Monte Carlo analysis could help radiographers to optimise the set up of X-ray machines used for mammography and reduce the number of breast cancers missed by the technique as well as avoiding false positives.
Mauro Valente of the University of Cordoba, Argentina, and colleagues Germán Tirao and Clara Quintana, also of the CONICET research centre in Buenos Aires, tested several different configurations used by radiographers to carry out X-ray mammography and analysed the results statistically using a Monte Carlo technique.
This Monte Carlo approach uses repeated random sampling of the data to calculate the most likely results from a given set of parameters. By finding which parameters improve X-ray image quality and which reduce it, the team was able to find the optimal set-up for obtaining the best image with minimal radiation dose to the patient.
The team points out that factors such as the material used for the positive electrode, the anode, in the X-ray machine are beyond the control of the radiographer. However, the accelerating voltage applied during mammography significantly affects image quality.
The team said that the algorithm they have developed from its Monte Carlo calculations might also be used to carry out reliable and consistent detection of cancerous tissue in the breast automatically.