REVIEW

Teledermoscopy – An Emerging Technology for Skin Cancer Detection

Kristen Delans, BS^1*, Elianna Goldstein, BS², James M. Grichnik, MD, PhD³, Beth Goldstein, MD⁴ and Adam O. Goldstein, MD, MPH⁵

¹Virginia Commonwealth University School of Medicine, Richmond, Virginia, USA; ²Skinvest, Inc., Chapel Hill, North Carolina, USA; ³Dermatology and Cutaneous Surgery, University of South Florida Health Morsani College of Medicine, Tampa, Florida, USA; ⁴Department of Dermatology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA; ⁵Department of Family Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

Keywords: dermoscopy; dermatoscopy; melanoma; skin cancer; smartphone teledermatology; teledermoscopy; telehealth

Abstract

Dermatology faces a worsening scarcity of providers, especially since the onset of the COVID-19 pandemic. With lengthening waiting periods for skin cancer screening examinations, there is a distinct need for alternatives to in-person evaluation. Delayed diagnosis is associated with poorer outcomes, especially in melanoma. Teledermatology has the potential to prevent the increased morbidity and mortality associated with late-stage diagnosis, especially when utilized with dermoscopy. In the literature, this novel field of ‘teledermoscopy’ has exhibited accuracy and reliability comparable to face-to-face visits, and it is a promising alternative intervention for those who require triaging or for patients who are unable to access in-person care (rural, underserved populations). Although early data are promising, formal guidelines for acquisition and interpretation of dermatoscopic images must be established before wider implementation is possible. With standardization, use at home or in primary care offices might relieve some of the pressure on an overburdened dermatologic care system and help patients requiring urgent care to be seen more expediently.

 

 

Morbidity and mortality of melanoma and nonmelanoma skin cancers continue to rise in the United States and globally. Global melanoma cases are projected to increase to over 500,000 new cases and almost 100,000 deaths annually; in the United States, by 2040, melanoma is projected to be the second most common cancer among women and the most common cancer annually among men.^1,2

The annual cost of treating such skin cancers in the United States is estimated at $8.1 billion.³ A large portion of the time and expense associated with skin cancer treatment, worldwide, can be attributed to late-stage carcinomas. This is especially true in melanoma – the third most common but overall the deadliest form of skin cancer.^4,5 This review focuses on newer advances in technology-based modalities, such as teledermoscopy, to improve skin cancer detection, along with barriers and research needs to broader adoption of such modalities.⁶

Skin Cancer Prevention and Screening

Considerable research has focused on improving primary and secondary prevention strategies, such as reducing sun exposure and indoor tanning, wearing sun-protective clothing, and using sunscreens.^7–9 However, with rising cases and, subsequently, rising treatment costs, research works into early melanoma and nonmelanoma skin cancer detection interventions are crucial. Further efforts to decrease the morbidity and mortality of skin cancer may involve improved diagnostic accuracy of screening tools and increased access to screening exams at regular intervals.^10–12 Improved screening methods also decrease wait times for seeing providers and decrease the anxiety prevalent among patients at risk of skin cancer.

The relative scarcity of dermatology providers and the growing demand for appointments only exacerbate this issue. With 40% of the United States classified as a ‘dermatology desert’, the lack of physical access to dermatology specialists has resulted in significant delays for skin cancer screening.¹³ This provider shortage poses a danger to patients with skin cancer, especially those facing a melanoma diagnosis. Even short delays in evaluation, diagnosis, and treatment for melanomas can impact outcomes.^14,15 For these reasons, it is vital for the healthcare system to advance and implement skin cancer screening alternatives for at-risk patients.^12,16,17

Dermoscopy In Clinical Practice

One of the most frequently utilized non-invasive screening tools in dermatology is the dermoscope – a hand-held device that uses light and magnification to help trained clinicians examine a patient’s skin.^18,19 Most dermatologists utilize dermoscopy to view moles and other skin lesions at a microscopic level. In the hands of an experienced physician, specific or characteristic findings greatly aid in diagnosis.²⁰ Additionally, dermoscopy allows for further discrimination of concerning features between lesions that might look similar to the unaided eye, allowing for more accurate identification among malignant lesions.^20,21

