environment. We report the use of ATR-FTIR spectral data combined with a RBF-SVM for the diagnosis of gliomas (high-grade and low-grade) from non-cancer with sensitivities and specificities on average of 93.75 and 96.53% respectively. The proposed diagnostic regime has the ability to reduce mortality and morbidity rates.

The ability to diagnose cancer rapidly with high sensitivity and specificity is essential to exploit advances in new treatments to lead significant reductions in mortality and morbidity. Current cancer diagnostic tests observing tissue architecture and specific protein expression for specific cancers suffer from inter-observer variability, poor detection rates and occur when the patient is symptomatic. A new method for the detection of cancer using 1 μl of human serum, attenuated total reflection—Fourier transform infrared spectroscopy and pattern recognition algorithms is reported using a 433 patient dataset (3897 spectra). To the best of our knowledge, we present the largest study on serum mid-infrared spectroscopy for cancer research. We achieve optimum sensitivities and specificities using a Radial Basis Function Support Vector Machine of between 80.0 and 100 % for all strata and identify the major spectral features, hence biochemical components, responsible for the discrimination within each stratum. We assess feature fed-SVM analysis for our cancer versus non-cancer model and achieve 91.5 and 83.0 % sensitivity and specificity respectively. We demonstrate the use of infrared light to provide a spectral signature from human serum to detect, for the first time, cancer versus non-cancer, metastatic cancer versus organ confined, brain cancer severity and the organ of origin of metastatic disease from the same sample enabling stratified diagnostics depending upon the clinical question asked.Electronic supplementary materialThe online version of this article (doi:10.1007/s11060-016-2060-x) contains supplementary material, which is available to authorized users.