ABSTRACT
BACKGROUND AND METHODS: The Melanoma Institute of Australia (MIA) and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms were developed to help guide sentinel lymph node biopsy (SLNB) decisions. Although statistically validated, whether these prediction models provide clinical benefit at National Comprehensive Cancer Network guideline-endorsed thresholds is unknown. We conducted a net benefit analysis to quantify the clinical utility of these nomograms at risk thresholds of 5%-10% compared to the alternative strategy of biopsying all patients. External validation data for MIA and MSKCC nomograms were extracted from respective published studies. RESULTS: The MIA nomogram provided added net benefit at a risk threshold of 9% but net harm at 5%-8% and 10%. The MSKCC nomogram provided added net benefit at risk thresholds of 5% and 9%-10% but net harm at 6%-8%. When present, the magnitude of net benefit was small (1-3 net avoidable biopsies per 100 patients). CONCLUSION: Neither model consistently provided added net benefit compared to performing SLNB for all patients. DISCUSSION: Based on published data, use of the MIA or MSKCC nomograms as decision-making tools for SLNB at risk thresholds of 5%-10% does not clearly provide clinical benefit to patients.
Subject(s)
Breast Neoplasms , Melanoma , Humans , Female , Sentinel Lymph Node Biopsy , Nomograms , Lymphatic Metastasis/pathology , Patient Selection , ROC Curve , Melanoma/surgery , Melanoma/pathology , Australia , Lymph Nodes/pathology , Breast Neoplasms/pathologyABSTRACT
The COVID-19 pandemic created a unique challenge to health care systems, requiring rapid implementation of telemedicine services to provide continued care to patients while preserving personal protective equipment and decreasing the risk of disease transmission. Herein, we describe how our institution, an urban cancer center, utilized provider-to-provider telemedicine consultations (interprofessional e-consults) to provide subspecialty access to care to vulnerable patients in the epicenter of a global pandemic.
Subject(s)
COVID-19 , Neoplasms , Telemedicine , Humans , Pandemics , Referral and Consultation , Delivery of Health CareABSTRACT
BACKGROUND: Melanoma screening includes the assessment of changes in melanocytic lesions using images. However, previous studies of normal nevus temporal changes showed variable results and the optimal method for evaluating these changes remains unclear. Our aim was to evaluate the reproducibility of (a) nevus count done at a single time point (method I) versus two time points (method II); and (b) manual and automated nevus diameter measurements. MATERIALS AND METHODS: In a first experiment, participants used either a single time point or a two time point annotation method to evaluate the total number and size of nevi on the back of an atypical mole syndrome patient. A Monte Carlo simulation was used to calculate the variance observed. In a second experiment, manual measurements of nevi on 2D images were compared to an automated measurement on 3D images. Percent difference in the paired manual and automated measurements was calculated. RESULTS: Mean nevus count was 137 in method I and 115.5 in method II. The standard deviation was greater in method I (38.80) than in method II (4.65) (p = 0.0025). Manual diameter measurements had intraclass correlation coefficient of 0.88. The observed mean percent difference between manual and automated diameter measurements was 1.5%. Lightly pigmented and laterally located nevi had a higher percent difference. CONCLUSIONS: Comparison of nevi from two different time points is more consistent than nevus count performed separately at each time point. In addition, except for selected cases, automated measurements of nevus diameter on 3D images can be used as a time-saving reproducible substitute for manual measurement on 2D images.