A recent Cochrane Review demonstrated that dermoscopy in a trained user was more effective in diagnosing melanoma than simple visual inspection of the skin.²² When used correctly, a dermoscope is an effective tool for not only dermatologists but also practitioners of multiple specialties. Studies on the feasibility and accuracy of dermoscopic use in primary care clinics demonstrate that, with proper training and education, primary care providers find dermoscopy a valuable resource in identifying skin lesions.²³ Despite a generally positive reception by family physicians in research studies, a number of obstacles remain to widely implement dermoscopic evaluation in primary care, including a need for increased access to the tool itself, improved training, and a change in perception surrounding the complexity of use.^23,24 In addition to increasing the chances of detecting skin cancer during routine physical examination, expansion of dermoscopy use into primary care offices has also prompted investigation of the possible role for dermoscopic evaluation in the telehealth setting. However, it is important to note that there is an ongoing learning curve with dermoscopy, and biopsy rates are often higher early in training. Therefore, it is important to gain sufficient experience in order to improve accuracy.

Teledermatology and Skin Cancer Detection

Teledermatology is a growing option that complements traditional in-person dermatology visits. Since the COVID-19 pandemic, significant growth has occurred in utilization of telehealth dermatology (‘teledermatology’).^25,26 Recent research demonstrates that dermatologists and patients are comfortable addressing many conditions remotely during video-enabled visits. Superficial infections, scars, eczema, and pigmentary disorders are all conditions where dermatologists report ‘maximum’ levels of confidence diagnosing and treating remotely.^27,28 General increases have also occurred in physician confidence pre- and post-intervention in teledermatology studies.^27,29 An increase in the utilization of teledermatology offers an opportunity to decrease the backlog for dermatologic care and reduce wait times for skin cancer screening appointments. This is especially important for rural and underserved patient populations, which often experience a disproportionate backlog for dermatologic care compared to their urban counterparts.^30–32 Teledermatology allows for triaging patients on order to reserve in-office care for those who truly require a face-to-face (FTF) encounter.³³

Multiple issues arise considering teledermatology and skin cancer detection. For instance, without the use of a dermoscope, teledermatology has more limited evidence on its ability to accurately triage lesions from the initial remote visit to the office.³⁴ For instance, sensitivity for diagnosis of melanoma using just photo images might be as low as 59%, and specificity might also be as low as 30%. Such poor diagnostic thresholds may relate to inadequate acquisition of high-quality images from the patient to the provider.

Teledermoscopy and skin cancer detection

‘Teledermoscopy’ is a term that describes dual utilization of telehealth technology and virtual transmission of dermoscopic images.^35,36 The utilization of dermoscopic techniques out-of-office via telemedicine may be used to better differentiate benign lesions from more worrisome lesions that require more timely intervention to rule out cancerous growth.³⁷ For instance, the combination approach increases diagnostic skin cancer sensitivity to 85% and specificity to 92%.³⁴ When used in conjunction with video-visit and patient portal technology, teledermoscopy may support easing in scheduling burdens experienced by dermatologic providers.^10,26 Teledermoscopy appears to effectively triage ‘spot checks’, sending the most concerning lesions to be seen in-person quickly, while reassuring clearly benign lesions that might allow patients to avoid an in-person encounter altogether.^35–39 For those patients without ready access to a dermatologist due to financial or geographic limitation, teledermoscopy may afford the only opportunity for early detection of cutaneous malignancies.^40,41

A recent study by Sangeeta et al. in 2019 compared the effectiveness of FTF workflows with teledermoscopy in the diagnosis of skin cancer. Teledermoscopy was proven superior to traditional referral for the detection of cancer. In this study (which was conducted using a dermoscope-fitted digital camera, a picture archiving and communication system, and image retrieval), teledermoscopy was associated with a 39% reduction in the need for in-person evaluation.⁴² In a 2015 study by Boerve et al., 816 patients referred via smartphone-facilitated teledermoscopy were compared to 746 patients referred via the traditional paper-based system. The results demonstrated that, when surgical treatment was required, patients who had melanoma, melanoma in situ, squamous cell carcinoma, and basal cell carcinoma had significantly shorter wait times when referred via teledermoscopy compared to direct referrals. The use of teledermoscopy also increased the accuracy of triage decisions; and only 0.4% of the referrals had to be excluded due to poor image quality.⁴³

