| 1. |
- Forsea, Ana-Maria, et al.
(författare)
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Inequalities in the patterns of dermoscopy use and training across Europe : conclusions of the Eurodermoscopy pan-European survey
- 2020
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Ingår i: European journal of dermatology : EJD. - : John Libbey Eurotext. - 1167-1122 .- 1952-4013. ; 30:5, s. 524-531
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Dermoscopy is a widely used technique, recommended in clinical practice guidelines worldwide for the early diagnosis of skin cancers. Intra-European disparities are reported for early detection and prognosis of skin cancers, however, no information exists about regional variation in patterns of dermoscopy use across Europe.OBJECTIVE: To evaluate the regional differences in patterns of dermoscopy use and training among European dermatologists.MATERIALS & METHODS: An online survey of European-registered dermatologists regarding dermoscopy training, practice and attitudes was established. Answers from Eastern (EE) versus Western European (WE) countries were compared and their correlation with their respective countries' gross domestic product/capita (GDPc) and total and government health expenditure/capita (THEc and GHEc) was analysed.RESULTS: We received 4,049 responses from 14 WE countries and 3,431 from 18 EE countries. A higher proportion of WE respondents reported dermoscopy use (98% vs. 77%, p<0.001) and training during residency (43% vs. 32%) or anytime (96.5% vs. 87.6%) (p<0.001) compared to EE respondents. The main obstacles in dermoscopy use were poor access to dermoscopy equipment in EE and a lack of confidence in one's skills in WE. GDPc, THEc and GHEc correlated with rate of dermoscopy use and dermoscopy training during residency (Spearman rho: 0.5-0.7, p<0.05), and inversely with availability of dermoscopy equipment.CONCLUSION: The rates and patterns of dermoscopy use vary significantly between Western and Eastern Europe, on a background of economic inequality. Regionally adapted interventions to increase access to dermoscopy equipment and training might enhance the use of this technique towards improving the early detection of skin cancers.
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| 2. |
- Haenssle, H A, et al.
(författare)
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Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.
- 2018
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Ingår i: Annals of Oncology. - : Elsevier BV. - 1569-8041 .- 0923-7534. ; 29:8, s. 1836-1842
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Tidskriftsartikel (refereegranskat)abstract
- Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN's diagnostic performance to larger groups of dermatologists are lacking.Google's Inception v4 CNN architecture was trained and validated using dermoscopic images and corresponding diagnoses. In a comparative cross-sectional reader study a 100-image test-set was used (level-I: dermoscopy only; level-II: dermoscopy plus clinical information and images). Main outcome measures were sensitivity, specificity and area under the curve (AUC) of receiver operating characteristics (ROC) for diagnostic classification (dichotomous) of lesions by the CNN versus an international group of 58 dermatologists during level-I or -II of the reader study. Secondary end points included the dermatologists' diagnostic performance in their management decisions and differences in the diagnostic performance of dermatologists during level-I and -II of the reader study. Additionally, the CNN's performance was compared with the top-five algorithms of the 2016 International Symposium on Biomedical Imaging (ISBI) challenge.In level-I dermatologists achieved a mean (±standard deviation) sensitivity and specificity for lesion classification of 86.6% (±9.3%) and 71.3% (±11.2%), respectively. More clinical information (level-II) improved the sensitivity to 88.9% (±9.6%, P=0.19) and specificity to 75.7% (±11.7%, P<0.05). The CNN ROC curve revealed a higher specificity of 82.5% when compared with dermatologists in level-I (71.3%, P<0.01) and level-II (75.7%, P<0.01) at their sensitivities of 86.6% and 88.9%, respectively. The CNN ROC AUC was greater than the mean ROC area of dermatologists (0.86 versus 0.79, P<0.01). The CNN scored results close to the top three algorithms of the ISBI 2016 challenge.For the first time we compared a CNN's diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists were outperformed by the CNN. Irrespective of any physicians' experience, they may benefit from assistance by a CNN's image classification.This study was registered at the German Clinical Trial Register (DRKS-Study-ID: DRKS00013570; https://www.drks.de/drks_web/).
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| 3. |
- Liopyris, Konstantinos, et al.
(författare)
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Expert agreement on the presence and spatial localization of melanocytic features in dermoscopy.