Subject(s)
Dysplastic Nevus Syndrome , Nevus, Pigmented , Nevus , Skin Neoplasms , Humans , Nevus/diagnostic imaging , Nevus, Pigmented/diagnostic imaging , Reproducibility of Results , Skin Neoplasms/diagnostic imagingSubject(s)
Melanoma , Skin Neoplasms , Humans , Melanoma/diagnosis , Skin Neoplasms/diagnosis , Melanoma, Cutaneous MalignantABSTRACT
Histopathology for tumor margin assessment is time-consuming and expensive. High-resolution full-field optical coherence tomography (FF-OCT) images fresh tissues rapidly at cellular resolution and potentially facilitates evaluation. Here, we define FF-OCT features of normal and neoplastic skin lesions in fresh ex vivo tissues and assess its diagnostic accuracy for malignancies. For this, normal and neoplastic tissues were obtained from Mohs surgery, imaged using FF-OCT, and their features were described. Two expert OCT readers conducted a blinded analysis to evaluate their diagnostic accuracies, using histopathology as the ground truth. A convolutional neural network was built to distinguish and outline normal structures and tumors. Of the 113 tissues imaged, 95 (84%) had a tumor (75 basal cell carcinomas [BCCs] and 17 squamous cell carcinomas [SCCs]). The average reader diagnostic accuracy was 88.1%, with a sensitivity of 93.7%, and a specificity of 58.3%. The artificial intelligence (AI) model achieved a diagnostic accuracy of 87.6 ± 5.9%, sensitivity of 93.2 ± 2.1%, and specificity of 81.2 ± 9.2%. A mean intersection-over-union of 60.3 ± 10.1% was achieved when delineating the nodular BCC from normal structures. Limitation of the study was the small sample size for all tumors, especially SCCs. However, based on our preliminary results, we envision FF-OCT to rapidly image fresh tissues, facilitating surgical margin assessment. AI algorithms can aid in automated tumor detection, enabling widespread adoption of this technique.
Subject(s)
Carcinoma, Basal Cell , Carcinoma, Squamous Cell , Skin Neoplasms , Humans , Skin Neoplasms/diagnostic imaging , Skin Neoplasms/surgery , Mohs Surgery/methods , Artificial Intelligence , Feasibility Studies , Tomography, Optical Coherence/methods , Carcinoma, Basal Cell/diagnostic imaging , Carcinoma, Basal Cell/surgery , Carcinoma, Basal Cell/pathology , Carcinoma, Squamous Cell/diagnostic imaging , Carcinoma, Squamous Cell/surgeryABSTRACT
BACKGROUND: For patients with melanoma, the decision to perform sentinel lymph node biopsy (SLNB) is based on the estimated risk of lymph node metastasis. We assessed 3 melanoma SLNB risk-prediction models' statistical performance and their ability to improve clinical decision making (clinical utility) on a cohort of melanoma SLNB cases. STUDY DESIGN: Melanoma patients undergoing SLNB at a single center from 2003 to 2021 were identified. The predicted probabilities of sentinel lymph node positivity using the Melanoma Institute of Australia, Memorial Sloan Kettering Cancer Center (MSK), and Friedman nomograms were calculated. Receiver operating characteristic and calibration curves were generated. Clinical utility was assessed via decision curve analysis, calculating the net SLNBs that could have been avoided had a given model guided selection at different risk thresholds. RESULTS: Of 2,464 melanoma cases that underwent SLNB, 567 (23.0%) had a positive sentinel lymph node. The areas under the receiver operating characteristic curves for the Melanoma Institute of Australia, MSK, and Friedman models were 0.726 (95% CI, 0.702 to 0.750), 0.720 (95% CI, 0.697 to 0.744), and 0.721 (95% CI, 0.699 to 0.744), respectively. For all models, calibration was best at predicted positivity rates below 30%. The MSK model underpredicted risk. At a 10% risk threshold, only the Friedman model would correctly avoid a net of 6.2 SLNBs per 100 patients. The other models did not reduce net avoidable SLNBs at risk thresholds of ≤10%. CONCLUSIONS: The tested nomograms had comparable performance in our cohort. The only model that achieved clinical utility at risk thresholds of ≤10% was the Friedman model.
