恶性黑色素瘤的诊断热点

doi:10.16150/j.1671-2870.2023.03.02

摘要/Abstract

摘要：

全球的恶性黑色素瘤（黑色素瘤）发病率从1990年的2.01/10万增加到2019年的3.75/10万。黑色素瘤在中国的发病率和死亡率低于全球平均水平，但近年来其发病率的增长速度（3%~5%）是中国恶性肿瘤发病率中增长最快的，每年新发黑色素瘤患者达2~3万例。黑色素瘤易侵袭和转移，Ⅳ期患者的5年生存率仅为4.6%。早期诊断与治疗，能极大地改善黑色素瘤患者的预后。目前恶性黑色素瘤诊断热点包括视诊辅助工具、人工智能辅助诊断、组织学诊断及鉴别诊断等。视诊辅助工具可用于筛查黑色素瘤，皮肤镜和皮肤共聚焦技术（皮肤CT），诊断黑色素瘤灵敏度可分别为61%及100%；人工智能为基础诊断黑色素瘤比单纯的人工智能或医师诊断准确率更高，可将黑色素瘤诊断准确率从55.6%提高至75.0%。组织学诊断二代测序技术的不断进步，尚缺乏适用于所有黑色素瘤的客观的、高重复性免疫组织化学标志，但随着黑色素瘤基因组学的研究逐渐深入，BRAF V600E、NRAS突变已经应用于临床诊治及预后评估。黑色素瘤侵袭性强，许多患者确诊时即为晚期，因此，我国黑色素瘤诊疗需重视多学科诊疗团队模式，并促进建立在多学科共识基础上的诊疗原则和指南。

关键词: 黑色素瘤, 皮肤镜, 皮肤CT, 人工智能, 组织学, 鉴别诊断

Abstract:

The global incidence of melanoma increased from 2.01/ 100 000 in 1990 to 3.75/100 000 in 2019. The incidence and mortality rate of malignant melanoma in China is lower than that of the global average, but in recent years, its incidence rate has increased (3% to 5%). Malignant melanoma is the fastest growing malignant tumor in China, and new melanoma patients reach 20 000 to 30 000 cases every year. Melanoma is prone to invasion and metastasis, and the 5-year survival rate of stage IV patients is only 4.6%. Early diagnosis and treatment can greatly improve the prognosis of patients with malignant melanoma. At present, the hot spots in the diagnosis of malignant melanoma include visual aid, artificial intelligence-assisted diagnosis, histological diagnosis and differential diagnosis. Visual AIDS can be used to screen for melanoma, and dermoscopy and skin confocal technology (CT) can diagnose melanoma with sensitivity of 61% and 100%, respectively. AI based diagnosis of malignant melanoma is more accurate than that of artificial intelligence alone or doctors, and can improve the diagnosis accuracy of malignant melanoma from 55.6% to 75.0%. With the continuous progress of second-generation sequencing technology in histology diagnosis, there is still a lack of objectively and highly repeatable immunohistochemical markers applicable to all melanomas. However, with the development of melanoma genomics research, BRAF V600E and NRAS mutations have been applied in clinical diagnosis, treatment and prognosis assessment. Malignant melanoma is highly invasive, and many patients are in the advanced stage when diagnosed. Therefore, the diagnosis and treatment of melanoma in China should pay attention to the multidisciplinary diagnosis and treatment team model, and promote the diagnosis and treatment principles and guidelines based on multidisciplinary consensus.

Key words: Melanoma, Dermoscope, Skin CT, Artificial intelligence, Histology, Differential diagnosis

中图分类号:

R739.5

吴娜明, 李军, 陶娟. 恶性黑色素瘤的诊断热点[J]. 诊断学理论与实践, 2023, 22(03): 215-220.

WU Nanming, LI Jun, TAO Juan. Hot spots in diagnosis of malignant melanoma[J]. Journal of Diagnostics Concepts & Practice, 2023, 22(03): 215-220.

