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.

Dermatoscopic patterns of cutaneous metastases: A multicentre cross-sectional study of the International Dermoscopy Society.

BACKGROUND: The detection of cutaneous metastases (CMs) from various primary tumours represents a diagnostic challenge. OBJECTIVES: Our aim was to evaluate the general characteristics and dermatoscopic features of CMs from different primary tumours. METHODS: Retrospective, multicentre, descriptive, cross-sectional study of biopsy-proven CMs. RESULTS: We included 583 patients (247 females, median age: 64 years, 25%-75% percentiles: 54-74 years) with 632 CMs, of which 52.2% (n = 330) were local, and 26.7% (n = 169) were distant. The most common primary tumours were melanomas (n = 474) and breast cancer (n = 59). Most non-melanoma CMs were non-pigmented (n = 151, 95.6%). Of 169 distant metastases, 54 (32.0%) appeared on the head and neck region. On dermatoscopy, pigmented melanoma metastases were frequently structureless blue (63.6%, n = 201), while amelanotic metastases were typified by linear serpentine vessels and a white structureless pattern. No significant difference was found between amelanotic melanoma metastases and CMs of other primary tumours. CONCLUSIONS: The head and neck area is a common site for distant CMs. Our study confirms that most pigmented melanoma metastasis are structureless blue on dermatoscopy and may mimic blue nevi. Amelanotic metastases are typified by linear serpentine vessels and a white structureless pattern, regardless of the primary tumour.

[Immunohistochemical analysis of a hypoxia-associated signature in melanomas with positive and negative sentinel lymph nodes : Hypoxia-associated signature of primary cutaneous melanomas]. / Immunhistochemische Analyse einer Hypoxie-assoziierten Signatur in Melanomen mit positivem und negativem Schildwächterlymphknoten : Hypoxie-assoziierte Signatur primär kutaner Melanome.

Metabolic reprogramming mediated by hypoxia-inducible factors and its downstream targets plays a crucial role in many human malignancies. Excessive proliferation of tumor cells under hypoxic conditions leads to metabolic reprogramming and altered gene expression enabling tumors to adapt to their hypoxic environment. Here we analyzed the metabolic signatures of primary cutaneous melanomas with positive and negative sentinel node status in order to evaluate potential differences in their metabolic signature. We found a positive correlation of the expression of glucose transporter 1 (GLUT-1) with tumor thickness and ulceration in all melanomas with subgroup analyses as well as in the subgroup with a negative sentinel node. Furthermore, the expression of vascular endothelial growth factor (VEGF) was positively correlated with the presence of ulceration in melanomas with positive sentinel node.

[Successful treatment of chronic prurigo with dupilumab]. / Erfolgreiche Behandlung einer chronischen Prurigo mit Dupilumab.

Chronic prurigo is characterized by persistent itching und partly accompanied by secondary skin excoriation. Diagnostic evaluation is of special relevance and atopic diathesis is a frequent pathogenic factor. We present a patient with prurigo of multifactorial etiology (atopic diathesis, impaired kidney function, diabetes and polyneuropathy). After several unsuccessful prior treatment approaches, the patient was treated with dupilumab, which resulted in a tremendous improvement of itching, skin lesions, and quality of life.

Collective human intelligence outperforms artificial intelligence in a skin lesion classification task.

