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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 4, Iss. 1 — Jan. 1, 2013
  • pp: 77–88
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Determination of chronological aging parameters in epidermal keratinocytes by in vivo harmonic generation microscopy

Yi-Hua Liao, Szu-Yu Chen, Sin-Yo Chou, Pei-Hsun Wang, Ming-Rung Tsai, and Chi-Kuang Sun  »View Author Affiliations


Biomedical Optics Express, Vol. 4, Issue 1, pp. 77-88 (2013)
http://dx.doi.org/10.1364/BOE.4.000077


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Abstract

Skin aging is an important issue in geriatric and cosmetic dermatology. To quantitatively analyze changes in keratinocytes related to intrinsic aging, we exploited a 1230 nm-based in vivo harmonic generation microscopy, combining second- and third-harmonic generation modalities. 52 individuals (21 men and 31 women, age range 19–79) were examined on the sun-protected volar forearm. Through quantitative analysis by the standard algorithm provided, we found that the cellular and nuclear size of basal keratinocytes, but not that of granular cells, was significantly increased with advancing age. The cellular and nuclear areas, which have an increase of 0.51 μm2 and 0.15 μm2 per year, respectively, can serve as scoring indices for intrinsic skin aging.

© 2012 OSA

1. Introduction

2. Materials and methods

2.1. Study population

2.2. Cr:F-based HGB system

The HGB system as previously described was adapted from a commercial confocal scanning system (FV300, Olympus, Tokyo, Japan) combined with an inverted microscope (IX71, Olympus, Tokyo, Japan; Fig. 1(a)
Fig. 1 (a) A schema of a 1230 nm-based HGB system adapted from a commercial confocal scanning system combined with an inverted microscope; DBS: dichroic beam splitter; CF: color filter; BF: band-pass filter; PMT: photomultiplier tube. (b) Sketch of a home-designed vacuum-pump plate used for sample stabilization; IW: imaging window; C: circular intaglio. (c) The implementation of the vacuum-pump plate which is combined with sample stage of inverted microscope.
) [16

16. S.-Y. Chen, S.-U. Chen, H.-Y. Wu, W.-J. Lee, Y.-H. Liao, and C.-K. Sun, “In vivo virtual biopsy of human skin by using noninvasive higher harmonic generation microscopy,” IEEE J. Sel. Top. Quantum Electron. 16(3), 478–492 (2010). [CrossRef]

]. A 1230 nm femtosecond Cr-F laser was used for excitation to lessen skin attenuation [18

18. T.-M. Liu, S.-W. Chu, C.-K. Sun, B.-L. Lin, P. C. Cheng, and I. Johnson, “Multiphoton confocal microscopy using a femtosecond Cr:forsterite laser,” Scanning 23(4), 249–254 (2001). [CrossRef] [PubMed]

20

20. M.-C. Chan, T.-M. Liu, S.-P. Tai, and C.-K. Sun, “Compact fiber-delivered Cr:forsterite laser for nonlinear light microscopy,” J. Biomed. Opt. 10(5), 054006 (2005). [CrossRef] [PubMed]

]. Using this system, a submicron and 1 μm resolution in lateral and axial directions and a >300 μm penetrability were achieved [16

16. S.-Y. Chen, S.-U. Chen, H.-Y. Wu, W.-J. Lee, Y.-H. Liao, and C.-K. Sun, “In vivo virtual biopsy of human skin by using noninvasive higher harmonic generation microscopy,” IEEE J. Sel. Top. Quantum Electron. 16(3), 478–492 (2010). [CrossRef]

,17

17. S. Y. Chen, H. Y. Wu, and C.-K. Sun, “In vivo harmonic generation biopsy of human skin,” J. Biomed. Opt. 14(6), 060505 (2009). [CrossRef] [PubMed]

].

2.3. Skin-stabilization device

2.4. Imaging protocols

In the HGB imaging, horizontal sections were obtained instead of vertical sections. By moving the objective in the z direction, stacks of image versus depth (XYZ) beginning from the stratum corneum, through the epidermis, and to the upper dermis were obtained for analysis. Five-μm step size was used. The image frame rate was 2.7 seconds per frame with 512 × 512 pixels. The image dimensions were approximately 120 μm × 120 μm.

