Spectral pre and post processing for infrared and Raman spectroscopy of biological tissues and cells

Abstract

Vibrational Spectroscopy, both infrared absorption and Raman spectroscopy, have attracted increasing attention for biomedical applications, from in vivo and ex vivo disease diagnostics and screening, to in vitro screening of therapeutics. There remain, however, many challenges related to the accuracy of analysis of physically and chemically inhomogeneous samples, across heterogeneous sample sets. Data preprocessing is required to deal with variations in instrumental responses and intrinsic spectral backgrounds and distortions in order to extract reliable spectral data. Data postprocessing is required to extract the most reliable information from the sample sets, based on often very subtle changes in spectra associated with the targeted pathology or biochemical process. This review presents the current understanding of the factors influencing the quality of spectra recorded and the pre-processing steps commonly employed to improve on spectral quality. It further explores some of the most common techniques which have emerged for classification and analysis of the spectral data for biomedical applications. The importance of sample presentation and measurement conditions to yield the highest quality spectra in the first place is emphasised, as is the potential of model simulated datasets to validate both pre-and post-processing protocols.

Ultra-filtration of human serum for improved quantitative analysis of low molecular weight biomarkers using ATR-IR spectroscopy

“…The IR spectrum contains rich and specific information about the molecular composition of the human serum which, coupled to advanced multivariate analysis tools, could deliver accurate diagnostics. Recent systematic studies have demonstrated the potential of IR serum based diagnosis with different data mining approaches such as Principal Components Analysis (PCA), PCA coupled to Linear Discriminant Analysis (PCA-LDA), Random Forest or Support Vector Machine (SVM) [26][27][28][29][30] . However, the development of spectroscopic technologies with medical perspectives needs to align with clinical requirements to enable clinical translation of these promising technologies 31 .…”

Vibrational spectroscopy as a tool for studying drug-cell interaction: Could high throughput vibrational spectroscopic screening improve drug development?

“…Transflection IR, in comparison, uses cheap MirrIR slides that are easier to handle. [39] As the beam passes through the sample twice, transflection IR also results in better signal-to-noise, and a reduced acquisition time can be used to achieve the same quality spectra as with transmission IR. [58] Alternatively, this means for transflection IR can use samples with less thickness can be used.…”

“…The primary disadvantage of transmission IR is that it generally requires high cost substrates such as calcium fluoride, which are also brittle, and therefore care must be taken when handling them. [39] The cost of the substrate would make translating this technique into a HTS platform difficult as a result of the cost involved. However, if substrates could be reused this would reduce the consumable cost.…”

“…These include vertex component analysis [49], classic least squares analysis [50], spectral cross correlation analysis [50], artificial neural networks [51] and genetic algorithm [52], but for the purpose of this review these will not be discussed further. For further discussion of these techniques and their application, reference is made to Byrne et al [39].…”

“…Byrne et al [39] recently summarised the major pre and post processing methods employed for IR and Raman spectroscopic analysis of tissues and cells. Pre processing methods involve improving spectral quality by removal of background features caused by physical effects, sample preparation and substrate.…”