Browsing by Author "Liopyris, Konstantinos"

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    Clinical and dermoscopic features associated with lichen planus-like keratoses that undergo skin biopsy: A single-center, observational study
    (2019) Liopyris, Konstantinos; Cristian Navarrete-Dechent; Dusza, Stephen W.; Marghoob, Ashfaq A.; Deng, Liang; Wilson, Barbara B.; Marchetti, Michael A.
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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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    Dermoscopy of linear basal cell carcinomas, a potential mimicker of linear lesions: a descriptive case series
    (2022) Navarrete-Dechent, Cristián; Marchetti, Michael; Uribe González, Pablo Francisco; Schwartz, Rodrigo; Liopyris, Konstantinos; Marghoob, Nadeem; Galimany Navajas, Lucas Fernando; Castro, Juan; Jaimes, Natalia; Rabinovitz, Harold; Moraes, Ana; Marghoob, Ashfaq; Abarzúa-Araya, Alvaro
    Introduction: Among the various widely recognized basal cell carcinoma (BCC) clinical patterns, linear basal cell carcinoma (LBCC) is an uncommon morphologic variant of BCC. Objectives: Describe the clinical and dermoscopic characteristics of LBCC. Methods: Retrospective study including LBCC cases from 5 dermatology centers in North and South America. Biopsy-proven primary BCCs, that presented with at least 3:1 length:width ratio on physical examination, irrespective of tumor subtype or location, were included. Clinical and dermoscopic analysis were performed by 2 experts in dermoscopy. Results: Eighteen cases of LBCC met our inclusion criteria and were included in the study. Median age at diagnosis was 86.0 years, 10 patients (58.8%) were males. Regarding anatomic location, 11/18.
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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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    In vivo imaging characterization of basal cell carcinoma and cutaneous response to high-dose ionizing radiation therapy: A prospective study of reflectance confocal microscopy, dermoscopy, and ultrasonography
    (2021) Navarrete-Dechent, Cristian; Cordova, Miguel; Liopyris, Konstantinos; Aleissa, Saud; Rajadhyaksha, Milind; Cohen, Gil'ad; Marghoob, Ashfaq A.; Rossi, Anthony M.; Barker, Christopher A.
    Background: Radiation therapy (RT) is a treatment option for select skin cancers. The histologic effects of RT on normal skin or skin cancers are not well characterized. Dermoscopy, high-frequency ultrasonography (HFUS), and reflectance confocal microscopy (RCM) are noninvasive imaging modalities that may help characterize RT response.
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    Incidence of New Primary Cutaneous Melanoma in Patients With Metastatic Melanoma Treated With Immune Checkpoint Inhibitors A Single-Center Cohort Study
    (2021) Nanda, Japbani K.; Dusza, Stephen W.; Navarrete-Dechent, Cristian; Liopyris, Konstantinos; Marghoob, Ashfaq A.; Marchetti, Michael A.
    Question What is the incidence of new primary cutaneous melanoma (CM) after initiating immune checkpoint inhibitor therapy for metastatic melanoma? Findings In this single-center observational cohort study, 42 of 2251 patients (1.9%) who received immune checkpoint inhibitors were diagnosed with 48 melanomas. The incidence rate was approximately 1100 cases per 100000 person-years, and the cumulative cause-specific risk of new CM after 5 years was 4.9%; patients diagnosed with a new primary CM were more likely to have a family history of melanoma. Meaning Patients who receive checkpoint inhibitors for treatment of metastatic melanoma remain at risk for the development of new primary CMs.
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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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    Lentigo maligna melanoma mapping using reflectance confocal microscopy correlates with staged excision: A prospective study
    (2023) Navarrete-Dechent, Cristian; Cordova, Miguel; Aleissa, Saud; Liopyris, Konstantinos; Dusza, Stephen W.; Kose, Kivanc; Busam, Klaus J.; Hollman, Travis; Lezcano, Cecilia; Pulitzer, Melissa; Chen, Chih-Shan J.; Lee, Erica H.; Rossi, Anthony M.; Nehal, Kishwer S.
    Background: Lentigo maligna/lentigo maligna melanoma (LM/LMM) can present with subclinical extension that may be difficult to define preoperatively and lead to incomplete excision and potential recurrence. Preliminarily studies have used reflectance confocal microscopy (RCM) to assess LM/LMM margins.
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    Melanocytic Lesions. Other Melanoma Subtypes
    (CRC Press, 2022) Navarrete Dechent, Cristián Patricio; Liopyris, Konstantinos; Jaimes, Natalia; Marghoob, Ashfaq A.
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    Nonmelanocytic Lesions
    (CRC Press, 2022) Navarrete Dechent, Cristián Patricio; Liopyris, Konstantinos; Marghoob, Ashfaq A.
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    Paradoxical effect of epinephrine on lesion redness and vascularity
    (2023) Nazir, Zaeem H.; Rishpon, Ayelet; Kose, Kivanc; Marghoob, Nadeem G.; Liopyris, Konstantinos; Navarrete-Dechent, Cristian; Dusza, Stephen W.; Daoud, Alexander; Marghoob, Ashfaq A.