Several studies have been conducted comparing the accuracy of in-person examinations to those of teledermoscopy (with subsequent physician diagnosis via images). The accuracy of diagnosis via teledermoscopy is contingent on the experience of the observer and the difficulty of characterization of a given lesion. However, studies have, for the most part, demonstrated biopsy-proven consensus between the two screening modalities.^44,45 One recent study in Denmark revealed that among 600 skin lesions evaluated by teledermoscopy and subsequently compared to FTF evaluation, the concordance between FTF and teledermoscopy, and the interobserver concordance of two separate teledermoscopy evaluations were moderate to substantial (AC1 = 0.57–0.71).⁴⁵ Piccolo et al. conducted a similar study in 2000, where histopathology was acknowledge as the gold standard in dermatologic diagnoses. Notably, however, 85% of the diagnoses reached by teledermoscopy were correct (results varied from 77 to 75%), a result similar to the accuracy of FTF diagnosis (reported to be 91%).⁴⁴

Patient comfort and proficiency in teledermoscopic evaluation of skin lesions are also important components of teledermoscopy. In one study, both the diagnostic concordance of teledermoscopy and patient’s receptiveness to the modality were investigated in short-term monitoring of nevi. The study reported 97% agreement with decisions made by clinical dermatologists, and patients were largely amenable to teledermoscopy for monitoring between in-person visits.

Challenges to Improved Skin Cancer Detection and Triage Using Teledermoscopy

Teledermoscopy faces distinct barriers in patient care compared to in-person visits. One of the most crucial constraints to teledermoscopy is effective evaluation of malignant lesions through access to dermoscopic images. Repeatedly, physicians report that their ability to remotely rule out skin cancers, especially melanoma, is dependent on a concomitant use of such dermatoscopic images.^27,29

Patients and providers may be concerned with costs associated with the utilization of teledermoscopy in their care. While teledermoscopy may increase immediate upfront costs for patients, they may find the added expense is an acceptable trade-off for the decrease in wait time to evaluation. In an Australian study completed in 2018, although there was a slight increase in overall healthcare cost associated with the utilization of teledermoscopy in dermatologic evaluation, it was also associated with a decrease in time to intervention (mean wait time decreased by 26 days).⁴⁶

In addition, the cost for the equipment must be considered. High-end dermatoscopes, such as DermLite DL3N ($1,500 USD), are likely beyond the acceptable price range for home-dermoscopy users.⁴⁷ Fortunately, the literature contains evidence that more affordable options might be available for both primary care providers and home-dermoscopy users. Unconventional methods, such as using clip-on mobile lenses (traditionally used to checking currency bills, and easily available online for as low as $6 USD) plus a smartphone camera may be used to capture high-quality images of cutaneous lesions. This alternative tool does lack a polarized light source, but utilization of an interface medium (such as ultrasound gel) produces similar results at very low cost.⁴⁸

While several studies utilizing teledermoscopy report good accuracy compared to FTF visits, not all studies have demonstrated concordance between the two modalities for evaluation. Comprehensive findings on the accuracy of teledermoscopy were reported in a larger scale 2017 review by Finnane et al. The paper investigated diagnostic accuracy (defined as agreement with histopathology for excised lesions or clinical diagnosis for non-excised lesions) of FTF dermatology consultation versus teledermoscopy as reported by 21 separate studies. The review demonstrated that the accuracy of FTF consultation was higher (67 to 85% agreement with reference standard) when compared with teledermatology (51 to 85% agreement with reference standard), for the diagnosis of skin cancer.⁴⁹ The literature also includes evidence that teledermoscopy may increase the accuracy of providers who do not have dermatologic training and allow for inclusion of outside specialties in triaging patients. The accuracy and reliability of teledermoscopy versus clinical diagnosis for skin cancers by general practitioners and surgical specialists (when diagnostic algorithms were utilized) was reported in one investigation. It demonstrated a diagnostic accuracy between teledermoscopic and histopathologic diagnosis at 90.91% – an improvement compared to clinical evaluation alone (accuracy was 82.64%).

