Browsing by Author "Scope, Alon"

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    Deep Learning for Basal Cell Carcinoma Detection for Reflectance Confocal Microscopy
    (2022) Campanella, Gabriele; Navarrete-Dechent, Cristian; Liopyris, Konstantinos; Monnier, Jilliana; Aleissa, Saud; Minhas, Brahmteg; Scope, Alon; Longo, Caterina; Guitera, Pascale; Pellacani, Giovanni; Kose, Kivanc; Halpern, Allan C.; Fuchs, Thomas J.; Jain, Manu
    Basal cell carcinoma (BCC) is the most common skin cancer, with over 2 million cases diagnosed annually in the UnitedStates. Conventionally, BCC is diagnosed by naked eye examination and dermoscopy. Suspicious lesions are either removed or biopsied for histopathological confirmation, thus lowering the specificity of noninvasive BCC diagnosis. Recently, reflectance confocal microscopy, a noninvasive diagnostic technique that can image skin lesions at cellular level resolution, has shown to improve specificity in BCC diagnosis and reduced the number needed to biopsy by 2-3 times. In this study, we developed and evaluated a deep learning-based artificial intelligence model to automatically detect BCC in reflectance confocal microscopy images. The proposed model achieved an area under the curve for the receiver operator characteristic curve of 89.7%(stack level) and 88.3%(lesion level), a performance on par with that of reflectance confocal microscopy experts. Furthermore, themodel achieved an area under the curve of 86.1% on a held-out test set from international collaborators, demonstrating the reproducibility and generalizability of the proposed automated diagnostic approach. These results provide a clear indication that the clinical deployment of decision support systems for the detection of BCC in reflectance confocal microscopy images has the potential for optimizing the evaluation and diagnosis of patients with skin cancer.
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    Expert Agreement on the Presence and Spatial Localization of Melanocytic Features in Dermoscopy
    (2024) Liopyris, Konstantinos; Navarrete-Dechent, Cristian; Marchetti, Michael A.; Rotemberg, Veronica; Apalla, Zoe; Argenziano, Giuseppe; Blum, Andreas; Braun, Ralph P.; Carrera, Cristina; Codella, Noel C. F.; Combalia, Marc; Dusza, Stephen W.; Gutman, David A.; Helba, Brian; Hofmann-Wellenhof, Rainer; Jaimes, Natalia; Kittler, Harald; Kose, Kivanc; Lallas, Aimilios; Longo, Caterina; Malvehy, Josep; Menzies, Scott; Nelson, Kelly C.; Paoli, John; Puig, Susana; Rabinovitz, Harold S.; Rishpon, Ayelet; Russo, Teresa; Scope, Alon; Soyer, H. Peter; Stein, Jennifer A.; Stolz, Willhelm; Sgouros, Dimitrios; Stratigos, Alexander J.; Swanson, David L.; Thomas, Luc; Tschandl, Philipp; Zalaudek, Iris; Weber, Jochen; Halpern, Allan C.; Marghoob, Ashfaq A.
    Dermoscopy aids in melanoma detection; however, agreement on dermoscopic features, including those of high clinical relevance, remains poor. In this study, 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 1 of 31 melanocytic-specific features were submitted by 25 world experts as exemplars. Using a web-based platform that allows for image markup 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 eight achieving excellent agreement (Gwet's AC >0.75) and seven of them being melanomaspecific 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, a 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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    International Skin Imaging Collaboration-Designated Diagnoses (ISIC-DX): Consensus terminology for lesion diagnostic labeling
    (2024) Scope, Alon; Liopyris, Konstantinos; Weber, Jochen; Barnhill, Raymond L.; Braun, Ralph P.; Curiel-Lewandrowski, Clara N.; Elder, David E.; Ferrara, Gerardo; Grant-Kels, Jane M.; Jeunon, Thiago; Lallas, Aimilios; Lin, Jennifer Y.; Marchetti, Michael A.; Marghoob, Ashfaq A.; Navarrete-Dechent, Cristian; Pellacani, Giovanni; Soyer, Hans Peter; Stratigos, Alexander; Thomas, Luc; Kittler, Harald; Rotemberg, Veronica; Halpern, Allan C.
