Review of smartphone mobile applications for skin cancer detection: what are the changes in availability, functionality, and costs to users over time?

Artificial Intelligence Smartphone Application for Detection of Simulated Skin Changes: An In Vivo Pilot Study

BACKGROUND

The development of artificial intelligence (AI) is rapidly expanding, showing promise in the dermatological field. Skin checks are a resource-heavy challenge that could potentially benefit from AI-tool assistance, particularly if provided in widely available AI solutions. A novel smartphone application(app)-based AI system, "SCAI," was developed and trained to recognize spots in paired images of skin, pursuing identification of new skin lesions. This pilot study aimed to investigate the feasibility of the SCAI-app to identify simulated skin changes in vivo.

MATERIALS AND METHODS

The study was conducted in a controlled setting with healthy volunteers and standardized, simulated skin changes (test spots), consisting of customized 3-mm adhesive spots in three colors (black, brown, and red). Each volunteer had a total of eight test spots adhered to four areas on back and legs. The SCAI-app collected smartphone- and template-guided standardized images before and after test spot application, using its backend AI algorithms to identify changes between the paired images.

RESULTS

Twenty-four volunteers were included, amounting to a total of 192 test spots. Overall, the detection algorithms identified test spots with a sensitivity of 92.0% (CI: 88.1-95.9) and a specificity of 95.5% (CI: 95.0-96.0). The SCAI-app's positive predictive value was 38.0% (CI: 31.0-44.9), while the negative predictive value was 99.7% (CI: 99.0-100).

CONCLUSION

This pilot study showed that SCAI-app could detect simulated skin changes in a controlled in vivo setting. The app's feasibility in a clinical setting with real-life skin lesions remains to be investigated, where the challenge with false positives in particular needs to be addressed.

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.

Examining labelling guidelines for AI-based software as a medical device: A review and analysis of dermatology mobile applications in Australia

In recent years, there has been a surge in the development of AI-based Software as a Medical Device (SaMD), particularly in visual specialties such as dermatology. In Australia, the Therapeutic Goods Administration (TGA) regulates AI-based SaMD to ensure its safe use. Proper labelling of these devices is crucial to ensure that healthcare professionals and the general public understand how to use them and interpret results accurately. However, guidelines for labelling AI-based SaMD in dermatology are lacking, which may result in products failing to provide essential information about algorithm development and performance metrics. This review examines existing labelling guidelines for AI-based SaMD across visual medical specialties, with a specific focus on dermatology. Common recommendations for labelling are identified and applied to currently available dermatology AI-based SaMD mobile applications to determine usage of these labels. Of the 21 AI-based SaMD mobile applications identified, none fully comply with common labelling recommendations. Results highlight the need for standardized labelling guidelines. Ensuring transparency and accessibility of information is essential for the safe integration of AI into health care and preventing potential risks associated with inaccurate clinical decisions.

Comparing preferences for skin cancer screening: AI-enabled app vs dermatologist

BACKGROUND AND AIM

Skin cancer is a major public health issue. While self-examinations and professional screenings are recommended, they are rarely performed. Mobile health (mHealth) apps utilising artificial intelligence (AI) for skin cancer screening offer a potential solution to aid self-examinations; however, their uptake is low. Therefore, the aim of this research was to examine provider and user characteristics influencing people's decisions to seek skin cancer screening performed by a mHealth app or a dermatologist.

METHODS

Two forced-choice conjoint experiments with Nmain = 1591 and Nreplication = 308 participants from the United States were conducted online to investigate preferences for screening providers. In addition to the provider type (mHealth app vs dermatologist), the following provider attributes were manipulated: costs, expertise, privacy policy, and result details. Subsequently, a questionnaire assessed various user characteristics, including demographics, attitudes toward AI technology and medical mistrust.

RESULTS

Outcomes were consistent across the two studies. The provider type was the most influential factor, with the dermatologist being selected more often than the mHealth app. Cost, expertise, and privacy policy also significantly impacted decisions. Demographic subgroup analyses showed rather consistent preference trends across various age, gender, and ethnicity groups. Individuals with greater medical mistrust were more inclined to choose the mHealth app. Trust, accuracy, and quality ratings were higher for the dermatologist, whether selected or not.

