Raman and Infrared Spectroscopy and Their Application in Disease Diagnostics - Essay Example

Raman and Infrared Spectroscopy and Their Application in Disease Diagnostics Name Course Instructor City/state Date Introduction Developments in spectrometer technology have ensured significant progress in Raman and Infrared spectroscopy within the biochemistry field. They rely on the principle of molecular vibrations which depend on the structure and composition of samples [1]. Infrared microanalysis has been historically used in the field of science for sample-chemical characterization. With the discovery of Raman effects of light in 1928, quantum property of light has been studied. This discovery opened up room for scientific researches [2]. Thus, Raman microscopes have been in the field for a quiet a long time but it has faced criticisms with regard to high cost, complexity of the systems and a wavelength axis which is tedious to calibrate. However, recent Raman microscopy developments have addressed these shortcomings [3]. Raman spectroscopy has been proposed as the new tool for diagnosis abnormalities in tissues using real-time and noninvasive technique [4]. This system has discrimination algorithms and multivariate analysis of sample statistics making it possible to automatically classify spectra into relevant categories based on pathological and histological characteristics. Raman has been instrumental in characterizing tissues of cervix, skin, breast and gastrointestinal tract making it a useful tool in diagnosing cancers. However, recent developments in infrared microscopy enable for characterization of samples physically. The technique is basically a non-destructive in nature and it has been in the use for analyzing cells, fluids, tissues. Therefore, the technique has been aiding the detecting different diseases as well as malignancy stages in cervical, prostate and colon tissue infections [5]. This essay compares Raman and IR spectroscopes and discusses their application in the medical field. Raman Instrumentation The set up of this spectroscopy has three major components namely the excitation source or the laser, sample illumination and a system for light collection and a detection system. The excitation source In most cases, Raman spectroscopy uses Near-Infrared (NIR) radiation as an excitation source and it stretches from 780-1100nm [6]. This range reduces fluorescence effect thus detects weak Raman signals. On the other hand, the laser act as a source of monochromatic light and it separates lights that have been scattered elastically from the in elastically scattered illumination, detector and spectrograph [7]. Sample illumination system Since Raman has weak scattering signal, efficient collection of this scattered light is necessary [2]. Under practical instances, delivery and collection of light is by the silica fibers. However, silica molecules are Raman active resulting in unwanted signals which can are controlled by the use of band pass filters at the rear of delivery fiber. Besides, a notch filter at the front of collection fiber also blocks fluorescent effects though some Raman probes have filters that give a compact design. The detection system The detection system is usually a charged coupled device (CCD) that uses holographic grating. However, recently developed surface enhanced Raman scattering (SERS) has challenged the fluorescent based detection methods since it has a high sensitivity and detects multiple components that are present in mixtures [8]. SERS makes it possible to obtain fingerprint spectra that, a property that makes this Raman detection technique a preference for multiple analyses of the samples. Thus, it has been possible to directly detect DNA with SERS detection technique. On the other hand, SERS relies on adsorption or the proximity of the sample or analyte to metal substrate. SERS substrate takes the form of rough metal surface or colloid solution or rough electrode. Enhancement or detection thus takes 103-106 and is usually combined with chromophore for effecting its surface detection [8]. Infrared instrumentation Most IR instrumentation adopts FTIR spectroscopy [9]. This technique is advantageous since it has multiplex, excellent wave numbers and is throughput [3]. Its basic components include radiation source that is a broad band, interferometer, sample chamber and fast detector. The set up makes