Micro-Raman Spectroscopy for Assessment of Periodontal Disease Follow-Up Micro-Raman spectroscopy for assessment of periodontal disease follow-up Carlo Camerlingo 1 , Fabrizia d’Apuzzo 2 , Vincenzo Grassia 2 , Letizia Perillo 2 , Maria Lepore 3 1 CNR-SPIN, Istituto superconduttori, materiali innovativi e dispositivi, Pozzuoli, Italy; 2. Dipt. multidisc. Spec.medico-chirurgiche e odontoiatriche, Seconda Università di Napoli, Napoli, Italy; 3. Dipt. di Medicina Sperimentale, Seconda Università di Napoli, Napoli, Italy; The aim of this study is to investigate the potentiality of the micro-Raman spectroscopy (m-RS) for the follow up of periodontal disease in a not invasive way. m -RS was performed on gingival crevicular fluid (GCF). The fluid was pooled from informed periodontal and health patients by using standardized sterile absorbent paper cones inserted 1 mm into the gingival crevice and left in situ for 30 s, without blood, saliva and plaque contamination. GCF collect with paper strips 1
Micro-Raman Spectroscopy for Assessment of Periodontal Disease Follow-Up Micro-Raman spectroscopy The sample is excited by a He-Ne laser operating at a light wavelength Jobin Yvon TRIAX l = 633 nm, with a maximum LN 2 cooled He-Ne laser 180 monocromator nominal power of 17 mW. The signal CCD is collected by a Jobin-Yvon TriAx 180 monocromator, equipped with a 100x liquid N 2 cooled CCD and a grating objective of 1800 grooves/mm, allowing a spectral resolution of 4 cm -1 . The PC acquisition sample laser light is focused on the sample surface by means of a 100 x (n.a. Moving holder 0.90) optical objective on a excitation area of about 10 m m of Schematic view of experimental set up size. The spectra were obtained using accumulation times ranging in 60- 300 seconds. 2
Micro-Raman Spectroscopy for Assessment of Periodontal Disease Follow-Up Wavelet based numerical data treatment 240000 220000 200000 180000 160000 140000 4000 22000 3000 400 2000 The spectra typically show a 1000 0 -1000 smeared background signal, with -2000 1500 300 20000 1000 intensity of order of about 80% of 500 0 -500 the whole average intensity. In -1000 200 IDWT 600 400 DWT order to enhance signal readability 18000 200 0 -200 -400 and attenuate background and noise -600 100 1000 500 components we use a numerical 0 16000 -500 -1000 data treatment based on wavelet 0 -1500 400 300 200 algorithm [1]. The spectrum signal 100 14000 0 -100 is cut up into different ‘scale’ -100 -200 -300 200 100 components, by using spatially 0 12000 -100 -200 -200 localized functions with average -300 200 150 100 50 zero value (namely wavelets , small 1200 1400 1600 1800 2000 1200 1400 1600 1800 0 -50 -100 -150 waves) instead of conventional -200 150 100 50 Fourier transform sinusoidal 0 -50 -100 functions. -150 This make possible to keep information on both frequency and spatial dependence of the signal. Basically the signal is represented in terms of the sum of elementary wavelets and decomposed in two signals, one containing the low frequency components (approximation A) and the other one the fluctuations (detail D). The algorithm is iteratively applied to the “approximated” part of the function and a higher level of A and D component pair is generated. A hierarchical representation of the data set is thus obtained allowing a multi-resolution analysis, know as discrete wavelet transform (DWT). Starting from the decomposed signal, the spectrum can be reconstructed (IDWT) removing low and high frequency components due to spurious background and non-correlated noise signal respectively. MATLAB 6.5 program (by MathWorks Inc.) was used for wavelet analysis with wavelet family of biorthogonal functions “bior6.8 ” . [1] Camerlingo, C.; Zenone F.; Gaeta G.M.; Riccio R.; Lepore M. Wavelet data processing of micro-Raman spectra of biological samples. 3 Meas. Sci. Technol. 2006 , 17 , 298-303.3 .
