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Multimode Imaging in the Thermal Infrared for Chemical Contrast Enhancement. Part 3: Visualizing Blood on Fabrics Heather Brooke, Megan R. Baranowski, Jessica N. McCutcheon, Stephen L. Morgan, and Michael L. Myrick* Department of Chemistry and Biochemistry, 631 Sumter Street, University of South Carolina, Columbia, South Carolina 29208 Infrared thermal imaging using lock-in and molecular factor computing methods for the detection of blood on a dark, acrylic fabric is shown. Contrast differences between the clean fabric and the fabric stained with blood diluted as low as 1:100 are reported. We have also demonstrated that this method can be used to discriminate between a bloodstain and four common interfering agents (bleach, rust, cherry soda, and coffee) to other blood detection methods. These results indicate that this system could be useful for crime scene investigations by focusing nondestructive attention on areas more likely to be suitable for further analysis. The detection of invisible stains is an important part of crime scene analysis. The most common current method for detection of latent bloodstains uses luminol, which allows the visualization of latent bloodstains by a nonspecific, chemiluminescent reaction of the luminol reagent catalyzed by the iron in hemoglobin. When ambient light is blocked, the stains can be visualized in the dark using an UV light source. Luminol allows visualization with a rapid response time but has several disadvantages: toxicity; compromising the stain integrity; difficulty in ambient light conditions (e.g. outdoors); and susceptibility to false positives and false negatives, because chemiluminescence is also catalyzed by free copper and iron ions, as well as strong oxidizers such as bleach.1 The spectral profile of blood exhibits pronounced absorption bands in the mid infrared (MIR) range, most notably the amide regions (3290, 1650, 1540 cm-1), arising from the proteins in blood. Conversely, three of the four most common crime scene textiles/fibers (cotton, polyester, acrylic, and nylon) do not have significant absorbance in the amide region, with nylon, a polyamide, being the exception. On the basis of these observations, we began to explore the characteristic infrared spectral signature of blood as an approach to detect stains invisible to the eye. De Wael et al. describe several different spectroscopic methods for detecting blood particles, including visible microspectroscopy, Raman, and infrared (IR).2 While they are able to confirm the presence of blood, the sampling method consists of a tape lifting * To whom correspondence should be addressed. Phone: 803-777-6018. (1) Larkin, T.; Gannicliffe, C. Sci. Justice 2008, 48, 71–75. (2) De Wael, K.; Lepot, L.; Gason, F.; Gilbert, B. Forensic Sci. Int. 2008, 180, 37–42. 10.1021/ac101107v 2010 American Chemical Society Published on Web 09/23/2010
technique. The tape is manually screened under a microscope for particles that appear like blood, which are then examined spectroscopically. A number of other groups have also performed forensic spectroscopic studies on blood, including Raman,3,4 IR,5 and UV/vis6 techniques, which are able to confirm blood particles. Our lab has also conducted attenuated total reflectance (ATR) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) measurements on fabric samples, in the mid-IR region, combined with chemometric analyses, and found that it is possible to distinguish between spectra of neat and stained fabrics.7 These spectroscopic techniques are good confirmatory methods; however, they are mostly performed in the lab and are not screening methods. Current sampling methods, such as the tape lifting technique, require testing of the entire suspect area. Our goal is to develop an approach that can quickly and easily scan a crime scene and identify areas of interest for further, more sensitive, or selective, testing. This approach would increase the efficiency of crime scene analysis by reducing the time spent sampling and analyzing areas that have little or no pertinent evidence. An added benefit would be the ability to determine whether a detected signal is consistent with, or inconsistent with, bloodstaining. Previously, we explored varying the response of thermal detectors with addition of chemical films that act as filtering or sensitizing layers.8 Adding chemical films to a thermal imaging detector is not a trivial exercise; therefore, we have focused our initial efforts on the use of chemical filters. The concept embodied in both approaches, however, is “like detects like”, e.g., a chemical filter masks the spectral signature from similar chemicals in the scene, providing an approximation of the power of hyperspectral imaging. This approach using chemical filters has been called “molecular factor computing”.9-11 Here, we apply this technique, (3) Virkler, K.; Lednev, I. K. Anal. Bioanal. Chem. 2010, 396, 525–534. (4) Virkler, K.; Lednev, I. K. Anal. Chem. 2009, 81, 7773–7777. (5) Botonjic-Sehic, E.; Brown, C. W.; Lamontagne, M.; Tsaparikos, M. Spectroscopy 2009, 24, 42–48. (6) Miskelly, G. A.; Wagner, J. H. Forensic Sci. Int. 2005, 155, 112–118. (7) Trimboli, A. R.; McCutcheon, J. N.; Hartzell-Baguley, B. Taylor, H. M.; Schultz, D. K. Myrick, M. L.; Morgan, S. L., unpublished work. (8) Simcock, M. N.; Myrick, M. L. Appl. Spectrosc. 2006, 60, 1469–1476. (9) Dai, B.; Urbas, A.; Douglas, C. C.; Lodder, R. A. Pharm. Res. 2007, 24, 1441–1449. (10) Fong, A.; Hieftje, G. M. Appl. Spectrosc. 1995, 49, 1261–1267. (11) Fong, A.; Hieftje, G. M. Appl. Spectrosc. 1995, 49, 493–498.
