Pigment Network Analysis in Melanoma and Nevi: Retrospective Study from Snippets to Full Dermoscopic Images

Noa Kremer; Isabella  N. Dana; Emmanouil  Chousakos; Larissa  M. Pastore; Halpern C. Halpern; Stephen W. Dusza; Jochen  Weber; Ofer Reiter; Aimilios Lallas; Cristian Navarrete-Dechent; Ralph Braun; Harold  Rabinovitz; Gustavo  Carvalho; Rashek  Kazi; Rozina  B. Zeidan; Shirin  Bajaj; Nicholas  R. Kurtansky; Ashfaq  Marghoob

doi:10.5826/dpc.1504a5700

Pigment Network Analysis in Melanoma and Nevi: Retrospective Study from Snippets to Full Dermoscopic Images

Authors

Noa Kremer Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA. 2 Tel Aviv University Faculty of Medical and Health Sciences, Tel-Aviv, Israel.
Isabella N. Dana SUNY Downstate Health Sciences University College of Medicine, Brooklyn, NY
Emmanouil Chousakos 1st Department of Pathology, Medical School, National & Kapodistrian University of Athens, Greece
Larissa M. Pastore Department of Internal Medicine, Cooper University Hospital, Camden, NJ 08103
Halpern C. Halpern Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA
Stephen W. Dusza Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA
Jochen Weber Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA
Ofer Reiter Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA. 2 Tel Aviv University Faculty of Medical and Health Sciences, Tel-Aviv, Israel.
Aimilios Lallas First Department of Dermatology, Aristotle University School of Medicine, Thessaloniki, Greece
Cristian Navarrete-Dechent Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA. 7. Department of Dermatology, Facultad de Medicina, Pontificia Universidad Cato´lica de Chile, Santiago, Chile
Ralph Braun Department of Dermatology, University Hospital Zurich, Gloriastrasse, Zurich, Switzerland
Harold Rabinovitz Department of Dermatology, University of Miami Miller School of Medicine, Miami, Florida, USA
Gustavo Carvalho Cutaneous Oncology Department, A.C. Camargo Cancer Center, São Paulo, Brazil
Rashek Kazi Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA.
Rozina B. Zeidan Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA. 12. Medical Scientist Training Program, Stony Brook University, Stony Brook, New York, USA.
Shirin Bajaj Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA
Nicholas R. Kurtansky Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA
Ashfaq Marghoob Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA

Keywords:

Pigment network (typical/atypical), Snippet, Melanoma, Visual context

Abstract

Introduction: Atypical network is a dermoscopic criterion that helps in the diagnosis of melanoma. Despite its importance, the interpretation of atypical networks varies widely among experts.

Objective: This study examined the impact of viewing the whole lesion versus viewing foci of pigment network (i.e., snippets) in isolation from within the lesion on expert classification of pigment network in dermoscopic images.

Method: Six dermoscopy experts, blinded to the diagnosis, each evaluated a total of 92 images (80 nevi and 12 melanomas) for the presence of typical versus atypical pigment network. While 57% of images had consistent classification of the network between whole lesion and snippets, 43% shifted the network classification between the snippet to the whole lesion view. Melanomas were more prone than nevi to intra-rater discrepancy between whole lesion and snippets (54.2% vs. 41.7%; odds ratio (OR): 1.65; 95% confidence interval (CI): 1.11–2.47). The inter-observer agreement was higher for the snippet view (65.22%) than for the whole lesion view (55%).

Results: These findings suggest that both the objective morphology of the pigment network and the subjective interpretation of the network in context with other features within the lesion influence expert classification of pigment network.

Conclusion: Factors such as the variability in the distribution, thickness, and color of network lines, overall pattern, and other dermoscopic structures likely contributed to the classification changes.

References

Williams NM, Rojas KD, Reynolds JM, Kwon D, ShumTien J, Jaimes N. Assessment of Diagnostic Accuracy of Dermoscopic Structures and Patterns Used in Melanoma Detection: A Systematic Review and Meta-analysis. JAMA Dermatol. 2021;157(9):1078-1088. DOI: 10.1001/jamadermatol.2021.2845.