CONCLUSION

Our results offer valuable insights for technology developers, healthcare providers, and policymakers, contributing to unlocking the potential of skin cancer screening apps in bridging healthcare gaps in underserved communities.

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.

Dermoscopic dark corner artifacts removal: Friend or foe?

BACKGROUND AND OBJECTIVES

One of the more significant obstacles in classification of skin cancer is the presence of artifacts. This paper investigates the effect of dark corner artifacts, which result from the use of dermoscopes, on the performance of a deep learning binary classification task. Previous research attempted to remove and inpaint dark corner artifacts, with the intention of creating an ideal condition for models. However, such research has been shown to be inconclusive due to a lack of available datasets with corresponding labels for dark corner artifact cases.

METHODS

To address these issues, we label 10,250 skin lesion images from publicly available datasets and introduce a balanced dataset with an equal number of melanoma and non-melanoma cases. The training set comprises 6126 images without artifacts, and the testing set comprises 4124 images with dark corner artifacts. We conduct three experiments to provide new understanding on the effects of dark corner artifacts, including inpainted and synthetically generated examples, on a deep learning method.

RESULTS

Our results suggest that introducing synthetic dark corner artifacts which have been superimposed onto the training set improved model performance, particularly in terms of the true negative rate. This indicates that deep learning learnt to ignore dark corner artifacts, rather than treating it as melanoma, when dark corner artifacts were introduced into the training set. Further, we propose a new approach to quantifying heatmaps indicating network focus using a root mean square measure of the brightness intensity in the different regions of the heatmaps.

CONCLUSIONS

The proposed artifact methods can be used in future experiments to help alleviate possible impacts on model performance. Additionally, the newly proposed heatmap quantification analysis will help to better understand the relationships between heatmap results and other model performance metrics.

Position statement of the EADV Artificial Intelligence (AI) Task Force on AI-assisted smartphone apps and web-based services for skin disease

BACKGROUND

As the use of smartphones continues to surge globally, mobile applications (apps) have become a powerful tool for healthcare engagement. Prominent among these are dermatology apps powered by Artificial Intelligence (AI), which provide immediate diagnostic guidance and educational resources for skin diseases, including skin cancer.

OBJECTIVE

This article, authored by the EADV AI Task Force, seeks to offer insights and recommendations for the present and future deployment of AI-assisted smartphone applications (apps) and web-based services for skin diseases with emphasis on skin cancer detection.

METHODS

An initial position statement was drafted on a comprehensive literature review, which was subsequently refined through two rounds of digital discussions and meticulous feedback by the EADV AI Task Force, ensuring its accuracy, clarity and relevance.

RESULTS

Eight key considerations were identified, including risks associated with inaccuracy and improper user education, a decline in professional skills, the influence of non-medical commercial interests, data security, direct and indirect costs, regulatory approval and the necessity of multidisciplinary implementation. Following these considerations, three main recommendations were formulated: (1) to ensure user trust, app developers should prioritize transparency in data quality, accuracy, intended use, privacy and costs; (2) Apps and web-based services should ensure a uniform user experience for diverse groups of patients; (3) European authorities should adopt a rigorous and consistent regulatory framework for dermatology apps to ensure their safety and accuracy for users.

CONCLUSIONS

The utilisation of AI-assisted smartphone apps and web-based services in diagnosing and treating skin diseases has the potential to greatly benefit patients in their dermatology journeys. By prioritising innovation, fostering collaboration and implementing effective regulations, we can ensure the successful integration of these apps into clinical practice.

Advances in Early Detection of Melanoma and the Future of At-Home Testing

The past decade has seen numerous advancements in approaches to melanoma detection, each with the common goal to stem the growing incidence of melanoma and its mortality rate. These advancements, while well documented to increase early melanoma detection, have also garnered considerable criticism of their efficacy for improving survival rates. In this review, we discuss the current state of such early detection approaches that do not require direct dermatologist intervention. Our findings suggest that a number of at-home and non-specialist methods exist with high accuracy for detecting melanoma, albeit with a few notable concerns worth further investigation. Additionally, research continues to find new approaches using artificial intelligence which have promise for the future.