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combined with multimode thermal imaging,12 to our objective of distinguishing bloodstains. With proper tuning, we are able to display a near-real-time image on a viewing screen that highlights bloodstains at dilutions as low as 1:100. EXPERIMENTAL SECTION The instrument, data acquisition, and analysis are the same as described in ref 12, with the exceptions that (a) the gold standard was mostly covered with black masking tape to reduce glare in the images; (b) the filter was composed of an albumin film rather than Acryloid B67; and (c) the filter was removed from its holder and held by hand to reduce vignetting as a means to improve the calculation of contrast values. Sample Preparation. A sample of tricolored, unfinished acrylic fabric was doped with whole blood and four dilutions (10×, 25×, 50×, and 100×) in an isotonic solution (Dulbecco’s Phosphate Buffered Saline, D8537, Sigma-Aldrich). The stains were dripped onto the fabric with glass pipettes, using approximately 1 to 2 mL each, in the shape of representative Roman numerals: I for whole blood, X for 10× dilution, V for 25× dilution, L for 50× dilution, and C for 100× dilution, and they were allowed to dry overnight. A second piece of acrylic fabric was doped with five different types of stains: whole blood, bleach (Clorox), rust (ferric oxide powder, U.T. Baker, suspended in water), cherry soda (CocaCola), and coffee (medium roast, Kroger Ground Special Roast). These substances were chosen because they give false positives to one or more of the current blood detection methods, including the luminol technique.13 The stains were applied in the shape of a representative letter: B for blood, L for bleach, R for rust, S for cherry soda, and C for coffee. Filter Preparation. We determined through a computer simulation14 that filters composed of g8 µm of the protein albumin were best suited to serve as single filters among those we could produce in our lab for discriminating neat blood on acrylic. A KBr window was dip-coated in a solution of 20.0886 g of albumin/120 mL of DI H2O, using a sample changer (Gilson 223, Middleton WI), adapted for dip-coating purposes. The KBr substrate was held vertically and lowered into the solution at a rate of 100 mm/s, remained in the solution for 1 s, removed at a rate of 200 mm/s, and then allowed to dry in a vertical position. The thickness of the coating was ∼18 µm as determined by FT-IR transmission (Nexus 470, ThermoNicolet, Madison, WI). RESULTS AND DISCUSSION Blood Dilutions. Figure 1 is a photograph taken of acrylic fabric doped with different blood dilutions. In visible light, the only discernible stains are the whole blood and 10× dilution. Figure 2a-f shows images obtained using the alternating current (AC) thermal imaging technique described in ref 12. As expected, there is no discrimination in the direct current (DC) average image shown in Figure 2a, which is analogous to a traditional IR thermal emission image. However, all the stains show a distinct contrast with respect to the background fabric in (12) Brooke, H.; Baranowski, M. R.; McCutcheon, J. N.; Morgan, S. L.; Myrick, M. L. Anal. Chem., in press, DOI: 10.1021/ac101109w. (13) Dixon, T. R.; Samudra, A. V.; Stewart, W. D.; Johari, O. J. Forensic Sci. 1976, 21, 797–803. (14) Brooke, H.; Baranowski, M. R.; McCutcheon, J. N.; Morgan, S. L.; Myrick, M. L. Anal. Chem., in press, DOI: 10.1021/ac101108z.