    IntroductionEpinephrine is commonly used in combination with local anesthetic (lidocaine/epinephrine) due to its beneficial vasoconstrictive properties. Typically, pallor is appreciated after injection as a sign of effect; however, we observed that some cutaneous malignancies paradoxically revealed increased redness and vascularity after injection of lidocaine/epinephrine. In this study, we investigate this phenomenon among a series of biopsied lesions to identify characteristics of lesions associated with increased redness and/or vascularity.ObjectivesTo determine characteristics of lesions which become redder or more vascular after injection with lidocaine/epinephrine prior to biopsy.MethodsThis cross-sectional study consisted of a convenience sample of lesions scheduled for biopsy. Lesions were photographed prior to and 7 min after injection of lidocaine/epinephrine as a part of standard care. Two readers blinded to study objectives and histopathological diagnosis assessed lesions for changes in redness and vascular features.ResultsFifty-four lesions from 47 patients-61.7% male, mean age 64.8 years, age-range 24-91 were included. Thirty-six lesions were biopsy confirmed malignant, with 5 in situ and 31 invasive malignancies; the remaining 18 lesions were benign. In comparison with non-malignant lesions, malignant lesions were associated with an increase in clinically appreciable vascular features after injection of lidocaine/epinephrine, X-2 (1) = 21.600, p < 0.001. Further stratification into benign, in situ, and invasive lesions strengthened the association, X-2 (1) = 23.272, p < 0.001.ConclusionsCombination lidocaine/epinephrine has been shown to paradoxically increase the visibility of vessels seen in cutaneous malignancies. This is consistent with prior literature suggesting aberrant adrenergic signaling in neoangiogenic vessels.
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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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    Reflectance confocal microscopy terminology for non-melanocytic skin lesions: A Delphi consensus of experts
    (Elsevier Inc., 2025) Navarrete Dechent, Cristian Patricio; Longo, Caterina; Liopyris, Konstantinos; Ardigo, Marco; Ahlgrimm-Siess, Verena; Bahadoran, Phillipe; Carrera, Cristina; Braga, Juliana Casagrande Tavoloni; Chen, Chih-Shan J.; Correa, Lilia; Carvahlo, Nathalie de; Durkin, John; Farnetani, Francesca; Grant-Kels, Jane M.; Gill, Melissa; Gonzalez, Salvador; Hartmann, Daniela; Hoffman-Wellenhof, Rainer; Huho, Albert; Ludzik, Joanna; Malvehy, Josep; Marghoob, Ashfaq A.; Moscarella, Elvira; Oliviero, Margaret; Puig, Susana; Rabinovitz, Harold; Rao, Babar; Rezze, Gisele G.; Rossi, Anthony M.; Rubinstein, Gene; Ruini, Cristel; Sattler, Elke; Soyer, H. Peter; Schwartz, Rodrigo; Thng, Steven; Ulrich, Martina; Witkowski, Alexander; Dusza, Stephen W.; Guitera, Pascale; Pellacani, Giovanni; Scope, Alon; Jain, Manu
    Background There is lack of uniformity in reflectance confocal microscopy (RCM) terminology. Objective To establish expert consensus on a standardized set of RCM terms that describe non-melanocytic lesions (NML). Methods We invited RCM experts to participate in a Delphi-consensus study. Fifty-nine RCM descriptors were extracted from a previous systematic review on RCM terminology for describing NML. Of these, 35 items were presented as 4 groups of synonymous terms and 24 items as single, non-synonymous terms. For the first round, an agreement threshold was set at >70%. Participants could also propose new terms. Terms with ≤70% agreement and newly proposed terms were carried over to the next round. For subsequent rounds, agreement threshold was set at >50%. Results The study was conducted between June 2021 and May 2023. Forty-two of 44 (95%) invited experts participated. Three iterative Delphi rounds were completed, resulting in a consensus list of 36 terms, including 32 synonymous- and 4 non-synonymous- terms for describing NML. Limitations Only experts were included. We did not evaluate definitions of terms in the study. Conclusions We propose a simplified list of RCM terms, vetted by RCM experts, for describing and diagnosing NML. Uniform terminology could benefit clinical practice, research, and education.
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    The degradation of performance of a state-of-the-art skin image classifier when applied to patient-driven internet search
    (2022) Han, Seung Seog; Navarrete-Dechent, Cristian; Liopyris, Konstantinos; Kim, Myoung Shin; Park, Gyeong Hun; Woo, Sang Seok; Park, Juhyun; Shin, Jung Won; Kim, Bo Ri; Kim, Min Jae; Donoso, Francisca; Villanueva, Francisco; Ramirez, Cristian; Chang, Sung Eun; Halpern, Allan; Kim, Seong Hwan; Na, Jung-Im
    Model Dermatology (; Build2021) is a publicly testable neural network that can classify 184 skin disorders. We aimed to investigate whether our algorithm can classify clinical images of an Internet community along with tertiary care center datasets. Consecutive images from an Internet skin cancer community ('RD' dataset, 1,282 images posted between 25 January 2020 to 30 July 2021; ) were analyzed retrospectively, along with hospital datasets (Edinburgh dataset, 1,300 images; SNU dataset, 2,101 images; TeleDerm dataset, 340 consecutive images). The algorithm's performance was equivalent to that of dermatologists in the curated clinical datasets (Edinburgh and SNU datasets). However, its performance deteriorated in the RD and TeleDerm datasets because of insufficient image quality and the presence of out-of-distribution disorders, respectively. For the RD dataset, the algorithm's Top-1/3 accuracy (39.2%/67.2%) and AUC (0.800) were equivalent to that of general physicians (36.8%/52.9%). It was more accurate than that of the laypersons using random Internet searches (19.2%/24.4%). The Top-1/3 accuracy was affected by inadequate image quality (adequate = 43.2%/71.3% versus inadequate = 32.9%/60.8%), whereas participant performance did not deteriorate (adequate = 35.8%/52.7% vs. inadequate = 38.4%/53.3%). In this report, the algorithm performance was significantly affected by the change of the intended settings, which implies that AI algorithms at dermatologist-level, in-distribution setting, may not be able to show the same level of performance in with out-of-distribution settings.