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- Presentation
Before the Blade: Current Application and Future Direction for Non-Invasive Imaging for Pigmented Lesions
Description
Michael Kwa, a pigmented lesion expert from Boston University, presents on non-invasive imaging applications for pigmented lesions, covering current modalities and future prospects. The aims include reviewing efficacy, identifying practical uses, and discussing future diagnostic directions. Biopsy remains the gold standard, but imaging proves beneficial for patients with numerous atypical nevi or those fatigued by multiple procedures. Current standards, like dermoscopy and photography, reduce unnecessary biopsies and provide benefits like improved melanoma detection and survival rates. Innovations in artificial intelligence (AI) enhance diagnostic accuracy by helping clinicians differentiate benign from malignant lesions and streamline whole-body imaging. Various other imaging techniques are discussed, including high-frequency ultrasound and electrical impedance spectroscopy, each with unique advantages and limitations. Confocal microscopy shows promise in accurately assessing lesion characteristics and reducing biopsy needs. Emerging technologies like spectroscopy offer insights at the cellular level, paving the way for future advancements in skin cancer diagnosis. Kwa emphasizes the exciting developments in imaging technologies and AI that could significantly impact clinical practice for complex pigmented lesions, highlighting the need for continuous improvement and integration of these tools in dermatological care.
View moreConclusions
- Non-invasive imaging technologies, such as serial dermoscopy and total body photography, significantly reduce the number of biopsies needed for diagnosing melanoma.
- Current guidelines recommend total body photography for specific high-risk patient groups, thereby improving monitoring and early diagnosis.
- Serial dermoscopy has shown a mortality benefit, leading to greater overall survival in patients monitored over time.
- Innovations in artificial intelligence are enhancing the accuracy of dermoscopy and may reduce unnecessary biopsies in benign cases.
- Emerging imaging techniques like confocal microscopy provide high-resolution insights and can reduce unnecessary biopsies by 50-60%.
- The use of spectroscopy offers molecular-level information that can further differentiate melanoma from benign lesions.
- Future advancements aim to enhance the accuracy and application of imaging technologies through clinical correlation and standardization of biochemical signals.
- The Melanoma Man. Public post for skin cancer awareness. Facebook ., 4 Nov. 2020, https://www.facebook.com/TheMelanomaMan. Accessed 22 Feb 2024.
- International Skin Imaging Collaboration. /S/C, www.isic-archive.com/. Accessed 22 Feb. 2024.
- Nelson KC, Swetter SM, Saboda K, Chen SC, Curiel-Lewandrowski C. Evaluation of the Number-Needed-to-Biopsy Metric for the Diagnosis of Cutaneous Melanoma: A Systematic Review and Meta-analysis. JAMA Dermatology. 2019;155(10):1167-1174.
- Terushkin V, Warycha M, Levy M, Kopf AW, Cohen DE, Polsky D. Analysis of the Benign to Malignant Ratio of Lesions Biopsied by a General Dermatologist Before and After the Adoption of Dermoscopy. Archives of Dermatology. 2010;146(3):343-344.
- Ji-Xu A, Dinnes J, Matin RN. Total body photography for the diagnosis of cutaneous melanoma in adults: a systematic review and meta-analysis. British Journal of Dermatology. 2021;185(2):302-312.
- Skudalski L, Waldman R, Kerr PE, Grant-Kels JM. Melanoma: How and when to consider clinical diagnostic technologies. Journal of the American Academy of Dermatology. 2022;86(3):503-512.
- Babino G, Lallas A, Agozzino M, et al. Melanoma diagnosed on digital dermoscopy monitoring: A side-by-side image comparison is needed to improve early detection. Journal of the American Academy of Dermatology. 2021;85(3):619-625.
- Lallas, Aimilios, et al. Second primary melanomas in a cohort of 977 melanoma patients within the first 5 years of monitoring. Journal of the American Academy of Dermatology 82.2 (2020): 398-406.
- Strunck JL, Smart TC, Boucher KM, Secrest AM, Grossman D. Improved melanoma outcomes and survival in patients monitored by total body photography: A natural experiment. J Dermatol. 2020;47(4):342-347.
- Waldman RA, Grant-Kels JM, Curiel CN, et al. Consensus recommendations for the use of noninvasive melanoma detection techniques based on results of an international Delphi process. J Am Acad Dermatol. 2021;85(3):745-749. doi:10.1016/j.jaad.2019.09.046
- Marchetti MA, Cowen EA, Kurtansky NR, et al. Prospective validation of dermoscopy-based open-source artificial intelligence for melanoma diagnosis (PROVE-AI study). npj Digit Med. 2023;6(1):1-11. doi:10.1038/s41746-023-00872-1
- Marchetti MA, Nazir ZH, Nanda JK, et al. 3D Whole-body skin imaging for automated melanoma detection. Journal of the European Academy of Dermatology and Venereology. 2023;37(5):945-950. doi:10.1111/jdv.18924.