Micro-Raman Spectroscopy for Assessment of Periodontal Disease Follow-Up Raman signal (arb. units) Raman signal substrate Raman signal after linear regression 800 1200 1600 2000 2400 2800 3200 -1 ) wavenumber shift (cm After the wavelet process the Raman signal of the substrate (paper cone) is subtracted from the raman signal of the sample by performing a linear regression of data. 4
Micro-Raman Spectroscopy for Assessment of Periodontal Disease Follow-Up GCF39 For signal interpretation the 400 1449 1656 Raman signal (arb. units) spectra were analyzed in terms of convoluted Lorentzian shaped 200 1321 vibration modes. Peaks constituting the spectrum were manually selected in order to 0 define the starting conditions for a best-fit procedure based on the Levenberg-Marquardt nonlinear -200 least-square method to determine convolution peaks with 1200 1400 1600 1800 -1 ) wavenumber (cm optimized intensity, position and width. Raman spectrum of GCF from a health patient. Protein contribution to spectrum are clearly evinced from the peaks at 1321 cm -1 (Amide III) , at 1449 cm -1 (CH 2 ), at 1580 cm -1 (C-C stretching) and at 1656 cm -1 (Amide I). 5
Micro-Raman Spectroscopy for Assessment of Periodontal Disease Follow-Up What we look for… The level of osteopontin in gingival crevicular fluid has been found to correlate with clinical measure of periodontal disease [2] Carotenoid concentration in GCF is expected to increase with the severity increase of the disease and in chronic periodontitis, with respect to healthy or gingivitis control. [2-3] [2] Gonchukov, S.; Sukhinina A.; Bakhmutov D; Minaeva S. Raman Spectroscopy of saliva as perspective method for periodontitis diagnostics. Laser Phys. Lett. 2012 , 9 ,73-77. [3] Kim, S.C.; Kim, O.-S., Kim, O.-J.; Kim, Y.-J.; Chung, H.-J. Antioxidant profile of whole saliva after scaling and root planing in periodontal disease, J Periodontal Implant Sci 2010, 40 , 164-171. 6
Micro-Raman Spectroscopy for Assessment of Periodontal Disease Follow-Up (a) (b) CH 3 CH def. Amide I Amide III Raman signal (arb. units) 2600 2800 3000 3200 1200 1400 1600 1800 2000 2931 (c) (d) 1655 1629 1591 2972 1676 2878 2700 2850 3000 1500 1550 1600 1650 1700 1750 -1 ) wavenumber (cm Raman spectrum of GCF from healthy patient for the 1200-2000 cm -1 ( a ) and 2500- 3100 cm -1 wavenumber range (b). Deconvolution in Lorentzian peaks of the Amide I spectrum region (1500-1750 cm -1 ) (c) and CH 3 region (2800-3000 cm -1 ) (d). 7
Micro-Raman Spectroscopy for Assessment of Periodontal Disease Follow-Up 1537 1685 The intense peak at about 1537 cm -1 1594 Raman signal (arb. units) is likely due to the formation of 1650 isomerization products containing 1624 C=C groups [4] related to an increase of degraded carotene in GCF. 1500 1550 1600 1650 1700 1750 -1 ) wavenumber shift (cm Raman spectrum of GCF from patient affected by chronic periodontitis: Deconvolution in Lorentzian peaks of the Amide I spectrum region (1500-1750 cm -1 ). 4. Noda, I.; Marcott, C.; Two-dimensional Raman (2D Raman) correlation spectroscopy study of non-oxidative photodegradation of b -carotene. J. Phys. Chem. A 2002 , 106, 3371-3376. 8
Micro-Raman Spectroscopy for Assessment of Periodontal Disease Follow-Up Conclusions A not invasive method based on m -RS of GCF for follow up of periodontal diseases is proposed and tested. An automatic numerical data treatment based on wavelet algorithm was used in order to suppress the uncorrelated signal, to subtract the background signal and to increase the quantitative readibility of the Raman signal . An increase of degraded carotenoide content in GCF, as a mark of the inflammatory state, is inferred from the Raman spectra of chronic periodontitis affected patients. Even if a more systematic and wide investigation is necessary to validate the proposed methods, the preliminary results confirm the big potentiality of m-RS for specific molecular fingerprinting in medical applications. 9
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