The Comparative Use of Multiple Electronic Devices in the Teledermoscopic Diagnosis of Early Melanoma

Comparison of Extended Skin Cancer Screening Using a Three-Step Advanced Imaging Programme vs. Standard-of-Care Examination in a High-Risk Melanoma Patient Cohort

Modern diagnostic procedures, such as three-dimensional total body photography (3D-TBP), digital dermoscopy (DD), and reflectance confocal microscopy (RCM), can improve melanoma diagnosis, particularly in high-risk patients. This study assessed the benefits of combining these advanced imaging techniques in a three-step programme in managing high-risk patients. This study included 410 high-risk melanoma patients who underwent a specialised imaging consultation in addition to their regular skin examinations in outpatient care. At each visit, the patients underwent a 3D-TBP, a DD for suspicious findings, and an RCM for unclear DD findings. The histological findings of excisions initiated based on imaging consultation and outpatient care were compared. Imaging consultation detected sixteen confirmed melanomas (eight invasive and eight in situ) in 39 excised pigmented lesions. Outpatient care examination detected seven confirmed melanomas (one invasive and six in situ) in 163 excised melanocytic lesions. The number needed to excise (NNE) in the imaging consultation was significantly lower than that in the outpatient care (2.4 vs. 23.3). The NNE was 2.6 for DD and 2.3 for RCM. DD, 3D-TBP, or RCM detected melanomas that were not detected by the other imaging methods. The three-step imaging programme improves melanoma detection and reduces the number of unnecessary excisions in high-risk patients.

Patient-led teledermatology for skin lesion triage: a service evaluation of the DyplensTM dermoscope

Despite the huge improvement in smartphone cameras, there has not been any real interest in the UK in pursuing patient-facing teledermatology within the sphere of skin lesion triage. High-specification dermoscopic images can be generated with smartphone attachments, but, to date, no formal clinical trial has been performed to establish the efficacy and feasibility of these consumer-level dermoscopes in skin lesion triage. The objectives of this study were to assess the ability of patients to capture dermoscopic images using a smartphone attachment, and to identify the safety and diagnostic accuracy of consumer-level dermoscopy in triaging out benign skin lesions from the 2-week-wait (2WW) cancer pathway. We recruited 78 patients already attending a face-to-face clinic at two locations. They were provided with instruction leaflets and asked to obtain dermoscopic and macroscopic images of their lesion(s) using their own smartphones. The images (and a brief history) were distributed to five experienced blinded assessors (consultants), who were asked to state their working diagnosis and outcome (reassurance, routine review or 2WW pathway), as they would in teledermatology. We compared their outcomes to the gold-standard in-person diagnosis and/or histological diagnosis, where available. The device achieved 100% sensitivity in diagnosing melanoma and squamous cell carcinoma (SCC). The specificity for the diagnoses of melanoma (89%) and SCC (83%) was high. The overall diagnostic accuracy was 77% for both benign and malignant lesions, The diagnostic accuracy was high for seborrhoeic keratosis (91%) and simple naevi (81%). Patient-captured dermoscopic images using bespoke smartphone attachments could be the future in safely triaging out benign lesions.

A European Multicentric Investigation of Atypical Melanocytic Skin Lesions of Palms and Soles: The iDScore-PalmoPlantar Database

Background: The differential diagnosis of atypical melanocytic palmoplantar skin lesions (aMPLs) represents a diagnostic challenge, including atypical nevi (AN) and early melanomas (MMs) that display overlapping clinical and dermoscopic features. We aimed to set up a multicentric dataset of aMPL dermoscopic cases paired with multiple anamnestic risk factors and demographic and morphologic data. Methods: Each aMPL case was paired with a dermoscopic and clinical picture and a series of lesion-related data (maximum diameter value; location on the palm/sole in 17 areas; histologic diagnosis; and patient-related data (age, sex, family history of melanoma/sunburns, phototype, pheomelanin, eye/hair color, multiple/dysplastic body nevi, and traumatism on palms/soles). Results: A total of 542 aMPL cases-113 MM and 429 AN-were collected from 195 males and 347 females. No sex prevalence was found for melanomas, while women were found to have relatively more nevi. Melanomas were prevalent on the heel, plantar arch, and fingers in patients aged 65.3 on average, with an average diameter of 17 mm. Atypical nevi were prevalent on the plantar arch and palmar area of patients aged 41.33 on average, with an average diameter of 7 mm. Conclusions: Keeping in mind the risk profile of an aMPL patient can help obtain a timely differentiation between malignant/benign cases, thus avoiding delayed and inappropriate excision, respectively, with the latter often causing discomfort/dysfunctional scarring, especially at acral sites.