enables for combination of the lateral information in the FTIR spectrometers. Besides, the technique has detectors that are single channeled that restrict radiation at sample plane using an aperture. However, the development of FT-IR spectroscopy changed the IR analytical technique since it has allowed for fast, high-throughput and non-destructive analysis of a big range of samples [10]. This technique thus changed the initial instrumentation IR since it assumes that the sample’s functional groups absorb infrared (IR) beams. This absorption makes the sample components to vibrate in making them bent, stretched, deformed or a combination of vibrations. The vibrations correspond directly to specific. Biochemical species and resulting in an infrared spectrum which is usually known as fingerprint characteristic these substances [11]. Multiple channel detection enables this technique to acquire the entire image in the same time or duration as acquiring of single spectra. Advantages of Raman NIR lasers help in fluorescence suppression and the technique uses a single photon process of scattering light [1]. This implies the process does not need absorption. Nonetheless fewer materials get absorbed in its NIR region. Therefore, the lasers never produce fluorescence effect with normal Raman scattering. The other advantages involve its application with liquids and solids, non-destructiveness and the possibility of sample analysis through glass. Disadvantages of Raman NIR excitation decreases sensitivity since scattering efficiency of Raman is directly proportional to wavelength (laser wavelength) [1]. The problem increases with the CCD detector sensitivity within NIR range. On the other hand, Raman lasers portray beam qualities that are not suitable for microscopy. This compromises partial resolution thus results may not obey theoretical prediction. Furthermore, the spectroscopy can never be used on alloys or metals and that it has a very weak Raman Effect. Finally, the technique leads to sample heating from the intensive laser radiation which may damage the sample and can cover Raman spectrum. Advantages of IR It is suitable for analyzing solids, gases, semi-solids polymers and powders which Raman technique is unable to process [12]. Secondly, IR has intensities, peak positions, shapes and widths which provide very useful information. The technique measures speed of transmission at a maximum absorption point and it plots values against concentration thus eliminating possible errors. Finally, the system uses sensitive technique which routinely detects micrograms and it is inexpensive. Disadvantages of IR Atoms and monatomic ions have no infrared spectra [5]. Moreover, mononuclear molecules that are diatomic also do not have infrared spectra. In addition, it is difficult to analyze complex aqueous solutions and mixtures under infrared spectroscopy. IR does not provide specific information on exact molecule position making it difficult to differentiate if a molecule is pure or a mixture. Comparison of Raman and infrared spectroscopy Firstly, there are eminent differences on the Raman and infrared spectroscopes [13]. Infrared red microanalysis has is spatial resolution limited by light wavelength and aperture to approximately 10 microns. However, dispersive Raman spectroscopy is, there is large numerical aperture with short execution wavelength making three times better in its spatial resolution. Besides, Raman spectroscopy does not apply experimental samples that show fluorescence. However, infrared microscopes do not suffer from fluorescence effects. Uses of Raman an IR in disease diagnosis Raman technique has been recognized as one of the technological advances towards cervical cancer screening [14]. In this case, the technology uses its chemometric analysis that normally shows parallel transition from cell normalcy to their malignancy state. This assists in cervical cancer diagnosis as well classification of the existing cervical disorders. On the other hand, linear analysis shows that Raman has the ability to differentiate pre-cancerous tissues from the normal tissues [6]. On the other hand, it helps in diagnosis of low-grade and the high-grade pre-cancer conditions. Raman is also applicable in the diagnosis of skin cancers. Diagnosis of skin cancers has been relying on physical medical examinations using skin biopsy and dermatoscope. The