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Agüero R, Buchanan KL, Navarrete-Dechent C, Marghoob AA, Stein JA, Landy MS, Leachman SA, Linden KG, Garcet S, Krueger JG, Gareau DS. The Impact of Melanoma Imaging Biomarker Cues on Detection Sensitivity and Specificity in Melanoma versus Clinically Atypical Nevi. Cancers (Basel) 2024; 16:3077. [PMID: 39272935 PMCID: PMC11394255 DOI: 10.3390/cancers16173077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 08/31/2024] [Accepted: 09/02/2024] [Indexed: 09/15/2024] Open
Abstract
Incorporation of dermoscopy and artificial intelligence (AI) is improving healthcare professionals' ability to diagnose melanoma earlier, but these algorithms often suffer from a "black box" issue, where decision-making processes are not transparent, limiting their utility for training healthcare providers. To address this, an automated approach for generating melanoma imaging biomarker cues (IBCs), which mimics the screening cues used by expert dermoscopists, was developed. This study created a one-minute learning environment where dermatologists adopted a sensory cue integration algorithm to combine a single IBC with a risk score built on many IBCs, then immediately tested their performance in differentiating melanoma from benign nevi. Ten participants evaluated 78 dermoscopic images, comprised of 39 melanomas and 39 nevi, first without IBCs and then with IBCs. Participants classified each image as melanoma or nevus in both experimental conditions, enabling direct comparative analysis through paired data. With IBCs, average sensitivity improved significantly from 73.69% to 81.57% (p = 0.0051), and the average specificity improved from 60.50% to 67.25% (p = 0.059) for the diagnosis of melanoma. The index of discriminability (d') increased significantly by 0.47 (p = 0.002). Therefore, the incorporation of IBCs can significantly improve physicians' sensitivity in melanoma diagnosis. While more research is needed to validate this approach across other healthcare providers, its use may positively impact melanoma screening practices.
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Affiliation(s)
- Rosario Agüero
- Department of Dermatology, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago 8330024, Chile
| | - Kendall L Buchanan
- Department of Dermatology, Medical College of Georgia at Augusta University, Augusta, GA 30904, USA
| | - Cristián Navarrete-Dechent
- Melanoma and Skin Cancer Unit, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago 8330024, Chile
- Memorial Sloan Kettering Skin Cancer Center, New York, NY 10022, USA
| | - Ashfaq A Marghoob
- Memorial Sloan Kettering Skin Cancer Center, New York, NY 10022, USA
| | - Jennifer A Stein
- Ronald O. Perelman Department of Dermatology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Michael S Landy
- Department of Psychology, New York University, New York, NY 10003, USA
- Center for Neural Science, New York University, New York, NY 10003, USA
| | - Sancy A Leachman
- Dermatology Department, Oregon Health & Science University, Portland, OR 97239, USA
| | - Kenneth G Linden
- Dermatology Department, University of California Irvine, Irvine, CA 92868, USA
- Chao Family Comprehensive Cancer Center, University of California Irvine, Irvine, CA 92868, USA
| | - Sandra Garcet
- Laboratory for Investigative Dermatology, Rockefeller University, New York, NY 10065, USA
| | - James G Krueger
- Laboratory for Investigative Dermatology, Rockefeller University, New York, NY 10065, USA
| | - Daniel S Gareau
- Laboratory for Investigative Dermatology, Rockefeller University, New York, NY 10065, USA
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Beeler N, Ziegler E, Volz A, Navarini AA, Kapur M. The effects of procedural and conceptual knowledge on visual learning. ADVANCES IN HEALTH SCIENCES EDUCATION : THEORY AND PRACTICE 2024; 29:1243-1263. [PMID: 38060072 PMCID: PMC11368992 DOI: 10.1007/s10459-023-10304-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 11/12/2023] [Indexed: 12/08/2023]
Abstract
Even though past research suggests that visual learning may benefit from conceptual knowledge, current interventions for medical image evaluation often focus on procedural knowledge, mainly by teaching classification algorithms. We compared the efficacy of pure procedural knowledge (three-point checklist for evaluating skin lesions) versus combined procedural plus conceptual knowledge (histological explanations for each of the three points). All students then trained their classification skills with a visual learning resource that included images of two types of pigmented skin lesions: benign nevi and malignant melanomas. Both treatments produced significant and long-lasting effects on diagnostic accuracy in transfer tasks. However, only students in the combined procedural plus conceptual knowledge condition significantly improved their diagnostic performance in classifying lesions they had seen before in the pre- and post-tests. Findings suggest that the provision of additional conceptual knowledge supported error correction mechanisms.
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Affiliation(s)
- Nadja Beeler
- Professorship for Learning Sciences and Higher Education, ETH Zurich, RZ Building, Clausiusstrasse 59, 8092, Zurich, Switzerland.
| | - Esther Ziegler
- Professorship for Learning Sciences and Higher Education, ETH Zurich, RZ Building, Clausiusstrasse 59, 8092, Zurich, Switzerland
| | - Andreas Volz
- Dermatologie am Rhein, Blumenrain 20, 4051, Basel, Switzerland
| | - Alexander A Navarini
- Department of Dermatology, University Hospital Basel, Burgfelderstrasse 101, 4055, Basel, Switzerland
| | - Manu Kapur
- Professorship for Learning Sciences and Higher Education, ETH Zurich, RZ Building, Clausiusstrasse 59, 8092, Zurich, Switzerland
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Boleti APDA, Jacobowski AC, Monteiro-Alfredo T, Pereira APR, Oliva MLV, Maria DA, Macedo MLR. Cutaneous Melanoma: An Overview of Physiological and Therapeutic Aspects and Biotechnological Use of Serine Protease Inhibitors. Molecules 2024; 29:3891. [PMID: 39202970 PMCID: PMC11357276 DOI: 10.3390/molecules29163891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Revised: 08/11/2024] [Accepted: 08/14/2024] [Indexed: 09/03/2024] Open
Abstract
BACKGROUND Metastatic melanoma stands out as the most lethal form of skin cancer because of its high propensity to spread and its remarkable resistance to treatment methods. METHODS In this review article, we address the incidence of melanoma worldwide and its staging phases. We thoroughly investigate the different melanomas and their associated risk factors. In addition, we underscore the principal therapeutic goals and pharmacological methods that are currently used in the treatment of melanoma. RESULTS The implementation of targeted therapies has contributed to improving the approach to patients. However, because of the emergence of resistance early in treatment, overall survival and progression-free periods continue to be limited. CONCLUSIONS We provide new insights into plant serine protease inhibitor therapeutics, supporting high-throughput drug screening soon, and seeking a complementary approach to explain crucial mechanisms associated with melanoma.
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Affiliation(s)
- Ana Paula De Araújo Boleti
- Laboratory of Protein Purification and Their Biological Functions, Food Technology and Public Health Unit, Federal University of Mato Grosso do Sul (UFMS), Campo Grande 79070-900, MS, Brazil; (A.P.D.A.B.); (A.C.J.); (T.M.-A.); (A.P.R.P.)
| | - Ana Cristina Jacobowski
- Laboratory of Protein Purification and Their Biological Functions, Food Technology and Public Health Unit, Federal University of Mato Grosso do Sul (UFMS), Campo Grande 79070-900, MS, Brazil; (A.P.D.A.B.); (A.C.J.); (T.M.-A.); (A.P.R.P.)
| | - Tamaeh Monteiro-Alfredo
- Laboratory of Protein Purification and Their Biological Functions, Food Technology and Public Health Unit, Federal University of Mato Grosso do Sul (UFMS), Campo Grande 79070-900, MS, Brazil; (A.P.D.A.B.); (A.C.J.); (T.M.-A.); (A.P.R.P.)
| | - Ana Paula Ramos Pereira
- Laboratory of Protein Purification and Their Biological Functions, Food Technology and Public Health Unit, Federal University of Mato Grosso do Sul (UFMS), Campo Grande 79070-900, MS, Brazil; (A.P.D.A.B.); (A.C.J.); (T.M.-A.); (A.P.R.P.)
| | - Maria Luiza Vilela Oliva
- Departamento de Bioquímica, Universidade Federal de São Paulo (UNIFESP), São Paulo 04023-062, SP, Brazil;
| | - Durvanei Augusto Maria
- Divisão de Ciências Fisiológicas e Químicas, Serviço de Bioquímica, Instituto Butantan, São Paulo 05585-000, SP, Brazil;
| | - Maria Lígia Rodrigues Macedo
- Laboratory of Protein Purification and Their Biological Functions, Food Technology and Public Health Unit, Federal University of Mato Grosso do Sul (UFMS), Campo Grande 79070-900, MS, Brazil; (A.P.D.A.B.); (A.C.J.); (T.M.-A.); (A.P.R.P.)
- Department of Pharmaceutical Sciences, Food, and Nutrition, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, MS, Brazil
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Arouch B, Elboim-Gabyzon M. The role of physical therapists in the early detection of skin melanoma: insights from an anonymous survey. Front Med (Lausanne) 2024; 11:1436206. [PMID: 39170048 PMCID: PMC11337224 DOI: 10.3389/fmed.2024.1436206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Accepted: 07/01/2024] [Indexed: 08/23/2024] Open
Abstract
Introduction Skin melanoma is the most severe form of skin cancer. Recent years have seen an increase in melanoma incidence. Melanomas often appear on the back, a hidden area, leading to late diagnoses. Physical therapists, who frequently treat patients with lower back pain, could play a crucial role in early melanoma detection. Methods An anonymous online survey was conducted among 254 Israeli physical therapists to assess their perspectives on melanoma detection, their knowledge in identifying suspicious lesions, and their referral patterns. The survey included sections on demographics, professional perspectives, melanoma knowledge, personal or family experiences with melanoma, and referral frequency for dermatological evaluation. Results The survey revealed that 75.2% of physical therapists viewed melanoma detection as part of their professional duties, yet 59.1% reported insufficient knowledge in identifying suspicious lesions. Despite this, 94.1% expressed a desire to improve their knowledge. However, only 44.1% actively referred patients with suspicious lesions to dermatologists. There was a significant positive correlation between professional experience and referral rates (p-value < 0.001), indicating that more experienced therapists were more likely to refer patients. Discussion The study highlights the critical need for incorporating melanoma detection training into physical therapy education and professional development. Enhancing physical therapists' knowledge and skills in this area could improve early detection and patient outcomes. Despite the potential role of physical therapists in melanoma detection, current training programs lack emphasis on this aspect, underscoring the importance of revising educational curricula to include skin cancer detection techniques. Conclusion The findings suggest that while physical therapists recognize their role in melanoma detection, there is a significant knowledge gap. Addressing this through targeted education and training could enhance early detection efforts and improve patient care.
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Affiliation(s)
- Bar Arouch
- Department of Physical Therapy, School of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel
- Clalit Health Services, Holon Branch, Holon, Israel
| | - Michal Elboim-Gabyzon
- Department of Physical Therapy, School of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel
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Foltz EA, Ludzik J, Leachman S, Stoos E, Greiling T, Teske N, Clayton L, Becker AL, Witkowski A. Revolutionizing Skin Cancer Triage: The Role of Patient-Initiated Teledermoscopy in Remote Diagnosis. Cancers (Basel) 2024; 16:2565. [PMID: 39061204 PMCID: PMC11274391 DOI: 10.3390/cancers16142565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 07/09/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
INTRODUCTION Teledermatology, defined as the use of remote imaging technologies to provide dermatologic healthcare services to individuals in a distant setting, has grown considerably in popularity since its widespread implementation during the COVID-19 pandemic. Teledermoscopy employs a smartphone dermatoscope attachment paired with a smartphone camera to visualize colors and microstructures within the epidermis and superficial dermis that cannot be seen with the naked eye ABCD criteria alone. METHODS Our retrospective observational cohort and case-control study evaluated the utility of loaning a smartphone dermatoscope attachment to patients for remote triage of self-selected lesions of concern for skin cancer. The primary outcome was the number (percentage) of in-person follow-up visits required for patients who submitted lesion images, either with or without accompanying dermoscopic images. A medical record review was conducted on all Oregon Health & Science University Department of Dermatology spot check image submissions utilizing the smartphone dermatoscopes between August 2020 and August 2022. De-identified dermoscopic images of lesions that included corresponding non-dermoscopic clinical images in their submission (n = 70) were independently reviewed by a blinded expert dermoscopist. The expert used standard clinical algorithms (ABCD criteria for clinical images; dermoscopy three-point checklist for dermoscopic images) to determine whether the imaged lesion should be converted to an in-person visit for further evaluation and consideration for biopsy. RESULTS Of the 70 lesions submitted with corresponding clinical and dermoscopy images, 60 met the criteria for in-person evaluation from clinical (non-dermoscopic) image review compared to 28 meeting the criteria for in-person evaluation from dermoscopic images of the same lesion. Thus, a 53% reduction in conversion to an in-person consultation with the addition of smartphone dermatoscope images in virtual lesion triage was observed (p < 0.001, McNemar's Test). CONCLUSION Implementing patient-led teledermoscopy may reduce the frequency of in-person visits for benign lesions and consequently improve access to in-person dermatology consultations for patients with concerning and possibly malignant lesions.
