The role of technology in melanoma screening and diagnosis

DermSynth3D: Synthesis of in-the-wild annotated dermatology images

In recent years, deep learning (DL) has shown great potential in the field of dermatological image analysis. However, existing datasets in this domain have significant limitations, including a small number of image samples, limited disease conditions, insufficient annotations, and non-standardized image acquisitions. To address these shortcomings, we propose a novel framework called DermSynth3D. DermSynth3D blends skin disease patterns onto 3D textured meshes of human subjects using a differentiable renderer and generates 2D images from various camera viewpoints under chosen lighting conditions in diverse background scenes. Our method adheres to top-down rules that constrain the blending and rendering process to create 2D images with skin conditions that mimic in-the-wild acquisitions, ensuring more meaningful results. The framework generates photo-realistic 2D dermatological images and the corresponding dense annotations for semantic segmentation of the skin, skin conditions, body parts, bounding boxes around lesions, depth maps, and other 3D scene parameters, such as camera position and lighting conditions. DermSynth3D allows for the creation of custom datasets for various dermatology tasks. We demonstrate the effectiveness of data generated using DermSynth3D by training DL models on synthetic data and evaluating them on various dermatology tasks using real 2D dermatological images. We make our code publicly available at https://github.com/sfu-mial/DermSynth3D.

Multidisciplinary patient-centered approach to the management of skin cancer

In recent years, new approaches for optimal patient management of cancer have focused on patient-centered care, with integration of tumour-directed treatment and patient-directed supportive and palliative care throughout the disease journey from prevention through screening, diagnosis, treatment, and follow-up. In 2022, at the International Forum of Dermatology (IFD), a scientific session was entirely dedicated to highlight recent developments on patient-centered approaches in skin cancer. An international panel of different groups of participants involved in a patient's journey on the management of skin cancer presented and discussed challenges and barriers that persist in the field of skin cancer prevention and care pathways. Although primary prevention remains a crucial step in the prevention of melanoma, the different surveys performed during the last 20 years demonstrate that the use of sunscreen increases very slowly. Secondary prevention that includes skin screening and diagnostic measures may benefit from the development of digital tools. To improve adherence, patients need accurate, reliable information about their disease and the treatment options, and this type of content that can also be made available on digital tools. Shared decision-making is a hallmark of a patient-centered approach and requires health care providers who can communicate well to patients and their families, underscoring the pivotal role of health care professionals all through the patient journey. Health care providers have a crucial role in supporting patients through their journey in skin cancer. They will benefit from mobile apps and technologies that have been developed recently to address challenges in skin cancer prevention, detection and care, including those that are primarily directed to the patient. However, more peer-reviewed studies are needed as well as regulations to ensure that apps are accurate, reliable, and up to date.

Biosensors for melanoma skin cancer diagnostics

Skin cancer is a critical global public health concern, with melanoma being the deadliest variant, correlated to 80% of skin cancer-related deaths and a remarkable propensity to metastasize. Despite notable progress in skin cancer prevention and diagnosis, the limitations of existing methods accentuate the demand for precise diagnostic tools. Biosensors have emerged as valuable clinical tools, enabling rapid and reliable point-of-care (POC) testing of skin cancer. This review offers insights into skin cancer development, highlights essential cutaneous melanoma biomarkers, and assesses the current landscape of biosensing technologies for diagnosis. The comprehensive analysis in this review underscores the transformative potential of biosensors in revolutionizing melanoma skin cancer diagnosis, emphasizing their critical role in advancing patient outcomes and healthcare efficiency. The increasing availability of these approaches supports direct diagnosis and aims to reduce the reliance on biopsies, enhancing POC diagnosis. Recent advancements in biosensors for skin cancer diagnosis hold great promise, with their integration into healthcare expected to enhance early detection accuracy and reliability, thereby mitigating socioeconomic disparities.

Factors Affecting Recurrence and Survival for Patients with High-Risk Stage II Melanoma

BACKGROUND

In the current era of effective adjuvant therapies and de-escalation of surgery, distinguishing which patients with high-risk stage II melanoma are at increased risk of recurrence after excision of the primary lesion is essential to determining appropriate treatment and surveillance plans.

METHODS

A single-center retrospective study analyzed patients with stage IIB or IIC melanoma. Demographic and tumor data were collected, and genomic analysis of formalin-fixed, paraffin-embedded tissue samples was performed via an internal next-generation sequencing (NGS) platform (SNaPshot). The end points examined were relapse-free survival (RFS), distant metastasis-free survival (DMFS), overall survival (OS), and melanoma-specific survival (MSS). Uni- and multivariable Cox regressions were performed to calculate the hazard ratios.