process is expensive and time consuming hence there has been the need to develop non-invasive tools for diagnosing skin cancers. Raman technique uses NIR spectroscopy for diagnosing in vivo skin cancers [4]. This technique is outstanding since it improved skin cancer diagnosis due to its ability of detecting molecular changes that occurs due to tissue pathology. This technique therefore differentiates cancerous lesions from any benign deformities. Its sensitivity is at 90% with a specificity of 75%. On the other hand, Raman has also been a useful tool in diagnosing breast cancer, a disease condition which has been on the rise in the modern world [15]. The technique makes it possible to study vivo samples of the breast tissues by using NIR Raman to study normal and benign tissue lesions [4]. After this, the technique examines these samples and diagnoses the disease using diagnostic algorithm. IR can be used to diagnose leukaemia, cancer of the blood cells [5]. A milestone has been made in IR diagnosis by introducing the idea of discriminating drug resistance and sensitive leukaemia cells. The FT-IR technology has been on the use for discriminating DNA structures of cells from both normal persons and patients with leukaemia [10]. This discrimination thus allows for differentiation between normal blood cells and cancerous blood cells. On the other hand, Ramar is widely used in detecting brain tumors especially metastatic brain cancer [16]. In this case, the technique uses algorithms linear analyses for examining the spectra. A study on rat brains showed how IR spectroscopy can be useful in diagnosing brain tumors [17]. Thus the technique distinguishes normal tissues of the brain from malignant tissues. In addition, IR has been on the use for determining levels of glucose in the blood so as to help in diagnosing diabetic conditions. Thus, an IR spectroscopy has been useful in analysis of urine and blood constituents. In this case, least-square regression is a mathematical model that calculates glucose concentration in the blood sample rendering the technique useful for clinical diabetic diagnosis. SERS provides a mechanism for detecting three pathogens that are responsible for meningitis [8]. This technique is advantageous since it analyses multiple samples and has high sensitivity. Therefore, the technique is commendable since it detects many diseases. On the other hand, it has been in the use for detecting many DNA sequences at the same time. Detection of many analytes is an advantage that makes SERS the most preferred Raman technique in clinical applications. Therefore, this multiple analysis allows for detection and analysis of meningitis that is caused by three bacteria. Thus SERS gives different analyses on these pathogens making it possible to diagnose meningitis. However, the process has a limitation of fluorescence but it is still possible to quantify different pathogens. FTIR can be used to diagnose ovarian cancer since it provides a mechanism for classifying and analyzing serum or blood plasma [18]. This technique is capable of discriminating ovarian as well as endometrial cancer from the non-cancer controls. However, an endometrial classification has less accuracy as opposed to the ovarian cancer classification. For one, ovarian cancer is rather aggressive. Conversely, endometrial cancer has a majority in the stage I of less aggressiveness [19]. This makes the technique a bit challenging in diagnosing endometrial cancers. Recently, FTIR has been in the use for analyzing changes in sclerosis since this spectroscopy identifies minute structural changes [7]. Therefore, it helps in studying neuropathology of this disease making diagnosis easy by explaining how lesions form in the human body. This is the application of FTIR imaging in biomedical field [20]. Conclusion In summary, developments in the field of biochemistry has availed new techniques of diagnosing cellular diseases. The new techniques discussed in this essay are the IR and Raman spectroscopes that have been a milestone off optical science. However, the two techniques differ in the way their microscopes function. IR in particular has a limited resolution while Raman has a large numerical aperture giving it the best possible resolution. In addition, the techniques have various advantages and disadvantages that are unique to them. Raman does not need absorption process hence