A risk-scoring model for the differential diagnosis of lentigo maligna and other atypical pigmented facial lesions of the face: The facial iDScore

BACKGROUND

Due to progressive ageing of the population, the incidence of facial lentigo maligna (LM) of the face is increasing. Many benign simulators of LM and LMM, known as atypical pigmented facial lesions (aPFLs-pigmented actinic keratosis, solar lentigo, seborrheic keratosis, seborrheic-lichenoid keratosis, atypical nevus) may be found on photodamaged skin. This generates many diagnostic issues and increases the number of biopsies, with a subsequent impact on aesthetic outcome and health insurance costs.

OBJECTIVES

Our aim was to develop a risk-scoring classifier-based algorithm to estimate the probability of an aPFL being malignant. A second aim was to compare its diagnostic accuracy with that of dermoscopists so as to define the advantages of using the model in patient management.

MATERIALS AND METHODS

A total of 154 dermatologists analysed 1111 aPFLs and their management in a teledermatology setting: They performed pattern analysis, gave an intuitive clinical diagnosis and proposed lesion management options (follow-up/reflectance confocal microscopy/biopsy). Each case was composed of a dermoscopic and/or clinical picture plus metadata (histology, age, sex, location, diameter). The risk-scoring classifier was developed and tested on this dataset and then validated on 86 additional aPFLs.

RESULTS

The facial Integrated Dermoscopic Score (iDScore) model consisted of seven dermoscopic variables and three objective parameters (diameter ≥ 8 mm, age ≥ 70 years, male sex); the score ranged from 0 to 16. In the testing set, the facial iDScore-aided diagnosis was more accurate (AUC = 0.79 [IC 95% 0.757-0.843]) than the intuitive diagnosis proposed by dermatologists (average of 43.5%). In the management study, the score model reduced the number of benign lesions sent for biopsies by 41.5% and increased the number of LM/LMM cases sent for reflectance confocal microscopy or biopsy instead of follow-up by 66%.

CONCLUSIONS

The facial iDScore can be proposed as a feasible tool for managing patients with aPFLs.

Development and Implementation of a Web-Based International Registry Dedicated to Atypical Pigmented Skin Lesions of the Face: Teledermatologic Investigation on Epidemiology and Risk Factors

Background: Atypical pigmented facial lesions (aPFLs) often display clinical and dermoscopic equivocal and/or overlapping features, thus causing a challenging and delayed diagnosis and/or inappropriate excisions. No specific registry dedicated to aPFL paired with clinical data is available to date. Methods: The dataset is hosted on a specifically designed web platform. Each complete case was composed of the following data: (1) one dermoscopic picture; (2) one clinical picture; (3) two lesion data, that is, maximum diameter and facial location (e.g., orbital area/forehead/nose/cheek/chin/mouth); (4) patient's demographics: family history of melanoma, history of sunburns in childhood, phototype, pheomelanine, eyes/hair color, multiple nevi/dysplastic nevi on the body; and (5) acquisition device (videodermatoscope/camera-based/smartphone-based system). Results: A total of 11 dermatologic centers contributed to a final teledermoscopy database of 1,197 aPFL with a distribution of 353 lentigo maligna (LM), 146 lentigo maligna melanoma (LMM), 231 pigmented actinic keratoses, 266 solar lentigo, 125 atypical nevi, 48 seborrheic keratosis, and 28 seborrheic-lichenoid keratoses. The cheek site was involved in half of aPFL cases (50%). Compared with those with the other aPFL cases, patients with LM/LMM were predominantly men, older (69.32 ± 12.9 years on average vs. 62.69 ± 14.51), exhibited larger lesions (11.88 ± 7.74 mm average maximum diameter vs. 9.33 ± 6.46 mm), and reported a positive history of sunburn in childhood. Conclusions: The iDScore facial dataset currently represents a precious source of data suitable for the design of diagnostic support tools based on risk scoring classifiers to help dermatologists in recognizing LM/LMM among challenging aPFL in clinical practice.