2.5. Damage evaluation

2.6. Analysis protocols

To reveal morphological features of granular and basal cells, analysis was performed on THG images obtained from the stratum granulosum and stratum basale. For the NC ratio analysis of basal cells and granular cells, at least 2 images (per volunteer) with the majority of cells sectioned were chosen. In each image, all the sectioned cells with nuclei were selected, and the total cytoplasmic and nuclear area was obtained by summing the individual cytoplasmic and nuclear area. The volumic NC ratio was obtained by dividing the total nuclear area by the total cytoplasmic area. For the analysis of the cellular and nuclear size of basal cells, at least 3 images (per volunteer) with the majority of basal cells with nuclei sectioned were chosen; in each image, the first 5-10 cells with the largest cross-section were selected for measuring the cell and nucleus areas and at least 25 cells were selected for each volunteer. For the analysis of the cellular and nuclear size of granular cells, at least 2 images (per volunteer) with the majority of granular cells sectioned were chosen; in each image, all cells were selected for measuring the cell and nucleus areas and at least 25 cells were selected for each volunteer. These criteria were to avoid measuring an off-centered cross-section area of the cell and the nucleus. These cellular parameters were evaluated by three independent observers.

2.7. Statistical analysis

The result of the cellular and nuclear size was expressed as mean ± standard deviation. The value of correlation coefficient between age and cellular/nuclear size was calculated using a Pearson linear regression model. One-way analysis of variance (ANOVA) or Kruskal-Wallis test was used for comparisons among three age groups. Statistics were performed with the SPSS 12.0 software (SPSS Inc., Chicago, IL), and P < 0.05 was considered statistically significant.

3. Results

3.1. In vivo HGB imaging of human skin

3.2. In vivo analysis of age-dependent alterations of granular cells

3.3. In vivo analysis of age-dependent alterations of basal cells

Figure 4
Fig. 4 Four representative in vivo THG images of epidermal basal cells obtained from the volar forearm of (a) 24-, (b) 39-, (c) 56-, and (d) 74-year-old volunteers. The widened THG-dark intercellular spaces between basal keratinocytes were indicated by arrows in (b-d). Scale bar = 50 μm.
showed representative in vivo THG images obtained at the basal layer of forearm skin from four differently-aged volunteers (24, 39, 56, and 74 years old, respectively). Comparing these four images, a more highly organized honeycomb structure of basal cells could be observed in the young skin (Fig. 4(a)), where the basal cells were in a regular oval shape. In contrast, basal cells in the older skin became irregular in shape and gradually lost the organized structures (Fig. 4(b)-(d)). In the stratum basale, the THG-dark intercellular spaces between basal keratinocytes in the aged skin (arrows in Fig. 4(b)-(d)) were wider and more irregular in width than those observed in the young group (Fig. 4(a)). It was found that the cellular and nuclear size seemed to be larger in the elderly comparing to the young subjects. In order to quantify these morphological observations, cytological analysis was performed on the THG images to reveal the correlation between the cellular/nuclear size and aging.

By using the algorithm given in Materials and methods, the cellular and nuclear size of the basal cells was analyzed from in vivo THG images of 52 healthy subjects, as revealed in Fig. 4. We found that the average area of the basal cell and its nucleus increased with advancing age. The average area of the basal cell was 48.2 ± 3.98 μm2 at the age of 19-29 years, 60.2 ± 6.74 μm2 at 30-59 years, and increased to 70.7 ± 6.47 μm2 at 60-79 years (Fig. 5(a)
Fig. 5 The cellular size (a), nuclear size (c), and NC ratio (e) of the basal cells. A significant positive correlation was shown between age and the cellular area (b; correlation coefficient r = 0.940) as well as between age and the nuclear area (d; correlation coefficient r = 0.911) of basal cells; **P < 0.0001. No significant correlation was found between age and NC ratio (f); NS, no significance.
). A strong positive correlation was observed between the cellular size and age (Fig. 5(b); Pearson correlation coefficient r = 0.940). On the other hand, as shown in Fig. 5(c), the average area of the nucleus was 13.4 ± 1.72 μm2 at the age of 19-29 years, 15.8 ± 2.97 μm2 at 30-59 years, and increased to 20.1 ± 2.79 μm2 at 60-79 years. A strong positive correlation was also observed between the nuclear size and age (Fig. 5(d); r = 0.911). Based on the linear regression equations, the average area of cell = 36.18 + 0.51 × age and the average area of nucleus = 9.82 + 0.15 × age, indicating that the cellular area increased 0.51 μm2 and the nuclear area increased 0.15 μm2 per year. The one-way ANOVA analysis also showed a statistically significant difference in the cellular and nuclear size among these three different-aged groups (Figs. 5(a) and 5(c); P < 0.0001). Besides, greater standard deviation of the cellular and nuclear size was found in subjects over 30 years old (Figs. 5(a) and 5(c), vertical bars), which suggested that the basal cells and their nuclei became polymorphic and increased in heterogeneity with advancing age.