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Affiliation(s)
- Emilie A. Foltz
- Department of Dermatology, Oregon Health & Science University, Portland, OR 97239, USA
- Elson S. Floyd College of Medicine, Washington State University, Spokane, WA 99202, USA
| | - Joanna Ludzik
- Department of Dermatology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Sancy Leachman
- Department of Dermatology, Oregon Health & Science University, Portland, OR 97239, USA
- Knight Cancer Research Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Elizabeth Stoos
- Department of Dermatology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Teri Greiling
- Department of Dermatology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Noelle Teske
- Department of Dermatology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Lara Clayton
- Department of Dermatology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Alyssa L. Becker
- Department of Dermatology, Oregon Health & Science University, Portland, OR 97239, USA
- John A. Burns School of Medicine, University of Hawai’i at Manoa, Honolulu, HI 96822, USA
| | - Alexander Witkowski
- Department of Dermatology, Oregon Health & Science University, Portland, OR 97239, USA
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Yousef YA, Alkhatib F, Elfalah M, AlRyalat SA, Mohammad M, AlHabahbeh O, AlJabari R, Zweifel S, AlNawiaseh I, Rejdak R, Toro MD. Assessing the Impact of Simulated Color Vision Deficiency on Ophthalmologists' Ability to Differentiate between Choroidal Melanoma and Choroidal Nevus. J Clin Med 2024; 13:3626. [PMID: 38930154 PMCID: PMC11204884 DOI: 10.3390/jcm13123626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 06/28/2024] Open
Abstract
Background: Color vision deficiency (CVD) is an often-overlooked issue within the medical community, and its consequences remain insufficiently explored. We aim to evaluate how CVD affects diagnostic accuracy and distinguish between malignant choroidal melanoma and benign choroidal nevus among ophthalmologists. Methods: In this cross-sectional study, we engaged ophthalmologists through a web-based survey distributed via the professional ophthalmology society's social media channels. The survey encompassed a series of three fundus images representing normal fundus, choroidal nevus, and choroidal melanoma. Each image underwent simulation for the three primary types of CVD-protanopia, deuteranopia, and tritanopia-alongside a non-simulated version. Results: The study included 41 participants, averaging 40 years of age (±9.2), comprising 28 (68%) men and 13 (32%) women. Significantly lower rates of identifying orange pigments were observed in simulated protanopia images compared to non-simulated ones (p = 0.038). In simulated deutranopia images, the recognition of melanotic lesions was notably reduced compared to non-simulated images (p = 0.048). No such limitation was observed for tritanopia. However, participants retained their ability to identify subretinal fluid and estimate tumor thickness in simulated and non-simulated images. Concerning simulated images of choroidal nevi, participants misdiagnosed nevi as choroidal melanoma in 37% of cases in simulated protanopia nevi images and 41% in simulated deutranopia nevi images. This resulted in unnecessary referrals of benign lesions as malignant, emphasizing the potential for mistaken diagnoses. Nevertheless, almost all simulated images of malignant melanoma were correctly referred for specialized oncological treatment. Conclusions: The simulated CVD conditions of protanopia and deuteranopia affected the accuracy of identifying the melanotic nature of the choroidal tumor and the presence of orange pigments. This limitation led to challenges in correctly diagnosing choroidal melanoma and choroidal nevus, resulting in extra referrals for nevus cases. However, participants were safe and could still determine the possible risk of eyes with choroidal melanoma, so most referred melanoma cases to specialized oncologists as needed.
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Affiliation(s)
- Yacoub A. Yousef
- Department of Surgery (Ophthalmology), King Hussein Cancer Center, Amman 11941, Jordan; (F.A.); (M.M.); (O.A.); (R.A.); (I.A.)
| | - Fawzieh Alkhatib
- Department of Surgery (Ophthalmology), King Hussein Cancer Center, Amman 11941, Jordan; (F.A.); (M.M.); (O.A.); (R.A.); (I.A.)
| | - Mutasem Elfalah
- Division of Ophthalmology, Department of Special Surgery, School of Medicine, The University of Jordan, Amman 11942, Jordan; (M.E.); (S.A.A.)
| | - Saif Aldeen AlRyalat
- Division of Ophthalmology, Department of Special Surgery, School of Medicine, The University of Jordan, Amman 11942, Jordan; (M.E.); (S.A.A.)
| | - Mona Mohammad
- Department of Surgery (Ophthalmology), King Hussein Cancer Center, Amman 11941, Jordan; (F.A.); (M.M.); (O.A.); (R.A.); (I.A.)
| | - Omar AlHabahbeh
- Department of Surgery (Ophthalmology), King Hussein Cancer Center, Amman 11941, Jordan; (F.A.); (M.M.); (O.A.); (R.A.); (I.A.)
| | - Reem AlJabari
- Department of Surgery (Ophthalmology), King Hussein Cancer Center, Amman 11941, Jordan; (F.A.); (M.M.); (O.A.); (R.A.); (I.A.)
| | - Sandrine Zweifel
- Department of Ophthalmology, University of Zürich, 8057 Zürich, Switzerland;
| | - Ibrahim AlNawiaseh
- Department of Surgery (Ophthalmology), King Hussein Cancer Center, Amman 11941, Jordan; (F.A.); (M.M.); (O.A.); (R.A.); (I.A.)
| | - Robert Rejdak
- Department of General and Pediatric Ophthalmology, Medical University of Lublin, 20-079 Lublin, Poland;
| | - Mario Damiano Toro
- Department of General and Pediatric Ophthalmology, Medical University of Lublin, 20-079 Lublin, Poland;
- Eye Clinic, Public Health Department, University of Naples Federico II, 80131 Naples, Italy
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Strzelecki M, Kociołek M, Strąkowska M, Kozłowski M, Grzybowski A, Szczypiński PM. Artificial intelligence in the detection of skin cancer: State of the art. Clin Dermatol 2024; 42:280-295. [PMID: 38181888 DOI: 10.1016/j.clindermatol.2023.12.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2024]
Abstract
The incidence of melanoma is increasing rapidly. This cancer has a good prognosis if detected early. For this reason, various systems of skin lesion image analysis, which support imaging diagnostics of this neoplasm, are developing very dynamically. To detect and recognize neoplastic lesions, such systems use various artificial intelligence (AI) algorithms. This area of computer science applications has recently undergone dynamic development, abounding in several solutions that are effective tools supporting diagnosticians in many medical specialties. In this contribution, a number of applications of different classes of AI algorithms for the detection of this skin melanoma are presented and evaluated. Both classic systems based on the analysis of dermatoscopic images as well as total body systems, enabling the analysis of the patient's whole body to detect moles and pathologic changes, are discussed. These increasingly popular applications that allow the analysis of lesion images using smartphones are also described. The quantitative evaluation of the discussed systems with particular emphasis on the method of validation of the implemented algorithms is presented. The advantages and limitations of AI in the analysis of lesion images are also discussed, and problems requiring a solution for more effective use of AI in dermatology are identified.
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Affiliation(s)
- Michał Strzelecki
- Institute of Electronics, Lodz University of Technology, Łódź, Poland.
| | - Marcin Kociołek
- Institute of Electronics, Lodz University of Technology, Łódź, Poland
| | - Maria Strąkowska
- Institute of Electronics, Lodz University of Technology, Łódź, Poland
| | - Michał Kozłowski
- Department of Mechatronics and Technical and IT Education, Faculty of Technical Science, University of Warmia and Mazury, Olsztyn, Poland
| | - Andrzej Grzybowski
- Institute for Research in Ophthalmology, Foundation for Ophthalmology Development, Poznan, Poland
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Mahmoud NM, Soliman AM. Early automated detection system for skin cancer diagnosis using artificial intelligent techniques. Sci Rep 2024; 14:9749. [PMID: 38679633 PMCID: PMC11056372 DOI: 10.1038/s41598-024-59783-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 04/15/2024] [Indexed: 05/01/2024] Open
Abstract
Recently, skin cancer is one of the spread and dangerous cancers around the world. Early detection of skin cancer can reduce mortality. Traditional methods for skin cancer detection are painful, time-consuming, expensive, and may cause the disease to spread out. Dermoscopy is used for noninvasive diagnosis of skin cancer. Artificial Intelligence (AI) plays a vital role in diseases' diagnosis especially in biomedical engineering field. The automated detection systems based on AI reduce the complications in the traditional methods and can improve skin cancer's diagnosis rate. In this paper, automated early detection system for skin cancer dermoscopic images using artificial intelligent is presented. Adaptive snake (AS) and region growing (RG) algorithms are used for automated segmentation and compared with each other. The results show that AS is accurate and efficient (accuracy = 96%) more than RG algorithm (accuracy = 90%). Artificial Neural networks (ANN) and support vector machine (SVM) algorithms are used for automated classification compared with each other. The proposed system with ANN algorithm shows high accuracy (94%), precision (96%), specificity (95.83%), sensitivity (recall) (92.30%), and F1-score (0.94). The proposed system is easy to use, time consuming, enables patients to make early detection for skin cancer and has high efficiency.
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Affiliation(s)
- Nourelhoda M Mahmoud
- Biomedical Engineering Department, Faculty of Engineering, Minia University, Minya, Egypt.
| | - Ahmed M Soliman
- Biomedical Engineering Department, Faculty of Engineering, Helwan University, Cairo, Egypt
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Dessinioti C, Plaka M, Befon A, Polidorou D, Stefanaki I, Kypreou K, Theology V, Stratigos AJ. A Retrospective Study of Diameter and Breslow Thickness in Invasive Melanomas. Dermatology 2024; 240:462-467. [PMID: 38290473 DOI: 10.1159/000536151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 01/01/2024] [Indexed: 02/01/2024] Open
Abstract
INTRODUCTION A diameter larger than 6 mm is included in the criteria used in public health messages to detect a cutaneous melanoma. We aimed to investigate the independent association of Breslow thickness with the melanoma diameter. METHODS A retrospective study was performed in patients with invasive melanomas of the nodular melanoma (NM) or superficial spreading melanoma (SSM) subtype. The quartiles of the diameter (lower, median, upper) were studied in non-parametric quantile regression model. RESULTS In total, 537 cases of invasive melanomas were included and 60% had Breslow thickness ≤1.0 mm. There were 429 SSM (79.9%) and 108 NM (20.1%). Although NMs were significantly thicker (median Breslow thickness: 2.7 mm vs. 0.7 mm, respectively, p < 0.0001), they were not associated with larger diameter compared to SSMs (p = 0.71). After adjustment for age and sex, melanoma location and subtype, having Breslow thickness ≤1.0 mm was not significantly associated with the lower quartile, median and upper quartile of the diameter (p values: 0.063, 0.083, and 0.791, respectively). CONCLUSION In our study including melanomas of the NM or SSM subtype, Breslow thickness was not associated with the diameter, adding evidence to support the limitations of using diameter larger than 6 mm for the detection of invasive melanomas and indicating the potential of smaller melanomas to be thicker tumors.
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Affiliation(s)
- Clio Dessinioti
- Skin Cancer and Melanoma Unit, 1st Department of Dermatology, A.Sygros Hospital, University of Athens, Athens, Greece
| | - Mihaella Plaka
- Skin Cancer and Melanoma Unit, 1st Department of Dermatology, A.Sygros Hospital, University of Athens, Athens, Greece
| | - Angelliki Befon
- Skin Cancer and Melanoma Unit, 1st Department of Dermatology, A.Sygros Hospital, University of Athens, Athens, Greece
- State Department of Dermatology, A.Sygros Hospital, Athens, Greece
| | - Dorothea Polidorou
- Skin Cancer and Melanoma Unit, 1st Department of Dermatology, A.Sygros Hospital, University of Athens, Athens, Greece
- State Department of Dermatology, A.Sygros Hospital, Athens, Greece
| | - Irene Stefanaki
- Skin Cancer and Melanoma Unit, 1st Department of Dermatology, A.Sygros Hospital, University of Athens, Athens, Greece
| | - Katerina Kypreou
- Skin Cancer and Melanoma Unit, 1st Department of Dermatology, A.Sygros Hospital, University of Athens, Athens, Greece
| | - Varvara Theology
- Department of Histopathology, A.Sygros Hospital, University of Athens, Athens, Greece
| | - Alexander J Stratigos
- Skin Cancer and Melanoma Unit, 1st Department of Dermatology, A.Sygros Hospital, University of Athens, Athens, Greece
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Huang HY, Hsiao YP, Karmakar R, Mukundan A, Chaudhary P, Hsieh SC, Wang HC. A Review of Recent Advances in Computer-Aided Detection Methods Using Hyperspectral Imaging Engineering to Detect Skin Cancer. Cancers (Basel) 2023; 15:5634. [PMID: 38067338 PMCID: PMC10705122 DOI: 10.3390/cancers15235634] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 11/20/2023] [Accepted: 11/24/2023] [Indexed: 08/15/2024] Open
Abstract
Skin cancer, a malignant neoplasm originating from skin cell types including keratinocytes, melanocytes, and sweat glands, comprises three primary forms: basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and malignant melanoma (MM). BCC and SCC, while constituting the most prevalent categories of skin cancer, are generally considered less aggressive compared to MM. Notably, MM possesses a greater capacity for invasiveness, enabling infiltration into adjacent tissues and dissemination via both the circulatory and lymphatic systems. Risk factors associated with skin cancer encompass ultraviolet (UV) radiation exposure, fair skin complexion, a history of sunburn incidents, genetic predisposition, immunosuppressive conditions, and exposure to environmental carcinogens. Early detection of skin cancer is of paramount importance to optimize treatment outcomes and preclude the progression of disease, either locally or to distant sites. In pursuit of this objective, numerous computer-aided diagnosis (CAD) systems have been developed. Hyperspectral imaging (HSI), distinguished by its capacity to capture information spanning the electromagnetic spectrum, surpasses conventional RGB imaging, which relies solely on three color channels. Consequently, this study offers a comprehensive exploration of recent CAD investigations pertaining to skin cancer detection and diagnosis utilizing HSI, emphasizing diagnostic performance parameters such as sensitivity and specificity.
