A computational algorithm was designed to produce a measure of DW image distortion across the prostate. This algorithm was tested and validated on virtual phantoms incorporating known degrees and distributions of distortion. A study was then carried out on DW image volumes from three sets of 10 patients who had been imaged previously. These volumes had been radiologically assessed to have, respectively, 'no distortion' or 'significant distortion' or the potential for 'significant distortion' due to susceptibility effects from hip prostheses. Prostate outlines were drawn on a T2-weighted (T2W) image 'gold-standard' volume and on an ADC image volume derived from DW images acquired over the same region. The algorithm was then applied to these outlines to quantify and map image distortion. The proposed method correctly reproduced known distortion values and distributions in virtual phantoms. It also successfully distinguished between the three groups of patients: mean distortion in 'non-distorted' image volumes, 1.942 ± 0.582 mm; 'distorted', 4.402 ± 1.098 mm; and 'hip patients' 8.083 ± 4.653 mm; P < 0.001. This work has demonstrated and validated a means of quantifying and mapping image distortion in clinical prostate MRI cases.