The diagnostic value of fine needle aspiration in parotid lumps

Mallon DH, Kostalas M, MacPherson FJ et al. The diagnostic value of fine needle aspiration in parotid lumps. Ann R Coll Surg Engl 2013; 95: 258–262 doi 10.1308/003588413X13511609958370We read with interest the article by Mallon et al and would like to make further comment. Their paper documents what is becoming increasingly clear about fine needle aspiration (FNA) in the salivary glands. In experienced hands, it is capable of a high degree of accuracy, and is quick and safe to perform. FNA performance is optimised by the use of ultrasonography guidance, presence of cytologist/cytology technician to allow repeat aspiration and use of ancillary cytology techniques. Outside specialised units, however, the performance of FNA varies widely, as demonstrated in the recent meta-analysis by Schmidt et al.¹Even in optimised circumstances, FNA remains associated with both a high rate of non-diagnostic sampling and also false negative results.¹ These perceived failings have led to investigation into alternative biopsy techniques, which may more reliably provide an accurate preoperative diagnosis, allowing informed patient consent and appropriate operative selection.Ultrasonography guided core biopsy (USCB) has been described recently in the parotid glands, and has been shown to be both highly accurate and well tolerated.² USCB obtains a core of tissue, using a small bore needle (18G or 20G) deployed via an automated biopsy device, which can be sent for immunohistochemical analysis. This enables typing and grading of tumours. Furthermore, it allows improved diagnosis of nodal hyperplasia and the differentiation of reactive node from low grade lymphoma. USCB does not appear to be associated with either the high non-diagnostic and false negative rates or the variability in performance associated with FNA.³ We would recommend that USCB should be considered the biopsy technique of choice for parotid lump diagnosis, particularly in units where FNA is undertaken in non-optimised circumstances.