RESULTS

The study included 92 patients with a median age of 69 years and a male/female ratio of 2:1. A Breslow depth greater than 4 mm, a higher mitotic rate, an advanced T stage, and a KIT mutation had a negative impact on RFS. A primary lesion in the head and neck, a mitotic rate exceeding 10 mitoses per mm2, a CDH1 mutation, or a KIT mutation was significantly associated with a shorter DMFS. Overall survival was significantly lower with older age at diagnosis and a higher mitotic rate. An older age at diagnosis also had a negative impact on MSS.

CONCLUSION

Traditional histopathologic factors and specific tumor mutations displayed a significant correlation with disease recurrence and survival for patients with high-risk stage II melanoma. This study supported the use of genomic testing of high-risk stage II melanomas for prognostic prediction and risk stratification.

On-Site Melanoma Diagnosis Utilizing a Swellable Microneedle-Assisted Skin Interstitial Fluid Sampling and a Microfluidic Particle Dam for Visual Quantification of S100A1

Malignant melanoma (MM) is the most aggressive form of skin cancer. The delay in treatment will induce metastasis, resulting in a poor prognosis and even death. Here, a two-step strategy for on-site diagnosis of MM is developed based on the extraction and direct visual quantification of S100A1, a biomarker for melanoma. First, a swellable microneedle is utilized to extract S100A1 in skin interstitial fluid (ISF) with minimal invasion. After elution, antibody-conjugated magnetic microparticles (MMPs) and polystyrene microparticles (PMPs) are introduced. A high expression level of S100A1 gives rise to a robust binding between MMPs and PMPs and reduces the number of free PMPs. By loading the reacted solution into the device with a microfluidic particle dam, the quantity of free PMPs after magnetic separation is displayed with their accumulation length inversely proportional to S100A1 levels. A limit of detection of 18.7 ng mL-1 for S100A1 is achieved. The animal experiment indicates that ISF-based S100A1 quantification using the proposed strategy exhibits a significantly higher sensitivity compared with conventional serum-based detection. In addition, the result is highly comparable with the gold standard enzyme-linked immunosorbent assay based on Lin's concordance correlation coefficient, suggesting the high practicality for routine monitoring of melanoma.

Artificial intelligence and skin cancer

Artificial intelligence is poised to rapidly reshape many fields, including that of skin cancer screening and diagnosis, both as a disruptive and assistive technology. Together with the collection and availability of large medical data sets, artificial intelligence will become a powerful tool that can be leveraged by physicians in their diagnoses and treatment plans for patients. This comprehensive review focuses on current progress toward AI applications for patients, primary care providers, dermatologists, and dermatopathologists, explores the diverse applications of image and molecular processing for skin cancer, and highlights AI's potential for patient self-screening and improving diagnostic accuracy for non-dermatologists. We additionally delve into the challenges and barriers to clinical implementation, paths forward for implementation and areas of active research.

Review of the application of the most current sophisticated image processing methods for the skin cancer diagnostics purposes

This paper presents the most current and innovative solutions applying modern digital image processing methods for the purpose of skin cancer diagnostics. Skin cancer is one of the most common types of cancers. It is said that in the USA only, one in five people will develop skin cancer and this trend is constantly increasing. Implementation of new, non-invasive methods plays a crucial role in both identification and prevention of skin cancer occurrence. Early diagnosis and treatment are needed in order to decrease the number of deaths due to this disease. This paper also contains some information regarding the most common skin cancer types, mortality and epidemiological data for Poland, Europe, Canada and the USA. It also covers the most efficient and modern image recognition methods based on the artificial intelligence applied currently for diagnostics purposes. In this work, both professional, sophisticated as well as inexpensive solutions were presented. This paper is a review paper and covers the period of 2017 and 2022 when it comes to solutions and statistics. The authors decided to focus on the latest data, mostly due to the rapid technology development and increased number of new methods, which positively affects diagnosis and prognosis.

Melanin Stacking Differences in Pigmented and Non-Pigmented Melanomas: Quantitative Differentiation between Pigmented and Non-Pigmented Melanomas Based on Light-Scattering Properties

Cutaneous melanoma is a cancer with metastatic potential characterized by varying amounts of pigment-producing melanocytes, and it is one of the most aggressive and fatal forms of skin malignancy, with several hundreds of thousands of cases each year. Early detection and therapy can lead to decreased morbidity and decreased cost of therapy. In the clinic, this often translates to annual skin screenings, especially for high-risk patients, and generous use of the ABCDE (asymmetry, border irregularity, color, diameter, evolving) criteria. We have used a new technique termed vibrational optical coherence tomography (VOCT) to non-invasively differentiate between pigmented and non-pigmented melanomas in a pilot study. The VOCT results reported in this study indicate that both pigmented and non-pigmented melanomas have similar characteristics, including new 80, 130, and 250 Hz peaks. Pigmented melanomas have larger 80 Hz peaks and smaller 250 Hz peaks than non-pigmented cancers. The 80 and 250 Hz peaks can be used to quantitative characterize differences between different melanomas. In addition, infrared light penetration depths indicated that melanin in pigmented melanomas has higher packing densities than in non-pigmented lesions. Using machine learning techniques, the sensitivity and specificity of differentiating skin cancers from normal skin are shown to range from about 78% to over 90% in this pilot study. It is proposed that using AI on both lesion histopathology and mechanovibrational peak heights may provide even higher specificity and sensitivity for differentiating the metastatic potential of different melanocytic lesions.

