Diagnostic Strategies / Algorithms

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Main PageDiagnostic Strategies / AlgorithmsABCD rule
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Description revised pattern analysisThis glossary term has not yet been described., pattern analysis, ABCDThis glossary term has not yet been described. rule, Menzies Method, sevenThis glossary term has not yet been described. pointThis glossary term has not yet been described. checklistis a type of informational job aid used to reduce failure by compensating for potential limits of human memory and attention., 3 point checklist, chaos and cluesThis glossary term has not yet been described.This an algorithm used in dermoscopy [[Chaos and Clues]], TADA, prediction without pigment, color wheelThis glossary term has not yet been described. approach and other algorithms
Author(s) Ralph P. Braun
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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:

Pattern analysis Harald Kittler, Florentia Dimitriou
ABCD rule Michael Kunz, Wilhelm Stolz
Menzies Method Scott Menzies, Ralph P. Braun
Seven Point Checklist Alina De Rosa, Teresa Russo, Giulia Calabrese, Giuseppe Argenziano
Three point checklist Teresa Russo, Giuseppe Argenziano, Alina De Rosa
Chaos and Clues Harald Kittler, Cliff Rosendahl, Aksana Marozava
TADA Ashfaq A. Marghoob, Natalia Jaimes
Prediction without Pigment Harald Kittler, Cliff Rosendahl, Aksana Marozava
The color wheel approach Nadeem Marghoob, Corinna Psomadakis, Orit Markowitz
The blue black rule
BRAFF checklist for acral melanoma


User=

Algorithms for pigmented lesions include the three-pointThis glossary term has not yet been described. checklist, the AC rule, the blue-black rule, and chaos and clues. Overall, these algorithms have a sensitivityThis glossary term has not yet been described. between 78.2% and 92.9%, and a specificityThis glossary term has not yet been described. ranging from 64% up to 92.3% for the diagnosisis the identification of the nature and cause of a certain phenomenon. Diagnosis is used in many different disciplines with variations in the use of logic, analytics, and experience to determine "cause and effect". In systems engineering and computer science, it is typically used to determine the causes of symptoms, mitigations, and solutions of pigmented skin cancers, including melanomaThis glossary term has not yet been described. or pigmented basal cell carcinomas (BCCAbbreviation for Basal Cell Carcinoma).3,6-8
The three-point checklist

The three-point checklist was initially developed for non-experts as a skin cancerThis glossary term has not yet been described. 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 structuresThis glossary term has not yet been described., 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 depigmentationThis glossary term has not yet been described. and/or blue pepper-like granules.
  • Atypical networkNetwork with increased variability in the color, thickness, and spacing of the lines of the network; asymmetrically distributed; gray color, defined as Pigment networkThis glossary term has not yet been described. with thick lines and irregular holes.



Asymmetry in the distribution of colorsThis glossary term has not yet been described. and structures within a lesion is considered the best predictor of malignancy, followed by blue-white structures and atypical networkNetwork with increased variability in the color, thickness, and spacing of the lines of the network; asymmetrically distributed; gray color.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 (SCCSquamous cell carcinoma), 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 criteriameasure of how well one variable or set of variables predicts an outcome:

  • 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 colorColor (American English) or colour (Commonwealth English) is the characteristic of human visual perception described through color categories, with names such as red, yellow, purple, or blue., 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. MelanomaThis glossary term has not yet been described. 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 networkSerpiginous interconnecting broadened hypopigmented lines that surround elongated and curvilinear globules., irregular streaksThis glossary term has not yet been described., regression structuresThis glossary term has not yet been described., and irregular brown structureless areas.5 SpecificityThis glossary term has not yet been described. 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 melanomaThis glossary term has not yet been described., 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 CluesThis glossary term has not yet been described.
This algorithmIn mathematics and computer science, an algorithm (Listeni/ˈælɡərɪðəm/ AL-gə-ri-dhəm) is a self-contained sequence of actions to be performed. Algorithms can perform calculation, data processing and automated reasoning tasks. 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 helpRefers to giving assistance or support to others for mutual benefit 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 keratosisThis glossary term has not yet been described., 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 AlgorithmIn mathematics and computer science, an algorithm (Listeni/ˈælɡərɪðəm/ AL-gə-ri-dhəm) is a self-contained sequence of actions to be performed. Algorithms can perform calculation, data processing and automated reasoning tasks. (TADA) was created as a relatively simple, easy-to-use and learn algorithm that can guide managementThis glossary term has not yet been described. decision in a skin cancer triage setting. TADA is discussed in a separate subchapter.


ReferencesThis is material contained in a footnote or bibliography holding further information.

1. Triage. Published 1991. Accessed. 2. Soyer HP, Argenziano G, Zalaudek I, et al. Three-pointThis glossary term has not yet been described. checklist of dermoscopyThe examination of [skin lesions] with a 'dermatoscope'. This traditionally consists of a magnifier (typically x10), a non-polarised light source, a transparent plate and a liquid medium between the instrument and the skin, and allows inspection of skin lesions unobstructed by skin surface reflections. Modern dermatoscopes dispense with the use of liquid medium and instead use polarised light to cancel out skin surface reflections.. 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. DermatoscopyThe examination of [skin lesions] with a 'dermatoscope'. This traditionally consists of a magnifier (typically x10), a non-polarised light source, a transparent plate and a liquid medium between the instrument and the skin, and allows inspection of skin lesions unobstructed by skin surface reflections. Modern dermatoscopes dispense with the use of liquid medium and instead use polarised light to cancel out skin surface reflections. 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. DermoscopyThe examination of [skin lesions] with a 'dermatoscope'. This traditionally consists of a magnifier (typically x10), a non-polarised light source, a transparent plate and a liquid medium between the instrument and the skin, and allows inspection of skin lesions unobstructed by skin surface reflections. Modern dermatoscopes dispense with the use of liquid medium and instead use polarised light to cancel out skin surface reflections. 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 imagesA representation of a person, animal or thing, photographed, painted or otherwise made visible. 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-pigmentedThis glossary term has not yet been described. skin malignancy. Dermatol Pract Concept. 2014;4(1):59-66.