Browsing by Author "Longo, Caterina"

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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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    Delphi Consensus Among International Experts on the Diagnosis, Management, and Surveillance for Lentigo Maligna
    (2023) Longo, Caterina; Navarrete-Dechent, Cristian; Tschandl, Philipp; Apalla, Zoe; Argenziano, Giuseppe; Braun, Ralph P.; Bataille, Veronique; Cabo, Horacio; Hoffmann-Wellhenhof, Rainer; Forsea, Ana Maria; Garbe, Claus; Guitera, Pascale; Raimond, Karls; Marghoob, Ashfaq A.; Malvehy, Josep; Del Marmol, Veronique; Moreno, David; Nehal, Kishwer S.; Nagore, Eduardo; Paoli, John; Pellacani, Giovanni; Peris, Ketty; Puig, Susana; Soyer, H. Peter; Swetter, Susan; Stratigos, Alexander; Stolz, Wilhelm; Thomas, Luc; Tiodorovic, Danica; Zalaudek, Iris; Kittler, Harald; Lallas, Aimilios
    Introduction: Melanoma of the lentigo maligna (LM) type is challenging. There is lack of consensus on the optimal diagnosis, treatment, and follow-up.
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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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    Lentigo maligna and lentigo maligna melanoma in patients younger than 50 years: a multicentre international clinical-dermoscopic study
    (2024) Longo, Caterina; Sticchi, Alberto; Curti, Alex; Kaleci, Shaniko; Moscarella, Elvira; Argenziano, Giuseppe; Thomas, Luc; Guitera, Pascale; Huang, Chen; Tiodorovic, Danica; Apalla, Zoe; Peris, Ketty; del Regno, Laura; Guida, Stefania; Lallas, Aimilios; Kittler, Harald; Pellacani, Giovanni; Navarrete-Dechent, Cristian
    Background Lentigo maligna/lentigo maligna melanoma (LM/LMM) is usually diagnosed in older patients, when lesions are larger. However, it is important to detect it at an earlier stage to minimize the area for surgical procedure.
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    Natural language processing in dermatology: A systematic literature review and state of the art
    (2024) Paganelli, Alessia; Spadafora, Marco; Navarrete‐Dechent, Cristian; Guida, Stefania; Pellacani, Giovanni; Longo, Caterina
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    Superficial angiomyxoma of the skin
    (2016) Abarzúa, Alvaro; Lallas, Aimillios; Piana, Simonetta; Longo, Caterina; Moscarella, Elvira; Argenziano, Giuseppe
    Superficial angiomyxomas (SA) of the skin are rare benign cutaneous tumors of soft tissue composedof prominent myxoid matrix and numerous blood vessels. SA are more common in males [1] and theyare usually located on the trunk but can also appear on the lower limbs, head, neck and genitalia [2,3].Treatment is surgical, the total excision is curative, but local recurrence is possible [4]. Herein wepresent a 72-year-old patient with a history of melanoma in situ, with a new lesion on the lower back.
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    Use of game-based learning strategies for dermatology and dermoscopy education: a cross-sectional survey of members of the International Dermoscopy Society
    (2024) Donoso, Francisca; Peirano, Dominga; Aguero, Rosario; Longo, Caterina; Apalla, Zoe; Lallas, Aimilios; Jaimes, Natalia; Navarrete-Dechent, Cristian
    Background Dermoscopy is a valuable tool in the diagnosis of various skin conditions. It increases sensitivity and specificity in skin cancer diagnosis, as well as in infectious, inflammatory and hair diseases. However, mastering the intricacies of dermoscopy can be challenging. In this context, innovative educational methods are sought, including game-based learning (GBL) strategies. Objectives To describe current perceptions, knowledge and use of GBL strategies in dermoscopy education, and identify strengths and challenges to enhance their use. Methods A web-based cross-sectional survey with 25 questions was distributed to members of the International Dermoscopy Society between October 2022 and April 2023. Responses were collected and analysed using frequency analysis and graphical representation. Results In total, 801 responses were received. Of these, 46.6% of respondents were unfamiliar with gamification and serious games. Among those acquainted with these concepts, 56.3% reported using GBL strategies for education. Younger participants were more likely to use GBL strategies (P = 0.02). Participants familiar with GBL believed it enhanced medical education (78.5%) but should not entirely replace traditional teaching methods (96.0%). For dermoscopy education specifically, 22.1% of respondents had used GBL strategies, with Kahoot! (35.5%) and YOUdermoscopy (24.1%) being the most commonly used platforms. Respondents found gaming strategies to be fun (95.5%), motivating (91.0%) and valuable for e-learning (94.4%). Conclusions Results from this survey demonstrate a favourable perception of GBL strategies in dermatology education, including dermoscopy. While there are ongoing challenges in validation, GBL strategies are promising and valuable tools that can aid the learning and teaching experience. Addressing implementation barriers and validating existing games could optimize the impact of GBL on dermatology education.
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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