Argenziano G, Soyer HP, Chimenti S, et al. Dermoscopy of pigmented skin lesions: results of a consensus meeting via the Internet. J Am Acad Dermatol. 2003;48(5):679-693. DOI:10.1067/mjd.2003.281.

Malvehy J, Puig S, Argenziano G, Marghoob AA, Soyer HP; International Dermoscopy Society Board members. Dermoscopy report: proposal for standardization. Results of a consensus meeting of the International Dermoscopy Society. J Am Acad Dermatol. 2007;57(1):84-95. DOI: 10.1016/j.jaad.2006.02.051.

Kittler H, Marghoob AA, Argenziano G, et al. Standardization of terminology in dermoscopy/dermatoscopy: Results of the third consensus conference of the International Society of Dermoscopy. J Am Acad Dermatol. 2016;74(6):1093-1106. DOI: 10.1016/j.jaad.2015.12.038.

Lallas A, Longo C, Manfredini M, et al. Accuracy of Dermoscopic Criteria for the Diagnosis of Melanoma In Situ. JAMA Dermatol. 2018;154(4):414-419. DOI: 10.1001/jamadermatol.2017.6447.

Liopyris K, Navarrete-Dechent C, Marchetti MA, et al. Expert Agreement on the Presence and Spatial Localization of Melanocytic Features in Dermoscopy. J Invest Dermatol. 2024;144(3):531-539.e13. DOI: 10.1016/j.jid.2023.01.045.

Henning JS, Dusza SW, Wang SQ, et al. The CASH (color, architecture, symmetry, and homogeneity) algorithm for dermoscopy. J Am Acad Dermatol. 2007;56(1):45-52. DOI: 10.1016/j.jaad.2006.09.003.

Nachbar F, Stolz W, Merkle T, et al. The ABCD rule of dermatoscopy. High prospective value in the diagnosis of doubtful melanocytic skin lesions. J Am Acad Dermatol. 1994;30(4):551-559. DOI:10.1016/s0190-9622(94)70061-3.

Rosendahl C, Cameron A, McColl I, Wilkinson D. Dermatoscopy in routine practice - ‘chaos and clues’. Aust Fam Physician. 2012;41(7):482-487. 10. Todorovic D. Context effects in visual perception and their explanations. Rev Psychol. 2010;17(1):17-32.

Kazemimoghadam M, Yang Z, Chen M, Ma L, Lu W, Gu X. Leveraging global binary masks for structure segmentation in medical images. Phys Med Biol. 2023;68(18):10.1088/1361-6560/acf2e2. Published 2023 Sep 13. DOI: 10.1088/1361-6560/acf2e2.

Angayarkanni N, Kumar D. Euclidean Distance Transform (EDT) algorithm applied to binary image for finding breast cancer. Biomed Pharmacol J. 2015;8(1):407-411. DOI: 10.13005/bpj/628.

Panasiti V, Devirgiliis V, Curzio M, et al. The reticular point of view in dermatoscopy. J Am Acad Dermatol. 2009;61(4):605-610. DOI: 10.1016/j.jaad.2009.04.006.

Marghoob NG, Liopyris K, Jaimes N. Dermoscopy: A Review of the Structures That Facilitate Melanoma Detection. J Am Osteopath Assoc. 2019;119(6):380-390. DOI: 10.7556/jaoa.2019.067.

Tschandl P, Kittler H, Schmid K, Zalaudek I, Argenziano G. Teaching dermatoscopy of pigmented skin tumours to novices: comparison of analytic vs. heuristic approach. J Eur Acad Dermatol Venereol. 2015;29(6):1198-1204. DOI: 10.1111/jdv.12790.

Carrera C, Marchetti MA, Dusza SW, et al. Validity and Reliability of Dermoscopic Criteria Used to Differentiate Nevi From Melanoma: A Web-Based International Dermoscopy Society Study. JAMA Dermatol. 2016;152(7):798-806. DOI: 10.1001/jamadermatol.2016.0624.

Barhoumi W, Baâzaoui A. Pigment network detection in dermatoscopic images for melanoma diagnosis. IRBM. 2014;35(3)128–138. DOI: 10.1016/j.irbm.2013.12.010.