In addition to the analysis of the cellular and nuclear size, the volumic NC ratio of the basal cells from each subject was analyzed. From Fig. 5(e), it was found that the NC ratio remained consistent among different-aged groups. The NC ratio of basal cell was 0.35 ± 0.022 at the age of 19-29 years, 0.35 ± 0.013 at 30-59 years, and 0.35 ± 0.016 at 60-79 years, as shown in Fig. 5(f). The average NC ratio of basal cells from all the subjects was 0.35 ± 0.018. Comparing among these three different-aged groups, there was no statistically significant age-dependent difference in the NC ratio of basal cells (one-way ANOVA; P > 0.05). The cellular size, nuclear size, and NC ratio of basal keratinocytes among these three different-aged groups were summarized in Table 1. Taken altogether, we found that the cellular and nuclear size of basal keratinocytes, but not that of granular cells, was significantly increased with advancing age.

Moreover, we found that there were no significant gender differences in the cellular and nuclear size of the basal cells (Student’s t-test; P > 0.05, respectively). The average area of the basal cell was 57.3 ± 10.97 μm2 in women and 58.9 ± 10.59 μm2 in men. The average area of the nucleus was 15.7 ± 3.18 μm2 in women and 16.2 ± 3.39 μm2 in men. In addition, according to the linear regression analysis, strong positive correlations were observed between the cellular size and age in female (Fig. 6(a)
Fig. 6 The cellular (a, b) and nuclear size (c, d) of the basal cells in female and male subjects. A significant positive correlation was shown between age and the cellular area as well as between age and the nuclear area in female (a and c) and male subjects (b and d). r, correlation coefficient.
; Pearson correlation coefficient r = 0.923) and male subjects (Fig. 6(b); r = 0.956), respectively. A statistically significant linear relationship was also found between the nuclear size and age in both female (Fig. 6(c); r = 0.883) and male subjects (Fig. 6(d); r = 0.924). The above results showed that the positive correlation of cellular/nuclear size of basal keratinocytes and age did not differ by gender.

4. Discussion and conclusion

The small deviation of the NC ratio for each volunteer indicated a good consistency of the analysis protocol based on THG imaging. According to our results, the NC ratio remained consistent in differently-aged skin. Koehler et al. also showed no difference of the NC ratio between different age groups [28

28. M. J. Koehler, S. Zimmermann, S. Springer, P. Elsner, K. König, and M. Kaatz, “Keratinocyte morphology of human skin evaluated by in vivo multiphoton laser tomography,” Skin Res. Technol. 17(4), 479–486 (2011). [CrossRef] [PubMed]

]. However, when malignant transformation like actinic keratoses occurred, we observed that the NC ratio of keratinocyte became significantly higher comparing to normal skin [16

16. S.-Y. Chen, S.-U. Chen, H.-Y. Wu, W.-J. Lee, Y.-H. Liao, and C.-K. Sun, “In vivo virtual biopsy of human skin by using noninvasive higher harmonic generation microscopy,” IEEE J. Sel. Top. Quantum Electron. 16(3), 478–492 (2010). [CrossRef]

,28

28. M. J. Koehler, S. Zimmermann, S. Springer, P. Elsner, K. König, and M. Kaatz, “Keratinocyte morphology of human skin evaluated by in vivo multiphoton laser tomography,” Skin Res. Technol. 17(4), 479–486 (2011). [CrossRef] [PubMed]

].

We also observed that some intercellular spaces between individual basal cell became widened as skin aged. Similar findings of widened inter-keratinocyte spaces have been found in sun-protected skin in some extent through electron microscopy analysis [32

32. M. Yaar and B. Gilchrest, “Aging of skin,” in Fitzpatrick’s Dermatology in General Medicine, I. M. Freedberg, A. Z. Eisen, K. Wolff, K. F. Austen, L. A. Goldsmith, and S. I. Katz, eds. (McGraw-Hill, New York, 2003), pp 1386–1398.

