A spiculated mass target model for clinical image quality control in digital mammography

Quality assurance of breast imaging has a long history of using test objects to optimize and follow up imaging devices. In particular, the evaluation of new techniques benefits from suitable test objects. The applicability of a phantom consisting of spiculated masses to assess image quality and its dependence on dose in flat field digital mammography (FFDM) and digital breast tomosynthesis systems (DBT) is investigated.

Two spiculated masses in five different sizes each were created from a database of clinical tumour models. The masses were produced using 3D printing and embedded into a cuboid phantom. Image quality is determined by the number of spicules identified by human observers.

The results suggest that the effect of dose on spicule detection is limited especially in cases with smaller objects and probably hidden by the inter-reader variability. Here, an average relative inter-reader variation of the counted number of 31% was found (maximum 83%). The mean relative intra-reader variability was found to be 17%. In DBT, sufficiently good results were obtained only for the largest masses.

It is possible to integrate spiculated masses into a cuboid phantom. It is easy to print and should allow a direct and prompt evaluation of the quality status of the device by counting visible spicules. Human readout presented the major uncertainty in this study, indicating that automated readout may improve the reproducibility and consistency of the results considerably.

A cuboid phantom including clinical objects as spiculated lesion models for visual assessing the image quality in FFDM and DBT was developed and is introduced in this work. The evaluation of image quality works best with the two larger masses with 21 spicules.