Perspectives and Experiences of Patient-Led Melanoma Surveillance Using Digital Technologies From Clinicians Involved in the MEL-SELF Pilot Randomized Controlled Trial: Qualitative Interview Study

BACKGROUND

The growing number of melanoma patients who need long-term surveillance increasingly exceeds the capacity of the dermatology workforce, particularly outside of metropolitan areas. Digital technologies that enable patients to perform skin self-examination and send dermoscopic images of lesions of concern to a dermatologist (mobile teledermoscopy) are a potential solution. If these technologies and the remote delivery of melanoma surveillance are to be incorporated into routine clinical practice, they need to be accepted by clinicians providing melanoma care, such as dermatologists and general practitioners (GPs).

OBJECTIVE

This study aimed to explore perceptions of potential benefits and harms of mobile teledermoscopy, as well as experiences with this technology, among clinicians participating in a pilot randomized controlled trial (RCT) of patient-led melanoma surveillance.

METHODS

This qualitative study was nested within a pilot RCT conducted at dermatologist and skin specialist GP-led melanoma clinics in New South Wales, Australia. We conducted semistructured interviews with 8 of the total 11 clinicians who were involved in the trial, including 4 dermatologists (3 provided teledermatology, 2 were treating clinicians), 1 surgical oncologist, and 3 GPs with qualifications in skin cancer screening (the remaining 3 GPs declined an interview). Thematic analysis was used to analyze the data with reference to the concepts of "medical overuse" and "high-value care."

RESULTS

Clinicians identified several potential benefits, including increased access to dermatology services, earlier detection of melanomas, reassurance for patients between scheduled visits, and a reduction in unnecessary clinic visits. However, they also identified some potential concerns regarding the use of the technology and remote monitoring that could result in diagnostic uncertainty. These included poor image quality, difficulty making assessments from a 2D digital image (even if good quality), insufficient clinical history provided, and concern that suspicious lesions may have been missed by the patient. Clinicians thought that uncertainty arising from these concerns, together with perceived potential medicolegal consequences from missing a diagnosis, might lead to increases in unnecessary clinic visits and procedures. Strategies suggested for achieving high-value care included managing clinical uncertainty to decrease the potential for medical overuse and ensuring optimal placement of patient-led teledermoscopy within existing clinical care pathways to increase the potential for benefits.

CONCLUSIONS

Clinicians were enthusiastic about the potential and experienced benefits of mobile teledermoscopy; however, managing clinical uncertainty will be necessary to achieve these benefits in clinical care outside of trial contexts and minimize potential harms from medical overuse.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trials Registry ACTRN12616001716459; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371865.

Mobile health applications for pregnancy in Iran: Current state investigation

BACKGROUND

The expansion of pregnancy-related mobile applications has led to an increase in the usage of these applications by Iranian women, which has the potential to have a long-term impact on women's pregnancy health and, as a result, community health. The goal of this research was to investigate the state of pregnancy-related mobile applications in Iran.

MATERIALS AND METHODS

This was a descriptive-applied research approach which was conducted in 2020. One hundred and fifty-seven pregnancy apps from different Iranian mobile app markets were installed and were examined in terms of the resources used and their validity, subject distribution, participation of obstetricians in the app development, apps volume, rank acquired by users and distribution of apps according to the developers. The relationship between the number of resources used and user rankings was also tested.

RESULTS

A total of 157 apps were categorized into 12 subject categories based on their content. Only 1.3% of the apps were developed with the participation of obstetricians. Only 5% of the apps had used reliable information resources. Furthermore, the number of resources referenced in the studied apps did not have a significant relationship with star ratings (r = 0.03, P = 0.64), according to the Pearson correlation test.