BACKGROUND AND OBJECTIVES: Convolutional neural networks (CNN) enable accurate diagnosis of medical images and perform on or above the level of individual physicians. Recently, collective human intelligence (CoHI) was shown to exceed the diagnostic accuracy of individuals. Thus, diagnostic performance of CoHI (120 dermatologists) versus individual dermatologists versus two state-of-the-art CNN was investigated. PATIENTS AND METHODS: Cross-sectional reader study with presentation of 30 clinical cases to 120 dermatologists. Six diagnoses were offered and votes collected via remote voting devices (quizzbox®, Quizzbox Solutions GmbH, Stuttgart, Germany). Dermatoscopic images were classified by a binary and multiclass CNN (FotoFinder Systems GmbH, Bad Birnbach, Germany). Three sets of diagnostic classifications were scored against ground truth: (1) CoHI, (2) individual dermatologists, and (3) CNN. RESULTS: CoHI attained a significantly higher accuracy [95 % confidence interval] (80.0 % [62.7 %-90.5 %]) than individual dermatologists (75.7 % [73.8 %-77.5 %]) and CNN (70.0 % [52.1 %-83.3 %]; all P < 0.001) in binary classifications. Moreover, CoHI achieved a higher sensitivity (82.4 % [59.0 %-93.8 %]) and specificity (76.9 % [49.7 %-91.8 %]) than individual dermatologists (sensitivity 77.8 % [75.3 %-80.2 %], specificity 73.0 % [70.6 %-75.4 %]) and CNN (sensitivity 70.6 % [46.9 %-86.7 %], specificity 69.2 % [42.4 %-87.3 %]). The diagnostic accuracy of CoHI was superior to that of individual dermatologists (P < 0.001) in multiclass evaluation, with the accuracy of the latter comparable to multiclass CNN. CONCLUSIONS: Our analysis revealed that the majority vote of an interconnected group of dermatologists (CoHI) outperformed individuals and CNN in a demanding skin lesion classification task.

Auswirkungen des "dunklen Rand-Artefakts" in dermatoskopischen Bildern auf die diagnostische Leistungsfähigkeit eines deep learning neuronalen Netzwerkes mit Marktzulassung.

HINTERGRUND UND ZIELE: Systeme künstlicher Intelligenz (durch "deep learning" faltende neuronale Netzwerke; engl. convolutional neural networks, CNN) erreichen inzwischen bei der Klassifikation von Hautläsionen vergleichbar gute Ergebnisse wie Dermatologen. Allerdings müssen die Limitationen solcher Systeme vor flächendeckendem klinischem Einsatz bekannt sein. Daher haben wir den Einfluss des "dunklen Rand-Artefakts" (engl. dark corner artefact; DCA) in dermatoskopischen Bildern auf die diagnostische Leistung eines CNN mit Marktzulassung zur Klassifikation von Hautläsionen untersucht. PATIENTEN UND METHODEN: Ein Datensatz aus 233 Bildern von Hautläsionen (60 maligne und 173 benigne) ohne DCA (Kontrolle) wurde digital so modifiziert, dass kleine, mittlere oder große DCA zu sehen waren. Alle 932 Bilder wurden dann mittels CNN mit Marktzulassung (Moleanalyzer-Pro® , FotoFinder Systems) auf Malignitätsscores hin analysiert. Das Spektrum reichte von 0-1; ein Score von > 0,5 wurde als maligne klassifiziert. ERGEBNISSE: In der Kontrollserie ohne DCA erreichte das CNN eine Sensitivität von 90,0 % (79,9 %-95,3 %), eine Spezifität von 96,5 % (92,6 %-98,4 %) sowie eine Fläche unter der Kurve (AUC, area under the curve) der "receiver operating characteristic" (ROC) von 0,961 (0,932-0,989). In den Datensätzen mit kleinen beziehungsweise mittleren DCA war die diagnostische Leistung vergleichbar. In den Bildersätzen mit großen DCA wurden allerdings signifikant höhere Malignitätsscores erzielt. Dies führte zu einer signifikant verminderten Spezifität (87,9 % [82,2 %-91,9 %], P < 0,001) sowie einer nicht signifikant erhöhten Sensitivität (96,7 % [88,6 %-99,1 %]). Die ROC-AUC blieb mit 0,962 (0,935-0,989) unverändert. SCHLUSSFOLGERUNGEN: Die Klassifizierung mittels des CNN war bei dermatoskopischen Bildern mit kleinen oder mittleren DCA nicht beeinträchtigt, das System zeigte jedoch Schwächen bei großen DCA. Wenn Ärzte solche Bilder zur Klassifikation mittels CNN einreichen, sollten sie sich dieser Grenzen der Technologie bewusst sein.

Dark corner artefact and diagnostic performance of a market-approved neural network for skin cancer classification.