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Figure 1. Photograph of tricolored acrylic fabric sample doped with five blood dilutions (whole blood, 10×, 25×, 50×, and 100×). Only whole blood and the 10× dilution are visibly recognizable.
Figure 2b, the in-phase AC reflectance (AC-0) images, down to the 100× dilution. In ref 12, we established a method to compare the contrast between the background and a stain, which we term the Fisher contrast (FC) because it is based on the Fisher ratio15 of the univariate average pixel intensity. The conventional Weber contrast16 is independent of the image noise or variability and, therefore, is not as useful for defining discrimination ability. These values are reported in Table 1. Ordinarily, one would consider Fisher ratios below 1 rather poor, yet stains are clearly visible on fabrics even with much lower single-pixel Fisher contrasts. We believe the reason that stains are observable with low Fisher contrasts is because the eye “averages” over many pixels when viewing the images. We also find that the experimental Fisher contrast improves significantly as pixels are averaged into groups. For example, the Fisher contrast for whole blood in AC-0 mode improves from 33.19 to 94.93 if four pixels are averaged in each measurement. The image contrast does not exhibit a linear relationship with concentration level: 50× and 100× dilutions appear almost the same contrast, for example. This observation is consistent with other studies done in our lab of film coatings on fabric samples.17 In those studies, we found that films can, under certain conditions, exhibit strong effects on fabric reflectance at low concentrations, followed by more gradually increasing effects at higher concentrations, due to changes in the effective path length in the fabric diffuse reflectance. In another paper,14 we selected the albumin filter for blood detection via simulation based on linear discriminant analysis using the Fisher ratio (as opposed to the image “Fisher contrast” we have defined here), and we can compare the expected/ simulated value of the Fisher ratio to that measured experimentally for the discrimination of blood-doped fabric from neat. The simulated output was calculated using the spectrum of the actual ∼18 µm filter that was used for these experiments. The Fisher ratio for the experimental data was found to be 32.20, compared (15) Fisher, R. A. Ann. Eugenics 1936, 7, 179–188. (16) Tang, J. S.; Peli, E.; Acton, S. IEEE Signal Process. Lett. 2003, 10, 289– 292. (17) Baranowski, M. R.; Brooke, H.; McCutcheon, J. N.; Morgan, S. L.; Myrick, M. L. Appl. Spec., submitted for publication.
Figure 2. (A) DC average of unfiltered data showing no contrast between fabric and stains. (B) AC-0 unfiltered image showing significant contrast between fabric and all blood dilutions (whole blood, I; 10×, X; 25×, V; 50×, L; and 100×, C). (C) AC-90 unfiltered image showing heating/cooling effects of sample; contrast is measurable between fabric and blood dilutions to 25×. (D) DC average of sample taken with an ∼18 µm albumin filter in front of the camera. As expected, there is no change from the unfiltered DC image. (E) AC-0 filtered image, the decrease in contrast is partly due to reduced signal intensity and partly to discrimination of molecular bands. (F) AC-90 filtered image. Table 1. Measured and Simulated Contrast Values for Multimode Images of an Acrylic Fabric Sample with Bloodstains of Various Dilutions image mode AC-0 simulated AC-0 AC-0 filtered simulated AC-0 filtered AC-90 AC-90 filtered AC-0 AC-0 filtered
whole blood
10×
Fisher Contrast 33.19 2.36 93.70 39.53a 20.02 1.61 89.08 36.69a 1.01 0.17 0.62 0.08 Weber Contrast (%) 54.56 26.16 48.82 25.20
25×
50×
100×
0.48 2.02 0.19 2.46 0.08 0.01
0.36 2.51 0.28 2.70 0.01 0.01
0.29 2.50 0.15 2.23 0.00 0.00
9.37 6.63
7.30 6.78
6.30 4.97
Fisher Ratio from Linear Discriminant Analysis experimental 32.20 2.67 0.45 0.36 0.29 simulated 144.88 235.48a 86.66 42.11 42.54 a Simulations used a 5× dilution sample instead of 10×. Simulations do not include pixel noise of the microbolometer camera; experimental values are based on single-pixel intensities and improve if several pixels are averaged.