- 2023
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Ingår i: The Journal of investigative dermatology. - 1523-1747. ; 144:3
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Tidskriftsartikel (refereegranskat)abstract
- Dermoscopy aids in melanoma detection; however, agreement on dermoscopic features, including those of high clinical relevance, remains poor. Herein we attempted to evaluate agreement among experts on 'exemplar images' not only for the presence of melanocytic-specific features but also for spatial localization. This was a cross-sectional, multicenter, observational study. Dermoscopy images exhibiting at least one of 31 melanocytic-specific features were submitted by 25 world experts as 'exemplars'. Using a web-based platform that allows for image mark-up of specific contrast-defined regions (superpixels), 20 expert readers annotated 248 dermoscopic images in collections of 62 images. Each collection was reviewed by five independent readers. A total of 4,507 feature observations were performed. Good-to-excellent agreement was found for 14 of 31 features (45.2%), with 8 achieving excellent agreement (Gwet's AC >0.75) and 7 of them being melanoma-specific features. These features were: 'Peppering /Granularity' (0.91); 'Shiny White Streaks' (0.89); 'Typical Pigment network' (0.83); 'Blotch Irregular' (0.82); 'Negative Network' (0.81); 'Irregular Globules' (0.78); 'Dotted Vessels' (0.77) and 'Blue Whitish Veil' (0.76). By utilizing an exemplar dataset, good-to-excellent agreement was found for 14 features that have previously been shown useful in discriminating nevi from melanoma. All images are public (www.isic-archive.com) and can be used for education, scientific communication and machine learning experiments.
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| 4. |
- Menzies, Scott W, et al.
(författare)
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Dermoscopic evaluation of amelanotic and hypomelanotic melanoma.
- 2008
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Ingår i: Archives of dermatology. - : American Medical Association (AMA). - 1538-3652 .- 0003-987X. ; 144:9, s. 1120-7
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Tidskriftsartikel (refereegranskat)abstract
- To determine the predictive dermoscopic features of amelanotic and hypomelanotic melanoma.
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| 5. |
- Menzies, Scott W, et al.
(författare)
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Dermoscopic Evaluation of Nodular Melanoma.
- 2013
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Ingår i: JAMA dermatology (Chicago, Ill.). - : American Medical Association (AMA). - 2168-6084 .- 2168-6068. ; 149:6, s. 699-709
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Tidskriftsartikel (refereegranskat)abstract
- IMPORTANCE Nodular melanoma (NM) is a rapidly progressing potentially lethal skin tumor for which early diagnosis is critical. OBJECTIVE To determine the dermoscopy features of NM. DESIGN Eighty-three cases of NM, 134 of invasive non-NM, 115 of nodular benign melanocytic tumors, and 135 of nodular nonmelanocytic tumors were scored for dermoscopy features using modified and previously described methods. Lesions were separated into amelanotic/hypomelanotic or pigmented to assess outcomes. SETTING Predominantly hospital-based clinics from 5 continents. MAIN OUTCOME MEASURES Sensitivity, specificity, and odds ratios for features/models for the diagnosis of melanoma. RESULTS Nodular melanoma occurred more frequently as amelanotic/hypomelanotic (37.3%) than did invasive non-NM (7.5%). Pigmented NM had a more frequent (compared with invasive non-NM; in descending order of odds ratio) symmetrical pigmentation pattern (5.8% vs 0.8%), large-diameter vessels, areas of homogeneous blue pigmentation, symmetrical shape, predominant peripheral vessels, blue-white veil, pink color, black color, and milky red/pink areas. Pigmented NM less frequently displayed an atypical broadened network, pigment network or pseudonetwork, multiple blue-gray dots, scarlike depigmentation, irregularly distributed and sized brown dots and globules, tan color, irregularly shaped depigmentation, and irregularly distributed and sized dots and globules of any color. The most important positive correlating features of pigmented NM vs nodular nonmelanoma were peripheral black dots/globules, multiple brown dots, irregular black dots/globules, blue-white veil, homogeneous blue pigmentation, 5 to 6 colors, and black color. A model to classify a lesion as melanocytic gave a high sensitivity (>98.0%) for both nodular pigmented and nonnodular pigmented melanoma but a lower sensitivity for amelanotic/hypomelanotic NM (84%). A method for diagnosing amelanotic/hypomelanotic malignant lesions (including basal cell carcinoma) gave a 93% sensitivity and 70% specificity for NM. CONCLUSIONS AND RELEVANCE When a progressively growing, symmetrically patterned melanocytic nodule is identified, NM needs to be excluded.
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| 6. |
- Russo, Teresa, et al.
