Peer Reviewed: IR Spectroscopy in Clinical and Diagnostic Applications

Oct 1, 2004 - sues, or fluids they affect; these differences are the basis of every- day clinical chemical tests, tissue staining, and medical imaging...
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IR spectroscopy’s sensitivity to molecular structure and interactions provides a “molecular fingerprint”, which is the basis for biomedical applications.

Janie Dubois U.S. Food and Drug Administration and University of Maryland

R. Anthony Shaw National Research Council of Canada

iagnostic medicine typically relies upon myriad measurements and observations to determine the presence and nature of disease. Clinicians look for deviations from the norm, especially changes that have a qualitative or quantitative relationship with a known set of symptoms characterizing a particular disease. In addition to the physical symptoms, diseases cause changes in the chemical composition of the organs, tissues, or fluids they affect; these differences are the basis of everyday clinical chemical tests, tissue staining, and medical imaging techniques. IR spectroscopy not only probes the chemical composition of a sample but also determines the precise position and amplitude of IR absorption bands that reflect interactions among the matrix constituents. Because of its sensitivity to both molecular structure and molecular interactions, the spectrum is often referred to as a molecular fingerprint of the sample; the specificity of that fingerprint is the basis for biomedical applications. At first glance, biomedical diagnostics using IR spectroscopy appear to be straightforward, simply entailing the acquisition of spectra corresponding to diseases and control samples. However, the two main practical requirements of any useful diagnostic test are that it be sensitive and specific. Spectral changes that characterize one specific disease must simultaneously rule out other diagnostic possibilities and must be distinguishable from the intrinsic spectroscopic variability that is a consequence of the biological heterogeneity of samples. Therefore, the development of diagnostic methods based on IR spectroscopy depends critically upon the collection of large numbers of spectra and the corresponding qualitative and/or quantitative tests, followed by the extraction of spectral attributes that faith-

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in Clinical and Diagnostic Applications © 2004 AMERICAN CHEMICAL SOCIETY

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fully reproduce, or surpass the accuracy of, existing methods. The potential utility and advantages of IR-based diagnostic tests are found in the nature of the measurement and its ease of implementation. Once such a diagnostic test has been discovered (the difficult part!), its objectivity and simplicity and the relatively low cost of the instrumentation make it potentially accessible not only to large hospitals but also to smaller practices, even to individual physicians’ offices. In this article, we lead the reader through some examples that capitalize on the range of qualitative and quantitative chemical information available and illustrate the diagnostic capabilities of IR spectroscopy.

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FIGURE 1. IR spectra of serum in the native state and as a dry film. Asterisks denote water absorptions. The spectrum of the film has been displaced on the vertical axis for comparison. The transmission spectrum of the serum was acquired using a path length of 6 µm. The spectrum of the dry film was acquired by diluting the serum 50:50 in water and drying a 7-µL aliquot onto a 13-mm-diam barium fluoride window.

Back in the old days The historical development of IR spectroscopy dates back to the discovery of “calorific rays” (i.e., IR radiation) by Herschel in 1800 (1, 2). Before ~1940, the only way to acquire an IR spectrum was to build a homemade spectrometer. However, in the United States, the number of spectrometers increased from 15 in 1938 to more than 500 in 1947 as industrial manufacturers entered the scene. One important accomplishment during that period was the determination of the structure of penicillin, with the high-frequency C=O stretching mode of the -lactam ring serving to confirm the molecule’s structure. IR spectra of biological materials such as steroids, natural products, and bacteria were published in the 1950s. Notwithstanding these early forays into biochemistry and medicine, for decades IR spectroscopy was largely confined to the determination of chemical structure. In the 1970s and 1980s, the technique benefited from the development and easy availability of FT spectrometers (3). More recently, the enormous advances in computational power have enabled the development, refinement, and widespread implementation of data acquisition and processing methods. These innovations opened the door to previously unthinkable research and applications and extended the reach of IR spectroscopy to biological problems (4 –6). The biomedical spectroscopy community operates at the leading edge of instrumentation and processing methods. With the integration of automated sampling devices for high-throughput and array detectors adding a spatial dimension to spectroscopic sample characterization (7, 8), today’s FTIR spectrometers routinely produce volumes of data on a scale that was inconceivable a decade ago. This capability is essential for effective analysis of complex biological samples. Whereas a single spectrum characterizes a single compound, useful investigations of disease states may require hundreds or thousands of spectra or more. The sheer volume of data, and the often-subtle nature of the effects that are sought, has dictated the adoption and development of very sophisticated interpretative methods (9). Biomedical spectroscopists have embraced chemometrics and other 362 A

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mathematical processing methods to extract and exploit a larger portion of the spectral information, including some that would otherwise go unnoticed.

The fundamentals still apply By virtue of their sheer complexity, the spectroscopic signatures of tissues and fluids, with their broad overlapping bands, seem to be far removed from those encountered in more traditional applications. Nevertheless, the knowledge gleaned from model studies serves as a useful guide to understanding the chemical origins of the complex patterns associated with biological specimens. To that end, it is useful to remember the underlying principles of mid-IR spectroscopy. Mid-IR spectroscopy is based on the absorption of light in the 400–4000 cm–1 range, which corresponds almost exclusively to molecular vibrational modes. Compositional information is present in the form of spectral bands arising from skeletal and functional group vibrations. Although simple molecules produce simple IR spectra with well-resolved absorptions, the number of bands and the extent of band overlap increase with the number of chemical functional groups present in a sample (10, 11). Quantitatively, mid-IR spectroscopy of non-scattering samples obeys Beer’s law— absorbance is proportional to the concentration of a particular component or functional group (10). Consequently, the spectra of biological specimens reflect both the structural complexity of the individual components and their relative abundances. Some guidance for the assignment and interpretation of complex spectra originating from biomedical samples is available from the large libraries of spectra that have been acquired from biochemical and biological components over the years (6). For example, proteins display the amide I band at ~1650 cm–1 (largely the C=O stretch) and the amide II band at ~1540 cm–1 (N–H bend), lipids contribute absorptions at ~1740 cm–1 (C=O stretch) and 2852/2920 cm–1 (symmetric/asymmetric CH2 stretch), and the PO2– vibrations of DNA are typically located at ~1080 cm–1

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(symmetric stretch) and 1240 cm–1 (asymmetric stretch). The position and amplitude of these absorption bands are governed by the nature and concentrations of the constituents and by other factors of possible diagnostic relevance, including the molecular conformation of the constituents and interactions among them. A well-known example is the sensitivity of the protein amide I band to protein secondary structure (12).

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FIGURE 2. With a powerful source of IR light, good-quality spectra can be obtained for very small pixel sizes. With a conventional IR microscope, the signal deteriorates badly at apertures