FTF visits likely result in a higher ‘yield’ than teledermoscopy alone. In a study by Janda et al., 42 additional lesions were noted during clinical skin examination compared to dermoscopy (20 in the intervention group and 22 in the control group), including one clinically presenting as melanoma (dysplastic nevus), two basal cell carcinomas (one confirmed in the intervention group, and one resolved before surgery in the control group), and one squamous cell carcinoma (confirmed in the intervention group). Additionally, it was noted that some areas of the body are not easily viewed by the patient and may be missed on self-examination.⁵⁰ It should be noted that while many patients are open to utilizing teledermoscopy as an additional screening tool, some patients lack confidence in their ability to identify cancerous lesions. Therefore, patient education and skill in taking accurate images are other items to consider in the teledermoscopy implementation. Rather than replacing FTF evaluation altogether, most patients state that they would prefer performing self-examinations in-between in-person visits, to monitor for change.⁵¹

Widespread implementation of home teledermoscopy will also benefit from standardization and guidelines for use. In a 2022 article by Camaj Deda et al., a detailed methodology is described; the goal of the article is to outline a protocol for dermatoscopic image acquisition that is reproducible and reliable. The paper contains checklists that describe lighting, background, resolution, color, and other important considerations that affect the quality of dermatoscopic store-and-forward (SAF) images. These guidelines are a promising start to address the need for standardization of teledermoscopy. However, as the authors mention, there still exists a need for validated diagnostic criteria and standardized characteristics when examining home dermoscopy images.⁵² Additionally, systemic protocols must be in place for dermatoscopic images that are taken by patients at home or in the primary care setting. Once collected, reading by a trained dermatologist may be possible via direct communication with patients’ charts or with remote partnerships between primary care providers and dermatologists. As new advances are made in the realm of teledermoscopy, it may also become possible for artificial intelligence (AI) software to read these dermoscopy images.

Future Directions

The utilization of AI software in the evaluation of suspicious skin lesions is an additional new development in the field of dermatology. A large 2022 study compared the accuracy of trained AI algorithms vs. 18 dermatologists in the diagnosis of skin lesions using dermatoscopic images. The algorithms performed better than experts in most categories, with the exception of actinic keratoses (similar accuracy on average) and images from categories not included in algorithmic training data.⁵³ Stiff et al. evaluated the advantages and challenges of AI in the detection of melanoma using dermoscopy in a 2022 review article. They concluded that AI may offer benefits beyond diagnosis; it can detect features that predict melanoma prognosis such as likelihood of response to immune checkpoint inhibitors and may be able to classify patients as ‘high risk’ (which coincides with a significantly decreased chance for progression-free survival).⁵⁴

Disparities in the delivery of care to skin-of-color patients are a growing topic of conversation in the dermatologic community. The literature suggests minority patients experience delayed diagnosis and poorer outcomes compared to their Caucasian counterparts for a variety of dermatologic conditions, including melanoma.^55–58 A concerted effort must be put forth to avoid perpetuating these disparities in the development of AI software for utilization in teledermoscopic evaluation.⁵⁹ Recent studies have commented on the image collections used to train AI software, pointing out a distinct paucity in reference images containing darker skin tones.^60–62 A recent study by Daneshjou et al. pointed out the challenge of developing an unbiased and accurate data set for AI training, and the importance of fine-tuning AI models to close the performance gap between light and dark skin tones.⁶⁰ Future research and development should emphasize the importance of training AI software to recognize and accurately diagnose dermatoscopic images in patients of all skin tones.

With smartphone ownership increasing to 85% of adult Americans over the past decade, the use of smartphone-compatible dermoscopes, as well as smartphone applications specifically designed for live or SAF (Software Agent Framework) evaluation, is a growing subject of research and development. Smartphones are able to capture high-quality images, and more options for dermoscope attachments are available for purchase.⁶³ The integration of these smartphone attachments with SAF software, teledermatology, and even AI technology might vastly increase the opportunities for skin cancer screening in patients who otherwise lack access. However, there are several areas of concern that are critical to successful widespread implementation of home dermoscopy for skin cancer screening, including continued improvements in SAF software, standardized image acquisition, effective communication within electronic medical records, and clear guidelines for patient education and follow-up.

Conclusions

With rising demands for dermatologic evaluation and a relative scarcity of providers, there is a clear need to implement triaging mechanisms to expand access to care. Teledermoscopy may offer such a solution; however, the intervention does have room for improvement as a screening tool when compared to traditional in-person evaluation by a dermatologist. Additionally, reviews of teledermoscopy have noted methodological limitations in many studies, indicating a need for more standardized data collection.⁴⁹ Optimization and standardization of methodologies used in future studies are crucial. Study data that accurately report the conditions under which teledermoscopy is successful will increase the likelihood of the intervention becoming a more widely used screening tool.

