A plea for standardization of confocal microscopy and optical coherence tomography parameters to evaluate physiological and para-physiological skin conditions in cosmetic science.
cosmetic
evaluation methodology
optical coherence tomography
reflectance confocal microscopy
skin
Journal
Experimental dermatology
ISSN: 1600-0625
Titre abrégé: Exp Dermatol
Pays: Denmark
ID NLM: 9301549
Informations de publication
Date de publication:
07 2021
07 2021
Historique:
revised:
17
03
2021
received:
15
01
2021
accepted:
07
04
2021
pubmed:
23
4
2021
medline:
19
3
2022
entrez:
22
4
2021
Statut:
ppublish
Résumé
Non-invasive reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) have been extended to the dermo-cosmetic field, for skin pathophysiology understanding and therapeutics monitoring. However, standardized methodology and parameters to interpret structures and changes in these settings are still lacking. Present study aimed to propose a validated standard methodology and a list of defined parameters for objective non-pathological skin assessments in the cosmetically sensitive cheekbone area of the face. OCT and RCM quantitative, semi-quantitative and qualitative features were considered for assessments. Validation process included 50 sets of images divided into two age groups. Inter-rater reliability was explored to assess the influence of the proposed methodology. Quantitative OCT parameters of "epidermal thickness," "density and attenuation coefficients" and "vascular density" were considered and calculated. Severity scales were developed for semi-quantitative OCT features of "disruption of collagen" and "vascular asset," while extent scales were produced for semi-quantitative RCM "irregular honeycomb," "mottled pigmentation" and "polycyclic papillary contours." Qualitative assessment was obtained for RCM type of collagen, and comparison between age groups was performed for all features considered. Severity visual scales assistance proved excellent inter-rater agreement across all semi-quantitative and qualitative domains. The assistance of shareable software systems allows for objective OCT quantitative parameters measurement. The use of standard reference scales, within a defined assessment methodology, offers high inter-rater reliability and thus reproducibility for semi-quantitative and qualitative OCT and RCM parameters. Taken together, our results may represent a starting point for a standardized application of RCM and OCT in dermo-cosmetic research and practice.
Substances chimiques
Cosmetics
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
911-922Informations de copyright
© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Références
Kislevitz M, Lu KB, Wamsley C, Hoopman J, Kenkel J, Akgul Y. Novel use of non-invasive devices and microbiopsies to assess facial skin rejuvenation following laser treatment. Lasers Surg Med. 2020;52:822-830.
Longo C, Galimberti M, De Pace B, Pellacani G, Bencini PL. Laser skin rejuvenation: epidermal changes and collagen remodeling evaluated by in vivo confocal microscopy. Lasers Med Sci. 2013;28:769-776.
Longo C, Pellacani G, Tourlaki A, Galimberti M, Bencini PL. Melasma and low-energy Q-switched laser: treatment assessment by means of in vivo confocal microscopy. Lasers Med Sci. 2014;29:1159-1163.
Kunzi-Rapp K, Dierickx CC, Cambier B, Drosner M. Minimally invasive skin rejuvenation with Erbium: YAG laser used in thermal mode. Lasers Surg Med. 2006;38:899-907.
Guida S, Galimberti MG, Bencini M, Pellacani G, Bencini PL. Treatment of striae distensae with non-ablative fractional laser: clinical and in vivo microscopic documentation of treatment efficacy. Lasers Med Sci. 2018;33:75-78.
Guida S, Pellacani G, Bencini PL. Picosecond laser treatment of atrophic and hypertrophic surgical scars: in vivo monitoring of results by means of 3D imaging and reflectance confocal microscopy. Skin Res Technol. 2019;25:896-902.
Rovatti PP, Pellacani G, Guida S. Hyperdiluted calcium hydroxylapatite 1: 2 for mid and lower facial skin rejuvenation: efficacy and safety. Dermatol Surg. 2020;46:e112-e117.
Bayliss SE, Takwoingi Y, Davenport C, et al. High-frequency ultrasound for diagnosing skin cancer in adults. Cochrane Database Syst Rev. 2018;12:CD013188.
Bhatta AK, Keyal U, Liu Y. Application of high frequency ultrasound in dermatology. Discov Med. 2018;26(145):237-242.
Malvehy J, Pellacani G. Dermoscopy, confocal microscopy and other non-invasive tools for the diagnosis of non-melanoma skin cancers and other skin conditions. Acta Derm Venereol. 2017;218:22-30. https://doi.org/10.2340/00015555-2720
Benati E, Bellini V, Borsari S, et al. Quantitative evaluation of healthy epidermis by means of multiphoton microscopy and fluorescence lifetime imaging microscopy. Skin Res Technol. 2011;17:295-303.