(författare)
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Indications for Digital Monitoring of Patients With Multiple Nevi: Recommendations from the International Dermoscopy Society
- 2022
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Ingår i: Dermatology Practical and Conceptual. - : Mattioli1885. - 2160-9381. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: In patients with multiple nevi, sequential imaging using total body skin photography (TBSP) coupled with digital dermoscopy (DD) documentation reduces unnecessary excisions and improves the early detection of melanoma. Correct patient selection is essential for optimizing the efficacy of this diagnostic approach. Objectives: The purpose of the study was to identify, via expert consensus, the best indications for TBSP and DD follow-up. Methods: This study was performed on behalf of the International Dermoscopy Society (IDS). We attained consensus by using an e-Delphi methodology. The panel of participants included international experts in dermoscopy. In each Delphi round, experts were asked to select from a list of indications for TBSP and DD. Results: Expert consensus was attained after 3 rounds of Delphi. Participants considered a total nevus count of 60 or more nevi or the presence of a CDKN2A mutation sufficient to refer the patient for digital monitoring. Patients with more than 40 nevi were only considered an indication in case of personal history of melanoma or red hair and/or a MC1R mutation or history of organ transplantation. Conclusions: Our recommendations support clinicians in choosing appropriate follow-up regimens for patients with multiple nevi and in applying the time-consuming procedure of sequential imaging more efficiently. Further studies and real-life data are needed to confirm the usefulness of this list of indications in clinical practice.
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| 7. |
- Sinz, Christoph, et al.
(författare)
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Accuracy of dermatoscopy for the diagnosis of nonpigmented cancers of the skin.
- 2017
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Ingår i: Journal of the American Academy of Dermatology. - : Elsevier BV. - 1097-6787 .- 0190-9622. ; 77:6, s. 1100-1109
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Tidskriftsartikel (refereegranskat)abstract
- Nonpigmented skin cancer is common, and diagnosis with the unaided eye is error prone.To investigate whether dermatoscopy improves the diagnostic accuracy for nonpigmented (amelanotic) cutaneous neoplasms.We collected a sample of 2072 benign and malignant neoplastic lesions and inflammatory conditions and presented close-up images taken with and without dermatoscopy to 95 examiners with different levels of experience.The area under the curve was significantly higher with than without dermatoscopy (0.68 vs 0.64, P<.001). Among 51 possible diagnoses, the correct diagnosis was selected in 33.1% of cases with and 26.4% of cases without dermatoscopy (P<.001). For experts, the frequencies of correct specific diagnoses of a malignant lesion improved from 40.2% without to 51.3% with dermatoscopy. For all malignant neoplasms combined, the frequencies of appropriate management strategies increased from 78.1% without to 82.5% with dermatoscopy.The study deviated from a real-life clinical setting and was potentially affected by verification and selection bias.Dermatoscopy improves the diagnosis and management of nonpigmented skin cancer and should be used as an adjunct to examination with the unaided eye.
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| 8. |
- Tiodorovic, Danica, et al.
(författare)
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Dermatoscopic patterns of cutaneous metastases: A multicentre cross-sectional study of the International Dermoscopy Society
- 2024
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Ingår i: JOURNAL OF THE EUROPEAN ACADEMY OF DERMATOLOGY AND VENEREOLOGY. - 0926-9959 .- 1468-3083.
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundThe detection of cutaneous metastases (CMs) from various primary tumours represents a diagnostic challenge.ObjectivesOur aim was to evaluate the general characteristics and dermatoscopic features of CMs from different primary tumours.MethodsRetrospective, multicentre, descriptive, cross-sectional study of biopsy-proven CMs.ResultsWe 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.ConclusionsThe 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.
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| 9. |
- Tognetti, Linda, et al.
(författare)
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Dermoscopy of atypical pigmented lesions of the face: Variation according to facial areas.
- 2023
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Ingår i: Experimental dermatology. - 0906-6705 .- 1600-0625. ; 32:12, s. 2166-2172
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Tidskriftsartikel (refereegranskat)abstract
- Atypical pigmented facial lesions (aPFLs)-including lentigo maligna (LM) and lentigo maligna melanoma (LMM), solar lentigo (SL), pigmented actinic keratosis (PAK), atypical nevi (AN), seborrheic keratosis (SK) and lichen planus-like keratosis (LPLK)-can exhibit clinical and dermoscopic overlapping features. We aimed to investigate if and how 14 dermoscopic features suggestive for the aforementioned aPFLs vary according to six facial sites among 1197 aPFLs cases (excised to rule out malignancy) along with lesion and patients' metadata. According to distribution and association analysis, aPFLs on the forehead of a male patient aged>69years displaying the obliterated follicular openings pattern, appear to be more at risk of malignancy. Of converse, aPFLs of the orbital/cheek/nose area with evident and regular follicular openings with diameter<10mm in a female aged below 68 are probably benign. The obliterated follicular openings, keratin plugs, evident and regular follicular openings and target-like pattern features differed significantly among six facial areas in all aPFLs cases. Lesion of the nose may show both features suggestive of malignancy and benignity (e.g. many SL and PAK may display target-like pattern and some LM/LMM cases display keratin plugs and evident and follicular openings), making these features less specific.