参考文献 36

[1]	WANG J Y, WANG E B, SWETTER S M. What is melanoma?[J]. JAMA. 2023, 329(11):948. doi: 10.1001/jama.2022.24888 pmid: 36867424
[2]	ARNOLD M, SINGH D, LAVERSANNE M, et al. Global burden of cutaneous melanoma in 2020 and projections to 2040[J]. JAMA Dermatol, 2022, 158(5):495-503. doi: 10.1001/jamadermatol.2022.0160 pmid: 35353115
[3]	BAI R, HUANG H, LI M, et al. Temporal trends in the incidence and mortality of skin malignant melanoma in china from 1990 to 2019[J]. J Oncol, 2021:9989824.
[4]	LIN L, LI Z, YAN L, et al. Global, regional, and national cancer incidence and death for 29 cancer groups in 2019 and trends analysis of the global cancer burden, 1990-2019[J]. J Hematol Oncol, 2021, 14(1):197. doi: 10.1186/s13045-021-01213-z
[5]	CUI C, WANG X, LIAN B, et al. OrienX010, an oncolytic virus, in patients with unresectable stage IIIC-IV melanoma: a phase Ib study[J]. J Immunother Cancer, 2022, 10(4):e004307. doi: 10.1136/jitc-2021-004307 URL
[6]	PARRA L M, WEBSTER R M. The malignant melanoma market[J]. Nat Rev Drug Discov, 2022. 21(7):489-490. doi: 10.1038/d41573-022-00075-5
[7]	DESSINIOTI C, GELLER A C, STRATIGOS A J. A review of nevus-associated melanoma: What is the evidence?[J]. J Eur Acad Dermatol Venereol, 2022, 36(11):1927-1936. doi: 10.1111/jdv.v36.11 URL
[8]	RIGEL D S, RUSSAK J, FRIEDMAN R. The evolution of melanoma diagnosis: 25 years beyond the ABCDs[J]. CA Cancer J Clin, 2010, 60(5):301-316. doi: 10.3322/caac.20074 URL
[9]	ILYAS M, COSTELLO C M, ZHANG N, et al. The role of the ugly duckling sign in patient education[J]. J Am Acad Dermatol, 2017, 77(6):1088-1095. doi: S0190-9622(17)32054-6 pmid: 28964538
[10]	CABRERA R, RECULE F. Unusual clinical presentations of malignant melanoma: a review of clinical and histologic features with special emphasis on dermatoscopic findings[J]. Am J Clin Dermatol, 2018, 19(Suppl 1):15-23. doi: 10.1007/s40257-018-0373-6 pmid: 30374898
[11]	XIONG Y Q, MA S J, MO Y, et al. Comparison of dermoscopy and reflectance confocal microscopy for the diagnosis of malignant skin tumours: a meta-analysis[J]. J Cancer Res Clin Oncol, 2017, 143(9):1627-1635. doi: 10.1007/s00432-017-2391-9 URL
[12]	ARGENZIANO G, KITTLER H, FERRARA G, et al. Slow-growing melanoma: a dermoscopy follow-up study[J]. Br J Dermatol, 2010, 162(2):267-273. doi: 10.1111/j.1365-2133.2009.09416.x pmid: 19785607
[13]	TEJERA-VAQUERIZO A, ARIAS-SANTIAGO S, NAGORE E, et al. Defining the dermoscopic characteristics of fast-growing cutaneous melanomas[J]. Melanoma Res, 2015, 25(3):269-272. doi: 10.1097/CMR.0000000000000157 URL
[14]	DEINLEIN T, ARZBERGER E, ZALAUDEK I, et al. Dermoscopic characteristics of melanoma according to the criteria "ulceration" and "mitotic rate" of the AJCC 2009 staging system for melanoma[J]. PLoS One, 2017, 12(4):e0174871. doi: 10.1371/journal.pone.0174871 URL
[15]	YU Z, NGUYEN J, NGUYEN T D, et al. Early melanoma diagnosis with sequential dermoscopic images[J]. IEEE Trans Med Imaging, 2022, 41(3):633-646. doi: 10.1109/TMI.2021.3120091 URL
[16]	ELSHOT Y S, TIO D C K S, VAN HAERSMA-DE WITH A S E, et al. Lentigo maligna (melanoma): a systematic review and meta-analysis on surgical techniques and presurgical mapping by reflectance confocal microscopy[J]. J Eur Acad Dermatol Venereol, 2023, 37(5):871-883. doi: 10.1111/jdv.v37.5 URL
[17]	CONDORELLI A G, FARNETANI F, CIARDO S, et al. Dynamic dermoscopic and reflectance confocal microscopic changes of melanocytic lesions excised during follow up[J]. J Am Acad Dermatol, 2022, 86(5):1049-1057. doi: 10.1016/j.jaad.2021.03.081 URL