BACKGROUND AND OBJECTIVES: Convolutional neural networks (CNN) have proven dermatologist-level performance in skin lesion classification. Prior to a broader clinical application, an assessment of limitations is crucial. Therefore, the influence of a dark tubular periphery in dermatoscopic images (also called dark corner artefact [DCA]) on the diagnostic performance of a market-approved CNN for skin lesion classification was investigated. PATIENTS AND METHODS: A prospective image set of 233 skin lesions (60 malignant, 173 benign) without DCA (control-set) was modified to show small, medium or large DCA. All 932 images were analyzed by a market-approved CNN (Moleanalyzer-Pro® , FotoFinder Systems), providing malignancy scores (range 0-1) with the cut-off > 0.5 indicating malignancy. RESULTS: In the control-set the CNN achieved a sensitivity of 90.0 % (79.9 % - 95.3 %), a specificity of 96.5 % (92.6 % - 98.4 %), and an area under the curve (AUC) of receiver operating characteristics (ROC) of 0.961 (0.932 - 0.989). Comparable diagnostic performance was observed in the DCAsmall-set and DCAmedium-set. Conversely, in the DCAlarge-set significantly increased malignancy scores triggered a significantly decreased specificity (87.9 % [82.2 % - 91.9 %], P < 0.001), non-significantly increased sensitivity (96.7 % [88.6 % - 99.1 %]) and unchanged ROC-AUC of 0.962 (0.935 - 0.989). CONCLUSIONS: Convolutional neural network classification was robust in images with small and medium DCA, but impaired in images with large DCA. Physicians should be aware of this limitation when submitting images to CNN classification.

Vascular Endothelial Growth Factor Receptor-3 Expression Predicts Sentinel Node Status in Primary Cutaneous Melanoma.

This study analysed the expression of vascular endothelial growth factor-A (VEGF), VEGFR-2, and VEGFR-3 in primary cutaneous melanomas with positive and negative sentinel node status (SLN) (a total of 58 specimens divided into 2 groups of 29 for each status). The specimens were collected from the pathological archive of the department of Dermatology, Venereology and Allergology of the University Medical Center Heidelberg. A quantification score was developed for protein expression, by considering the percentage of positive melanoma cells (0: 0%, 1: up to 1%, 2: 2-10%, 3: 11-50%, and 4: > 50%) in relation to the intensity of staining (0: negative, 1: low, 2: medium, 3: strong). Tumoural VEGFR-3 expression (mean ± standard deviation) in SLN+ tumours (9.62 ± 3.09) was significantly stronger than in SLN- tumours (6.13 ± 3.87; p < 0.001). A binary logistic regression model proved VEGFR-3 expression and tumour thickness to be significant independent predictors of SLN. These data provide evidence that VEGFR-3 expression may play a critical role in the pathogenesis of malignant melanoma and that its investigation may help to improve the selection of patients with primary cutaneous melanoma for sentinel node biopsy.

[Effectiveness of intralesional steroid injections in granulomatous inflammation after tattooing]. / Therapieansprechen auf intraläsionale Steroidinjektionen bei granulomatöser Entzündungsreaktion nach Tätowierungen.

Tattoos, including permanent makeup, may entail diverse complications like viral or bacterial infections and allergic and inflammatory reactions. In the latter case, besides exogenous pigment, histology shows an either lymphocytic or histiocytic-granulomatous infiltrate, depending on the predominant reaction pattern. We report successful treatment with intralesional triamcinolone acetonide injections in two individuals who developed granulomatous inflammation after tattooing.

[Inflammoscopy: dermatoscopy for inflammatory, infiltrating and infectious dermatoses : Indication and standardization of dermatoscopic terminology]. / Inflammoskopie: Dermatoskopie bei entzündlichen, infiltrierenden und infektiösen Dermatosen : Indikation und standardisierte dermatoskopische Terminologie.