CONCLUSION

Iranian mobile applications in the field of pregnancy have grown significantly in terms of quantity, subject diversity, and user acceptance; however, the credibility of the information in these apps cannot be validated. This serves as a reminder to users to exercise caution while using such apps.

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.

Holistic health record for Hidradenitis suppurativa patients

Hidradenitis suppurativa (HS) is a recurrent inflammatory skin disease with a complex etiopathogenesis whose treatment poses a challenge in the clinical practice. Here, we present a novel integrated pipeline produced by the European consortium BATMAN (Biomolecular Analysis for Tailored Medicine in Acne iNversa) aimed at investigating the molecular pathways involved in HS by developing new diagnosis algorithms and building cellular models to pave the way for personalized treatments. The objectives of our european Consortium are the following: (1) identify genetic variants and alterations in biological pathways associated with HS susceptibility, severity and response to treatment; (2) design in vitro two-dimensional epithelial cell and tri-dimensional skin models to unravel the HS molecular mechanisms; and (3) produce holistic health records HHR to complement medical observations by developing a smartphone application to monitor patients remotely. Dermatologists, geneticists, immunologists, molecular cell biologists, and computer science experts constitute the BATMAN consortium. Using a highly integrated approach, the BATMAN international team will identify novel biomarkers for HS diagnosis and generate new biological and technological tools to be used by the clinical community to assess HS severity, choose the most suitable therapy and follow the outcome.

Usefulness of Smartphones in Dermatology: A US-Based Review

(1) Background: As smartphones have become more widely used, they have become an appealing tool for health-related functions. For dermatology alone, hundreds of applications (apps) are available to download for both patients and providers. (2) Methods: The Google Play Store and Apple App Store were searched from the United States using dermatology-related terms. Apps were categorized based on description, and the number of reviews, download cost, target audience, and use of AI were recorded. The top apps from each category by number of reviews were reported. Additionally, literature on the benefits and limitations of using smartphones for dermatology were reviewed. (3) Results: A total of 632 apps were included in the study: 395 (62.5%) were marketed towards patients, 203 (32.1%) towards providers, and 34 (5.4%) towards both; 265 (41.9%) were available only on the Google Play Store, 146 (23.1%) only on the Apple App Store, and 221 (35.0%) were available on both; and 595 (94.1%) were free to download and 37 (5.9%) had a cost to download, ranging from USD 0.99 to USD 349.99 (median USD 37.49). A total of 99 apps (15.7%) reported the use of artificial intelligence. (4) Conclusions: Although there are many benefits of using smartphones for dermatology, lack of regulation and high-quality evidence supporting the efficacy and accuracy of apps hinders their potential.

Skin chromophore mapping by smartphone RGB camera under spectral band and spectral line illumination

SIGNIFICANCE

Multispectral imaging enables mapping of chromophore content changes in skin neoplasms, which helps to diagnose a pathology. Different types of light sources can be used for the imaging. Design of laser-based illuminators is more complicated and, consequently, they are more expensive than LED-based illuminators. On the other hand, spectral line illumination has the advantage of less complicated calculations, since only the discrete maximum wavelengths need to be considered. Spectral band and spectral line approaches for multispectral skin diagnostics have not been compared so far. This can help to evaluate the accuracy and effectiveness of both approaches.

AIM

To compare two specific illumination modalities-spectral band and spectral line illumination-from the point of performance for mapping of in vivo skin chromophores.

APPROACH

Three spectral images of the same skin malformations were captured by a smartphone RGB camera with two different add-on illuminators comprising LED emitters and laser emitters, respectively. Five types of benign skin neoplasms were included in our study. Concentrations of skin melanin, oxy- and deoxy-hemoglobin at image pixel groups were calculated using the Beer-Lambert law.

RESULTS

Skin chromophore maps and statistical analysis of mean concentrations' changes in the neoplasms compared to the surrounding skin are presented and discussed. The data of the laser emitters led to significantly higher (∼10 times) increase of the oxy-hemoglobin values in vascular neoplasms and much lower deoxy-hemoglobin values, if compared to the data obtained by the LED emitters.

