Cutaneous melanoma

The Lancet, Journal Year: 2023, Volume and Issue: 402(10400), P. 485 - 502

Published: July 24, 2023

Language: Английский

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Skin Lesions Classification Into Eight Classes for ISIC 2019 Using Deep Convolutional Neural Network and Transfer Learning

IEEE Access, Journal Year: 2020, Volume and Issue: 8, P. 114822 - 114832

Published: Jan. 1, 2020

Melanoma is a type of skin cancer with high mortality rate. The different types lesions result in an inaccurate diagnosis due to their similarity. Accurate classification the early stages enables dermatologists treat patients and save lives. This paper proposes model for highly accurate lesions. proposed utilized transfer learning pre-trained GoogleNet. parameters are used as initial values, then these will be modified through training. latest well-known public challenge dataset, ISIC 2019, test ability classify kinds successfully classified eight classes lesions, namely, melanoma, melanocytic nevus, basal cell carcinoma, actinic keratosis, benign dermatofibroma, vascular lesion, Squamous carcinoma. achieved accuracy, sensitivity, specificity, precision percentages 94.92%, 79.8%, 97%, 80.36%, respectively. can detect images that do not belong any one where unknown images.

Language: Английский

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NCCN Guidelines® Insights: Melanoma: Cutaneous, Version 2.2021

Journal of the National Comprehensive Cancer Network, Journal Year: 2021, Volume and Issue: 19(4), P. 364 - 376

Published: April 1, 2021

Over the past few years, NCCN Guidelines for Melanoma: Cutaneous have been expanded to include pathways treatment of microscopic satellitosis (added in v2.2020), and following Principles sections: Molecular Testing v2.2019), Systemic Therapy Considerations Brain Metastases Management v3.2020). The v1.2021 update included additional modifications these sections notable revisions of: Pathology, Surgical Margins Wide Excision Primary Melanoma, Sentinel Lymph Node Biopsy, Completion/Therapeutic Dissection, Radiation Therapy. These Insights discuss important changes pathology surgery recommendations, as well additions systemic therapy options patients with advanced disease.

Language: Английский

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Overcoming Immune Evasion in Melanoma

International Journal of Molecular Sciences, Journal Year: 2020, Volume and Issue: 21(23), P. 8984 - 8984

Published: Nov. 26, 2020

Melanoma is the most aggressive and dangerous form of skin cancer that develops from transformed melanocytes. It crucial to identify melanoma at its early stages, in situ, as it "curable" this stage. However, after metastasis, difficult treat five-year survival only 25%. In recent years, a better understanding etiology progression has made possible for development targeted therapeutics, such vemurafenib immunotherapies, advanced melanomas. review, we focus on molecular mechanisms mediate progression, with special immune evasion strategies utilized by melanomas, evade host surveillances. The proposed mechanism action roles immunotherapeutic agents, ipilimumab, nivolumab, pembrolizumab, atezolizumab, adoptive T- cell therapy plus T-VEC treatment are discussed. implore steps onset exploited these tumor cells, identification biomarkers predict response critical design improved improve clinical outcomes patients deadly disease.

Language: Английский

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The Spatial Landscape of Progression and Immunoediting in Primary Melanoma at Single-Cell Resolution

Cancer Discovery, Journal Year: 2022, Volume and Issue: 12(6), P. 1518 - 1541

Published: April 4, 2022

Cutaneous melanoma is a highly immunogenic malignancy that surgically curable at early stages but life-threatening when metastatic. Here we integrate high-plex imaging, 3D high-resolution microscopy, and spatially resolved microregion transcriptomics to study immune evasion immunoediting in primary melanoma. We find recurrent cellular neighborhoods involving tumor, immune, stromal cells change significantly along progression axis precursor states, situ, invasive tumor. Hallmarks of immunosuppression are already detectable regions. When tumors become locally invasive, consolidated restricted suppressive environment forms the tumor-stromal boundary. This established by cytokine gradients promote expression MHC-II IDO1, PD1-PDL1-mediated cell contacts macrophages, dendritic cells, T cells. A few millimeters away, cytotoxic synapse with fields tumor regression. Thus, invasion can coexist within each other single specimen. The reorganization ecosystem an excellent setting which evasion. Guided classic histopathology, spatial profiling proteins mRNA reveals morphologic molecular features evolution involve localized paracrine signaling direct cell-cell contact. article highlighted In Issue feature, p. 1397.