]. This THG-revealed change of the intercellular spaces implies that the connection between the basal cells becomes looser and would contribute to the fragility of aged skin. Further studies are required to clarify this observatory phenomenon.

This study involves the application of in vivo HGB to investigate morphological changes of keratinocytes associated with intrinsic skin aging. Compared to the multiphoton fluorescence technique, SHG and THG leave almost no energy in the interacted matters and possess the noninvasiveness nature [33

33. E. Brown, T. McKee, E. diTomaso, A. Pluen, B. Seed, Y. Boucher, and R. K. Jain, “Dynamic imaging of collagen and its modulation in tumors in vivo using second-harmonic generation,” Nat. Med. 9(6), 796–801 (2003). [CrossRef] [PubMed]

]. From this research, the cellular and nuclear size of basal keratinocytes is found to be good indices for scoring intrinsic skin aging. Take advantage of its histologic resolution to analyze cellular size, nuclear size as well as NC ratios in epidermal keratinocytes, HGB is applicable to identify actinic keratosis, Bowen’s disease, squamous cell carcinoma, and basal cell carcinoma. Combining the noninvasive nature, high resolution, high penetration, safety and the three-dimensional sectioning power of THG microscopy, in vivo HGB is expected to become a new methodology in future dermatological clinical diagnosis, serial evaluation of treatment, and cosmetic research.

Acknowledgments

We thank Y. S. Tseng (Department of Dermatology, National Taiwan University Hospital) for statistical analysis. This project was supported by the National Health Research Institute (NHRI-EX99-9936EI and NHRI-EX100-9936EI), National Science Council (NSC 100-2120-M-002-009), and Molecular Imaging Center, National Taiwan University.

References and links

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M. A. Farage, K. W. Miller, P. Elsner, and H. I. Maibach, “Intrinsic and extrinsic factors in skin ageing: a review,” Int. J. Cosmet. Sci. 30(2), 87–95 (2008). [CrossRef] [PubMed]

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E. M. Buckingham and A. J. Klingelhutz, “The role of telomeres in the ageing of human skin,” Exp. Dermatol. 20(4), 297–302 (2011). [CrossRef] [PubMed]

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M. Sugimoto, R. Yamashita, and M. Ueda, “Telomere length of the skin in association with chronological aging and photoaging,” J. Dermatol. Sci. 43(1), 43–47 (2006). [CrossRef] [PubMed]

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S. I. S. Rattan, “Aging of skin cells in culture,” in Textbook of Aging Skin, M. A. Farage, K. W. Miller, and H. I. Maibach, eds. (Springer-Verlag, Heidelberg, 2010), pp. 487–492.

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N. A. Fenske and C. W. Lober, “Structural and functional changes of normal aging skin,” J. Am. Acad. Dermatol. 15(4), 571–585 (1986). [CrossRef] [PubMed]

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M. El-Domyati, S. Attia, F. Saleh, D. Brown, D. E. Birk, F. Gasparro, H. Ahmad, and J. Uitto, “Intrinsic aging vs. photoaging: a comparative histopathological, immunohistochemical, and ultrastructural study of skin,” Exp. Dermatol. 11(5), 398–405 (2002). [CrossRef] [PubMed]

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B. A. Gilchrest, “Skin aging and photoaging: an overview,” J. Am. Acad. Dermatol. 21(3), 610–613 (1989). [CrossRef] [PubMed]

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M. Gniadecka and G. B. Jemec, “Quantitative evaluation of chronological ageing and photoageing in vivo: studies on skin echogenicity and thickness,” Br. J. Dermatol. 139(5), 815–821 (1998). [CrossRef] [PubMed]

10.

J. M. Waller and H. I. Maibach, “Age and skin structure and function, a quantitative approach (I): blood flow, pH, thickness, and ultrasound echogenicity,” Skin Res. Technol. 11(4), 221–235 (2005). [CrossRef] [PubMed]

11.

S. Sakai, M. Yamanari, A. Miyazawa, M. Matsumoto, N. Nakagawa, T. Sugawara, K. Kawabata, T. Yatagai, and Y. Yasuno, “In vivo three-dimensional birefringence analysis shows collagen differences between young and old photo-aged human skin,” J. Invest. Dermatol. 128(7), 1641–1647 (2008). [CrossRef] [PubMed]

12.

