Diagnostic Strategies / Algorithms
|Description||revised pattern analysis, pattern analysis, ABCD rule, Menzies Method, seven point checklist, 3 point checklist, chaos and clues, TADA, prediction without pigment, color wheel approach and other algorithms|
|Author(s)||Ralph P. Braun|
|Responsible author||Ralph Braun → send e-mail|
|Status update||May 20, 2019|
|Status by||Ralph P. Braun|
revised pattern analysis, pattern analysis, ABCD rule, Menzies Method, seven point checklist, 3 point checklist, chaos and clues, TADA, prediction without pigment, color wheel approach and other algorithms
It has the following subchapters:
Algorithms for pigmented lesions include the three-point checklist, the AC rule, the blue-black rule, and chaos and clues. Overall, these algorithms have a sensitivity between 78.2% and 92.9%, and a specificity ranging from 64% up to 92.3% for the diagnosis of pigmented skin cancers, including melanoma or pigmented basal cell carcinomas (BCC).3,6-8
The three-point checklist
The three-point checklist was initially developed for non-experts as a skin cancer screening tool. The three-point checklist has a high sensitivity for pigmented skin cancers, including pigmented BCC and melanoma 2,6 This checklist includes three dermoscopic features, including:
- Asymmetry of pattern and structures, defined as asymmetry in the distribution of dermoscopic color and/or structures in one or two perpendicular axes. The contour or silhouette of the lesion does not factor into whether the lesion is symmetric or not.
- Blue-white structures, defined as blue-white veil and/or white scar-like depigmentation and/or blue pepper-like granules.
- Atypical network, defined as Pigment network with thick lines and irregular holes.
Asymmetry in the distribution of colors and structures within a lesion is considered the best predictor of malignancy, followed by blue-white structures and atypical network.6 One point is assigned to each criterion present in the lesion. Lesions with a total score of 2 or 3 points are considered positive, and a skin biopsy or referral is recommended. The three-point checklist has a sensitivity of 79% to 91% and a specificity of 71-72% for the diagnosis of melanoma and BCC.6,7 Since the three-point checklist was not developed to identify pigmented squamous cell carcinomas (SCC), it is recommended that any pigmented lesion with focal adherent keratin or a rough texture that reveals an asymmetric dermoscopic pattern is considered suspicious to avoid missing a pigmented SCC.
The AC Rule
The AC rule was developed as a simple rule to identify lesions that may be suspicious for melanoma.3 The AC rule uses two dermoscopic criteria:
- Asymmetry in the distribution of structures and colors
- Color variation. Multiple colors within the lesion with black or blue-grey color being most suggestive of melanoma.
The AC Rule has been tested in laypersons and expert dermoscopists, demonstrating a sensitivity of 92.9% and 86.7%, and a specificity of 64.1% and 92.3%for melanoma, respectively. 3,8
The Blue-Black Rule
The blue –black rule was proposed to identify pigmented nodular melanomas, which often appear as symmetric papules or nodules.5 This rule is based on the presence of blue-back color, which is defined as the presence of these two colors in at least 10% of the lesion surface area. (Figure 5c.6, 5c.8, 5c.9)
The presence of the blue-black color in a papule or nodule demonstrated 78.2% sensitivity for melanoma, which improved up to 84.6% when the observer also sought to look for other melanoma-specific structures. Melanoma specific-structures are listed in Table 3. In the study Argenziano and colleagues evaluated the lesions for the presence of specific melanoma structures, including atypical network, negative network, irregular streaks, regression structures, and irregular brown structureless areas.5 Specificity for melanoma was 80.5% when using the blue-black rule only, 97.6% when using the classic melanoma-specific structures only, and 80.5% when using both criteria (i.e. blue-black rule and classic melanoma structures). In addition to detecting nodular melanoma, the presence of blue-black color can also aid in the detection of other heavily pigmented skin malignancies, including pigmented nodular BCCs.5 (Figure 5c.9)
Chaos and Clues
This algorithm was also developed for the evaluation of pigmented skin lesions and is discussed in the correspoinding subchapter.
Altogether, these four algorithms were develop to aid in the diagnosis of pigmented skin cancer, including melanoma and pigmented BCC; however, they will not help in the detection of any skin cancer devoid of pigment, and amelanotic or hypomelanotic skin cancers may be missed. In addition, since the main purpose of these algorithms is not to miss a pigmented skin cancer, it is possible that some benign pigmented lesions, such as thrombosed hemangiomas, angiokeratomas, or pigmented seborrheic keratosis, may be misclassified as suspicious and subjected to biopsy.
ALGORITHMS FOR NON-PIGMENTED LESIONS
Prediction without Pigment algorithm
This algorithm was created for the evaluation of amelanotic lesions, and is discussed in the subchapter. 9
ALGORITHM FOR PIGMENTED AND NON-PIGMENTED LESIONS
The Triage Amalgamated Dermoscopic Algorithm (TADA) was created as a relatively simple, easy-to-use and learn algorithm that can guide management decision in a skin cancer triage setting. TADA is discussed in a separate subchapter.
1. Triage. Published 1991. Accessed. 2. Soyer HP, Argenziano G, Zalaudek I, et al. Three-point checklist of dermoscopy. A new screening method for early detection of melanoma. Dermatology. 2004;208(1):27-31. 3. Luttrell MJ, Hofmann-Wellenhof R, Fink-Puches R, Soyer HP. The AC Rule for melanoma: a simpler tool for the wider community. J Am Acad Dermatol. 2011;65(6):1233-1234. 4. Rosendahl C, Cameron A, McColl I, Wilkinson D. Dermatoscopy in routine practice - 'chaos and clues'. Aust Fam Physician. 2012;41(7):482-487. 5. Argenziano G, Longo C, Cameron A, et al. Blue-black rule: a simple dermoscopic clue to recognize pigmented nodular melanoma. Br J Dermatol. 2011;165(6):1251-1255. 6. Zalaudek I, Argenziano G, Soyer HP, et al. Three-point checklist of dermoscopy: an open internet study. Br J Dermatol. 2006;154(3):431-437. 7. Argenziano G, Puig S, Zalaudek I, et al. Dermoscopy improves accuracy of primary care physicians to triage lesions suggestive of skin cancer. J Clin Oncol. 2006;24(12):1877-1882. 8. Luttrell MJ, McClenahan P, Hofmann-Wellenhof R, Fink-Puches R, Soyer HP. Laypersons' sensitivity for melanoma identification is higher with dermoscopy images than clinical photographs. Br J Dermatol. 2012;167(5):1037-1041. 9. Rosendahl C, Cameron A, Tschandl P, Bulinska A, Zalaudek I, Kittler H. Prediction without Pigment: a decision algorithm for non-pigmented skin malignancy. Dermatol Pract Concept. 2014;4(1):59-66.