- Bessoud B, Lassau N, Koscielny S, et al. High-frequency sonography and color Doppler in the management of pigmented skin lesions. Ultrasound in Medicine & Biology. 2003;29(6):875-879.
- Oranges T, Janowska A, Scatena C, et al. Ultra-High Frequency Ultrasound in Melanoma Management. Journal of Ultrasound in Medicine. 2023;42(1):99-108.
- Heibel HD, Hooey L, Cockerell CJ. A Review of Noninvasive Techniques for Skin Cancer Detection in Dermatology. Am J Clin Dermatol. 2020;21(4):513-524.
- Malvehy J, Hauschild A, Curiel-Lewandrowski C, et al. Clinical performance of the Nevisense system in cutaneous melanoma detection: an international, multicentre, prospective and blinded clinical trial on efficacy and safety. British Journal of Dermatology. 2014;171(5):1099-1107.
- MacLellan AN, Price EL, Publicover-Brouwer P, et al. The use of noninvasive imaging techniques in the diagnosis of melanoma: a prospective diagnostic accuracy study. Journal of the American Academy of Dermatology. 2021;85(2):353-359.
- Monheit G, Cognetta AB, Ferris L, et al. The Performance of MelaFind: A Prospective Multicenter Study. Archives of Dermatology. 2011;147(2):188-194.
- Gambichler T, Schmid-Wendtner M h ., Plura I, et al. A multicentre pilot study investigating high-definition optical coherence tomography in the differentiation of cutaneous melanoma and melanocytic naevi. Journal of the European Academy of Dermatology and Venereology. 2015;29(3):537-541.
- Pellacani G, Scope A, Gonzalez S, et al. Reflectance confocal microscopy made easy: The 4 must-know key features for the diagnosis of melanoma and nonmelanoma skin cancers. Journal of the American Academy of Dermatology. 2019;81(2):520-526.
- Rajadhyaksha M, Marghoob A, Rossi A, Halpern AC, Nehal KS. Reflectance confocal microscopy of skin in vivo: From bench to bedside. Lasers in Surgery and Medicine. 2017;49(1):7-19.
- Pellacani G, Pepe P, Casari A, Longo C. Reflectance confocal microscopy as a second-level examination in skin oncology improves diagnostic accuracy and saves unnecessary excisions: a longitudinal prospective study. British Journal of Dermatology. 2014;171(5):1044-1051. doi:10.1111/bjd.13148
- Longo C, Mazzeo M, Raucci M, et al. Dark pigmented lesions: Diagnostic accuracy of dermoscopy and reflectance confocal microscopy in a tertiary referral center for skin cancer diagnosis. Journal of the American Academy of Dermatology. 2021;84(6):1568-1574. doi:10.1016/j.jaad.2020.07.084
- Faldetta C, Kaleci S, Chester J, et al. Melanoma clinicopathological groups characterized and compared with dermoscopy and reflectance confocal microscopy. Journal of the American Academy of Dermatology. 2020;83(4):983-992.
- Lee HJ, Chen Z, Collard M, Chen F, Chen J, Wu M, Alani R, Cheng J. Multimodal Metabolic Imaging Reveals Pigment Reduction and Lipid Accumulation in Metastatic Melanoma. BME Frontiers. 2021;2021:9860123.
- Zhang Y, Moy AJ, Feng X, et al. Assessment of Raman Spectroscopy for Reducing Unnecessary Biopsies for Melanoma Screening. Molecules. 2020;25(12):2852. doi:10.3390/molecules25122852
- Hartman RI, Trepanowski N, Chang MS, et al. Multicenter prospective blinded melanoma detection study with a handheld elastic scattering spectroscopy device. JAAD International. 2024;15:24-31.
- Lui H, Zhao J, McLean D, Zeng H. Real-time Raman Spectroscopy for In Vivo Skin Cancer Diagnosis. Cancer Research. 2012;72(10):2491-2500. doi:10.1158/0008-5472.CAN-11-4061.
- Kose K, Bozkurt A, Alessi-Fox C, et al. Utilizing Machine Learning for Semantic segmentation of reflectance confocal microscopy mosaics of pigmented lesions using weak labels. Sci Rep. 2021;11:3679.
- Yélamos O, Cordova M, Blank N, et al. Correlation of Handheld Reflectance Confocal Microscopy With Radial Video Mosaicing for Margin Mapping of Lentigo Maligna and Lentigo Maligna Melanoma. JAMA Dermatology. 2017;153(12):1278-1284.
- Pellacani G, De Carvalho N, Ciardo S, et al. The smart approach: feasibility of lentigo maligna superficial margin assessment with hand-held reflectance confocal microscopy technology. Journal of the European Academy of Dermatology and Venereology. 2018;32(10):1687-1694.
- Navarrete-Dechent C, Cordova M, Aleissa S, et al. Lentigo maligna melanoma mapping using reflectance confocal microscopy correlates with staged excision: A prospective study. Journal of the American Academy of Dermatology. 2023;88(2):371-379.