CONCLUSIONS

Analysis of the obtained chromophore distribution maps and concentration variations in neoplasms led to conclusion that the spectral line illumination approach is more appropriate for this application. Considering only the peak wavelengths of illumination spectral bands leads to essentially different results if compared to those obtained by spectral line illumination and may cause misinterpretations in the clinical assessment of skin neoplasms.

Cancer worry after facial nonmelanoma skin cancer resection and reconstruction: A 1-year prospective study

OBJECTIVE

Nonmelanoma skin cancer (NMSC) is one of the most diagnosed cancers in the world, with the number of new occurrences rising every year. Most patients with facial skin cancer experience cancer-related worry. Yet, little is known about their worry during the period after cancer treatment. This study aimed to assess the long-term change of cancer worry after surgical treatment in patients with NMSC.

METHODS

Patients undergoing surgery for facial NMSC between December 2017 and March 2020 were asked to complete the FACE-Q Skin Cancer-Cancer Worry scale before (baseline), 3-month, and 1-year post-surgery.

RESULTS

A total of 151 patients completed the baseline and 3-month, and 99 (65.6%) the 1-year post-operative survey. A significant decrease in cancer worry score was seen between baseline and 3-month post-surgery (p < 0.001). No difference was found between the 3-month and 1-year post-surgery scores (p = 0.78). Less improvement in cancer worry was seen for patients who had one facial skin cancer in their medical history (p = 0.001) and patients who had a history of facial surgery (p < 0.001).

CONCLUSION

Post-surgery patients still experience cancer worry. Therefore, targeted counseling might be of value when coping with cancer-related concerns. Patients with a history of facial NMSC and patients with a history of facial surgery might benefit from additional counseling.

Artificial intelligence: how it works and criteria for assessment

Artificial intelligence is a term used to describe computer technology in the modeling of intelligent behavior and critical thinking comparable to that of humans. To date, some of the first areas of medicine to be influenced by advances in artificial intelligence technologies will be those most dependent on imaging. These include ophthalmology, radiology, and dermatology. In connection with the emergence of numerous medical applications, scientists have formulated criteria for their assessment. This list included: clinical validation, regular application updates, functional focus, cost, availability of an information block for specialists and patients, compliance with the conditions of government regulation, and registration. One of the applications that meet all the requirements is the ProRodinki software package, developed for use by patients and specialists in the Russian Federation. Taking into account a widespread and rapidly developing competitive environment, it is necessary to soberly treat the resources of such applications, not exaggerating their capabilities and not considering them as a substitute for a specialist.

IMPROVE 1.0: Individual Monitoring of Psoriasis Activity by Regular Online App Questionnaires and Outpatient Visits

Smartphone apps gain more and more importance in supporting management of chronic diseases. Psoriasis is a highly prevalent, lifelong chronic inflammatory skin disease with a high impact on patient's quality of life. Disease management includes regular topical and systemic treatment of skin lesions as well as co-treatment of metabolic and psychologic disorders. In this study, we investigated the potential of a new smartphone app (IMPROVE 1.0) for individual monitoring of disease activity and disease influencing factors. Twelve out of 50 psoriasis patients asked for study participation performed self-assessment of psoriasis severity, life quality, and stress scores using the app over a period of 1 year. Every 2 months, study participants were carefully examined by a dermatologist in order to control the quality of app-reported data. We found that psoriasis severity and life quality values as entered in the app closely correlate to physician's examination. Furthermore, we detected strong correlations of disease activity with life quality and psoriasis serum biomarker. Temporal relations between psoriasis aggravation and previous changes of lifestyle factors, such as increased stress levels, were observed in individual patients, indicating a high potential for preventive interventions in future psoriasis apps. The vast majority of study participants evaluated IMPROVE 1.0 app positively and wish to include the app into their daily life. Hence, we demonstrate that smartphone apps are a useful tool to raise self-awareness for the dimensions of complex diseases and fully integrate psoriasis patients into individual disease management. These data are important to develop more advanced digital tools supporting the management of chronic diseases in the future.