S. Neerken, G. W. Lucassen, M. A. Bisschop, E. Lenderink, and T. A. Nuijs, “Characterization of age-related effects in human skin: A comparative study that applies confocal laser scanning microscopy and optical coherence tomography,” J. Biomed. Opt. 9(2), 274–281 (2004). [CrossRef] [PubMed]

13.

M. J. Koehler, K. König, P. Elsner, R. Bückle, and M. Kaatz, “In vivo assessment of human skin aging by multiphoton laser scanning tomography,” Opt. Lett. 31(19), 2879–2881 (2006). [CrossRef] [PubMed]

14.

M. J. Koehler, S. Hahn, A. Preller, P. Elsner, M. Ziemer, A. Bauer, K. König, R. Bückle, J. W. Fluhr, and M. Kaatz, “Morphological skin ageing criteria by multiphoton laser scanning tomography: non-invasive in vivo scoring of the dermal fibre network,” Exp. Dermatol. 17(6), 519–523 (2008). [CrossRef] [PubMed]

15.

C. Longo, A. Casari, F. Beretti, A. M. Cesinaro, and G. Pellacani, “Skin aging: in vivo microscopic assessment of epidermal and dermal changes by means of confocal microscopy,” J. Am. Acad. Dermatol. (2011). [CrossRef] [PubMed]

16.

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17.

S. Y. Chen, H. Y. Wu, and C.-K. Sun, “In vivo harmonic generation biopsy of human skin,” J. Biomed. Opt. 14(6), 060505 (2009). [CrossRef] [PubMed]

18.

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26.

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28.

M. J. Koehler, S. Zimmermann, S. Springer, P. Elsner, K. König, and M. Kaatz, “Keratinocyte morphology of human skin evaluated by in vivo multiphoton laser tomography,” Skin Res. Technol. 17(4), 479–486 (2011). [CrossRef] [PubMed]

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30.

Y. Soroka, Z. Ma’or, Y. Leshem, L. Verochovsky, R. Neuman, F. M. Brégégère, and Y. Milner, “Aged keratinocyte phenotyping: morphology, biochemical markers and effects of Dead Sea minerals,” Exp. Gerontol. 43(10), 947–957 (2008). [CrossRef] [PubMed]

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32.

M. Yaar and B. Gilchrest, “Aging of skin,” in Fitzpatrick’s Dermatology in General Medicine, I. M. Freedberg, A. Z. Eisen, K. Wolff, K. F. Austen, L. A. Goldsmith, and S. I. Katz, eds. (McGraw-Hill, New York, 2003), pp 1386–1398.

33.

E. Brown, T. McKee, E. diTomaso, A. Pluen, B. Seed, Y. Boucher, and R. K. Jain, “Dynamic imaging of collagen and its modulation in tumors in vivo using second-harmonic generation,” Nat. Med. 9(6), 796–801 (2003). [CrossRef] [PubMed]

OCIS Codes
(110.0180) Imaging systems : Microscopy
(170.1530) Medical optics and biotechnology : Cell analysis
(170.1610) Medical optics and biotechnology : Clinical applications
(170.1870) Medical optics and biotechnology : Dermatology
(170.3880) Medical optics and biotechnology : Medical and biological imaging
(190.4160) Nonlinear optics : Multiharmonic generation

ToC Category:
Dermatological Applications

History
Original Manuscript: September 10, 2012
Revised Manuscript: October 29, 2012
Manuscript Accepted: October 30, 2012
Published: December 13, 2012

Citation
Yi-Hua Liao, Szu-Yu Chen, Sin-Yo Chou, Pei-Hsun Wang, Ming-Rung Tsai, and Chi-Kuang Sun, "Determination of chronological aging parameters in epidermal keratinocytes by in vivo harmonic generation microscopy," Biomed. Opt. Express 4, 77-88 (2013)
http://www.opticsinfobase.org/boe/abstract.cfm?URI=boe-4-1-77


