TY - JOUR
T1 - Technological advances for the detection of melanoma
T2 - Advances in diagnostic techniques
AU - Fried, Lauren
AU - Tan, Andrea
AU - Bajaj, Shirin
AU - Liebman, Tracey N.
AU - Polsky, David
AU - Stein, Jennifer A.
N1 - Publisher Copyright:
© 2020
PY - 2020/10
Y1 - 2020/10
N2 - Managing the balance between accurately identifying early stage melanomas while avoiding obtaining biopsy specimens of benign lesions (ie, overbiopsy) is the major challenge of melanoma detection. Decision making can be especially difficult in patients with extensive atypical nevi. Recognizing that the primary screening modality for melanoma is subjective examination, studies have shown a tendency toward overbiopsy. Even low-risk routine surgical procedures are associated with morbidity, mounting health care costs, and patient anxiety. Recent advancements in noninvasive diagnostic modalities have helped improve diagnostic accuracy, especially when managing melanocytic lesions of uncertain diagnosis. Breakthroughs in artificial intelligence have also shown exciting potential in changing the landscape of melanoma detection. In the first article in this continuing medical education series, we review novel diagnostic technologies, such as automated 2- and 3-dimensional total body imaging with sequential digital dermoscopic imaging, reflectance confocal microscopy, and electrical impedance spectroscopy, and we explore the logistics and implications of potentially integrating artificial intelligence into existing melanoma management paradigms.
AB - Managing the balance between accurately identifying early stage melanomas while avoiding obtaining biopsy specimens of benign lesions (ie, overbiopsy) is the major challenge of melanoma detection. Decision making can be especially difficult in patients with extensive atypical nevi. Recognizing that the primary screening modality for melanoma is subjective examination, studies have shown a tendency toward overbiopsy. Even low-risk routine surgical procedures are associated with morbidity, mounting health care costs, and patient anxiety. Recent advancements in noninvasive diagnostic modalities have helped improve diagnostic accuracy, especially when managing melanocytic lesions of uncertain diagnosis. Breakthroughs in artificial intelligence have also shown exciting potential in changing the landscape of melanoma detection. In the first article in this continuing medical education series, we review novel diagnostic technologies, such as automated 2- and 3-dimensional total body imaging with sequential digital dermoscopic imaging, reflectance confocal microscopy, and electrical impedance spectroscopy, and we explore the logistics and implications of potentially integrating artificial intelligence into existing melanoma management paradigms.
KW - artificial intelligence
KW - confocal microscopy
KW - dermoscopy
KW - electrical impedance spectroscopy
KW - machine learning
KW - melanoma
KW - sequential digital dermoscopic imaging
KW - total body photography
UR - http://www.scopus.com/inward/record.url?scp=85090331424&partnerID=8YFLogxK
U2 - 10.1016/j.jaad.2020.03.121
DO - 10.1016/j.jaad.2020.03.121
M3 - Review article
C2 - 32348823
AN - SCOPUS:85090331424
SN - 0190-9622
VL - 83
SP - 983
EP - 992
JO - Journal of the American Academy of Dermatology
JF - Journal of the American Academy of Dermatology
IS - 4
ER -