Many of the findings reported in these preliminary studies are promising, as they establish a possible role for teledermoscopy in bridging the care gap left by the shortage of community dermatologists, especially in rural and underserved areas. With the demand for dermatology appointments far exceeding supply, it is crucial to triage complaints and allocate in-person visits to those who truly require FTF treatment.⁴³ While not a replacement for FTF total body skin examinations, teledermoscopy is an attractive tool to decrease the burden of skin cancers and improve screening, especially in populations with limited access to dermatological care.^64,65 Implementation of teledermoscopy may reduce unnecessary biopsies by enabling home monitoring of suspicious lesions. It also may increase the overall cost-efficiency of dermatologic care by reducing the number of unnecessary in-person visits for clearly benign skin lesions.

Contributors

Kristen Delans wrote much of the first draft of the manuscript. Elianna Goldstein, James Grichnik, Adam Goldstein, and Beth Goldstein contributed portions of the introduction, discussion, and conclusions. All authors participated in organization and content of the article.

Acknowledgments

None.

References

1. Rahib L, Wehner MR, Matrisian LM, Nead KT. Estimated projection of US cancer incidence and death to 2040. JAMA Netw Open 2021; 4(4). doi: 10.1001/jamanetworkopen.2021.4708
2. Arnold M, Singh D, Laversanne M, Vignat J, Vaccarella S, Meheus F, et al. Global burden of cutaneous melanoma in 2020 and projections to 2040. JAMA Dermatol 2022 May 1; 158(5): 495. doi: 10.1001/jamadermatol.2022.0160
3. Skin Cancer Foundation. Skin cancer facts & statistics. New York: Skin Cancer Foundation; 2022.
4. Guy GP, Machlin SR, Ekwueme DU, Yabroff KR. Prevalence and costs of skin cancer treatment in the U.S., 2002–2006 and 2007–2011. Am J Prev Med 2015; 48(2). doi: 10.1016/j.amepre.2014.08.036
5. Guy GP, Ekwueme DU, Tangka FK, Richardson LC. Melanoma treatment costs: a systematic review of the literature, 1990–2011. Am J Prev Med 2012; 43(5): 537–45. doi: 10.1016/j.amepre.2012.07.031
6. Leachman SA, Cassidy PB, Chen SC, Curiel C, Geller A, Gareau D, et al. Methods of Melanoma Detection. Cancer Treat Res. 2016; 167: 51–105. doi: 10.1007/978-3-319-22539-5_3
7. Grossman DC, Curry SJ, Owens DK, Barry MJ, Caughey AB, Davidson KW, et al. Behavioral counseling to prevent skin cancer: US preventive services task force recommendation statement. JAMA. 2018; 319(11): 1134–1142. doi: 10.1001/jama.2018.1623
8. King SC, Chen S. Analyzing the cost of preventing nonmelanoma skin cancer. J Investig Dermatol 2009; 129. doi: 10.1038/jid.2009.237
9. Akamine KL, Gustafson CJ, Davis SA, Levender MM, Feldman SR. Trends in sunscreen recommendation among US physicians. JAMA Dermatol. 2014; 150(1): 51–5. doi: 10.1001/jamadermatol.2013.4741
10. Coustasse A, Sarkar R, Abodunde B, Metzger BJ, Slater CM. Use of teledermatology to improve dermatological access in rural areas. Telemed J E Health 2019; 25(11): 1022–32. doi: 10.1089/tmj.2018.0130
11. Zakaria A, Maurer T, Su G, Amerson E. Impact of teledermatology on the accessibility and efficiency of dermatology care in an urban safety-net hospital: a pre-post analysis. J Am Acad Dermatol 2019; 81(6). doi: 10.1016/j.jaad.2019.08.016
12. Lange M, Plorina EV, Lihacova I, Derjabo A, Spigulis J. Skin cancer screening – better safe than sorry. SHS Web Conf 2020; 85. doi: 10.1051/shsconf/20208502003
13. Kimball AB, Resneck JS. The US dermatology workforce: a specialty remains in shortage. J Am Acad Dermatol 2008; 59(5): 741–5. doi: 10.1016/j.jaad.2008.06.037