Advancing Dermatological Care: A Comprehensive Narrative Review of Tele-Dermatology and mHealth for Bridging Gaps and Expanding Opportunities beyond the COVID-19 Pandemic

Mobile health (mHealth) has recently had significant advances in tele-dermatology (TD) thanks to the developments following the COVID-19 pandemic. This topic is very important, as telemedicine and mHealth, when applied to dermatology, could improve both the quality of healthcare for citizens and the workflow in the health domain. The proposed study was centered on the last three years. We conducted an overview on the opportunities, the perspectives, and the problems involved in TD integration with mHealth. The methodology of the narrative review was based on: (I) a search of PubMed and Scopus and (II) an eligibility assessment, using properly proposed parameters. The outcome of the study showed that during the COVID-19 pandemic, TD integration with mHealth advanced rapidly. This integration enabled the monitoring of dermatological problems and facilitated remote specialist visits, reducing face-to-face interactions. AI and mobile apps have empowered citizens to take an active role in their healthcare. This differs from other imaging sectors where information exchange is limited to professionals. The opportunities for TD in mHealth include improving service quality, streamlining healthcare processes, reducing costs, and providing more accessible care. It can be applied to various conditions, such as (but not limited to) acne, vitiligo, psoriasis, and skin cancers. Integration with AI and augmented reality (AR), as well as the use of wearable sensors, are anticipated as future developments. However, integrating TD with mHealth also brings about problems and challenges related to regulations, ethics, cybersecurity, data privacy, and device management. Scholars and policymakers need to address these issues while involving citizens in the process.

Lead Time from First Suspicion of Malignant Melanoma in Primary Care to Diagnostic Excision: a Cohort Study Comparing Teledermatoscopy and Traditional Referral to a Dermatology Clinic at a Tertiary Hospital

INTRODUCTION

The increasing use of teledermatoscopy in clinical practice has led to demands to evaluate the effects of this new technology on traditional healthcare systems.

OBJECTIVES

To study lead times from first consultation in primary care to diagnostic excision of suspected malignant melanoma lesions in traditional referrals to a tertiary hospital-based dermatology clinic compared with mobile teledermatoscopy referrals.

METHODS

A retrospective cohort study design was used. Data on sex, age, pathology, caregivers, clinical diagnosis, date for first visit to primary care unit, and date for diagnostic excision were collected from medical records. Patients managed through traditional referral (n=53) were compared with patients managed at primary care units using teledermatoscopy (n=128) regarding lead time from first visit to diagnostic excision.

RESULTS

Mean time from date of first visit at primary care unit to diagnostic excision did not differ between the traditional referral and teledermatoscopy groups (16.2 vs. 15.7 days, median 10 vs. 13 days, p=0.657). Lead times from date of referral to diagnostic excision did not significantly differ (15.7 vs. 12.8 days, median 10 vs. 9 days, p=0.464).

CONCLUSIONS

Our study indicates that lead time to diagnostic excision for patients with suspected malignant melanoma managed by teledermatoscopy was comparable and not inferior to that of the traditional referral pathway. If teledermatoscopy is used at first consultation in primary care, it could potentially be more efficient than traditional referral.

Digital skin imaging applications, part II: a comprehensive survey of post-acquisition image utilization features and technology standards

BACKGROUND

Despite the increasing ubiquity and accessibility of teledermatology applications, few studies have comprehensively surveyed their features and technical standards. Importantly, features implemented after the point of capture are often intended to augment image utilization, while technical standards affect interoperability with existing healthcare systems. We aim to comprehensively survey image utilization features and technical characteristics found within publicly discoverable digital skin imaging applications.

MATERIALS AND METHODS

Applications were identified and categorized as described in Part I. Included applications were then further assessed by three independent reviewers for post-imaging content, tools, and functionality. Publicly available information was used to determine the presence or absence of relevant technology standards and/or data characteristics.

RESULTS

A total of 20 post-image acquisition features were identified across three general categories: (1) metadata attachment, (2) functional tools (i.e., those that utilized images or in-app content to perform a user-directed function), and (3) image processing. Over 80% of all applications implemented metadata features, with nearly half having metadata features only. Individual feature occurred and feature richness varied significantly by primary audience (p < 0.0001) and function (p < 0.0001). On average, each application included under three features. Less than half of all applications requested consent for user-uploaded photos and fewer than 10% provided clear data use and privacy policies.

CONCLUSION

Post-imaging functionality in skin imaging applications varies significantly by primary audience and intended function, though nearly all applications implemented metadata labeling. Technical standards are often not implemented or reported consistently. Gaps in the provision of clear consent, data privacy, and data use policies should be urgently addressed.