Seidenari S, Arginelli F, Bassoli S, et al. Multiphoton laser microscopy and fluorescence lifetime imaging for the evaluation of the skin. Dermatol Res Pract. 2012;2012:810749. Epub 2011 Nov 28.
Pan ZY, Dong DK, Chen SJ, Lu LY, Hu TT, Ju Q. In vivo reflectance confocal microscopy in daily practice: image features correlated to histopathology. Skin Res Technol. 2018;24:223-228.
Pellacani G, Ulrich M, Casari A, et al. Grading keratinocyte atypia in actinic keratosis: a correlation of reflectance confocal microscopy and histopathology. J Eur Acad Dermatol Venereol. 2015;29:2216-2221.
Pedrazzani M, Breugnot J, Rouaud-Tinguely P, et al. Comparison of line-field confocal optical coherence tomography images with histological sections: validation of a new method for in vivo and non-invasive quantification of superficial dermis thickness. Skin Res Technol. 2020;26:398-404.
Themstrup L, De Carvalho N, Nielsen SM, et al. In vivo differentiation of common basal cell carcinoma subtypes by microvascular and structural imaging using dynamic optical coherence tomography. Exp Dermatol. 2018;27:156-165.
Garbarino F, Migliorati S, Farnetani F, et al. Nodular skin lesions: correlation of reflectance confocal microscopy and optical coherence tomography features. J Eur Acad Dermatol Venereol. 2020;34:101-111.
Dorrell DN, Strowd LC. Skin cancer detection technology. Dermatol Clin. 2019;37:527-536.
Segura S, Pellacani G, Puig S, et al. In vivo microscopic features of nodular melanomas: dermoscopy, confocal microscopy, and histopathologic correlates. Arch Dermatol. 2008;144:1311-1320.
Scope A, Benvenuto-Andrade C, Agero AL, et al. In vivo reflectance confocal microscopy imaging of melanocytic skin lesions: consensus terminology glossary and illustrative images. J Am Acad Dermatol. 2007;57:644-658.
Wurm EM, Curchin CE, Lambie D, et al. Confocal features of equivocal facial lesions on severely sun-damaged skin: four case studies with dermatoscopic, confocal, and histopathologic correlation. J Am Acad Dermatol. 2012;66:463-473.
Boone MA, Marneffe A, Suppa M, et al. High-definition optical coherence tomography algorithm for the discrimination of actinic keratosis from normal skin and from squamous cell carcinoma. J Eur Acad Dermatol Venereol. 2015;29:1606-1615.
Boone MA, Suppa M, Pellacani G, et al. High-definition optical coherence tomography algorithm for discrimination of basal cell carcinoma from clinical BCC imitators and differentiation between common subtypes. J Eur Acad Dermatol Venereol. 2015;29:1771-1780.
Moraes Pinto Blumetti TC, Cohen MP, Gomes EE, et al. Optical coherence tomography (OCT) features of nevi and melanomas and their association with intraepidermal or dermal involvement: a pilot study. J Am Acad Dermatol. 2015;73:315-317.
Agozzino M, Gonzalez S, Ardigò M. Reflectance confocal microscopy for inflammatory skin diseases. Actas Dermosifiliogr. 2016;107:631-639.
Guida S, Ciardo S, De Pace B, et al. The influence of MC1R on dermal morphological features of photo-exposed skin in women revealed by reflectance confocal microscopy and optical coherence tomography. Exp Dermatol. 2019;28:1321-1327.
Ulrich M, Themstrup L, de Carvalho N, et al. Dynamic optical coherence tomography in dermatology. Dermatology. 2016;232:298-311.
Schuh S, Holmes J, Ulrich M, et al. Imaging blood vessel morphology in skin: dynamic optical coherence tomography as a novel potential diagnostic tool in dermatology. Dermatol Ther. 2017;7:187-202.
Manfredini M, Mazzaglia G, Ciardo S, et al. Does skin hydration influence keratinocyte biology? In vivo evaluation of microscopic skin changes induced by moisturizers by means of reflectance confocal microscopy. Skin Res Technol. 2013;19:299-307.
Themstrup L, Ciardo S, Manfredi M, et al. In vivo, micro-morphological vascular changes induced by topical brimonidine studied by Dynamic optical coherence tomography. J Eur Acad Dermatol Venereol. 2016;30:974-979.
Vasquez-Pinto LM, Maldonado EP, Raele MP, Amaral MM, de Freitas AZ. Optical coherence tomography applied to tests of skin care products in humans:a case study. Skin Res Technol. 2015;21:90-93.
Jung S, Lademann J, Darvin ME, et al. In vivo characterization of structural changes after topical application of glucocorticoids in healthy human skin. J Biomed Opt. 2017;22:76018.
Shlivko IL, Kamensky VA, Donchenko EV, Agrba P. Morphological changes in skin of different phototypes under the action of topical corticosteroid therapy and tacrolimus. Skin Res Technol. 2014;20:136-140.
