The nonlinear spectral imaging system is applied to in vivo
imaging of the lower inner arm skin of Caucasian and Asian volunteers. Accurate background subtraction is critical in the analysis of the (nonlinear) spectral images, and background correction procedures are frequently time-consuming and prone to artifacts. In previous work on spectral imaging of skin [7
], the analysis time was dominated by accurate background correction. Here, we improve the speed and accuracy of this procedure by simultaneously recording the emission and background spectra. The raw data file of the image contains three spectra per pixel: one emission spectrum and two background spectra. In
, a raw spectral image of human skin is analyzed. The emission spectrum of the specimen is projected on row 2; here the autofluorescence of epidermal cells is observed. The image quality for row 2 is, however, compromised by the background. The background gradually increases from the top to the bottom of the image, as can be readily observed in the background images of row 1 and 3. Moreover, the background shows a (reproducible) periodic signal, which results in diagonal lines in the images. Using background subtraction (row2-0.5* [row1 + row3], see ), these effects are corrected for. Also, the baseline level of the spectrum is now close to zero (was ~180, see spectra in ) and the effect of background on RGB conversion is minimized (see RGB images in ).
Fig. 2 Effect of simultaneous background recording on the quality of the spectral image of in vivo Caucasian human skin. (Left) Individual intensity and real color RGB images of the three spectra that are recorded for each pixel (row1 = background, row2 = emission (more ...)
The above background correction procedure significantly improves the quality of the images and was applied to all the images shown here. A Z-stack of 10 XY images of in vivo
Caucasian human skin is shown in
. In addition, an XZ image through the center of the stack is shown in the same figure (top left). The pixel dwell time was 128 µs per pixel, 6.5 seconds for a 224 × 224 pixel image and ~1 minute for the total stack. The excitation power was 15 mW, sufficiently low to avoid significant photodamage [25
]. Various structures can be distinguished. A part of the Stratum Corneum, corresponding to a furrow, extends into the recorded stack and exhibits bright green autofluorescence that probably originates from clusters of keratin. Epidermal cells have predominantly blue/green emission because of NADH, keratin and flavins. Some cells are melanized, which results in additional yellow/green emission. In the dermis, violet second harmonic generation (SHG) of collagen fibers is observed, as well as blue/green autofluorescence of elastic fibers. Vessel-like structures with orange emission can also be distinguished in the papillary dermis (upper region of the dermis) and correspond to blood capillaries.
Fig. 3 3D nonlinear spectral imaging of in vivo human skin (Caucasian skin type). Background corrected real color RGB images are shown. XY images are 224 × 224 pixels, corresponding to 70 × 70 µm2; imaging depth is 40 µm. Excitation (more ...)
A major advantage of the high-resolution EMCCD based spectrograph is that full autofluorescence spectra of skin components can be recorded. This is demonstrated in
for Caucasian and Asian skin. The images were recorded at the junction between epidermis and dermis. The fluorescence spectra are averaged on four regions of interest (ROIs) that contain: (1) epidermal cells, (2) melanized epidermal cells, (3) collagen fibers and (4) elastin fibers. In the dermis, two major components can be distinguished: a second harmonic generation (SHG) band at 380 nm from collagen and autofluorescence that mainly originates from the closely located elastin fibers. Because of the overlap of the networks formed by these two major components of the dermis, there is some bleed-through in their spectra (). The spectra of the collagen fibers SHG and elastin fibers autofluorescence are the same for both volunteers. Our data indicate that the epidermal cells, however, contain a skin type dependent contribution of melanin. Already from the RGB images, it is clear that melanin contribution (yellow/green autofluorescence) is stronger in the Asian skin type. Since melanin is composed of heterogeneous oligomers of fluorophores, its emission spectrum strongly depends on experimental conditions (as shown for synthetic melanin by Teuchner et al
]). Here, the spectra of melanin enriched cells exhibit an additional autofluorescence component at wavelengths longer than 550 nm. For the least melanized epidermal cells, the autofluorescence peaks at 480 nm, and the emission is a combination of NADH (450 nm), keratin (470 nm) and FAD (520 nm) autofluorescence. The spectra of nonmelanized epidermal cells of the two skin types are comparable. The melanized cells in Asian skin exhibit much stronger melanin autofluorescence than in Caucasian skin. For comparison, the spectrum of nonmelanized epidermal cells is added (gray line) to the spectrum in .
