A sensor in the tip of a needle can distinguish between different body tissues, offering more accurate samples for biopsies.

Fine needle aspiration (FNA) biopsy is used to extract tissue from a specific region of the body for subsequent examination of the cells. The needle must be guided by ultrasound or optical imaging, as high precision is required. However, these guidance methods are not always effective, as image resolution can be poor.

This has prompted Tao Li and colleagues at the University of Michigan, US, to design a needle with an integrated sensor to be used alongside ultrasound and imaging methods in order to improve precision during a biopsy. The piezoelectric sensor, made from lead zirconate titanate, is mounted inside the tip cavity and has a thickness of 50 microns and a diameter of 100 microns. When the needle passes from one type of body tissue to another, the researchers see a change in frequency of the output signal.

In particular, FNA biopsies are used for extracting cells from thyroid nodules in the neck where accuracy is imperative because of the proximity of the carotid artery. Li has tested the newly developed sensing needle in a model used by physicians in training. The role of the thyroid is played by an olive and the surrounding tissue by a synthetic gel. In this model, Li's sensing needle successfully detects the change in material from gel to olive. Li has shown that the device can also differentiate between porcine fat and tissue.

Li's sensing needle works at depths of up to 25 millimetres, which is sufficient for thyroid biopsies. However, for the device to be used in FNA biopsies of the breast, kidney or liver longer needles are required, and this gives sensor performance problems to overcome, said Li. As the main drawback of ultrasound methods is interference in deep tissue biopsies, extending this method to longer needles could greatly improve biopsy procedures.

'If manufacturing processes are developed which reduce the production cost of the device so it can be used as disposable, the system could be widely used by healthcare professionals in the next two or three years,' said Li.

Alison Stoddart