    Background: A common terminology for diagnosis is critically important for clinical communication, education, research and artificial intelligence. Prevailing lexicons are limited in fully representing skin neoplasms. Objectives: To achieve expert consensus on diagnostic terms for skin neoplasms and their hierarchical mapping. Methods: Diagnostic terms were extracted from textbooks, publications and extant diagnostic codes. Terms were hierarchically mapped to super-categories (e.g. 'benign') and cellular/tissue-differentiation categories (e.g. 'melanocytic'), and appended with pertinent-modifiers and synonyms. These terms were evaluated using a modified-Delphi consensus approach. Experts from the International-Skin-Imaging-Collaboration (ISIC) were surveyed on agreement with terms and their hierarchical mapping; they could suggest modifying, deleting or adding terms. Consensus threshold was >75% for the initial rounds and >50% for the final round. Results: Eighteen experts completed all Delphi rounds. Of 379 terms, 356 (94%) reached consensus in round one. Eleven of 226 (5%) benign-category terms, 6/140 (4%) malignant-category terms and 6/13 (46%) indeterminate-category terms did not reach initial agreement. Following three rounds, final consensus consisted of 362 terms mapped to 3 super-categories and 41 cellular/tissue-differentiation categories. Conclusions: We have created, agreed upon, and made public a taxonomy for skin neoplasms and their hierarchical mapping. Further study will be needed to evaluate the utility and completeness of the lexicon.
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    Perifollicular linear projections: A dermatoscopic criterion for the diagnosis of lentigo maligna on the face
    (2024) Navarrete-Dechent, Cristian; Jaimes, Natalia; Dusza, Stephen W.; Liopyris, Konstantinos; Marchetti, Michael A.; Cordova, Miguel; Oliviero, Margaret; Villaseca, Miguel A.; Pulitzer, Melissa; Busam, Klaus J.; Rossi, Anthony M.; Rabinovitz, Harold S.; Nehal, Kishwer S.; Scope, Alon; Marghoob, Ashfaq A.
    Background: Lentigo maligna (LM) can mimic benign, flat, pigmented lesions and can be challenging to diagnose. Objective: To describe a new dermatoscopic feature termed "perifollicular linear projections (PLP)"as a diagnostic criterion for LM on the face. Methods: Retrospective study on reflectance confocal microscopy and dermatoscopy images of flat facial pigmented lesions originating from 2 databases. PLP were defined as short, linear, pigmented projections emanating from hair follicles. Dermatoscopy readers were blinded to the final histopathologic diagnosis. Results: From 83 consecutive LMs, 21/83 (25.3%) displayed "bulging of hair follicles"on reflectance confocal microscopy and 18 of these 21 (85.7%), displayed PLP on dermatoscopy. From a database of 2873 consecutively imaged and biopsied lesions, 252 flat-pigmented facial lesions were included. PLP was seen in 47/76 melanomas (61.8%), compared with 7/176 lesions (3.9%) with other diagnosis (P \ .001). The sensitivity was 61.8% (95% CI, 49.9%-72.7%), specificity 96.0% (95% CI, 92.9%-98.4%). PLP was independently associated with LM diagnosis on multivariate analysis (OR 26.1 [95% CI, 9.6%-71.0]). Limitations: Retrospective study. Conclusion: PLP is a newly described dermatoscopic criterion that may add specificity and sensitivity to the early diagnosis of LM located on the face. We postulate that PLP constitutes an intermediary step in the LM progression model. ( J Am Acad Dermatol 2024;90:52-7.)
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    Visualizing Touton Giant Cells Under Reflectance Confocal Microscopy in Two Cases of Juvenile Xanthogranuloma
    (2023) Peirano, Dominga; Donoso, Francisca; Hidalgo, Leonel; Feuerhake, Teo; Scope, Alon; Longo, Caterina; Navarrete-Dechent, Cristian