Language: Английский

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Does the morphology of cutaneous melanoma help to explain the international differences in survival? Results from 1 578 482 adults diagnosed during 2000–2014 in 59 countries (CONCORD-3)

British Journal of Dermatology, Journal Year: 2022, Volume and Issue: 187(3), P. 364 - 380

Published: March 29, 2022

Abstract Background CONCORD-3 highlighted wide disparities in population-based 5-year net survival for cutaneous melanoma during 2000–2014. Clinical evidence suggests marked international differences the proportion of lethal acral and nodular subtypes melanoma. Objectives We aimed to assess whether morphology may explain global variation survival. Methods Patients with were grouped into following seven morphological categories: malignant melanoma, not otherwise specified (International Classification Diseases Oncology, third revision code 8720), superficial spreading (8743), lentigo maligna (8742), (8721), lentiginous (8744), desmoplastic (8745) other morphologies (8722–8723, 8726–8727, 8730, 8740–8741, 8746, 8761, 8770–8774, 8780). estimated using nonparametric Pohar Perme estimator, correcting background mortality by single year age, sex calendar each country or region. All-ages estimates standardized International Cancer Survival Standard weights. fitted a flexible parametric model estimate effect on hazard death. Results Worldwide, ranged between 7% 13%. Acral accounted less than 2% all registrations but was more common Asia (6%) Central South America (7%). Overall, 36% tumours classified as During 2010–2014, age-standardized 95% higher Oceania, North most European countries, only 71% Taiwan. 66% 95%. Nodular had poorest prognosis countries. The multivariable analysis data from registries complete information stage found that sex, age at diagnosis partially risk death subtypes. Conclusions This study provides broadest picture distribution trends main 59 poorer melanomas, frequent Latin America, need health policies specific populations improve awareness, early access treatment. What is already known about this topic? histopathological features vary markedly worldwide. melanomas aggressive histological predominantly dark skin fair skin. does add? extent which these when are combined. provides, first time, comparisons 5 years over 1.5 million adults diagnosed highlights favourable melanomas. later fully excess compared

Language: Английский

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Cutaneous Malignant Melanoma: A Review of Early Diagnosis and Management

World Journal of Oncology, Journal Year: 2021, Volume and Issue: 12(1), P. 7 - 19

Published: Jan. 1, 2021

Cutaneous melanoma (CM) is a malignant tumor formed from pigment-producing cells called melanocytes. It one of the most aggressive and fatal forms skin malignancy. In last decades, CM's incidence has gradually risen, with 351,880 new cases in 2015. Since 1960s, its increased steadily, 2019, approximately 96,000 cases. A greater understanding early diagnosis management CM urgently needed because high mortality rates due to metastatic melanoma. Timely detection crucial for successful treatment, but histopathology may also pose significant challenge this objective. Early are essential contribute better survival patient. To control malignancy, such information expected be particularly useful possible lesions development therapeutic approaches. This article reviews available on discusses information's potential facilitating future prospective. World J Oncol. 2021;12(1):7-19 doi: https://doi.org/10.14740/wjon1349

Language: Английский

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Artificial Intelligence in Dermatology Image Analysis: Current Developments and Future Trends

Journal of Clinical Medicine, Journal Year: 2022, Volume and Issue: 11(22), P. 6826 - 6826

Published: Nov. 18, 2022

Background: Thanks to the rapid development of computer-based systems and deep-learning-based algorithms, artificial intelligence (AI) has long been integrated into healthcare field. AI is also particularly helpful in image recognition, surgical assistance basic research. Due unique nature dermatology, AI-aided dermatological diagnosis based on recognition become a modern focus future trend. Key scientific concepts review: The use 3D imaging allows clinicians screen label skin pigmented lesions distributed disorders, which can provide an objective assessment documentation lesion sites. Dermatoscopes combined with intelligent software help dermatologist easily correlate each close-up corresponding marked body map. In addition, field prosthetics assist rehabilitation patients restore limb function after amputation tumors. aim study: For benefit patients, dermatologists have obligation explore opportunities, risks limitations applications. This study focuses application emerging dermatology aid clinical treatment, analyzes current state summarizes its trends prospects so as realize impact new technological innovations traditional practices that they embrace AI-based medical approaches more quickly.

Language: Английский

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Clinical aspects of multiple endocrine neoplasia type 1

Nature Reviews Endocrinology, Journal Year: 2021, Volume and Issue: 17(4), P. 207 - 224

Published: Feb. 9, 2021

Language: Английский

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Artificial Intelligence in Dermatology: Challenges and Perspectives

Dermatology and Therapy, Journal Year: 2022, Volume and Issue: 12(12), P. 2637 - 2651

Published: Oct. 28, 2022

Artificial intelligence (AI) based on machine learning and convolutional neuron networks (CNN) is rapidly becoming a realistic prospect in dermatology. Non-melanoma skin cancer the most common worldwide melanoma one of deadliest forms cancer. Dermoscopy has improved physicians' diagnostic accuracy for recognition but unfortunately it remains comparatively low. AI could provide invaluable aid early evaluation diagnosis In last decade, there been breakthrough new research publications field AI. Studies have shown that CNN algorithms can classify lesions from dermoscopic images with superior or at least equivalent performance compared to clinicians. Even though very promising results reader studies, their generalizability applicability everyday clinical practice remain elusive. Herein we attempted summarize potential pitfalls challenges were underlined studies pinpoint strategies overcome limitations future studies. Finally, tried analyze advantages opportunities lay ahead better dermatology patients, use our practices.

Language: Английский

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