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Novel Imaging Techniques in Skin Diseases
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Novel Imaging Techniques in Skin Diseases

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Dermatology".

Deadline for manuscript submissions: closed (15 January 2022) | Viewed by 12357

Special Issue Editors

Dr. Marco Manfredini

E-Mail Website
Guest Editor
Dermatology Unit, Department of Surgical, Medical, Dental and Morphological Sciences with Interest in Transplant, Oncological and Regenerative Medicine, University of Modena and Reggio Emilia, 41124 Modena, Italy
Interests: non-invasive diagnosis; acne; hidradenitis suppurativa; BCC; melanoma; dermatoscopy; RCM; OCT; MPM
Special Issues, Collections and Topics in MDPI journals
Dr. Silvana Ciardo

E-Mail Website
Guest Editor
Dermatology Unit, Department of Surgical, Medical, Dental and Morphological Sciences related to Transplant, Oncology and Regenerative Medicine, University of Modena and Reggio Emilia, Modena, Italy
Interests: RCM (Reflectance Confocal Microscopy); OCT (optical Coherence tomography); Aging

Special Issue Information

Dear Colleagues,

The area of non-invasive diagnosis of skin disease is a constantly expanding field of research. The development of novel diagnostic devices allows in vivo and ex vivo tissue imaging, refining the management of the patient in a diagnostic bench-to-bed-side approach. Today, new emerging technologies for the microscopic and functional characterization of skin diseases are faster and more accurate than before. Several studies have already assessed the physiologic processes and the pathogenetic deviations of the skin. At present, the complexity of inflammatory and the tumoral diseases has been investigated by several researchers, but many other findings and observations are yet to be discovered and demonstrated. In addition to the study of skin diseases, the objective assessment of normal aging processes and of their improvements, which can be induced by several therapeutic procedures (including aesthetics), are still at the beginning of a long and fertile path. The present Special Issue aims to increase our knowledge of the physiological and pathological skin processes, analyzed with the eye of the novel imaging techniques that are currently available or under development. In summary, this is a great opportunity to expand our understanding of the skin and of the new technological devices that will become more important for everyday clinical practice.

Dr. Marco Manfredini
Dr. Silvana Ciardo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Non-invasive diagnosis
  • Skin diseases
  • Reflectance confocal microscopy
  • Optical coherence tomography
  • Multiphoton microscopy
  • Skin tumors
  • Inflammatory diseases
  • Aging

Published Papers (4 papers)

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Research

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15 pages, 5562 KiB  
Article
Differentiating Malignant from Benign Pigmented or Non-Pigmented Skin Tumours—A Pilot Study on 3D Hyperspectral Imaging of Complex Skin Surfaces and Convolutional Neural Networks
by Vivian Lindholm, Anna-Maria Raita-Hakola, Leevi Annala, Mari Salmivuori, Leila Jeskanen, Heikki Saari, Sari Koskenmies, Sari Pitkänen, Ilkka Pölönen, Kirsi Isoherranen and Annamari Ranki
J. Clin. Med. 2022, 11(7), 1914; https://doi.org/10.3390/jcm11071914 - 30 Mar 2022
Cited by 15 | Viewed by 2903
Abstract
Several optical imaging techniques have been developed to ease the burden of skin cancer disease on our health care system. Hyperspectral images can be used to identify biological tissues by their diffuse reflected spectra. In this second part of a three-phase pilot study, [...] Read more.
Several optical imaging techniques have been developed to ease the burden of skin cancer disease on our health care system. Hyperspectral images can be used to identify biological tissues by their diffuse reflected spectra. In this second part of a three-phase pilot study, we used a novel hand-held SICSURFIS Spectral Imager with an adaptable field of view and target-wise selectable wavelength channels to provide detailed spectral and spatial data for lesions on complex surfaces. The hyperspectral images (33 wavelengths, 477–891 nm) provided photometric data through individually controlled illumination modules, enabling convolutional networks to utilise spectral, spatial, and skin-surface models for the analyses. In total, 42 lesions were studied: 7 melanomas, 13 pigmented and 7 intradermal nevi, 10 basal cell carcinomas, and 5 squamous cell carcinomas. All lesions were excised for histological analyses. A pixel-wise analysis provided map-like images and classified pigmented lesions with a sensitivity of 87% and a specificity of 93%, and 79% and 91%, respectively, for non-pigmented lesions. A majority voting analysis, which provided the most probable lesion diagnosis, diagnosed 41 of 42 lesions correctly. This pilot study indicates that our non-invasive hyperspectral imaging system, which involves shape and depth data analysed by convolutional neural networks, is feasible for differentiating between malignant and benign pigmented and non-pigmented skin tumours, even on complex skin surfaces. Full article
(This article belongs to the Special Issue Novel Imaging Techniques in Skin Diseases)
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11 pages, 626 KiB  
Article
Usefulness of Dermoscopy in Localized Scleroderma (LoS, Morphea) Diagnosis and Assessment-Monocentric Cross-Sectional Study
by Paulina Szczepanik-Kułak, Anna Michalak-Stoma and Dorota Krasowska
J. Clin. Med. 2022, 11(3), 764; https://doi.org/10.3390/jcm11030764 - 30 Jan 2022
Cited by 2 | Viewed by 2672
Abstract
Morphea, also known as localized scleroderma (LoS), is a chronic autoimmune disease of the connective tissue. The clinical picture of LoS distinguishes between active and inactive lesions. Sometimes the clinical findings are challenging to identify, and therefore, the need for additional methods is [...] Read more.
Morphea, also known as localized scleroderma (LoS), is a chronic autoimmune disease of the connective tissue. The clinical picture of LoS distinguishes between active and inactive lesions. Sometimes the clinical findings are challenging to identify, and therefore, the need for additional methods is emphasized. Our study aimed to demonstrate the characteristic dermoscopic features in morphea skin lesions, focusing on demonstrating features in active and inactive lesions. In our patients (n = 31) with histopathologically proven LoS, we performed clinical evaluation of lesions (n = 162): active/inactive and according to both disease activity (modified localized scleroderma severity index, mLoSSI) and damage (localized scleroderma skin damage index, LoSDI) parameters. In addition, we took into account compression locations to determine whether skin trauma, a known etiopathogenetic factor in LoS, affects the dermoscopic pattern of the lesions. We performed a dermoscopy of the lesions, categorizing the images according to the severity within the observed field. We showed that within the active lesions (clinically and with high mLoSSI), white clouds and linear branching vessels had the highest severity. These features decreased within the observed field in inactive lesions and with high LoSDI. Brownish structureless areas were most intense in inactive lesions with high LoSDI. Erythematous areas, linear branching vessels, dotted vessels, and crystalline structures were statistically significant for pressure locations. We have shown dermoscopy is a valuable tool to assess the activity or inactivity of lesions, which translates into appropriate therapeutic decisions and the possibility of monitoring the patient during and after therapy for possible relapse. Full article
(This article belongs to the Special Issue Novel Imaging Techniques in Skin Diseases)
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Review