Fig. 4 Nonlinear spectral imaging of the epidermal / dermal junction of Caucasian (red lines) and Asian (blue lines) skin. In the background corrected real color RGB images, ROIs are indicated by white squares; EC = epidermal cells, mEC = melanized epidermal (more ...)
To confirm that the additional yellow emission is due to melanin, a series of images at the papillary epidermis/dermis interface were recorded (
). Here, autofluorescence of melanin can be detected [28
]. For three volunteers with Caucasian skin, the same observation is made: clusters of cells exhibiting yellow or green emission are located around dermal papilla. The difference in apparent color is likely due to different levels of tanning; low melanin levels appear green in the RGB images due to the presence of the red melanin fluorescence and blue autofluorescence (NADH, keratin). An increasing level of melanization results in a red shift of the observed color from green to yellow.
Fig. 5 Nonlinear spectral imaging of the epidermal / dermal junction of three volunteers with Caucasian skin. The images are 224 × 224 pixels, corresponding to 70 × 70 µm2. Excitation power is 15-20 mW, acquisition time is 128 µs (more ...)
Improvements in acquisition speed reduce the amount of detected signal. Due to the use of an EMCCD in our setup this is partly compensated. EMCCDs have a high sensitivity and low readout noise even at fast readout speeds. The sensitivity is much higher than systems equipped with multiplier tubes (PMTs) and it extends well into the red. The effect of signal level is exemplified in , where the signal-to-noise (S/N) ratio is varied by averaging the spectrum in each pixel by binning (N = 1, 9 (3 × 3) and 25 (5 × 5)). Note that the spectra are averaged, and that the resulting R, G, and B values are scaled and multiplied by the original (not-averaged) intensity value in the pixel. Spectral averaging does not visually improve the color contrast in the images. The spectrum recorded in 1 pixel (128 μs, ~15mW, image acquired at the epidermal-dermal junction) is sufficient for RGB conversion. Since RGB conversion only involves multiplication of spectra, it is fast. On a standard computer, an image of 224 × 224 pixels is converted in less than a second.
The real color representation of the spectral images can be used to discriminate between different structures in tissue. To investigate the sensitivity of the real color RGB representation to noise and its uniqueness for the structural features in skin, ternary plots of the RGB values are made (see
). These ternary plots display the relative contribution of the R, G, and B values for selected pixels. Five ROIs are selected: epidermal cells (EC), partly melanized EC, melanized EC, collagen and elastic fibers. The values of the pixels in these ROIs are overlaid in one plot. The ternary representation of unbinned pixels is not sufficient to uniquely identify components. By averaging over N = 9 and N = 25, however, clearly non-overlapping clouds of pixels are observed for most of the ROIs. The RGB values of the pixels containing elastic fibers are, however, very similar to the ones that represent partly melanized epidermal cells. This is not surprising since the spectra are very similar (see ). Since they are located in a different layer of the skin, it is nevertheless easy to separate them.
Fig. 6 (Top) Effect of spectral averaging on the quality of real color RGB images. For each pixel, the spectrum is averaged over N = 1 (blue area and spectrum), N = 9 (red) or 25 pixels (green); the intensity is not averaged, see text. (Center) RGB images of (more ...)
In conclusion, the fast nonlinear spectral imaging method presented here provides a powerful means to record images of in vivo human skin. Due to the use of an EMCCD based spectrograph, image acquisition time is significantly reduced and sensitivity is increased compared to systems equipped with regular CCD cameras. Importantly, this system affords real time correction for background by the simultaneous recording of background spectra. In combination with real color visualization it provides a rapid and photon efficient way to obtain color contrasted images that can be employed to readily identify regions of interest in the specimen. Further analyses of such regions can be carried out by utilizing the full wavelength resolution of the spectrograph. Here, clear differences it is shown that different emission spectra are obtained for the epidermal cells with different levels of melanin. Moreover, the ternary representation of R, G, and B values of their spectra allows for the discrimination between the different epidermal cells: melanized, partly melanized and nonmelanized cells. Future work will be devoted to spectral unmixing of the individual spectral components in the skin. This is of special interest for studies on e.g. the distribution of melanin between the different skin phototypes.