it requires limited time for preparation of the sample though it has decreased sensitivity due to NIR excitation. In the contrary, IR can be used to analyse any molecule form but analyzing complex solutions becomes difficult. The two techniques have been in the use in disease diagnosis with recent developments showing that they can be used in determining cancerous cells in the body. Areas of concern like cervical cancers, prostrate cancers and brain tumors are poised to benefit a great deal from the development of these areas of biochemistry. On the other hand, the report discusses SERS and FTIR as new techniques that have been aiding in disease diagnosis. References 1. Kraft, C 2004, bioanalytical applications of Raman spectroscopy, Analytical bioanalytical chemistry, vol.3278, no.1, pp60-62. 2. ANDOR, 2014, Raman Spectroscopy An introduction to Raman Spectroscopy, viewed 24 feb 2014 http://www.andor.com/learning-academy/raman-spectroscopy-an-introduction-to-raman-spectroscopy 3. Robert, B 2005, ‘Photonic crystal development yields breakthrough in Raman spectroscopy’, Sensor Review, vol. 25, no. 3, pp.195-196. 4. Motz, J. S, Gandhi, S. J, Scepanovic, O. R, Haka, A. S, Dasari, R. R 2005, ‘Real-time Raman system for in vivo disease diagnosis’, journal of biomedical optics,vol.10, no.3, p1-6. 5. Dubouis, J & Shaw, R. A 2004, ‘IR application in clinical and diagnostic application’, analytical chemistry, vol.76, no.1, pp360-367. 6. Sing, B, Gautam, R, Kumar, S, Kumar, B. N V, Nongthomba, U, Nandi, D, Mukherjee, G, Santosh, V, Somasundaram, K & Umapathy 2012, ‘Application of vibration microspectroscopy to biology and medicine’, current science, vol.102, no. 232-244. 7. Kraft, C, Steiner, G, Beleites, C & Salzer, R 2009, ‘disease recognition by infrared and Raman spectroscopy’, Journal of Biophoton, vol.1, no. 1-2, 13-28. 8. Gracie, K, Correa, E, Mabbott, Dougan, J. A, Graham, D, Goodacre, R and Faulds, K 2014, ‘simultaneous detection and quantification of three bacterial meningitis pathogens by SERS’, chemical science, vol.5, no.1, p1030-1040 9. Peter, R.G & James, A. H 2007, Fourier Transformation Infrared Spectrpmetry, Wiley Interscience, Canada 10. Lasch, P & Nauman, D, FTIR microspectroscopic imaging of human carcinoma in thin sections based on pattern recognition techniques. 11. Ellis, D.I & Goodacre, R 2006, ‘Metabolic fingerprinting in disease diagnosis: biomedical applications of infrared and Raman spectroscopy, analyst, vol.131, no.1, 875-885 12. Sheffield Hallam University, 2014 Infra-Red Absorption Spectroscopy: Instrumentation, viewed 24 February 2014http://teaching.shu.ac.uk/hwb/chemistry/tutorials/molspec/irspec3.htm> 13. Tague, T J 2007, ‘Infrared and Raman Microscopy: Complementary or Redundant Techniques?’, microsc microanal, vol. 13, no.13, 1696-1697. 14. Ellis, D. I, Cowcher, D. P, Ashton, L, O’Hagan & Goodacre 2013, ‘Illuminating disease and enlightening biomedicine: Raman spectroscopy as a diagnostic tool’, analyst, vol.138, no.1, 3871-3874. 15. Keller, M. D, Kanter, E. M & Mahaden-Jasen, A November 2006, ‘Raman spectroscopy for Cancer Diagnosi’, spectroscopy, vol.21, no. 11, pp.33-41. 16. Fullwood, L. M, Clemens, G Griffiths, D Ashton, K, Dawson, T.P, Lea, R.W, Davis, C, Bonnier, F, Byrne, H. J & Baker, M 2014, ‘Investigating the use of Raman and immersion Raman spectroscopy for spectral histopathology of metastatic brain cancer and primary sites of origin analytical methods. Online. http://dx.doi.org/10.1039/c3ay42190b 17. Amharref, N, Beljebbar, Dukic, S, Venteo, Schneider, L, Pullot, M, Vistelle, R & Manfait, M 2006, ‘brain tissue characterization by infrared imaging in a rat gliomal model, Biochemistry’, vol.1758, no. 1, 892-899. 18. Gajjar, K, Trevisan, J, Owens, G, Keating, P. J, Wood, N. J, Stringfellow, H.F , Martin-Hirsch, P.L & Martin, F.L2013, ‘Fourier-transform infrared spectroscopy coupled with a classification machine for the analysis of blood plasma or serum: a novel approach for ovarian cancer’, analyst, vol. 138, no. 1, 1317-1376. 19. Amaya, C 18 March 2010, Infrared spectroscopy aids cancer diagnosis, viewed 24 Feb 2010 http://www.rsc.org/Publishing/Journals/cb/Volume/2010/04/infrared_spectroscopy.asp 20. Stone, N, Kendall, C, Spepherd, N, Crow, P & Barr, H 2002, ‘Near-infrared Raman spectroscopy imaging and linear discrimination analysis technology’, Cancer Res. Treat, vol.33, no.1, 564-573. Read More