Dermatoscopy as a noninvasive diagnostic tool is not only useful in the differentiation of malignant and benign skin tumors, but is also effective in the diagnosis of inflammatory, infiltrative and infectious dermatoses. As a result, the need for diagnostic punch biopsies in dermatoses could be reduced. Hereby the selection of affected skin areas is essential. The diagnostic accuracy is independent of the skin type. Helpful dermatoscopic features include vessels morphology and distribution, scales colors and distribution, follicular findings, further structures such as colors and morphology as well as specific clues. The dermatoscopic diagnosis is made based on the descriptive approach in clinical routine, teaching and research. In all clinical and dermatoscopic diagnoses that remain unclear, a punch biopsy with histopathology should be performed. The dermatoscope should be cleaned after every examination according to the guidelines.

Differentiation of combined nevi and melanomas: Case-control study with comparative analysis of dermoscopic features.

BACKGROUND AND OBJECTIVES: Combined nevi (CN) show two or more components of major nevus subtypes and simulate melanomas. We investigated a panel of dermoscopic features and three dermoscopic algorithms for differentiating CN from melanomas. PATIENTS AND METHODS: Retrospective, blinded case-control study using dermoscopic images of 36 CN and 36 melanoma controls. Twenty-one dermoscopic features validated for the diagnosis of melanocytic lesions, the number of colors, and three dermoscopic algorithms were investigated (ABCD rule of dermoscopy, Menzies scoring method, 7-point checklist). RESULTS: Five of seven features indicative of nevi were observed significantly more frequently in CN than in melanomas (all p < 0.05) and two were exclusively found in CN. Eleven out of 14 features indicative of melanomas were observed significantly more frequently in melanomas than in CN (all p < 0.03) and five were exclusively found in melanomas. The mean (± SD) number of colors in CN was lower than in melanomas (2.1 ± 0.6 versus 3.4 ± 0.7; p < 0.001). Among tested algorithms the ABCD rule of dermoscopy performed best (sensitivity 91.7 %, specificity 77.8 %). CONCLUSIONS: The ABCD rule of dermoscopy differentiated CN from melanomas most efficiently. Additional knowledge of dermoscopic features to be expected exclusively in either CN or melanomas should help dermatologists to make a correct clinical diagnosis.

Physicians' level of hindrance by body hair in dermatoscopy and clinical benefit of an automated hair removal algorithm.

BACKGROUND AND OBJECTIVES: Dermatoscopy may be hindered by body hair, and the development of an automated hair removal algorithm (AuHRA) might improve the diagnostic accuracy. However, the physicians' exact level of hindrance and the clinical benefit attained by AuHRA has not been assessed. The objectives of this study are to quantify the physicians' level of hindrance by body hair and the level of improvement in the visibility of underlying dermatoscopic patterns after application of AuHRA to digital images of hair-covered nevi. PATIENTS AND METHODS: A cross-sectional reader study including 59 sets of dermatoscopic images of benign nevi that were presented to six dermatologists. Each set included three images of one individual nevus (unshaved/physically shaved/digitally shaved with AuHRA), which were compared to each other within each set to assess the level of improvement caused by hair removal. RESULTS: In comparison to unshaved lesions, dermatologists attributed the highest mean level of improvement to a physical shave (+1.36, p < 0.001) followed by AuHRA's digital shave (+0.79, p < 0.001). The majority of dermatologists considered the application of AuHRA as helpful and confirmed a medical need. CONCLUSIONS: The dermatologists in our study confirmed a substantial impairment of the dermatoscopic examination by body hair. We demonstrated a clinical benefit attained by AuHRA in comparison to unshaved or physically shaved lesions.

Differenzierung von kombinierten Nävi und Melanomen: Fallkontrollstudie mit komparativer Analyse der dermatoskopischen Merkmale.