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Affiliation(s)
- Hung-Yi Huang
- Department of Dermatology, Ditmanson Medical Foundation Chiayi Christian Hospital, Chia Yi City 60002, Taiwan;
| | - Yu-Ping Hsiao
- Department of Dermatology, Chung Shan Medical University Hospital, No.110, Sec. 1, Jianguo N. Rd., South District, Taichung City 40201, Taiwan;
- Institute of Medicine, School of Medicine, Chung Shan Medical University, No.110, Sec. 1, Jianguo N. Rd., South District, Taichung City 40201, Taiwan
| | - Riya Karmakar
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi City 62102, Taiwan; (R.K.); (A.M.)
| | - Arvind Mukundan
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi City 62102, Taiwan; (R.K.); (A.M.)
| | - Pramod Chaudhary
- Department of Aeronautical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai 600 062, India;
| | - Shang-Chin Hsieh
- Department of Plastic Surgery, Kaohsiung Armed Forces General Hospital, 2, Zhongzheng 1st. Rd., Lingya District, Kaohsiung 80284, Taiwan
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi City 62102, Taiwan; (R.K.); (A.M.)
- Department of Medical Research, Dalin Tzu Chi General Hospital, No. 2, Min-Sheng Rd., Dalin Town, Chia Yi City 62247, Taiwan
- Technology Development, Hitspectra Intelligent Technology Co., Ltd., Kaohsiung 80661, Taiwan
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11
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Lam GT, Martini C, Brooks T, Prabhakaran S, Hopkins AM, Ung BSY, Tang J, Caruso MC, Brooks RD, Johnson IRD, Sorvina A, Hickey SM, Karageorgos L, Klebe S, O’Leary JJ, Brooks DA, Logan JM. Insights into Melanoma Clinical Practice: A Perspective for Future Research. Cancers (Basel) 2023; 15:4631. [PMID: 37760601 PMCID: PMC10526186 DOI: 10.3390/cancers15184631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 08/30/2023] [Accepted: 09/18/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND Early diagnosis is the key to improving outcomes for patients with melanoma, and this requires a standardized histological assessment approach. The objective of this survey was to understand the challenges faced by clinicians when assessing melanoma cases, and to provide a perspective for future studies. METHODS Between April 2022 and February 2023, national and international dermatologists, pathologists, general practitioners, and laboratory managers were invited to participate in a six-question online survey. The data from the survey were assessed using descriptive statistics and qualitative responses. RESULTS A total of 54 responses were received, with a 51.4% (n = 28) full completion rate. Of the respondents, 96.4% reported ambiguity in their monthly melanoma diagnosis, and 82.1% routinely requested immunohistochemistry (IHC) testing to confirm diagnosis. SOX10 was the most frequently requested marker, and most respondents preferred multiple markers over a single marker. Diagnostic and prognostic tests, as well as therapeutic options and patient management, were all identified as important areas for future research. CONCLUSIONS The respondents indicated that the use of multiple IHC markers is essential to facilitate diagnostic accuracy in melanoma assessment. Survey responses indicate there is an urgent need to develop new biomarkers for clinical decision making at multiple critical intervention points.
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Affiliation(s)
- Giang T. Lam
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
| | - Carmela Martini
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
| | - Tiffany Brooks
- Adelaide Medical School, University of Adelaide, North Terrace, Adelaide, SA 5000, Australia
- Aware Women’s Health Private Clinic, Adelaide, SA 5006, Australia
| | - Sarita Prabhakaran
- College of Medicine and Public Health, Flinders University, Adelaide, SA 5042, Australia
| | - Ashley M. Hopkins
- College of Medicine and Public Health, Flinders University, Adelaide, SA 5042, Australia
| | - Ben S.-Y. Ung
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
| | - Jingying Tang
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
| | - Maria C. Caruso
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
| | - Robert D. Brooks
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
| | - Ian R. D. Johnson
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
| | - Alexandra Sorvina
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
| | - Shane M. Hickey
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
| | - Litsa Karageorgos
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
| | - Sonja Klebe
- College of Medicine and Public Health, Flinders University, Adelaide, SA 5042, Australia
- Department of Surgical Pathology, SA Pathology at Flinders Medical Centre, Adelaide, SA 5042, Australia
| | - John J. O’Leary
- Department of Histopathology, Trinity College Dublin, D02 PN40 Dublin, Ireland
| | - Douglas A. Brooks
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
- Department of Histopathology, Trinity College Dublin, D02 PN40 Dublin, Ireland
| | - Jessica M. Logan
- Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA 5000, Australia
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12
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Dessinioti C, Tsiakou A, Christodoulou A, Stratigos AJ. Clinical and Dermoscopic Findings of Nevi after Photoepilation: A Review. Life (Basel) 2023; 13:1832. [PMID: 37763236 PMCID: PMC10532922 DOI: 10.3390/life13091832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/21/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023] Open
Abstract
Atypical clinical and dermoscopic findings, or changes in pigmented melanocytic lesions located on body areas treated with lasers or intense pulsed light (IPL) for hair removal (photoepilation), have been described in the literature. There are three prospective studies in a total of 79 individuals with 287 melanocytic nevi and several case reports reporting the dermoscopic findings and changes after photoepilation. Clinical changes have been reported in 20-100% of individuals, while dermoscopic changes have been observed in 48% to 93% of nevi. More frequent dermoscopic changes included bleaching, the development of pigmented globules, and irregular hyperpigmented areas and regression structures, including gray areas, gray dots/globules, and whitish structureless areas. The diagnostic approach for pigmented lesions with atypical dermoscopic findings and changes after photo-epilation included reflectance confocal microscopy, sequential digital dermoscopy follow-up, and/or excision and histopathology. Challenges pertaining to these diagnostic steps in the context of photoepilation include the detection of findings that may warrant a biopsy to exclude melanoma (ugly duckling, irregular hyperpigmented areas, blue-gray or white areas, and loss of pigment network), the potential persistence of changes at follow-up, and that a histopathologic diagnosis may not be possible due to the distortion of melanocytes or complete regression of the lesion. Furthermore, these diagnostic approaches can be time-consuming, require familiarization of the physician with dermoscopic features, may cause anxiety to the individual, and highlight that avoiding passes of the laser or IPL devices over pigmented lesions is key.
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Affiliation(s)
- Clio Dessinioti
- 1st Department of Dermatology-Venereology, Andreas Sygros Hospital, National and Kapodistrian University of Athens, 16121 Athens, Greece
| | - Andriani Tsiakou
- State Department of Dermatology-Venereology, Andreas Sygros Hospital, 16121 Athens, Greece
| | - Athina Christodoulou
- 1st Department of Dermatology-Venereology, Andreas Sygros Hospital, National and Kapodistrian University of Athens, 16121 Athens, Greece
| | - Alexander J. Stratigos
- 1st Department of Dermatology-Venereology, Andreas Sygros Hospital, National and Kapodistrian University of Athens, 16121 Athens, Greece
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13
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Choudhari J, Nimma R, Nimal SK, Totakura Venkata SK, Kundu GC, Gacche RN. Prosopis juliflora (Sw.) DC phytochemicals induce apoptosis and inhibit cell proliferation signaling pathways, EMT, migration, invasion, angiogenesis and stem cell markers in melanoma cell lines. JOURNAL OF ETHNOPHARMACOLOGY 2023; 312:116472. [PMID: 37062530 DOI: 10.1016/j.jep.2023.116472] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 05/08/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Prosopis juliflora (Sw.), DC is a xerophytic plant species that extensively grow in Asia, Africa, Australia, and Brazil. From ancient time P. juliflora is being utilized in various folk remedies for example in wound healing, fever, inflammation, measles, excrescences, diarrhea and dysentery. Traditionally, gum, paste, and smoke obtained from the leaves and pods are applied for anticancer, antidiabetic, anti-inflammatory, and antimicrobial purposes. AIM OF THE STUDY Our previous studies have demonstrated the promising potential of Prosopis Juliflora leaves methanol extract (PJLME) against breast cancer, and suggested its possible integration as a complementary medicine for the effective management of breast cancer. However, evidence against how PJLME mechanistically target the cancer proliferative pathways and other targets is poorly understood. The basic aim of the present study was to understand the anti-melanoma potential of PJLME against B16f10 cells with possible mechanisms of action. MATERIALS AND METHODS MTT assay was used to determine cell viability. Wound and transwell migration assay was performed to check migration potential of cells after PJLME treatment, while clonogenic assay was carried out to understand its colony inhibition actvity. Flow cytometry was used to perform annexin V/PI assay (apoptosis assay), ROS assay, cell cycle analysis. In-vitro angiogenesis assay was performed to check formation of capillary like vascular structure after PJLME treatment. Apoptotic genes, signaling pathways markers, EMT markers and stem cell markers were determined by western blotting. In-vivo BALB/C mice xenograft model study was performed to check the effect of PJLME on in-vivo melanoma tumor growth. RESULTS The experimental outcome of the present study has clearly demonstrated the inhibition of growth, migration, invasion, colony formation and apoptosis inducing potential of PJLME against mouse melanoma cancer cells. Treatment of B16F10 melanoma cells with PJLME resulted in arrest of cell cycle at G0/G1 phase. Annexin V-FITC/PI assay confirmed the apoptosis inducing potential of PJLME in B16F10 and A375 melanoma cells. Furthermore, Western blot experiments confirmed that the treatment of PJLME downregulates the expression of anti-apoptotic gene like Bcl2 and increase the expression profile of pro-apoptotic genes like Bax, Bad, and Bak in B16F10 melanoma cells. HUVEC (Human umbilical vein endothelial cells) tube formation assay clearly demonstrated the anti-angiogenic potential of PJLME. The study also revealed that PJLME has potential to inhibit the Akt and Erk signaling pathways which are participating in cancer cell proliferation, migration, invasion etc. The outcome of qRT-PCR and immunoblotting analysis clearly unveiled that PJLME treatment leads to downregulation of epithelial-mesenchymal transition (EMT) as well as stem cell markers. Finally, the in-vivo animal xenograft model study also revealed the anti-melanoma potential of PJLME by significantly inhibiting the B16F10 melanoma tumor growth in BALB/c mice model. The LC-ESI-MS/MS analysis of PJLME showed the presence of variety of bioactive molecules associated with anticancer effects. CONCLUSION The outcome of the present investigation clearly demonstrated the anti-melanoma potential of PJLME against B16f10 melanoma cells. PJLME can be explored as an adjuvant or complementary therapy against melanoma cancer, however further studies are required to understand the clinical efficacy of PJLME. Nevertheless, it can be further explored as a promising resource for identification of novel anticancer candidate drug.
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Affiliation(s)
- Jasoda Choudhari
- Department of Biotechnology, Savitribai Phule Pune University, Pune, 411007, MS, India
| | | | - Snehal K Nimal
- Department of Biotechnology, Savitribai Phule Pune University, Pune, 411007, MS, India
| | | | - Gopal C Kundu
- National Centre for Cell Science, Pune, 411007, India; School of Biotechnology, KIIT Deemed University, Bhubaneswar, 751 024, India
| | - Rajesh N Gacche
- Department of Biotechnology, Savitribai Phule Pune University, Pune, 411007, MS, India.
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14
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Khan MA, Akram T, Zhang Y, Alhaisoni M, Al Hejaili A, Shaban KA, Tariq U, Zayyan MH. SkinNet‐ENDO: Multiclass skin lesion recognition using deep neural network and Entropy‐Normal distribution optimization algorithm with ELM. INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY 2023; 33:1275-1292. [DOI: 10.1002/ima.22863] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/31/2023] [Indexed: 08/25/2024]
Abstract
AbstractThe early diagnosis of skin cancer through clinical methods reduces the human mortality rate. The manual screening of dermoscopic images is not an efficient procedure; therefore, researchers working in the domain of computer vision employed several algorithms to classify the skin lesion. The existing computerized methods have a few drawbacks, such as low accuracy and high computational time. Therefore, in this work, we proposed a novel deep learning and Entropy‐Normal Distribution Optimization Algorithm with extreme learning machine (NDOEM)‐based architecture for multiclass skin lesion classification. The proposed architecture consists of five fundamental steps. In the first step, two contrast enhancement techniques including hybridization of mathematical formulation and convolutional neural network are implemented prior to data augmentation. In the second step, two pre‐trained deep learning models, EfficientNetB0 and DarkNet19, are fine‐tuned and retrained through the transfer learning. In the third step, features are extracted from the fine‐tuned models and later the most discriminant features are selected based on novel Entropy‐NDOELM algorithm. The selected features are finally fused using a parallel correlation technique in the fourth step to generate the result feature vectors. Finally, the resultant features are again down‐sampled using the proposed algorithm and the resultant features are passed to the extreme learning machine (ELM) for the final classification. The simulations are conducted on three publicly available datasets as HAM10000, ISIC2018, and ISIC2019 to achieving an accuracy of 95.7%, 96.3%, and 94.8% respectively.