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References

  1. M. A. Farage, K. W. Miller, P. Elsner, and H. I. Maibach, “Intrinsic and extrinsic factors in skin ageing: a review,” Int. J. Cosmet. Sci.30(2), 87–95 (2008). [CrossRef] [PubMed]
  2. K.-I. Nakamura, N. Izumiyama-Shimomura, M. Sawabe, T. Arai, Y. Aoyagi, M. Fujiwara, E. Tsuchiya, Y. Kobayashi, M. Kato, M. Oshimura, K. Sasajima, K. Nakachi, and K. Takubo, “Comparative analysis of telomere lengths and erosion with age in human epidermis and lingual epithelium,” J. Invest. Dermatol.119(5), 1014–1019 (2002). [CrossRef] [PubMed]
  3. E. M. Buckingham and A. J. Klingelhutz, “The role of telomeres in the ageing of human skin,” Exp. Dermatol.20(4), 297–302 (2011). [CrossRef] [PubMed]
  4. M. Sugimoto, R. Yamashita, and M. Ueda, “Telomere length of the skin in association with chronological aging and photoaging,” J. Dermatol. Sci.43(1), 43–47 (2006). [CrossRef] [PubMed]
  5. S. I. S. Rattan, “Aging of skin cells in culture,” in Textbook of Aging Skin, M. A. Farage, K. W. Miller, and H. I. Maibach, eds. (Springer-Verlag, Heidelberg, 2010), pp. 487–492.
  6. N. A. Fenske and C. W. Lober, “Structural and functional changes of normal aging skin,” J. Am. Acad. Dermatol.15(4), 571–585 (1986). [CrossRef] [PubMed]
  7. M. El-Domyati, S. Attia, F. Saleh, D. Brown, D. E. Birk, F. Gasparro, H. Ahmad, and J. Uitto, “Intrinsic aging vs. photoaging: a comparative histopathological, immunohistochemical, and ultrastructural study of skin,” Exp. Dermatol.11(5), 398–405 (2002). [CrossRef] [PubMed]
  8. B. A. Gilchrest, “Skin aging and photoaging: an overview,” J. Am. Acad. Dermatol.21(3), 610–613 (1989). [CrossRef] [PubMed]
  9. M. Gniadecka and G. B. Jemec, “Quantitative evaluation of chronological ageing and photoageing in vivo: studies on skin echogenicity and thickness,” Br. J. Dermatol.139(5), 815–821 (1998). [CrossRef] [PubMed]
  10. J. M. Waller and H. I. Maibach, “Age and skin structure and function, a quantitative approach (I): blood flow, pH, thickness, and ultrasound echogenicity,” Skin Res. Technol.11(4), 221–235 (2005). [CrossRef] [PubMed]
  11. S. Sakai, M. Yamanari, A. Miyazawa, M. Matsumoto, N. Nakagawa, T. Sugawara, K. Kawabata, T. Yatagai, and Y. Yasuno, “In vivo three-dimensional birefringence analysis shows collagen differences between young and old photo-aged human skin,” J. Invest. Dermatol.128(7), 1641–1647 (2008). [CrossRef] [PubMed]
  12. S. Neerken, G. W. Lucassen, M. A. Bisschop, E. Lenderink, and T. A. Nuijs, “Characterization of age-related effects in human skin: A comparative study that applies confocal laser scanning microscopy and optical coherence tomography,” J. Biomed. Opt.9(2), 274–281 (2004). [CrossRef] [PubMed]
  13. M. J. Koehler, K. König, P. Elsner, R. Bückle, and M. Kaatz, “In vivo assessment of human skin aging by multiphoton laser scanning tomography,” Opt. Lett.31(19), 2879–2881 (2006). [CrossRef] [PubMed]
  14. M. J. Koehler, S. Hahn, A. Preller, P. Elsner, M. Ziemer, A. Bauer, K. König, R. Bückle, J. W. Fluhr, and M. Kaatz, “Morphological skin ageing criteria by multiphoton laser scanning tomography: non-invasive in vivo scoring of the dermal fibre network,” Exp. Dermatol.17(6), 519–523 (2008). [CrossRef] [PubMed]
  15. C. Longo, A. Casari, F. Beretti, A. M. Cesinaro, and G. Pellacani, “Skin aging: in vivo microscopic assessment of epidermal and dermal changes by means of confocal microscopy,” J. Am. Acad. Dermatol. (2011). [CrossRef] [PubMed]
  16. S.-Y. Chen, S.-U. Chen, H.-Y. Wu, W.-J. Lee, Y.-H. Liao, and C.-K. Sun, “In vivo virtual biopsy of human skin by using noninvasive higher harmonic generation microscopy,” IEEE J. Sel. Top. Quantum Electron.16(3), 478–492 (2010). [CrossRef]
  17. S. Y. Chen, H. Y. Wu, and C.-K. Sun, “In vivo harmonic generation biopsy of human skin,” J. Biomed. Opt.14(6), 060505 (2009). [CrossRef] [PubMed]
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