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| 10. |
- Tognetti, Linda, et al.
(författare)
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Development and Implementation of a Web-Based International Registry Dedicated to Atypical Pigmented Skin Lesions of the Face: Teledermatologic Investigation on Epidemiology and Risk Factors.
- 2023
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Ingår i: Telemedicine journal and e-health : the official journal of the American Telemedicine Association. - : Mary Ann Liebert Inc. - 1556-3669. ; 29:9, s. 1356-1365
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Tidskriftsartikel (refereegranskat)abstract
- Background: Atypical pigmented facial lesions (aPFLs) often display clinical and dermoscopic equivocal and/or overlapping features, thus causing a challenging and delayed diagnosis and/or inappropriate excisions. No specific registry dedicated to aPFL paired with clinical data is available to date. Methods: The dataset is hosted on a specifically designed web platform. Each complete case was composed of the following data: (1) one dermoscopic picture; (2) one clinical picture; (3) two lesion data, that is, maximum diameter and facial location (e.g., orbital area/forehead/nose/cheek/chin/mouth); (4) patient's demographics: family history of melanoma, history of sunburns in childhood, phototype, pheomelanine, eyes/hair color, multiple nevi/dysplastic nevi on the body; and (5) acquisition device (videodermatoscope/camera-based/smartphone-based system). Results: A total of 11 dermatologic centers contributed to a final teledermoscopy database of 1,197 aPFL with a distribution of 353 lentigo maligna (LM), 146 lentigo maligna melanoma (LMM), 231 pigmented actinic keratoses, 266 solar lentigo, 125 atypical nevi, 48 seborrheic keratosis, and 28 seborrheic-lichenoid keratoses. The cheek site was involved in half of aPFL cases (50%). Compared with those with the other aPFL cases, patients with LM/LMM were predominantly men, older (69.32±12.9 years on average vs. 62.69±14.51), exhibited larger lesions (11.88±7.74mm average maximum diameter vs. 9.33±6.46mm), and reported a positive history of sunburn in childhood. Conclusions: The iDScore facial dataset currently represents a precious source of data suitable for the design of diagnostic support tools based on risk scoring classifiers to help dermatologists in recognizing LM/LMM among challenging aPFL in clinical practice.
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| 11. |
- Tschandl, Philipp, et al.
(författare)
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Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks.
- 2019
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Ingår i: JAMA dermatology. - : American Medical Association (AMA). - 2168-6084 .- 2168-6068. ; 55:1, s. 58-65
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Tidskriftsartikel (refereegranskat)abstract
- Convolutional neural networks (CNNs) achieve expert-level accuracy in the diagnosis of pigmented melanocytic lesions. However, the most common types of skin cancer are nonpigmented and nonmelanocytic, and are more difficult to diagnose.To compare the accuracy of a CNN-based classifier with that of physicians with different levels of experience.A CNN-based classification model was trained on 7895 dermoscopic and 5829 close-up images of lesions excised at a primary skin cancer clinic between January 1, 2008, and July 13, 2017, for a combined evaluation of both imaging methods. The combined CNN (cCNN) was tested on a set of 2072 unknown cases and compared with results from 95 human raters who were medical personnel, including 62 board-certified dermatologists, with different experience in dermoscopy.The proportions of correct specific diagnoses and the accuracy to differentiate between benign and malignant lesions measured as an area under the receiver operating characteristic curve served as main outcome measures.Among 95 human raters (51.6% female; mean age, 43.4 years; 95% CI, 41.0-45.7 years), the participants were divided into 3 groups (according to years of experience with dermoscopy): beginner raters (<3 years), intermediate raters (3-10 years), or expert raters (>10 years). The area under the receiver operating characteristic curve of the trained cCNN was higher than human ratings (0.742; 95% CI, 0.729-0.755 vs 0.695; 95% CI, 0.676-0.713; P<.001). The specificity was fixed at the mean level of human raters (51.3%), and therefore the sensitivity of the cCNN (80.5%; 95% CI, 79.0%-82.1%) was higher than that of human raters (77.6%; 95% CI, 74.7%-80.5%). The cCNN achieved a higher percentage of correct specific diagnoses compared with human raters (37.6%; 95% CI, 36.6%-38.4% vs 33.5%; 95% CI, 31.5%-35.6%; P=.001) but not compared with experts (37.3%; 95% CI, 35.7%-38.8% vs 40.0%; 95% CI, 37.0%-43.0%; P=.18).Neural networks are able to classify dermoscopic and close-up images of nonpigmented lesions as accurately as human experts in an experimental setting.
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