to a simulated value of 144.88 for whole blood on this fabric. In ref 14, we calculated the optimum albumin film thickness to be 2-10 µm for a 5× blood dilution; our experimental albumin film thickness of 18 µm (gravimetrically determined) was significantly greater than we would have optimally selected for the 5× dilution. Figure 2c is the out of phase, thermal re-emission AC (AC-90) image, which is significantly less intense than the reflection signal. In this imaging mode, dilutions only up to 25× show observable contrast differences, with values reported in Table 1. In this image, the intensities appear opposite of those in the AC-0 image, due to the inverse relation between reflection and emission as described in ref 12. Weber contrast figures are not reported for the AC-90 images because the average values of intensity are very close to zero, making the WC parameter unstable. Figures 2d-f shows the same sample viewed through an albumin filter in front of the camera. Figure 2d is the DC average of this filtered data and shows no real change compared to the
unfiltered DC average. However, Figure 2e, the AC-0 filtered image, shows a measurable decrease in contrast (values reported in Table 1) compared to Figure 2b, which is consistent with expectations for a proteinaceous stain. The test samples used here were prepared, vide supra, by pipetting fluids onto the fabric, while the reference samples used to select the albumin filter were prepared by the more reproducible method of dip coating. Nevertheless, the simulated Fisher ratios for the test samples using the albumin filter are broadly in agreement (though higher by factors of 3-5) with the experimental results as shown in Table 1, particularly given the different noise characteristics of the uncooled microbolometer array used for the test versus the FT-IR used for the reference data collection. Figure 2f is the AC-90 filtered image, and the contrast values are reported in Table 1. That there is a loss of contrast between the unfiltered and albumin-filtered images is at least partially attributable to the loss of AC intensity in the presence of the absorption filter when the signal variability is defined by pixelto-pixel noise. Blood Discrimination. Figure 3(Left) is a photograph taken of a sample of the same acrylic fabric doped with whole blood and with four blood interfering agents: bleach, rust, cherry soda, and coffee.13 In visible light, the blood and rust stains show contrast with the background fabric, but none of the other three stains are obvious to the eye. Figure 3(Right) is an image taken with the IR camera in ambient conditions, before the light source was turned on. As expected, there is no contrast in the image between any of the stains and the fabric background. The gold standard, which reflects ambient IR light, is observed faintly. Figure 4 shows multimode images of the sample of blood interfering agents. Figure 4a is the DC average, which is equivalent to the passive IR image in Figure 3(Right). (The gold standard is relatively bright because the source was on during this test and the standard has very high reflectivity.) Figure 4b is the unfiltered AC-0 image. The only stains that have significant contrast with the background fabric are the blood and soda. Fisher Analytical Chemistry, Vol. 82, No. 20, October 15, 2010
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Figure 3. (Left) Photograph taken of an acrylic fabric sample doped whole blood and four interfering agents (bleach, rust, cherry soda, and coffee) that give false positives to one or more blood detection methods. (Right) An image taken with the infrared camera in ambient conditions, before the light source was turned on. There is no distinction between any of the stains and the fabric background.
Figure 4. (A) DC average of unfiltered data showing no contrast between fabric and stains. (B) AC-0 unfiltered image showing significant contrast between fabric and blood and soda only. (C) AC-90 unfiltered image showing heating/cooling effects of sample, contrast is measurable for the bloodstain. (D) DC average of sample taken with an ∼18 µm albumin filter in front of the camera. As expected, there is no change from the unfiltered DC image. (E) AC-0 filtered image, the decrease in contrast is roughly the same for the blood and soda as the filter was chosen to maximize the contrast between blood and fabric only. (F) AC-90 filtered image does show a decrease in contrast as well; however, it is likely due to the intensity loss with the presence of the filter.