Subject(s)
Melanoma , Sentinel Lymph Node , Skin Neoplasms , Humans , Sentinel Lymph Node Biopsy , Melanoma/pathology , Nomograms , Lymphatic Metastasis/pathology , Sentinel Lymph Node/pathology , Lymph Nodes/pathology , Skin Neoplasms/surgery , Skin Neoplasms/pathology , Retrospective StudiesABSTRACT
The use of artificial intelligence (AI) has the potential to improve the assessment of lesions suspicious of melanoma, but few clinical studies have been conducted. We validated the accuracy of an open-source, non-commercial AI algorithm for melanoma diagnosis and assessed its potential impact on dermatologist decision-making. We conducted a prospective, observational clinical study to assess the diagnostic accuracy of the AI algorithm (ADAE) in predicting melanoma from dermoscopy skin lesion images. The primary aim was to assess the reliability of ADAE's sensitivity at a predefined threshold of 95%. Patients who had consented for a skin biopsy to exclude melanoma were eligible. Dermatologists also estimated the probability of melanoma and indicated management choices before and after real-time exposure to ADAE scores. All lesions underwent biopsy. Four hundred thirty-five participants were enrolled and contributed 603 lesions (95 melanomas). Participants had a mean age of 59 years, 54% were female, and 96% were White individuals. At the predetermined 95% sensitivity threshold, ADAE had a sensitivity of 96.8% (95% CI: 91.1-98.9%) and specificity of 37.4% (95% CI: 33.3-41.7%). The dermatologists' ability to assess melanoma risk significantly improved after ADAE exposure (AUC 0.7798 vs. 0.8161, p = 0.042). Post-ADAE dermatologist decisions also had equivalent or higher net benefit compared to biopsying all lesions. We validated the accuracy of an open-source melanoma AI algorithm and showed its theoretical potential for improving dermatology experts' ability to evaluate lesions suspicious of melanoma. Larger randomized trials are needed to fully evaluate the potential of adopting this AI algorithm into clinical workflows.
ABSTRACT
On the basis of the clinical impression and current knowledge, acquired melanocytic nevi and melanomas may not occur in random localizations. The goal of this study was to identify whether their distribution on the back is random and whether the location of melanoma correlates with its adjacent lesions. Therefore, patient-level and lesion-level spatial analyses were performed using the ClarkâEvans test for complete spatial randomness. A total of 311 patients with three-dimensional total body photography (average age of 40.08 [30â49] years; male/female ratio: 128/183) with 5,108 eligible lesions in total were included in the study (mean sum of eligible lesions per patient of 16.42 [3â199]). The patient-level analysis revealed that the distributions of acquired melanocytic neoplasms were more likely to deviate toward clustering than dispersion (average z-score of â0.55 [95% confidence interval = â0.69 to â0.41; P < 0.001]). The lesion-level analysis indicated a higher portion of melanomas (n = 57 of 72, 79.2% [95% confidence interval = 69.4â88.9%]) appearing in proximity to neighboring melanocytic neoplasms than to nevi (n = 2,281 of 5,036, 45.3% [95% confidence interval = 43.9â46.7%]). In conclusion, the nevi and melanomas' distribution on the back tends toward clustering as opposed to dispersion. Furthermore, melanomas are more likely to appear proximally to their neighboring neoplasms than to nevi. These findings may justify various oncogenic theories and improve diagnostic methodology.
Subject(s)
Melanoma , Nevus, Pigmented , Nevus , Skin Neoplasms , Humans , Female , Male , Adult , Skin Neoplasms/pathology , Nevus, Pigmented/pathology , Melanoma/pathology , PhotographyABSTRACT
Tertiary lymphoid structures (TLS) are specialized lymphoid formations that serve as local repertoire of T- and B-cells at sites of chronic inflammation, autoimmunity, and cancer. While presence of TLS has been associated with improved response to immune checkpoint blockade therapies and overall outcomes in several cancers, its prognostic value in basal cell carcinoma (BCC) has not been investigated. Herein, we determined the prognostic impact of TLS by relating its prevalence and maturation with outcome measures of anti-tumor immunity, namely tumor infiltrating lymphocytes (TILs) and tumor killing. In 30 distinct BCCs, we show the presence of TLS was significantly enriched in tumors harboring a nodular component and more mature primary TLS was associated with TIL counts. Moreover, assessment of the fibrillary matrix surrounding tumors showed discrete morphologies significantly associated with higher TIL counts, critically accounting for heterogeneity in TIL count distribution within TLS maturation stages. Specifically, increased length of fibers and lacunarity of the matrix with concomitant reduction in density and alignment of fibers were present surrounding tumors displaying high TIL counts. Given the interest in inducing TLS formation as a therapeutic intervention as well as its documented prognostic value, elucidating potential impediments to the ability of TLS in driving anti-tumor immunity within the tumor microenvironment warrants further investigation. These results begin to address and highlight the need to integrate stromal features which may present a hindrance to TLS formation and/or effective function as a mediator of immunotherapy response.