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11 pages, 1925 KiB  
Review
Dermoscopy, Reflectance Confocal Microscopy and Optical Coherence Tomography Features of Acne: A Systematic Review
by Antonio Alma, Alberto Sticchi, Camilla Chello, Stefania Guida, Francesca Farnetani, Johanna Chester, Vincenzo Bettoli, Giovanni Pellacani and Marco Manfredini
J. Clin. Med. 2022, 11(7), 1783; https://doi.org/10.3390/jcm11071783 - 24 Mar 2022
Cited by 10 | Viewed by 3003
Abstract
Noninvasive imaging techniques have recently outlined precise microscopic features of acne elementary lesions and accurate quantifications for disease severity staging and therapeutical efficacy follow-up. The aim of this review is to systematically describe current applications of dermoscopy, reflectance confocal microscopy (RCM), and optical [...] Read more.
Noninvasive imaging techniques have recently outlined precise microscopic features of acne elementary lesions and accurate quantifications for disease severity staging and therapeutical efficacy follow-up. The aim of this review is to systematically describe current applications of dermoscopy, reflectance confocal microscopy (RCM), and optical coherence tomography (OCT) in acne vulgaris assessment and management. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. We included studies conducted on human subjects with elementary lesions of acne vulgaris, reporting assessment of the lesions with dermoscopy, RCM, and/or OCT. At present there are few large studies regarding acne and noninvasive imaging techniques, representing the main limitation of this review. Clinical examination represents the first line in acne diagnosis and treatment. However, dermoscopy, RCM, and OCT are further tools that can improve acne classification, monitoring of treatment, and pathophysiologic characterization. In the near future, dermoscopy, RCM, and OCT could become routinely used for the evaluation of acne vulgaris to provide a deeper knowledge of the disease and to guide the clinician in the prescription of tailored treatment protocols based on each patient’s characteristics. Full article
(This article belongs to the Special Issue Novel Imaging Techniques in Skin Diseases)
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13 pages, 2331 KiB  
Review
Artificial Intelligence-Based Approaches to Reflectance Confocal Microscopy Image Analysis in Dermatology
by Ana Maria Malciu, Mihai Lupu and Vlad Mihai Voiculescu
J. Clin. Med. 2022, 11(2), 429; https://doi.org/10.3390/jcm11020429 - 14 Jan 2022
Cited by 20 | Viewed by 3003
Abstract
Reflectance confocal microscopy (RCM) is a non-invasive imaging method designed to identify various skin diseases. Confocal based diagnosis may be subjective due to the learning curve of the method, the scarcity of training programs available for RCM, and the lack of clearly defined [...] Read more.
Reflectance confocal microscopy (RCM) is a non-invasive imaging method designed to identify various skin diseases. Confocal based diagnosis may be subjective due to the learning curve of the method, the scarcity of training programs available for RCM, and the lack of clearly defined diagnostic criteria for all skin conditions. Given that in vivo RCM is becoming more widely used in dermatology, numerous deep learning technologies have been developed in recent years to provide a more objective approach to RCM image analysis. Machine learning-based algorithms are used in RCM image quality assessment to reduce the number of artifacts the operator has to view, shorten evaluation times, and decrease the number of patient visits to the clinic. However, the current visual method for identifying the dermal-epidermal junction (DEJ) in RCM images is subjective, and there is a lot of variation. The delineation of DEJ on RCM images could be automated through artificial intelligence, saving time and assisting novice RCM users in studying the key DEJ morphological structure. The purpose of this paper is to supply a current summary of machine learning and artificial intelligence’s impact on the quality control of RCM images, key morphological structures identification, and detection of different skin lesion types on static RCM images. Full article
(This article belongs to the Special Issue Novel Imaging Techniques in Skin Diseases)
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