ratios for these two analytes are 37.8 and 10.6, respectively. We note that the FC for blood in this sample is roughly equivalent to the FC value for the previous sample. Bleach and rust produce a false positive with luminol (i.e., they elicit chemiluminescence), yet they are not detectable using these IR imaging modes. Figure 4c is the AC-90 image, which reveals the magnitude of the AC heating/cooling thermal re-emission function of the sample (FC ) 2.1 and 0.0 for the blood and soda, respectively). In this image, the blood appears lighter than the surrounding fabric (as in Figure 2c above). The soda stain is not observed in this image. The strength of the AC thermal reemission owes a portion of its magnitude to the strength of the corresponding absorption, and thus, we would expect the bloodstain to have a larger re-emission signal because of its somewhat greater absorption in the AC-0 images. However, the difference between the behaviors of the blood and soda stains is too great to attribute it to this source alone. Instead, the major contribution and difference between the two types of stains is likely physical, the blood stiffens the fabric and fills in spaces between fibers more fully than the soda stain does. 8430
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Dried blood is spectroscopically distinguished from, for example, the sugars in a nondiet soda by several factors, but the most important of these for the purpose of discrimination is the presence of protein. Proteins exhibit strong and characteristic bands, among which are those known as the amide A (∼3290 cm-1/3.04 µm), amide I (∼1650 cm-1/6.06 µm), and amide II (∼1540 cm-1/6.49 µm). These would be considered by most spectroscopists as the most distinctive indicators of the presence and nature of proteins in a sample. Unfortunately, the spectral window of our microbolometer camera excludes these most important regions because of the limitations of the necessary “antireflection” coating applied to the camera’s germanium window. The discrimination achieved in this work using any of the various modes of infrared imaging then depends on relatively weak bands in the spectral signature of blood that are not such distinctive signatures of proteins. It is probable, then, that an instrument specifically designed to function in the 3-6.5 µm wavelength region would provide stronger contrast and, thus, higher discriminating power against organic chemical interferences such as sugars.
Figure 4d-f displays the multimode images of the same sample taken with the albumin filter in front of the camera lens. As before, the filtered DC image (Figure 4d) shows no significant change from the unfiltered image. The filtered AC-0 image, shown in Figure 4e, does exhibit a decrease in the contrast for both the blood and soda (FC ) 25.2 and 6.9, respectively). The filter causes a ∼35% decrease in the contrast for both stains and, so, does not add any additional discrimination. However, the albumin filter was chosen by simulation to produce high contrast between the fabric and blood, not between blood and other types of stains. We anticipate that better filters or combinations of filters could be selected via simulation that would be more appropriate for discrimination between blood and soda or other interfering agents. Figure 4f is the filtered AC-90 image, which does show some decrease in contrast (FC ) 1.1 and 0.0, for blood and soda, respectively), though it is likely a result of the intensity decrease with the presence of a filter as mentioned previously (vide supra). CONCLUSIONS We have shown that our method of multimode imaging gives online, near-real-time contrast discrimination between neat fabric and bloodstains, sensitive to at least a 100× dilution factor. The total time required for collecting and analyzing the data is less than 2 min. This multimode imaging technique with filtering provides a tool for quickly and easily scanning a crime scene for areas that warrant further confirmatory testing.
We have also shown discrimination between blood and four stains that give false positives to current blood identification methods, using both the AC-0 and AC-90 phase images. These preliminary results shown here suggest that this approach could be a reasonable screening method for rapid visualization of bloodstains. It is not, however, and is not intended to be a confirmatory method, for which further site-specific testing would be recommended. By combining the multimode imaging with simulation-selected filters (as described in ref. 14), we believe additional chemical discrimination is possible. ACKNOWLEDGMENT This project was supported by Award No. 2007-DN-BX-K199 awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect those of the Department of Justice. The authors also acknowledge the University of South Carolina Electron Microscopy Center for instrument use and scientific and technical assistance. H.B. thanks the Graduate School of the University of South Carolina (Columbia) for travel and other support during this project. Received for review April 27, 2010. Accepted August 6, 2010. AC101107V
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