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Affiliation(s)
- Muhammad Attique Khan
- Department of Computer Science HITEC University Taxila Pakistan
- Department of Informatics University of Leicester Leicester UK
| | - Tallha Akram
- Department of Electrical and Computer Engineering COMSATS University Islamabad Wah Campus Pakistan
| | - Yu‐Dong Zhang
- Department of Informatics University of Leicester Leicester UK
| | - Majed Alhaisoni
- Computer Sciences Department, College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh Saudi Arabia
| | - Abdullah Al Hejaili
- Faculty of Computers & Information Technology, Computer Science Department University of Tabuk Tabuk Saudi Arabia
| | - Khalid Adel Shaban
- Computer Science Department, College of Computing and Informatics Saudi Electronic University Ryiadh Saudi Arabia
| | - Usman Tariq
- Department of Management Information Systems College of Business Administration, Prince Sattam Bin Abdulaziz University Al‐Kharj Saudi Arabia
| | - Muhammad H. Zayyan
- Computer Science Department, Faculty of Computers and Information Sciences Mansoura University Mansoura Egypt
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15
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Michalkova R, Mirossay L, Kello M, Mojzisova G, Baloghova J, Podracka A, Mojzis J. Anticancer Potential of Natural Chalcones: In Vitro and In Vivo Evidence. Int J Mol Sci 2023; 24:10354. [PMID: 37373500 DOI: 10.3390/ijms241210354] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 06/12/2023] [Accepted: 06/17/2023] [Indexed: 06/29/2023] Open
Abstract
There is no doubt that significant progress has been made in tumor therapy in the past decades. However, the discovery of new molecules with potential antitumor properties still remains one of the most significant challenges in the field of anticancer therapy. Nature, especially plants, is a rich source of phytochemicals with pleiotropic biological activities. Among a plethora of phytochemicals, chalcones, the bioprecursors of flavonoid and isoflavonoids synthesis in higher plants, have attracted attention due to the broad spectrum of biological activities with potential clinical applications. Regarding the antiproliferative and anticancer effects of chalcones, multiple mechanisms of action including cell cycle arrest, induction of different forms of cell death and modulation of various signaling pathways have been documented. This review summarizes current knowledge related to mechanisms of antiproliferative and anticancer effects of natural chalcones in different types of malignancies including breast cancers, cancers of the gastrointestinal tract, lung cancers, renal and bladder cancers, and melanoma.
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Affiliation(s)
- Radka Michalkova
- Department of Pharmacology, Faculty of Medicine, Pavol Jozef Šafárik University, 040 01 Košice, Slovakia
| | - Ladislav Mirossay
- Department of Pharmacology, Faculty of Medicine, Pavol Jozef Šafárik University, 040 01 Košice, Slovakia
| | - Martin Kello
- Department of Pharmacology, Faculty of Medicine, Pavol Jozef Šafárik University, 040 01 Košice, Slovakia
| | - Gabriela Mojzisova
- Center of Clinical and Preclinical Research MEDIPARK, Faculty of Medicine, Pavol Jozef Šafárik University, 040 01 Košice, Slovakia
| | - Janette Baloghova
- Department of Dermatovenerology, Faculty of Medicine, Pavol Jozef Šafárik University, 040 01 Košice, Slovakia
| | - Anna Podracka
- Department of Dermatovenerology, Faculty of Medicine, Pavol Jozef Šafárik University, 040 01 Košice, Slovakia
| | - Jan Mojzis
- Department of Pharmacology, Faculty of Medicine, Pavol Jozef Šafárik University, 040 01 Košice, Slovakia
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16
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Marrone M, Caterino C, Musci G, Cazzato G, Ingravallo G, Lupo C, Casatta N, Stellacci A, Armenio A. Photography as the Sole Means of Proof: Medical Liability in Dermatology. Diagnostics (Basel) 2023; 13:diagnostics13061033. [PMID: 36980340 PMCID: PMC10047858 DOI: 10.3390/diagnostics13061033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 02/25/2023] [Accepted: 03/07/2023] [Indexed: 03/12/2023] Open
Abstract
Malignant melanoma is a cutaneous malignancy resulting from the uncontrolled proliferation of melanocytes and poses a challenge diagnostically because neoplastic lesions can mimic benign lesions, which are much more common in the population. Doctors, when they suspect the presence of melanoma, arrange for its removal and the performance of a histological examination to ascertain its diagnosis; in cases where the dermatoscopic examination is indicative of benignity, however, after the lesion is removed, histological examination is not always performed, a very dangerous occurrence and a harbinger of further medico-legal problems. The authors present a court litigation case of an “alleged” failure to diagnose malignant melanoma in a patient who died of brain metastases from melanoma in the absence of a certain location of the primary tumor: the physician who had removed a benign lesion a few months earlier was sued, and only thanks to the presence of photographic documentation was the health care provider able to prove his extraneousness. The aim of this paper is to formulate a proposal for a dermatological protocol to be followed in cases of excisions of benign skin lesions with a twofold purpose: on the one hand, to be able to prove, in a judicial context, the right action on the part of the sanitarians; on the other hand, to avoid the rise of so-called “defensive medicine”.
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Affiliation(s)
- Maricla Marrone
- Section of Legal Medicine, Department of Interdisciplinary Medicine (DIM), University of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Cristina Caterino
- Section of Legal Medicine, Department of Interdisciplinary Medicine (DIM), University of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Gianluca Musci
- Section of Legal Medicine, Department of Interdisciplinary Medicine (DIM), University of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Gerardo Cazzato
- Section of Molecular Pathology, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari “Aldo Moro”, 70124 Bari, Italy
- Correspondence: ; Tel.: +39-3405203641
| | - Giuseppe Ingravallo
- Section of Molecular Pathology, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Carmelo Lupo
- Innovation Department, Diapath S.p.A., Via Savoldini n.71, 24057 Martinengo, Italy
| | - Nadia Casatta
- Innovation Department, Diapath S.p.A., Via Savoldini n.71, 24057 Martinengo, Italy
| | - Alessandra Stellacci
- Section of Legal Medicine, Department of Interdisciplinary Medicine (DIM), University of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Andrea Armenio
- Plastic Surgery Department, IRCCS Istituto Tumori “Giovanni Paolo II”, V.le O. Flacco, 65, 70124 Bari, Italy
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17
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Halo Nevi in the Pediatric Population. JOURNAL OF THE DERMATOLOGY NURSES' ASSOCIATION 2023. [DOI: 10.1097/jdn.0000000000000719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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18
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A comprehensive analysis of dermoscopy images for melanoma detection via deep CNN features. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104186] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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19
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Hum YC, Tan HR, Tee YK, Yap WS, Tan TS, Salim MIM, Lai KW. The development of skin lesion detection application in smart handheld devices using deep neural networks. MULTIMEDIA TOOLS AND APPLICATIONS 2022; 81:41579-41610. [DOI: 10.1007/s11042-021-11013-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 04/29/2021] [Accepted: 05/05/2021] [Indexed: 07/26/2024]
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20
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Liu S, Fan Y, Li K, Zhang H, Wang X, Ju R, Huang L, Duan M, Zhou F. Integration of lncRNAs, Protein-Coding Genes and Pathology Images for Detecting Metastatic Melanoma. Genes (Basel) 2022; 13:genes13101916. [PMID: 36292801 PMCID: PMC9602061 DOI: 10.3390/genes13101916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/16/2022] [Accepted: 10/18/2022] [Indexed: 11/04/2022] Open
Abstract
Melanoma is a lethal skin disease that develops from moles. This study aimed to integrate multimodal data to predict metastatic melanoma, which is highly aggressive and difficult to treat. The proposed EnsembleSKCM method evaluated the prediction performances of long noncoding RNAs (lncRNAs), protein-coding messenger genes (mRNAs) and pathology images (images) for metastatic melanoma. Feature selection was used to screen for metastatic biomarkers in the lncRNA and mRNA datasets. The integrated EnsembleSKCM model was built based on the weighted results of the lncRNA-, mRNA- and image-based models. EnsembleSKCM achieved 0.9444 in the prediction accuracy of metastatic melanoma and outperformed the single-modal prediction models based on the lncRNA, mRNA and image data. The experimental data suggest the importance of integrating the complementary information from the three data modalities. WGCNA was used to analyze the relationship of molecular-level features and image features, and the results show connections between them. Another cohort was used to validate our prediction.
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Affiliation(s)
- Shuai Liu
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
| | - Yusi Fan
- College of Software, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
| | - Kewei Li
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
| | - Haotian Zhang
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
| | - Xi Wang
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
| | - Ruofei Ju
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
| | - Lan Huang
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
| | - Meiyu Duan
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
| | - Fengfeng Zhou
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
- Correspondence: ; Tel./Fax: +86-431-8516-6024
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21
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Evaluating a game-based randomized experiment to increase melanoma identification among adults living in the U.S. Soc Sci Med 2022; 310:115281. [PMID: 36001916 DOI: 10.1016/j.socscimed.2022.115281] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 07/26/2022] [Accepted: 08/09/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND Although cutaneous melanoma diagnoses are rising, morbidity and mortality can be reduced through early detection. This investigation seeks to improve melanoma identification accuracy, attitudes, and intentions among a lay population by comparing the effectiveness of different melanoma identification training strategies and the effect of real-time decisional feedback on a melanoma identification task. We developed an innovative, game-based approach and hypothesize differences among frequently used melanoma identification training modalities (i.e, the Asymmetry/Border/Color/Diameter [ABCD] rule, the Ugly Duckling Rule [UDS], and a modality that combines them both, ABCDF (where the F stands for 'funny looking"), and investigate differences in types of immediate feedback on a melanoma identification task. METHODS We conducted a national online randomized experiment to test a 4 (melanoma training strategies: ABCD, UDS, ABCD-F, control) × 3 (feedback: Dermatological, Dermatological + Motivational, control) factorial design on melanoma identification, skin cancer beliefs (perceived susceptibility, severity, response efficacy, self-efficacy), attitudes, and prevention intentions. RESULTS ABCD training (p < .001) and UDS training (p = .05) resulted in significantly higher melanoma identification than the control. All training types resulted in significantly higher self-efficacy than the control (p = .02). Both Dermatological (p = .02) and Dermatological + Motivational feedback (p = .01) elicited significantly lower melanoma identification than the control condition, although this effect may be due to differences observed among participants who received UDS training. There was a significant main effect of feedback on self-efficacy (p = .002), where both Dermatological and Dermatological + Motivational feedback elicited higher levels of self-efficacy than the control. CONCLUSIONS Our results suggest that game-based ABCD and UDS training strategies could increase melanoma identification accuracy. Real-time feedback reduced accuracy, but was associated with increased self-efficacy related to melanoma detection outcomes.
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22
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Assessing the impact of color blindness on the ability of identifying benign and malignant skin lesions by naked-eye examination. PLoS One 2022; 17:e0270487. [PMID: 35921375 PMCID: PMC9348688 DOI: 10.1371/journal.pone.0270487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 06/10/2022] [Indexed: 12/02/2022] Open
Abstract
Background Color vision deficiency describes the inability to distinguish certain shades of color. The aim of this study was to assess the impact of having color vision deficiency on the accuracy of distinguishing benign and malignant skin lesions by naked-eye examination. Methods This was a cross-sectional study conducted during the period August 2020 to February 2021. We randomly selected a total of 20 nevi and 20 melanoma images from an open access image database. The 40 images were divided into four sets of images, each set contained 5 benign and 5 malignant skin lesion images simulated as if they were seen by a protanope physician, deuteranope physician, tritanope physician, and a set of images presented without simulation. In an online survey, students who were in their final year of medical school or had newly graduated were asked to diagnose each image as benign or malignant. Results A total of 140 participants were included with a mean (SD) age of 24.88 (1.51). We found a significantly higher mean accuracy for non-simulated images compared to deuteranope simulated images (p< 0.001, mean difference = 11.07, 95% CI 8.40 to 13.74). We did not find a significant difference in accuracy classification for protanope simulated images (p = 0.066), nor for tritanope simulated images (p = 0.315). Classification accuracy for malignant lesions was higher than classification accuracy for benign lesions, with the highest difference belonging to deuteranope simulated images, with a difference in mean accuracy of classifying malignant lesions by 32.2 (95% CI 27.0 to 37.6). Conclusion Deuteranope participants (i.e., green color deficiency) had a significantly lower accuracy of distinguishing pigmented skin lesions as benign or malignant, an impact not found for other color vision deficiencies, which was mainly for misdiagnosing benign lesions as malignant.
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A Novel Approach for the Shape Characterisation of Non-Melanoma Skin Lesions Using Elliptic Fourier Analyses and Clinical Images. J Clin Med 2022; 11:jcm11154392. [PMID: 35956008 PMCID: PMC9369039 DOI: 10.3390/jcm11154392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 07/23/2022] [Accepted: 07/27/2022] [Indexed: 12/07/2022] Open
Abstract
The early detection of Non-Melanoma Skin Cancer (NMSC) is crucial to achieve the best treatment outcomes. Shape is considered one of the main parameters taken for the detection of some types of skin cancer such as melanoma. For NMSC, the importance of shape as a visual detection parameter is not well-studied. A dataset of 993 standard camera images containing different types of NMSC and benign skin lesions was analysed. For each image, the lesion boundaries were extracted. After an alignment and scaling, Elliptic Fourier Analysis (EFA) coefficients were calculated for the boundary of each lesion. The asymmetry of lesions was also calculated. Then, multivariate statistics were employed for dimensionality reduction and finally computational learning classification was employed to evaluate the separability of the classes. The separation between malignant and benign samples was successful in most cases. The best-performing approach was the combination of EFA coefficients and asymmetry. The combination of EFA and asymmetry resulted in a balanced accuracy of 0.786 and an Area Under Curve of 0.735. The combination of EFA and asymmetry for lesion classification resulted in notable success rates when distinguishing between benign and malignant lesions. In light of these results, skin lesions’ shape should be integrated as a fundamental part of future detection techniques in clinical screening.
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Kulcsarova K, Baloghova J, Necpal J, Skorvanek M. Skin Conditions and Movement Disorders: Hiding in Plain Sight. Mov Disord Clin Pract 2022; 9:566-583. [PMID: 35844274 PMCID: PMC9274368 DOI: 10.1002/mdc3.13436] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 02/17/2022] [Accepted: 03/07/2022] [Indexed: 11/09/2022] Open
Abstract
Skin manifestations are well-recognized non-motor symptoms of Parkinson's disease (PD) and other hypokinetic and hyperkinetic movement disorders. Skin conditions are usually well visible during routine clinical examination and their recognition may play a major role in diagnostic work-up. In this educational review we: (1) briefly outline skin conditions related to Parkinson's disease, including therapy-related skin complications and their management; (2) discuss the role of skin biopsies in early diagnosis of PD and differential diagnosis of parkinsonian syndromes; and focus more on areas which have not been reviewed in the literature before, including (3) skin conditions related to atypical parkinsonism, and (4) skin conditions related to hyperkinetic movement disorders. In case of rare hyperkinetic movement disorders, specific dermatological manifestations, like presence of angiokeratomas, telangiectasias, Mongolian spots, lipomas, ichthyosis, progeroid skin changes and others may point to a very specific group of disorders and help guide further investigations.