14. Cortez JL, Fadadu RP, Konda S, Grimes B, Wei ML. Disparities in access for melanoma screening by region, specialty, and insurance: a cross-sectional audit study. JAAD Int 2022; 7: 78–85. doi: 10.1016/j.jdin.2022.02.008
15. Suneja T, Smith ED, Chen JG, Zipperstein KJ, Fleischer J, Feldman SR. Waiting times to see a dermatologist are perceived as too long by dermatologists: implications for the dermatology workforce. Arch Dermatol 2001; 137(10): 1303–7. doi: 10.1001/archderm.137.10.1303
16. Narayanamurthy V, Padmapriya P, Noorasafrin A, Pooja B, Hema K, Firus Khan AY, et al. Skin cancer detection using non-invasive techniques. RSC Adv 2018; 8. doi: 10.1039/C8RA04164D
17. Lamm R, Lyons W, So W, Willis AI. Advanced-stage melanoma at presentation following the peak of the pandemic: a COVID-19 cancer canary in a Coal Mine. World J Surg 2022; 46(8): 1820–5. doi: 10.1007/s00268-022-06623-9
18. Greaney L, King I. Dermoscopy – dermatologists only? Br J Oral Maxillofac Surg 2017; 55(10). doi: 10.1016/j.bjoms.2017.08.300
19. Chen YA, Seiverling E, Rill J. Analysis of dermoscopy teaching modalities in United States dermatology residency programs. Dermatol Pract Concept 2017; 7(3): 38–4. doi: 10.5826/dpc.070308
20. Errichetti E, Stinco G. The practical usefulness of dermoscopy in general dermatology. G Ital Dermatol Venereol 2015; 150(1–2): 1–14.
21. Hoorens I, Vossaert K, Lanssens S, Dierckxsens L, Argenziano G, Brochez L. Value of dermoscopy in a population-based screening sample by dermatologists. Dermatol Pract Concept 2019; 9(3): 200–6. doi: 10.5826/dpc.0903a05
22. Dinnes J, Deeks JJ, Chuchu N, Ferrante di Ruffano L, Matin RN, Thomson DR, et al. Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults. Cochrane Database Syst Rev 2018; 2018. doi: 10.1002/14651858.CD011902.pub2
23. Williams NM, Marghoob AA, Seiverling E, Usatine R, Tsang D, Jaimes N. Perspectives on dermoscopy in the primary care setting. J Am Board Fam Med 2020; 33(6): 1022–4. doi: 10.3122/jabfm.2020.06.200238
24. Jones OT, Jurascheck LC, van Melle MA, Hickman S, Burrows NP, Hall PN, et al. Dermoscopy for melanoma detection and triage in primary care: a systematic review. BMJ Open 2019; 9: e027529. doi: 10.1136/bmjopen-2018-027529
25. Hadeler E, Gitlow H, Nouri K. Definitions, survey methods, and findings of patient satisfaction studies in teledermatology: a systematic review. Arch Dermatol Res 2021; 313: 205–15. doi: 10.1007/s00403-020-02110-0
26. Maddukuri S, Patel J, Lipoff JB. Teledermatology addressing disparities in health care access: a review. Curr Dermatol Rep 2021; 10: 40–7. doi: 10.1007/s13671-021-00329-2
27. Giavina Bianchi M, Santos A, Cordioli E. Dermatologists’ perceptions on the utility and limitations of teledermatology after examining 55,000 lesions. J Telemed Telecare 2021; 27(3): 166–73. doi: 10.1177/1357633X19864829
28. Singh SR, Meka AP, Nguyen G, Tejasvi T. Teledermoscopy for teledermatology. Curr Dermatol Rep 2016; 5: 71–6. doi: 10.1007/s13671-016-0133-x
29. Dovigi E, Kwok EYL, English JC. A framework-driven systematic review of the barriers and facilitators to teledermatology implementation. Curr Dermatol Rep 2020; 9: 353–61. doi: 10.1007/s13671-020-00323-0
30. Raef HS, Hourihan M, Macdonald JM, Lewis J, Seiverling EV. Addressing geographic disparities in dermatology through virtual educational outreach. SKIN J Cutan Med 2022; 6(1): 36–40. doi: 10.25251/skin.6.1.6
31. Marson J, Litchman G, Rigel D. Differential impact of COVID-19 on urban versus rural dermatologic practice logistics and recovery: a cross-sectional investigation of the first wave. SKIN J Cutan Med 2021; 5(2): 118–24. doi: 10.25251/skin.5.2.6
32. Osborne N, Muzumdar S, Mostow EN, Feng H. Rural dermatology: statistical measures and epidemiology. In: Dermatology in rural settings. 2021.