ABSTRACT
BACKGROUND: Nasal scarring can compromise aesthetics and function given its complex three-dimensional structure and central location. This study aimed to measure patients' satisfaction after reconstruction for nasal defects following Mohs micrographic surgery. METHODS: Patients presenting with nasal nonmelanoma skin cancer at Memorial Sloan Kettering Cancer Center New York, USA and Catharina Hospital Eindhoven, Netherlands from April 2017 to November 2019 were asked to participate. Reconstruction type, complications, and patients satisfaction were assessed. Patients completed the FACE-Q Skin Cancer - Satisfaction with Facial Appearance scale (preoperative and 1-year postoperative) and the Appraisal of Scars scale (1-year postoperative). RESULTS: A total of 128 patients completed the preand postoperative scales. There were 35 (27%) surgical defects repaired with primary closures, 71 (55.5%) with flaps, and 22 (17.2%) with full-thickness skin grafts (FTSG). Patients that underwent a flap or FTSG reconstruction had higher scar satisfaction scores than primary closures (p = 0.03). A trend was seen with patients following flap reconstructions scoring 7.8 points higher than primary closures and patients with upper nose defects scoring 6.4 points higher than lower nose defects. Males were significantly more satisfied than females. No significant difference was observed in the preoperative and postoperative facial appearance scores between the three groups (p = 0.39). CONCLUSION: Patients are more satisfied in the long term with their scars after flap reconstructions compared to primary closures. Therefore, nasal skin reconstruction may not follow the traditional reconstructive ladder and more complex approaches may lead to higher long-term scar satisfaction.
Subject(s)
Nose Neoplasms , Plastic Surgery Procedures , Rhinoplasty , Skin Neoplasms , Female , Humans , Male , Mohs Surgery/adverse effects , Nose/surgery , Nose Neoplasms/surgery , Plastic Surgery Procedures/adverse effects , Plastic Surgery Procedures/methods , Rhinoplasty/methods , Skin Neoplasms/surgery , Surgical Flaps/transplantationABSTRACT
The primary cause of the increase in melanoma incidence in the United States has been suggested to be overdiagnosis. We used Surveillance, Epidemiology, and End Result Program data from 1975 to 2017 to examine epidemiologic trends of melanoma incidence and mortality and better characterize overdiagnosis in white Americans. Over the 43-year period, incidence and mortality showed discordant temporal changes across population subgroups; trends most suggestive of overdiagnosis alone were present in females aged 55-74. Other groups showed mixed changes suggestive of overdiagnosis plus changes in underlying disease risk (decreasing risk in younger individuals and increasing risk in older males). Cohort effects were identified for male and female mortality and male incidence but were not as apparent for female incidence, suggesting that period effects have had a greater influence on changes in incidence over time in females. Encouraging trends included long-term declines in mortality in younger individuals and recent stabilization of invasive incidence in individuals aged 15-44 years and males aged 45-54 years. Melanoma in situ incidence, however, has continued to increase throughout the population. Overdiagnosis appears to be relatively greater in American females and for melanoma in situ.
Subject(s)
Melanoma , Skin Neoplasms , Aged , Female , Humans , Incidence , Male , Melanoma/diagnosis , Melanoma/epidemiology , Overdiagnosis , Skin Neoplasms/diagnosis , Skin Neoplasms/epidemiology , United States/epidemiology , Melanoma, Cutaneous MalignantABSTRACT
BACKGROUND: Previous studies of artificial intelligence (AI) applied to dermatology have shown AI to have higher diagnostic classification accuracy than expert dermatologists; however, these studies did not adequately assess clinically realistic scenarios, such as how AI systems behave when presented with images of disease categories that are not included in the training dataset or images drawn from statistical distributions with significant shifts from training distributions. We aimed to simulate these real-world scenarios and evaluate the effects of image source institution, diagnoses outside of the training set, and other image artifacts on classification accuracy, with the goal of informing clinicians and regulatory agencies about safety and real-world accuracy. METHODS: We designed a large dermoscopic image classification challenge to quantify the performance of machine learning algorithms for the task of skin cancer classification from dermoscopic images, and how this performance is affected by shifts in statistical distributions of data, disease categories not represented in training datasets, and imaging or lesion artifacts. Factors that might be beneficial to performance, such as clinical metadata and external training data collected by challenge participants, were also evaluated. 