HINTERGRUND: Kombinierte Nävi (KN) zeigen zwei oder mehr Komponenten bestimmter Nävustypen und stellen klassische Melanomsimulatoren dar. In dieser Studie wurde eine vorab definierte Auswahl dermatoskopischer Merkmale sowie drei diagnostische Algorithmen hinsichtlich der Differenzierung von KN und Melanomen evaluiert. PATIENTEN UND METHODIK: Retrospektive, verblindete Fallkontrollstudie mit Vergleich dermatoskopischer Bilder von 36 KN sowie 36 Melanomen. Insgesamt wurden 21 dermatoskopische Merkmale, die Anzahl der Farben sowie drei diagnostische Algorithmen (ABCD-Regel, Menzies-Score, 7-Punkte-Checkliste) untersucht. ERGEBNISSE: 5 von 7 typischen Nävus-Merkmalen wurden signifikant häufiger in KN im Vergleich zu Melanomen gefunden (alle p < 0,05) und zwei Merkmale wurden ausschließlich in KN gefunden. 11 von 14 typischen Melanom-Merkmalen wurden signifikant häufiger in Melanomen im Vergleich zu KN gefunden (alle p < 0,03) und fünf Merkmale wurden ausschließlich in Melanomen gefunden. Die mittlere (± SD) Anzahl der Farben in KN war niedriger im Vergleich zu den Melanomen (2,1 ± 0,6 vs. 3,4 ± 0,7; p < 0,001). Bei den untersuchten Algorithmen zeigte die ABCD-Regel der Dermatoskopie die beste diagnostische Leistung (Sensitivität 91,7 %, Spezifität 77,8 %). SCHLUSSFOLGERUNGEN: Die ABCD-Regel der Dermatoskopie erzielte die beste Differenzierung von KN und Melanomen. Zusätzliches Wissen über KN- oder Melanom-spezifische dermatoskopische Merkmale kann zur sicheren klinischen Diagnose beitragen.

Dermatofluoroscopy diagnostics in different pigmented skin lesions: Strengths and weaknesses.

BACKGROUND: The melanin fluorescence of skin lesions is measurable with two-photon excitation, a process termed dermatofluoroscopy, which has shown a shift from the green spectra in benign melanocytic lesions to the red spectra in melanoma. This study addressed the question as to which kind of pigmented lesions can be correctly diagnosed as melanin-bearing malignant tumors. METHODS: 476 pigmented lesions including 101 cutaneous melanomas were analyzed with dermatofluoroscopy, measuring the melanin fluorescence in a grid-like fashion with a separation of measurement points of 0.2 mm. The results of the dermatofluoroscopy are presented as a diagnostic score with a cut-off score of ≥ 28 for the diagnosis of melanin-bearing malignant tumors, and were compared to the gold standard of histopathology. RESULTS: A highly significant difference (p < 0.0001) between the diagnostic scores of different skin tumors was found. Dermatofluoroscopy scores showed the highest sensitivity for melanomas (92.1 %). Interestingly, most pigmented basal cell carcinomas (BCCs, 88.9 %) were diagnosed as melanin-bearing malignant tumors. A higher sensitivity for the correct diagnosis was observed in older patients (≥ 53 years, p = 0.003), in patients with skin tanning (p = 0.025), and in patients with freckles during childhood (p = 0.046). CONCLUSIONS: Two-photon fluorescence is an innovative technique for the diagnosis of pigmented skin lesions, and shows a high sensitivity for detection of melanomas and pigmented BCCs.

Angiogenesis in Ocular and Extraocular Sebaceous Carcinoma.

To shed more light on the pathogenesis of sebaceous carcinoma, we analysed the expression of proteins related to angiogenesis in 18 ocular and 22 extraocular sebaceous carcinomas using a broad panel of immunohistochemical markers. To quantify the expression of D2-40, vascular endothelial growth factor, vascular endothelial growth factor receptor-2 and -3, we calculated a quantification score by considering the percentage of positive tumour cells (0=0%, 1=up to 1%, 2=2-10%, 3=11-50%, and 4=>50%) in relation to the staining intensity (0=negative, 1=low, 2=medium, and 3=strong). Additionally, lymphatic microvessel density in the D2-40 stained sections was counted. Vascular endothelial growth factor receptor-3 (quantification score 9.42 ± 2.94) was significantly more strongly expressed than vascular endothelial growth factor receptor-2 (quantification score 2.15 ± 2.42, p < 0.001). Furthermore, epidermal vascular endothelial growth factor expression was negatively correlated with the intratumoural lymphatic vessel density, and the ratio of small lymphatics to large lymphatics was much higher in intratumoural tissue than in paratumoural tissue and in intraindividual control tissue, suggesting a lymphangiogenetic potential of sebaceous carcinoma.