33. Tan E, Yung A, Jameson M, Oakley A, Rademaker M. Successful triage of patients referred to a skin lesion clinic using teledermoscopy (IMAGE IT trial). Br J Dermatol 2010; 162(4): 803–11. doi: 10.1111/j.1365-2133.2010.09673.x
34. Chuchu N, Dinnes J, Takwoingi Y, Matin RN, Bayliss SE, Davenport C, et al. Teledermatology for diagnosing skin cancer in adults. Cochrane Database Syst Rev 2018; 2018. doi: 10.1002/14651858.CD013193
35. Kong F, Horsham C, Rayner J, Simunovic M, O’Hara M, Peter Soyer H, et al. Consumer preferences for skin cancer screening using mobile teledermoscopy: a qualitative study. Dermatology 2020; 236(2): 97–104. doi: 10.1159/000505620
36. Horsham C, Snoswell C, Vagenas D, Loescher LJ, Gillespie N, Peter Soyer H, et al. Is teledermoscopy ready to replace face-to-face examinations for the early detection of skin cancer? Consumer views, technology acceptance, and satisfaction with care. Dermatology 2020; 236(2): 90–6. doi: 10.1159/000506154
37. Bruce AF, Mallow JA, Theeke LA. The use of teledermoscopy in the accurate identification of cancerous skin lesions in the adult population: a systematic review. J Telemed Telecare 2018; 24. doi: 10.1177/1357633X16686770
38. Gilling S, Mortz CG, Vestergaard T. Patient satisfaction and expectations regarding mobile teledermoscopy in general practice for diagnosis of non-melanoma skin cancer and malignant melanoma. Acta Derm Venereol 2020; 100(8). doi: 10.2340/00015555-3459
39. Uppal SK, Beer J, Hadeler E, Gitlow H, Nouri K. The clinical utility of teledermoscopy in the era of telemedicine. Dermatol Ther 2021; 34. doi: 10.1111/dth.14766
40. Lee KJ, Finnane A, Soyer HP. Recent trends in teledermatology and teledermoscopy. Rev Dermatol Pract Concept 2018; 8(3): 214–23. doi: 10.5826/dpc.0803a013
41. Hue L, Makhloufi S, Sall N’diaye P, Blanchet-Bardon C, Sulimovic L, Pomykala F, et al. Real-time mobile teledermoscopy for skin cancer screening targeting an agricultural population: an experiment on 289 patients in France. J Eur Acad Dermatol Venereol 2016 Jan; 30(1): 20–4. doi: 10.1111/jdv.13404
42. Marwaha SS, Fevrier H, Alexeeff S, Crowley E, Haiman M, Pham N, et al. Comparative effectiveness study of face-to-face and teledermatology workflows for diagnosing skin cancer. J Am Acad Dermatol 2019; 81(5): 1099–106. doi: 10.1016/j.jaad.2019.01.067
43. Börve A, Dahlén Gyllencreutz J, Terstappen K, Johansson Backman E, Alden-Bratt A, Danielsson M, et al. Smartphone teledermoscopy referrals: a novel process for improved triage of skin cancer patients. Acta Derm Venereol 2015; 95(2): 186–90. doi: 10.2340/00015555-1906
44. Piccolo D, Smolle J, Argenziano G, Wolf IH, Braun R, Cerroni L, et al. Teledermoscopy – results of a multicentre study on 43 pigmented skin lesions. J Telemed Telecare 2000; 6(3). doi: 10.1258/1357633001935202
45. Vestergaard T, Prasad SC, Schuster A, Laurinaviciene R, Andersen MK, Bygum A. Diagnostic accuracy and interobserver concordance: teledermoscopy of 600 suspicious skin lesions in Southern Denmark. J Eur Acad Dermatol Venereol 2020; 34(7). doi: 10.1111/jdv.16275
46. Snoswell CL, Caffery LJ, Whitty JA, Soyer HP, Gordon LG. Cost-effectiveness of skin cancer referral and consultation using teledermoscopy in Australia. JAMA Dermatol 2018; 154(6): 694–700. doi: 10.1001/jamadermatol.2018.0855
47. Acharya P, Mathur M. Use of a mobile application to perform video dermatoscopy with a handheld dermatoscope. J Am Acad Dermatol 2021; 84(3): 139–14. doi: 10.1016/j.jaad.2019.06.1316
48. Gupta S, Aggarwal K, Yadav A, Gujrathi A. Low-cost video dermatoscope using an inexpensive clip-on lens. JAAD Int 2020; 1: 9–10. doi: 10.1016/j.jdin.2020.02.002