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Affiliation(s)
- Kristina Kulcsarova
- Department of Neurology, Medical FacultyUniversity of Pavol Jozef SafarikPavolSlovak Republic
- Department of NeurologyUniversity Hospital L. PasteurKosiceSlovak Republic
| | - Janette Baloghova
- Department of DermatovenerologyMedical Faculty, University of Pavol Jozef SafarikKosiceSlovak Republic
- Department of DermatovenerologyUniversity Hospital L. PasteurKosiceSlovak Republic
| | - Jan Necpal
- Department of NeurologyZvolen HospitalZvolenSlovak Republic
| | - Matej Skorvanek
- Department of Neurology, Medical FacultyUniversity of Pavol Jozef SafarikPavolSlovak Republic
- Department of NeurologyUniversity Hospital L. PasteurKosiceSlovak Republic
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25
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Liu C, Ding X, Wei C, Pei Y, Meng F, Zhong Y, Liu Y. LncRNA LNCOC1 is Upregulated in Melanoma and Serves as a Potential Regulatory Target of miR-124 to Suppress Cancer Cell Invasion and Migration. CLINICAL, COSMETIC AND INVESTIGATIONAL DERMATOLOGY 2022; 15:751-762. [PMID: 35502349 PMCID: PMC9056108 DOI: 10.2147/ccid.s359786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 04/12/2022] [Indexed: 12/24/2022]
Abstract
Background A cascade of genes and pathways have been reported in the precise regulation of malignant melanoma (MM). Previous study has demonstrated that lncRNA LNCOC1 is an oncogenic factor in the pathogenesis and development of various cancers. The present study explored the functionalities of LNCOC1 and its interactions with miR-124 in MM. Methods A total of 65 melanoma patients were enrolled in this study. The expression of LNCOC1 and miR-124 after cell transfection were detected by RT-qPCR. The migration rates of SK-MEL-3 and A375 cells after transient transfection with LNCOC1 expression vector and miR-124 mimic was detected by trans-well assay. Results LNCOC1 was accumulated to high levels in melanoma, and it was significantly correlated with the low survival rate of melanoma patients. Our bioinformatics data showed that miR-124 could target LNCOC1. Overexpression of miR-124 could downregulate LNCOC1. However, up-regulated the expression of LNCOC1 did not affect the expression of miR-124. Our correlation analysis also revealed that the expression of LNCOC1 and miR-124 were inversely correlated in both melanoma tissues and non-tumor tissues. The trans-well invasion and migration assays indicated that overexpression of miR-124 inhibited the melanoma cell invasion and migration. However, overexpression of LNCOC1 promoted melanoma cell invasion and migration. Conclusion LNCOC1 is upregulated in melanoma, which can be considered as a potential target of miR-124 in modulating melanoma cell invasion and migration. LNCOC1 may also be an interfering target of MM therapy.
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Affiliation(s)
- Changhai Liu
- Department of Burn and Plastic Surgery, The First Affiliated of Hospital of Kangda College of Nanjing Medical University/The First People's Hospital of Lianyungang, Lianyungang, People's Republic of China
| | - Xiangsheng Ding
- Department of Burn and Plastic Surgery, The First Affiliated of Hospital of Kangda College of Nanjing Medical University/The First People's Hospital of Lianyungang, Lianyungang, People's Republic of China
| | - Cuie Wei
- Department of Burn and Plastic Surgery, The First Affiliated of Hospital of Kangda College of Nanjing Medical University/The First People's Hospital of Lianyungang, Lianyungang, People's Republic of China
| | - Yongdong Pei
- Department of Burn and Plastic Surgery, The First Affiliated of Hospital of Kangda College of Nanjing Medical University/The First People's Hospital of Lianyungang, Lianyungang, People's Republic of China
| | - Fanjun Meng
- Department of Burn and Plastic Surgery, The First Affiliated of Hospital of Kangda College of Nanjing Medical University/The First People's Hospital of Lianyungang, Lianyungang, People's Republic of China
| | - Yuren Zhong
- Department of Burn and Plastic Surgery, The First Affiliated of Hospital of Kangda College of Nanjing Medical University/The First People's Hospital of Lianyungang, Lianyungang, People's Republic of China
| | - Yi Liu
- Department of Burn Plastic Surgery and Wound Repair, Second Hospital of Lanzhou University, Lanzhou, People's Republic of China
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Martin-Gonzalez M, Azcarraga C, Martin-Gil A, Carpena-Torres C, Jaen P. Efficacy of a Deep Learning Convolutional Neural Network System for Melanoma Diagnosis in a Hospital Population. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19073892. [PMID: 35409575 PMCID: PMC8997631 DOI: 10.3390/ijerph19073892] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 03/19/2022] [Accepted: 03/21/2022] [Indexed: 02/04/2023]
Abstract
(1) Background: The purpose of this study was to evaluate the efficacy in terms of sensitivity, specificity, and accuracy of the quantusSKIN system, a new clinical tool based on deep learning, to distinguish between benign skin lesions and melanoma in a hospital population. (2) Methods: A retrospective study was performed using 232 dermoscopic images from the clinical database of the Ramón y Cajal University Hospital (Madrid, Spain). The skin lesions images, previously diagnosed as nevus (n = 177) or melanoma (n = 55), were analyzed by the quantusSKIN system, which offers a probabilistic percentage (diagnostic threshold) for melanoma diagnosis. The optimum diagnostic threshold, sensitivity, specificity, and accuracy of the quantusSKIN system to diagnose melanoma were quantified. (3) Results: The mean diagnostic threshold was statistically lower (p < 0.001) in the nevus group (27.12 ± 35.44%) compared with the melanoma group (72.50 ± 34.03%). The area under the ROC curve was 0.813. For a diagnostic threshold of 67.33%, a sensitivity of 0.691, a specificity of 0.802, and an accuracy of 0.776 were obtained. (4) Conclusions: The quantusSKIN system is proposed as a useful screening tool for melanoma detection to be incorporated in primary health care systems.
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Affiliation(s)
- Manuel Martin-Gonzalez
- Service of Dermatology, Hospital Universitario Ramón y Cajal, 28034 Madrid, Spain; (C.A.); (P.J.)
- Instituto Ramón y Cajal de Investigación Sanitaria, 28034 Madrid, Spain
- Correspondence:
| | - Carlos Azcarraga
- Service of Dermatology, Hospital Universitario Ramón y Cajal, 28034 Madrid, Spain; (C.A.); (P.J.)
| | - Alba Martin-Gil
- Ocupharm Research Group, Department of Optometry and Vision, Faculty of Optics and Optometry, Complutense University of Madrid, 28037 Madrid, Spain; (A.M.-G.); (C.C.-T.)
| | - Carlos Carpena-Torres
- Ocupharm Research Group, Department of Optometry and Vision, Faculty of Optics and Optometry, Complutense University of Madrid, 28037 Madrid, Spain; (A.M.-G.); (C.C.-T.)
| | - Pedro Jaen
- Service of Dermatology, Hospital Universitario Ramón y Cajal, 28034 Madrid, Spain; (C.A.); (P.J.)
- Instituto Ramón y Cajal de Investigación Sanitaria, 28034 Madrid, Spain
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Abstract
Because many skin lesions and disorders can appear similar, primary care clinicians often struggle to diagnose them definitively without histopathologic information obtained from a biopsy. This review article explains how to decide whether a lesion should be biopsied and what type of biopsy technique to use and then outlines the stepwise approach to each of the most common skin biopsy techniques: shave, saucerization, punch, fusiform, and subcutaneous nodule biopsies. Finally, potential pitfalls and complications are discussed so the clinician can avoid those and can provide a cosmetically acceptable result from these common outpatient procedures.
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Affiliation(s)
- Jason D Greenwood
- Department of Family Medicine, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - Stephen P Merry
- Department of Family Medicine, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - Christopher L Boswell
- Department of Family Medicine, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA.
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28
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Rojas KD, Perez ME, Marchetti MA, Nichols AJ, Penedo FJ, Jaimes N. Skin Cancer: Primary, Secondary, and Tertiary Prevention. Part II. J Am Acad Dermatol 2022; 87:271-288. [DOI: 10.1016/j.jaad.2022.01.053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 01/12/2022] [Accepted: 01/26/2022] [Indexed: 10/19/2022]
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29
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Skin Tumors. Fam Med 2022. [DOI: 10.1007/978-3-030-54441-6_149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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30
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Newcomer K, Robbins KJ, Perone J, Hinojosa FL, Chen D, Jones S, Kaufman CK, Weiser R, Fields RC, Tyler DS. Malignant melanoma: evolving practice management in an era of increasingly effective systemic therapies. Curr Probl Surg 2022; 59:101030. [PMID: 35033317 PMCID: PMC9798450 DOI: 10.1016/j.cpsurg.2021.101030] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 05/12/2021] [Indexed: 01/03/2023]
Affiliation(s)
- Ken Newcomer
- Department of Surgery, Barnes-Jewish Hospital, Washington University, St. Louis, MO
| | | | - Jennifer Perone
- Department of Surgery, University of Texas Medical Branch, Galveston, TX
| | | | - David Chen
- e. Department of Medicine, Washington University, St. Louis, MO
| | - Susan Jones
- f. Department of Pediatrics, Washington University, St. Louis, MO
| | | | - Roi Weiser
- University of Texas Medical Branch, Galveston, TX
| | - Ryan C Fields
- Department of Surgery, Washington University, St. Louis, MO
| | - Douglas S Tyler
- Department of Surgery, University of Texas Medical Branch, Galveston, TX.
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31
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Ji X, Castellino SM, Mertens AC, Zhao J, Nogueira L, Jemal A, Yabroff KR, Han X. Association of Medicaid Expansion With Cancer Stage and Disparities in Newly Diagnosed Young Adults. J Natl Cancer Inst 2021; 113:1723-1732. [PMID: 34021352 PMCID: PMC9989840 DOI: 10.1093/jnci/djab105] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 03/22/2021] [Accepted: 05/19/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Young adults (YAs) experience higher uninsurance rates and more advanced stage at cancer diagnosis than older counterparts. We examined the association of the Affordable Care Act Medicaid expansion with insurance coverage and stage at diagnosis among YAs newly diagnosed with cancer. METHODS Using the National Cancer Database, we identified 309 413 YAs aged 18-39 years who received a first cancer diagnosis in 2011-2016. Outcomes included percentages of YAs without health insurance at diagnosis, with stage I (early-stage) diagnoses, and with stage IV (advanced-stage) diagnoses. We conducted difference-in-difference (DD) analyses to examine outcomes before and after states implemented Medicaid expansion compared with nonexpansion states. All statistical tests were 2-sided. RESULTS The percentage of uninsured YAs decreased more in expansion than nonexpansion states (adjusted DD = -1.0 percentage points [ppt], 95% confidence interval [CI] = -1.4 to -0.7 ppt, P < .001). The overall percentage of stage I diagnoses increased (adjusted DD = 1.4 ppt, 95% CI = 0.6 to 2.2 ppt, P < .001) in expansion compared with nonexpansion states, with greater improvement among YAs in rural areas (adjusted DD = 7.2 ppt, 95% CI = 0.2 to 14.3 ppt, P = .045) than metropolitan areas (adjusted DD = 1.3 ppt, 95% CI = 0.4 to 2.2 ppt, P = .004) and among non-Hispanic Black patients (adjusted DD = 2.2 ppt, 95% CI = -0.03 to 4.4 ppt, P = .05) than non-Hispanic White patients (adjusted DD = 1.4 ppt, 95% CI = 0.4 to 2.3 ppt, P = .008). Despite the non-statistically significant change in stage IV diagnoses overall, the percentage declined more (adjusted DD = -1.2 ppt, 95% CI = -2.2 to -0.2 ppt, P = .02) among melanoma patients in expansion relative to nonexpansion states. CONCLUSIONS We provide the first evidence, to our knowledge, on the association of Medicaid expansion with shifts to early-stage cancer at diagnosis and a narrowing of rural-urban and Black-White disparities in YA cancer patients.