25 331 training images collected from two datasets (in Vienna [HAM10000] and Barcelona [BCN20000]) between Jan 1, 2000, and Dec 31, 2018, across eight skin diseases, were provided to challenge participants to design appropriate algorithms. The trained algorithms were then tested for balanced accuracy against the HAM10000 and BCN20000 test datasets and data from countries not included in the training dataset (Turkey, New Zealand, Sweden, and Argentina). Test datasets contained images of all diagnostic categories available in training plus other diagnoses not included in training data (not trained category). We compared the performance of the algorithms against that of 18 dermatologists in a simulated setting that reflected intended clinical use. FINDINGS: 64 teams submitted 129 state-of-the-art algorithm predictions on a test set of 8238 images. The best performing algorithm achieved 58·8% balanced accuracy on the BCN20000 data, which was designed to better reflect realistic clinical scenarios, compared with 82·0% balanced accuracy on HAM10000, which was used in a previously published benchmark. Shifted statistical distributions and disease categories not included in training data contributed to decreases in accuracy. Image artifacts, including hair, pen markings, ulceration, and imaging source institution, decreased accuracy in a complex manner that varied based on the underlying diagnosis. When comparing algorithms to expert dermatologists (2460 ratings on 1269 images), algorithms performed better than experts in most categories, except for actinic keratoses (similar accuracy on average) and images from categories not included in training data (26% correct for experts vs 6% correct for algorithms, p<0·0001). For the top 25 submitted algorithms, 47·1% of the images from categories not included in training data were misclassified as malignant diagnoses, which would lead to a substantial number of unnecessary biopsies if current state-of-the-art AI technologies were clinically deployed. INTERPRETATION: We have identified specific deficiencies and safety issues in AI diagnostic systems for skin cancer that should be addressed in future diagnostic evaluation protocols to improve safety and reliability in clinical practice. FUNDING: Melanoma Research Alliance and La Marató de TV3.
Subject(s)
Melanoma , Skin Neoplasms , Artificial Intelligence , Dermoscopy/methods , Humans , Melanoma/diagnostic imaging , Melanoma/pathology , Reproducibility of Results , Skin Neoplasms/diagnostic imaging , Skin Neoplasms/pathologyABSTRACT
Reflectance confocal microscopy (RCM) with endogenous backscattered contrast can noninvasively image basal cell carcinomas (BCCs) in skin. However, BCCs present with high nuclear density, and the relatively weak backscattering from nuclei imposes a fundamental limit on contrast, detectability, and diagnostic accuracy. We investigated PARPi-FL, an exogenous nuclear poly(adenosine diphosphate ribose) polymerase (PARP1)-targeted fluorescent contrast agent, and fluorescence confocal microscopy toward improving BCC diagnosis. Methods: We tested PARP1 expression in 95 BCC tissues using immunohistochemistry, followed by PARPi-FL staining in 32 fresh surgical BCC specimens. The diagnostic accuracy of PARPi-FL contrast was evaluated in 83 surgical specimens. The optimal parameters for permeability of PARPi-FL through intact skin was tested ex vivo on 5 human skin specimens and in vivo in 3 adult Yorkshire pigs. Results: We found significantly higher PARP1 expression and PARPi-FL binding in BCCs than in normal skin structures. Blinded reading of RCM-and-fluorescence confocal microscopy images by 2 experts demonstrated a higher diagnostic accuracy for BCCs with combined fluorescence and reflectance contrast than for RCM alone. Optimal parameters (time and concentration) for PARPi-FL transepidermal permeation through intact skin were successfully determined. Conclusion: Combined fluorescence and reflectance contrast may improve noninvasive BCC diagnosis with confocal microscopy.