49. Finnane A, Dallest K, Janda M, Soyer HP. Teledermatology for the diagnosis and management of skin cancer: a systematic review. JAMA Dermatol 2017; 153. doi: 10.1001/jamadermatol.2016.4361
50. Janda M, Loescher LJ, Banan P, Horsham C, Soyer HP. Lesion selection by melanoma high-risk consumers during skin self-examination using mobile teledermoscopy. JAMA Dermatol 2014; 150: 656–8. doi: 10.1001/jamadermatol.2013.7743
51. Koh U, Horsham C, Soyer HP, Loescher LJ, Gillespie N, Vagenas D, et al. Consumer acceptance and expectations of a mobile health application to photograph skin lesions for early detection of melanoma. Dermatology 2018; 235(1): 4–10. doi: 10.1159/000493728
52. Camaj Deda L, Goldberg RH, Jamerson TA, Lee I, Tejasvi T. Dermoscopy practice guidelines for use in telemedicine. NPJ Digit Med 2022 Apr 27; 5(1): 55. doi: 10.1038/s41746-022-00587-9
53. Combalia M, Codella N, Rotemberg V, Carrera C, Dusza S, Gutman D, et al. Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge. Lancet Digit Health 2022 May; 4(5): e330–9. doi: 10.1016/S2589-7500(22)00021-8
54. Stiff KM, Franklin MJ, Zhou Y, Madabhushi A, Knackstedt TJ. Artificial intelligence and melanoma: a comprehensive review of clinical, dermoscopic, and histologic applications. Pigment Cell Melanoma Res 2022; 35: 203–11. doi: 10.1111/pcmr.13027
55. Agbai ON, Buster K, Sanchez M, Hernandez C, Kundu RV, Chiu M, et al. Skin cancer and photoprotection in people of color: a review and recommendations for physicians and the public. J Am Acad Dermatol 2014; 70(4): 748–62. doi: 10.1016/j.jaad.2013.11.038
56. Sierro TJ, Blumenthal LY, Hekmatjah J, Chat VS, Kassardjian AA, Read C, et al. Differences in health care resource utilization and costs for keratinocyte carcinoma among racioethnic groups: a population-based study. J Am Acad Dermatol 2022; 86(2): 373–8. doi: 10.1016/j.jaad.2021.07.005
57. Brady J, Kashlan R, Ruterbusch J, Farshchian M, Moossavi M. Racial disparities in patients with melanoma: a multivariate survival analysis. Clin Cosmet Investig Dermatol 2021; 14: 547–50. doi: 10.2147/CCID.S311694
58. Hogue L, Harvey VM. Basal cell carcinoma, squamous cell carcinoma, and cutaneous melanoma in skin of color patients. Dermatol Clin 2019; 37: 519–26. doi: 10.1016/j.det.2019.05.009
59. Pangti R, Mathur J, Chouhan V, Kumar S, Rajput L, Shah S, et al. A machine learning-based, decision support, mobile phone application for diagnosis of common dermatological diseases. J Eur Acad Dermatol Venereol 2021; 35(2): 536–45. doi: 10.1111/jdv.16967
60. Daneshjou R, Vodrahalli K, Novoa RA, Jenkins M, Liang W, Rotemberg V, et al. Disparities in dermatology AI performance on a diverse, curated clinical image set. Sci Adv 2022 Aug 12; 8(32). doi: 10.1126/sciadv.abq6147
61. Groh M, Harris C, Soenksen L, Lau F, Han R, Kim A, et al. Evaluating deep neural networks trained on clinical images in dermatology with the fitzpatrick 17k dataset. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2021; 1820–8.
62. Tschandl P, Rosendahl C, Kittler H. Data descriptor: the HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions. Sci Data 2018; 5. doi: 10.1038/sdata.2018.161
63. Ouellette S, Rao BK. Usefulness of smartphones in dermatology: a US-based review. Int J Environ Res Public Health 2022; 19. doi: 10.3390/ijerph19063553
64. Walocko FM, Tejasvi T. Teledermatology applications in skin cancer diagnosis. Dermatol Clin 2017; 35: 559–63. doi: 10.1016/j.det.2017.06.002
65. Zink A, Kolbinger A, Leibl M, Léon Suarez I, Gloning J, Merkel C, et al. Teledermoscopy by mobile phones: reliable help in the diagnosis of skin lesions? Hautarzt 2017; 68(11): 890–5. doi: 10.1007/s00105-017-4042-0

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