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Affiliation(s)
- Xu Ji
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.,Aflac Cancer and Blood Disorders Center, Children's Healthcare of Atlanta, Atlanta, GA, USA
| | - Sharon M Castellino
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.,Aflac Cancer and Blood Disorders Center, Children's Healthcare of Atlanta, Atlanta, GA, USA
| | - Ann C Mertens
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.,Aflac Cancer and Blood Disorders Center, Children's Healthcare of Atlanta, Atlanta, GA, USA.,Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Jingxuan Zhao
- Surveillance and Health Equity Science, American Cancer Society, Atlanta, GA, USA
| | - Leticia Nogueira
- Surveillance and Health Equity Science, American Cancer Society, Atlanta, GA, USA
| | - Ahmedin Jemal
- Surveillance and Health Equity Science, American Cancer Society, Atlanta, GA, USA
| | - K Robin Yabroff
- Surveillance and Health Equity Science, American Cancer Society, Atlanta, GA, USA
| | - Xuesong Han
- Surveillance and Health Equity Science, American Cancer Society, Atlanta, GA, USA
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32
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Matias M, Pinho JO, Penetra MJ, Campos G, Reis CP, Gaspar MM. The Challenging Melanoma Landscape: From Early Drug Discovery to Clinical Approval. Cells 2021; 10:3088. [PMID: 34831311 PMCID: PMC8621991 DOI: 10.3390/cells10113088] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 11/02/2021] [Accepted: 11/06/2021] [Indexed: 02/06/2023] Open
Abstract
Melanoma is recognized as the most dangerous type of skin cancer, with high mortality and resistance to currently used treatments. To overcome the limitations of the available therapeutic options, the discovery and development of new, more effective, and safer therapies is required. In this review, the different research steps involved in the process of antimelanoma drug evaluation and selection are explored, including information regarding in silico, in vitro, and in vivo experiments, as well as clinical trial phases. Details are given about the most used cell lines and assays to perform both two- and three-dimensional in vitro screening of drug candidates towards melanoma. For in vivo studies, murine models are, undoubtedly, the most widely used for assessing the therapeutic potential of new compounds and to study the underlying mechanisms of action. Here, the main melanoma murine models are described as well as other animal species. A section is dedicated to ongoing clinical studies, demonstrating the wide interest and successful efforts devoted to melanoma therapy, in particular at advanced stages of the disease, and a final section includes some considerations regarding approval for marketing by regulatory agencies. Overall, considerable commitment is being directed to the continuous development of optimized experimental models, important for the understanding of melanoma biology and for the evaluation and validation of novel therapeutic strategies.
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Affiliation(s)
- Mariana Matias
- Research Institute for Medicines, iMed.ULisboa, Faculty of Pharmacy, Universidade de Lisboa, Av. Prof. Gama Pinto, 1649-003 Lisboa, Portugal
| | - Jacinta O Pinho
- Research Institute for Medicines, iMed.ULisboa, Faculty of Pharmacy, Universidade de Lisboa, Av. Prof. Gama Pinto, 1649-003 Lisboa, Portugal
| | - Maria João Penetra
- Research Institute for Medicines, iMed.ULisboa, Faculty of Pharmacy, Universidade de Lisboa, Av. Prof. Gama Pinto, 1649-003 Lisboa, Portugal
| | - Gonçalo Campos
- CICS-UBI-Health Sciences Research Centre, University of Beira Interior, Av. Infante D. Henrique, 6201-506 Covilhã, Portugal
| | - Catarina Pinto Reis
- Research Institute for Medicines, iMed.ULisboa, Faculty of Pharmacy, Universidade de Lisboa, Av. Prof. Gama Pinto, 1649-003 Lisboa, Portugal
| | - Maria Manuela Gaspar
- Research Institute for Medicines, iMed.ULisboa, Faculty of Pharmacy, Universidade de Lisboa, Av. Prof. Gama Pinto, 1649-003 Lisboa, Portugal
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33
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Love N, Shimada YJ. Japanese Medical Mnemonics-Language, Reflection, and Art. JAMA 2021; 326:1238-1240. [PMID: 34609474 DOI: 10.1001/jama.2021.6972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
- Nick Love
- CHA Cambridge Hospital, Cambridge, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Now with Department of Dermatology, University of California, Davis
| | - Yuichi J Shimada
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, New York
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34
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Janowska A, Oranges T, Iannone M, Romanelli M, Dini V. Seborrheic keratosis-like melanoma: a diagnostic challenge. Melanoma Res 2021; 31:407-412. [PMID: 34132226 DOI: 10.1097/cmr.0000000000000756] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
This article summarizes the main epidemiologic and diagnostic features of seborrheic keratosis-like (SK-like) melanoma. We performed a review of the current literature. The real and current incidence and prevalence of SK-like melanoma are unknown. Many lesions are misdiagnosed and not excised with histopathologic confirmation, or excised without an appropriate surgical approach due to a benign clinical and dermoscopic appearance. SK-like melanoma presents both melanoma and SK features. SK-like melanoma and SK are often clinically indistinguishable even for experienced dermatologists. Clinically, it develops as a black-dark brown or light slightly elevated, papule, nodule or plaque with rapid growth and a regular or irregular shape. SK-like melanoma presents melanocytic and nonmelanocytic dermoscopic features. Irregular dark-brown dots/globules, a blue-grayish veil, streaks, irregular pigmentation or network and brown lines point to a melanoma diagnosis. Among the nonmelanocytic features, milia-like cysts and comedo-like openings have been highlighted. The association of polarized and nonpolarized dermoscopic techniques is more accurate for studying the dermoscopic features of SK-like melanoma. If the dermoscopic features are unclear, further investigations with reflectance confocal microscopy (RCM) or biopsy with histologic examination are essential. SK-like melanoma is a dermatologic challenge. Careful clinical and dermoscopic evaluation favor a correct diagnosis. In unclear cases, it is important to perform a biopsy with histologic examination to confirm the correct diagnosis.
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Affiliation(s)
| | - Teresa Oranges
- Department of Dermatology, University of Pisa, Pisa
- Department of Pediatrics, Dermatology Unit, Meyer Children's University Hospital, Florence, Italy
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35
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Liu P, Su J, Zheng X, Chen M, Chen X, Li J, Peng C, Kuang Y, Zhu W. A Clinicopathological Analysis of Melanocytic Nevi: A Retrospective Series. Front Med (Lausanne) 2021; 8:681668. [PMID: 34447761 PMCID: PMC8383488 DOI: 10.3389/fmed.2021.681668] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/17/2021] [Indexed: 12/22/2022] Open
Abstract
Purpose: Melanocytic nevi are common cutaneous lesions. This study aimed to demonstrate the concordance and discordance between clinical and histopathological diagnoses of melanocytic nevi and the importance of histological evaluation in differentiating malignant lesions from diseases with similar clinical manifestations. Patients and Methods: We studied 4,561 consecutive patients with a clinical diagnosis of melanocytic nevi from 2014 to 2019. We compared the clinical diagnosis with the histopathological diagnosis to establish a histopathological concordance rate and then investigated the effects of clinical characteristics and the reasons for removal on misclassification. Results: Among 4,561 patients who were clinically diagnosed with melanocytic nevi, the overall histopathological concordance rate was 82.11% (3,745 of 4,561 patients), while the histopathological discordance rate was 17.89% (816 of 4,561 patients). The histopathological concordance included 90.25% common acquired melanocytic nevi (3,380 of 3,745 patients) and 9.75% other benign melanocytic neoplasms (365 of 3,745 patients). The most common diagnostic change was to seborrheic keratosis (n = 470, 10.30%), followed by basal cell carcinoma (n = 64, 1.40%), vascular tumor (n = 53, 1.16%), fibroma (n = 43, 0.94%), epidermoid cyst (n = 34, 0.75%), wart (n = 30, 0.66%), melanoma (n = 24, 0.53%), Bowen's disease (n = 16, 0.35%), squamous cell carcinoma (n = 4, 0.09%), keratoacanthoma (n = 2, 0.04%), and other neoplasms (n = 76, 1.67%). Male sex, old age, location of the lesion, and the reasons for removal have a potential effect on misclassification. The percentages of misclassified lesions on the trunk and limbs and the perineum and buttocks were higher than those in lesions without a change in diagnosis. Importantly, locations of lesions on the head and neck were significantly related to a change in diagnosis to non-melanoma skin cancer, while locations on the hands and feet were significantly related to a change in diagnosis to melanoma. In addition to a typical clinical features, removal due to lesion changes or repeated stimulation was significantly associated with a change in diagnosis to melanoma. Conclusions: Our study emphasizes the clinical differential diagnosis of melanocytic nevi, especially the possibility of malignant tumors. The occurrence of clinical features associated with clinicopathological discordance should raise the clinical suspect and be carefully differentiated from malignant tumors.
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Affiliation(s)
- Panpan Liu
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Skin Cancer and Psoriasis, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Changsha, China
| | - Juan Su
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Skin Cancer and Psoriasis, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Changsha, China
| | - Xuanwei Zheng
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Skin Cancer and Psoriasis, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Changsha, China
| | - Mingliang Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Skin Cancer and Psoriasis, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Changsha, China
| | - Xiang Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Skin Cancer and Psoriasis, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Changsha, China
| | - Jie Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Skin Cancer and Psoriasis, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Changsha, China
| | - Cong Peng
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Skin Cancer and Psoriasis, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Changsha, China
| | - Yehong Kuang
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Skin Cancer and Psoriasis, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Changsha, China
| | - Wu Zhu
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Skin Cancer and Psoriasis, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Changsha, China
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36
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Abstract
Recently, the incidence of skin cancer has increased considerably and is seriously threatening human health. Automatic detection of this disease, where early detection is critical to human life, is quite challenging. Factors such as undesirable residues (hair, ruler markers), indistinct boundaries, variable contrast, shape differences, and color differences in the skin lesion images make automatic analysis quite difficult. To overcome these challenges, a highly effective segmentation method based on a fully convolutional network (FCN) is presented in this paper. The proposed improved FCN (iFCN) architecture is used for the segmentation of full-resolution skin lesion images without any pre- or post-processing. It is to support the residual structure of the FCN architecture with spatial information. This situation, which creates a more advanced residual system, enables more precise detection of details on the edges of the lesion, and an analysis independent of skin color can be performed. It offers two contributions: determining the center of the lesion and clarifying the edge details despite the undesirable effects. Two publicly available datasets, the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 Challenge and PH2 datasets, are used to evaluate the performance of the iFCN method. The mean Jaccard index is 78.34%, the mean Dice score is 88.64%, and the mean accuracy value is 95.30% for the proposed method for the ISBI 2017 test dataset. Furthermore, the mean Jaccard index is 87.1%, the mean Dice score is 93.02%, and the mean accuracy value is 96.92% for the proposed method for the PH2 test dataset.
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Affiliation(s)
- Şaban Öztürk
- Technology Faculty, Electrical and Electronics Engineering, Amasya University, Amasya, Turkey.
| | - Umut Özkaya
- Engineering and Natural Science Faculty, Electrical and Electronics Engineering, Konya Technical University, Konya, Turkey
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Foahom Gouabou AC, Damoiseaux JL, Monnier J, Iguernaissi R, Moudafi A, Merad D. Ensemble Method of Convolutional Neural Networks with Directed Acyclic Graph Using Dermoscopic Images: Melanoma Detection Application. SENSORS (BASEL, SWITZERLAND) 2021; 21:3999. [PMID: 34200521 PMCID: PMC8229112 DOI: 10.3390/s21123999] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 06/02/2021] [Accepted: 06/04/2021] [Indexed: 11/16/2022]
Abstract
The early detection of melanoma is the most efficient way to reduce its mortality rate. Dermatologists achieve this task with the help of dermoscopy, a non-invasive tool allowing the visualization of patterns of skin lesions. Computer-aided diagnosis (CAD) systems developed on dermoscopic images are needed to assist dermatologists. These systems rely mainly on multiclass classification approaches. However, the multiclass classification of skin lesions by an automated system remains a challenging task. Decomposing a multiclass problem into a binary problem can reduce the complexity of the initial problem and increase the overall performance. This paper proposes a CAD system to classify dermoscopic images into three diagnosis classes: melanoma, nevi, and seborrheic keratosis. We introduce a novel ensemble scheme of convolutional neural networks (CNNs), inspired by decomposition and ensemble methods, to improve the performance of the CAD system. Unlike conventional ensemble methods, we use a directed acyclic graph to aggregate binary CNNs for the melanoma detection task. On the ISIC 2018 public dataset, our method achieves the best balanced accuracy (76.6%) among multiclass CNNs, an ensemble of multiclass CNNs with classical aggregation methods, and other related works. Our results reveal that the directed acyclic graph is a meaningful approach to develop a reliable and robust automated diagnosis system for the multiclass classification of dermoscopic images.
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Affiliation(s)
- Arthur Cartel Foahom Gouabou
- Laboratoire d’Informatique et Systèmes, Aix-Marseille University, 163 Avenue de Luminy, CEDEX 09, 13288 Marseille, France; (J.-L.D.); (J.M.); (R.I.); (A.M.); (D.M.)
| | - Jean-Luc Damoiseaux
- Laboratoire d’Informatique et Systèmes, Aix-Marseille University, 163 Avenue de Luminy, CEDEX 09, 13288 Marseille, France; (J.-L.D.); (J.M.); (R.I.); (A.M.); (D.M.)
| | - Jilliana Monnier
- Laboratoire d’Informatique et Systèmes, Aix-Marseille University, 163 Avenue de Luminy, CEDEX 09, 13288 Marseille, France; (J.-L.D.); (J.M.); (R.I.); (A.M.); (D.M.)
- Centre de Recherche en Cancerologie de Marseille (CRCM), 27 Boulevard Lei Roure, 13009 Marseille, France
| | - Rabah Iguernaissi
- Laboratoire d’Informatique et Systèmes, Aix-Marseille University, 163 Avenue de Luminy, CEDEX 09, 13288 Marseille, France; (J.-L.D.); (J.M.); (R.I.); (A.M.); (D.M.)
| | - Abdellatif Moudafi
- Laboratoire d’Informatique et Systèmes, Aix-Marseille University, 163 Avenue de Luminy, CEDEX 09, 13288 Marseille, France; (J.-L.D.); (J.M.); (R.I.); (A.M.); (D.M.)
| | - Djamal Merad
- Laboratoire d’Informatique et Systèmes, Aix-Marseille University, 163 Avenue de Luminy, CEDEX 09, 13288 Marseille, France; (J.-L.D.); (J.M.); (R.I.); (A.M.); (D.M.)