Long-Term Sequential Digital Dermoscopy of Low-Risk Patients May Not Improve Early Diagnosis of Melanoma Compared to Periodical Handheld Dermoscopy

Sequential digital dermoscopy (SDD) enables the diagnosis of a subgroup of slow-growing melanomas that lack suspicious features at baseline examination but exhibit detectable change on follow-up. The combined use of total-body photography and SDD is recommended in high-risk subjects by current guidelines. To establish the usefulness of SDD for low-risk individuals, we conducted a retrospective study using electronic medical records of low-risk patients with a histopathological diagnosis of cutaneous melanoma between 1 January 2016 and 31 December 2019, who had been referred and monitored for long-term follow-up of clinically suspicious melanocytic nevi. We sought to compare the distribution of "early" cutaneous melanoma, defined as melanoma in situ and pT1a melanoma, between SDD and periodical handheld dermoscopy in low-risk patients. A total of 621 melanomas were diagnosed in a four-year timespan; 471 melanomas were diagnosed by handheld dermoscopy and 150 by digital dermoscopy. Breslow tumor thickness was significantly higher for melanomas diagnosed by handheld compared to digital dermoscopy (0.56 ± 1.53 vs. 0.26 ± 0.84, p = 0.030, with a significantly different distribution of pT stages between the two dermoscopic techniques. However, no significant difference was found with respect to the distribution of pT stages, mean Breslow tumor thickness, ulceration, and prevalence of associated melanocytic nevus in tumors diagnosed on periodical handheld dermoscopy compared to SDD. Our results confirm that periodical dermoscopic examination enables the diagnosis of cutaneous melanoma at an earlier stage compared to first-time examination as this was associated in our patients with better prognostic features. However, in our long-term monitoring of low-risk subjects, Breslow tumor thickness and pT stage distribution did not differ between handheld periodical dermoscopy and SDD.

Genomic and proteomic findings in early melanoma and opportunities for early diagnosis

Overdiagnosis of early melanoma is a significant problem. Due to subtle unique and overlapping clinical and histological criteria between pigmented lesions and the risk of mortality from melanoma, some benign pigmented lesions are diagnosed as melanoma. Although histopathology is the gold standard to diagnose melanoma, there is a demand to find alternatives that are more accurate and cost-effective. In the current "omics" era, there is gaining interest in biomarkers to help diagnose melanoma early and to further understand the mechanisms driving tumor progression. Genomic investigations have attempted to differentiate malignant melanoma from benign pigmented lesions. However, genetic biomarkers of early melanoma diagnosis have not yet proven their value in the clinical setting. Protein biomarkers may be more promising since they directly influence tissue phenotype, a result of by-products of genomic mutations, posttranslational modifications and environmental factors. Uncovering relevant protein biomarkers could increase confidence in their use as diagnostic signatures. Currently, proteomic investigations of melanoma progression from pigmented lesions are limited. Studies have previously characterised the melanoma proteome from cultured cell lines and clinical samples such as serum and tissue. This has been useful in understanding how melanoma progresses into metastasis and development of resistance to adjuvant therapies. Currently, most studies focus on metastatic melanoma to find potential drug therapy targets, prognostic factors and markers of resistance. This paper reviews recent advancements in the genomics and proteomic fields and reports potential avenues, which could help identify and differentiate melanoma from benign pigmented lesions and prevent the progression of melanoma.

Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence

We live in an unprecedented time in oncology. We have accumulated samples and cases in cohorts larger and more complex than ever before. New technologies are available for quantifying solid or liquid samples at the molecular level. At the same time, we are now equipped with the computational power necessary to handle this enormous amount of quantitative data. Computational models are widely used helping us to substantiate and interpret data. Under the label of systems and precision medicine, we are putting all these developments together to improve and personalize the therapy of cancer. In this review, we use melanoma as a paradigm to present the successful application of these technologies but also to discuss possible future developments in patient care linked to them. Melanoma is a paradigmatic case for disruptive improvements in therapies, with a considerable number of metastatic melanoma patients benefiting from novel therapies. Nevertheless, a large proportion of patients does not respond to therapy or suffers from adverse events. Melanoma is an ideal case study to deploy advanced technologies not only due to the medical need but also to some intrinsic features of melanoma as a disease and the skin as an organ. From the perspective of data acquisition, the skin is the ideal organ due to its accessibility and suitability for many kinds of advanced imaging techniques. We put special emphasis on the necessity of computational strategies to integrate multiple sources of quantitative data describing the tumour at different scales and levels.

