Literature DB >> 31965207

[New optical examination procedures for the diagnosis of skin diseases].

K Sies1, J K Winkler1, M Zieger2, M Kaatz2, H A Haenssle3.   

Abstract

BACKGROUND: Since the establishment of dermoscopy as a routine examination procedure in dermatology, the spectrum of noninvasive, optical devices has further expanded. In difficult-to-diagnose clinical cases, these systems may support dermatologists to arrive at a correct diagnosis without the need for a surgical biopsy.
OBJECTIVE: To give an overview about technical background, indications and diagnostic performance regarding four new optical procedures: reflectance confocal microscopy, in vivo multiphoton tomography, dermatofluoroscopy, and systems based on image analysis by artificial intelligence (AI).
MATERIALS AND METHODS: This article is based on a selective review of the literature, as well as the authors' personal experience from clinical studies relevant for market approval of the devices.
RESULTS: In contrast to standard histopathological slides with vertical cross sections, reflectance confocal microscopy and in vivo multiphoton tomography allow for "optical biopsies" with horizontal cross sections. Dermatofluoroscopy and AI-based image analyzers provide a numerical score, which helps to correctly classify a skin lesion. The presented new optical procedures may be applied for the diagnosis of skin cancer as well as inflammatory skin diseases.
CONCLUSION: The presented optical procedures provide valuable additional information that supports dermatologists in making the correct diagnosis. However, a surgical biopsy followed by dermatohistopathological examination remains the diagnostic gold standard in dermatology.

Entities:  

Keywords:  Confocal laser scan microscopy; Dermatofluoroscopy; Multiphoton tomography; Noninvasive diagnostics; Screening

Mesh:

Year:  2020        PMID: 31965207     DOI: 10.1007/s00105-019-04531-z

Source DB:  PubMed          Journal:  Hautarzt        ISSN: 0017-8470            Impact factor:   0.751


  29 in total

1.  Melanoma detection by analysis of clinical images using convolutional neural network.

Authors:  E Nasr-Esfahani; S Samavi; N Karimi; S M R Soroushmehr; M H Jafari; K Ward; K Najarian
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2016-08

2.  In vivo reflectance confocal microscopy imaging of melanocytic skin lesions: consensus terminology glossary and illustrative images.

Authors:  Alon Scope; Cristiane Benvenuto-Andrade; Anna-Liza C Agero; Josep Malvehy; Susana Puig; Milind Rajadhyaksha; Klaus J Busam; Diego E Marra; Abel Torres; Iva Propperova; Richard G Langley; Ashfaq A Marghoob; Giovanni Pellacani; Stefania Seidenari; Allan C Halpern; Salvador Gonzalez
Journal:  J Am Acad Dermatol       Date:  2007-07-16       Impact factor: 11.527

3.  In Vivo Multiphoton Microscopy of Basal Cell Carcinoma.

Authors:  Mihaela Balu; Christopher B Zachary; Ronald M Harris; Tatiana B Krasieva; Karsten König; Bruce J Tromberg; Kristen M Kelly
Journal:  JAMA Dermatol       Date:  2015-10       Impact factor: 10.282

4.  Multicentre study on inflammatory skin diseases from The International Confocal Working Group: specific confocal microscopy features and an algorithmic method of diagnosis.

Authors:  M Ardigo; C Longo; S Gonzalez
Journal:  Br J Dermatol       Date:  2016-04-18       Impact factor: 9.302

5.  Patient acceptance and trust in automated computer-assisted diagnosis of melanoma with dermatofluoroscopy.

Authors:  Christine Fink; Lorenz Uhlmann; Maja Hofmann; Andrea Forschner; Thomas Eigentler; Claus Garbe; Alexander Enk; Holger A Haenssle
Journal:  J Dtsch Dermatol Ges       Date:  2018-06-21       Impact factor: 5.584

6.  Diagnostic accuracy of dermatofluoroscopy in cutaneous melanoma detection: results of a prospective multicentre clinical study in 476 pigmented lesions.

Authors:  A Forschner; U Keim; M Hofmann; I Spänkuch; D Lomberg; B Weide; I Tampouri; T Eigentler; C Fink; C Garbe; H A Haenssle
Journal:  Br J Dermatol       Date:  2018-06-07       Impact factor: 9.302

7.  Reflectance confocal microscopy made easy: The 4 must-know key features for the diagnosis of melanoma and nonmelanoma skin cancers.

Authors:  Giovanni Pellacani; Alon Scope; Salvador Gonzalez; Pascale Guitera; Francesca Farnetani; Josep Malvehy; Alexander Witkowski; Nathalie De Carvalho; Omar Lupi; Caterina Longo
Journal:  J Am Acad Dermatol       Date:  2019-04-05       Impact factor: 11.527

8.  Sensitivity and specificity of multiphoton laser tomography for in vivo and ex vivo diagnosis of malignant melanoma.

Authors:  Enrico Dimitrow; Mirjana Ziemer; Martin Johannes Koehler; Johannes Norgauer; Karsten König; Peter Elsner; Martin Kaatz
Journal:  J Invest Dermatol       Date:  2009-01-29       Impact factor: 8.551

9.  Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks.

Authors:  Philipp Tschandl; Cliff Rosendahl; Bengu Nisa Akay; Giuseppe Argenziano; Andreas Blum; Ralph P Braun; Horacio Cabo; Jean-Yves Gourhant; Jürgen Kreusch; Aimilios Lallas; Jan Lapins; Ashfaq Marghoob; Scott Menzies; Nina Maria Neuber; John Paoli; Harold S Rabinovitz; Christoph Rinner; Alon Scope; H Peter Soyer; Christoph Sinz; Luc Thomas; Iris Zalaudek; Harald Kittler
Journal:  JAMA Dermatol       Date:  2019-01-01       Impact factor: 10.282

10.  Deep neural networks show an equivalent and often superior performance to dermatologists in onychomycosis diagnosis: Automatic construction of onychomycosis datasets by region-based convolutional deep neural network.

Authors:  Seung Seog Han; Gyeong Hun Park; Woohyung Lim; Myoung Shin Kim; Jung Im Na; Ilwoo Park; Sung Eun Chang
Journal:  PLoS One       Date:  2018-01-19       Impact factor: 3.240

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