[18]	VERA J, LAI X, BAUR A, et al. Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence[J]. Brief Bioinform, 2022, 23(6):bbac433. doi: 10.1093/bib/bbac433 URL
[19]	ESTEVA A, KUPREL B, NOVOA R A, et al. Dermatologist-level classification of skin cancer with deep neural networks[J]. Nature, 2017, 542(7639):115-118. doi: 10.1038/nature21056
[20]	SOENKSEN L R, KASSIS T, CONOVER S T, et al. Using deep learning for dermatologist-level detection of suspicious pigmented skin lesions from wide-field images[J]. Sci Transl Med, 2021, 13(581):eabb3652. doi: 10.1126/scitranslmed.abb3652 URL
[21]	PHILLIPS M, MARSDEN H, JAFFE W, et al. Assessment of accuracy of an artificial intelligence algorithm to detect melanoma in images of skin lesions[J]. JAMA Netw Open, 2019, 2(10):e1913436. doi: 10.1001/jamanetworkopen.2019.13436 URL
[22]	ROZEMAN E A, HOEFSMIT E P, REIJERS I L M, et al. Survival and biomarker analyses from the OpACIN-neo and OpACIN neoadjuvant immunotherapy trials in stage Ⅲ melanoma[J]. Nat Med, 2021, 27(2):256-263. doi: 10.1038/s41591-020-01211-7
[23]	HAENSSLE H A, FINK C, SCHNEIDERBAUER R, et al. Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists[J]. Ann Oncol, 2018, 29(8):1836-1842. doi: S0923-7534(19)34105-5 pmid: 29846502
[24]	ANDTBACKA R H, GERSHENWALD J E. Role of sentinel lymph node biopsy in patients with thin melanoma[J]. J Natl Compr Canc Netw, 2009, 7(3):308-317. doi: 10.6004/jnccn.2009.0023 URL
[25]	KASHANI-SABET M. Molecular markers in melanoma[J]. Br J Dermatol, 2014, 170(1):31-35.
[26]	DANKORT D, CURLEY D P, CARTLIDGE R A, et al. Braf(V600E) cooperates with Pten loss to induce metastatic melanoma[J]. Nat Genet, 2009, 41(5):544-552. doi: 10.1038/ng.356 pmid: 19282848
[27]	TEIXIDO C, CASTILLO P, MARTINEZ-VILA C, et al. Molecular markers and targets in melanoma[J]. Cells, 2021, 10(9):2320. doi: 10.3390/cells10092320 URL
[28]	Cancer Genome Atlas Network. Genomic classification of cutaneous melanoma[J]. Cell, 2015, 161(7):1681-1696. doi: 10.1016/j.cell.2015.05.044 pmid: 26091043
[29]	GIBNEY G T, MESSINA J L, FEDORENKO I V, et al. Paradoxical oncogenesis--the long-term effects of BRAF inhibition in melanoma[J]. Nat Rev Clin Oncol, 2013, 10(7):390-399. doi: 10.1038/nrclinonc.2013.83 pmid: 23712190
[30]	RANDIC T, KOZAR I, MARGUE C, et al. NRAS mutant melanoma: towards better therapies[J]. Cancer Treat Rev, 2021, 99:102238. doi: 10.1016/j.ctrv.2021.102238 URL
[31]	YEH I, BUSAM K J. Spitz melanocytic tumours - a review[J]. Histopathology, 2022, 80(1):122-134. doi: 10.1111/his.v80.1 URL
[32]	RAGHAVAN S S, PETERNEL S, MULLY T W, et al. Spitz melanoma is a distinct subset of spitzoid melanoma[J]. Mod Pathol, 2020, 33(6):1122-1134. doi: 10.1038/s41379-019-0445-z URL
[33]	MARQUES P C, DINIZ L M, SPELTA K, et al. Desmoplastic melanoma: a rare variant with challenging diagnosis[J]. An Bras Dermatol, 2019, 94(1):82-85. doi: S0365-05962019000100014 pmid: 30726469
[34]	MCCARTHY S W, SCOLYER R A, PALMER A A. Desmoplastic melanoma: a diagnostic trap for the unwary[J]. Pathology, 2004, 36(5):445-451. doi: 10.1080/00313020412331285336 URL
[35]	DEWANE M E, KELSEY A, OLIVIERO M, et al. Melanoma on chronically sun-damaged skin: Lentigo maligna and desmoplastic melanoma[J]. J Am Acad Dermatol, 2019, 81(3):823-833. doi: S0190-9622(19)30510-9 pmid: 30930085
[36]	MUINONEN-MARTIN A J, O'SHEA S J, NEWTON-BISHOP J. Amelanotic melanoma[J]. BMJ, 2018, 360:k826.