High-definition optical coherence tomography algorithm for discrimination of basal cell carcinoma from clinical BCC imitators and differentiation between common subtypes.

BACKGROUND

Preliminary studies have described morphological features of basal cell carcinoma (BCC) imaged by high-definition optical coherence tomography (HD-OCT) and suggested that this technique may aid in its diagnosis and management. However, systematic studies evaluating the accuracy of HD-OCT for the diagnosis of BCC are lacking.

OBJECTIVE

The aim of this study was to identify three-dimensional (3-D) HD-OCT features able i) to distinguish BCC from clinical BCC imitators and ii) to discriminate between the most common BCC subtypes. Based on these particular features, a diagnostic algorithm will be suggested.

METHOD: A total of 50 histopathologically confirmed BCCs (18 superficial, 19 nodular, 13 infiltrative) were imaged by HD-OCT at the centre of the lesion prior to standard surgical excision and subsequent histopathological analysis. Fifty images of clinical BCC imitators were also retrieved as a 'pitfalls' group.

RESULTS

The simultaneous presence of grey/dark subepidermal (hemi-spherical) or intradermal lobulated structure(s) presenting a typical cockade feature in both HD-OCT modes was a significant feature for BCC diagnosis. Features discriminating between BCC subtypes were location of the roof of BCC lobules, vascular pattern of the papillary plexus and stretching effect on the stroma. Clinical BCC imitators such as actinic keratosis, compound and intradermal naevi, amelanotic melanoma, sebaceous hyperplasia and small haemangioma could be differentiated from BCC by means of HD-OCT.

CONCLUSION

This study provides a thorough description of 3-D HD-OCT features that can permit discrimination of BCC from clinical BCC imitators and differentiation of BCC subtypes. Based on these features, a diagnostic algorithm is proposed which requires additional validation, but enhances current understanding of the morphological correlates of HD-OCT images in skin.