Dermoscopy practice guidelines for use in telemedicine

Teledermoscopy, or the utilization of dermatoscopic images in telemedicine, can help diagnose dermatologic disease remotely, triage lesions of concern (i.e., determine whether in-person consultation with a dermatologist is necessary, biopsy, or reassure the patient), and monitor dermatologic lesions over time. Handheld dermatoscopes, a magnifying apparatus, have become a commonly utilized tool for providers in many healthcare settings and professions and allows users to view microstructures of the epidermis and dermis. This Dermoscopy Practice Guideline reflects current knowledge in the field of telemedicine to demonstrate the correct capture, usage, and incorporation of dermoscopic images into everyday practice.

Melanoma: How and When to Consider Clinical Diagnostic Technologies

In response to rising rates of melanoma worldwide, novel non-invasive melanoma detection techniques are emerging to facilitate the early detection of melanoma and decrease unnecessary biopsies of benign pigmented lesions. Because they often report similar study findings, it may be difficult to determine how best to incorporate these technologies into clinical practice based on their supporting studies alone. As an expansion of the recent article by Fried et al.¹, which reviewed the clinical data supporting these non-invasive melanoma detection techniques, the first article in this continuing medical education series provides practical advice on how and when to use various non-invasive melanoma detection techniques into clinical practice.

Etiologies of Melanoma Development and Prevention Measures: A Review of the Current Evidence

Simple Summary

Melanoma constitutes a major public health risk, with the rates of diagnosis increasing on a yearly basis. Monitoring for risk factors and preventing dangerous behaviors that increase melanoma risk, such as tanning, are important measures for melanoma prevention. Additionally, assessing the effectiveness of various methods to prevent sun exposure and sunburns—which can lead to melanoma—is important to help identify ways to reduce the development of melanoma. We summarize the recent evidence regarding the heritable and behavioral risks underlying melanoma, as well as the current methods used to reduce the risk of developing melanoma and to improve the diagnosis of this disease.

Abstract

(1) Melanoma is the most aggressive dermatologic malignancy, with an estimated 106,110 new cases to be diagnosed in 2021. The annual incidence rates continue to climb, which underscores the critical importance of improving the methods to prevent this disease. The interventions to assist with melanoma prevention vary and typically include measures such as UV avoidance and the use of protective clothing, sunscreen, and other chemopreventive agents. However, the evidence is mixed surrounding the use of these and other interventions. This review discusses the heritable etiologies underlying melanoma development before delving into the data surrounding the preventive methods highlighted above. (2) A comprehensive literature review was performed to identify the clinical trials, observational studies, and meta-analyses pertinent to melanoma prevention and incidence. Online resources were queried to identify epidemiologic and clinical trial information. (3) Evidence exists to support population-wide screening programs, the proper use of sunscreen, and community-targeted measures in the prevention of melanoma. Clinical evidence for the majority of the proposed preventive chemotherapeutics is presently minimal but continues to evolve. (4) Further study of these chemotherapeutics, as well as improvement of techniques in artificial intelligence and imaging techniques for melanoma screening, is warranted for continued improvement of melanoma prevention.

The Value of Total Body Photography for the Early Detection of Melanoma: A Systematic Review

Early detection of melanoma is critical to reduce the mortality and morbidity rates of this tumor. Total body photography (TBP) may aid in the early detection of melanoma. To summarize the current evidence on TBP for the early detection of melanoma, we performed a systematic literature search in Medline, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL) for eligible records up to 6th August 2020. Outcomes of interest included melanoma incidence, incisional and excisional biopsy rates, as well as the Breslow's index of detected tumors. Results from individual studies were described qualitatively. The risks of bias and applicability of the included studies was assessed using the QUADAS-2 checklist. In total, 14 studies published between 1997 and 2020 with an overall sample size of n = 12082 (range 100-4692) were included in the qualitative analysis. Individuals undergoing TBP showed a trend towards a lower Breslow's thickness and a higher proportion of in situ melanomas compared to those without TBP. The number needed to excise one melanoma varied from 3:1 to 14.3:1 and was better for lesions that arose de novo than for tracked ones. The included studies were judged to be of unclear methodological concern with specific deficiencies in the domains "flow and timing" and "reference standard". The use of TBP can improve the early detection of melanoma in high-risk populations. Future studies are warranted to reduce the heterogeneity of phenotypic risk factor definition and the technical implementation of TBP. Artificial intelligence-assisted analysis of images derived from 3-D TBP systems and digital dermoscopy may further improve the early detection of melanoma.