Clinical practice guidelines for the diagnosis and management of melanoma: melanomas that lack classical clinical features

Abstract

A Cancer Council Australia multidisciplinary working group is currently revising and updating the 2008 evidence-based clinical practice guidelines for the management of cutaneous melanoma. While there have been many recent improvements in treatment options for metastatic melanoma, early diagnosis remains critical to reducing mortality from the disease. Improved awareness of the atypical presentations of this common malignancy is required to achieve this. A chapter of the new guidelines was therefore developed to aid recognition of atypical melanomas. Main recommendations: Because thick, life-threatening melanomas may lack the more classical ABCD (asymmetry, border irregularity, colour variegation, diameter > 6 mm) features of melanoma, a thorough history of the lesion with regard to change in morphology and growth over time is essential. Any lesion that is changing in morphology or growing over a period of more than one month should be excised or referred for prompt expert opinion. Changes in management as a result of the guidelines: These guidelines provide greater emphasis on improved recognition of the atypical presentations of melanoma, in particular nodular, desmoplastic and acral lentiginous subtypes, with particular awareness of hypomelanotic and amelanotic lesions.

Diagnosis and management of cutaneous melanoma

“…Clinical signs of invasion may include a palpable component and dermoscopic features such as milky pink or blue-grey structureless areas, chrysalis structures (white streaks) and polymorphous vessels ( Figure 1). 2,3 Importantly, some melanomas (nodular and desmoplastic subtypes in particular) may be pink or skin-coloured and relatively featureless ( Figure 2). 2,4 An individual's underlying risk should be considered when assessing lesions of concern and tailoring surveillance.…”

Use of artificial intelligence in skin cancer diagnosis and management

“…Skin cancer (including melanocytic and keratinocytic malignancy) is the most common cancer in Australia and among Caucasian populations worldwide. Melanoma is responsible for the majority of skin cancer deaths in Australia and has various presentations . While dermoscopy has improved the accuracy of melanoma diagnosis, significant variability occurs and is largely a function of clinical expertise.…”

“…Several studies have now shown that CNNs trained on retrospective image data collected at a single time point are capable of classifying skin cancer with sensitivities and specificities equal or superior to that of dermatologists (Box 1), and clinicians with less experience gain most from AI support under experimental conditions . Hypomelanotic and acral melanoma can be more challenging to diagnose clinically, and this could potentially present a challenge for automated classification. However, CNNs have achieved greater accuracy for hypopigmented and acral lesions in comparison with human experts, at least in silica .…”

Can clinical decision making be enhanced by artificial intelligence?

“…If AI is proven to be effective in prospective studies, clinicians will likely welcome the support system, as it should decrease their risk of overlooking a melanoma in practice. However, the sensitivity will still not be 100% as there are unusual presentations that even AI would not have recognized . However, overall, use of AI should free up clinicians’ time to serve more patients, to explain treatment plans and options better, and to counsel patients distraught by a diagnosis of malignancy.…”