Manfredini M, Greco M, Farnetani F, et al. In vivo monitoring of topical therapy for acne with reflectance confocal microscopy. Skin Res Technol. 2017;23:36-40.
Casari A, Farnetani F, De Pace B, et al. In vivo assessment of cytological changes by means of reflectance confocal microscopy: demonstration of the effect of topical vitamin E on skin irritation caused by sodium lauryl sulfate. Contact Dermatitis. 2017;76:131-137.
Themstrup L, Welzel J, Ciardo S, et al. Validation of Dynamic optical coherence tomography for non-invasive, in vivo microcirculation imaging of the skin. Microvasc Res. 2016;107:97-105.
Manfredi M, Grana C, Pellacani G. Skin surface reconstruction and 3D vessels segmentation in speckle variance of optical coherence tomography. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) SCITEPRESS - Science and Technology Publications, Lda. 2016;4:234-240.
Rajadhyaksha M, Grossman M, Esterowitz D, et al. In vivo confocal scanning laser microscopy of human skin: melanin provides strong contrast. J Invest Dermatol. 1995;104:946-952.
Pellacani G, Guitera P, Longo C, et al. The impact of in vivo reflectance confocal microscopy for the diagnostic accuracy of melanoma and equivocal melanocytic lesions. J Invest Dermatol. 2007;127:2759-2765.
Yücel D, Themstrup L, Manfredi M, Jemec GB. Optical coherence tomography of basal cell carcinoma: density and signal attenuation. Skin Res Technol. 2016;22:497-504.
Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15:155-163.
Aractingi S, Pellacani G. Computational neural network in melanocytic lesions diagnosis: artificial intelligence to improve diagnosis in dermatology? Eur J Dermatol. 2019;29:4-7.
O'Leary S, Fotouhi A, Turk D, et al. OCT image atlas of healthy skin on sun-exposed areas. Skin Res Technol. 2018;24:570-586.
Welzel J, Reinhardt C, Lankenau E, Winter C, Wolff HH. Changes in function and morphology of normal human skin: evaluation using optical coherence tomography. Br J Dermatol. 2004;150:220-225.
Longo C, Ciardo S, Pellacani G. Non-invasive, investigative methods in skin aging. G Ital Dermatol Venereol. 2015;150:675-686.
Longo C, Casari A, Beretti F, Cesinaro AM, Pellacani G. Skin aging: in vivo microscopic assessment of epidermal and dermal changes by means of confocal microscopy. J Am Acad Dermatol. 2013;68:e73-82.
Longo C, Casari A, De Pace B, Simonazzi S, Mazzaglia G, Pellacani G. Proposal for an in vivo histopathologic scoring system for skin aging by means of confocal microscopy. Skin Res Technol. 2013;19:e167-e173.
Newton VL, Mcconnell JC, Hibbert SA, Graham HK, Watson RE. Skin aging: molecular pathology, dermal remodelling and the imaging revolution. G Ital Dermatol Venereol. 2015;150:665-674.
Trojahn C, Dobos G, Richter C, Blume-Peytavi U, Kottner J. Measuring skin aging using optical coherence tomography in vivo: a validation study. J Biomed Opt. 2015;20:45003.
Boone MA, Suppa M, Marneffe A, Miyamoto M, Jemec GB, Del Marmol V. High-definition optical coherence tomography intrinsic skin ageing assessment in women: a pilot study. Arch Dermatol Res. 2015;307:705-720.
Hara Y, Yamashita T, Kikuchi K, et al. Visualization of age-related vascular alterations in facial skin using optical coherence tomography-based angiography. J Dermatol Sci. 2018;90:96-98.
Querleux B, Baldeweck T, Diridollou S, et al. Skin from various ethnic origins and aging: an in vivo cross-sectional multimodality imaging study. Skin Res Technol. 2009;15:306-313.
Neerken S, Lucassen GW, Bisschop MA, Lenderink E, Nuijs TA. Characterization of age-related effects in human skin: a comparative study that applies confocal laser scanning microscopy and optical coherence tomography. J Biomed Opt. 2004;9:274-281.
Tsugita T, Nishijima T, Kitahara T, Takema Y. Positional differences and aging changes in Japanese woman epidermal thickness and corneous thickness determined by OCT (optical coherence tomography). Skin Res Technol. 2013;19:242-250.
Guida S, Ciardo S, De Pace B, et al. Atrophic and hypertrophic skin photoaging and melanocortin-1 receptor (MC1R): the missing link. J Am Acad Dermatol. 2020;23.
Shlivko IL, Petrova GA, Zor'kina MV, et al. Complex assessment of age-specific morphofunctional features of skin of different anatomic localizations. Skin Res Technol. 2013;19:e85-92.