PURPOSE: Texture analysis (TA) has proved to be useful to distinguish different tissues and disease states using magnetic resonance imaging (MRI). TA has been successfully applied clinically to improve identification of abnormalities in the brain, liver, and bone and, more recently, has been used to enhance the specificity of breast MRI. This preclinical study used a custom-made phantom containing different grades of reticulated foam embedded in agarose gel to assess the capability of TA to distinguish between different texture objects, under different imaging conditions. The aim was to assess whether TA could be used reliably with clinical protocols that were not optimized for texture analysis and also to investigate the effect that changing imaging sequence parameters would have on the outcome of TA. METHODS: Clinical fast gradient echo sequences and two different breast RF coils were used in order to reflect standard clinical practice. Three protocols were used: (1) a high spatial resolution protocol run on a 1.5 Tesla (T) MRI scanner, (2) a parameter matched sequence run on a 3.0 T magnet, and (3) a high temporal resolution protocol also run on a 3.0 T magnet.For each protocol, three sequence parameters (repetition time, bandwidth/echo time, and flip angle) were altered from the baseline values to assess the impact of changes in acquisition parameters on the outcome of TA. RESULTS: TA was performed using MAZDA software and clearly differentiated four foam phantoms when using the wavelet transform method (WAV), also moderately so with the co-occurrence matrix method (COM). The outcome was generally improved for imaging protocols acquired on the 3.0 T scanner, particularly for the high spatial resolution protocol where changes to the acquisition parameters influenced the TA, especially changes to the bandwidth/echo time. For the other protocols, TA outcome was less affected by changes to the imaging parameters. CONCLUSIONS: This phantom study shows that acquisition parameters and protocols that are typically used for clinical breast imaging can result in good TA. Our findings suggest that changes to sequence parameters may not greatly influence the outcome of texture analysis, but rather that spatial resolution may be the most important factor to consider.