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38
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Zhu Y, Lesch A, Li X, Lin TE, Gasilova N, Jović M, Pick HM, Ho PC, Girault HH. Rapid Noninvasive Skin Monitoring by Surface Mass Recording and Data Learning. JACS AU 2021; 1:598-611. [PMID: 34056635 PMCID: PMC8154208 DOI: 10.1021/jacsau.0c00074] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Indexed: 05/08/2023]
Abstract
Skin problems are often overlooked due to a lack of robust and patient-friendly monitoring tools. Herein, we report a rapid, noninvasive, and high-throughput analytical chemical methodology, aiming at real-time monitoring of skin conditions and early detection of skin disorders. Within this methodology, adhesive sampling and laser desorption ionization mass spectrometry are coordinated to record skin surface molecular mass in minutes. Automated result interpretation is achieved by data learning, using similarity scoring and machine learning algorithms. Feasibility of the methodology has been demonstrated after testing a total of 117 healthy, benign-disordered, or malignant-disordered skins. Remarkably, skin malignancy, using melanoma as a proof of concept, was detected with 100% accuracy already at early stages when the lesions were submillimeter-sized, far beyond the detection limit of most existing noninvasive diagnosis tools. Moreover, the malignancy development over time has also been monitored successfully, showing the potential to predict skin disorder progression. Capable of detecting skin alterations at the molecular level in a nonsurgical and time-saving manner, this analytical chemistry platform is promising to build personalized skin care.
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Affiliation(s)
- Yingdi Zhu
- Institute of Chemical Sciences and Engineering, School of Basic Sciences, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Andreas Lesch
- Department of Industrial Chemistry "Toso Montanari", Universita degli Studi di Bologna, 40136 Bologna, Italy
| | - Xiaoyun Li
- Department of Fundamental Oncology, Université de Lausanne, 1066 Epalinges, Switzerland
- Ludwig Institute for Cancer Research, Université de Lausanne, 1066 Epalinges, Switzerland
| | - Tzu-En Lin
- Institute of Biomedical Engineering, College of Electrical and Computer Engineering, National Chiao Tung University, 30010 Hsinchu, Taiwan
| | - Natalia Gasilova
- Institute of Chemical Sciences and Engineering, School of Basic Sciences, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Milica Jović
- Institute of Chemical Sciences and Engineering, School of Basic Sciences, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Horst Matthias Pick
- Environmental Engineering Institute, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Ping-Chih Ho
- Department of Fundamental Oncology, Université de Lausanne, 1066 Epalinges, Switzerland
- Ludwig Institute for Cancer Research, Université de Lausanne, 1066 Epalinges, Switzerland
| | - Hubert H Girault
- Institute of Chemical Sciences and Engineering, School of Basic Sciences, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
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39
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Payano-Griffin S. Sonography as a Prognostic Indicator of Breslow Depth: Primary Malignant Melanoma of the Auricular Helix. JOURNAL OF DIAGNOSTIC MEDICAL SONOGRAPHY 2021. [DOI: 10.1177/8756479320981024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Malignant melanoma is a cellular cancer that produces pigmentation of the skin. The tendency toward melanoma may be inherited, and risk factors are increased with overexposure to the sun and ultraviolet radiation. Melanomas commonly present as a dark, asymmetrical, mole-like spot that spreads, with an irregular border. It is uncommon to find a melanoma in the auricular regions and even rarer for it to be a primary malignancy of the auricles. Utilizing sonography to evaluate melanoma lesions could serve as a prognostic indicator, regarding Breslow’s depth, an aide in staging, as well as surgical planning. However, utilizing multiple diagnostic imaging modalities is essential in the proper evaluation and staging of a melanoma. Currently there are revolutionary, effective systemic therapies available for patients with a metastatic melanoma. Current therapies are focused on immunotherapy and checkpoint inhibitors. These treatment options provide an opportunity for selected metastatic melanoma patients to achieve healthy long-term success.
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Affiliation(s)
- Shirly Payano-Griffin
- Neuro Interventional Radiology: Ultrasound Department, The University of Texas MD Anderson Cancer Center, Katy, TX, USA
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41
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Otero C, Podlipnik S, Carrera C, Garcia-Herrera A, Alós L, Combalia M, Domínguez M, Malvehy J, Puig S. Dermoscopic, confocal and histopathologic characteristics of small-diameter melanomas (minimelanoma): a cross sectional study. Australas J Dermatol 2021; 62:e256-e261. [PMID: 33667318 DOI: 10.1111/ajd.13562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 01/12/2021] [Accepted: 01/13/2021] [Indexed: 11/29/2022]
Affiliation(s)
- Camila Otero
- Dermatology Department, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain
| | - Sebastian Podlipnik
- Dermatology Department, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomediques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Cristina Carrera
- Dermatology Department, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomediques August Pi I Sunyer (IDIBAPS), Barcelona, Spain.,Biomedical Research Networking Center on Rare Diseases (CIBERER), ISCIII, Barcelona, Spain
| | - Adriana Garcia-Herrera
- Dermatology of Histopathology, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain
| | - Llúcia Alós
- Dermatology of Histopathology, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain
| | - Marc Combalia
- Dermatology Department, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain
| | - Mireia Domínguez
- Dermatology Department, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain
| | - Josep Malvehy
- Dermatology Department, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomediques August Pi I Sunyer (IDIBAPS), Barcelona, Spain.,Biomedical Research Networking Center on Rare Diseases (CIBERER), ISCIII, Barcelona, Spain
| | - Susana Puig
- Dermatology Department, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomediques August Pi I Sunyer (IDIBAPS), Barcelona, Spain.,Biomedical Research Networking Center on Rare Diseases (CIBERER), ISCIII, Barcelona, Spain
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42
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Razavi A, Keshavarz-Fathi M, Pawelek J, Rezaei N. Chimeric antigen receptor T-cell therapy for melanoma. Expert Rev Clin Immunol 2021; 17:209-223. [PMID: 33481629 DOI: 10.1080/1744666x.2021.1880895] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
INTRODUCTION In recent years, chimeric antigen receptor (CAR) T cell therapy has emerged as a cancer treatment. After initial therapeutic success for hematologic malignancies, this approach has been extended for the treatment of solid tumors including melanoma. AREAS COVERED T cells need to be reprogramed to recognize specific antigens expressed only in tumor cells, a difficult problem since cancer cells are simply transformed normal cells. Tumor antigens, namely, CSPG4, CD70, and GD2 have been targeted by CAR-T cells for melanoma. Moreover, different co-stimulatory signaling domains need to be selected to direct T cell fate. In this review, various approaches for the treatment of melanoma and their effectiveness are comprehensively reviewed and the current status, challenges, and future perspective of CAR-T cell therapy for melanoma are discussed. Literature search was accomplished in three databases (PubMed, Google scholar, and Clinicaltrials.gov). Published papers and clinical trials were screened and relevant documents were included by checking pre-defined eligibility criteria. EXPERT OPINION Despite obstacles and the risk of adverse events, CAR T cell therapy could be used for patients with treatment-resistant cancer. Clinical trials are underway to determine the efficacy of this approach for the treatment of melanoma.
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Affiliation(s)
- Azadehsadat Razavi
- Department of Animal Biology, Faculty of Biology Sciences, University of Kharazmi, Tehran, Iran.,Cancer Immunology Project (CIP), Universal Scientific Education and Research Network (USERN), Tehran, Iran.,Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahsa Keshavarz-Fathi
- Cancer Immunology Project (CIP), Universal Scientific Education and Research Network (USERN), Tehran, Iran.,School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - John Pawelek
- Department of Dermatology and the Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Nima Rezaei
- Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran.,Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.,Cancer Immunology Project (CIP), Universal Scientific Education and Research Network (USERN), Stockholm, Sweden
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43
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Curve-Based Classification Approach for Hyperspectral Dermatologic Data Processing. SENSORS 2021; 21:s21030680. [PMID: 33498303 PMCID: PMC7863929 DOI: 10.3390/s21030680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 01/13/2021] [Accepted: 01/15/2021] [Indexed: 12/24/2022]
Abstract
This paper shows new contributions in the detection of skin cancer, where we present the use of a customized hyperspectral system that captures images in the spectral range from 450 to 950 nm. By choosing a 7 × 7 sub-image of each channel in the hyperspectral image (HSI) and then taking the mean and standard deviation of these sub-images, we were able to make fits of the resulting curves. These fitted curves had certain characteristics, which then served as a basis of classification. The most distinct fit was for the melanoma pigmented skin lesions (PSLs), which is also the most aggressive malignant cancer. Furthermore, we were able to classify the other PSLs in malignant and benign classes. This gives us a rather complete classification method for PSLs with a novel perspective of the classification procedure by exploiting the variability of each channel in the HSI.
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44
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Jojoa Acosta MF, Caballero Tovar LY, Garcia-Zapirain MB, Percybrooks WS. Melanoma diagnosis using deep learning techniques on dermatoscopic images. BMC Med Imaging 2021; 21:6. [PMID: 33407213 PMCID: PMC7789790 DOI: 10.1186/s12880-020-00534-8] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Accepted: 12/08/2020] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Melanoma has become more widespread over the past 30 years and early detection is a major factor in reducing mortality rates associated with this type of skin cancer. Therefore, having access to an automatic, reliable system that is able to detect the presence of melanoma via a dermatoscopic image of lesions and/or skin pigmentation can be a very useful tool in the area of medical diagnosis. METHODS Among state-of-the-art methods used for automated or computer assisted medical diagnosis, attention should be drawn to Deep Learning based on Convolutional Neural Networks, wherewith segmentation, classification and detection systems for several diseases have been implemented. The method proposed in this paper involves an initial stage that automatically crops the region of interest within a dermatoscopic image using the Mask and Region-based Convolutional Neural Network technique, and a second stage based on a ResNet152 structure, which classifies lesions as either "benign" or "malignant". RESULTS Training, validation and testing of the proposed model was carried out using the database associated to the challenge set out at the 2017 International Symposium on Biomedical Imaging. On the test data set, the proposed model achieves an increase in accuracy and balanced accuracy of 3.66% and 9.96%, respectively, with respect to the best accuracy and the best sensitivity/specificity ratio reported to date for melanoma detection in this challenge. Additionally, unlike previous models, the specificity and sensitivity achieve a high score (greater than 0.8) simultaneously, which indicates that the model is good for accurate discrimination between benign and malignant lesion, not biased towards any of those classes. CONCLUSIONS The results achieved with the proposed model suggest a significant improvement over the results obtained in the state of the art as far as performance of skin lesion classifiers (malignant/benign) is concerned.
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Affiliation(s)
| | | | | | - Winston Spencer Percybrooks
- Department of Electrical and Electronics Engineering, Universidad del Norte, Km.5 Vía Puerto Colombia, Barranquilla, Colombia
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45
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Hessler M, Jalilian E, Xu Q, Reddy S, Horton L, Elkin K, Manwar R, Tsoukas M, Mehregan D, Avanaki K. Melanoma Biomarkers and Their Potential Application for In Vivo Diagnostic Imaging Modalities. Int J Mol Sci 2020; 21:E9583. [PMID: 33339193 PMCID: PMC7765677 DOI: 10.3390/ijms21249583] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 12/09/2020] [Accepted: 12/12/2020] [Indexed: 12/16/2022] Open
Abstract
Melanoma is the deadliest form of skin cancer and remains a diagnostic challenge in the dermatology clinic. Several non-invasive imaging techniques have been developed to identify melanoma. The signal source in each of these modalities is based on the alteration of physical characteristics of the tissue from healthy/benign to melanoma. However, as these characteristics are not always sufficiently specific, the current imaging techniques are not adequate for use in the clinical setting. A more robust way of melanoma diagnosis is to "stain" or selectively target the suspect tissue with a melanoma biomarker attached to a contrast enhancer of one imaging modality. Here, we categorize and review known melanoma diagnostic biomarkers with the goal of guiding skin imaging experts to design an appropriate diagnostic tool for differentiating between melanoma and benign lesions with a high specificity and sensitivity.
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Affiliation(s)
- Monica Hessler
- Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA; (M.H.); (Q.X.); (S.R.); (L.H.); (K.E.); (R.M.)
- Department of Dermatology, School of Medicine, Wayne State University School of Medicine, Detroit, MI 48201, USA;
| | - Elmira Jalilian
- Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, IL 60607, USA;
| | - Qiuyun Xu
- Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA; (M.H.); (Q.X.); (S.R.); (L.H.); (K.E.); (R.M.)
| | - Shriya Reddy
- Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA; (M.H.); (Q.X.); (S.R.); (L.H.); (K.E.); (R.M.)
| | - Luke Horton
- Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA; (M.H.); (Q.X.); (S.R.); (L.H.); (K.E.); (R.M.)
- Department of Dermatology, School of Medicine, Wayne State University School of Medicine, Detroit, MI 48201, USA;
| | - Kenneth Elkin
- Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA; (M.H.); (Q.X.); (S.R.); (L.H.); (K.E.); (R.M.)
- Department of Dermatology, School of Medicine, Wayne State University School of Medicine, Detroit, MI 48201, USA;
| | - Rayyan Manwar
- Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA; (M.H.); (Q.X.); (S.R.); (L.H.); (K.E.); (R.M.)
- Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Maria Tsoukas
- Department of Dermatology, University of Illinois at Chicago, Chicago, IL 60607, USA;
| | - Darius Mehregan
- Department of Dermatology, School of Medicine, Wayne State University School of Medicine, Detroit, MI 48201, USA;
| | - Kamran Avanaki
- Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA
- Department of Dermatology, University of Illinois at Chicago, Chicago, IL 60607, USA;
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Martos-Cabrera L, Sampedro-Ruiz R, Delgado-Jimenez Y, Gallo E, Navarro R, Aragües M, Llamas-Velasco M, Chicharro P, Rodríguez-Jiménez P. Geometric border as a marker for melanoma diagnosis: Study of 200 consecutive melanocytic lesions. Dermatol Ther 2020; 34:e14617. [PMID: 33283403 DOI: 10.1111/dth.14617] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 11/24/2020] [Accepted: 11/26/2020] [Indexed: 10/22/2022]
Abstract
The ABCD rule has long been proposed as a guidance for malignant melanoma (MM) diagnosis. We aimed to define a new simple, straightforward tool that could be useful in early melanoma detection and must be validated in further studies. We conducted a prospective historic cohort study of 200 melanocytic lesions classifying them according to the presence of geometric borders. Sixty-four percent of the MM and 31% of the melanocytic nevi presented with geometric borders. Lesions with two straight borders that formed a noncurvilinear angle presented a 2.1-fold higher risk of being malignant after excision. When comparing melanomas with geometric and nongeometric border, we found a tendency toward better prognostic markers in the geometric lesions. Lesions located in the extremities and melanoma subtype SSM were more common in the geometric group. Regarding pathologic features, a deeper Breslow (mean, 3.8 vs 1.4 mm), presence of ulceration (25% vs 5%) and a higher number of mitosis was found in the nongeometric group. On the other hand, more regression was found in the geometric group while both groups showed similar degree of lymphovascular infiltration. We propose geometric border as another clinical criterion to take into account when suspecting MM, which must be validated in further studies. The ABCDE rule could be completed with a G for geometry.
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Affiliation(s)
- Luisa Martos-Cabrera
- Department of Dermatology, Instituto de Investigación Sanitaria la Princesa (IIS-IP), Hospital Universitario de La Princesa, Madrid, Spain
| | - Raquel Sampedro-Ruiz
- Department of Dermatology, Instituto de Investigación Sanitaria la Princesa (IIS-IP), Hospital Universitario de La Princesa, Madrid, Spain
| | - Yolanda Delgado-Jimenez
- Department of Dermatology, Instituto de Investigación Sanitaria la Princesa (IIS-IP), Hospital Universitario de La Princesa, Madrid, Spain
| | - Elena Gallo
- Department of Dermatology, Instituto de Investigación Sanitaria la Princesa (IIS-IP), Hospital Universitario de La Princesa, Madrid, Spain
| | - Raquel Navarro
- Department of Dermatology, Instituto de Investigación Sanitaria la Princesa (IIS-IP), Hospital Universitario de La Princesa, Madrid, Spain
| | - Maximiliano Aragües
- Department of Dermatology, Instituto de Investigación Sanitaria la Princesa (IIS-IP), Hospital Universitario de La Princesa, Madrid, Spain
| | - Mar Llamas-Velasco
- Department of Dermatology, Instituto de Investigación Sanitaria la Princesa (IIS-IP), Hospital Universitario de La Princesa, Madrid, Spain
| | - Pablo Chicharro
- Department of Dermatology, Instituto de Investigación Sanitaria la Princesa (IIS-IP), Hospital Universitario de La Princesa, Madrid, Spain
| | - Pedro Rodríguez-Jiménez
- Department of Dermatology, Instituto de Investigación Sanitaria la Princesa (IIS-IP), Hospital Universitario de La Princesa, Madrid, Spain
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Loescher L, Heslin K, Silva G, Muramoto M. Partnering With Massage Therapists to Communicate Information on Reducing the Risk of Skin Cancer Among Clients: Longitudinal Study. JMIR Form Res 2020; 4:e21309. [PMID: 33136054 PMCID: PMC7669440 DOI: 10.2196/21309] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 07/15/2020] [Accepted: 10/02/2020] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Skin cancer affects millions of Americans and is an important focus of disease prevention efforts. Partnering with non-health care practitioners such as massage therapists (MTs) can reduce the risk of skin cancer. MTs see clients' skin on a regular basis, which can allow MTs to initiate "helping conversations" (ie, brief behavioral interventions aimed at reducing the risk of skin cancer). OBJECTIVE The purpose of this study was to evaluate (1) the feasibility of recruiting, enrolling, and retaining Arizona MTs in an online electronic training (e-training) and (2) the preliminary efficacy of e-training on knowledge, attitudes/beliefs, and practice of risk reduction for skin cancer. We explored MTs' ability to assess suspicious skin lesions. METHODS We adapted the existing educational content on skin cancer for applicability to MTs and strategies from previous research on helping conversations. We assessed the feasibility of providing such e-training, using Research Electronic Data Capture (REDCap) tools for data capture. We assessed the preliminary efficacy using established self-report surveys at baseline, immediately post training, and at 3 and 6 months post training. RESULTS A total of 95 participants enrolled in the study, of which 77% (73/95) completed the assessments at 6 months (overall attrition=23%). Project satisfaction and e-training acceptability were high. Knowledge, personal behaviors (skin self-examination, clinical skin examination, sun protection frequency), and practice attitudes (appropriateness and comfort with client-focused communication) of risk reduction for skin cancer improved significantly and were sustained throughout the study. CONCLUSIONS The e-training was feasible and could be delivered online successfully to MTs. Participants were highly satisfied with and accepting of the e-training. As such, e-training has potential as an intervention in larger trials with MTs for reducing the risk of skin cancer. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.2196/13480.
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Affiliation(s)
- Lois Loescher
- College of Nursing, University of Arizona, Tucson, AZ, United States
| | - Kelly Heslin
- College of Nursing, University of Arizona, Tucson, AZ, United States
| | - Graciela Silva
- College of Nursing, University of Arizona, Tucson, AZ, United States
| | - Myra Muramoto
- Colleges of Medicine and Public Health, University of Arizona, Tucson, AZ, United States
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Goldsmith SM. Comment on “Re-evaluating the ABCD criteria using a consecutive series of melanomas”. J Am Acad Dermatol 2020; 83:e297. [DOI: 10.1016/j.jaad.2020.05.098] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 05/02/2020] [Indexed: 11/29/2022]
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Po Harvey Chin Y, Hsin Huang I, Yu Hou Z, Yu Chen P, Bassir F, Han Wang H, Ting Lin Y, Chuan Jack Li Y. User satisfaction with a smartphone-compatible, artificial intelligence-based cutaneous pigmented lesion evaluator. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2020; 195:105649. [PMID: 32750631 DOI: 10.1016/j.cmpb.2020.105649] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 07/04/2020] [Indexed: 06/11/2023]
Abstract
INTRODUCTION Melanoma is the most aggressive type of skin cancer, and it may arise from a cutaneous pigmented lesion. As artificial intelligence (AI)-based teledermatology services hold promise in redefining the melanoma screening paradigm, a study that evaluates user satisfaction with a smartphone-compatible, AI-based cutaneous pigmented lesion evaluator is lacking. METHODS Data was collected between April and May 2019 in Taiwan. To assess user satisfaction with MoleMe, an AI-based cutaneous pigmented lesion evaluator on a smartphone, users were asked to complete a questionnaire designed to evaluate four aspects, including interaction, impact on daily life, usability, and overall performance, after completing a MoleMe evaluation session. For each question, users could rank their satisfaction level from 1 to 5, with five showing strongly satisfied and one showing strongly unsatisfied. The Kruskal-Wallis and Wilcoxon rank-sum tests were used to compare user satisfaction among different age groups, genders, and risk predictions received. RESULT A total of 1231 questionnaires were collected for analysis. Over 90% of the participants were satisfied (score = 4 or 5) and over 75% of the participants were strongly satisfied (score 5) with MoleMe, in terms of usability, interaction, and impact on daily life. The user satisfaction did not show a significant difference between genders, age groups, and risk predictions received. (all P > 0.05) CONCLUSION: With high user satisfaction regardless of age group, gender, and risk prediction received, AI-based teledermatology services on a smartphone such as MoleMe may potentially achieve widespread usage and be beneficial to both patients and physicians.
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Affiliation(s)
- Yen Po Harvey Chin
- Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan; Department of Biomedical Informatics, Harvard Medical School, MA, USA; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, USA
| | - I Hsin Huang
- Department of General Medicine, Taipei Medical University Hospital, Taipei, Taiwan
| | - Ze Yu Hou
- Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan
| | - Po Yu Chen
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, MA, USA
| | - Fatima Bassir
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, USA
| | - Hsiao Han Wang
- Department of Dermatology, Taipei Municipal Wan Fang Hospital, Taipei, Taiwan
| | - Yu Ting Lin
- Department of Dermatology, Taipei Municipal Wan Fang Hospital, Taipei, Taiwan
| | - Yu Chuan Jack Li
- Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan; Department of Dermatology, Taipei Municipal Wan Fang Hospital, Taipei, Taiwan.
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Leon R, Martinez-Vega B, Fabelo H, Ortega S, Melian V, Castaño I, Carretero G, Almeida P, Garcia A, Quevedo E, Hernandez JA, Clavo B, M. Callico G. Non-Invasive Skin Cancer Diagnosis Using Hyperspectral Imaging for In-Situ Clinical Support. J Clin Med 2020; 9:E1662. [PMID: 32492848 PMCID: PMC7356572 DOI: 10.3390/jcm9061662] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 05/27/2020] [Indexed: 02/08/2023] Open
Abstract
Skin cancer is one of the most common forms of cancer worldwide and its early detection its key to achieve an effective treatment of the lesion. Commonly, skin cancer diagnosis is based on dermatologist expertise and pathological assessment of biopsies. Although there are diagnosis aid systems based on morphological processing algorithms using conventional imaging, currently, these systems have reached their limit and are not able to outperform dermatologists. In this sense, hyperspectral (HS) imaging (HSI) arises as a new non-invasive technology able to facilitate the detection and classification of pigmented skin lesions (PSLs), employing the spectral properties of the captured sample within and beyond the human eye capabilities. This paper presents a research carried out to develop a dermatological acquisition system based on HSI, employing 125 spectral bands captured between 450 and 950 nm. A database composed of 76 HS PSL images from 61 patients was obtained and labeled and classified into benign and malignant classes. A processing framework is proposed for the automatic identification and classification of the PSL based on a combination of unsupervised and supervised algorithms. Sensitivity and specificity results of 87.5% and 100%, respectively, were obtained in the discrimination of malignant and benign PSLs. This preliminary study demonstrates, as a proof-of-concept, the potential of HSI technology to assist dermatologists in the discrimination of benign and malignant PSLs during clinical routine practice using a real-time and non-invasive hand-held device.
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Affiliation(s)
- Raquel Leon
- Institute for Applied Microelectronics (IUMA), University of Las Palmas de Gran Canaria (ULPGC), 35017 Las Palmas de Gran Canaria, Spain; (B.M.-V.); (H.F.); (S.O.); (V.M.); (E.Q.); (G.M.C.)
| | - Beatriz Martinez-Vega
- Institute for Applied Microelectronics (IUMA), University of Las Palmas de Gran Canaria (ULPGC), 35017 Las Palmas de Gran Canaria, Spain; (B.M.-V.); (H.F.); (S.O.); (V.M.); (E.Q.); (G.M.C.)
| | - Himar Fabelo
- Institute for Applied Microelectronics (IUMA), University of Las Palmas de Gran Canaria (ULPGC), 35017 Las Palmas de Gran Canaria, Spain; (B.M.-V.); (H.F.); (S.O.); (V.M.); (E.Q.); (G.M.C.)
| | - Samuel Ortega
- Institute for Applied Microelectronics (IUMA), University of Las Palmas de Gran Canaria (ULPGC), 35017 Las Palmas de Gran Canaria, Spain; (B.M.-V.); (H.F.); (S.O.); (V.M.); (E.Q.); (G.M.C.)
| | - Veronica Melian
- Institute for Applied Microelectronics (IUMA), University of Las Palmas de Gran Canaria (ULPGC), 35017 Las Palmas de Gran Canaria, Spain; (B.M.-V.); (H.F.); (S.O.); (V.M.); (E.Q.); (G.M.C.)
| | - Irene Castaño
- Department of Dermatology, Hospital Universitario de Gran Canaria Doctor Negrín, Barranco de la Ballena s/n, 35010 Las Palmas de Gran Canaria, Spain; (I.C.); (G.C.)
| | - Gregorio Carretero
- Department of Dermatology, Hospital Universitario de Gran Canaria Doctor Negrín, Barranco de la Ballena s/n, 35010 Las Palmas de Gran Canaria, Spain; (I.C.); (G.C.)
| | - Pablo Almeida
- Department of Dermatology, Complejo Hospitalario Universitario Insular-Materno Infantil, Avenida Maritima del Sur, s/n, 35016 Las Palmas de Gran Canaria, Spain; (P.A.); (J.A.H.)
| | - Aday Garcia
- Department of Electromedicine, Complejo Hospitalario Universitario Insular-Materno Infantil, Avenida Maritima del Sur, s/n, 35016 Las Palmas de Gran Canaria, Spain;
| | - Eduardo Quevedo
- Institute for Applied Microelectronics (IUMA), University of Las Palmas de Gran Canaria (ULPGC), 35017 Las Palmas de Gran Canaria, Spain; (B.M.-V.); (H.F.); (S.O.); (V.M.); (E.Q.); (G.M.C.)
| | - Javier A. Hernandez
- Department of Dermatology, Complejo Hospitalario Universitario Insular-Materno Infantil, Avenida Maritima del Sur, s/n, 35016 Las Palmas de Gran Canaria, Spain; (P.A.); (J.A.H.)
| | - Bernardino Clavo
- Research Unit, Hospital Universitario de Gran Canaria Doctor Negrín, Barranco de la Ballena s/n, 35010 Las Palmas de Gran Canaria, Spain;
| | - Gustavo M. Callico
- Institute for Applied Microelectronics (IUMA), University of Las Palmas de Gran Canaria (ULPGC), 35017 Las Palmas de Gran Canaria, Spain; (B.M.-V.); (H.F.); (S.O.); (V.M.); (E.Q.); (G.M.C.)
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