An Internet-Based Self-Help Intervention for Skin Picking (SaveMySkin): Pilot Randomized Controlled Trial.

BACKGROUND: In spite of the psychosocial burden and medical risks associated with skin picking disorder, the health care system does not provide sufficient treatment for affected individuals to date. Therefore, an internet-based self-help program for skin picking was developed to offer easily accessible support for this population. OBJECTIVE: This pilot study evaluated the internet-based self-help program SaveMySkin. The 12-week program is based on cognitive-behavioral therapy and contains comprehensive information and exercises, a daily supportive monitoring system, and dermatological and psychological counseling via internet chat. Primary objectives were the investigation of attitudes and expectations toward the program, intervention effects on skin picking severity, user satisfaction, adherence, and willingness to participate. Secondary outcomes included the feasibility of study procedures, adequacy of assessment instruments, effects on skin picking-related impairment, dimensions of skin picking, and general psychological impairment. METHODS: A two-arm randomized controlled trial was conducted in a sample of 133 participants (female: 124/133, 93.2%; mean age 26.67 [SD 6.42]) recruited via the internet. Inclusion required a minimum age of 17 years and at least mild skin picking severity. Participants were randomly allocated to the intervention (64/133, 48.1%) or waitlist control group (69/133, 51.9%). All assessments were conducted online and based on self-report. RESULTS: The willingness to participate was very high in the study, so the initially planned sample size of 100 was exceeded after only 18 days. Participant expectations indicate that they believed the program to be beneficial for them (131/133, 98.5%) and provide a feeling of support (119/133, 89.5%). Reasons for study participation were insufficient outpatient health care (83/133, 62.4%) and flexibility regarding time (106/133, 79.7%) and location (109/133, 82.0%). The post-assessment was completed by 65.4% (87/133) of the sample. The majority of the intervention group who completed the entire post-assessment were satisfied with SaveMySkin (28/38, 74%) and agreed that the program is an appropriate support service (35/38, 92%). On average, participants viewed 29.31 (SD 42.02) pages in the program, and 47% (30/64) of the intervention group used the monitoring at least once a week. In comparison with the control group, the intervention group displayed substantial improvements in the skin picking severity total score (Cohen d=0.67) and especially on the subscale Symptom Severity (Cohen d=0.79). No effects on secondary outcomes were found. CONCLUSIONS: This study confirms the need for easily accessible interventions for skin picking disorder and the high interest in internet-based self-help within the target population. It provides important insights into the attitudes toward online support and actual user experiences. Participant feedback will be used to further enhance the intervention. Our results point to the preliminary efficacy of SaveMySkin and may lay the foundation for future research into the efficacy and cost-effectiveness of the program in a multicenter clinical trial. TRIAL REGISTRATION: German Clinical Trial Register DRKS00015236; https://www.drks.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00015236. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1016/j.conctc.2018.100315.

[Reflectance confocal microscopy in Shiitake dermatitis]. / Konfokale Lasermikroskopie bei Shiitake-Dermatitis.

Shiitake dermatitis usually occurs 1-2 days after consumption of incompletely cooked or raw shiitake mushrooms and is characterized by linear, pruritic, erythematous papulovesicular rashes. It is caused by lentinan, a polysaccharide component of the cell walls of shiitake mushrooms. The histological examination showed an eczema-like morphology with spongiosis and lymphohistiocytic infiltrates. The results of reflectance confocal microscopy (RCM) correlated with the histopathological investigations. Therefore, RCM can be used for non-invasive diagnostic confirmation of Shiitake dermatitis in the future.

Design of an Algorithm for Automated, Computer-Guided PASI Measurements by Digital Image Analysis.