Subject(s)
Carcinoma, Basal Cell , Skin Neoplasms , Animals , Carcinoma, Basal Cell/diagnostic imaging , Carcinoma, Basal Cell/pathology , Carcinoma, Basal Cell/surgery , Cell Nucleus/pathology , Immunohistochemistry , Microscopy, Confocal/methods , Skin Neoplasms/diagnostic imaging , Skin Neoplasms/pathology , SwineABSTRACT
Patient expectations of the scar after Mohs micrographic surgery (MMS) are often not realistic, leading to subsequent psychosocial sequelae such as anxiety, depression, and avoidance of social situations. When patient expectations are not met, this may also contribute to a decrease in patient satisfaction after surgery. Therefore, altering expectation levels may change patient satisfaction and psychosocial distress levels after surgery. To assess whether patient satisfaction improves in patients after MMS when patients view the surgical defect prior to reconstruction. Patients undergoing facial MMS between December 2017 and September 2019 were included. Patients received or did not receive a mirror after MMS to view the surgical defect before closing the defect. Patients were asked to complete the Dutch FACE-Q Skin Cancer before, one-week, three-months, and one-year after MMS. A total of 113 patients where included. One-hundred-eight (95.6%), 113 (100%), and 93 (82.3%) questionnaires were completed, one-week, three-months, and one-year follow-up, respectively. Satisfaction with facial appearance and appraisal of scars significantly improved over time for all patients, no such improvement was seen for appearance-related distress. Female patients who looked in the mirror had higher satisfaction with facial appearance than female patients who did not look in the mirror. Also, lower appearance-related distress scores were seen in patients who looked in the mirror prior to a flap reconstruction. Showing the defect in the mirror prior to the reconstruction may result in higher patient satisfaction in female patients and patients before undergoing a flap reconstruction.
Subject(s)
Cicatrix/psychology , Mohs Surgery/adverse effects , Plastic Surgery Procedures/psychology , Skin Neoplasms/surgery , Surgical Wound/psychology , Aged , Aged, 80 and over , Cicatrix/diagnosis , Cicatrix/etiology , Esthetics , Face , Female , Humans , Male , Middle Aged , Netherlands , Patient Satisfaction , Plastic Surgery Procedures/adverse effects , Severity of Illness Index , Surgical Flaps/transplantation , Surgical Wound/surgeryABSTRACT
BACKGROUND: Immune checkpoint inhibitors (ICIs) are approved to treat multiple cancers. Retrospective analyses demonstrate acceptable safety of ICIs in most patients with autoimmune disease, although disease exacerbation may occur. Psoriasis vulgaris is a common, immune-mediated disease, and outcomes of ICI treatment in patients with psoriasis are not well described. Thus we sought to define the safety profile and effectiveness of ICIs in patients with pre-existing psoriasis. METHODS: In this retrospective cohort study, patients from eight academic centers with pre-existing psoriasis who received ICI treatment for cancer were evaluated. Main safety outcomes were psoriasis exacerbation and immune-related adverse events (irAEs). We also assessed progression-free survival (PFS) and overall survival. RESULTS: Of 76 patients studied (50 (66%) male; median age 67 years; 62 (82%) with melanoma, 5 (7%) with lung cancer, 2 (3%) with head and neck cancer, and 7 (9%) with other cancers; median follow-up 25.1 months (range=0.2-99 months)), 51 (67%) received anti-PD-1 antibodies, 8 (11%) anti-CTLA-4, and 17 (22%) combination of anti-PD-1/CTLA-4. All patients had pre-existing psoriasis, most frequently plaque psoriasis (46 patients (61%)) and 15 (20%) with psoriatic arthritis. Forty-one patients (54%) had received any prior therapy for psoriasis although only two (3%) were on systemic immunosuppression at ICI initiation. With ICI treatment, 43 patients (57%) experienced a psoriasis flare of cutaneous and/or extracutaneous disease after a median of 44 days of receiving ICI. Of those who experienced a flare, 23 patients (53%) were managed with topical therapy only; 16 (21%) needed systemic therapy. Only five patients (7%) required immunotherapy discontinuation for psoriasis flare. Forty-five patients (59%) experienced other irAEs, 17 (22%) of which were grade 3/4. PFS with landmark analysis was significantly longer in patients with a psoriasis flare versus those without (39 vs 8.7 months, p=0.049). CONCLUSIONS: In this multicenter study, ICI therapy was associated with frequent psoriasis exacerbation, although flares were manageable with standard psoriasis treatments and few required ICI discontinuation. Patients who experienced disease exacerbation performed at least as well as those who did not. Thus, pre-existing psoriasis should not prevent patients from receiving ICIs for treatment of malignancy.
Subject(s)
Immune Checkpoint Inhibitors/therapeutic use , Psoriasis/drug therapy , Adult , Aged , Aged, 80 and over , Female , Humans , Immune Checkpoint Inhibitors/pharmacology , Male , Middle Aged , Retrospective StudiesABSTRACT
This survey study reports the perspectives and preferences of US adults regarding use of photographs of their skin in medical research, education, and development of image-based artificial intelligence (AI).