Digital skin imaging applications, part I: Assessment of image acquisition technique features

BACKGROUND

The rapid adoption of digital skin imaging applications has increased the utilization of smartphone-acquired images in dermatology. While this has enormous potential for scaling the assessment of concerning skin lesions, the insufficient quality of many consumer/patient-taken images can undermine clinical accuracy and potentially harm patients due to lack of diagnostic interpretability. We aim to characterize the current state of digital skin imaging applications and comprehensively assess how image acquisition features address image quality.

MATERIALS AND METHODS

Publicly discoverable mobile, web, and desktop-based skin imaging applications, identified through keyword searches in mobile app stores, Google Search queries, previous teledermatology studies, and expert recommendations were independently assessed by three reviewers. Applications were categorized by primary audience (consumer-facing, nonhospital-based practice, or enterprise/health system), function (education, store-and-forward teledermatology, live-interactive teledermatology, electronic medical record adjunct/clinical imaging storage, or clinical triage), in-app connection to a healthcare provider (yes or no), and user type (patient, provider, or both).

RESULTS

Just over half (57%) of 191 included skin imaging applications had at least one of 14 image acquisition technique features. Those that were consumer-facing, intended for educational use, and designed for both patient and physician users had significantly greater feature richness (p < 0.05). The most common feature was the inclusion of text-based imaging tips, followed by the requirement to submit multiple images and body area matching.

CONCLUSION

Very few skin imaging applications included more than one image acquisition technique feature. Feature richness varied significantly by audience, function, and user categories. Users of digital dermatology tools should consider which applications have standardized features that improve image quality.

Teledermatology in 2020: past, present and future perspectives

Born in 1995, teledermatology (TD) turns 25 years old today. Since then, TD evolved according to patients and physicians needs. The present review aimed to summarize all the efforts and experiences carried out in the field of TD and its subspecialties, the evolution and the future perspectives. A literature search was conducted in PubMed and Google Scholar. The state of the art of the "tele-dermo research" included TD and clinical trials, TD/TDS web platforms, TDS and artificial intelligence studies. Finally, the future perspective of TD/TDS in the era of social distancing was discussed. Using TD in specific situations adds several benefits including time-effectiveness of intervention and reduction in the waiting time for the first visit, reduced travel-costs, reduced sanitary costs, equalization of access from patient to specialistic consult. The communication technologies devices currently available can adequately support the growing needs of tele-assistance. A main limit is the current lack of a common clear European regulation for practicing TD, encompassing privacy issues and data management. The pandemic lockdown of 2020 has highlighted the importance of performing TD for all those patient, elderly and/or fragile, where the alternative would be no care at all. Many efforts are needed to develop efficient workflows and TD programs to facilitate the interplay among the different TD actors, along with practice guidelines or position statements.

A new deep learning approach integrated with clinical data for the dermoscopic differentiation of early melanomas from atypical nevi

BACKGROUND

Timely recognition of malignant melanoma (MM) is challenging for dermatologists worldwide and represents the main determinant for mortality. Dermoscopic examination is influenced by dermatologists' experience and fails to achieve adequate accuracy and reproducibility in discriminating atypical nevi (AN) from early melanomas (EM).

OBJECTIVE

We aimed to develop a Deep Convolutional Neural Network (DCNN) model able to support dermatologists in the classification and management of atypical melanocytic skin lesions (aMSL).

METHODS

A training set (630 images), a validation set (135) and a testing set (214) were derived from the idScore dataset of 979 challenging aMSL cases in which the dermoscopic image is integrated with clinical data (age, sex, body site and diameter) and associated with histological data. A DCNN_aMSL architecture was designed and then trained on both dermoscopic images of aMSL and the clinical/anamnestic data, resulting in the integrated "iDCNN_aMSL" model. Responses of 111 dermatologists with different experience levels on both aMSL classification (intuitive diagnosis) and management decisions (no/long follow-up; short follow-up; excision/preventive excision) were compared with the DCNNs models.

RESULTS

In the lesion classification study, the iDCNN_aMSL achieved the best accuracy, reaching an AUC = 90.3 %, SE = 86.5 % and SP = 73.6 %, compared to DCNN_aMSL (SE = 89.2 %, SP = 65.7 %) and intuitive diagnosis of dermatologists (SE = 77.0 %; SP = 61.4 %).

CONCLUSIONS

The iDCNN_aMSL proved to be the best support tool for management decisions reducing the ratio of inappropriate excision. The proposed iDCNN_aMSL model can represent a valid support for dermatologists in discriminating AN from EM with high accuracy and for medical decision making by reducing their rates of inappropriate excisions.