The Psoriasis Area and Severity Index (PASI) is the most accepted method for psoriasis severity scoring. However, a prominent level of subjectivity and a low intra- and inter-rater reproducibility was reported. Therefore, an accurate and reproducible measure of psoriasis severity is needed, especially in the setting of registration studies for systemic anti-psoriatic drugs. Herein we describe a robust, user-friendly, computer-guided technology that allows for automated PASI measurements after total body imaging and digital image analysis. For this purpose, a novel image processing software for PASI calculations was developed, which was combined with a commercially available, automated image capturing system. Our data shows, that the software was able to accurately calculate the proportion of psoriatic skin surface as well as the severity of erythema, induration, and desquamation by anatomic region. In a pilot clinical validation the time-efficient technology showed a high reproducibility and high levels of agreement to results attained by PASI-trained physicians. Therefore, automated computer-guided PASI measurements hold the promise of significantly reducing the physicians' workload while ensuring a high level of reproducibility and standardization.

Patient acceptance and trust in automated computer-assisted diagnosis of melanoma with dermatofluoroscopy.

BACKGROUND AND OBJECTIVES: Automated computer-guided diagnostic procedures are increasingly being integrated into patient care. However, in contrast to the increasing application of automation, patient acceptance and trust in such technologies has rarely been studied. Automated diagnosis of melanoma with dermatofluoroscopy was recently approved by regulatory agencies. The objective of this study is to assess patient acceptance and trust in automated melanoma diagnosis with dermatofluoroscopy. PATIENTS AND METHODS: We examined 140 pigmented skin lesions with dermatofluoroscopy as part of a prospective clinical study. Four weeks after their examination with dermatofluoroscopy, we contacted 100 patients with a 10-item questionnaire addressing their acceptance and trust in this technology on a five-point visual analogue scale. RESULTS: A "high" to "very high" level of patient acceptance and trust in dermatofluoroscopy was found in 74 % of responders. Most patients agreed that computer-assisted diagnoses are trustworthy and may generally improve the diagnostic performance of physicians. However, all responders insisted on the interpretation of computer-assisted diagnoses by a physician and frequently rejected the idea of computers completely replacing physicians. CONCLUSION: Patient acceptance and trust in dermatofluoroscopy was high. Patients clearly supported the use of automated, computer-assisted diagnostics as an adjunct to the physicians' examination.

The status of dermoscopy in Germany - results of the cross-sectional Pan-Euro-Dermoscopy Study.

BACKGROUND: Survey on the current status of dermoscopy in Germany. METHODS: In the context of a pan-European internet-based study (n = 7,480) conducted by the International Dermoscopy Society, 880 German dermatologists were asked to answer questions with respect to their level of training as well as their use and perceived benefit of dermoscopy. RESULTS: Seven hundred and sixty-two (86.6 %) participants practiced dermatology in a publicly funded health care setting; 98.4 % used a dermoscope in routine clinical practice. About 93 % (n = 814) stated to have had more than five years of experience in the use of dermoscopy. Dermoscopy was considered useful in the diagnosis of melanoma by 93.6 % (n = 824); for pigmented skin tumors, by 92.4 % (n = 813); in the follow-up of melanocytic lesions, by 88.6 % (n = 780); for non-pigmented lesions, by 71.4 % (n = 628), in the follow-up of non-melanocytic lesions, by 52.7 % (n = 464); and for inflammatory skin lesions, by 28.5 % (n = 251). Overall, 86.5 % (n = 761) of participants felt that - compared to naked-eye examination - dermoscopy increased the number of melanomas diagnosed; 77,7 % (n = 684) considered the number of unnecessary excisions of benign lesions to be decreased. Participants who personally felt that dermoscopy improved their ability to diagnose melanoma were significantly i) younger, ii) had been practicing dermatology for a shorter period of time, iii) were less commonly employed by an university-affiliated dermatology department, iv) were more frequently working in an office-based public health care setting, and v) had more frequently been trained in dermoscopy during their dermatology residency. CONCLUSIONS: The findings presented herein ought to be integrated into future residency and continuing medical education programs with the challenge to improve dermato-oncological care and to expand the diagnostic spectrum of dermoscopy to include inflammatory skin diseases.